atmosphere

Article

Energy Balances and Greenhouse Gas Emissions ofAgriculture in the Shihezi Oasis of China

Zhengang Yan 123 Fuqin Hou 4 and Fujiang Hou 121 State Key Laboratory of Grassland Agro-Ecosystems Key Laboratory of Grassland Livestock Industry

Innovation Ministry of Agriculture Lanzhou 730020 Gansu China yanzhggsaueducn2 College of Pastoral Agriculture Science and Technology Lanzhou University Lanzhou 730000 Gansu China3 College of Information and Science Technology Gansu Agricultural University Lanzhou 730070 Gansu China4 Xinjiang Western Animal Husbandry Limited Company Shihezi 832000 Xinjiang China houfqxj163com Correspondence cyhoufjlzueducn

Received 1 June 2020 Accepted 12 July 2020 Published 24 July 2020

Abstract The objective of this study was to evaluate the difference of crop and livestock productsregarding energy balances greenhouse gas (GHG) emissions carbon economic efficiency and wateruse efficiency using a life cycle assessment (LCA) methodology on farms in three sub-oases within theShihezi Oasis of China The three sub-oases were selected within the Gobi Desert at Shizongchang(SZC) Xiayedi (XYD) and Mosuowan (MSW) to represent the various local oasis types i Oasisii overlapping oasis-desert and iii Gobi oasis The results indicated that crop production in XYDOasis had higher energy balances (22147 GJha) and a net energy ratio (539) than in the other twooases (p lt 001) The production of 1 kg CW of sheep in XYD Oasis resulted in significantly higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases (p lt 001)The water use efficiency of crop production in the SZC Oasis was lower than that of the XYD andMSW oases (p lt 005) Alfalfa production generated the lowest CO2-eq emissions (809 Mg CO2-eqhayear) and had the highest water use efficiency (4582 MJm3) Alfalfa (118 yenkg CO2-eq) and maize(114 yenkg CO2-eq) had a higher carbon economic efficiency than other crops (p lt 001) The mainsources of GHG emissions for crop production were fertilizer and irrigation The structural equationmodelling (SEM) of agricultural systems in the Shihezi Oasis showed that the livestock categorysignificantly influenced the economic income energy and carbon balances

Keywords Shihezi Oasis agricultural production systems life cycle assessment energy balancesgreenhouse gas emissions

1 Introduction

The typical Shihezi meta-ecosystem of mountains oases and desert in northwest China consistsof Tianshan Mountain Shihezi Oasis and the Gurbantunggut Desert The areas of the mountain oasisand desert in this ecosystem are 2541 km2 7681 km2 and 10996 km2 respectively [1] The ManasiRiver is the lifeblood of the Shihezi Oasis It originates from Tianshan Mountain and runs dryin the Gurbantunggut Desert Agricultural production in the Shihezi Oasis is located in threesub-oases Shizongchang (SZC) Xiayedi (XYD) and Mosuowan (MSW) More than 95 of peoplefarm produce and energy production are concentrated in these sub-oases At present many problemssuch as secondary salinization of cropland desertification chemical pollution and climate changehave seriously threatened the sustainability of oasis agriculture through a lack of knowledge andunderstanding of oasis agricultural management [2] There exists a close relationship betweenagricultural production and energy use [3] Agricultural production requires high human-appliedenergy inputs of which a large proportion are imported (ie fertilizer diesel electricity pesticide

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etc) the remaining being produced on farms as bio-energy (ie seed manure and animate energyprovided by living plants in nature) Crop yields can be improved (ie at economic maximum) byincreasing the net energy (outputsinputs) of crops [4]

Since 1950 the average rate of increase in global temperatures has been 017 C per decadedue to agricultural practices [5] Agriculture has been considered as a major contributor to GHGemissions [6] Crop yields in developing countries are projected to decrease due to global climatechange [7] As elsewhere there are enormous challenges of alleviating greenhouse gas (GHG) emissionsfrom agricultural production due to the heterogeneous nature and biophysical complexity of farmingsystems in China [8]

Characterizing the energy balances and GHG emissions of agricultural practices in the Shihezi Oasisoffer key information to mitigate carbon emissions and ensure food security [6] Energy consumptionand GHG emissions involve on-farm and off-farm inputs which are carbon-based operations andproducts [8] In this study the system boundary and scope of calculating energy balances and GHGemissions only included farm agricultural production practices using the life cycle assessment (LCA)methodology The objectives of this study were to calculate the differences of energy balances andGHG emissions from various oasis ecotypes (SZC vs XYD vs MSW) in the Shihezi Oasis associatedwith producing per unit of crop and livestock products using the LCA technique Moreover findingthe difference in energy balance and GHG emissions between six crops and water use efficiency of cropproduction in the Shihezi Oasis was the other aim of this study

2 Materials and Methods

21 Study Site

Shihezi Oasis which is divided into the three sub-oases the SZC XYD and MSW oases is locatedin the center of the northern foothills of Tianshan Mountain in XinJiang China (8458primendash8664prime E4326primendash4520prime N Figures 1 and S1) Agricultural production in the Shihezi Oasis is dividedgeographically into three contrasting systems (Figures 1 and S1)

Figure 1 Satellite map of the study site in Xinjiang China

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(a) SZC sub-oasis with a total area of 3758 times 103 ha of which 205 times 103 ha is cultivated sits onan inclined piedmont plain The Manasi River winds its way through the northeast of thesub-oasis other surface and groundwater sources are abundant and in a rural zone of ShiheziCity a freshwater spring overflow is used for flood (border dyke) irrigation

(b) XYD sub-oasis with a total area of 300 times 103 ha of which 61 times 103 ha is cultivated lies where theManasi River downstream oasis system and Gurban Tunggut Desert overlap

(c) MSW sub-oasis with a total area of 137 times 103 ha of which 44 times 103 ha is cultivated lies where theManasi River allows the sub-oasis to cut through the Gurban Tunggut Desert for a distance of60 km

22 Data Collection

Data were collected from official records published literature and farm survey data The farmsurveys were carried out from 2015 to 2016 with a selection of a random 354 farmers in this study(Tables S1 and S2) Inputs of crop production comprised of labor seed fertilizer pesticide fuel andelectricity consumption plastic film and the life and working hours of farm machines Outputs of cropproduction accounted as crop products including grain straw and roots Inputs of livestock productionwere comprised of labor feed (intake source and processing) and fuel and electricity consumptionOutputs of livestock production only included livestock products (carcass weight milk and wool)To quantify the GHG emissions from livestock production data from livestock production includedcategories livestock numbers age feed sources and feed usage Structural equation modelling (SEM)can evaluate direct and indirect effects between variables by expected statistical relationships An SEManalysis program named AMOS 190 (IBM Corporation New York USA) was used to evaluate thedirect and indirect effects of predictor variables on net income energy balances and carbon balancesA good fit for that model is 0 le χ2df le 2 and 005 lt p le 1 [9]

23 Goal and Scope Definition

Based on the ISO standard the overall goal and scope of this study was to evaluate energybalances and GHG emissions on farms [10] The specific aim was to quantify the sustainabilityimpacts associated with energy balances and GHG emissions per ha of cropland and kg of livestockproducts between three sub-oases in Shihezi of China The target audience included the farm and itsstakeholders consumers and the public

24 Functional Unit

The functional unit was defined for the purposes of this study with GJha for carbon balancesof crop production and MJkg of carcass weight (CW) and milk for carbon balances of livestockBased on information from the global warming potential for a 100-year period the data of CH4 andN2O emissions were converted into CO2 equivalents with 34 for CH4 and 298 for N2O The units ofGHG emissions were kg CO2-eqha for cropland kg CO2-eqkg for crop products and kg CO2-eqkgCW and milk for livestock products

25 Calculation of Energy Balances

The human-applied energy inputs of crop production are calculated as Equation (1)

EIcrop = CIl times ECl + CIs times ECs + CI f times EC f + CIp times ECp + CIie times ECie+CIpm times ECpm + CIdc times ECdc + CImd times ECmd

(1)

where EIcrop is the unit area of total energy inputs for crop production (MJha) CI is the unit area ofenergy input for crop production and EC is the energy coefficient (Table 1) In regards to indexing l s

f p ie pm dc and md are inputs of human labor (h) seed (kg) fertilizers (kg) pesticides (kg) electricity

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consumption for irrigation (kwh) and plastic films (kg) respectively The energy outputs for eachcategory of crop including the grain straw and roots are calculated as Equation (2)

EOcrop = CYgrain times ECgrain + CYstraw times ECstraw + CYroot times ECroot (2)

where EOcrop is the unit area of total energy outputs from crop products (MJha) and CY is the unit areaof yield In regards to indexing grain straw and root are grain (kg) straw (kg) and roots (kg) of cropproducts respectively

Table 1 Factors used for the calculation of energy inputs and energy outputs

Energy Factors of Agricultural Production Inputs

Seed(MJkg seed)

Wheat (spring) 179 [11]Maize 10465 [12]Cotton 22024 [13]Alfalfa 10882 [11]Grape 1516 [13]

Tomato 1633 [14]

Fertilizer(MJkg fertilizer)

N 781 [12]P 174 [12]K 137 [12]

Farmyard manure(MJkg manure) Animal manure 1463 [12]

Pesticide(MJkg pesticide)

Herbicides 278 [12]Insecticides 233 [12]Fungicides 121 [12]

Mulch (MJkg mulch) Plastic mulch 519 [6]Fuel (MJkg fuel) Diesel 4778 [6]

Electricity (MJkwh electricity) Electricityfor irrigation 12

Transportation(MJkg truck) Truck 88 [11]

Maintenance ofmachinery (MJkg tractor) Tractor 521 [15]

Human labor (MJh) Male 068 [12]Female 052 [12]

Forage feed(MJkg feed)

Wheat hay 1505 [16]Maize hay 1522 [16]Alfalfa hay 188 [16]

Concentrate feed(MJkg feed)

Maize 1826 [16]Soybean 1883 [16]

Wheat husk 1372 [16]Energy Factors of Agricultural Products

Grain (MJkg grain)

Wheat (spring) 1256 [16]Maize 1826 [16]Cotton 22024 [16]Grape 2341 [16]

Tomato 1258 [13]

Hay (MJkg hay)

Wheat (spring) 1505 [16]Maize 1522 [16]Alfalfa 188 [16]Cotton 1737 [16]

Livestock products (MJkg product)

Lamb 12877 [13]Beef 1388 [13]Milk 2889 [13]Wool 2341 [11]

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The energy inputs of livestock production are calculated as Equation (3)

EIlivestock = (msum

j=1(LI f eed j times EC f eed j) + LIdrug times ECdrug + LIlabor times EClabor

+LIelec times ECelec + LIcoal times ECcoal)CWlivestock

(3)

where EIlivestock is the unit carcass (milk) weight of total energy inputs for livestock production (MJkgCW and milk) LI is the unit livestock of energy input for livestock production and CWlivestock is the unitlivestock of carcass weight (ie the weight of meat with bone except for fur viscera head hooves andblood) In regards to indexing feed drug labor elec coal j and m are feed inputs (kg) veterinary drugs (kg)human labor (h) electricity consumption for lighting of livestock housing (kwh) coal consumption forheating of livestock housing in winter (kg) feed classified j and feed types respectively

The energy outputs of livestock products are calculated as Equation (4)

EOlivestock = (LYcarcass times ECcarcass + LYmilk times ECmilk + LYwool times ECwool)CWlivestock (4)

where EOlivestock is the unit carcass (milk) weight of total energy outputs from livestock products (MJkgCW and milk) and LY is the unit livestock of yield In regards to indexing carcass milk and wool arecarcass weight (kg) milk (kg) and wool of livestock (kg) respectively

The energy indices of balances and ratios are calculated as follows

EBcropamplivestock = EOcropamplivestock minus EIcropamplivestock (5)

NERcropamplivestock =EOcropamplivestock

EIcropamplivestock(6)

where EBcropamplivestock represents the energy balances of crops (MJha) or livestock (MJCW andmilk) NERcropamplivestock represents the net energy ratio (outputinput) of crop or livestock productionEOcropamplivestock and EIcropamplivestock represent the same parameters of the above equation respectively

26 Calculation of GHG Emissions

The GHG emissions for each category of crop production input are calculated as Equation (7)

CEcrop = CIs times EFs + CI f times EF f + CIp times EFp + CIie times EFie + CIpm times EFpm

+AIdc times EFdc + AImd times EFmd + SOILres(7)

where CEcrop is the unit area of GHG emissions (kg CO2-eqha) and EF is the emission factor (Table 2)SOILres is the unit area of GHG emissions from soil respiration (kg CO2-eqha) using the followingEquation (8) [17]

SOILres = 155times e0031timesTtimes

Ptimes SOC(P + 068) times (P + 223)

(8)

where T P and SOC are the annual mean temperature (C) the annual rainfall (m) and soil organiccarbon between a 0 and 20 cm depth (kg Cmminus2) respectively [10]

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Table 2 Factors used for the calculation of GHG emissions

Item Sub-Item Factors References

Emission Factors of GHG for Agricultural Production

Seed 1

(kg CO2-eqkg seed)

Wheat (spring) 0477 [18]Maize 385 [19]Cotton 2383 [18]Alfalfa 9643 [18]Grape 235 [2]

Tomato 163 [20]

Fertilizer(kg CO2-eqkg fertilizer)

N 638 [21]P 0733 [22]K 055 [22]

Soil emissions CO2 after N application 0633 [11]Soil emissions N2O after N application 6205 [23]

Pesticide(kg CO2-eqkg pesticide)

Herbicides 231 [5]Insecticides 187 [5]Fungicides 13933 [24]

Mulch (kg CO2-eqkg mulch) Plastic mulch 18993 [6]

Electricity (tCO2-eqkwh electricity) Electricityfor irrigation 0917 [25]

Fuel (kg CO2-eqL fuel) Diesel 2629 [6]

Tractor depreciation(kg CO2-eqyear)

Tractor 7810 1407 [26]Tractor 5560 049 [26]

Tractor 10021202 132 [26]Tractor 250 016 [26]

Harvester 1200 066 [26]Harvester 154 134 [26]

Feed processing(kg CO2-eqkg feed)

Maize 00102 [27]Soybean 01013 [27]Wheat 00319 [27]

CH4 emissions from entericfermentation

(kg CO2-eqheadyear)

Sheep 125 [11]Beef cattle 1175 [11]

Dairy cattle 1525 [11]CH4 emissions frommanure management

(kg CO2-eqheadyear)

Sheep 275 [11]Beef cattle 25 [11]

Dairy cattle 250 [11]N2O emissions frommanure managementkg CO2-eqheadyear)

Sheep 623 [11]Beef cattle 1204 [11]

Dairy cattle 1067 [11]1 Including seed production cleaning and packaging 2 Including exhaled carbon dioxide of adult labor

Carbon stocks of crop production are calculated using Equation (9) [28]

CScrop = CSgrain + CSstem + CSroot (9)

where CScrop CSgain CSstem and CSroot represent the unit area of carbon values accumulated in crops(kg CO2-eqha) grain (kg CO2-eqha) stems (kg CO2-eqha) and roots (kg CO2-eqha) respectively

Carbon balances of crop production are calculated as Equation (10)

CBcrop = CScrop minusCEcrop (10)

where CBcrop represents the unit area of carbon balances (kg CO2-eqha)The yearly GHG emissions from each livestock species are calculated using Equation (11)

CElivestock = (TCO2 f eed + TCO2drug + TCO2elec + TCO2coal + TCH4enteric+TCH4manure + TN2Omanure)CWlivestock

(11)

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where CElivestock is the unit carcass (milk) weight of GHG emissions from livestock (kg CO2-eqkg CWand milk) TCO2 is the emissions of carbon dioxide TCH4 is the emissions of methane and TN2O is theemissions of nitrous oxide In regards to indexing enteric and manure are ruminant enteric fermentation(kg CO2-eqkg CW and milk) and manure management (kg CO2-eqkg CW and milk) respectively

The carbon stock and carbon balances of livestock production are calculated as the followingEquations (12) and (13) [29]

CSlivestock = (LW times 02)CWlivestock (12)

CBlivestock = CSlivestock minusCElivestock (13)

where CSlivestock is the carbon stock of livestock (kg CO2-eqkg CW and milk) and LW is the live weightof livestock CBlivestock is the carbon balance (kg CO2-eqkg CW and milk)

27 Calculation of Carbon Economic Efficiency

Based on emissions per one kilogram of carbon dioxide equivalence from agricultural productsthe total carbon economic efficiency associated with the mean market price of these products in 2015and 2016 (Table S3) is calculated using Equation (14) [28]

CEE =YPtimes PRICE

CE(14)

where CEE is the carbon economic efficiency (yenkg CO2-eq) YP is the yield of agricultural products(kg) PRICE is the price of agricultural products (yen) and CE is the GHG emissions from agriculturalproduction (kg CO2-eq)

28 Calculation of Water Use Efficiency

The analysis of energy balance per 1 cubic meter of water can find the relationship betweenirrigation and the net energy of crop production in the Shihezi Oasis The water use efficiency of cropproduction is calculated using Equation (15)

WUEcrop =EBcrop

WUcrop(15)

where WUEcrop EBcrop and WUcrop represent the water use efficiency of crops grown (MJm3)energy balances (MJha) and the water use of crops grown (m3ha) respectively

29 Statistical Analyses

We used the statistical program named Genstat170 (VSNI Corporation Hemel HempsteadUK) to analyze differences in energy indices (energy balances and net energy ratio) carbon indices(GHG emissions carbon stock carbon balances and carbon economic efficiency) water use and wateruse efficiency using inline linear models

3 Results

31 Yield and Water Use of Crop Production

The results of the yield and water use of crop production in three sub-oases of the Shihezi Oasisare presented in Table 3 The yields (kg DMha) of maize and cotton in SZC Oasis were significantlyhigher than in the other two oases (p lt 005) The water use for wheat (spring) and maize productionin SZC Oasis was higher than in the other two oases (p lt 005)

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Table 3 Yield and water use of crop production in the Shihezi sub-oases

SZC 1 XYD 2 MSW 3 SED 4 p-Value

Crop products (Mg DMha)Wheat (spring) 1565 a 1644 a 1067 b 0379 lt005

Maize 6000 a 4545 b 4889 b 0218 lt005Cotton 1342 a 1568 b 1553 c 0157 lt005Alfalfa - 1481 1362 - -Grape - 3034 3067 - -

Tomato 8175 - - - -Water use (1000 m3ha)

Wheat (spring) 677 a 559 c 639 b 0176 lt0001Maize 906 a 759 b 7623 b 0244 lt005Cotton 832 a 823 a 630 b 033 lt005Alfalfa - 417 506 - -Grape - 739 596 - -

Tomato 656 - - - -Farmland 767 a 753 a 6501 b 0202 lt005

1 SZC Shizongchang 2 SZC Xiayedi 3 SZC Mosuowan 4 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

32 Energy Balances Net Energy Ratio and Water Use Efficiency of Agricultural Production

The results of energy balances the net energy ratio and water use efficiency in three sub-oasesof Shihezi Oasis are presented in Table 4 and Table S4 For crop production the output energy(30869 GJha) energy balances (22147 GJha) and net energy ratio (539) in the XYD Oasis were thehighest among the three production systems the corresponding values of MSW Oasis were higherthan in the SZC Oasis respectively (Table 4) However the input energy (4258 GJha) in the MSWOasis was lower than in the other two oases (p lt 001) The net energy ratio (645) and energy balances(30946 MJha) of maize in the XYD Oasis were significantly higher than that of the SZC and MSWoases (Table 4) Alfalfa (1271) and maize (627) had higher net energy ratios than other crops (p lt 001)(Table S4) For livestock production the production of 1 kg CW of sheep in XYD Oasis resulted insignificantly higher energy balances than in the other two oases Similarly the net energy ratio (221) ofsheep in the XYD Oasis was significantly higher than that of the SZC and MSW oases (Table 4)

Table 4 Energy balances net energy ratio and water use efficiency of agricultural production in theShihezi sub-oases

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Energy inputCrop production (GJha)

Wheat (spring) 6319 a 6001 a 5539 b 3239 lt005Maize 5693 a 4217 c 5003 b 1913 lt0001Cotton 7691 a 5837 b 4112 c 5166 lt0001Alfalfa - 1909 2361 - -Grape - 3558 3754 - -

Tomato 4955 - - - -Farmland 6933 a 5847 b 4258 c 4416 lt0001

Livestock production (MJkg CW and milk)Sheep 1496 a 1096 b 1197 b 1225 lt005

Beef cattle 3884 a 3032 b 3001 b 5230 lt005Dairy cattle 144 a 130 b 132 b 0040 lt005

Energy output (GJha)Crop production (GJha)

Wheat (spring) 25582 b 26881 a 17436 c 14779 lt0001Maize 31363 36001 35024 7048 0317Cotton 9972 b 11649 a 11541 a 2709 lt005

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Table 4 Cont

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Alfalfa - 27848 25597 -Grape - 10128 1019 - -

Tomato 20415 - - - -Farmland 23069 c 30869 a 24764 b 16517 lt0001

Livestock production (MJkg CW and milk)Sheep 2923 2926 2929 0010 035

Beef cattle 8704 8701 8702 0002 0561Dairy cattle 256 254 254 0001 0570

Energy balances (GJha)Crop production (GJha)

Wheat (spring) 19563 b 2058 a 11897 c 13699 lt0001Maize 25707 b 30946 a 26997 b 8519 lt005Cotton 2282 c 5812 b 7429 a 7598 lt0001Alfalfa - 25539 23636 - -Grape - 2657 26436 - -

Tomato 1546 - - - -Farmland 16112 c 22147 a 20795 b 11452 lt0001

Livestock production (MJkg CW and Milk)Sheep 1711 b 1831 a 1718 b 1035 lt005

Beef cattle 4813 4901 4822 0924 0125Dairy cattle 110 112 108 0051 0214

Net energy ratio 1

Crop productionWheat 405 a 427 a 315 b 0185 lt005Maize 609 c 645 a 620 b 0225 lt0001Cotton 130 c 203 b 281 a 0219 lt0001Alfalfa - 1206 1305 - -Grape - 847 804 - -

Tomato 412 - - - -Farmland 332 c 539 a 463 b 0625 lt0001

Livestock productionSheep 195 b 221 a 197 b 0167 lt005

Beef cattle 229 b 243 a 231 b 0256 lt005Dairy cattle 178 180 177 0004 0524

Water use efficiency 2

Crop production (MJm3)Wheat (spring) 2892 ab 3684 a 1861 b 3196 lt005

Maize 757 c 1442 a 1180 b 1102 lt0001Cotton 273 c 699 b 1179 a 1321 lt0001Alfalfa - 2785 2350 - -Grape - 2557 2438 - -

Tomato 2359 - - - -Farmland 990 b 1399 a 1415 a 0812 lt005

1 net energy ratio = output energyinput energy 2 water use efficiency Water use based on energy balances3 SZC Shizongchang 4 SZC Xiayedi 5 SZC Mosuowan 6 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

33 GHG Emissions and Carbon Economic Efficiency of Agriculture Production

Carbon indices to evaluate agriculture production are presented in Table 5 and Table S4 Carbonbalances (minus112 Mg CO2-eqha) of crop production in SZC Oasis were lower than in the other twooases (p lt 005) (Table 5) GHG emissions (1772 Mg CO2-eqha) from cotton production weresignificantly higher than for the other five crops (p lt 001) (Table S4) Alfalfa had higher carbon stocks(2376 Mg CO2-eqha) and carbon balances (1597 Mg CO2-eqha) than other crops (p lt 001) (Table S4)According to the price of agricultural products (Table S3) and carbon input for farm productionSZC Oasis had a lower carbon economic efficiency (034 yenkg CO2-eq) of crop production than the other

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two oases (p lt 005) (Table 5) The carbon economic efficiency of maize (114 yenkg CO2-eq) and alfalfa(118 yenkg CO2-eq) were significantly higher than other crops (p lt 001) (Table S4)

Table 5 GHG emissions carbon stocks carbon balances and the carbon economic efficiency ofagricultural production in the Shihezi sub-oases

SZC 2 XYD 3 MSW 4 SED 5 p-Value

GHG emissionsCrop production (Mg CO2-eqha year)

Wheat (spring) 858 b 860 b 899 a 0065 lt005Maize 1245 a 1212 b 1209 b 0057 lt005Cotton 1772 1775 1769 0137 0981Alfalfa - 809 810 - -Grape - 1226 1219 - -

Tomato 1702 - - - -Farmland 1322 1294 1227 0377 0534

Livestock production (kg CO2-eqkg CW and milk)Sheep 923 a 835 ab 762 b 0305 0072

Beef cattle 2295 b 2419 a 2287 b 0237 lt005Dairy cattle 067 070 071 0013 0639

Carbon stocksCrop production (Mg CO2-eqha year)

Wheat (spring) 1044 b 1040 b 1086 a 0075 0069Maize 2352 a 2284 b 2283 b 0107 lt005Cotton 1313 1310 1311 0101 0995Alfalfa - 2383 2374 - -Grape - 1098 1100 - -

Tomato 1035 - - - -Farmland 1210 b 1594 a 1733 a 0582 lt0001

Livestock production (kg CO2-eqkg CW and milk)Sheep 106 a 176 ab 193 b 0061 0610

Beef cattle 357 322 354 0097 0287Dairy cattle 010 011 011 0003 0593

Carbon balancesCrop production (Mg CO2-eqha year)

Wheat (spring) 185 180 187 0012 0160Maize 1106 a 1072 b 1075 b 0050 lt005Cotton minus459 minus464 minus456 0037 0601Alfalfa - 1574 1563 - -Grape - minus128 minus118 - -

Tomato minus668 - - - -Farmland minus112 b 299 a 506 a 0798 lt005

Livestock production (kg CO2-eqkg CW and milk)Sheep minus763 b

minus660 ab minus569 a 0330 lt005Beef cattle minus1939 a

minus2097 b minus1932 a 0298 lt005Dairy cattle minus053 minus059 minus057 0011 0653

Carbon economic efficiency (yenkg CO2-eq)Crop production

Wheat 017 018 017 0001 0185Maize 116 117 114 0016 0802Cotton 070 072 070 0015 0872Alfalfa - 118 117 - -Grape - 041 042 - -

Tomato 032 - - - -Farmland 034 b 075 a 082 a 0042 lt0001

Livestock productionSheep 024 a 022 ab 020 b 0008 0063

Beef cattle 038 b 040 a 038 b 0004 lt005Dairy cattle 017 018 018 0609 0524

1 net energy ratio = output energyinput energy 2 SZC Shizongchang 3 SZC Xiayedi 4 SZC Mosuowan5 SED Standard error of differences a b and c represent means with different letters in a row differing significantly(p lt 005)

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34 Water Use Efficiency Based on Energy

Water use and the water use efficiency of crop production in the Shihezi Oasis are presented inTables 3 and 4 Among the three sub-oases in the Shihezi Oasis the water use of crop production in theMSW Oasis is lower than the corresponding value of the SZC and XYD oases (p lt 005) Howeverthe water use efficiency of crop production in the SZC Oasis is lower than that of the XYD and MSWoases (p lt 005) The water use (4590 m3ha) for alfalfa production in the Shihezi Oasis is the lowestwith the highest water use efficiency (4582 MJm3) (Table S4)

35 Contribution of Carbon Emissions

To further illustrate the relationship between GHG emissions and other factors Figure 2 showsthe contribution of GHG emissions from inputs of crop production The major GHG emission sourceswithin the crop production system are fertilizer and irrigation

Figure 2 Total GHG emissions from crop production and the contribution of emission sources

36 Effect Analysis of Structural Equation Modelling (SEM)

The effect analysis of SEM is presented in Table S5 The path modes show that the direct andtotal effects of the livestock breeding structure on predicted variables (farm net income energyand carbon balances) are much stronger than other dependent variables (Figure 3a total effects = 0647Figure 3b total effects = 0898 Figure 3c total effects = 1091 Figure 3d total effects = 0980Figure 3e total effects = 0898 and Figure 3f total effects = 01091) Similarly the path modesshow that the indirect effects of water use efficiency on economy income energy and carbon balancesare much stronger than those of other variables (Figure 3a indirect effects = 0196 Figure 3bindirect effects = 0297 and Figure 3c indirect effects = 0430)

Atmosphere 2020 11 781 12 of 17

Figure 3 Path models showing the direct and indirect effects of predictor variables on farm net incomeenergy balances and carbon balances The path models with significant correlations are presentedas solid lines The values on solid lines represent standardized regression weights Interruptedlines indicate no significant correlation between two variables Black arrows indicate positiveeffects For each endogenous variable the relative amount of explained variance is given Shadingindicates the greatest positive direct effect indirect effect and total effect between dependent andindependent variables OtoD The distance from the oasis to the desert (km) SPD Soil particle diameter(microm) PS Planting structure (planting crop type) WUE Water use efficiency (MJm3) BS Livestockbreeding structure (breeding livestock category) ECO Net income (1000 yenha) EB Energy balance(GJha) CB The difference value of carbon stock minus GHG emissions from agricultural productioninputs (Mg CO2-eqha) and OtoM The distance from the oasis to the desert (km) χ2 Chi-squarep Probability level df Degrees of freedom n Sample size

4 Discussion

41 Energy Balances and Net Energy Ratio

The present energy balances of agricultural production in the Shihezi Oasis are comparable tothose published elsewhere in the world using the similar methodology of calculating the input andoutput energy values on farms For example the input energy of cotton production (5880 GJha)in the Shihezi Oasis is much higher than that (31237 GJha) in Iran [30] This difference refers tothe low energy input of weed controlling and harvesting operations using human labor instead ofapplying machinery in Iran Nevertheless Shihezirsquos input energy for maize production (4971 GJha) isclose to that reported in Iran (50458 GJha) due to similar intensive and high input crop productionsystems [31] However our output energy including grain straw and roots of maize production(34121 GJha) is much higher than that only related to grain estimated in Iran (134946 GJha) [30]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 3 of 17

(a) SZC sub-oasis with a total area of 3758 times 103 ha of which 205 times 103 ha is cultivated sits onan inclined piedmont plain The Manasi River winds its way through the northeast of thesub-oasis other surface and groundwater sources are abundant and in a rural zone of ShiheziCity a freshwater spring overflow is used for flood (border dyke) irrigation

(b) XYD sub-oasis with a total area of 300 times 103 ha of which 61 times 103 ha is cultivated lies where theManasi River downstream oasis system and Gurban Tunggut Desert overlap

(c) MSW sub-oasis with a total area of 137 times 103 ha of which 44 times 103 ha is cultivated lies where theManasi River allows the sub-oasis to cut through the Gurban Tunggut Desert for a distance of60 km

22 Data Collection

Data were collected from official records published literature and farm survey data The farmsurveys were carried out from 2015 to 2016 with a selection of a random 354 farmers in this study(Tables S1 and S2) Inputs of crop production comprised of labor seed fertilizer pesticide fuel andelectricity consumption plastic film and the life and working hours of farm machines Outputs of cropproduction accounted as crop products including grain straw and roots Inputs of livestock productionwere comprised of labor feed (intake source and processing) and fuel and electricity consumptionOutputs of livestock production only included livestock products (carcass weight milk and wool)To quantify the GHG emissions from livestock production data from livestock production includedcategories livestock numbers age feed sources and feed usage Structural equation modelling (SEM)can evaluate direct and indirect effects between variables by expected statistical relationships An SEManalysis program named AMOS 190 (IBM Corporation New York USA) was used to evaluate thedirect and indirect effects of predictor variables on net income energy balances and carbon balancesA good fit for that model is 0 le χ2df le 2 and 005 lt p le 1 [9]

23 Goal and Scope Definition

Based on the ISO standard the overall goal and scope of this study was to evaluate energybalances and GHG emissions on farms [10] The specific aim was to quantify the sustainabilityimpacts associated with energy balances and GHG emissions per ha of cropland and kg of livestockproducts between three sub-oases in Shihezi of China The target audience included the farm and itsstakeholders consumers and the public

24 Functional Unit

The functional unit was defined for the purposes of this study with GJha for carbon balancesof crop production and MJkg of carcass weight (CW) and milk for carbon balances of livestockBased on information from the global warming potential for a 100-year period the data of CH4 andN2O emissions were converted into CO2 equivalents with 34 for CH4 and 298 for N2O The units ofGHG emissions were kg CO2-eqha for cropland kg CO2-eqkg for crop products and kg CO2-eqkgCW and milk for livestock products

25 Calculation of Energy Balances

The human-applied energy inputs of crop production are calculated as Equation (1)

EIcrop = CIl times ECl + CIs times ECs + CI f times EC f + CIp times ECp + CIie times ECie+CIpm times ECpm + CIdc times ECdc + CImd times ECmd

(1)

where EIcrop is the unit area of total energy inputs for crop production (MJha) CI is the unit area ofenergy input for crop production and EC is the energy coefficient (Table 1) In regards to indexing l s

f p ie pm dc and md are inputs of human labor (h) seed (kg) fertilizers (kg) pesticides (kg) electricity

Atmosphere 2020 11 781 4 of 17

consumption for irrigation (kwh) and plastic films (kg) respectively The energy outputs for eachcategory of crop including the grain straw and roots are calculated as Equation (2)

EOcrop = CYgrain times ECgrain + CYstraw times ECstraw + CYroot times ECroot (2)

where EOcrop is the unit area of total energy outputs from crop products (MJha) and CY is the unit areaof yield In regards to indexing grain straw and root are grain (kg) straw (kg) and roots (kg) of cropproducts respectively

Table 1 Factors used for the calculation of energy inputs and energy outputs

Energy Factors of Agricultural Production Inputs

Seed(MJkg seed)

Wheat (spring) 179 [11]Maize 10465 [12]Cotton 22024 [13]Alfalfa 10882 [11]Grape 1516 [13]

Tomato 1633 [14]

Fertilizer(MJkg fertilizer)

N 781 [12]P 174 [12]K 137 [12]

Farmyard manure(MJkg manure) Animal manure 1463 [12]

Pesticide(MJkg pesticide)

Herbicides 278 [12]Insecticides 233 [12]Fungicides 121 [12]

Mulch (MJkg mulch) Plastic mulch 519 [6]Fuel (MJkg fuel) Diesel 4778 [6]

Electricity (MJkwh electricity) Electricityfor irrigation 12

Transportation(MJkg truck) Truck 88 [11]

Maintenance ofmachinery (MJkg tractor) Tractor 521 [15]

Human labor (MJh) Male 068 [12]Female 052 [12]

Forage feed(MJkg feed)

Wheat hay 1505 [16]Maize hay 1522 [16]Alfalfa hay 188 [16]

Concentrate feed(MJkg feed)

Maize 1826 [16]Soybean 1883 [16]

Wheat husk 1372 [16]Energy Factors of Agricultural Products

Grain (MJkg grain)

Wheat (spring) 1256 [16]Maize 1826 [16]Cotton 22024 [16]Grape 2341 [16]

Tomato 1258 [13]

Hay (MJkg hay)

Wheat (spring) 1505 [16]Maize 1522 [16]Alfalfa 188 [16]Cotton 1737 [16]

Livestock products (MJkg product)

Lamb 12877 [13]Beef 1388 [13]Milk 2889 [13]Wool 2341 [11]

Atmosphere 2020 11 781 5 of 17

The energy inputs of livestock production are calculated as Equation (3)

EIlivestock = (msum

j=1(LI f eed j times EC f eed j) + LIdrug times ECdrug + LIlabor times EClabor

+LIelec times ECelec + LIcoal times ECcoal)CWlivestock

(3)

where EIlivestock is the unit carcass (milk) weight of total energy inputs for livestock production (MJkgCW and milk) LI is the unit livestock of energy input for livestock production and CWlivestock is the unitlivestock of carcass weight (ie the weight of meat with bone except for fur viscera head hooves andblood) In regards to indexing feed drug labor elec coal j and m are feed inputs (kg) veterinary drugs (kg)human labor (h) electricity consumption for lighting of livestock housing (kwh) coal consumption forheating of livestock housing in winter (kg) feed classified j and feed types respectively

The energy outputs of livestock products are calculated as Equation (4)

EOlivestock = (LYcarcass times ECcarcass + LYmilk times ECmilk + LYwool times ECwool)CWlivestock (4)

where EOlivestock is the unit carcass (milk) weight of total energy outputs from livestock products (MJkgCW and milk) and LY is the unit livestock of yield In regards to indexing carcass milk and wool arecarcass weight (kg) milk (kg) and wool of livestock (kg) respectively

The energy indices of balances and ratios are calculated as follows

EBcropamplivestock = EOcropamplivestock minus EIcropamplivestock (5)

NERcropamplivestock =EOcropamplivestock

EIcropamplivestock(6)

where EBcropamplivestock represents the energy balances of crops (MJha) or livestock (MJCW andmilk) NERcropamplivestock represents the net energy ratio (outputinput) of crop or livestock productionEOcropamplivestock and EIcropamplivestock represent the same parameters of the above equation respectively

26 Calculation of GHG Emissions

The GHG emissions for each category of crop production input are calculated as Equation (7)

CEcrop = CIs times EFs + CI f times EF f + CIp times EFp + CIie times EFie + CIpm times EFpm

+AIdc times EFdc + AImd times EFmd + SOILres(7)

where CEcrop is the unit area of GHG emissions (kg CO2-eqha) and EF is the emission factor (Table 2)SOILres is the unit area of GHG emissions from soil respiration (kg CO2-eqha) using the followingEquation (8) [17]

SOILres = 155times e0031timesTtimes

Ptimes SOC(P + 068) times (P + 223)

(8)

where T P and SOC are the annual mean temperature (C) the annual rainfall (m) and soil organiccarbon between a 0 and 20 cm depth (kg Cmminus2) respectively [10]

Atmosphere 2020 11 781 6 of 17

Table 2 Factors used for the calculation of GHG emissions

Item Sub-Item Factors References

Emission Factors of GHG for Agricultural Production

Seed 1

(kg CO2-eqkg seed)

Wheat (spring) 0477 [18]Maize 385 [19]Cotton 2383 [18]Alfalfa 9643 [18]Grape 235 [2]

Tomato 163 [20]

Fertilizer(kg CO2-eqkg fertilizer)

N 638 [21]P 0733 [22]K 055 [22]

Soil emissions CO2 after N application 0633 [11]Soil emissions N2O after N application 6205 [23]

Pesticide(kg CO2-eqkg pesticide)

Herbicides 231 [5]Insecticides 187 [5]Fungicides 13933 [24]

Mulch (kg CO2-eqkg mulch) Plastic mulch 18993 [6]

Electricity (tCO2-eqkwh electricity) Electricityfor irrigation 0917 [25]

Fuel (kg CO2-eqL fuel) Diesel 2629 [6]

Tractor depreciation(kg CO2-eqyear)

Tractor 7810 1407 [26]Tractor 5560 049 [26]

Tractor 10021202 132 [26]Tractor 250 016 [26]

Harvester 1200 066 [26]Harvester 154 134 [26]

Feed processing(kg CO2-eqkg feed)

Maize 00102 [27]Soybean 01013 [27]Wheat 00319 [27]

CH4 emissions from entericfermentation

(kg CO2-eqheadyear)

Sheep 125 [11]Beef cattle 1175 [11]

Dairy cattle 1525 [11]CH4 emissions frommanure management

(kg CO2-eqheadyear)

Sheep 275 [11]Beef cattle 25 [11]

Dairy cattle 250 [11]N2O emissions frommanure managementkg CO2-eqheadyear)

Sheep 623 [11]Beef cattle 1204 [11]

Dairy cattle 1067 [11]1 Including seed production cleaning and packaging 2 Including exhaled carbon dioxide of adult labor

Carbon stocks of crop production are calculated using Equation (9) [28]

CScrop = CSgrain + CSstem + CSroot (9)

where CScrop CSgain CSstem and CSroot represent the unit area of carbon values accumulated in crops(kg CO2-eqha) grain (kg CO2-eqha) stems (kg CO2-eqha) and roots (kg CO2-eqha) respectively

Carbon balances of crop production are calculated as Equation (10)

CBcrop = CScrop minusCEcrop (10)

where CBcrop represents the unit area of carbon balances (kg CO2-eqha)The yearly GHG emissions from each livestock species are calculated using Equation (11)

CElivestock = (TCO2 f eed + TCO2drug + TCO2elec + TCO2coal + TCH4enteric+TCH4manure + TN2Omanure)CWlivestock

(11)

Atmosphere 2020 11 781 7 of 17

where CElivestock is the unit carcass (milk) weight of GHG emissions from livestock (kg CO2-eqkg CWand milk) TCO2 is the emissions of carbon dioxide TCH4 is the emissions of methane and TN2O is theemissions of nitrous oxide In regards to indexing enteric and manure are ruminant enteric fermentation(kg CO2-eqkg CW and milk) and manure management (kg CO2-eqkg CW and milk) respectively

The carbon stock and carbon balances of livestock production are calculated as the followingEquations (12) and (13) [29]

CSlivestock = (LW times 02)CWlivestock (12)

CBlivestock = CSlivestock minusCElivestock (13)

where CSlivestock is the carbon stock of livestock (kg CO2-eqkg CW and milk) and LW is the live weightof livestock CBlivestock is the carbon balance (kg CO2-eqkg CW and milk)

27 Calculation of Carbon Economic Efficiency

Based on emissions per one kilogram of carbon dioxide equivalence from agricultural productsthe total carbon economic efficiency associated with the mean market price of these products in 2015and 2016 (Table S3) is calculated using Equation (14) [28]

CEE =YPtimes PRICE

CE(14)

where CEE is the carbon economic efficiency (yenkg CO2-eq) YP is the yield of agricultural products(kg) PRICE is the price of agricultural products (yen) and CE is the GHG emissions from agriculturalproduction (kg CO2-eq)

28 Calculation of Water Use Efficiency

The analysis of energy balance per 1 cubic meter of water can find the relationship betweenirrigation and the net energy of crop production in the Shihezi Oasis The water use efficiency of cropproduction is calculated using Equation (15)

WUEcrop =EBcrop

WUcrop(15)

where WUEcrop EBcrop and WUcrop represent the water use efficiency of crops grown (MJm3)energy balances (MJha) and the water use of crops grown (m3ha) respectively

29 Statistical Analyses

We used the statistical program named Genstat170 (VSNI Corporation Hemel HempsteadUK) to analyze differences in energy indices (energy balances and net energy ratio) carbon indices(GHG emissions carbon stock carbon balances and carbon economic efficiency) water use and wateruse efficiency using inline linear models

3 Results

31 Yield and Water Use of Crop Production

The results of the yield and water use of crop production in three sub-oases of the Shihezi Oasisare presented in Table 3 The yields (kg DMha) of maize and cotton in SZC Oasis were significantlyhigher than in the other two oases (p lt 005) The water use for wheat (spring) and maize productionin SZC Oasis was higher than in the other two oases (p lt 005)

Atmosphere 2020 11 781 8 of 17

Table 3 Yield and water use of crop production in the Shihezi sub-oases

SZC 1 XYD 2 MSW 3 SED 4 p-Value

Crop products (Mg DMha)Wheat (spring) 1565 a 1644 a 1067 b 0379 lt005

Maize 6000 a 4545 b 4889 b 0218 lt005Cotton 1342 a 1568 b 1553 c 0157 lt005Alfalfa - 1481 1362 - -Grape - 3034 3067 - -

Tomato 8175 - - - -Water use (1000 m3ha)

Wheat (spring) 677 a 559 c 639 b 0176 lt0001Maize 906 a 759 b 7623 b 0244 lt005Cotton 832 a 823 a 630 b 033 lt005Alfalfa - 417 506 - -Grape - 739 596 - -

Tomato 656 - - - -Farmland 767 a 753 a 6501 b 0202 lt005

1 SZC Shizongchang 2 SZC Xiayedi 3 SZC Mosuowan 4 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

32 Energy Balances Net Energy Ratio and Water Use Efficiency of Agricultural Production

The results of energy balances the net energy ratio and water use efficiency in three sub-oasesof Shihezi Oasis are presented in Table 4 and Table S4 For crop production the output energy(30869 GJha) energy balances (22147 GJha) and net energy ratio (539) in the XYD Oasis were thehighest among the three production systems the corresponding values of MSW Oasis were higherthan in the SZC Oasis respectively (Table 4) However the input energy (4258 GJha) in the MSWOasis was lower than in the other two oases (p lt 001) The net energy ratio (645) and energy balances(30946 MJha) of maize in the XYD Oasis were significantly higher than that of the SZC and MSWoases (Table 4) Alfalfa (1271) and maize (627) had higher net energy ratios than other crops (p lt 001)(Table S4) For livestock production the production of 1 kg CW of sheep in XYD Oasis resulted insignificantly higher energy balances than in the other two oases Similarly the net energy ratio (221) ofsheep in the XYD Oasis was significantly higher than that of the SZC and MSW oases (Table 4)

Table 4 Energy balances net energy ratio and water use efficiency of agricultural production in theShihezi sub-oases

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Energy inputCrop production (GJha)

Wheat (spring) 6319 a 6001 a 5539 b 3239 lt005Maize 5693 a 4217 c 5003 b 1913 lt0001Cotton 7691 a 5837 b 4112 c 5166 lt0001Alfalfa - 1909 2361 - -Grape - 3558 3754 - -

Tomato 4955 - - - -Farmland 6933 a 5847 b 4258 c 4416 lt0001

Livestock production (MJkg CW and milk)Sheep 1496 a 1096 b 1197 b 1225 lt005

Beef cattle 3884 a 3032 b 3001 b 5230 lt005Dairy cattle 144 a 130 b 132 b 0040 lt005

Energy output (GJha)Crop production (GJha)

Wheat (spring) 25582 b 26881 a 17436 c 14779 lt0001Maize 31363 36001 35024 7048 0317Cotton 9972 b 11649 a 11541 a 2709 lt005

Atmosphere 2020 11 781 9 of 17

Table 4 Cont

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Alfalfa - 27848 25597 -Grape - 10128 1019 - -

Tomato 20415 - - - -Farmland 23069 c 30869 a 24764 b 16517 lt0001

Livestock production (MJkg CW and milk)Sheep 2923 2926 2929 0010 035

Beef cattle 8704 8701 8702 0002 0561Dairy cattle 256 254 254 0001 0570

Energy balances (GJha)Crop production (GJha)

Wheat (spring) 19563 b 2058 a 11897 c 13699 lt0001Maize 25707 b 30946 a 26997 b 8519 lt005Cotton 2282 c 5812 b 7429 a 7598 lt0001Alfalfa - 25539 23636 - -Grape - 2657 26436 - -

Tomato 1546 - - - -Farmland 16112 c 22147 a 20795 b 11452 lt0001

Livestock production (MJkg CW and Milk)Sheep 1711 b 1831 a 1718 b 1035 lt005

Beef cattle 4813 4901 4822 0924 0125Dairy cattle 110 112 108 0051 0214

Net energy ratio 1

Crop productionWheat 405 a 427 a 315 b 0185 lt005Maize 609 c 645 a 620 b 0225 lt0001Cotton 130 c 203 b 281 a 0219 lt0001Alfalfa - 1206 1305 - -Grape - 847 804 - -

Tomato 412 - - - -Farmland 332 c 539 a 463 b 0625 lt0001

Livestock productionSheep 195 b 221 a 197 b 0167 lt005

Beef cattle 229 b 243 a 231 b 0256 lt005Dairy cattle 178 180 177 0004 0524

Water use efficiency 2

Crop production (MJm3)Wheat (spring) 2892 ab 3684 a 1861 b 3196 lt005

Maize 757 c 1442 a 1180 b 1102 lt0001Cotton 273 c 699 b 1179 a 1321 lt0001Alfalfa - 2785 2350 - -Grape - 2557 2438 - -

Tomato 2359 - - - -Farmland 990 b 1399 a 1415 a 0812 lt005

1 net energy ratio = output energyinput energy 2 water use efficiency Water use based on energy balances3 SZC Shizongchang 4 SZC Xiayedi 5 SZC Mosuowan 6 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

33 GHG Emissions and Carbon Economic Efficiency of Agriculture Production

Carbon indices to evaluate agriculture production are presented in Table 5 and Table S4 Carbonbalances (minus112 Mg CO2-eqha) of crop production in SZC Oasis were lower than in the other twooases (p lt 005) (Table 5) GHG emissions (1772 Mg CO2-eqha) from cotton production weresignificantly higher than for the other five crops (p lt 001) (Table S4) Alfalfa had higher carbon stocks(2376 Mg CO2-eqha) and carbon balances (1597 Mg CO2-eqha) than other crops (p lt 001) (Table S4)According to the price of agricultural products (Table S3) and carbon input for farm productionSZC Oasis had a lower carbon economic efficiency (034 yenkg CO2-eq) of crop production than the other

Atmosphere 2020 11 781 10 of 17

two oases (p lt 005) (Table 5) The carbon economic efficiency of maize (114 yenkg CO2-eq) and alfalfa(118 yenkg CO2-eq) were significantly higher than other crops (p lt 001) (Table S4)

Table 5 GHG emissions carbon stocks carbon balances and the carbon economic efficiency ofagricultural production in the Shihezi sub-oases

SZC 2 XYD 3 MSW 4 SED 5 p-Value

GHG emissionsCrop production (Mg CO2-eqha year)

Wheat (spring) 858 b 860 b 899 a 0065 lt005Maize 1245 a 1212 b 1209 b 0057 lt005Cotton 1772 1775 1769 0137 0981Alfalfa - 809 810 - -Grape - 1226 1219 - -

Tomato 1702 - - - -Farmland 1322 1294 1227 0377 0534

Livestock production (kg CO2-eqkg CW and milk)Sheep 923 a 835 ab 762 b 0305 0072

Beef cattle 2295 b 2419 a 2287 b 0237 lt005Dairy cattle 067 070 071 0013 0639

Carbon stocksCrop production (Mg CO2-eqha year)

Wheat (spring) 1044 b 1040 b 1086 a 0075 0069Maize 2352 a 2284 b 2283 b 0107 lt005Cotton 1313 1310 1311 0101 0995Alfalfa - 2383 2374 - -Grape - 1098 1100 - -

Tomato 1035 - - - -Farmland 1210 b 1594 a 1733 a 0582 lt0001

Livestock production (kg CO2-eqkg CW and milk)Sheep 106 a 176 ab 193 b 0061 0610

Beef cattle 357 322 354 0097 0287Dairy cattle 010 011 011 0003 0593

Carbon balancesCrop production (Mg CO2-eqha year)

Wheat (spring) 185 180 187 0012 0160Maize 1106 a 1072 b 1075 b 0050 lt005Cotton minus459 minus464 minus456 0037 0601Alfalfa - 1574 1563 - -Grape - minus128 minus118 - -

Tomato minus668 - - - -Farmland minus112 b 299 a 506 a 0798 lt005

Livestock production (kg CO2-eqkg CW and milk)Sheep minus763 b

minus660 ab minus569 a 0330 lt005Beef cattle minus1939 a

minus2097 b minus1932 a 0298 lt005Dairy cattle minus053 minus059 minus057 0011 0653

Carbon economic efficiency (yenkg CO2-eq)Crop production

Wheat 017 018 017 0001 0185Maize 116 117 114 0016 0802Cotton 070 072 070 0015 0872Alfalfa - 118 117 - -Grape - 041 042 - -

Tomato 032 - - - -Farmland 034 b 075 a 082 a 0042 lt0001

Livestock productionSheep 024 a 022 ab 020 b 0008 0063

Beef cattle 038 b 040 a 038 b 0004 lt005Dairy cattle 017 018 018 0609 0524

1 net energy ratio = output energyinput energy 2 SZC Shizongchang 3 SZC Xiayedi 4 SZC Mosuowan5 SED Standard error of differences a b and c represent means with different letters in a row differing significantly(p lt 005)

Atmosphere 2020 11 781 11 of 17

34 Water Use Efficiency Based on Energy

Water use and the water use efficiency of crop production in the Shihezi Oasis are presented inTables 3 and 4 Among the three sub-oases in the Shihezi Oasis the water use of crop production in theMSW Oasis is lower than the corresponding value of the SZC and XYD oases (p lt 005) Howeverthe water use efficiency of crop production in the SZC Oasis is lower than that of the XYD and MSWoases (p lt 005) The water use (4590 m3ha) for alfalfa production in the Shihezi Oasis is the lowestwith the highest water use efficiency (4582 MJm3) (Table S4)

35 Contribution of Carbon Emissions

To further illustrate the relationship between GHG emissions and other factors Figure 2 showsthe contribution of GHG emissions from inputs of crop production The major GHG emission sourceswithin the crop production system are fertilizer and irrigation

Figure 2 Total GHG emissions from crop production and the contribution of emission sources

36 Effect Analysis of Structural Equation Modelling (SEM)

The effect analysis of SEM is presented in Table S5 The path modes show that the direct andtotal effects of the livestock breeding structure on predicted variables (farm net income energyand carbon balances) are much stronger than other dependent variables (Figure 3a total effects = 0647Figure 3b total effects = 0898 Figure 3c total effects = 1091 Figure 3d total effects = 0980Figure 3e total effects = 0898 and Figure 3f total effects = 01091) Similarly the path modesshow that the indirect effects of water use efficiency on economy income energy and carbon balancesare much stronger than those of other variables (Figure 3a indirect effects = 0196 Figure 3bindirect effects = 0297 and Figure 3c indirect effects = 0430)

Atmosphere 2020 11 781 12 of 17

Figure 3 Path models showing the direct and indirect effects of predictor variables on farm net incomeenergy balances and carbon balances The path models with significant correlations are presentedas solid lines The values on solid lines represent standardized regression weights Interruptedlines indicate no significant correlation between two variables Black arrows indicate positiveeffects For each endogenous variable the relative amount of explained variance is given Shadingindicates the greatest positive direct effect indirect effect and total effect between dependent andindependent variables OtoD The distance from the oasis to the desert (km) SPD Soil particle diameter(microm) PS Planting structure (planting crop type) WUE Water use efficiency (MJm3) BS Livestockbreeding structure (breeding livestock category) ECO Net income (1000 yenha) EB Energy balance(GJha) CB The difference value of carbon stock minus GHG emissions from agricultural productioninputs (Mg CO2-eqha) and OtoM The distance from the oasis to the desert (km) χ2 Chi-squarep Probability level df Degrees of freedom n Sample size

4 Discussion

41 Energy Balances and Net Energy Ratio

The present energy balances of agricultural production in the Shihezi Oasis are comparable tothose published elsewhere in the world using the similar methodology of calculating the input andoutput energy values on farms For example the input energy of cotton production (5880 GJha)in the Shihezi Oasis is much higher than that (31237 GJha) in Iran [30] This difference refers tothe low energy input of weed controlling and harvesting operations using human labor instead ofapplying machinery in Iran Nevertheless Shihezirsquos input energy for maize production (4971 GJha) isclose to that reported in Iran (50458 GJha) due to similar intensive and high input crop productionsystems [31] However our output energy including grain straw and roots of maize production(34121 GJha) is much higher than that only related to grain estimated in Iran (134946 GJha) [30]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 4 of 17

consumption for irrigation (kwh) and plastic films (kg) respectively The energy outputs for eachcategory of crop including the grain straw and roots are calculated as Equation (2)

EOcrop = CYgrain times ECgrain + CYstraw times ECstraw + CYroot times ECroot (2)

where EOcrop is the unit area of total energy outputs from crop products (MJha) and CY is the unit areaof yield In regards to indexing grain straw and root are grain (kg) straw (kg) and roots (kg) of cropproducts respectively

Table 1 Factors used for the calculation of energy inputs and energy outputs

Energy Factors of Agricultural Production Inputs

Seed(MJkg seed)

Wheat (spring) 179 [11]Maize 10465 [12]Cotton 22024 [13]Alfalfa 10882 [11]Grape 1516 [13]

Tomato 1633 [14]

Fertilizer(MJkg fertilizer)

N 781 [12]P 174 [12]K 137 [12]

Farmyard manure(MJkg manure) Animal manure 1463 [12]

Pesticide(MJkg pesticide)

Herbicides 278 [12]Insecticides 233 [12]Fungicides 121 [12]

Mulch (MJkg mulch) Plastic mulch 519 [6]Fuel (MJkg fuel) Diesel 4778 [6]

Electricity (MJkwh electricity) Electricityfor irrigation 12

Transportation(MJkg truck) Truck 88 [11]

Maintenance ofmachinery (MJkg tractor) Tractor 521 [15]

Human labor (MJh) Male 068 [12]Female 052 [12]

Forage feed(MJkg feed)

Wheat hay 1505 [16]Maize hay 1522 [16]Alfalfa hay 188 [16]

Concentrate feed(MJkg feed)

Maize 1826 [16]Soybean 1883 [16]

Wheat husk 1372 [16]Energy Factors of Agricultural Products

Grain (MJkg grain)

Wheat (spring) 1256 [16]Maize 1826 [16]Cotton 22024 [16]Grape 2341 [16]

Tomato 1258 [13]

Hay (MJkg hay)

Wheat (spring) 1505 [16]Maize 1522 [16]Alfalfa 188 [16]Cotton 1737 [16]

Livestock products (MJkg product)

Lamb 12877 [13]Beef 1388 [13]Milk 2889 [13]Wool 2341 [11]

Atmosphere 2020 11 781 5 of 17

The energy inputs of livestock production are calculated as Equation (3)

EIlivestock = (msum

j=1(LI f eed j times EC f eed j) + LIdrug times ECdrug + LIlabor times EClabor

+LIelec times ECelec + LIcoal times ECcoal)CWlivestock

(3)

where EIlivestock is the unit carcass (milk) weight of total energy inputs for livestock production (MJkgCW and milk) LI is the unit livestock of energy input for livestock production and CWlivestock is the unitlivestock of carcass weight (ie the weight of meat with bone except for fur viscera head hooves andblood) In regards to indexing feed drug labor elec coal j and m are feed inputs (kg) veterinary drugs (kg)human labor (h) electricity consumption for lighting of livestock housing (kwh) coal consumption forheating of livestock housing in winter (kg) feed classified j and feed types respectively

The energy outputs of livestock products are calculated as Equation (4)

EOlivestock = (LYcarcass times ECcarcass + LYmilk times ECmilk + LYwool times ECwool)CWlivestock (4)

where EOlivestock is the unit carcass (milk) weight of total energy outputs from livestock products (MJkgCW and milk) and LY is the unit livestock of yield In regards to indexing carcass milk and wool arecarcass weight (kg) milk (kg) and wool of livestock (kg) respectively

The energy indices of balances and ratios are calculated as follows

EBcropamplivestock = EOcropamplivestock minus EIcropamplivestock (5)

NERcropamplivestock =EOcropamplivestock

EIcropamplivestock(6)

where EBcropamplivestock represents the energy balances of crops (MJha) or livestock (MJCW andmilk) NERcropamplivestock represents the net energy ratio (outputinput) of crop or livestock productionEOcropamplivestock and EIcropamplivestock represent the same parameters of the above equation respectively

26 Calculation of GHG Emissions

The GHG emissions for each category of crop production input are calculated as Equation (7)

CEcrop = CIs times EFs + CI f times EF f + CIp times EFp + CIie times EFie + CIpm times EFpm

+AIdc times EFdc + AImd times EFmd + SOILres(7)

where CEcrop is the unit area of GHG emissions (kg CO2-eqha) and EF is the emission factor (Table 2)SOILres is the unit area of GHG emissions from soil respiration (kg CO2-eqha) using the followingEquation (8) [17]

SOILres = 155times e0031timesTtimes

Ptimes SOC(P + 068) times (P + 223)

(8)

where T P and SOC are the annual mean temperature (C) the annual rainfall (m) and soil organiccarbon between a 0 and 20 cm depth (kg Cmminus2) respectively [10]

Atmosphere 2020 11 781 6 of 17

Table 2 Factors used for the calculation of GHG emissions

Item Sub-Item Factors References

Emission Factors of GHG for Agricultural Production

Seed 1

(kg CO2-eqkg seed)

Wheat (spring) 0477 [18]Maize 385 [19]Cotton 2383 [18]Alfalfa 9643 [18]Grape 235 [2]

Tomato 163 [20]

Fertilizer(kg CO2-eqkg fertilizer)

N 638 [21]P 0733 [22]K 055 [22]

Soil emissions CO2 after N application 0633 [11]Soil emissions N2O after N application 6205 [23]

Pesticide(kg CO2-eqkg pesticide)

Herbicides 231 [5]Insecticides 187 [5]Fungicides 13933 [24]

Mulch (kg CO2-eqkg mulch) Plastic mulch 18993 [6]

Electricity (tCO2-eqkwh electricity) Electricityfor irrigation 0917 [25]

Fuel (kg CO2-eqL fuel) Diesel 2629 [6]

Tractor depreciation(kg CO2-eqyear)

Tractor 7810 1407 [26]Tractor 5560 049 [26]

Tractor 10021202 132 [26]Tractor 250 016 [26]

Harvester 1200 066 [26]Harvester 154 134 [26]

Feed processing(kg CO2-eqkg feed)

Maize 00102 [27]Soybean 01013 [27]Wheat 00319 [27]

CH4 emissions from entericfermentation

(kg CO2-eqheadyear)

Sheep 125 [11]Beef cattle 1175 [11]

Dairy cattle 1525 [11]CH4 emissions frommanure management

(kg CO2-eqheadyear)

Sheep 275 [11]Beef cattle 25 [11]

Dairy cattle 250 [11]N2O emissions frommanure managementkg CO2-eqheadyear)

Sheep 623 [11]Beef cattle 1204 [11]

Dairy cattle 1067 [11]1 Including seed production cleaning and packaging 2 Including exhaled carbon dioxide of adult labor

Carbon stocks of crop production are calculated using Equation (9) [28]

CScrop = CSgrain + CSstem + CSroot (9)

where CScrop CSgain CSstem and CSroot represent the unit area of carbon values accumulated in crops(kg CO2-eqha) grain (kg CO2-eqha) stems (kg CO2-eqha) and roots (kg CO2-eqha) respectively

Carbon balances of crop production are calculated as Equation (10)

CBcrop = CScrop minusCEcrop (10)

where CBcrop represents the unit area of carbon balances (kg CO2-eqha)The yearly GHG emissions from each livestock species are calculated using Equation (11)

CElivestock = (TCO2 f eed + TCO2drug + TCO2elec + TCO2coal + TCH4enteric+TCH4manure + TN2Omanure)CWlivestock

(11)

Atmosphere 2020 11 781 7 of 17

where CElivestock is the unit carcass (milk) weight of GHG emissions from livestock (kg CO2-eqkg CWand milk) TCO2 is the emissions of carbon dioxide TCH4 is the emissions of methane and TN2O is theemissions of nitrous oxide In regards to indexing enteric and manure are ruminant enteric fermentation(kg CO2-eqkg CW and milk) and manure management (kg CO2-eqkg CW and milk) respectively

The carbon stock and carbon balances of livestock production are calculated as the followingEquations (12) and (13) [29]

CSlivestock = (LW times 02)CWlivestock (12)

CBlivestock = CSlivestock minusCElivestock (13)

where CSlivestock is the carbon stock of livestock (kg CO2-eqkg CW and milk) and LW is the live weightof livestock CBlivestock is the carbon balance (kg CO2-eqkg CW and milk)

27 Calculation of Carbon Economic Efficiency

Based on emissions per one kilogram of carbon dioxide equivalence from agricultural productsthe total carbon economic efficiency associated with the mean market price of these products in 2015and 2016 (Table S3) is calculated using Equation (14) [28]

CEE =YPtimes PRICE

CE(14)

where CEE is the carbon economic efficiency (yenkg CO2-eq) YP is the yield of agricultural products(kg) PRICE is the price of agricultural products (yen) and CE is the GHG emissions from agriculturalproduction (kg CO2-eq)

28 Calculation of Water Use Efficiency

The analysis of energy balance per 1 cubic meter of water can find the relationship betweenirrigation and the net energy of crop production in the Shihezi Oasis The water use efficiency of cropproduction is calculated using Equation (15)

WUEcrop =EBcrop

WUcrop(15)

where WUEcrop EBcrop and WUcrop represent the water use efficiency of crops grown (MJm3)energy balances (MJha) and the water use of crops grown (m3ha) respectively

29 Statistical Analyses

We used the statistical program named Genstat170 (VSNI Corporation Hemel HempsteadUK) to analyze differences in energy indices (energy balances and net energy ratio) carbon indices(GHG emissions carbon stock carbon balances and carbon economic efficiency) water use and wateruse efficiency using inline linear models

3 Results

31 Yield and Water Use of Crop Production

The results of the yield and water use of crop production in three sub-oases of the Shihezi Oasisare presented in Table 3 The yields (kg DMha) of maize and cotton in SZC Oasis were significantlyhigher than in the other two oases (p lt 005) The water use for wheat (spring) and maize productionin SZC Oasis was higher than in the other two oases (p lt 005)

Atmosphere 2020 11 781 8 of 17

Table 3 Yield and water use of crop production in the Shihezi sub-oases

SZC 1 XYD 2 MSW 3 SED 4 p-Value

Crop products (Mg DMha)Wheat (spring) 1565 a 1644 a 1067 b 0379 lt005

Maize 6000 a 4545 b 4889 b 0218 lt005Cotton 1342 a 1568 b 1553 c 0157 lt005Alfalfa - 1481 1362 - -Grape - 3034 3067 - -

Tomato 8175 - - - -Water use (1000 m3ha)

Wheat (spring) 677 a 559 c 639 b 0176 lt0001Maize 906 a 759 b 7623 b 0244 lt005Cotton 832 a 823 a 630 b 033 lt005Alfalfa - 417 506 - -Grape - 739 596 - -

Tomato 656 - - - -Farmland 767 a 753 a 6501 b 0202 lt005

1 SZC Shizongchang 2 SZC Xiayedi 3 SZC Mosuowan 4 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

32 Energy Balances Net Energy Ratio and Water Use Efficiency of Agricultural Production

The results of energy balances the net energy ratio and water use efficiency in three sub-oasesof Shihezi Oasis are presented in Table 4 and Table S4 For crop production the output energy(30869 GJha) energy balances (22147 GJha) and net energy ratio (539) in the XYD Oasis were thehighest among the three production systems the corresponding values of MSW Oasis were higherthan in the SZC Oasis respectively (Table 4) However the input energy (4258 GJha) in the MSWOasis was lower than in the other two oases (p lt 001) The net energy ratio (645) and energy balances(30946 MJha) of maize in the XYD Oasis were significantly higher than that of the SZC and MSWoases (Table 4) Alfalfa (1271) and maize (627) had higher net energy ratios than other crops (p lt 001)(Table S4) For livestock production the production of 1 kg CW of sheep in XYD Oasis resulted insignificantly higher energy balances than in the other two oases Similarly the net energy ratio (221) ofsheep in the XYD Oasis was significantly higher than that of the SZC and MSW oases (Table 4)

Table 4 Energy balances net energy ratio and water use efficiency of agricultural production in theShihezi sub-oases

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Energy inputCrop production (GJha)

Wheat (spring) 6319 a 6001 a 5539 b 3239 lt005Maize 5693 a 4217 c 5003 b 1913 lt0001Cotton 7691 a 5837 b 4112 c 5166 lt0001Alfalfa - 1909 2361 - -Grape - 3558 3754 - -

Tomato 4955 - - - -Farmland 6933 a 5847 b 4258 c 4416 lt0001

Livestock production (MJkg CW and milk)Sheep 1496 a 1096 b 1197 b 1225 lt005

Beef cattle 3884 a 3032 b 3001 b 5230 lt005Dairy cattle 144 a 130 b 132 b 0040 lt005

Energy output (GJha)Crop production (GJha)

Wheat (spring) 25582 b 26881 a 17436 c 14779 lt0001Maize 31363 36001 35024 7048 0317Cotton 9972 b 11649 a 11541 a 2709 lt005

Atmosphere 2020 11 781 9 of 17

Table 4 Cont

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Alfalfa - 27848 25597 -Grape - 10128 1019 - -

Tomato 20415 - - - -Farmland 23069 c 30869 a 24764 b 16517 lt0001

Livestock production (MJkg CW and milk)Sheep 2923 2926 2929 0010 035

Beef cattle 8704 8701 8702 0002 0561Dairy cattle 256 254 254 0001 0570

Energy balances (GJha)Crop production (GJha)

Wheat (spring) 19563 b 2058 a 11897 c 13699 lt0001Maize 25707 b 30946 a 26997 b 8519 lt005Cotton 2282 c 5812 b 7429 a 7598 lt0001Alfalfa - 25539 23636 - -Grape - 2657 26436 - -

Tomato 1546 - - - -Farmland 16112 c 22147 a 20795 b 11452 lt0001

Livestock production (MJkg CW and Milk)Sheep 1711 b 1831 a 1718 b 1035 lt005

Beef cattle 4813 4901 4822 0924 0125Dairy cattle 110 112 108 0051 0214

Net energy ratio 1

Crop productionWheat 405 a 427 a 315 b 0185 lt005Maize 609 c 645 a 620 b 0225 lt0001Cotton 130 c 203 b 281 a 0219 lt0001Alfalfa - 1206 1305 - -Grape - 847 804 - -

Tomato 412 - - - -Farmland 332 c 539 a 463 b 0625 lt0001

Livestock productionSheep 195 b 221 a 197 b 0167 lt005

Beef cattle 229 b 243 a 231 b 0256 lt005Dairy cattle 178 180 177 0004 0524

Water use efficiency 2

Crop production (MJm3)Wheat (spring) 2892 ab 3684 a 1861 b 3196 lt005

Maize 757 c 1442 a 1180 b 1102 lt0001Cotton 273 c 699 b 1179 a 1321 lt0001Alfalfa - 2785 2350 - -Grape - 2557 2438 - -

Tomato 2359 - - - -Farmland 990 b 1399 a 1415 a 0812 lt005

1 net energy ratio = output energyinput energy 2 water use efficiency Water use based on energy balances3 SZC Shizongchang 4 SZC Xiayedi 5 SZC Mosuowan 6 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

33 GHG Emissions and Carbon Economic Efficiency of Agriculture Production

Carbon indices to evaluate agriculture production are presented in Table 5 and Table S4 Carbonbalances (minus112 Mg CO2-eqha) of crop production in SZC Oasis were lower than in the other twooases (p lt 005) (Table 5) GHG emissions (1772 Mg CO2-eqha) from cotton production weresignificantly higher than for the other five crops (p lt 001) (Table S4) Alfalfa had higher carbon stocks(2376 Mg CO2-eqha) and carbon balances (1597 Mg CO2-eqha) than other crops (p lt 001) (Table S4)According to the price of agricultural products (Table S3) and carbon input for farm productionSZC Oasis had a lower carbon economic efficiency (034 yenkg CO2-eq) of crop production than the other

Atmosphere 2020 11 781 10 of 17

two oases (p lt 005) (Table 5) The carbon economic efficiency of maize (114 yenkg CO2-eq) and alfalfa(118 yenkg CO2-eq) were significantly higher than other crops (p lt 001) (Table S4)

Table 5 GHG emissions carbon stocks carbon balances and the carbon economic efficiency ofagricultural production in the Shihezi sub-oases

SZC 2 XYD 3 MSW 4 SED 5 p-Value

GHG emissionsCrop production (Mg CO2-eqha year)

Wheat (spring) 858 b 860 b 899 a 0065 lt005Maize 1245 a 1212 b 1209 b 0057 lt005Cotton 1772 1775 1769 0137 0981Alfalfa - 809 810 - -Grape - 1226 1219 - -

Tomato 1702 - - - -Farmland 1322 1294 1227 0377 0534

Livestock production (kg CO2-eqkg CW and milk)Sheep 923 a 835 ab 762 b 0305 0072

Beef cattle 2295 b 2419 a 2287 b 0237 lt005Dairy cattle 067 070 071 0013 0639

Carbon stocksCrop production (Mg CO2-eqha year)

Wheat (spring) 1044 b 1040 b 1086 a 0075 0069Maize 2352 a 2284 b 2283 b 0107 lt005Cotton 1313 1310 1311 0101 0995Alfalfa - 2383 2374 - -Grape - 1098 1100 - -

Tomato 1035 - - - -Farmland 1210 b 1594 a 1733 a 0582 lt0001

Livestock production (kg CO2-eqkg CW and milk)Sheep 106 a 176 ab 193 b 0061 0610

Beef cattle 357 322 354 0097 0287Dairy cattle 010 011 011 0003 0593

Carbon balancesCrop production (Mg CO2-eqha year)

Wheat (spring) 185 180 187 0012 0160Maize 1106 a 1072 b 1075 b 0050 lt005Cotton minus459 minus464 minus456 0037 0601Alfalfa - 1574 1563 - -Grape - minus128 minus118 - -

Tomato minus668 - - - -Farmland minus112 b 299 a 506 a 0798 lt005

Livestock production (kg CO2-eqkg CW and milk)Sheep minus763 b

minus660 ab minus569 a 0330 lt005Beef cattle minus1939 a

minus2097 b minus1932 a 0298 lt005Dairy cattle minus053 minus059 minus057 0011 0653

Carbon economic efficiency (yenkg CO2-eq)Crop production

Wheat 017 018 017 0001 0185Maize 116 117 114 0016 0802Cotton 070 072 070 0015 0872Alfalfa - 118 117 - -Grape - 041 042 - -

Tomato 032 - - - -Farmland 034 b 075 a 082 a 0042 lt0001

Livestock productionSheep 024 a 022 ab 020 b 0008 0063

Beef cattle 038 b 040 a 038 b 0004 lt005Dairy cattle 017 018 018 0609 0524

1 net energy ratio = output energyinput energy 2 SZC Shizongchang 3 SZC Xiayedi 4 SZC Mosuowan5 SED Standard error of differences a b and c represent means with different letters in a row differing significantly(p lt 005)

Atmosphere 2020 11 781 11 of 17

34 Water Use Efficiency Based on Energy

Water use and the water use efficiency of crop production in the Shihezi Oasis are presented inTables 3 and 4 Among the three sub-oases in the Shihezi Oasis the water use of crop production in theMSW Oasis is lower than the corresponding value of the SZC and XYD oases (p lt 005) Howeverthe water use efficiency of crop production in the SZC Oasis is lower than that of the XYD and MSWoases (p lt 005) The water use (4590 m3ha) for alfalfa production in the Shihezi Oasis is the lowestwith the highest water use efficiency (4582 MJm3) (Table S4)

35 Contribution of Carbon Emissions

To further illustrate the relationship between GHG emissions and other factors Figure 2 showsthe contribution of GHG emissions from inputs of crop production The major GHG emission sourceswithin the crop production system are fertilizer and irrigation

Figure 2 Total GHG emissions from crop production and the contribution of emission sources

36 Effect Analysis of Structural Equation Modelling (SEM)

The effect analysis of SEM is presented in Table S5 The path modes show that the direct andtotal effects of the livestock breeding structure on predicted variables (farm net income energyand carbon balances) are much stronger than other dependent variables (Figure 3a total effects = 0647Figure 3b total effects = 0898 Figure 3c total effects = 1091 Figure 3d total effects = 0980Figure 3e total effects = 0898 and Figure 3f total effects = 01091) Similarly the path modesshow that the indirect effects of water use efficiency on economy income energy and carbon balancesare much stronger than those of other variables (Figure 3a indirect effects = 0196 Figure 3bindirect effects = 0297 and Figure 3c indirect effects = 0430)

Atmosphere 2020 11 781 12 of 17

Figure 3 Path models showing the direct and indirect effects of predictor variables on farm net incomeenergy balances and carbon balances The path models with significant correlations are presentedas solid lines The values on solid lines represent standardized regression weights Interruptedlines indicate no significant correlation between two variables Black arrows indicate positiveeffects For each endogenous variable the relative amount of explained variance is given Shadingindicates the greatest positive direct effect indirect effect and total effect between dependent andindependent variables OtoD The distance from the oasis to the desert (km) SPD Soil particle diameter(microm) PS Planting structure (planting crop type) WUE Water use efficiency (MJm3) BS Livestockbreeding structure (breeding livestock category) ECO Net income (1000 yenha) EB Energy balance(GJha) CB The difference value of carbon stock minus GHG emissions from agricultural productioninputs (Mg CO2-eqha) and OtoM The distance from the oasis to the desert (km) χ2 Chi-squarep Probability level df Degrees of freedom n Sample size

4 Discussion

41 Energy Balances and Net Energy Ratio

The present energy balances of agricultural production in the Shihezi Oasis are comparable tothose published elsewhere in the world using the similar methodology of calculating the input andoutput energy values on farms For example the input energy of cotton production (5880 GJha)in the Shihezi Oasis is much higher than that (31237 GJha) in Iran [30] This difference refers tothe low energy input of weed controlling and harvesting operations using human labor instead ofapplying machinery in Iran Nevertheless Shihezirsquos input energy for maize production (4971 GJha) isclose to that reported in Iran (50458 GJha) due to similar intensive and high input crop productionsystems [31] However our output energy including grain straw and roots of maize production(34121 GJha) is much higher than that only related to grain estimated in Iran (134946 GJha) [30]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 5 of 17

The energy inputs of livestock production are calculated as Equation (3)

EIlivestock = (msum

j=1(LI f eed j times EC f eed j) + LIdrug times ECdrug + LIlabor times EClabor

+LIelec times ECelec + LIcoal times ECcoal)CWlivestock

(3)

where EIlivestock is the unit carcass (milk) weight of total energy inputs for livestock production (MJkgCW and milk) LI is the unit livestock of energy input for livestock production and CWlivestock is the unitlivestock of carcass weight (ie the weight of meat with bone except for fur viscera head hooves andblood) In regards to indexing feed drug labor elec coal j and m are feed inputs (kg) veterinary drugs (kg)human labor (h) electricity consumption for lighting of livestock housing (kwh) coal consumption forheating of livestock housing in winter (kg) feed classified j and feed types respectively

The energy outputs of livestock products are calculated as Equation (4)

EOlivestock = (LYcarcass times ECcarcass + LYmilk times ECmilk + LYwool times ECwool)CWlivestock (4)

where EOlivestock is the unit carcass (milk) weight of total energy outputs from livestock products (MJkgCW and milk) and LY is the unit livestock of yield In regards to indexing carcass milk and wool arecarcass weight (kg) milk (kg) and wool of livestock (kg) respectively

The energy indices of balances and ratios are calculated as follows

EBcropamplivestock = EOcropamplivestock minus EIcropamplivestock (5)

NERcropamplivestock =EOcropamplivestock

EIcropamplivestock(6)

where EBcropamplivestock represents the energy balances of crops (MJha) or livestock (MJCW andmilk) NERcropamplivestock represents the net energy ratio (outputinput) of crop or livestock productionEOcropamplivestock and EIcropamplivestock represent the same parameters of the above equation respectively

26 Calculation of GHG Emissions

The GHG emissions for each category of crop production input are calculated as Equation (7)

CEcrop = CIs times EFs + CI f times EF f + CIp times EFp + CIie times EFie + CIpm times EFpm

+AIdc times EFdc + AImd times EFmd + SOILres(7)

where CEcrop is the unit area of GHG emissions (kg CO2-eqha) and EF is the emission factor (Table 2)SOILres is the unit area of GHG emissions from soil respiration (kg CO2-eqha) using the followingEquation (8) [17]

SOILres = 155times e0031timesTtimes

Ptimes SOC(P + 068) times (P + 223)

(8)

where T P and SOC are the annual mean temperature (C) the annual rainfall (m) and soil organiccarbon between a 0 and 20 cm depth (kg Cmminus2) respectively [10]

Atmosphere 2020 11 781 6 of 17

Table 2 Factors used for the calculation of GHG emissions

Item Sub-Item Factors References

Emission Factors of GHG for Agricultural Production

Seed 1

(kg CO2-eqkg seed)

Wheat (spring) 0477 [18]Maize 385 [19]Cotton 2383 [18]Alfalfa 9643 [18]Grape 235 [2]

Tomato 163 [20]

Fertilizer(kg CO2-eqkg fertilizer)

N 638 [21]P 0733 [22]K 055 [22]

Soil emissions CO2 after N application 0633 [11]Soil emissions N2O after N application 6205 [23]

Pesticide(kg CO2-eqkg pesticide)

Herbicides 231 [5]Insecticides 187 [5]Fungicides 13933 [24]

Mulch (kg CO2-eqkg mulch) Plastic mulch 18993 [6]

Electricity (tCO2-eqkwh electricity) Electricityfor irrigation 0917 [25]

Fuel (kg CO2-eqL fuel) Diesel 2629 [6]

Tractor depreciation(kg CO2-eqyear)

Tractor 7810 1407 [26]Tractor 5560 049 [26]

Tractor 10021202 132 [26]Tractor 250 016 [26]

Harvester 1200 066 [26]Harvester 154 134 [26]

Feed processing(kg CO2-eqkg feed)

Maize 00102 [27]Soybean 01013 [27]Wheat 00319 [27]

CH4 emissions from entericfermentation

(kg CO2-eqheadyear)

Sheep 125 [11]Beef cattle 1175 [11]

Dairy cattle 1525 [11]CH4 emissions frommanure management

(kg CO2-eqheadyear)

Sheep 275 [11]Beef cattle 25 [11]

Dairy cattle 250 [11]N2O emissions frommanure managementkg CO2-eqheadyear)

Sheep 623 [11]Beef cattle 1204 [11]

Dairy cattle 1067 [11]1 Including seed production cleaning and packaging 2 Including exhaled carbon dioxide of adult labor

Carbon stocks of crop production are calculated using Equation (9) [28]

CScrop = CSgrain + CSstem + CSroot (9)

where CScrop CSgain CSstem and CSroot represent the unit area of carbon values accumulated in crops(kg CO2-eqha) grain (kg CO2-eqha) stems (kg CO2-eqha) and roots (kg CO2-eqha) respectively

Carbon balances of crop production are calculated as Equation (10)

CBcrop = CScrop minusCEcrop (10)

where CBcrop represents the unit area of carbon balances (kg CO2-eqha)The yearly GHG emissions from each livestock species are calculated using Equation (11)

CElivestock = (TCO2 f eed + TCO2drug + TCO2elec + TCO2coal + TCH4enteric+TCH4manure + TN2Omanure)CWlivestock

(11)

Atmosphere 2020 11 781 7 of 17

where CElivestock is the unit carcass (milk) weight of GHG emissions from livestock (kg CO2-eqkg CWand milk) TCO2 is the emissions of carbon dioxide TCH4 is the emissions of methane and TN2O is theemissions of nitrous oxide In regards to indexing enteric and manure are ruminant enteric fermentation(kg CO2-eqkg CW and milk) and manure management (kg CO2-eqkg CW and milk) respectively

The carbon stock and carbon balances of livestock production are calculated as the followingEquations (12) and (13) [29]

CSlivestock = (LW times 02)CWlivestock (12)

CBlivestock = CSlivestock minusCElivestock (13)

where CSlivestock is the carbon stock of livestock (kg CO2-eqkg CW and milk) and LW is the live weightof livestock CBlivestock is the carbon balance (kg CO2-eqkg CW and milk)

27 Calculation of Carbon Economic Efficiency

Based on emissions per one kilogram of carbon dioxide equivalence from agricultural productsthe total carbon economic efficiency associated with the mean market price of these products in 2015and 2016 (Table S3) is calculated using Equation (14) [28]

CEE =YPtimes PRICE

CE(14)

where CEE is the carbon economic efficiency (yenkg CO2-eq) YP is the yield of agricultural products(kg) PRICE is the price of agricultural products (yen) and CE is the GHG emissions from agriculturalproduction (kg CO2-eq)

28 Calculation of Water Use Efficiency

The analysis of energy balance per 1 cubic meter of water can find the relationship betweenirrigation and the net energy of crop production in the Shihezi Oasis The water use efficiency of cropproduction is calculated using Equation (15)

WUEcrop =EBcrop

WUcrop(15)

where WUEcrop EBcrop and WUcrop represent the water use efficiency of crops grown (MJm3)energy balances (MJha) and the water use of crops grown (m3ha) respectively

29 Statistical Analyses

We used the statistical program named Genstat170 (VSNI Corporation Hemel HempsteadUK) to analyze differences in energy indices (energy balances and net energy ratio) carbon indices(GHG emissions carbon stock carbon balances and carbon economic efficiency) water use and wateruse efficiency using inline linear models

3 Results

31 Yield and Water Use of Crop Production

The results of the yield and water use of crop production in three sub-oases of the Shihezi Oasisare presented in Table 3 The yields (kg DMha) of maize and cotton in SZC Oasis were significantlyhigher than in the other two oases (p lt 005) The water use for wheat (spring) and maize productionin SZC Oasis was higher than in the other two oases (p lt 005)

Atmosphere 2020 11 781 8 of 17

Table 3 Yield and water use of crop production in the Shihezi sub-oases

SZC 1 XYD 2 MSW 3 SED 4 p-Value

Crop products (Mg DMha)Wheat (spring) 1565 a 1644 a 1067 b 0379 lt005

Maize 6000 a 4545 b 4889 b 0218 lt005Cotton 1342 a 1568 b 1553 c 0157 lt005Alfalfa - 1481 1362 - -Grape - 3034 3067 - -

Tomato 8175 - - - -Water use (1000 m3ha)

Wheat (spring) 677 a 559 c 639 b 0176 lt0001Maize 906 a 759 b 7623 b 0244 lt005Cotton 832 a 823 a 630 b 033 lt005Alfalfa - 417 506 - -Grape - 739 596 - -

Tomato 656 - - - -Farmland 767 a 753 a 6501 b 0202 lt005

1 SZC Shizongchang 2 SZC Xiayedi 3 SZC Mosuowan 4 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

32 Energy Balances Net Energy Ratio and Water Use Efficiency of Agricultural Production

The results of energy balances the net energy ratio and water use efficiency in three sub-oasesof Shihezi Oasis are presented in Table 4 and Table S4 For crop production the output energy(30869 GJha) energy balances (22147 GJha) and net energy ratio (539) in the XYD Oasis were thehighest among the three production systems the corresponding values of MSW Oasis were higherthan in the SZC Oasis respectively (Table 4) However the input energy (4258 GJha) in the MSWOasis was lower than in the other two oases (p lt 001) The net energy ratio (645) and energy balances(30946 MJha) of maize in the XYD Oasis were significantly higher than that of the SZC and MSWoases (Table 4) Alfalfa (1271) and maize (627) had higher net energy ratios than other crops (p lt 001)(Table S4) For livestock production the production of 1 kg CW of sheep in XYD Oasis resulted insignificantly higher energy balances than in the other two oases Similarly the net energy ratio (221) ofsheep in the XYD Oasis was significantly higher than that of the SZC and MSW oases (Table 4)

Table 4 Energy balances net energy ratio and water use efficiency of agricultural production in theShihezi sub-oases

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Energy inputCrop production (GJha)

Wheat (spring) 6319 a 6001 a 5539 b 3239 lt005Maize 5693 a 4217 c 5003 b 1913 lt0001Cotton 7691 a 5837 b 4112 c 5166 lt0001Alfalfa - 1909 2361 - -Grape - 3558 3754 - -

Tomato 4955 - - - -Farmland 6933 a 5847 b 4258 c 4416 lt0001

Livestock production (MJkg CW and milk)Sheep 1496 a 1096 b 1197 b 1225 lt005

Beef cattle 3884 a 3032 b 3001 b 5230 lt005Dairy cattle 144 a 130 b 132 b 0040 lt005

Energy output (GJha)Crop production (GJha)

Wheat (spring) 25582 b 26881 a 17436 c 14779 lt0001Maize 31363 36001 35024 7048 0317Cotton 9972 b 11649 a 11541 a 2709 lt005

Atmosphere 2020 11 781 9 of 17

Table 4 Cont

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Alfalfa - 27848 25597 -Grape - 10128 1019 - -

Tomato 20415 - - - -Farmland 23069 c 30869 a 24764 b 16517 lt0001

Livestock production (MJkg CW and milk)Sheep 2923 2926 2929 0010 035

Beef cattle 8704 8701 8702 0002 0561Dairy cattle 256 254 254 0001 0570

Energy balances (GJha)Crop production (GJha)

Wheat (spring) 19563 b 2058 a 11897 c 13699 lt0001Maize 25707 b 30946 a 26997 b 8519 lt005Cotton 2282 c 5812 b 7429 a 7598 lt0001Alfalfa - 25539 23636 - -Grape - 2657 26436 - -

Tomato 1546 - - - -Farmland 16112 c 22147 a 20795 b 11452 lt0001

Livestock production (MJkg CW and Milk)Sheep 1711 b 1831 a 1718 b 1035 lt005

Beef cattle 4813 4901 4822 0924 0125Dairy cattle 110 112 108 0051 0214

Net energy ratio 1

Crop productionWheat 405 a 427 a 315 b 0185 lt005Maize 609 c 645 a 620 b 0225 lt0001Cotton 130 c 203 b 281 a 0219 lt0001Alfalfa - 1206 1305 - -Grape - 847 804 - -

Tomato 412 - - - -Farmland 332 c 539 a 463 b 0625 lt0001

Livestock productionSheep 195 b 221 a 197 b 0167 lt005

Beef cattle 229 b 243 a 231 b 0256 lt005Dairy cattle 178 180 177 0004 0524

Water use efficiency 2

Crop production (MJm3)Wheat (spring) 2892 ab 3684 a 1861 b 3196 lt005

Maize 757 c 1442 a 1180 b 1102 lt0001Cotton 273 c 699 b 1179 a 1321 lt0001Alfalfa - 2785 2350 - -Grape - 2557 2438 - -

Tomato 2359 - - - -Farmland 990 b 1399 a 1415 a 0812 lt005

1 net energy ratio = output energyinput energy 2 water use efficiency Water use based on energy balances3 SZC Shizongchang 4 SZC Xiayedi 5 SZC Mosuowan 6 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

33 GHG Emissions and Carbon Economic Efficiency of Agriculture Production

Carbon indices to evaluate agriculture production are presented in Table 5 and Table S4 Carbonbalances (minus112 Mg CO2-eqha) of crop production in SZC Oasis were lower than in the other twooases (p lt 005) (Table 5) GHG emissions (1772 Mg CO2-eqha) from cotton production weresignificantly higher than for the other five crops (p lt 001) (Table S4) Alfalfa had higher carbon stocks(2376 Mg CO2-eqha) and carbon balances (1597 Mg CO2-eqha) than other crops (p lt 001) (Table S4)According to the price of agricultural products (Table S3) and carbon input for farm productionSZC Oasis had a lower carbon economic efficiency (034 yenkg CO2-eq) of crop production than the other

Atmosphere 2020 11 781 10 of 17

two oases (p lt 005) (Table 5) The carbon economic efficiency of maize (114 yenkg CO2-eq) and alfalfa(118 yenkg CO2-eq) were significantly higher than other crops (p lt 001) (Table S4)

Table 5 GHG emissions carbon stocks carbon balances and the carbon economic efficiency ofagricultural production in the Shihezi sub-oases

SZC 2 XYD 3 MSW 4 SED 5 p-Value

GHG emissionsCrop production (Mg CO2-eqha year)

Wheat (spring) 858 b 860 b 899 a 0065 lt005Maize 1245 a 1212 b 1209 b 0057 lt005Cotton 1772 1775 1769 0137 0981Alfalfa - 809 810 - -Grape - 1226 1219 - -

Tomato 1702 - - - -Farmland 1322 1294 1227 0377 0534

Livestock production (kg CO2-eqkg CW and milk)Sheep 923 a 835 ab 762 b 0305 0072

Beef cattle 2295 b 2419 a 2287 b 0237 lt005Dairy cattle 067 070 071 0013 0639

Carbon stocksCrop production (Mg CO2-eqha year)

Wheat (spring) 1044 b 1040 b 1086 a 0075 0069Maize 2352 a 2284 b 2283 b 0107 lt005Cotton 1313 1310 1311 0101 0995Alfalfa - 2383 2374 - -Grape - 1098 1100 - -

Tomato 1035 - - - -Farmland 1210 b 1594 a 1733 a 0582 lt0001

Livestock production (kg CO2-eqkg CW and milk)Sheep 106 a 176 ab 193 b 0061 0610

Beef cattle 357 322 354 0097 0287Dairy cattle 010 011 011 0003 0593

Carbon balancesCrop production (Mg CO2-eqha year)

Wheat (spring) 185 180 187 0012 0160Maize 1106 a 1072 b 1075 b 0050 lt005Cotton minus459 minus464 minus456 0037 0601Alfalfa - 1574 1563 - -Grape - minus128 minus118 - -

Tomato minus668 - - - -Farmland minus112 b 299 a 506 a 0798 lt005

Livestock production (kg CO2-eqkg CW and milk)Sheep minus763 b

minus660 ab minus569 a 0330 lt005Beef cattle minus1939 a

minus2097 b minus1932 a 0298 lt005Dairy cattle minus053 minus059 minus057 0011 0653

Carbon economic efficiency (yenkg CO2-eq)Crop production

Wheat 017 018 017 0001 0185Maize 116 117 114 0016 0802Cotton 070 072 070 0015 0872Alfalfa - 118 117 - -Grape - 041 042 - -

Tomato 032 - - - -Farmland 034 b 075 a 082 a 0042 lt0001

Livestock productionSheep 024 a 022 ab 020 b 0008 0063

Beef cattle 038 b 040 a 038 b 0004 lt005Dairy cattle 017 018 018 0609 0524

1 net energy ratio = output energyinput energy 2 SZC Shizongchang 3 SZC Xiayedi 4 SZC Mosuowan5 SED Standard error of differences a b and c represent means with different letters in a row differing significantly(p lt 005)

Atmosphere 2020 11 781 11 of 17

34 Water Use Efficiency Based on Energy

Water use and the water use efficiency of crop production in the Shihezi Oasis are presented inTables 3 and 4 Among the three sub-oases in the Shihezi Oasis the water use of crop production in theMSW Oasis is lower than the corresponding value of the SZC and XYD oases (p lt 005) Howeverthe water use efficiency of crop production in the SZC Oasis is lower than that of the XYD and MSWoases (p lt 005) The water use (4590 m3ha) for alfalfa production in the Shihezi Oasis is the lowestwith the highest water use efficiency (4582 MJm3) (Table S4)

35 Contribution of Carbon Emissions

To further illustrate the relationship between GHG emissions and other factors Figure 2 showsthe contribution of GHG emissions from inputs of crop production The major GHG emission sourceswithin the crop production system are fertilizer and irrigation

Figure 2 Total GHG emissions from crop production and the contribution of emission sources

36 Effect Analysis of Structural Equation Modelling (SEM)

The effect analysis of SEM is presented in Table S5 The path modes show that the direct andtotal effects of the livestock breeding structure on predicted variables (farm net income energyand carbon balances) are much stronger than other dependent variables (Figure 3a total effects = 0647Figure 3b total effects = 0898 Figure 3c total effects = 1091 Figure 3d total effects = 0980Figure 3e total effects = 0898 and Figure 3f total effects = 01091) Similarly the path modesshow that the indirect effects of water use efficiency on economy income energy and carbon balancesare much stronger than those of other variables (Figure 3a indirect effects = 0196 Figure 3bindirect effects = 0297 and Figure 3c indirect effects = 0430)

Atmosphere 2020 11 781 12 of 17

Figure 3 Path models showing the direct and indirect effects of predictor variables on farm net incomeenergy balances and carbon balances The path models with significant correlations are presentedas solid lines The values on solid lines represent standardized regression weights Interruptedlines indicate no significant correlation between two variables Black arrows indicate positiveeffects For each endogenous variable the relative amount of explained variance is given Shadingindicates the greatest positive direct effect indirect effect and total effect between dependent andindependent variables OtoD The distance from the oasis to the desert (km) SPD Soil particle diameter(microm) PS Planting structure (planting crop type) WUE Water use efficiency (MJm3) BS Livestockbreeding structure (breeding livestock category) ECO Net income (1000 yenha) EB Energy balance(GJha) CB The difference value of carbon stock minus GHG emissions from agricultural productioninputs (Mg CO2-eqha) and OtoM The distance from the oasis to the desert (km) χ2 Chi-squarep Probability level df Degrees of freedom n Sample size

4 Discussion

41 Energy Balances and Net Energy Ratio

The present energy balances of agricultural production in the Shihezi Oasis are comparable tothose published elsewhere in the world using the similar methodology of calculating the input andoutput energy values on farms For example the input energy of cotton production (5880 GJha)in the Shihezi Oasis is much higher than that (31237 GJha) in Iran [30] This difference refers tothe low energy input of weed controlling and harvesting operations using human labor instead ofapplying machinery in Iran Nevertheless Shihezirsquos input energy for maize production (4971 GJha) isclose to that reported in Iran (50458 GJha) due to similar intensive and high input crop productionsystems [31] However our output energy including grain straw and roots of maize production(34121 GJha) is much higher than that only related to grain estimated in Iran (134946 GJha) [30]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 6 of 17

Table 2 Factors used for the calculation of GHG emissions

Item Sub-Item Factors References

Emission Factors of GHG for Agricultural Production

Seed 1

(kg CO2-eqkg seed)

Wheat (spring) 0477 [18]Maize 385 [19]Cotton 2383 [18]Alfalfa 9643 [18]Grape 235 [2]

Tomato 163 [20]

Fertilizer(kg CO2-eqkg fertilizer)

N 638 [21]P 0733 [22]K 055 [22]

Soil emissions CO2 after N application 0633 [11]Soil emissions N2O after N application 6205 [23]

Pesticide(kg CO2-eqkg pesticide)

Herbicides 231 [5]Insecticides 187 [5]Fungicides 13933 [24]

Mulch (kg CO2-eqkg mulch) Plastic mulch 18993 [6]

Electricity (tCO2-eqkwh electricity) Electricityfor irrigation 0917 [25]

Fuel (kg CO2-eqL fuel) Diesel 2629 [6]

Tractor depreciation(kg CO2-eqyear)

Tractor 7810 1407 [26]Tractor 5560 049 [26]

Tractor 10021202 132 [26]Tractor 250 016 [26]

Harvester 1200 066 [26]Harvester 154 134 [26]

Feed processing(kg CO2-eqkg feed)

Maize 00102 [27]Soybean 01013 [27]Wheat 00319 [27]

CH4 emissions from entericfermentation

(kg CO2-eqheadyear)

Sheep 125 [11]Beef cattle 1175 [11]

Dairy cattle 1525 [11]CH4 emissions frommanure management

(kg CO2-eqheadyear)

Sheep 275 [11]Beef cattle 25 [11]

Dairy cattle 250 [11]N2O emissions frommanure managementkg CO2-eqheadyear)

Sheep 623 [11]Beef cattle 1204 [11]

Dairy cattle 1067 [11]1 Including seed production cleaning and packaging 2 Including exhaled carbon dioxide of adult labor

Carbon stocks of crop production are calculated using Equation (9) [28]

CScrop = CSgrain + CSstem + CSroot (9)

where CScrop CSgain CSstem and CSroot represent the unit area of carbon values accumulated in crops(kg CO2-eqha) grain (kg CO2-eqha) stems (kg CO2-eqha) and roots (kg CO2-eqha) respectively

Carbon balances of crop production are calculated as Equation (10)

CBcrop = CScrop minusCEcrop (10)

where CBcrop represents the unit area of carbon balances (kg CO2-eqha)The yearly GHG emissions from each livestock species are calculated using Equation (11)

CElivestock = (TCO2 f eed + TCO2drug + TCO2elec + TCO2coal + TCH4enteric+TCH4manure + TN2Omanure)CWlivestock

(11)

Atmosphere 2020 11 781 7 of 17

where CElivestock is the unit carcass (milk) weight of GHG emissions from livestock (kg CO2-eqkg CWand milk) TCO2 is the emissions of carbon dioxide TCH4 is the emissions of methane and TN2O is theemissions of nitrous oxide In regards to indexing enteric and manure are ruminant enteric fermentation(kg CO2-eqkg CW and milk) and manure management (kg CO2-eqkg CW and milk) respectively

The carbon stock and carbon balances of livestock production are calculated as the followingEquations (12) and (13) [29]

CSlivestock = (LW times 02)CWlivestock (12)

CBlivestock = CSlivestock minusCElivestock (13)

where CSlivestock is the carbon stock of livestock (kg CO2-eqkg CW and milk) and LW is the live weightof livestock CBlivestock is the carbon balance (kg CO2-eqkg CW and milk)

27 Calculation of Carbon Economic Efficiency

Based on emissions per one kilogram of carbon dioxide equivalence from agricultural productsthe total carbon economic efficiency associated with the mean market price of these products in 2015and 2016 (Table S3) is calculated using Equation (14) [28]

CEE =YPtimes PRICE

CE(14)

where CEE is the carbon economic efficiency (yenkg CO2-eq) YP is the yield of agricultural products(kg) PRICE is the price of agricultural products (yen) and CE is the GHG emissions from agriculturalproduction (kg CO2-eq)

28 Calculation of Water Use Efficiency

The analysis of energy balance per 1 cubic meter of water can find the relationship betweenirrigation and the net energy of crop production in the Shihezi Oasis The water use efficiency of cropproduction is calculated using Equation (15)

WUEcrop =EBcrop

WUcrop(15)

where WUEcrop EBcrop and WUcrop represent the water use efficiency of crops grown (MJm3)energy balances (MJha) and the water use of crops grown (m3ha) respectively

29 Statistical Analyses

We used the statistical program named Genstat170 (VSNI Corporation Hemel HempsteadUK) to analyze differences in energy indices (energy balances and net energy ratio) carbon indices(GHG emissions carbon stock carbon balances and carbon economic efficiency) water use and wateruse efficiency using inline linear models

3 Results

31 Yield and Water Use of Crop Production

The results of the yield and water use of crop production in three sub-oases of the Shihezi Oasisare presented in Table 3 The yields (kg DMha) of maize and cotton in SZC Oasis were significantlyhigher than in the other two oases (p lt 005) The water use for wheat (spring) and maize productionin SZC Oasis was higher than in the other two oases (p lt 005)

Atmosphere 2020 11 781 8 of 17

Table 3 Yield and water use of crop production in the Shihezi sub-oases

SZC 1 XYD 2 MSW 3 SED 4 p-Value

Crop products (Mg DMha)Wheat (spring) 1565 a 1644 a 1067 b 0379 lt005

Maize 6000 a 4545 b 4889 b 0218 lt005Cotton 1342 a 1568 b 1553 c 0157 lt005Alfalfa - 1481 1362 - -Grape - 3034 3067 - -

Tomato 8175 - - - -Water use (1000 m3ha)

Wheat (spring) 677 a 559 c 639 b 0176 lt0001Maize 906 a 759 b 7623 b 0244 lt005Cotton 832 a 823 a 630 b 033 lt005Alfalfa - 417 506 - -Grape - 739 596 - -

Tomato 656 - - - -Farmland 767 a 753 a 6501 b 0202 lt005

1 SZC Shizongchang 2 SZC Xiayedi 3 SZC Mosuowan 4 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

32 Energy Balances Net Energy Ratio and Water Use Efficiency of Agricultural Production

The results of energy balances the net energy ratio and water use efficiency in three sub-oasesof Shihezi Oasis are presented in Table 4 and Table S4 For crop production the output energy(30869 GJha) energy balances (22147 GJha) and net energy ratio (539) in the XYD Oasis were thehighest among the three production systems the corresponding values of MSW Oasis were higherthan in the SZC Oasis respectively (Table 4) However the input energy (4258 GJha) in the MSWOasis was lower than in the other two oases (p lt 001) The net energy ratio (645) and energy balances(30946 MJha) of maize in the XYD Oasis were significantly higher than that of the SZC and MSWoases (Table 4) Alfalfa (1271) and maize (627) had higher net energy ratios than other crops (p lt 001)(Table S4) For livestock production the production of 1 kg CW of sheep in XYD Oasis resulted insignificantly higher energy balances than in the other two oases Similarly the net energy ratio (221) ofsheep in the XYD Oasis was significantly higher than that of the SZC and MSW oases (Table 4)

Table 4 Energy balances net energy ratio and water use efficiency of agricultural production in theShihezi sub-oases

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Energy inputCrop production (GJha)

Wheat (spring) 6319 a 6001 a 5539 b 3239 lt005Maize 5693 a 4217 c 5003 b 1913 lt0001Cotton 7691 a 5837 b 4112 c 5166 lt0001Alfalfa - 1909 2361 - -Grape - 3558 3754 - -

Tomato 4955 - - - -Farmland 6933 a 5847 b 4258 c 4416 lt0001

Livestock production (MJkg CW and milk)Sheep 1496 a 1096 b 1197 b 1225 lt005

Beef cattle 3884 a 3032 b 3001 b 5230 lt005Dairy cattle 144 a 130 b 132 b 0040 lt005

Energy output (GJha)Crop production (GJha)

Wheat (spring) 25582 b 26881 a 17436 c 14779 lt0001Maize 31363 36001 35024 7048 0317Cotton 9972 b 11649 a 11541 a 2709 lt005

Atmosphere 2020 11 781 9 of 17

Table 4 Cont

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Alfalfa - 27848 25597 -Grape - 10128 1019 - -

Tomato 20415 - - - -Farmland 23069 c 30869 a 24764 b 16517 lt0001

Livestock production (MJkg CW and milk)Sheep 2923 2926 2929 0010 035

Beef cattle 8704 8701 8702 0002 0561Dairy cattle 256 254 254 0001 0570

Energy balances (GJha)Crop production (GJha)

Wheat (spring) 19563 b 2058 a 11897 c 13699 lt0001Maize 25707 b 30946 a 26997 b 8519 lt005Cotton 2282 c 5812 b 7429 a 7598 lt0001Alfalfa - 25539 23636 - -Grape - 2657 26436 - -

Tomato 1546 - - - -Farmland 16112 c 22147 a 20795 b 11452 lt0001

Livestock production (MJkg CW and Milk)Sheep 1711 b 1831 a 1718 b 1035 lt005

Beef cattle 4813 4901 4822 0924 0125Dairy cattle 110 112 108 0051 0214

Net energy ratio 1

Crop productionWheat 405 a 427 a 315 b 0185 lt005Maize 609 c 645 a 620 b 0225 lt0001Cotton 130 c 203 b 281 a 0219 lt0001Alfalfa - 1206 1305 - -Grape - 847 804 - -

Tomato 412 - - - -Farmland 332 c 539 a 463 b 0625 lt0001

Livestock productionSheep 195 b 221 a 197 b 0167 lt005

Beef cattle 229 b 243 a 231 b 0256 lt005Dairy cattle 178 180 177 0004 0524

Water use efficiency 2

Crop production (MJm3)Wheat (spring) 2892 ab 3684 a 1861 b 3196 lt005

Maize 757 c 1442 a 1180 b 1102 lt0001Cotton 273 c 699 b 1179 a 1321 lt0001Alfalfa - 2785 2350 - -Grape - 2557 2438 - -

Tomato 2359 - - - -Farmland 990 b 1399 a 1415 a 0812 lt005

1 net energy ratio = output energyinput energy 2 water use efficiency Water use based on energy balances3 SZC Shizongchang 4 SZC Xiayedi 5 SZC Mosuowan 6 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

33 GHG Emissions and Carbon Economic Efficiency of Agriculture Production

Carbon indices to evaluate agriculture production are presented in Table 5 and Table S4 Carbonbalances (minus112 Mg CO2-eqha) of crop production in SZC Oasis were lower than in the other twooases (p lt 005) (Table 5) GHG emissions (1772 Mg CO2-eqha) from cotton production weresignificantly higher than for the other five crops (p lt 001) (Table S4) Alfalfa had higher carbon stocks(2376 Mg CO2-eqha) and carbon balances (1597 Mg CO2-eqha) than other crops (p lt 001) (Table S4)According to the price of agricultural products (Table S3) and carbon input for farm productionSZC Oasis had a lower carbon economic efficiency (034 yenkg CO2-eq) of crop production than the other

Atmosphere 2020 11 781 10 of 17

two oases (p lt 005) (Table 5) The carbon economic efficiency of maize (114 yenkg CO2-eq) and alfalfa(118 yenkg CO2-eq) were significantly higher than other crops (p lt 001) (Table S4)

Table 5 GHG emissions carbon stocks carbon balances and the carbon economic efficiency ofagricultural production in the Shihezi sub-oases

SZC 2 XYD 3 MSW 4 SED 5 p-Value

GHG emissionsCrop production (Mg CO2-eqha year)

Wheat (spring) 858 b 860 b 899 a 0065 lt005Maize 1245 a 1212 b 1209 b 0057 lt005Cotton 1772 1775 1769 0137 0981Alfalfa - 809 810 - -Grape - 1226 1219 - -

Tomato 1702 - - - -Farmland 1322 1294 1227 0377 0534

Livestock production (kg CO2-eqkg CW and milk)Sheep 923 a 835 ab 762 b 0305 0072

Beef cattle 2295 b 2419 a 2287 b 0237 lt005Dairy cattle 067 070 071 0013 0639

Carbon stocksCrop production (Mg CO2-eqha year)

Wheat (spring) 1044 b 1040 b 1086 a 0075 0069Maize 2352 a 2284 b 2283 b 0107 lt005Cotton 1313 1310 1311 0101 0995Alfalfa - 2383 2374 - -Grape - 1098 1100 - -

Tomato 1035 - - - -Farmland 1210 b 1594 a 1733 a 0582 lt0001

Livestock production (kg CO2-eqkg CW and milk)Sheep 106 a 176 ab 193 b 0061 0610

Beef cattle 357 322 354 0097 0287Dairy cattle 010 011 011 0003 0593

Carbon balancesCrop production (Mg CO2-eqha year)

Wheat (spring) 185 180 187 0012 0160Maize 1106 a 1072 b 1075 b 0050 lt005Cotton minus459 minus464 minus456 0037 0601Alfalfa - 1574 1563 - -Grape - minus128 minus118 - -

Tomato minus668 - - - -Farmland minus112 b 299 a 506 a 0798 lt005

Livestock production (kg CO2-eqkg CW and milk)Sheep minus763 b

minus660 ab minus569 a 0330 lt005Beef cattle minus1939 a

minus2097 b minus1932 a 0298 lt005Dairy cattle minus053 minus059 minus057 0011 0653

Carbon economic efficiency (yenkg CO2-eq)Crop production

Wheat 017 018 017 0001 0185Maize 116 117 114 0016 0802Cotton 070 072 070 0015 0872Alfalfa - 118 117 - -Grape - 041 042 - -

Tomato 032 - - - -Farmland 034 b 075 a 082 a 0042 lt0001

Livestock productionSheep 024 a 022 ab 020 b 0008 0063

Beef cattle 038 b 040 a 038 b 0004 lt005Dairy cattle 017 018 018 0609 0524

1 net energy ratio = output energyinput energy 2 SZC Shizongchang 3 SZC Xiayedi 4 SZC Mosuowan5 SED Standard error of differences a b and c represent means with different letters in a row differing significantly(p lt 005)

Atmosphere 2020 11 781 11 of 17

34 Water Use Efficiency Based on Energy

Water use and the water use efficiency of crop production in the Shihezi Oasis are presented inTables 3 and 4 Among the three sub-oases in the Shihezi Oasis the water use of crop production in theMSW Oasis is lower than the corresponding value of the SZC and XYD oases (p lt 005) Howeverthe water use efficiency of crop production in the SZC Oasis is lower than that of the XYD and MSWoases (p lt 005) The water use (4590 m3ha) for alfalfa production in the Shihezi Oasis is the lowestwith the highest water use efficiency (4582 MJm3) (Table S4)

35 Contribution of Carbon Emissions

To further illustrate the relationship between GHG emissions and other factors Figure 2 showsthe contribution of GHG emissions from inputs of crop production The major GHG emission sourceswithin the crop production system are fertilizer and irrigation

Figure 2 Total GHG emissions from crop production and the contribution of emission sources

36 Effect Analysis of Structural Equation Modelling (SEM)

The effect analysis of SEM is presented in Table S5 The path modes show that the direct andtotal effects of the livestock breeding structure on predicted variables (farm net income energyand carbon balances) are much stronger than other dependent variables (Figure 3a total effects = 0647Figure 3b total effects = 0898 Figure 3c total effects = 1091 Figure 3d total effects = 0980Figure 3e total effects = 0898 and Figure 3f total effects = 01091) Similarly the path modesshow that the indirect effects of water use efficiency on economy income energy and carbon balancesare much stronger than those of other variables (Figure 3a indirect effects = 0196 Figure 3bindirect effects = 0297 and Figure 3c indirect effects = 0430)

Atmosphere 2020 11 781 12 of 17

Figure 3 Path models showing the direct and indirect effects of predictor variables on farm net incomeenergy balances and carbon balances The path models with significant correlations are presentedas solid lines The values on solid lines represent standardized regression weights Interruptedlines indicate no significant correlation between two variables Black arrows indicate positiveeffects For each endogenous variable the relative amount of explained variance is given Shadingindicates the greatest positive direct effect indirect effect and total effect between dependent andindependent variables OtoD The distance from the oasis to the desert (km) SPD Soil particle diameter(microm) PS Planting structure (planting crop type) WUE Water use efficiency (MJm3) BS Livestockbreeding structure (breeding livestock category) ECO Net income (1000 yenha) EB Energy balance(GJha) CB The difference value of carbon stock minus GHG emissions from agricultural productioninputs (Mg CO2-eqha) and OtoM The distance from the oasis to the desert (km) χ2 Chi-squarep Probability level df Degrees of freedom n Sample size

4 Discussion

41 Energy Balances and Net Energy Ratio

The present energy balances of agricultural production in the Shihezi Oasis are comparable tothose published elsewhere in the world using the similar methodology of calculating the input andoutput energy values on farms For example the input energy of cotton production (5880 GJha)in the Shihezi Oasis is much higher than that (31237 GJha) in Iran [30] This difference refers tothe low energy input of weed controlling and harvesting operations using human labor instead ofapplying machinery in Iran Nevertheless Shihezirsquos input energy for maize production (4971 GJha) isclose to that reported in Iran (50458 GJha) due to similar intensive and high input crop productionsystems [31] However our output energy including grain straw and roots of maize production(34121 GJha) is much higher than that only related to grain estimated in Iran (134946 GJha) [30]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 7 of 17

where CElivestock is the unit carcass (milk) weight of GHG emissions from livestock (kg CO2-eqkg CWand milk) TCO2 is the emissions of carbon dioxide TCH4 is the emissions of methane and TN2O is theemissions of nitrous oxide In regards to indexing enteric and manure are ruminant enteric fermentation(kg CO2-eqkg CW and milk) and manure management (kg CO2-eqkg CW and milk) respectively

The carbon stock and carbon balances of livestock production are calculated as the followingEquations (12) and (13) [29]

CSlivestock = (LW times 02)CWlivestock (12)

CBlivestock = CSlivestock minusCElivestock (13)

where CSlivestock is the carbon stock of livestock (kg CO2-eqkg CW and milk) and LW is the live weightof livestock CBlivestock is the carbon balance (kg CO2-eqkg CW and milk)

27 Calculation of Carbon Economic Efficiency

Based on emissions per one kilogram of carbon dioxide equivalence from agricultural productsthe total carbon economic efficiency associated with the mean market price of these products in 2015and 2016 (Table S3) is calculated using Equation (14) [28]

CEE =YPtimes PRICE

CE(14)

where CEE is the carbon economic efficiency (yenkg CO2-eq) YP is the yield of agricultural products(kg) PRICE is the price of agricultural products (yen) and CE is the GHG emissions from agriculturalproduction (kg CO2-eq)

28 Calculation of Water Use Efficiency

The analysis of energy balance per 1 cubic meter of water can find the relationship betweenirrigation and the net energy of crop production in the Shihezi Oasis The water use efficiency of cropproduction is calculated using Equation (15)

WUEcrop =EBcrop

WUcrop(15)

where WUEcrop EBcrop and WUcrop represent the water use efficiency of crops grown (MJm3)energy balances (MJha) and the water use of crops grown (m3ha) respectively

29 Statistical Analyses

We used the statistical program named Genstat170 (VSNI Corporation Hemel HempsteadUK) to analyze differences in energy indices (energy balances and net energy ratio) carbon indices(GHG emissions carbon stock carbon balances and carbon economic efficiency) water use and wateruse efficiency using inline linear models

3 Results

31 Yield and Water Use of Crop Production

The results of the yield and water use of crop production in three sub-oases of the Shihezi Oasisare presented in Table 3 The yields (kg DMha) of maize and cotton in SZC Oasis were significantlyhigher than in the other two oases (p lt 005) The water use for wheat (spring) and maize productionin SZC Oasis was higher than in the other two oases (p lt 005)

Atmosphere 2020 11 781 8 of 17

Table 3 Yield and water use of crop production in the Shihezi sub-oases

SZC 1 XYD 2 MSW 3 SED 4 p-Value

Crop products (Mg DMha)Wheat (spring) 1565 a 1644 a 1067 b 0379 lt005

Maize 6000 a 4545 b 4889 b 0218 lt005Cotton 1342 a 1568 b 1553 c 0157 lt005Alfalfa - 1481 1362 - -Grape - 3034 3067 - -

Tomato 8175 - - - -Water use (1000 m3ha)

Wheat (spring) 677 a 559 c 639 b 0176 lt0001Maize 906 a 759 b 7623 b 0244 lt005Cotton 832 a 823 a 630 b 033 lt005Alfalfa - 417 506 - -Grape - 739 596 - -

Tomato 656 - - - -Farmland 767 a 753 a 6501 b 0202 lt005

1 SZC Shizongchang 2 SZC Xiayedi 3 SZC Mosuowan 4 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

32 Energy Balances Net Energy Ratio and Water Use Efficiency of Agricultural Production

The results of energy balances the net energy ratio and water use efficiency in three sub-oasesof Shihezi Oasis are presented in Table 4 and Table S4 For crop production the output energy(30869 GJha) energy balances (22147 GJha) and net energy ratio (539) in the XYD Oasis were thehighest among the three production systems the corresponding values of MSW Oasis were higherthan in the SZC Oasis respectively (Table 4) However the input energy (4258 GJha) in the MSWOasis was lower than in the other two oases (p lt 001) The net energy ratio (645) and energy balances(30946 MJha) of maize in the XYD Oasis were significantly higher than that of the SZC and MSWoases (Table 4) Alfalfa (1271) and maize (627) had higher net energy ratios than other crops (p lt 001)(Table S4) For livestock production the production of 1 kg CW of sheep in XYD Oasis resulted insignificantly higher energy balances than in the other two oases Similarly the net energy ratio (221) ofsheep in the XYD Oasis was significantly higher than that of the SZC and MSW oases (Table 4)

Table 4 Energy balances net energy ratio and water use efficiency of agricultural production in theShihezi sub-oases

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Energy inputCrop production (GJha)

Wheat (spring) 6319 a 6001 a 5539 b 3239 lt005Maize 5693 a 4217 c 5003 b 1913 lt0001Cotton 7691 a 5837 b 4112 c 5166 lt0001Alfalfa - 1909 2361 - -Grape - 3558 3754 - -

Tomato 4955 - - - -Farmland 6933 a 5847 b 4258 c 4416 lt0001

Livestock production (MJkg CW and milk)Sheep 1496 a 1096 b 1197 b 1225 lt005

Beef cattle 3884 a 3032 b 3001 b 5230 lt005Dairy cattle 144 a 130 b 132 b 0040 lt005

Energy output (GJha)Crop production (GJha)

Wheat (spring) 25582 b 26881 a 17436 c 14779 lt0001Maize 31363 36001 35024 7048 0317Cotton 9972 b 11649 a 11541 a 2709 lt005

Atmosphere 2020 11 781 9 of 17

Table 4 Cont

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Alfalfa - 27848 25597 -Grape - 10128 1019 - -

Tomato 20415 - - - -Farmland 23069 c 30869 a 24764 b 16517 lt0001

Livestock production (MJkg CW and milk)Sheep 2923 2926 2929 0010 035

Beef cattle 8704 8701 8702 0002 0561Dairy cattle 256 254 254 0001 0570

Energy balances (GJha)Crop production (GJha)

Wheat (spring) 19563 b 2058 a 11897 c 13699 lt0001Maize 25707 b 30946 a 26997 b 8519 lt005Cotton 2282 c 5812 b 7429 a 7598 lt0001Alfalfa - 25539 23636 - -Grape - 2657 26436 - -

Tomato 1546 - - - -Farmland 16112 c 22147 a 20795 b 11452 lt0001

Livestock production (MJkg CW and Milk)Sheep 1711 b 1831 a 1718 b 1035 lt005

Beef cattle 4813 4901 4822 0924 0125Dairy cattle 110 112 108 0051 0214

Net energy ratio 1

Crop productionWheat 405 a 427 a 315 b 0185 lt005Maize 609 c 645 a 620 b 0225 lt0001Cotton 130 c 203 b 281 a 0219 lt0001Alfalfa - 1206 1305 - -Grape - 847 804 - -

Tomato 412 - - - -Farmland 332 c 539 a 463 b 0625 lt0001

Livestock productionSheep 195 b 221 a 197 b 0167 lt005

Beef cattle 229 b 243 a 231 b 0256 lt005Dairy cattle 178 180 177 0004 0524

Water use efficiency 2

Crop production (MJm3)Wheat (spring) 2892 ab 3684 a 1861 b 3196 lt005

Maize 757 c 1442 a 1180 b 1102 lt0001Cotton 273 c 699 b 1179 a 1321 lt0001Alfalfa - 2785 2350 - -Grape - 2557 2438 - -

Tomato 2359 - - - -Farmland 990 b 1399 a 1415 a 0812 lt005

1 net energy ratio = output energyinput energy 2 water use efficiency Water use based on energy balances3 SZC Shizongchang 4 SZC Xiayedi 5 SZC Mosuowan 6 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

33 GHG Emissions and Carbon Economic Efficiency of Agriculture Production

Carbon indices to evaluate agriculture production are presented in Table 5 and Table S4 Carbonbalances (minus112 Mg CO2-eqha) of crop production in SZC Oasis were lower than in the other twooases (p lt 005) (Table 5) GHG emissions (1772 Mg CO2-eqha) from cotton production weresignificantly higher than for the other five crops (p lt 001) (Table S4) Alfalfa had higher carbon stocks(2376 Mg CO2-eqha) and carbon balances (1597 Mg CO2-eqha) than other crops (p lt 001) (Table S4)According to the price of agricultural products (Table S3) and carbon input for farm productionSZC Oasis had a lower carbon economic efficiency (034 yenkg CO2-eq) of crop production than the other

Atmosphere 2020 11 781 10 of 17

two oases (p lt 005) (Table 5) The carbon economic efficiency of maize (114 yenkg CO2-eq) and alfalfa(118 yenkg CO2-eq) were significantly higher than other crops (p lt 001) (Table S4)

Table 5 GHG emissions carbon stocks carbon balances and the carbon economic efficiency ofagricultural production in the Shihezi sub-oases

SZC 2 XYD 3 MSW 4 SED 5 p-Value

GHG emissionsCrop production (Mg CO2-eqha year)

Wheat (spring) 858 b 860 b 899 a 0065 lt005Maize 1245 a 1212 b 1209 b 0057 lt005Cotton 1772 1775 1769 0137 0981Alfalfa - 809 810 - -Grape - 1226 1219 - -

Tomato 1702 - - - -Farmland 1322 1294 1227 0377 0534

Livestock production (kg CO2-eqkg CW and milk)Sheep 923 a 835 ab 762 b 0305 0072

Beef cattle 2295 b 2419 a 2287 b 0237 lt005Dairy cattle 067 070 071 0013 0639

Carbon stocksCrop production (Mg CO2-eqha year)

Wheat (spring) 1044 b 1040 b 1086 a 0075 0069Maize 2352 a 2284 b 2283 b 0107 lt005Cotton 1313 1310 1311 0101 0995Alfalfa - 2383 2374 - -Grape - 1098 1100 - -

Tomato 1035 - - - -Farmland 1210 b 1594 a 1733 a 0582 lt0001

Livestock production (kg CO2-eqkg CW and milk)Sheep 106 a 176 ab 193 b 0061 0610

Beef cattle 357 322 354 0097 0287Dairy cattle 010 011 011 0003 0593

Carbon balancesCrop production (Mg CO2-eqha year)

Wheat (spring) 185 180 187 0012 0160Maize 1106 a 1072 b 1075 b 0050 lt005Cotton minus459 minus464 minus456 0037 0601Alfalfa - 1574 1563 - -Grape - minus128 minus118 - -

Tomato minus668 - - - -Farmland minus112 b 299 a 506 a 0798 lt005

Livestock production (kg CO2-eqkg CW and milk)Sheep minus763 b

minus660 ab minus569 a 0330 lt005Beef cattle minus1939 a

minus2097 b minus1932 a 0298 lt005Dairy cattle minus053 minus059 minus057 0011 0653

Carbon economic efficiency (yenkg CO2-eq)Crop production

Wheat 017 018 017 0001 0185Maize 116 117 114 0016 0802Cotton 070 072 070 0015 0872Alfalfa - 118 117 - -Grape - 041 042 - -

Tomato 032 - - - -Farmland 034 b 075 a 082 a 0042 lt0001

Livestock productionSheep 024 a 022 ab 020 b 0008 0063

Beef cattle 038 b 040 a 038 b 0004 lt005Dairy cattle 017 018 018 0609 0524

1 net energy ratio = output energyinput energy 2 SZC Shizongchang 3 SZC Xiayedi 4 SZC Mosuowan5 SED Standard error of differences a b and c represent means with different letters in a row differing significantly(p lt 005)

Atmosphere 2020 11 781 11 of 17

34 Water Use Efficiency Based on Energy

Water use and the water use efficiency of crop production in the Shihezi Oasis are presented inTables 3 and 4 Among the three sub-oases in the Shihezi Oasis the water use of crop production in theMSW Oasis is lower than the corresponding value of the SZC and XYD oases (p lt 005) Howeverthe water use efficiency of crop production in the SZC Oasis is lower than that of the XYD and MSWoases (p lt 005) The water use (4590 m3ha) for alfalfa production in the Shihezi Oasis is the lowestwith the highest water use efficiency (4582 MJm3) (Table S4)

35 Contribution of Carbon Emissions

To further illustrate the relationship between GHG emissions and other factors Figure 2 showsthe contribution of GHG emissions from inputs of crop production The major GHG emission sourceswithin the crop production system are fertilizer and irrigation

Figure 2 Total GHG emissions from crop production and the contribution of emission sources

36 Effect Analysis of Structural Equation Modelling (SEM)

The effect analysis of SEM is presented in Table S5 The path modes show that the direct andtotal effects of the livestock breeding structure on predicted variables (farm net income energyand carbon balances) are much stronger than other dependent variables (Figure 3a total effects = 0647Figure 3b total effects = 0898 Figure 3c total effects = 1091 Figure 3d total effects = 0980Figure 3e total effects = 0898 and Figure 3f total effects = 01091) Similarly the path modesshow that the indirect effects of water use efficiency on economy income energy and carbon balancesare much stronger than those of other variables (Figure 3a indirect effects = 0196 Figure 3bindirect effects = 0297 and Figure 3c indirect effects = 0430)

Atmosphere 2020 11 781 12 of 17

Figure 3 Path models showing the direct and indirect effects of predictor variables on farm net incomeenergy balances and carbon balances The path models with significant correlations are presentedas solid lines The values on solid lines represent standardized regression weights Interruptedlines indicate no significant correlation between two variables Black arrows indicate positiveeffects For each endogenous variable the relative amount of explained variance is given Shadingindicates the greatest positive direct effect indirect effect and total effect between dependent andindependent variables OtoD The distance from the oasis to the desert (km) SPD Soil particle diameter(microm) PS Planting structure (planting crop type) WUE Water use efficiency (MJm3) BS Livestockbreeding structure (breeding livestock category) ECO Net income (1000 yenha) EB Energy balance(GJha) CB The difference value of carbon stock minus GHG emissions from agricultural productioninputs (Mg CO2-eqha) and OtoM The distance from the oasis to the desert (km) χ2 Chi-squarep Probability level df Degrees of freedom n Sample size

4 Discussion

41 Energy Balances and Net Energy Ratio

The present energy balances of agricultural production in the Shihezi Oasis are comparable tothose published elsewhere in the world using the similar methodology of calculating the input andoutput energy values on farms For example the input energy of cotton production (5880 GJha)in the Shihezi Oasis is much higher than that (31237 GJha) in Iran [30] This difference refers tothe low energy input of weed controlling and harvesting operations using human labor instead ofapplying machinery in Iran Nevertheless Shihezirsquos input energy for maize production (4971 GJha) isclose to that reported in Iran (50458 GJha) due to similar intensive and high input crop productionsystems [31] However our output energy including grain straw and roots of maize production(34121 GJha) is much higher than that only related to grain estimated in Iran (134946 GJha) [30]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 8 of 17

Table 3 Yield and water use of crop production in the Shihezi sub-oases

SZC 1 XYD 2 MSW 3 SED 4 p-Value

Crop products (Mg DMha)Wheat (spring) 1565 a 1644 a 1067 b 0379 lt005

Maize 6000 a 4545 b 4889 b 0218 lt005Cotton 1342 a 1568 b 1553 c 0157 lt005Alfalfa - 1481 1362 - -Grape - 3034 3067 - -

Tomato 8175 - - - -Water use (1000 m3ha)

Wheat (spring) 677 a 559 c 639 b 0176 lt0001Maize 906 a 759 b 7623 b 0244 lt005Cotton 832 a 823 a 630 b 033 lt005Alfalfa - 417 506 - -Grape - 739 596 - -

Tomato 656 - - - -Farmland 767 a 753 a 6501 b 0202 lt005

1 SZC Shizongchang 2 SZC Xiayedi 3 SZC Mosuowan 4 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

32 Energy Balances Net Energy Ratio and Water Use Efficiency of Agricultural Production

The results of energy balances the net energy ratio and water use efficiency in three sub-oasesof Shihezi Oasis are presented in Table 4 and Table S4 For crop production the output energy(30869 GJha) energy balances (22147 GJha) and net energy ratio (539) in the XYD Oasis were thehighest among the three production systems the corresponding values of MSW Oasis were higherthan in the SZC Oasis respectively (Table 4) However the input energy (4258 GJha) in the MSWOasis was lower than in the other two oases (p lt 001) The net energy ratio (645) and energy balances(30946 MJha) of maize in the XYD Oasis were significantly higher than that of the SZC and MSWoases (Table 4) Alfalfa (1271) and maize (627) had higher net energy ratios than other crops (p lt 001)(Table S4) For livestock production the production of 1 kg CW of sheep in XYD Oasis resulted insignificantly higher energy balances than in the other two oases Similarly the net energy ratio (221) ofsheep in the XYD Oasis was significantly higher than that of the SZC and MSW oases (Table 4)

Table 4 Energy balances net energy ratio and water use efficiency of agricultural production in theShihezi sub-oases

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Energy inputCrop production (GJha)

Wheat (spring) 6319 a 6001 a 5539 b 3239 lt005Maize 5693 a 4217 c 5003 b 1913 lt0001Cotton 7691 a 5837 b 4112 c 5166 lt0001Alfalfa - 1909 2361 - -Grape - 3558 3754 - -

Tomato 4955 - - - -Farmland 6933 a 5847 b 4258 c 4416 lt0001

Livestock production (MJkg CW and milk)Sheep 1496 a 1096 b 1197 b 1225 lt005

Beef cattle 3884 a 3032 b 3001 b 5230 lt005Dairy cattle 144 a 130 b 132 b 0040 lt005

Energy output (GJha)Crop production (GJha)

Wheat (spring) 25582 b 26881 a 17436 c 14779 lt0001Maize 31363 36001 35024 7048 0317Cotton 9972 b 11649 a 11541 a 2709 lt005

Atmosphere 2020 11 781 9 of 17

Table 4 Cont

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Alfalfa - 27848 25597 -Grape - 10128 1019 - -

Tomato 20415 - - - -Farmland 23069 c 30869 a 24764 b 16517 lt0001

Livestock production (MJkg CW and milk)Sheep 2923 2926 2929 0010 035

Beef cattle 8704 8701 8702 0002 0561Dairy cattle 256 254 254 0001 0570

Energy balances (GJha)Crop production (GJha)

Wheat (spring) 19563 b 2058 a 11897 c 13699 lt0001Maize 25707 b 30946 a 26997 b 8519 lt005Cotton 2282 c 5812 b 7429 a 7598 lt0001Alfalfa - 25539 23636 - -Grape - 2657 26436 - -

Tomato 1546 - - - -Farmland 16112 c 22147 a 20795 b 11452 lt0001

Livestock production (MJkg CW and Milk)Sheep 1711 b 1831 a 1718 b 1035 lt005

Beef cattle 4813 4901 4822 0924 0125Dairy cattle 110 112 108 0051 0214

Net energy ratio 1

Crop productionWheat 405 a 427 a 315 b 0185 lt005Maize 609 c 645 a 620 b 0225 lt0001Cotton 130 c 203 b 281 a 0219 lt0001Alfalfa - 1206 1305 - -Grape - 847 804 - -

Tomato 412 - - - -Farmland 332 c 539 a 463 b 0625 lt0001

Livestock productionSheep 195 b 221 a 197 b 0167 lt005

Beef cattle 229 b 243 a 231 b 0256 lt005Dairy cattle 178 180 177 0004 0524

Water use efficiency 2

Crop production (MJm3)Wheat (spring) 2892 ab 3684 a 1861 b 3196 lt005

Maize 757 c 1442 a 1180 b 1102 lt0001Cotton 273 c 699 b 1179 a 1321 lt0001Alfalfa - 2785 2350 - -Grape - 2557 2438 - -

Tomato 2359 - - - -Farmland 990 b 1399 a 1415 a 0812 lt005

1 net energy ratio = output energyinput energy 2 water use efficiency Water use based on energy balances3 SZC Shizongchang 4 SZC Xiayedi 5 SZC Mosuowan 6 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

33 GHG Emissions and Carbon Economic Efficiency of Agriculture Production

Carbon indices to evaluate agriculture production are presented in Table 5 and Table S4 Carbonbalances (minus112 Mg CO2-eqha) of crop production in SZC Oasis were lower than in the other twooases (p lt 005) (Table 5) GHG emissions (1772 Mg CO2-eqha) from cotton production weresignificantly higher than for the other five crops (p lt 001) (Table S4) Alfalfa had higher carbon stocks(2376 Mg CO2-eqha) and carbon balances (1597 Mg CO2-eqha) than other crops (p lt 001) (Table S4)According to the price of agricultural products (Table S3) and carbon input for farm productionSZC Oasis had a lower carbon economic efficiency (034 yenkg CO2-eq) of crop production than the other

Atmosphere 2020 11 781 10 of 17

two oases (p lt 005) (Table 5) The carbon economic efficiency of maize (114 yenkg CO2-eq) and alfalfa(118 yenkg CO2-eq) were significantly higher than other crops (p lt 001) (Table S4)

Table 5 GHG emissions carbon stocks carbon balances and the carbon economic efficiency ofagricultural production in the Shihezi sub-oases

SZC 2 XYD 3 MSW 4 SED 5 p-Value

GHG emissionsCrop production (Mg CO2-eqha year)

Wheat (spring) 858 b 860 b 899 a 0065 lt005Maize 1245 a 1212 b 1209 b 0057 lt005Cotton 1772 1775 1769 0137 0981Alfalfa - 809 810 - -Grape - 1226 1219 - -

Tomato 1702 - - - -Farmland 1322 1294 1227 0377 0534

Livestock production (kg CO2-eqkg CW and milk)Sheep 923 a 835 ab 762 b 0305 0072

Beef cattle 2295 b 2419 a 2287 b 0237 lt005Dairy cattle 067 070 071 0013 0639

Carbon stocksCrop production (Mg CO2-eqha year)

Wheat (spring) 1044 b 1040 b 1086 a 0075 0069Maize 2352 a 2284 b 2283 b 0107 lt005Cotton 1313 1310 1311 0101 0995Alfalfa - 2383 2374 - -Grape - 1098 1100 - -

Tomato 1035 - - - -Farmland 1210 b 1594 a 1733 a 0582 lt0001

Livestock production (kg CO2-eqkg CW and milk)Sheep 106 a 176 ab 193 b 0061 0610

Beef cattle 357 322 354 0097 0287Dairy cattle 010 011 011 0003 0593

Carbon balancesCrop production (Mg CO2-eqha year)

Wheat (spring) 185 180 187 0012 0160Maize 1106 a 1072 b 1075 b 0050 lt005Cotton minus459 minus464 minus456 0037 0601Alfalfa - 1574 1563 - -Grape - minus128 minus118 - -

Tomato minus668 - - - -Farmland minus112 b 299 a 506 a 0798 lt005

Livestock production (kg CO2-eqkg CW and milk)Sheep minus763 b

minus660 ab minus569 a 0330 lt005Beef cattle minus1939 a

minus2097 b minus1932 a 0298 lt005Dairy cattle minus053 minus059 minus057 0011 0653

Carbon economic efficiency (yenkg CO2-eq)Crop production

Wheat 017 018 017 0001 0185Maize 116 117 114 0016 0802Cotton 070 072 070 0015 0872Alfalfa - 118 117 - -Grape - 041 042 - -

Tomato 032 - - - -Farmland 034 b 075 a 082 a 0042 lt0001

Livestock productionSheep 024 a 022 ab 020 b 0008 0063

Beef cattle 038 b 040 a 038 b 0004 lt005Dairy cattle 017 018 018 0609 0524

1 net energy ratio = output energyinput energy 2 SZC Shizongchang 3 SZC Xiayedi 4 SZC Mosuowan5 SED Standard error of differences a b and c represent means with different letters in a row differing significantly(p lt 005)

Atmosphere 2020 11 781 11 of 17

34 Water Use Efficiency Based on Energy

Water use and the water use efficiency of crop production in the Shihezi Oasis are presented inTables 3 and 4 Among the three sub-oases in the Shihezi Oasis the water use of crop production in theMSW Oasis is lower than the corresponding value of the SZC and XYD oases (p lt 005) Howeverthe water use efficiency of crop production in the SZC Oasis is lower than that of the XYD and MSWoases (p lt 005) The water use (4590 m3ha) for alfalfa production in the Shihezi Oasis is the lowestwith the highest water use efficiency (4582 MJm3) (Table S4)

35 Contribution of Carbon Emissions

To further illustrate the relationship between GHG emissions and other factors Figure 2 showsthe contribution of GHG emissions from inputs of crop production The major GHG emission sourceswithin the crop production system are fertilizer and irrigation

Figure 2 Total GHG emissions from crop production and the contribution of emission sources

36 Effect Analysis of Structural Equation Modelling (SEM)

The effect analysis of SEM is presented in Table S5 The path modes show that the direct andtotal effects of the livestock breeding structure on predicted variables (farm net income energyand carbon balances) are much stronger than other dependent variables (Figure 3a total effects = 0647Figure 3b total effects = 0898 Figure 3c total effects = 1091 Figure 3d total effects = 0980Figure 3e total effects = 0898 and Figure 3f total effects = 01091) Similarly the path modesshow that the indirect effects of water use efficiency on economy income energy and carbon balancesare much stronger than those of other variables (Figure 3a indirect effects = 0196 Figure 3bindirect effects = 0297 and Figure 3c indirect effects = 0430)

Atmosphere 2020 11 781 12 of 17

Figure 3 Path models showing the direct and indirect effects of predictor variables on farm net incomeenergy balances and carbon balances The path models with significant correlations are presentedas solid lines The values on solid lines represent standardized regression weights Interruptedlines indicate no significant correlation between two variables Black arrows indicate positiveeffects For each endogenous variable the relative amount of explained variance is given Shadingindicates the greatest positive direct effect indirect effect and total effect between dependent andindependent variables OtoD The distance from the oasis to the desert (km) SPD Soil particle diameter(microm) PS Planting structure (planting crop type) WUE Water use efficiency (MJm3) BS Livestockbreeding structure (breeding livestock category) ECO Net income (1000 yenha) EB Energy balance(GJha) CB The difference value of carbon stock minus GHG emissions from agricultural productioninputs (Mg CO2-eqha) and OtoM The distance from the oasis to the desert (km) χ2 Chi-squarep Probability level df Degrees of freedom n Sample size

4 Discussion

41 Energy Balances and Net Energy Ratio

The present energy balances of agricultural production in the Shihezi Oasis are comparable tothose published elsewhere in the world using the similar methodology of calculating the input andoutput energy values on farms For example the input energy of cotton production (5880 GJha)in the Shihezi Oasis is much higher than that (31237 GJha) in Iran [30] This difference refers tothe low energy input of weed controlling and harvesting operations using human labor instead ofapplying machinery in Iran Nevertheless Shihezirsquos input energy for maize production (4971 GJha) isclose to that reported in Iran (50458 GJha) due to similar intensive and high input crop productionsystems [31] However our output energy including grain straw and roots of maize production(34121 GJha) is much higher than that only related to grain estimated in Iran (134946 GJha) [30]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 9 of 17

Table 4 Cont

SZC 3 XYD 4 MSW 5 SED 6 p-Value

Alfalfa - 27848 25597 -Grape - 10128 1019 - -

Tomato 20415 - - - -Farmland 23069 c 30869 a 24764 b 16517 lt0001

Livestock production (MJkg CW and milk)Sheep 2923 2926 2929 0010 035

Beef cattle 8704 8701 8702 0002 0561Dairy cattle 256 254 254 0001 0570

Energy balances (GJha)Crop production (GJha)

Wheat (spring) 19563 b 2058 a 11897 c 13699 lt0001Maize 25707 b 30946 a 26997 b 8519 lt005Cotton 2282 c 5812 b 7429 a 7598 lt0001Alfalfa - 25539 23636 - -Grape - 2657 26436 - -

Tomato 1546 - - - -Farmland 16112 c 22147 a 20795 b 11452 lt0001

Livestock production (MJkg CW and Milk)Sheep 1711 b 1831 a 1718 b 1035 lt005

Beef cattle 4813 4901 4822 0924 0125Dairy cattle 110 112 108 0051 0214

Net energy ratio 1

Crop productionWheat 405 a 427 a 315 b 0185 lt005Maize 609 c 645 a 620 b 0225 lt0001Cotton 130 c 203 b 281 a 0219 lt0001Alfalfa - 1206 1305 - -Grape - 847 804 - -

Tomato 412 - - - -Farmland 332 c 539 a 463 b 0625 lt0001

Livestock productionSheep 195 b 221 a 197 b 0167 lt005

Beef cattle 229 b 243 a 231 b 0256 lt005Dairy cattle 178 180 177 0004 0524

Water use efficiency 2

Crop production (MJm3)Wheat (spring) 2892 ab 3684 a 1861 b 3196 lt005

Maize 757 c 1442 a 1180 b 1102 lt0001Cotton 273 c 699 b 1179 a 1321 lt0001Alfalfa - 2785 2350 - -Grape - 2557 2438 - -

Tomato 2359 - - - -Farmland 990 b 1399 a 1415 a 0812 lt005

1 net energy ratio = output energyinput energy 2 water use efficiency Water use based on energy balances3 SZC Shizongchang 4 SZC Xiayedi 5 SZC Mosuowan 6 SED Standard error of differences a b and c representmeans with different letters in a row differing significantly (p lt 005)

33 GHG Emissions and Carbon Economic Efficiency of Agriculture Production

Carbon indices to evaluate agriculture production are presented in Table 5 and Table S4 Carbonbalances (minus112 Mg CO2-eqha) of crop production in SZC Oasis were lower than in the other twooases (p lt 005) (Table 5) GHG emissions (1772 Mg CO2-eqha) from cotton production weresignificantly higher than for the other five crops (p lt 001) (Table S4) Alfalfa had higher carbon stocks(2376 Mg CO2-eqha) and carbon balances (1597 Mg CO2-eqha) than other crops (p lt 001) (Table S4)According to the price of agricultural products (Table S3) and carbon input for farm productionSZC Oasis had a lower carbon economic efficiency (034 yenkg CO2-eq) of crop production than the other

Atmosphere 2020 11 781 10 of 17

two oases (p lt 005) (Table 5) The carbon economic efficiency of maize (114 yenkg CO2-eq) and alfalfa(118 yenkg CO2-eq) were significantly higher than other crops (p lt 001) (Table S4)

Table 5 GHG emissions carbon stocks carbon balances and the carbon economic efficiency ofagricultural production in the Shihezi sub-oases

SZC 2 XYD 3 MSW 4 SED 5 p-Value

GHG emissionsCrop production (Mg CO2-eqha year)

Wheat (spring) 858 b 860 b 899 a 0065 lt005Maize 1245 a 1212 b 1209 b 0057 lt005Cotton 1772 1775 1769 0137 0981Alfalfa - 809 810 - -Grape - 1226 1219 - -

Tomato 1702 - - - -Farmland 1322 1294 1227 0377 0534

Livestock production (kg CO2-eqkg CW and milk)Sheep 923 a 835 ab 762 b 0305 0072

Beef cattle 2295 b 2419 a 2287 b 0237 lt005Dairy cattle 067 070 071 0013 0639

Carbon stocksCrop production (Mg CO2-eqha year)

Wheat (spring) 1044 b 1040 b 1086 a 0075 0069Maize 2352 a 2284 b 2283 b 0107 lt005Cotton 1313 1310 1311 0101 0995Alfalfa - 2383 2374 - -Grape - 1098 1100 - -

Tomato 1035 - - - -Farmland 1210 b 1594 a 1733 a 0582 lt0001

Livestock production (kg CO2-eqkg CW and milk)Sheep 106 a 176 ab 193 b 0061 0610

Beef cattle 357 322 354 0097 0287Dairy cattle 010 011 011 0003 0593

Carbon balancesCrop production (Mg CO2-eqha year)

Wheat (spring) 185 180 187 0012 0160Maize 1106 a 1072 b 1075 b 0050 lt005Cotton minus459 minus464 minus456 0037 0601Alfalfa - 1574 1563 - -Grape - minus128 minus118 - -

Tomato minus668 - - - -Farmland minus112 b 299 a 506 a 0798 lt005

Livestock production (kg CO2-eqkg CW and milk)Sheep minus763 b

minus660 ab minus569 a 0330 lt005Beef cattle minus1939 a

minus2097 b minus1932 a 0298 lt005Dairy cattle minus053 minus059 minus057 0011 0653

Carbon economic efficiency (yenkg CO2-eq)Crop production

Wheat 017 018 017 0001 0185Maize 116 117 114 0016 0802Cotton 070 072 070 0015 0872Alfalfa - 118 117 - -Grape - 041 042 - -

Tomato 032 - - - -Farmland 034 b 075 a 082 a 0042 lt0001

Livestock productionSheep 024 a 022 ab 020 b 0008 0063

Beef cattle 038 b 040 a 038 b 0004 lt005Dairy cattle 017 018 018 0609 0524

1 net energy ratio = output energyinput energy 2 SZC Shizongchang 3 SZC Xiayedi 4 SZC Mosuowan5 SED Standard error of differences a b and c represent means with different letters in a row differing significantly(p lt 005)

Atmosphere 2020 11 781 11 of 17

34 Water Use Efficiency Based on Energy

Water use and the water use efficiency of crop production in the Shihezi Oasis are presented inTables 3 and 4 Among the three sub-oases in the Shihezi Oasis the water use of crop production in theMSW Oasis is lower than the corresponding value of the SZC and XYD oases (p lt 005) Howeverthe water use efficiency of crop production in the SZC Oasis is lower than that of the XYD and MSWoases (p lt 005) The water use (4590 m3ha) for alfalfa production in the Shihezi Oasis is the lowestwith the highest water use efficiency (4582 MJm3) (Table S4)

35 Contribution of Carbon Emissions

To further illustrate the relationship between GHG emissions and other factors Figure 2 showsthe contribution of GHG emissions from inputs of crop production The major GHG emission sourceswithin the crop production system are fertilizer and irrigation

Figure 2 Total GHG emissions from crop production and the contribution of emission sources

36 Effect Analysis of Structural Equation Modelling (SEM)

The effect analysis of SEM is presented in Table S5 The path modes show that the direct andtotal effects of the livestock breeding structure on predicted variables (farm net income energyand carbon balances) are much stronger than other dependent variables (Figure 3a total effects = 0647Figure 3b total effects = 0898 Figure 3c total effects = 1091 Figure 3d total effects = 0980Figure 3e total effects = 0898 and Figure 3f total effects = 01091) Similarly the path modesshow that the indirect effects of water use efficiency on economy income energy and carbon balancesare much stronger than those of other variables (Figure 3a indirect effects = 0196 Figure 3bindirect effects = 0297 and Figure 3c indirect effects = 0430)

Atmosphere 2020 11 781 12 of 17

Figure 3 Path models showing the direct and indirect effects of predictor variables on farm net incomeenergy balances and carbon balances The path models with significant correlations are presentedas solid lines The values on solid lines represent standardized regression weights Interruptedlines indicate no significant correlation between two variables Black arrows indicate positiveeffects For each endogenous variable the relative amount of explained variance is given Shadingindicates the greatest positive direct effect indirect effect and total effect between dependent andindependent variables OtoD The distance from the oasis to the desert (km) SPD Soil particle diameter(microm) PS Planting structure (planting crop type) WUE Water use efficiency (MJm3) BS Livestockbreeding structure (breeding livestock category) ECO Net income (1000 yenha) EB Energy balance(GJha) CB The difference value of carbon stock minus GHG emissions from agricultural productioninputs (Mg CO2-eqha) and OtoM The distance from the oasis to the desert (km) χ2 Chi-squarep Probability level df Degrees of freedom n Sample size

4 Discussion

41 Energy Balances and Net Energy Ratio

The present energy balances of agricultural production in the Shihezi Oasis are comparable tothose published elsewhere in the world using the similar methodology of calculating the input andoutput energy values on farms For example the input energy of cotton production (5880 GJha)in the Shihezi Oasis is much higher than that (31237 GJha) in Iran [30] This difference refers tothe low energy input of weed controlling and harvesting operations using human labor instead ofapplying machinery in Iran Nevertheless Shihezirsquos input energy for maize production (4971 GJha) isclose to that reported in Iran (50458 GJha) due to similar intensive and high input crop productionsystems [31] However our output energy including grain straw and roots of maize production(34121 GJha) is much higher than that only related to grain estimated in Iran (134946 GJha) [30]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 10 of 17

two oases (p lt 005) (Table 5) The carbon economic efficiency of maize (114 yenkg CO2-eq) and alfalfa(118 yenkg CO2-eq) were significantly higher than other crops (p lt 001) (Table S4)

Table 5 GHG emissions carbon stocks carbon balances and the carbon economic efficiency ofagricultural production in the Shihezi sub-oases

SZC 2 XYD 3 MSW 4 SED 5 p-Value

GHG emissionsCrop production (Mg CO2-eqha year)

Wheat (spring) 858 b 860 b 899 a 0065 lt005Maize 1245 a 1212 b 1209 b 0057 lt005Cotton 1772 1775 1769 0137 0981Alfalfa - 809 810 - -Grape - 1226 1219 - -

Tomato 1702 - - - -Farmland 1322 1294 1227 0377 0534

Livestock production (kg CO2-eqkg CW and milk)Sheep 923 a 835 ab 762 b 0305 0072

Beef cattle 2295 b 2419 a 2287 b 0237 lt005Dairy cattle 067 070 071 0013 0639

Carbon stocksCrop production (Mg CO2-eqha year)

Wheat (spring) 1044 b 1040 b 1086 a 0075 0069Maize 2352 a 2284 b 2283 b 0107 lt005Cotton 1313 1310 1311 0101 0995Alfalfa - 2383 2374 - -Grape - 1098 1100 - -

Tomato 1035 - - - -Farmland 1210 b 1594 a 1733 a 0582 lt0001

Livestock production (kg CO2-eqkg CW and milk)Sheep 106 a 176 ab 193 b 0061 0610

Beef cattle 357 322 354 0097 0287Dairy cattle 010 011 011 0003 0593

Carbon balancesCrop production (Mg CO2-eqha year)

Wheat (spring) 185 180 187 0012 0160Maize 1106 a 1072 b 1075 b 0050 lt005Cotton minus459 minus464 minus456 0037 0601Alfalfa - 1574 1563 - -Grape - minus128 minus118 - -

Tomato minus668 - - - -Farmland minus112 b 299 a 506 a 0798 lt005

Livestock production (kg CO2-eqkg CW and milk)Sheep minus763 b

minus660 ab minus569 a 0330 lt005Beef cattle minus1939 a

minus2097 b minus1932 a 0298 lt005Dairy cattle minus053 minus059 minus057 0011 0653

Carbon economic efficiency (yenkg CO2-eq)Crop production

Wheat 017 018 017 0001 0185Maize 116 117 114 0016 0802Cotton 070 072 070 0015 0872Alfalfa - 118 117 - -Grape - 041 042 - -

Tomato 032 - - - -Farmland 034 b 075 a 082 a 0042 lt0001

Livestock productionSheep 024 a 022 ab 020 b 0008 0063

Beef cattle 038 b 040 a 038 b 0004 lt005Dairy cattle 017 018 018 0609 0524

1 net energy ratio = output energyinput energy 2 SZC Shizongchang 3 SZC Xiayedi 4 SZC Mosuowan5 SED Standard error of differences a b and c represent means with different letters in a row differing significantly(p lt 005)

Atmosphere 2020 11 781 11 of 17

34 Water Use Efficiency Based on Energy

Water use and the water use efficiency of crop production in the Shihezi Oasis are presented inTables 3 and 4 Among the three sub-oases in the Shihezi Oasis the water use of crop production in theMSW Oasis is lower than the corresponding value of the SZC and XYD oases (p lt 005) Howeverthe water use efficiency of crop production in the SZC Oasis is lower than that of the XYD and MSWoases (p lt 005) The water use (4590 m3ha) for alfalfa production in the Shihezi Oasis is the lowestwith the highest water use efficiency (4582 MJm3) (Table S4)

35 Contribution of Carbon Emissions

To further illustrate the relationship between GHG emissions and other factors Figure 2 showsthe contribution of GHG emissions from inputs of crop production The major GHG emission sourceswithin the crop production system are fertilizer and irrigation

Figure 2 Total GHG emissions from crop production and the contribution of emission sources

36 Effect Analysis of Structural Equation Modelling (SEM)

The effect analysis of SEM is presented in Table S5 The path modes show that the direct andtotal effects of the livestock breeding structure on predicted variables (farm net income energyand carbon balances) are much stronger than other dependent variables (Figure 3a total effects = 0647Figure 3b total effects = 0898 Figure 3c total effects = 1091 Figure 3d total effects = 0980Figure 3e total effects = 0898 and Figure 3f total effects = 01091) Similarly the path modesshow that the indirect effects of water use efficiency on economy income energy and carbon balancesare much stronger than those of other variables (Figure 3a indirect effects = 0196 Figure 3bindirect effects = 0297 and Figure 3c indirect effects = 0430)

Atmosphere 2020 11 781 12 of 17

Figure 3 Path models showing the direct and indirect effects of predictor variables on farm net incomeenergy balances and carbon balances The path models with significant correlations are presentedas solid lines The values on solid lines represent standardized regression weights Interruptedlines indicate no significant correlation between two variables Black arrows indicate positiveeffects For each endogenous variable the relative amount of explained variance is given Shadingindicates the greatest positive direct effect indirect effect and total effect between dependent andindependent variables OtoD The distance from the oasis to the desert (km) SPD Soil particle diameter(microm) PS Planting structure (planting crop type) WUE Water use efficiency (MJm3) BS Livestockbreeding structure (breeding livestock category) ECO Net income (1000 yenha) EB Energy balance(GJha) CB The difference value of carbon stock minus GHG emissions from agricultural productioninputs (Mg CO2-eqha) and OtoM The distance from the oasis to the desert (km) χ2 Chi-squarep Probability level df Degrees of freedom n Sample size

4 Discussion

41 Energy Balances and Net Energy Ratio

The present energy balances of agricultural production in the Shihezi Oasis are comparable tothose published elsewhere in the world using the similar methodology of calculating the input andoutput energy values on farms For example the input energy of cotton production (5880 GJha)in the Shihezi Oasis is much higher than that (31237 GJha) in Iran [30] This difference refers tothe low energy input of weed controlling and harvesting operations using human labor instead ofapplying machinery in Iran Nevertheless Shihezirsquos input energy for maize production (4971 GJha) isclose to that reported in Iran (50458 GJha) due to similar intensive and high input crop productionsystems [31] However our output energy including grain straw and roots of maize production(34121 GJha) is much higher than that only related to grain estimated in Iran (134946 GJha) [30]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 11 of 17

34 Water Use Efficiency Based on Energy

Water use and the water use efficiency of crop production in the Shihezi Oasis are presented inTables 3 and 4 Among the three sub-oases in the Shihezi Oasis the water use of crop production in theMSW Oasis is lower than the corresponding value of the SZC and XYD oases (p lt 005) Howeverthe water use efficiency of crop production in the SZC Oasis is lower than that of the XYD and MSWoases (p lt 005) The water use (4590 m3ha) for alfalfa production in the Shihezi Oasis is the lowestwith the highest water use efficiency (4582 MJm3) (Table S4)

35 Contribution of Carbon Emissions

To further illustrate the relationship between GHG emissions and other factors Figure 2 showsthe contribution of GHG emissions from inputs of crop production The major GHG emission sourceswithin the crop production system are fertilizer and irrigation

Figure 2 Total GHG emissions from crop production and the contribution of emission sources

36 Effect Analysis of Structural Equation Modelling (SEM)

The effect analysis of SEM is presented in Table S5 The path modes show that the direct andtotal effects of the livestock breeding structure on predicted variables (farm net income energyand carbon balances) are much stronger than other dependent variables (Figure 3a total effects = 0647Figure 3b total effects = 0898 Figure 3c total effects = 1091 Figure 3d total effects = 0980Figure 3e total effects = 0898 and Figure 3f total effects = 01091) Similarly the path modesshow that the indirect effects of water use efficiency on economy income energy and carbon balancesare much stronger than those of other variables (Figure 3a indirect effects = 0196 Figure 3bindirect effects = 0297 and Figure 3c indirect effects = 0430)

Atmosphere 2020 11 781 12 of 17

Figure 3 Path models showing the direct and indirect effects of predictor variables on farm net incomeenergy balances and carbon balances The path models with significant correlations are presentedas solid lines The values on solid lines represent standardized regression weights Interruptedlines indicate no significant correlation between two variables Black arrows indicate positiveeffects For each endogenous variable the relative amount of explained variance is given Shadingindicates the greatest positive direct effect indirect effect and total effect between dependent andindependent variables OtoD The distance from the oasis to the desert (km) SPD Soil particle diameter(microm) PS Planting structure (planting crop type) WUE Water use efficiency (MJm3) BS Livestockbreeding structure (breeding livestock category) ECO Net income (1000 yenha) EB Energy balance(GJha) CB The difference value of carbon stock minus GHG emissions from agricultural productioninputs (Mg CO2-eqha) and OtoM The distance from the oasis to the desert (km) χ2 Chi-squarep Probability level df Degrees of freedom n Sample size

4 Discussion

41 Energy Balances and Net Energy Ratio

The present energy balances of agricultural production in the Shihezi Oasis are comparable tothose published elsewhere in the world using the similar methodology of calculating the input andoutput energy values on farms For example the input energy of cotton production (5880 GJha)in the Shihezi Oasis is much higher than that (31237 GJha) in Iran [30] This difference refers tothe low energy input of weed controlling and harvesting operations using human labor instead ofapplying machinery in Iran Nevertheless Shihezirsquos input energy for maize production (4971 GJha) isclose to that reported in Iran (50458 GJha) due to similar intensive and high input crop productionsystems [31] However our output energy including grain straw and roots of maize production(34121 GJha) is much higher than that only related to grain estimated in Iran (134946 GJha) [30]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 12 of 17

Figure 3 Path models showing the direct and indirect effects of predictor variables on farm net incomeenergy balances and carbon balances The path models with significant correlations are presentedas solid lines The values on solid lines represent standardized regression weights Interruptedlines indicate no significant correlation between two variables Black arrows indicate positiveeffects For each endogenous variable the relative amount of explained variance is given Shadingindicates the greatest positive direct effect indirect effect and total effect between dependent andindependent variables OtoD The distance from the oasis to the desert (km) SPD Soil particle diameter(microm) PS Planting structure (planting crop type) WUE Water use efficiency (MJm3) BS Livestockbreeding structure (breeding livestock category) ECO Net income (1000 yenha) EB Energy balance(GJha) CB The difference value of carbon stock minus GHG emissions from agricultural productioninputs (Mg CO2-eqha) and OtoM The distance from the oasis to the desert (km) χ2 Chi-squarep Probability level df Degrees of freedom n Sample size

4 Discussion

41 Energy Balances and Net Energy Ratio

The present energy balances of agricultural production in the Shihezi Oasis are comparable tothose published elsewhere in the world using the similar methodology of calculating the input andoutput energy values on farms For example the input energy of cotton production (5880 GJha)in the Shihezi Oasis is much higher than that (31237 GJha) in Iran [30] This difference refers tothe low energy input of weed controlling and harvesting operations using human labor instead ofapplying machinery in Iran Nevertheless Shihezirsquos input energy for maize production (4971 GJha) isclose to that reported in Iran (50458 GJha) due to similar intensive and high input crop productionsystems [31] However our output energy including grain straw and roots of maize production(34121 GJha) is much higher than that only related to grain estimated in Iran (134946 GJha) [30]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 13 of 17

The net energy ratios of wheat and maize production in the research area are much higher than that(395 vs 213 627 vs 267 respectively) in Iran [3132] The reason for the lower output energy andnet energy ratio of crop production estimated in Iran is that the outputs included only grain Howeverthe net energy ratio of wheat production in this study is higher than that (395 vs 159) in Pakistan dueto less wheat yield as output energy [33] The corresponding value of maize production in the researcharea is also higher than that (687 vs 552) in Turkey due to less crop yields [34]

The flow of energy and matter is the driving force of agricultural development [35] Agriculturalproduction in the Shihezi Oasis is a high inputs and outputs system With the rapid developmentof agriculture high inorganic energy inputs can satisfy peoplersquos expectations of living standardsbut at the cost of environmental sustainability From data in this research study (cf Table S1) a moresustainable approach for Shihezi Oasis farmers would be to increase both alfalfa acreage and sheepnumbers in tandem

42 GHG Emissions from Agricultural Systems

Similarly GHG emissions from agricultural systems in the Shihezi Oasis are comparable to thoseevaluated in other places For example GHG emissions for maize production (121 MgCO2-eqha)in this study are similar to those reported in Iran (129 Mg CO2-eqha) due to similar energy inputsof maize production [31] As the effective value of economic output produced by the unit carboninput the signals of carbon economic efficiency can explain the benefits of carbon cost to societyThe present carbon economic efficiency for wheat production ($0027kg CO2-eq) is higher than that($0023kg CO2-eq) in the USA [36] The most significant reason for this difference is GHG emissionsfrom wheat production ranging from 014ndash038 CO2-eq per kg of wheat produced on farms in the USAApart from this paper there is no other related research on carbon balances in China which is significantenough to suggest adjusting the balance of crops with livestock production As already stated in theShihezi Oasis high inputs such as fertilizer mulch and machinery resulted in high outputs in cropproduction but also in high GHG emissions In addition if GHG emissions are to be related to climatepolicy framework in the future similar to legislation introduced in some other countries it will beessential to know the impact of those polices on crop and livestock production costs

43 Balance between Livestock and Forage Crops

There exists an imbalance between livestock and forage crop energy inputs vs outputs in theShihezi Oasis (Figure 4) Livestock numbers in the Shihezi Oasis are far greater than can be supportedby the forage crop supply For example the current forage crop supply in XYD Oasis could not meetthe feed demand of livestock which had the largest number of livestock among the three sub-oases inthe Shihezi Oasis Livestock feedstuff prices in the Shihezi Oasis whether bought or sold are the same(Table S2) indicating that the cost of growing feedstuff ldquoon farmrdquo is less than the cost of buying it fromoutside This is good reason for oasis forage maize and alfalfa acreage to be greatly increased and thusbringing the demand and supply into balance

Similarly the revenue (13976 yenha) of alfalfa production in 2014 was higher than that (10275 yenha)of cotton production in the oasis of the Manasi River The differences of net income per 100 sheep in2014 were yen29492 between proposed crop-livestock production compared to the current practices ofNileke County of the Xinjiang Autonomous Region in China [37] The revenue per hectare of maizeproduction in Dingxi City of Gansu Province in China was much higher than that (yen14070 vs yen3315)of wheat production in 2018 The net income of integrated crop-livestock production in 2018 was319 times that of intensive crop production [38]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 14 of 17

Figure 4 Feed demand compared to supplemental feed in the research site

44 Uncertainty of Energy Balances and GHG Emissions Assessment

As a basic assessment of energy balances and GHG emissions from agricultural systems in theShihezi Oasis there still existed many factors of uncertainty Firstly there were differences in dataof arable land area livestock numbers and inputs of agricultural production within each sub-oasisSecondly the statistical method of partial data in Chinarsquos literature is different from that in developedcountries Thirdly the coefficient for calculation of carbon balances and GHG emissions in the ShiheziOasis were estimated using overseas data reported by Zeng et al [39] and Cheng et al [6] In additionthe other factors such as energy consumption and GHG emissions from plastic mulch were onlyassociated with plastic production In this study we only used the Tier 1 method of IPCC 2013 toevaluate GHG emissions from livestock production [11] Nevertheless the basic estimation of energybalances and GHG emissions in the Shihezi Oasis may offer fundamental information for the Chinesegovernment to develop long-term agricultural policies on food security energy conservation andGHG emissions reduction in northwest China

5 Conclusions

The models of energy balances carbon balances carbon economic efficiency and water useefficiency developed in this study were used to calculate the differences of energy balances and GHGemissions from the three various local oasis ecotypes in the Shihezi Oasis The evaluation indicated thatcrop production in the XYD Oasis had higher energy balances (22147 GJha) and an energy ratio (539)than in the SZC and MSW oases The sheep production per kg of CW in the XYD Oasis had higherenergy balances (1831 MJkg CW) and an energy ratio (221) than in the other two oases The wateruse efficiency of crop production in the SZC Oasis was lower than that of the other two oases (p lt 005)These evaluation models in the present study were also used to calculate the differences of energybalances GHG emissions and carbon economic efficiency from local main crops in the Shihezi OasisWe found one hectare of forage crops (ie alfalfa and maize) generated fewer emissions than any ofthe other four crops (wheat cotton grapes and tomatoes) Alfalfa production in the Shihezi Oasishad the lowest water use (45940 m3ha) and highest water use efficiency (4582 MJm3) comparedwith all other five crops (wheat maize cotton grapes and tomatoes) The carbon economic efficiencyof maize relative to its market value was significantly higher than that for each of the other fivecrops Fertilizer and irrigation were the two main GHG emission sources from crop production in all

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 15 of 17

three sub-oases together Analysis of SEM showed that the livestock breeding structure and water useefficiency significantly influenced farm income and energy and carbon balances in the Shihezi OasisThe agro-system of Shihezi Oasis was dominated by crop production derived by high energy inputs(eg irrigation fertilizer and pesticide) The present production model of Shihezi Oasis will bringhigh risk to the environment and market However integrated crop-livestock production will increaseenergy use efficiency and decrease GHG emissions from the agriculture system in the Shihezi OasisA more sustainable approach for the agricultural development of Shihezi Oasis would be to increaseboth forage crop (ie alfalfa and maize) acreage and sheep numbers in tandem

Supplementary Materials The following are available online at httpwwwmdpicom2073-4433118781s1Figure S1 Longitudinal section of Shihezi study site to show Mountain-Oasis-Desert coupling ecological system(8458primendash8664prime E) Table S1 Average data of climate crop and livestock of the three sub-oases in the Shihezi Oasis(2015ndash2016) Table S2 The structured questionnaire of farm survey Table S3 Average market price of inputs andoutputs for agricultural production (2015ndash2016) Table S4 Energy balances carbon balances carbon economicefficiency water use and water use efficiency of crop grown in the Shihezi Oasis Table S5 The standardizeddirect indirect and total effects between dependent variables and predict variables

Author Contributions FH (Fujiang Hou) and ZY conceived and designed the experiments FH (Fuqin Hou)and ZY performed the experiments and farm survey ZY and FH (Fuqin Hou) analyzed the data ZY wrote themain manuscript text and FH (Fujiang Hou) reviewed the manuscript All authors have read and agreed to thepublished version of the manuscript

Funding This research was funded by the National Natural Science Foundation of China (No 31660347 and31172249) the National Key Project of Scientific and Technical Supporting Programs (No 2014CB138706)and Programme for Changjiang Scholars and University Innovation and Research Teams (No IRT13019)

Acknowledgments The authors thank Roger Davies (NZCFS) for his support in fruitful discussion

Conflicts of Interest The authors declare no conflict of interest

References

1 Ren JZ He DH Wang N Zhu XY Li ZQ Models of coupling agro-grassland systems in desert-oasisregion Acta Prataculturae Sin 1995 2 11ndash19 (In Chinese)

2 Kramer KJ Moll HC Nonhebel S Total greenhouse gas emissions related to the Dutch crop productionsystem Agric Ecosyst Environ 1999 72 9ndash16 [CrossRef]

3 Ozkan B Akcaoz H Fert C Energy inputndashoutput analysis in Turkish agriculture Renew Energy 2004 2939ndash51 [CrossRef]

4 Khoshnevisan B Rafiee S Omid M Mousazadeh H Rajaeifar MA Application of artificial neuralnetworks for prediction of output energy and GHG emissions in potato production in Iran Agric Syst 2014123 120ndash127 [CrossRef]

5 Lal R Carbon emission from farm operations Environ Int 2004 30 981ndash990 [CrossRef] [PubMed]6 Cheng K Pan G Smith P Luo T Li L Zheng J Zhang X Han X Yan M Carbon footprint of Chinarsquos

crop productionmdashAn estimation using agro-statistics data over 1993ndash2007 Agric Ecosyst Environ 2011 142231ndash237 [CrossRef]

7 Broad K Agrawala S The ethiopia food crisis-uses and limits of climate forecasts Science 2000 2891693ndash1694 [CrossRef]

8 Marland G West T Schlamadinger B Canella L Managing soil organic carbon in agriculture The neteffect on greenhouse gas emissions Tellus B 2003 613ndash621 [CrossRef]

9 Yan ZG Li W Yan TH Chang SH Hou FJ Evaluation of energy balances and greenhouse gasemissions from different agricultural production systems in Minqin Oasis China PeerJ 2019 7 e6890[CrossRef]

10 International Organization for Standardization ISO14044 Environmental ManagementmdashLife CycleAssessmentmdashRequirements and Guidelines ISO Geneva Switzerland 2006 pp 1ndash16

11 Intergovernmental Panel on Climate Change (IPCC) Climate Change 2014 Mitigation of Climate ChangeAvailable online httpwwwipccchreportar5wg3 (accessed on 21 July 2020)

12 Wen D Pimentel D Energy flow through an organic agroecosystem in China Agric Ecosyst Environ 198411 145ndash160 [CrossRef]

Atmosphere 2020 11 781 16 of 17

13 Pimentel D Handbook of Energy Utilization in Agriculture Bender M Ed CRC Press Boca Raton FL USA1980 pp 155ndash161

14 Huang ZW Yang DG Li XP Refu KT Analysis on the energy flow of the farmer households and thecharacteristics of the eco-economic fractals in the middle and lower reaches of the Tarim river Arid Zone Res2004 21 308ndash312 (In Chinese)

15 Lu FB Energy flow in the agroecosystem of farming-livestock-fruit Ecol Agric Res 1994 2 40ndash46(In Chinese)

16 Steve M How much carbon dioxide does the human breathe out every day in the world China Sci TechPanor Mag 2005 6 176ndash177 (In Chinese)

17 Chen ST Huang Y Zou J Shen Q Hu Z Qin Y Chen H Pan G Modeling interannual variability ofglobal soil respiration from climate and soil properties Agric For Meteorol 2010 150 590ndash605 [CrossRef]

18 West TO Marland GA Synthesis of carbon sequestration carbon emissions and net carbon flux inagriculture Comparing tillage practices in the United States Agric Ecosyst Environ 2002 91 217ndash232[CrossRef]

19 Shi LG Chen F Kong FL Fan SC The carbon footprint of winter wheat-summer maize croppingpattern on north China plain China Popul Resour Environ 2011 21 93ndash98 (In Chinese)

20 Blook H Kool A Luske B Ponsioen T Scholten J Methodology for Assessing Carbon Footprints ofHorticultural Products Available online httpswwwresearchgatenetpublication285690888 (accessed on21 July 2020)

21 Lu F Wang XK Han B Assessment on the availability of nitrogen fertilization in improving carbonsequestration potential of Chinarsquos cropland soil Chin J App Ecol 2008 19 2239ndash2250 (In Chinese)

22 Dubey A Lal R Carbon footprint and sustainability of agricultural production systems in Punjab Indiaand Ohio USA J Crop Improv 2009 23 332ndash350 [CrossRef]

23 Adom F Maes A Workman C Clayton-Nierderman Z Thoma G Shonnard D Regional carbonfootprint analysis of dairy feeds for milk production in the USA Int J Life Cycle Assess 2012 17 520ndash534[CrossRef]

24 Lal R Enhancing crop yields in the developing countries through restoration of the soil organic carbon poolin agricultural lands Land Degrad Dev 2010 17 197ndash209 [CrossRef]

25 Wang JQ Agricultural StandardsmdashFeeding Standard of Meat Producting Sheep and Goats (NYT 816-2004)Ministry of Agriculture of China Ed China Agriculture Press Beijing China 2004 pp 17ndash20

26 Dyer JA Desjardins RL Carbon dioxide emissions associated with the manufacturing of tractors and farmmachinery in Canada Biosyst Eng 2006 93 107ndash118 [CrossRef]

27 Meng XH Cheng GQ Zhang JB Wang YB Zhou HC Analyze on the spatialtemporal characteristicsof GHG estimation of livestockrsquos by life cycle assessment in China China Environ Sci 2014 34 2167ndash2176(In Chinese)

28 Shi LG Fan SG Kong FL Chen F Preliminary study on the carbon efficiency of main crops productionin north China plain Acta Agron Sin 2011 37 1485ndash1490 (In Chinese) [CrossRef]

29 Wu CC Gao XY Hou FJ Carbon balance of household production system in the transition zone fromthe loess plateau to the Qinghai-Tibet Plateau China Chin J Appl Ecol 2017 28 3341ndash3350 (In Chinese)

30 Pishgarkomleh SH Sefeedpari P Ghahderijani M Exploring energy consumption and CO2 emission ofcotton production in Iran J Renew Sustain Energy 2012 4 427ndash438

31 Yousefi M Damghani AM Khoramivafa M Energy consumption greenhouse gas emissions andassessment of sustainability index in corn agroecosystems of Iran Sci Total Environ 2014 493 330ndash335[CrossRef] [PubMed]

32 Khoshroo A Energy use pattern and greenhouse gas emission of wheat production A case study inIran Agric Commun 2014 2 9ndash14 Available online httpswwwresearchgatenetpublication262105641(accessed on 21 July 2020)

33 Abbas A Yang ML Ahmad R Yousaf K Iqbal T Energy use efficiency in wheat productiona case study of Paunjab Pakistan Fresenius Environ Bull 2017 26 6773ndash6779 Available online httpswwwprt-parlardedownload_feb_2017 (accessed on 21 July 2020)

34 Baran MF Gokdogan O Comparison of energy use efficiency of different tillage methods on thesecondary crop corn silage production Fresenius Environ Bull 2016 25 3808ndash3814 Available onlinehttpswwwprt-parlardedownload_afs_2016 (accessed on 21 July 2020)

Atmosphere 2020 11 781 17 of 17

35 Sere C Steinfeld H Groenewold J Food and Agricultural Organization of the United Nations (FAOUN)Available online httpwwwfaoorgWAIRDOCSLEADX6101EX6101E00HTM (accessed on 21 July 2020)

36 Soussana JF Tallec T Blanfort V Mitigating the greenhouse gas balance of ruminant production systemsthrough carbon sequestration in grasslands Animal 2010 4 334ndash350 [CrossRef] [PubMed]

37 Zhang YH The Research of Grassland Agricultural Development Model in Xinjiang PhD Thesis ShiheziUniversity Xinjiang China 2015 (In Chinese)

38 Zhang PP Comparison of Pastoral Agriculture and Traditional Agricultural Production Pattern in DingxiCity Masterrsquos Thesis Lanzhou University Gansu China 2019 (In Chinese)

39 Zeng XF Zhao SW Li XX Li T Liu J Main crops carbon footprint in pingluo county of the NingxiaHui autonomous region Bull Soil Water Conserv 2012 32 61ndash65 (In Chinese)

copy 2020 by the authors Licensee MDPI Basel Switzerland This article is an open accessarticle distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license (httpcreativecommonsorglicensesby40)