concentrations,spatialdistributions,andsourcesofheavy...

Research ArticleConcentrations Spatial Distributions and Sources of HeavyMetals in Surface Soils of the Coal Mining City Wuhai China

Qingwei Bu 1 Qingshan Li 1 Handan Zhang 1 Hongmei Cao 1 Wenwen Gong 2

Xin Zhang 1 Ke Ling 1 and Yibo Cao1

1School of Chemical amp Environmental Engineering China University of Mining amp Technology-Beijing Beijing 100083 China2Beijing Research Center for Agricultural Standards and Testing Beijing Academy of Agriculture and Forestry ScienceBeijing 100097 China

Correspondence should be addressed to Qingwei Bu qingweibucumtbeducn

Received 29 April 2020 Accepted 27 June 2020 Published 22 July 2020

Academic Editor Luqman C Abdullah

Copyright copy 2020 Qingwei Bu et al is is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Various studies have shown that soils surrounding mining areas are seriously polluted by heavy metals In this study 58 topsoil sampleswere systematically collected throughout the coal mining cityWuhai located within the InnerMongolia Autonomous Region of Chinae concentrations of As Hg Cr Ni Cu Zn Cd and Pb in these samples were measured and statistically analyzed e meanconcentrations of all heavymetals were lower than their Grade I values defined by the Chinese Soil Quality Standard However themeanconcentrations of individual heavy metals in many samples exceeded their background values e spatial distribution of heavy metalswas analyzed by the ordinary kriging interpolationmethode positivematrix factorizationmodel was used to ascertain contaminationsources of the eight heavy metals and to apportion the contribution of each source e most severely polluted area was the Wuhushanmine site in the Wuda district of Wuhai Our results showed that coal mining strongly affected heavy metal contamination of the localsoils Results of source apportionment indicated that contributions from industrial activities atmospheric deposition agriculturalactivities and natural sources were 313 263 219 and 205 respectivelyis clearly demonstrates that anthropogenic activitieshave markedly higher contribution rates than natural sources to heavy metal pollution in soils in this area

1 Introduction

Heavymetal contamination has attracted increasing concernover the past decades because it represents a potential hazardto human health and to the environment [1ndash3] In particularheavy metal pollution in soils has become a serious envi-ronmental problem around the world linked to rapid ur-banization and industrialization [4 5] Heavy metals in soilsare completely undegradable and are easily accumulated inorganisms through the food chain [6 7] In addition theycan be transported to distant downwind areas through at-mospheric diffusion and to rivers through surface runoffunder rainfall condition [8] erefore soil pollution byheavy metals has become a serious threat to human healthand regional ecological systems

It is commonly recognized that natural and anthropo-genic activities are the two major origins of heavy metals

Natural sources are mainly related to trace elements in thecrust [9] while anthropogenic sources are mainly related tometal smelting fuel and coal combustion coal mining andagricultural fertilization [10 11] To identify sources andunderstand the spatial variation of heavy metals in soilsmultivariate statistics combined with geostatistical methodswere generally used [12ndash14] Typically geostatisticalmethods are applied to study the spatial distributioncharacteristics of heavy metals in soils e ordinary krigingmethod is the main interpolation method frequently used tostudy the spatial distribution characteristics of heavy metalsin soils [12 15] it is based on measured data and a semi-variogram model to predict unknown sites [12 15 16] eUS Environmental Protection Agencyrsquos positive matrixfactorization (EPArsquos PMF) model is widely applied toevaluate the sources of heavy metals in soilse PMFmodelanalyzes and quantifies the contributions of different

HindawiJournal of ChemistryVolume 2020 Article ID 4705954 10 pageshttpsdoiorg10115520204705954

pollution sources to samples ere have been numerousstudies that systematically analyzed the pollution status ofheavy metals in soils by combining geostatistical methodswith the EPArsquos PMF model [14 17 18]

Coal mining grinding coal transportation and coalcombustion processes are known to transfer several heavymetals to the topsoil leading to contamination of heavymetals in mining regions [19ndash21] Tang et al [18] reportedconcentration levels of heavy metals in soils in Fuxin Chinae mean concentrations of As Cd Cr Ni and Zn allexceeded the soil background values of these heavy metalsIn fact the mean concentration of Cd was nine times higherthan its background value In contrast the mean concen-trations of Cu Hg and Pb were lower than their respectivebackground values Sun et al [22] studied the concentrationsof heavy metals in soils of Tangshan China e meanconcentrations of Zn Pb Cd Hg and Cu were higher thantheir background values while those of Cr Ni and As werelower than their background values None of them exceededtheir corresponding Grade II values defined by the ChineseSoil Environmental Quality Standard Hua et al [23]measured the concentrations of heavy metals in soils ofDaye China e mean concentrations of Cd Cu Pb andZn were higher than their background values while Cr NiandMn concentrations were notemean concentration ofCd was seven times higher than its background value Lianget al [14] investigated average contents of twelve heavymetals (Zn Cd Cu Hg Pb Sb As Mo V Fe and Cr) exceptfor Mn all exceeded their background levels in soils in HunanProvince In fact in Lianyuan the Hg level was higher than itscorresponding Grade II value defined by the Chinese SoilEnvironmental Quality Standard Reza et al [16] researched theaverage contents of heavy metals in a mining area of northwestIndia e mean concentrations of Cr Cd Ni and Pb were1123mgkg 260mgkg 875mgkg and 1831mgkg re-spectively Overall the degree of soil polluted by heavy metalsvaries significantly in different coal mining cities Furthermorethe sources contribution was dominated by anthropogenicactivities In contrast to other land-use areas [17 24 25] studiesof heavy metal pollution in soils of coal mining areas arerelatively few at presenterefore the existing information onheavy metals in soils of coal mining areas is clearly inadequatefor researchers andmanagers to comprehensively evaluate theircontamination levels and potential risks

Wuhai is a typical coal mining city within the InnerMongolia Autonomous Region China ere are 3147billion tons of coal reserves in Wuhai of which more than05 billion tons of coal have been excavated e develop-ment of chemical coal iron and steel production and otherindustries has likely led to the deterioration of soil quality inWuhai [26] However the pollution status of heavy metals insoils in Wuhai has not been investigated to date

e main objectives of this study were (1) to reportcontamination levels of eight heavy metals namely As HgCr Ni Cu Zn Cd and Pb (2) to ascertain spatial distri-bution characteristics using geostatistics and the ordinarykriging interpolation method and (3) to quantitativelyidentify sources of heavy metals in soils by using the EPArsquosPMF model

2 Materials and Methods

21 Study Area Wuhai (39deg02prime30Primendash39deg54prime5PrimeN 106deg36prime25Primendash107deg08prime05PrimeE) is located in the southwest of the InnerMongolia Autonomous Region adjacent to the Ningxia HuiAutonomous Region and at the junction of threedesertsmdashthe Wulanbuhe the Kubuqi and the Maowusue Yellow River crosses the region from south to northalong its eastern edge e city covers an area of around1754 km2 encompassing three administrative dis-trictsmdashHaibowan Wuda and Hainane city terrain is thehighest on its east and west sides and the lowest at its centerAverage annual precipitation and evaporation are 160 and3500mm respectively e diurnal temperature(minus366degCndash402degC) varies greatly which is characteristic of itstypical continental climate Wuhai has abundant coal re-sources comprising mainly bituminous and coking coals Itsindustries are centered on coal mining chemistry electricpower generation and building materials As an emergingenergy city its heavy metal soil contamination is closelyrelated to its rapid industrial development

22 Sample Collection and Concentration DeterminationA total of 58 surface soil samples were collected fromWuhaiduring 25 to 28 July 2019 (Figure 1) Sampling sites wereselected using a grid with a density of about one sampleevery 3ndash5 km [27 28] To ensure that the sampling sitesrepresented the soil quality of the entire monitoring area theland-use status and geological information were docu-mented to establish context e sampling sites covered thecoal mining area both sides of the Yellow River near themain highway beside a factory as well as farmlandgrassland and desert areas All of the soil samples werecollected from the 0ndash20 cm topsoil horizon using a stainlessspade [29] ey were immediately sealed in polyethyleneplastic bags to avoid contamination and labelede latitudeand longitude of each sampling point were recorded using aGPS and any relevant environmental information per-taining to the sample site was recorded

Sand (005ndash2mm) was the dominant soil particles in the0ndash20 cm soil profiles in the study areaus all samples weredried in open air at room temperature in a laboratory andsieved through a 2mm sieve after removing gravel and plantmaterials [30] e processed samples were sealed inpolyethylene plastic bags for concentration determinatione determination of Cr Ni Cu Zn Cd and Pb was carriedout according to themethod outlined in HJ803-2016 Hg wasdetermined according to the method outlined in DZT027917-2016 and Arsenic (As) was determined accordingto the method outlined in DZT027913-2016 e con-centrations of Cr Cd Pb Cu Zn and Ni were analyzed byinductively coupled plasma mass spectrometry while Hgand As were measured using atomic fluorescence spec-trometrye accuracy of the elemental analyzes was verifiedusing standard reference materials GSD-31 GSS-32 GSS-33and GSS-34 e results showed that the recoveries of theseeight heavy metals were within the range 946ndash1068Each set of ten samples included one duplicate sample and

2 Journal of Chemistry

relative standard deviations were lower than 15 for allbatch treatments Method detection limits (MDLs) were 100005 5 1 1 4 002 and 05mgkg for As Hg Cr Ni CuZn Cd and Pb respectively

23 Data Analysis

231 Descriptive Statistical Analysis SPSS 240 software(IBM Corp Armonk NY USA) was used for basic de-scriptive statistical analysis of the sample data isprovided the maximum minimum mean standard de-viation coefficient of variation skewness and kurtosisand allowed us to assess the normality for the sampledheavy metal concentrations e correlations betweenheavy metals were assessed using Pearsonrsquos correlationmethod

232 Geostatistical Analysis Geostatistical analysis is basedon regional variable theory and is used to study distributioncharacteristics and variation with geographic propertiesMeanwhile a semivariogram model was used to interpolateunknown points as an important complementary tool [31]In this study ArcGIS 102 (Esri Inc Redlands CA USA)was used for calculating the spatial distribution

characteristics of soil heavy metals using the ordinarykriging interpolation method [32] e original concen-tration data which did not meet the conditions of a normaldistribution were normalized using a logarithm transfor-mation and a normality test was carried out using a Q-Qplot e semivariogram model and kriging calculationmethod are defined as follows [33]

c(h) 1

2N(h)1113944

N(h)

i1Z xi( 1113857 minus Z xi + h( 11138571113858 1113859

2

1113954Z x0( 1113857 1113944N

i1λiZ xi( 1113857 (1)

where c(h) is semivariogram h is the step length or distanceN(h) is the number of pairs of sample points separated by hZ(xi) is the measured value of heavy metals in the soil at theregionalized variable position xi 1113954Z(x0) is the concentrationof the heavy metal to be tested n is the number of samplingpoints and λi is the set of weight coefficients e semi-variogrammodel includes linear spherical exponential andGaussian components In ordinary kriging space interpo-lation the optimal fitting model improves the accuracy ofinterpolation

T43

T45T44

T48T46

T50T49

T26

T52

T18

T19

T28T42

T27

T56

T51

T57T54T53

T47

T36T35

T37

T34

T32T33

T31T30T29

T14

T55

T23

T16T17

T20

T40

T41

T38T25

T21

T24

T22

T13T15

T12T11

T5

T39

T8

T10 T6T7 T9

T1 TN

T3 T2

T4

China

Inner Mongolia autonomous region 0 5 10 20 km

N

Sample sites

Wuhai

Figure 1 Location of study area and distribution of sampling sites

Journal of Chemistry 3

24 PositiveMatrix FactorizationModel e EPArsquos PMF 50is a modified factor analysis receptor model proposed byPaatero [34] It has been successfully applied to determinethe source apportionment of various types of environmentalpollution In our study EPArsquos PMF 50 was used to de-termine the source apportionment of heavy metals in localsoils According to the EPArsquos PMF 50 user guide

xij 1113944

p

k1gikfkj + eij (2)

where xij is the measurement matrix of the jth heavy metalelement in i number of samples gik is a contribution matrixof the kth source factor for i number of samples fkj is asource profile of jth heavy metal element for the kth sourcefactor and eij refers to the residual value for the jth metalelement in i number of samples e minimum value of theobjective function Q can be computed by the followingformula

Q 1113944n

i11113944

m

j1

xij minus 1113936p

k1 gikfkj

uij

⎛⎝ ⎞⎠

2

(3)

where uij refers to the uncertainty in the jth heavy metalelement for sample i e remarkable feature of PMF is thatit uses uncertainty to analyze the quality of all individualconcentration data points If the concentration of heavymetal does not exceed theMDL value then the uncertainty iscalculated using the following formula

Unc 56

times MDL (4)

while if the concentration of heavy metal exceeds its cor-responding MDL value then the uncertainty is calculatedusing this formula

Unc

(Error fraction times concentration)2 +(05 times MDL)21113969

(5)

3 Results and Discussion

31 Levels of Heavy Metal Contamination e statisticalcharacteristics of concentrations of As Hg Cr Ni Cu ZnCd and Pb in all soil samples are presented in Table 1 In thisstudy the soil background values for the Inner MongoliaAutonomous Region were used as evaluation criteria [35] Inaddition the concentrations of heavy metals in soils werecompared with Grade I and Grade II values of the ChineseSoil Environmental Quality Standard (GB15618-1995) emean concentrations of As Hg Cr Ni Cu Zn Cd and Pb insoils were 931mgkg 012mgkg 617mgkg 247mgkg196mgkg 552mgkg 016mgkg and 280mgkg re-spectively Generally the mean concentrations of heavymetals in the soils were all lower than their Grade I valuesdefined in the Chinese Soil Environmental Quality Standardalthough they exceeded their background values eexceedance ratios of As Hg Cr Ni Cu Zn Cd and Pb were100 293 100 983 966 396 100 and 100respectively e most serious heavy metal contaminations

were associated with Hg and Cd these species had meanconcentrations that exceeded their background values by 43and 42 times respectively is is consistent with previouslypublished statements that Hg and Cd produce the mostserious heavy metal contaminations in China [14 22 36]

e coefficients of variation of As Hg Cr Ni Cu ZnCd and Pb were 247 540 159 226 715812 483 and 139 respectively (Table 1) evariability of heavy metal concentrations was rankedHg gt Pb gt Zn gtCu gtCd gtAs gtNi gtCr erefore Hg PbZn Cu and Cd had higher coefficients of variation andwider concentration ranges than other heavy metals Soilsamples revealed very heterogeneous spatial distributionsof these metals indicating that their concentrations werestrongly influenced by anthropogenic sources [37] Incontrast As Cr and Ni had relatively low coefficients ofvariation suggesting that these heavy metals were lessaffected by anthropogenic sources

Table S1 shows a comparison of recently published heavymetal concentrations in soils from typical coal mining citiesand nonmining cities throughout China When compared todata for other typical coal mining cities our results indicatethat soil concentrations of As Cr Ni Cu and Pb representmoderate contamination levels the soil concentration of Hgrepresents a high contamination level while soil concen-trations of Zn and Cd represent low contamination levelsWhen compared to other studies conducted in nonminingcities the concentrations of As Hg Cr Ni and Pb representmoderate contamination levels while Cu Zn and Cdrepresent low contamination levels Additionally a com-parison of heavy metal concentrations in soils was also madebetween studies conducted in typical coal mining cities andnonmining citiese results show that concentrations of Hgin mining cities were slightly lower than those in nonminingcities but concentrations of As Cr Ni Cu Zn Cd and Pbwere not significantly different among cities

e above discussion indicates that heavy metals in soilsof Wuhai have been contaminated to different degrees withHg and Cd pollution being more severe than for other heavymetals Hg Pb Zn Cu and Cd showed more spatial var-iation than other heavy metals According to our compar-ison of concentrations of heavy metals in Chinese coalmining cities and nonmining cities heavy metal concen-trations in soils of Wuhai represent moderate contamina-tion erefore it is necessary to analyze the spatialdistribution characteristics to determine the heavy metalsources within this region

32 Spatial Distributions of Heavy Metal Concentrationse spatial distributions of heavy metal concentrations inthe soils of Wuhai are shown in Figure 2 Generally thespatial trends of heavy metals within the study area are asfollows the degree of heavy metal pollution is the highest inthe middle to western parts of Wuhai with lower degrees ofpollution to the south and north In the midwestern part ofWuhai there are mainly coalfields and a major highway Inthe south of Wuhai there are various infrastructure andland-use types including a gas company a cement plant a


petrol station and various expressways as well as large areasof farmland and grassland In the north of Wuhai there areexpressways and plastic manufacturing and coal chemicalengineering plants Heavy pollution of Hg Ni Cu Zn Cdand Pb was found in samples that were located in themidwestern part proximal to the Wuhushan coalfield in theWuda district of Wuhai In this region there are coal miningand coal transportation activities Clearly coal mining

activities made a significant contribution to heavy metalcontamination of soils in the midwestern part of Wuhai

Spatial distributions of Cu and Zn in soils were highlysimilar indicating that Cu and Zn may originate from thesame source Large areas having soils contaminated with Cuand Zn were situated in the midwestern northern andsouthwestern parts of Wuhai In the midwestern area highconcentrations of Cu and Zn were proximal to the coalfield

Cu (mgkg)121ndash150150ndash163163ndash170172ndash178178ndash192192ndash221221ndash282282ndash413413ndash694

170ndash172

294ndash381381ndash421

Zn (mgkg)

421ndash439439ndash447447ndash465465ndash505505ndash592592ndash781781ndash119119ndash209

Pb (mgkg)152ndash181181ndash196196ndash204204ndash220249ndash303303ndash407407ndash604604ndash977977ndash168

220ndash249


Cd (mgkg)



Ni (mgkg)



Cr (mgkg)



As (mgkg)

808ndash862862ndash902902ndash956956ndash103103ndash113113ndash126126ndash144


Hg (μgkg)

182ndash236236ndash369369ndash695695ndash150150ndash347347ndash831831ndash20212021ndash4947 144ndash168

0 5 10 20 km0 5 10 20 km 0 5 10 20 km 0 5 10 20 km

0 5 10 20 km 0 5 10 20 km 0 5 10 20 km 0 5 10 20 km

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

Figure 2 Spatial distribution of heavy metal concentrations in soils

Table 1 e statistical characteristics of concentrations of soil heavy metals in Wuhai (mgKg)

Element Mean Max Min SD CV () Backgrounda Grade Ib Grade IIc

As 931 168 637 230 247 630 15 30Hg 012 495 001 641 539 0028 015 05Cr 617 104 447 981 159 3650 90 200Ni 247 583 162 558 226 1730 40 50Cu 196 122 121 140 715 1290 35 100Zn 552 371 294 448 812 4860 100 250Cd 016 050 006 008 483 0037 02 03Pb 280 316 152 388 139 1500 35 300aSoil background values in Inner Mongolia Autonomous Region bGrade I of the Chinese Soil Environmental Quality Standard (GB15618-1995) cGrade II ofthe Chinese Soil Environmental Quality Standard 65lt pHlt 75 (GB15618-1995)


and the highway close to coal chemical industries andplastic manufacturing enterprises in the north and close to agas company a cement plant a gas station and expresswaysin the south We speculate that Cu and Zn contamination ofthe soil were caused by industrial emissions vehicle exhaustand mechanical deterioration particles which were laterdispersed and deposited by atmospheric processes[13 38 39]

e Pb hotspots were located in midwestern andsouthwestern parts of Wuhai as well as within the centralHaibowan district of Wuhai ese areas were proximal tothe major highway and surrounding coalfields e highestconcentration area was associated with the highway Vehicleexhaust and coal dust were likely important sources of Pb[40 41] is indicates that Cu Zn and Pb inputs to soilsmainly occurred via atmospheric deposition

e hotspots of Cd in soils were mainly distributed in themidwestern and southwestern parts of Wuhai In themidwestern area Cd was associated with the highway andsurrounding coalfield erefore coal mining and its as-sociated activities are likely the primary contributors to Cdcontamination [42] Elsewhere the Cd distributions coin-cided with Pb distributions especially in the southwest issuggests a similar dispersion of Cd and Pb related to asimilar source Vehicle exhaust could contribute both Cdand Pb inputs to soils [13 43] However other large-scaleareas with moderate concentrations of Cd were present insouthern to central areas of Wuhai ese areas host nu-merous industrial activities linked to a gas company a gasstation and a cement plant ese industries have beenpreviously linked to Cd contamination in soils [44] Cd andZn had zonal distributions toward the southwest along theYellow River possibly related to fluvial processes Pavolvicet al reported that both Cd and Zn have high potential foradhering to clay minerals and are readily transported byrivers is may lead to their accumulation in riparian soils[45]

e hotspots of Hg were in the midwestern part ofWuhai In this region Hg had an extreme value of more than60 times the background value far exceeding its Grade IIvalue Given the long history of coal mining in this area it islikely that large spoil quantities have been generated whichrelease Hg-rich effluents into the surrounding environment[22] Moreover other moderately polluted areas werescattered in central and southern parts of Wuhai associatedwith the gas company the gas station and the expresswaysPrevious studies have indicated that petrochemical plantsare a major source of Hg [46] Clearly the Hg distributionwas predominantly influenced by coal mining and the localpetrochemical industry [42 47]

Arsenic (As) concentrations increased continually fromnortheast to southwest with hotspots of Arsenic (As) sit-uated on the southwest limit of Wuhai within farmland anda village A number of reports have identified Arsenic (As) asoriginating from agricultural pesticides and fertilizers[48 49] In this region Arsenic (As) contamination in soilswas also likely related to agricultural activities

High concentrations of Cr were documented in thecentral Hainan district ofWuhai related to both the coalfield

and the local cement plant A Ni hotspot located in themidwestern part of Wuhai was also associated with coalmining In addition to the hotspot in the midwestern areaanother Ni hotspot occurred within the southern to centraldesert area having no obvious point sources of Ni ecoefficients of variation and spatial variances of Cr and Niwere both relatively low is indicates that Cr and Ni levelsin soils were primarily controlled by parent materials [50]

Overall the spatial distributions of Cu Zn and Pb weremainly affected by atmospheric deposition of airborneparticles Hg was mainly related to coal mining Cd wasmainly related to industrial activities Arsenic (As) wasmainly related to agricultural activities and Cr and Ni weremainly related to parent materials of the soils Furthermorespatial distribution of soil heavy metals is rarely influencedby transport in the atmosphere since sand has the highestfractions in the research area e sources of these heavymetals are discussed in detail below

33 Source Apportionment of Heavy Metals Pearsonrsquos cor-relation coefficients of the eight heavy metals are shown inTable S2 Strong correlations were found between Pb and CuZn Cd (plt 001) while pairs Ni and Cr Cu and As wereslightly correlated (plt 005) Hg did not display a correla-tion with any other heavy metals Significant correlationsbetween metal elements in soils suggest that they had similarcontamination sources For example Cu Zn and Pb may bederived from the same source (rgt 09) as reported by Maet al [13] Given the complexity of heavy metal pollution insoils related to human activities the conclusions based onour Pearsonrsquos correlation coefficient analysis are not com-prehensive erefore the EPArsquos PMF model was used toidentify and quantify the contribution rates of differentpollution sources in the study area Results are shown inFigure 3

Factor 1 was dominated by Hg (740) and Cd (435)e high coefficient of variation for Hg (540) indicates thatHg pollution is significantly affected by human activities Ithas been reported that Hg in soils mainly originates fromindustrial sources especially petrochemical production andcoal combustion [46 51 52] Similarly Cd also enters theenvironment through human activities via exhaust gas andcoal combustion emissions owing to the stable bond be-tween Cd and organic matter and sulfide in coal [53 54]ese sources are consistent with the distributions observedin our study A large number of coal mines are exploitedaround Wuhai to provide energy for thermal power ironand steel production and cement production plants Coal isalso extensively used as a raw material in the coal chemicalindustry and in metal smelting [55] In general the con-centrations of Hg and Cd in soils are mainly related toindustrial activities especially coal mining coal chemicalengineering and metal smelting erefore Factor 1 reflectsthe input from industrial activities

Factor 2 was dominated by Arsenic (As) (697) Ar-senic (As) is commonly used in fertilizers as an additive[56 57] therefore it is routinely introduced into soils duringfertilizer applications Arsenic (As) also is an effective


ingredient in various herbicides and pesticides used regu-larly in agricultural production [58 59] Animal excrementmay be another source of Arsenic (As) because antibioticsused for poultry contain it [60] Clearly Arsenic (As) ismainly linked to agricultural activities occurring within thelarge area of farmland and grassland in the southwesternpart of the study area ese long-term activities may lead toongoing enrichment of Arsenic (As) in local soils which willaggravate local Arsenic (As) pollution erefore Factor 2reflects the input of agricultural activities

Factor 3 was dominated by Cr (512) and Ni (386)Our descriptive statistical analysis revealed small coeffi-cients of variation for both Cr and Ni with similar con-centrations measured between background and samplevalues Differences in concentration between Cr and Ni

may be related to variability in the parent materials of thesoils Previous studies have shown that variations in Cr andNi in different soils are inherited from the parent material[15 22 61] Hence Factor 3 reflects inputs from mainlynatural sources

Factor 4 was weighted on Pb (784) Zn (447) andCu (320) which are all affected by human activitiesaccording to our descriptive statistical analysis Many pre-vious studies reported that the main sources of Pb in soils arevehicle exhaust emissions and coal combustion [62ndash64] Gaoet al found that Pb and Zn were derived from atmosphericdeposition of dust from open pit coal mines [65] Li et alfound that Cu Zn and Pb were all released in the smeltingprocess of sulfide minerals (sphalerite and galena) [15]Given the abundant coal resources and the long-term

Fact

or 1

conc

Base factor profiles ndash run 7

Fact

or 2

conc

Fa

ctor

3 co

nc

Fact

or 4

conc

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

0

20

40

60

80

100

Fact

or 4

()

0

20

40

60

80

100

Fact

or 3

()

0

20

40

60

80

100

Fact

or 2

()

0

20

40

60

80

100

Fact

or 1

()

Hg Cr Ni Cu Zn Cd PbAs

of speciesConc of species

Figure 3 Factor profiles from PMF model using soil heavy metal concentration data


mining and processing operations in the study area severalheavy metals contained in the coal enter the environment asdust In addition heavy metals contained in flue gas aredischarged into the atmosphere by many coal-burning in-dustries these enter the soil via wet and dry depositionprocesses Furthermore growth in the transport sectorwithin the study area has resulted in a large amount ofvehicle emissions containing Pb this Pb constantly entersthe soil via atmospheric deposition us Factor 4 reflectsthe contribution of atmospheric deposition

To summarize Hg and Cd point to sources of industrialactivities while Cu Zn and Pb are indicators of sources ofatmospheric deposition Moreover arsenic (As) is indicativeof the sources of agricultural activities while Cr and Ni pointto natural sources Based on the factor fingerprint of eachheavy metal the overall percent contribution of each sourcewas computed Industrial activities (313) contributedmost of the heavy metal content to Wuhai soils followed byatmospheric deposition (263) agricultural activities(219) and natural sources (205) Overall anthropo-genic sources were the predominant factors reflecting in-puts from coal mining coal chemical engineering metalsmelting coal burning vehicle emissions fertilizationpesticide spraying and other activities yielding a totalcontribution of approximately 80

4 Conclusions

is study investigated contamination levels spatial dis-tribution characteristics and percentage contributions ofvarious sources of heavy metals in soils in Wuhai China byusing descriptive statistical analysis ordinary kriging in-terpolation and EPArsquos PMF model Generally mean con-centrations of heavy metals in soils in Wuhai exceeded theirbackground values with exceedance ratios of As Hg Cr NiCu Zn Cd and Pb being 100 293 100 983 966396 100 and 100 respectively eir coefficients ofvariation ranged from 159 to 540 e most seriousheavymetal contaminations in this area were associated withHg and Cd According to comparisons between soils fromtypical coal mining and nonmining cities throughout ChinaWuhai soils were moderately contaminated by heavy metalsSpatial distributions and source apportionment suggest thatheavy pollution levels of Hg Ni Cu Zn Cd and Pbproximal to the Wuhushan coalfield of the Wuda district ofWuhai are linked to significant inputs from coal miningactivities Meanwhile Cu Zn and Pb contaminations weremainly derived from fuel and coal combustion followed byatmospheric deposition Hg and Cd contaminations weremainly derived from industrial activities including coalmining coal chemical engineering and metal smelting eArsenic (As) contamination was mainly related to agricul-tural activities with inputs from fertilizers herbicidespesticides and animal excrement In contrast parent ma-terials played a vital role in producing Cr and Ni enrich-ments in these soils Generally anthropogenic sources werethe predominant factors influencing heavy metal pollutionin this area

Data Availability

e numerical data used to support the findings of this studyare included within the article and the associated supportinginformation

Conflicts of Interest

e authors declare that they have no conflicts of interest

Acknowledgments

is work was cosupported by the National Key RampDProgram of China (2017YFC0504401) the National NaturalScience Foundation of China (21777188) and the Funda-mental Research Funds for the Central Universities in China(2015QH02) Q B was financially supported by Yue QiYoung Scholar Project China University of Mining ampTechnology Beijing (2017QN15)

Supplementary Materials

Table S1 summary of concentrations of soil heavy metalscollected from typical coal mining cities and nonminingcities in recent years (mgkg) Table S2 correlation coeffi-cients between different heavy metals (SupplementaryMaterials)

References

[1] T M Schnorr K Steenland M J un and R A RinskyldquoMortality in a cohort of antimony smelter workersrdquoAmerican Journal of Industrial Medicine vol 27 no 5pp 759ndash770 1995

[2] D Mergler H A Anderson L H M Chan et al ldquoMeth-ylmercury exposure and health effects in humans a world-wide concernrdquo AMBIO A Journal of the HumanEnvironment vol 36 no 1 pp 3ndash11 2007

[3] Y S Hedberg B Erfani M Matura and C Liden ldquoChro-mium(III) release from chromium-tanned leather elicits al-lergic contact dermatitis a use test studyrdquo Contact Dermatitisvol 78 no 5 pp 307ndash314 2018

[4] M Wang R Liu W Chen C Peng and B Markert ldquoEffectsof urbanization on heavy metal accumulation in surface soilsBeijingrdquo Journal of Environmental Sciences vol 64pp 328ndash334 2018

[5] GWang S Zhang L Xiao et al ldquoHeavy metals in soils from atypical industrial area in Sichuan China spatial distributionsource identification and ecological risk assessmentrdquo Envi-ronmental Science and Pollution Research vol 24 no 20pp 16618ndash16630 2017

[6] R W Feng C Y Wei S X Tu F C Wu and L S YangldquoAntimony accumulation and antioxidative responses in fourfern plantsrdquo Plant and Soil vol 317 no 1-2 pp 93ndash101 2009

[7] E Wcislo J Bronder A Bubak E Rodriguez-Valdes andJ L R Gallego ldquoHuman health risk assessment in restoringsafe and productive use of abandoned contaminated sitesrdquoEnvironment International vol 94 pp 436ndash448 2016

[8] W Han G Gao J Geng Y Li and Y Wang ldquoEcological andhealth risks assessment and spatial distribution of residualheavymetals in the soil of an e-waste circular economy park inTianjin Chinardquo Chemosphere vol 197 pp 325ndash335 2018


[9] J Liu J Liang X Yuan et al ldquoAn integrated model forassessing heavy metal exposure risk to migratory birds inwetland ecosystem a case study in Dongting Lake WetlandChinardquo Chemosphere vol 135 pp 14ndash19 2015

[10] S-X Quan B Yan F Yang N Li X-M Xiao and J-M FuldquoSpatial distribution of heavy metal contamination in soilsnear a primitive e-waste recycling siterdquo Environmental Scienceand Pollution Research vol 22 no 2 pp 1290ndash1298 2015

[11] M Romic and D Romic ldquoHeavy metals distribution in ag-ricultural topsoils in urban areardquo Environmental Geologyvol 43 no 7 pp 795ndash805 2003

[12] Y Wang X Duan and L Wang ldquoSpatial distribution andsource analysis of heavy metals in soils influenced by in-dustrial enterprise distribution case study in Jiangsu prov-incerdquo Science of the Total Environment vol 710 Article ID134953 2020

[13] L Ma Z Yang L Li and L Wang ldquoSource identification andrisk assessment of heavy metal contaminations in urban soilsof Changsha a mine-impacted city in Southern ChinardquoEnvironmental Science and Pollution Research vol 23 no 17pp 17058ndash17066 2016

[14] J Liang C Feng G Zeng et al ldquoSpatial distribution andsource identification of heavy metals in surface soils in atypical coal mine city Lianyuan Chinardquo EnvironmentalPollution vol 225 pp 681ndash690 2017

[15] X Li H Yang C Zhang et al ldquoSpatial distribution andtransport characteristics of heavy metals around an antimonymine area in central Chinardquo Chemosphere vol 170 pp 17ndash242017

[16] S K Reza U Baruah S K Singh and T H Das ldquoGeo-statistical and multivariate analysis of soil heavy metal con-tamination near coal mining area northeastern IndiardquoEnvironmental Earth Sciences vol 73 no 9 pp 5425ndash54332015

[17] W Hu H Wang L Dong et al ldquoSource identification ofheavy metals in peri-urban agricultural soils of southeastChina an integrated approachrdquo Environmental Pollutionvol 237 pp 650ndash661 2018

[18] J Tang M He Q Luo M Adeel and F Jiao ldquoHeavy metals inagricultural soils from a typical mining city in China spatialdistribution source apportionment and health risk assess-mentrdquo Polish Journal of Environmental Studies vol 29 no 2pp 1379ndash1390 2020

[19] Y Kang G Liu C-L Chou M H Wong L Zheng andR Ding ldquoArsenic in Chinese coals distribution modes ofoccurrence and environmental effectsrdquo Science of the TotalEnvironment vol 412-413 pp 1ndash13 2011

[20] S Dai R Zeng and Y Sun ldquoEnrichment of arsenic anti-mony mercury and thallium in a late permian anthracitefrom Xingren Guizhou southwest Chinardquo InternationalJournal of Coal Geology vol 66 no 3 pp 217ndash226 2006

[21] S F Dai D Ren Y G Tang M Yue and L M HaoldquoConcentration and distribution of elements in late permiancoals from western Guizhou province Chinardquo InternationalJournal of Coal Geology vol 61 no 1-2 pp 119ndash137 2005

[22] L Sun D Guo K Liu et al ldquoLevels sources and spatialdistribution of heavy metals in soils from a typical coal in-dustrial city of Tangshan Chinardquo Catena vol 175 pp 101ndash109 2019

[23] L Hua X Yang Y Liu X Tan and Y Yang ldquoSpatial dis-tributions pollution assessment and qualified source ap-portionment of soil heavy metals in a typical mineral miningcity in Chinardquo Sustainability vol 10 no 9 p 3115 2018

[24] L-M Cai Q-S Wang H-H Wen J Luo and S WangldquoHeavy metals in agricultural soils from a typical township inGuangdong province China occurrences and spatial distri-butionrdquo Ecotoxicology and Environmental Safety vol 168pp 184ndash191 2019

[25] S Xie F Yang H Feng C Wei and F Wu ldquoAssessment ofpotential heavy metal contamination in the peri-urban ag-ricultural soils of 31 provincial capital cities in Chinardquo En-vironmental Management vol 64 no 3 pp 366ndash380 2019

[26] Z Bian X Miao S Lei S-e ChenWWang and S Struthersldquoe challenges of reusing mining and mineral-processingwastesrdquo Science vol 337 no 6095 pp 702-703 2012

[27] X Liu J Wu and J Xu ldquoCharacterizing the risk assessment ofheavy metals and sampling uncertainty analysis in paddy fieldby geostatistics and GISrdquo Environmental Pollution vol 141no 2 pp 257ndash264 2006

[28] D Hou D OrsquoConnor P Nathanail L Tian and Y MaldquoIntegrated GIS and multivariate statistical analysis for re-gional scale assessment of heavy metal soil contamination acritical reviewrdquo Environmental Pollution vol 231 pp 1188ndash1200 2017

[29] H Chen Y Teng S Lu Y Wang and J Wang ldquoContami-nation features and health risk of soil heavy metals in ChinardquoScience of the Total Environment vol 512-513 pp 143ndash1532015

[30] W Ben Achiba N Gabteni A Lakhdar et al ldquoEffects of 5-year application of municipal solid waste compost on thedistribution and mobility of heavy metals in a Tunisian cal-careous soilrdquo Agriculture Ecosystems amp Environmentvol 130 no 3-4 pp 156ndash163 2009

[31] R Webster and M A Oliver Geostatistics for EnvironmentalScientists Wiley Chichester UK 2nd edition 2011

[32] D G Krige ldquoA atatistical approach to some basic minevaluation problems on the Witwatersrandrdquo Journal of theChemical Metallurgical and Mining Society of South Africavol 52 pp 119ndash139 1951

[33] L Mabit and C Bernard ldquoAssessment of spatial distributionof fallout radionuclides through geostatistics conceptrdquoJournal of Environmental Radioactivity vol 97 no 2-3pp 206ndash219 2007

[34] P Paatero and U Tapper ldquoPositive matrix factorization anon-negative factor model with optimal utilization of errorestimates of data valuesrdquo Environmetrics vol 5 no 2pp 111ndash126 1994

[35] CNEMC Background Values of Soil Elements in China ChinaEnvironmental Science Press Beijing China 1990 inChinese

[36] J Zou X Liu W Dai and Y Luan ldquoPollution assessment ofheavy metal accumulation in the farmland soils of Beijingrsquossuburbsrdquo Environmental Science and Pollution Researchvol 25 no 27 pp 27483ndash27492 2018

[37] D S Manta M Angelone A Bellanca R Neri andM Sprovieri ldquoHeavy metals in urban soils a case study fromthe city of Palermo (Sicily) Italyrdquo Science of the Total En-vironment vol 300 no 1ndash3 pp 229ndash243 2002

[38] R K Sharma M Agrawal and F M Marshall ldquoAtmosphericdeposition of heavy metals (Cu Zn Cd and Pb) in VaranasiCity Indiardquo Environmental Monitoring and Assessmentvol 142 no 1ndash3 pp 269ndash278 2008

[39] K B Githaiga S M Njuguna V A Makokha et al ldquoAs-sessment of Cu Zn Mn and Fe enrichment in Mt Kenyasoils evidence for atmospheric deposition and contamina-tionrdquo Environmental Monitoring and Assessment vol 192no 3 p 167 2020


[40] S Charlesworth M Everett R McCarthy A Ordontildeez andE de Miguel ldquoA comparative study of heavy metal con-centration and distribution in deposited street dusts in a largeand a small urban area Birmingham and Coventry WestMidlands UKrdquo Environment International vol 29 no 5pp 563ndash573 2003

[41] J Liang J Liu X Yuan et al ldquoFacile synthesis of alumina-decorated multi-walled carbon nanotubes for simultaneousadsorption of cadmium ion and trichloroethylenerdquo ChemicalEngineering Journal vol 273 pp 101ndash110 2015

[42] X Xiao J Zhang HWang et al ldquoDistribution and health riskassessment of potentially toxic elements in soils around coalindustrial areas a global meta-analysisrdquo Science of the TotalEnvironment vol 713 Article ID 135292 2020

[43] Y Liu S Lei and X Chen ldquoAssessment of heavy metalpollution and human health risk in urban soils of a coalmining city in east Chinardquo Human and Ecological Risk As-sessment vol 22 no 6 pp 1359ndash1374 2016

[44] X Xu J Qian E Xie X Shi and Y Zhao ldquoSpatio-temporalchange and pollution risk of agricultural soil cadmium in arapidly industrializing area in the Yangtze Delta region ofChinardquo International Journal of Environmental Research andPublic Health vol 15 no 12 p 2743 2018

[45] P Pavlovic M Mitrovic D Dorclevic et al ldquoAssessment ofthe contamination of riparian soil and vegetation by tracemetalsmdasha Danube river case studyrdquo Science of the TotalEnvironment vol 540 pp 396ndash409 2016

[46] J Lv Y Liu Z Zhang and J Dai ldquoFactorial kriging andstepwise regression approach to identify environmental fac-tors influencing spatial multi-scale variability of heavy metalsin soilsrdquo Journal of Hazardous Materials vol 261 pp 387ndash397 2013

[47] G J Liu L G Zheng Y Zhang et al ldquoDistribution and modeof occurrence of as Hg and Se and sulfur in coal seam 3 of theShanxi formation Yanzhou coalfield Chinardquo InternationalJournal of Coal Geology vol 71 no 2-3 pp 371ndash385 2007

[48] L Xu W Luo Y Lu et al ldquoStatus and fuzzy comprehensiveassessment of metals and arsenic contamination in farmlandsoils along the Yanghe river Chinardquo Chemistry and Ecologyvol 27 no 5 pp 415ndash426 2011

[49] H C Cao J D Wang and X L Zhang ldquoSpatial distributionof Cd Pb as contents in the farmland black soil in Jilinprovincerdquo Environmental Science vol 27 no 10 pp 2117ndash2122 2006 in Chinese

[50] H G Mikkonen R Dasika J A Drake C J WallisB O Clarke and S M Reichman ldquoEvaluation of environ-mental and anthropogenic influences on ambient backgroundmetal and metalloid concentrations in soilrdquo Science of theTotal Environment vol 624 pp 599ndash610 2018

[51] Y Li Y-b Wang X Gou Y-b Su and G Wang ldquoRiskassessment of heavy metals in soils and vegetables aroundnon-ferrous metals mining and smelting sites Baiyin ChinardquoJournal of Environmental Sciences vol 18 no 6 pp 1124ndash1134 2006

[52] T Berg E Fjeld and E Steinnes ldquoAtmospheric mercury inNorway contributions from different sourcesrdquo Science of theTotal Environment vol 368 no 1 pp 3ndash9 2006

[53] C Li Z Nie S Cui X Gong Z Wang and X Meng ldquoe lifecycle inventory study of cement manufacture in ChinardquoJournal of Cleaner Production vol 72 pp 204ndash211 2014

[54] W-Y Li L Zhong J Feng and K-C Xie ldquoRelease behaviorof As Hg Pb and Cd during coal gasificationrdquo EnergySources Part A Recovery Utilization and EnvironmentalEffects vol 32 no 9 pp 818ndash825 2010

[55] W Q Lin Q Sang T Yu andM FMa ldquoRestructing industrycategory and distribution across administrative areas based onenvironmental constraintmdasha case study of Wuhai and itssurrounding regions inner Mongolia autonomous regionChinardquo Advanced Materials Research vol 524ndash527pp 3283ndash3289 2012

[56] L Wang S Gao X Yin X Yu and L Luan ldquoArsenic ac-cumulation distribution and source analysis of rice in atypical growing area in north Chinardquo Ecotoxicology andEnvironmental Safety vol 167 pp 429ndash434 2019

[57] A A Meharg and M M Rahman ldquoArsenic contamination ofBangladesh paddy field soils implications for rice contribu-tion to arsenic consumptionrdquo Environmental Science ampTechnology vol 37 no 2 pp 229ndash234 2003

[58] M A Rahman H Hasegawa M M Rahman M A M Miahand A Tasmin ldquoStraighthead disease of rice (Oryza sativa L)induced by arsenic toxicityrdquo Environmental and ExperimentalBotany vol 62 no 1 pp 54ndash59 2008

[59] Y Li F Ye A Wang et al ldquoChronic arsenic poisoningprobably caused by arsenic-based pesticides findings from aninvestigation study of a householdrdquo International Journal ofEnvironmental Research and Public Health vol 13 no 1p 133 2016

[60] T Punshon B P Jackson A A Meharg T WarczackK Scheckel and M L Guerinot ldquoUnderstanding arsenicdynamics in agronomic systems to predict and prevent uptakeby crop plantsrdquo Science of the Total Environment vol 581-582pp 209ndash220 2017

[61] J Zhou K Feng Y Li and Y Zhou ldquoFactorial kriginganalysis and sources of heavy metals in soils of different land-use types in the Yangtze river delta of eastern Chinardquo En-vironmental Science and Pollution Research vol 23 no 15pp 14957ndash14967 2016

[62] T B Chen J W C Wong H Y Zhou and M H WongldquoAssessment of trace metal distribution and contamination insurface soils of Hong Kongrdquo Environmental Pollution vol 96no 1 pp 61ndash68 1997

[63] X Bi X Feng Y Yang et al ldquoEnvironmental contaminationof heavy metals from zinc smelting areas in Hezhang countywestern Guizhou Chinardquo Environment International vol 32no 7 pp 883ndash890 2006

[64] L Jiang J Liang X Yuan et al ldquoCo-pelletization of sewagesludge and biomass the density and hardness of pelletrdquoBioresource Technology vol 166 pp 435ndash443 2014

[65] Y Gao H Liu and G Liu ldquoe spatial distribution andaccumulation characteristics of heavy metals in steppe soilsaround three mining areas in Xilinhot in inner MongoliaChinardquo Environmental Science and Pollution Research vol 24no 32 pp 25416ndash25430 2017


pollution sources to samples ere have been numerousstudies that systematically analyzed the pollution status ofheavy metals in soils by combining geostatistical methodswith the EPArsquos PMF model [14 17 18]

Coal mining grinding coal transportation and coalcombustion processes are known to transfer several heavymetals to the topsoil leading to contamination of heavymetals in mining regions [19ndash21] Tang et al [18] reportedconcentration levels of heavy metals in soils in Fuxin Chinae mean concentrations of As Cd Cr Ni and Zn allexceeded the soil background values of these heavy metalsIn fact the mean concentration of Cd was nine times higherthan its background value In contrast the mean concen-trations of Cu Hg and Pb were lower than their respectivebackground values Sun et al [22] studied the concentrationsof heavy metals in soils of Tangshan China e meanconcentrations of Zn Pb Cd Hg and Cu were higher thantheir background values while those of Cr Ni and As werelower than their background values None of them exceededtheir corresponding Grade II values defined by the ChineseSoil Environmental Quality Standard Hua et al [23]measured the concentrations of heavy metals in soils ofDaye China e mean concentrations of Cd Cu Pb andZn were higher than their background values while Cr NiandMn concentrations were notemean concentration ofCd was seven times higher than its background value Lianget al [14] investigated average contents of twelve heavymetals (Zn Cd Cu Hg Pb Sb As Mo V Fe and Cr) exceptfor Mn all exceeded their background levels in soils in HunanProvince In fact in Lianyuan the Hg level was higher than itscorresponding Grade II value defined by the Chinese SoilEnvironmental Quality Standard Reza et al [16] researched theaverage contents of heavy metals in a mining area of northwestIndia e mean concentrations of Cr Cd Ni and Pb were1123mgkg 260mgkg 875mgkg and 1831mgkg re-spectively Overall the degree of soil polluted by heavy metalsvaries significantly in different coal mining cities Furthermorethe sources contribution was dominated by anthropogenicactivities In contrast to other land-use areas [17 24 25] studiesof heavy metal pollution in soils of coal mining areas arerelatively few at presenterefore the existing information onheavy metals in soils of coal mining areas is clearly inadequatefor researchers andmanagers to comprehensively evaluate theircontamination levels and potential risks

Wuhai is a typical coal mining city within the InnerMongolia Autonomous Region China ere are 3147billion tons of coal reserves in Wuhai of which more than05 billion tons of coal have been excavated e develop-ment of chemical coal iron and steel production and otherindustries has likely led to the deterioration of soil quality inWuhai [26] However the pollution status of heavy metals insoils in Wuhai has not been investigated to date

e main objectives of this study were (1) to reportcontamination levels of eight heavy metals namely As HgCr Ni Cu Zn Cd and Pb (2) to ascertain spatial distri-bution characteristics using geostatistics and the ordinarykriging interpolation method and (3) to quantitativelyidentify sources of heavy metals in soils by using the EPArsquosPMF model

2 Materials and Methods

21 Study Area Wuhai (39deg02prime30Primendash39deg54prime5PrimeN 106deg36prime25Primendash107deg08prime05PrimeE) is located in the southwest of the InnerMongolia Autonomous Region adjacent to the Ningxia HuiAutonomous Region and at the junction of threedesertsmdashthe Wulanbuhe the Kubuqi and the Maowusue Yellow River crosses the region from south to northalong its eastern edge e city covers an area of around1754 km2 encompassing three administrative dis-trictsmdashHaibowan Wuda and Hainane city terrain is thehighest on its east and west sides and the lowest at its centerAverage annual precipitation and evaporation are 160 and3500mm respectively e diurnal temperature(minus366degCndash402degC) varies greatly which is characteristic of itstypical continental climate Wuhai has abundant coal re-sources comprising mainly bituminous and coking coals Itsindustries are centered on coal mining chemistry electricpower generation and building materials As an emergingenergy city its heavy metal soil contamination is closelyrelated to its rapid industrial development

22 Sample Collection and Concentration DeterminationA total of 58 surface soil samples were collected fromWuhaiduring 25 to 28 July 2019 (Figure 1) Sampling sites wereselected using a grid with a density of about one sampleevery 3ndash5 km [27 28] To ensure that the sampling sitesrepresented the soil quality of the entire monitoring area theland-use status and geological information were docu-mented to establish context e sampling sites covered thecoal mining area both sides of the Yellow River near themain highway beside a factory as well as farmlandgrassland and desert areas All of the soil samples werecollected from the 0ndash20 cm topsoil horizon using a stainlessspade [29] ey were immediately sealed in polyethyleneplastic bags to avoid contamination and labelede latitudeand longitude of each sampling point were recorded using aGPS and any relevant environmental information per-taining to the sample site was recorded

Sand (005ndash2mm) was the dominant soil particles in the0ndash20 cm soil profiles in the study areaus all samples weredried in open air at room temperature in a laboratory andsieved through a 2mm sieve after removing gravel and plantmaterials [30] e processed samples were sealed inpolyethylene plastic bags for concentration determinatione determination of Cr Ni Cu Zn Cd and Pb was carriedout according to themethod outlined in HJ803-2016 Hg wasdetermined according to the method outlined in DZT027917-2016 and Arsenic (As) was determined accordingto the method outlined in DZT027913-2016 e con-centrations of Cr Cd Pb Cu Zn and Ni were analyzed byinductively coupled plasma mass spectrometry while Hgand As were measured using atomic fluorescence spec-trometrye accuracy of the elemental analyzes was verifiedusing standard reference materials GSD-31 GSS-32 GSS-33and GSS-34 e results showed that the recoveries of theseeight heavy metals were within the range 946ndash1068Each set of ten samples included one duplicate sample and



23 Data Analysis




c(h) 1

2N(h)1113944

N(h)

i1Z xi( 1113857 minus Z xi + h( 11138571113858 1113859

2

1113954Z x0( 1113857 1113944N

i1λiZ xi( 1113857 (1)


T43

T45T44

T48T46

T50T49

T26

T52

T18

T19

T28T42

T27

T56

T51

T57T54T53

T47

T36T35

T37

T34

T32T33

T31T30T29

T14

T55

T23

T16T17

T20

T40

T41

T38T25

T21

T24

T22

T13T15

T12T11

T5

T39

T8

T10 T6T7 T9

T1 TN

T3 T2

T4

China


N

Sample sites

Wuhai




xij 1113944

p

k1gikfkj + eij (2)


Q 1113944n

i11113944

m

j1

xij minus 1113936p

k1 gikfkj

uij

⎛⎝ ⎞⎠

2

(3)


Unc 56

times MDL (4)


Unc


(5)













170ndash172


Zn (mgkg)



220ndash249


Cd (mgkg)



Ni (mgkg)



Cr (mgkg)



As (mgkg)



Hg (μgkg)


0 5 10 20 km0 5 10 20 km 0 5 10 20 km 0 5 10 20 km

0 5 10 20 km 0 5 10 20 km 0 5 10 20 km 0 5 10 20 km

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW






















Fact

or 1

conc


Fact

or 2

conc

Fa

ctor

3 co

nc

Fact

or 4

conc

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

0

20

40

60

80

100

Fact

or 4

()

0

20

40

60

80

100

Fact

or 3

()

0

20

40

60

80

100

Fact

or 2

()

0

20

40

60

80

100

Fact

or 1

()







4 Conclusions


Data Availability




Acknowledgments




References






































































23 Data Analysis




c(h) 1

2N(h)1113944

N(h)

i1Z xi( 1113857 minus Z xi + h( 11138571113858 1113859

2

1113954Z x0( 1113857 1113944N

i1λiZ xi( 1113857 (1)


T43

T45T44

T48T46

T50T49

T26

T52

T18

T19

T28T42

T27

T56

T51

T57T54T53

T47

T36T35

T37

T34

T32T33

T31T30T29

T14

T55

T23

T16T17

T20

T40

T41

T38T25

T21

T24

T22

T13T15

T12T11

T5

T39

T8

T10 T6T7 T9

T1 TN

T3 T2

T4

China


N

Sample sites

Wuhai




xij 1113944

p

k1gikfkj + eij (2)


Q 1113944n

i11113944

m

j1

xij minus 1113936p

k1 gikfkj

uij

⎛⎝ ⎞⎠

2

(3)


Unc 56

times MDL (4)


Unc


(5)













170ndash172


Zn (mgkg)



220ndash249


Cd (mgkg)



Ni (mgkg)



Cr (mgkg)



As (mgkg)



Hg (μgkg)


0 5 10 20 km0 5 10 20 km 0 5 10 20 km 0 5 10 20 km

0 5 10 20 km 0 5 10 20 km 0 5 10 20 km 0 5 10 20 km

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW






















Fact

or 1

conc


Fact

or 2

conc

Fa

ctor

3 co

nc

Fact

or 4

conc

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

0

20

40

60

80

100

Fact

or 4

()

0

20

40

60

80

100

Fact

or 3

()

0

20

40

60

80

100

Fact

or 2

()

0

20

40

60

80

100

Fact

or 1

()







4 Conclusions


Data Availability




Acknowledgments




References






































































xij 1113944

p

k1gikfkj + eij (2)


Q 1113944n

i11113944

m

j1

xij minus 1113936p

k1 gikfkj

uij

⎛⎝ ⎞⎠

2

(3)


Unc 56

times MDL (4)


Unc


(5)













170ndash172


Zn (mgkg)



220ndash249


Cd (mgkg)



Ni (mgkg)



Cr (mgkg)



As (mgkg)



Hg (μgkg)


0 5 10 20 km0 5 10 20 km 0 5 10 20 km 0 5 10 20 km

0 5 10 20 km 0 5 10 20 km 0 5 10 20 km 0 5 10 20 km

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW






















Fact

or 1

conc


Fact

or 2

conc

Fa

ctor

3 co

nc

Fact

or 4

conc

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

0

20

40

60

80

100

Fact

or 4

()

0

20

40

60

80

100

Fact

or 3

()

0

20

40

60

80

100

Fact

or 2

()

0

20

40

60

80

100

Fact

or 1

()







4 Conclusions


Data Availability




Acknowledgments




References









































































170ndash172


Zn (mgkg)



220ndash249


Cd (mgkg)



Ni (mgkg)



Cr (mgkg)



As (mgkg)



Hg (μgkg)


0 5 10 20 km0 5 10 20 km 0 5 10 20 km 0 5 10 20 km

0 5 10 20 km 0 5 10 20 km 0 5 10 20 km 0 5 10 20 km

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW

N

S

EW






















Fact

or 1

conc


Fact

or 2

conc

Fa

ctor

3 co

nc

Fact

or 4

conc

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

0

20

40

60

80

100

Fact

or 4

()

0

20

40

60

80

100

Fact

or 3

()

0

20

40

60

80

100

Fact

or 2

()

0

20

40

60

80

100

Fact

or 1

()







4 Conclusions


Data Availability




Acknowledgments




References





















































































Fact

or 1

conc


Fact

or 2

conc

Fa

ctor

3 co

nc

Fact

or 4

conc

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

10ndash4

10ndash3

10ndash2

10ndash1

100

101

102

0

20

40

60

80

100

Fact

or 4

()

0

20

40

60

80

100

Fact

or 3

()

0

20

40

60

80

100

Fact

or 2

()

0

20

40

60

80

100

Fact

or 1

()







4 Conclusions


Data Availability




Acknowledgments




References







































































4 Conclusions


Data Availability




Acknowledgments




References





































































concentrations,spatialdistributions,andsourcesofheavy...

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