spatial and temporal patterns of ch 4 and n 2 o fluxes from north america as estimated by...
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Spatial and temporal patterns of CH4 and N2O fluxes from North America as estimated
by process-based ecosystem model
Hanqin Tian, Xiaofeng Xu and other ESRA Members
Ecosystem Science and Regional Analysis LaboratoryAuburn University
Non-CO2 Greenhouse Gases Workshop, Boulder, CO, October 22-24, 2008
Satellite Data
Eddy Flux
Ecosystem Experiments
Flask Data
MeasuringModeling
Synthesis
The Integrated Ecosystem Modeling Approach
DLEM
Outline
• Why do we estimate CH4 and N2O fluxes using ecosystem model?
• A case study in North America– DLEM: a process-based ecosystem model
– Site level model verification
– Comparison with other studies
– Model application on the regional level
Why do we use ecosystem modeling approach?
Attributing controls on non-CO2 fluxes
Anthropogenic and natural factors
Spatial and temporal extrapolation
Prediction
(a)(a)
The Dynamic Land Ecosystem Model
- Key components and interactions
The Dynamic Land Ecosystem Model
- Key processes, fluxes and pools
GPP
SOC
CH4 production
Atmospheric CH4 oxidation
DOC
CH4 oxidation
Net CH4 fluxes
Three methane-associated processes are incorporated in DLEM: methane production in soil, the oxidation of produced methane during transportation, atmospheric methane oxidation
Methane module of DLEM
NO3- NO2
- NH4+
NO2- NO N2O N2 NO3
-
Atmosphere
Anaerobic micro-sites
Aerobic micro-sites
Soil
Nitrification and denitrification are determined by environmental conditions as soil moisture, temperature, pH
Nitrous oxide module of DLEM
Model input data
• Climate dataset (precipitation, temperature, humidity)
• Nitrogen deposition
• Ozone concentration
• Land use and land cover change
• Historical CO2 concentration
• Fertilizer, irrigation area
Model validation for CH4 fluxes
Durham forest (42N, 73W) The observed data are from BOREAS
Site level Validation on CH4
Durham forest (42N, 73W) The observed data are from BOREAS
Model validation for N2O fluxes
N2O from wetland (33.5E, 47.58N) Observed data are from Song et al. (2008)
Method Li et al., 1996 This study
Model DNDC DLEM
Spatial resolution state 32km × 32km
US N2O emission for 1990 (no tillage and manure)
0.186-0.204 (gN/m2/year)
Cropland and pasture
0.1699 (gN/m2/year)
Cropland only
Model Intercomparison
DLEM-based estimation of CH4 and N2O emission from North America terrestrial
ecosystems
• Study Period: 1979-2005
• Spatial resolution: 32 km
• Time step: Daily
• Forces: multiple factors
1 Tundra2 Boreal broad-leaf deciduous forests3 Boreal needle-leaf evergreen forests4 Boreal needle-leaf deciduous forests5 Temperate broad-leaf deciduous forests6 Temperate broad-leaf evergreen forests7 Temperate needle-leaf evergreen forests8 Temperate needle-leaf deciduous forests9 Tropical/subtropical broad-leaf deciduous forests10 Tropical/subtropical broad-leaf evergreen forests11 Open shrub12 Close shrub13 C3 grassland14 C4 grassland15 Grass peatland16 Forest peatland17 Grass permanent wetland18 Forest permanent wetland19 Grass seasonal wetland20 Forest seasonal wetland21 Desert22 Mixed forests24 Temperate needle-leaf evergreen forests in tropical area
Input data: Climatic variability during 1979-2005
Input data: Ozone concentration
Input data: Nitrogen fertilization
Data are from FAO and USDA
9
10
11
12
13
1975 1980 1985 1990 1995 2000 2005
Date (year)
Nit
roge
n a
pp
licat
ion
(T
gN/y
ear)
Input data: Nitrogen deposition
Mean annual
CH4 fluxes for 1979-1985
Mean annual
CH4 fluxes for 1986-1995
Mean annual
CH4 fluxes for 1996-2005
Annual CH4 fluxes from Mexico, USA and Canada
Mean annual
N2O fluxes for 1979-1985
Mean annual
N2O fluxes for 1986-1995
Mean annual
N2O fluxes for 1996-2005
Annual N2O fluxes from Mexico, USA and Canada
Nitrogen fertilization effects on N2O fluxes in Conterminous US during 1945-2005
Summary• DLEM is capable of capturing spatial and temporal patterns of CH4 and
N2O fluxes in North American terrestrial ecosystems.
• DLEM could be used to quantify the relative contribution of multiple factors. Our simulated results suggest that climate (temperature and precipitation) is the primary control over interannual variability of CH4 and N2O over North America during1979- 2005, the air pollution and land cover/land use change could substantially alter the fluxes of CH4 and N2O over the region.
• Ecosystem modeling approach can add a new dimension of the NACP non-CO2 greenhouse gases synthesis.
Needs for ecosystem modeling approach to CH4 and N2O fluxes
• Data needs: – Vegetation maps, particularly wetland area/distribution
– Land management (fertilization, irrigation)
• Validation: – Site level: validate against long-term observations
– Regional Level: comparison with inverse modeling and bottom-up inventories
• Model improvement: To better address some key processes such as soil thawing.
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