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.