Research and Development/Tech Change/Emerging Technologies, Resource /Energy Economics and Policy,

Cai, Yongxia

Cronin, Timothy W.

Gurgel, Angelo Costa

Kicklighter, David W.

Melillo, Jerry M.

Paltsev, Sergey

Reilly, John M.

English

Research Papers in Economics

 
 
 
Green House Gas Mitigation Policy, Bio-fuels and Land-use Change 
- a Dynamic Analysis 
              Yongxia Cai
1, David W. Kicklighter
2, Angelo Gurgel
1, Sergey Paltsev
1, Timothy W. 
Cronin
1, John M. Reilly
1, Jerry M. Melillo
2 
               1 Joint Program on the Science and Policy of Global Change, Massachusetts Institute of 
Technology 
               2 The Ecosystems Center, Marine Biological Laboratory 
 
 
 
 
Poster prepared for presentation at the Agricultural & Applied Economics Association 2010 
AAEA, CAES, & WAEA Joint Annual Meeting, Denver, Colorado, July 25-27, 2010 
 
 
 
 
 
 
 
 
 
 
Copyright 2010 by Yongxia Cai. All rights reserved. Readers may make verbatim copies of this 
document for non-commercial purposes by any means, provided that this copyright notice 
appears on all such copies. Green House Gas Mitigation Policy, Bio-fuels and Land-use Change - a Dynamic Analysis
Yongxia Cai1, David W. Kicklighter2, Angelo Gurgel1, Sergey Paltsev1,Timothy W. Cronin1, John M. Reilly1, Jerry M. Melillo2
1. Motivation
2. Methodology
4. Future Work
Agricultural green house gas (GHG) emissions, GHG mitigation policy, climate, 
biofuels, land-use changes and economic activities are highly interactive. Previous 
investigations have, at best, loosely linked models that describe these components or 
more often have focused on one way interactions. 
Within the MIT Integrated Global System Model (IGSM) framework, we develop a 
dynamic linkage between an complex economic model– MIT Emissions Prediction and 
Policy Analysis (EPPA) model and the Terrestrial Ecosystem Model (TEM) from Marine 
Biology Laboratory (MBL) to study the dynamic interactions of greenhouse gas 
emissions policy, land-use activities and the implications for second generation biofuels 
production.
EPPA is a multi-sector, multi-region 
computable general equilibrium (CGE) 
model of the world economy with 16 
regions and 21 sectors. EPPA 
simulates the economy recursively at 
5-year intervals from 2000 to 2100.
TEM is an ecosystem model that 
describes carbon and nitrogen 
dynamics of plants and soils for 
terrestrial ecosystems of the globe. The 
TEM operates on a monthly time step 
and at a grid-cell spatial resolution of 
0.5 x 0.5 latitude by longitudes. 
Figure 1. IGSM - Integrated Global System Modeling Framework
(Source: http://globalchange.mit.edu/igsm/index.html)
3.1 Global land productivity ( area weighted NPP index)   
Crop                               Managed forest                         Pasture                             Natural forest  Natural grass
3.3 Global land use in 2000, 2050 and 2100 (billion ha)  3.2 Biomass energy production (EJ/year)
Figure 2. EPPA -TEM linkage
3.4 Regional land used for bio-fuel production (billion ha)
No_ref                                       No_pol                                         Yes_ref         Yes_pol
a. We aggregate productivity changes 
from TEM to the regional scale for EPPA.  
b. EPPA simulates green house gas 
emissions as input to IGSM and 
estimates regional land use.
c. IGSM simulates future climate: 
temperature, precipitation, CO2 and O3
concentrations.
d. A cross section econometric land 
use model is used to downscale regional 
land use information from EPPA to the 
grid level of TEM.
2.3 Scenario analysis 
Linkage scenario: Yes -- the dynamic linkage
No -- the loose linkage in Wang (2008) and Mellio et al (2009)
Policy scenario:    Ref -- no policies to mitigate green house gas emissions
Pol -- 550 ppm CO2 stabilization policy
2.1 IGSM Review
2.2 Dynamic linkage
3. Results
4. Conclusion
• With dynamic linkage, managed forest land and natural forest land are more productive, pasture land less productive, little effect 
on productivity of crop land and natural grass land under both the policy and reference case.
• Climate mitigation policy leads to large-scale bio-fuels energy. As a result, managed forest, pasture, natural forest and natural 
grass land are diverted to produce biomass. Dynamic linkage results in further reduction of managed forest, especially in Africa, Latin 
America and United States.
1 Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology
2 The Ecosystems Center, Marine Biological Laboratory
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Green House Gas Mitigation Policy, Bio-fuels and Land-use Change- a Dynamic Analysis

Green House Gas Mitigation Policy, Bio-fuels and Land-use Change- a Dynamic Analysis

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