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dc.contributor.advisorKaren R. Polenske.en_US
dc.contributor.authorWang, Xiaodong, Ph. D. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Urban Studies and Planning.en_US
dc.date.accessioned2008-09-03T15:35:08Z
dc.date.available2008-09-03T15:35:08Z
dc.date.copyright2008en_US
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/42412
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2008.en_US
dc.descriptionIncludes bibliographical references (p. 155-162).en_US
dc.description.abstractGreenhouse gas (GHG) emissions are widely acknowledged to be responsible for much of the global warming in the past century. A number of approaches have been proposed to mitigate GHG emissions. Since the burning of fossil-based fuels is an important source of GHGs, the policies on GHG-mitigation encourage the replacement of fossil-based energy with biomass energy. However, a large-scale development of biomass energy may lead to changes in agricultural land use, which are important sources of GHG emissions, and therefore undermine the effectiveness of GHG-mitigation policies. In this research, I analyze the impacts of GHG-mitigation policies on five types of agricultural land (cropland, managed forestry land, pasture land, un-managed forestry land, and un-managed grassland) as well as carbon stored in such land during the 21st century. The scholars in the MIT Joint Program of Science and Policy on Global Change use the Integrated Global Systems Model (IGSM) to simulate changes in climate in response to GHG-mitigation policies, while the researchers at the U. S. Marine Biological Laboratory (MBL) apply the Terrestrial Ecosystem Model (TEM) to simulate land productivities. Based on the predictions of land characteristics affecting land-use decisions, I develop an econometric model to predict the land use affected by climate, GHGs, and tropospheric ozone at the grid-cell scale of 0.5 * 0.5 longitude by latitude. I use the Emissions Prediction and Policy Analysis (EPPA) model to capture the regional land use driven by economic forces. Then, I develop the downscaling methods to link these two land-use effects. I conduct this research in two scenarios: in the baseline, I assume that there are no policies to mitigate GHG emissions during the 21st century; in the policy scenario, I assume that there are specific policies to limit GHG emissions during the 21st century.en_US
dc.description.abstract(cont.) I confirm the hypothesis that biomass-energy production would lead to the conversion of the five types of agricultural land, and the carbon stored in such land would decrease; the GHG-mitigation policies, leading to more production of biomass energy and conversion of agricultural land, would cause an even more severe loss of the carbon stored in agricultural land. Although the GHG-mitigation policies would generally reduce the atmospheric GHG emissions by using more energy from biomass, such endeavors would be partly counteracted by the land-use conversion as a result of large-scale production of biomass energy.en_US
dc.description.statementofresponsibilityby Xiaodong Wang.en_US
dc.format.extent162 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectUrban Studies and Planning.en_US
dc.titleImpacts of greenhouse gas mitigation policies on agricultural landen_US
dc.title.alternativeImpacts of GHG mitigation policies on agricultural landen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Urban Studies and Planning
dc.identifier.oclc237214321en_US


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