Keywords
agent-based modeling, low-carbon agricultural policies, land-use and land-cover change, life-cycle assessment, Brazilian Amazon
Location
Session H4: Modeling for Low Carbon Economies
Start Date
19-6-2014 9:00 AM
End Date
19-6-2014 10:20 AM
Abstract
Agriculture and agriculture-inflicted land use change is a major source of greenhouse gas (GHG) emissions. Reducing excessive deforestation and intensification of agricultural land use and consequently reducing associated GHG emissions is an important pathway of transition to a global low-carbon economy. Adoption of low-carbon agricultural systems and practices requires setting appropriate economic incentives for land users through smart policy instruments. For effective implementation of such instruments integrated ex-ante policy assessments are crucial. In this article we discuss and illustrate the benefits and potentials of applying multi-agent system models for the assessment of low-carbon policies and technologies. As an empirical example we discuss the use of the software package MPMAS that we are currently deploying for the assessment of impacts of low-carbon technologies and policies in the Southern part of Brazilian Amazon. Our agent-based application implements one-to-one correspondence between real-world farms and computational agents and is able to realize spatially explicit simulations of farm behavior. MPMAS is externally coupled with the dynamic, process-based crop growth model MONICA hereby interlinking economic behavior of farms with processes of carbon, nitrogen and water turnover. The values of GHG emissions are simulated by the biochemistry model DNDC, which was calibrated in situ based on empirical measurements. Our application has a graphical GIS-interface that can inform policy evaluators about simulated results.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
Assessment of Policies for Low-Carbon Agriculture by means of Multi-Agent Simulation
Session H4: Modeling for Low Carbon Economies
Agriculture and agriculture-inflicted land use change is a major source of greenhouse gas (GHG) emissions. Reducing excessive deforestation and intensification of agricultural land use and consequently reducing associated GHG emissions is an important pathway of transition to a global low-carbon economy. Adoption of low-carbon agricultural systems and practices requires setting appropriate economic incentives for land users through smart policy instruments. For effective implementation of such instruments integrated ex-ante policy assessments are crucial. In this article we discuss and illustrate the benefits and potentials of applying multi-agent system models for the assessment of low-carbon policies and technologies. As an empirical example we discuss the use of the software package MPMAS that we are currently deploying for the assessment of impacts of low-carbon technologies and policies in the Southern part of Brazilian Amazon. Our agent-based application implements one-to-one correspondence between real-world farms and computational agents and is able to realize spatially explicit simulations of farm behavior. MPMAS is externally coupled with the dynamic, process-based crop growth model MONICA hereby interlinking economic behavior of farms with processes of carbon, nitrogen and water turnover. The values of GHG emissions are simulated by the biochemistry model DNDC, which was calibrated in situ based on empirical measurements. Our application has a graphical GIS-interface that can inform policy evaluators about simulated results.
