How a Pareto frontier complements scenario projections in land use change impact assessment. (November 2017)

• Record Type: Journal Article
• Authors: Verstegen, Judith A.; Jonker, Jan Gerrit Geurt; Karssenberg, Derek; van der Hilst, Floor; Schmitz, Oliver; de Jong, Steven M.; Faaij, André P.C.
• Is Part Of: Environmental modelling & software. Volume 97(2017)
• Page Start: 287
• Page End: 302
• Publication Date: 2017-11
• Subjects: Pareto frontier -- Ethanol -- Optimization -- Brazil -- Genetic algorithm -- GHG emissions; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.08.006
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: To evaluate the sustainability of potential agricultural land developments, scenario projections with land use change models are often combined with environmental impact assessments. Although this allows inter-scenario comparison of impacts, it does not permit interpretation of scenarios in the light of theoretically optimal impacts. A Pareto frontier provides this information. We demonstrate this for ethanol production in Goiás, Brazil, in 2030. For a Business-as-Usual scenario projection, the spatial configuration, production costs, and GHG emissions of the production chain are compared with those obtained from spatial optimization and summarized by the Pareto frontier. Projected production costs are 729 $/m 3 ethanol, with GHG emissions of 40 kg CO2 -eq/m 3 ethanol. The Pareto frontier indicates an improvement potential of ∼50 $/m 3 ethanol when keeping emissions fixed, or ∼250 kg CO2 -eq/m 3 ethanol when keeping costs fixed. Robust locations having low costs and emissions show where and how improvements are reached, offering instruments for policy (re)design. Highlights: Linking scenario impacts to a Pareto frontier allows assessing scenario performance. From this performance assessment, improvement quantity and location can be derived. Robust locations and/or characteristics offer information for land policy redesign. Case study assesses future production costs and GHG emissions of ethanol in Goiás. Constrained improvements for 2030 are ∼50 $ or ∼250 kg CO2 -eq per m 3 ethanol.