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Developing a conceptual model to quantify eco-compensation based on environmental and economic cost-benefit analysis for promoting the ecologically intensified agriculture

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  • Zhen, Huayang
  • Qiao, Yuhui
  • Zhao, Haijun
  • Ju, Xuehai
  • Zanoli, Raffaele
  • Waqas, Muhammad Ahmed
  • Lun, Fei
  • Knudsen, Marie Trydeman

Abstract

Eco-compensation is essential for promoting ecologically intensive agriculture to reduce the environmental impact of the agricultural sector. However, a comprehensive and performance-based tool to quantify eco-compensation is not yet available. Here, we present a comprehensive model of eco-compensation standards based on internal and external trade-offs (ESBIET) and their valuation methods based on farm-level cost-benefit analysis. We calculated the internal economic costs and benefits using conventional life cycle costing and profit analysis. The ecosystem service and disservice values were recorded as external benefits and costs, which were valued using the revealed preference approach and the Environmental Priorities Strategies model, respectively. We incorporated the Coase theorem and Pigou theory into this model to quantify government compensation, which complements market compensation. The ESBIET model was tested using a case study of greenhouse vegetable production in eight conventional (CON), eight organic (ORG), and seven community-supported agriculture (CSA) greenhouse vegetable production farms. This article also described the key features, potential users and future opportunities for improving our ESBITE model. At its core, the ESBIET model can be effectively used to design eco-compensation measures to promote ecologically intensified agriculture.

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  • Zhen, Huayang & Qiao, Yuhui & Zhao, Haijun & Ju, Xuehai & Zanoli, Raffaele & Waqas, Muhammad Ahmed & Lun, Fei & Knudsen, Marie Trydeman, 2022. "Developing a conceptual model to quantify eco-compensation based on environmental and economic cost-benefit analysis for promoting the ecologically intensified agriculture," Ecosystem Services, Elsevier, vol. 56(C).
    • Handle: RePEc:eee:ecoser:v:56:y:2022:i:c:s2212041622000389
    DOI: 10.1016/j.ecoser.2022.101442
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