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<p>This study presents a spatially explicit optimization framework to support subnational climate policy in Vietnam’s livestock sector. By integrating a genetic algorithm with district-level emissions modeling, we have identified cost-effective allocations of eight mitigation options in Quang Binh province to help meet the national methane reduction target of 12.39% by 2030. Drawing on livestock census data, IPCC emission factors, and region-specific marginal abatement costs (MACs), the model generates scenarios that achieve reductions of 13.9–29.3% in provincial GHG emissions. The most effective measures, which are biochar supplementation for cattle and silage feeding for buffaloes, not only deliver the greatest emission reductions at the lowest MACs, but also improve livestock productivity, offering strong economic co-benefits. Other interventions such as manure separation and expanded biogas systems also yield high mitigation potential, particularly when supported by carbon revenues or external incentives. With a net abatement cost of − 7.268 million USD and economic gains of 7.627 million USD under a carbon price of 5 USD/tCO₂eq, our approach demonstrates how targeted, locally grounded strategies can align economic development with national climate goals. While simplified in terms of its behavioral assumptions, the model offers a practical, scalable tool for low-emission planning in data-constrained contexts and is transferable to other provinces under Vietnam’s climate commitments.</p>

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Economic Coordination for Climate Policy: Optimizing Livestock Sector Emission Reduction Using Genetic Algorithms and Agent-Based Modeling in Quang Binh, Vietnam

  • 期刊论文

  • 发表日期：

    2025年7月28日

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  • An The Ngo,
  • Linda See,
  • Trinh Van Mai

摘要

This study presents a spatially explicit optimization framework to support subnational climate policy in Vietnam’s livestock sector. By integrating a genetic algorithm with district-level emissions modeling, we have identified cost-effective allocations of eight mitigation options in Quang Binh province to help meet the national methane reduction target of 12.39% by 2030. Drawing on livestock census data, IPCC emission factors, and region-specific marginal abatement costs (MACs), the model generates scenarios that achieve reductions of 13.9–29.3% in provincial GHG emissions. The most effective measures, which are biochar supplementation for cattle and silage feeding for buffaloes, not only deliver the greatest emission reductions at the lowest MACs, but also improve livestock productivity, offering strong economic co-benefits. Other interventions such as manure separation and expanded biogas systems also yield high mitigation potential, particularly when supported by carbon revenues or external incentives. With a net abatement cost of − 7.268 million USD and economic gains of 7.627 million USD under a carbon price of 5 USD/tCO₂eq, our approach demonstrates how targeted, locally grounded strategies can align economic development with national climate goals. While simplified in terms of its behavioral assumptions, the model offers a practical, scalable tool for low-emission planning in data-constrained contexts and is transferable to other provinces under Vietnam’s climate commitments.