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<p>Waste-to-Energy (WTE) power plants are vital for sustainable waste management and renewable energy, but their operation raises significant public health concerns due to atmospheric emissions. Existing research often overlooks comprehensive population exposure assessments and lacks integrated approaches for spatial siting, stack height optimization under real-world air quality constraints and the incorporation of carbon credit revenue with profit-exposure weighting scenarios in receptor-centric models. This study develops a novel multi-objective optimization model within an integrated GIS-AERMOD-GAMS framework to address these gaps. Our model concurrently maximizes total profit and minimizes total sensitive receptor exposure to key pollutants, strictly enforcing plant-level emission constraints. The analysis identifies the C400 (RM400/ton CO<sub>2</sub>) as the Optimal Environmental Intervention Price, consistently incentivizing the environmentally superior 120&#xa0;m stack even in high-profit scenarios (Wprofit ≤ 0.9). Results confirm the effectiveness of regulatory mandates, where solutions prioritizing human exposure (Wexposure ≥ 0.05) demonstrate optimal outcomes, while profit-driven solutions (Wprofit = 1.0) favour less protective 100&#xa0;m stacks. The framework provides a systematic methodology for sustainable WTE planning, applied to Pasir Gudang, Malaysia. Spatial analysis of Pasir Gudang identified four potential WTE locations and 17 sensitive receptors. The multi-objective optimization model achieved a 30.63% reduction in sensitive receptor exposure with a negligible 0.50% cost increase. The integrated optimization analysis reveals that regulatory policy levers like exposure weighting thresholds and stack height mandates can significantly reduce environmental impact. In addition, the findings highlight the importance of strategic site selection in balancing environmental protection and economic viability for WTE planning.</p>

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Multi-objective optimisation for waste-to-energy planning towards sustainability development

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月2日

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  • Adeline Zhi Li Tan,
  • Wai Shin Ho,
  • Mimi H. Hassim,
  • Faizuan Abdullah,
  • Li Yee Lim

摘要

Waste-to-Energy (WTE) power plants are vital for sustainable waste management and renewable energy, but their operation raises significant public health concerns due to atmospheric emissions. Existing research often overlooks comprehensive population exposure assessments and lacks integrated approaches for spatial siting, stack height optimization under real-world air quality constraints and the incorporation of carbon credit revenue with profit-exposure weighting scenarios in receptor-centric models. This study develops a novel multi-objective optimization model within an integrated GIS-AERMOD-GAMS framework to address these gaps. Our model concurrently maximizes total profit and minimizes total sensitive receptor exposure to key pollutants, strictly enforcing plant-level emission constraints. The analysis identifies the C400 (RM400/ton CO2) as the Optimal Environmental Intervention Price, consistently incentivizing the environmentally superior 120 m stack even in high-profit scenarios (Wprofit ≤ 0.9). Results confirm the effectiveness of regulatory mandates, where solutions prioritizing human exposure (Wexposure ≥ 0.05) demonstrate optimal outcomes, while profit-driven solutions (Wprofit = 1.0) favour less protective 100 m stacks. The framework provides a systematic methodology for sustainable WTE planning, applied to Pasir Gudang, Malaysia. Spatial analysis of Pasir Gudang identified four potential WTE locations and 17 sensitive receptors. The multi-objective optimization model achieved a 30.63% reduction in sensitive receptor exposure with a negligible 0.50% cost increase. The integrated optimization analysis reveals that regulatory policy levers like exposure weighting thresholds and stack height mandates can significantly reduce environmental impact. In addition, the findings highlight the importance of strategic site selection in balancing environmental protection and economic viability for WTE planning.