Cost accounting-based assessment of the net social benefit of German waste-to-energy plants under stricter environmental valuation: Public-record evidence from 2017 to 2023

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Type of the article: Research Article

Abstract
Municipal waste-to-energy is often assessed through technical efficiency, energy output, or regulatory compliance. Yet, these indicators do not show whether plants create positive social welfare after operating costs and environmental damages are monetized. This study examines how operational performance, emissions intensity, and stricter environmental valuation shape the net social benefit of German municipal waste-to-energy plants from 2017 to 2023. Germany serves as a benchmark case because its mature waste-to-energy sector, European emissions regulation, and public environmental and energy-market reporting enable transparent public-record welfare assessment. The study constructs a plant-year analytical dataset for 70 facilities from publicly accessible administrative, environmental, market, and technical records, with net social benefit treated as a constructed welfare-accounting measure based on observed records, documented public proxies, and explicit valuation assumptions. It uses plant- and year-fixed-effects models, valuation sensitivity tests, and an optimization-based decision-support layer. The descriptive evidence shows substantial welfare heterogeneity, with a mean traceable-baseline net social benefit of 17.9 euros per metric ton under the central valuation case and lower mean welfare under higher shadow prices. The fixed-effects results do not provide statistical support for the hypothesized operational drivers in the public-data panel: energy recovery, emissions intensity, availability, oxygen instability, and the interaction between emissions intensity and the shadow price index are not statistically significant. The study contributes by integrating cost accounting, externality valuation, and operational performance into a transparent public-record welfare metric for policy appraisal.

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    • Table 1. Descriptive statistics for plant–year variables (Germany, 2017–2023)
    • Table 2. NSB decomposition based on traceable baseline components (€/t), sample mean (Germany, 2017–2023)
    • Table 3. Fixed-effects estimates for NSB (€/t), hypothesis tests (Germany, 2017–2023)
    • Table 4. Shadow-price sensitivity of NSB and key coefficients (Germany, 2017–2023)
    • Table 5. GA–ANFIS operating configurations and implied NSB (central valuation case)
    • Table A1. Municipal solid waste incineration (MSWI) plants in the analytical frame (n = 66)
    • Table A2. RDF power plants included in the analytical sample (to complete n = 70)
    • Table A3. Variable provenance and construction status used to construct the analytical dataset
    • Conceptualization
      Arwa H. Amoush, Salah Kayed
    • Data curation
      Arwa H. Amoush, Abdulhadi Ramadan, Almotasem Al Huniti, Salah Kayed
    • Formal Analysis
      Arwa H. Amoush, Abdulhadi Ramadan, Almotasem Al Huniti, Salah Kayed
    • Investigation
      Arwa H. Amoush, Salah Kayed
    • Resources
      Arwa H. Amoush, Abdulhadi Ramadan, Salah Kayed
    • Validation
      Arwa H. Amoush, Salah Kayed
    • Visualization
      Arwa H. Amoush
    • Writing – original draft
      Arwa H. Amoush, Salah Kayed
    • Methodology
      Abdulhadi Ramadan, Almotasem Al Huniti, Salah Kayed
    • Software
      Abdulhadi Ramadan, Almotasem Al Huniti
    • Writing – review & editing
      Abdulhadi Ramadan, Almotasem Al Huniti
    • Funding acquisition
      Almotasem Al Huniti
    • Project administration
      Salah Kayed
    • Supervision
      Salah Kayed