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A dynamic programming model for environmental investment decision-making in coal mining

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  • Yu, Shiwei
  • Gao, Siwei
  • sun, Han

Abstract

Coal is the widespread fossil fuel on earth. It provides the necessary material foundation for economic development of a country. However, coal mining activities cause a lot of environmental impacts that are hazardous to the health of citizens in mining regions and place costs on the government. According to government laws and regulations, coal mines should invest in related pollution treatment projects to meet the emission standards. How to allocate the limited resources among a set of pollutant treatment projects to minimize the total losses, including penal loss and vacancy loss, from an investment perspective is a typical decision-making problem. Therefore, the present study proposed a discrete dynamic programming procedure to provide an effective solution for decision-making in treatment project investment. Furthermore, a case study involving the Laojuntang coal mine of Zhengzhou Coal Industry (Group) of China on the treatment project investment problem was implemented using the proposed model. The results demonstrate that the proposed model is effective and applicable for environmental investment decision-making at a typical coal mine in terms of minimizing the total losses.

Suggested Citation

  • Yu, Shiwei & Gao, Siwei & sun, Han, 2016. "A dynamic programming model for environmental investment decision-making in coal mining," Applied Energy, Elsevier, vol. 166(C), pages 273-281.
    • Handle: RePEc:eee:appene:v:166:y:2016:i:c:p:273-281
    DOI: 10.1016/j.apenergy.2015.09.099
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    Cited by:

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    2. Lucrezia Manservigi & Mattia Cattozzo & Pier Ruggero Spina & Mauro Venturini & Hilal Bahlawan, 2020. "Optimal Management of the Energy Flows of Interconnected Residential Users," Energies, MDPI, vol. 13(6), pages 1-21, March.
    3. Linfeng Li & Miyuan Shan & Ying Li & Sheng Liang, 2017. "A Dynamic Programming Model for Operation Decision-Making in Bicycle Sharing Systems under a Sustainable Development Perspective," Sustainability, MDPI, vol. 9(6), pages 1-21, June.
    4. Nadiia Charkovska & Mariia Halushchak & Rostyslav Bun & Zbigniew Nahorski & Tomohiro Oda & Matthias Jonas & Petro Topylko, 2019. "A high-definition spatially explicit modelling approach for national greenhouse gas emissions from industrial processes: reducing the errors and uncertainties in global emission modelling," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 907-939, August.
    5. Amiri, Leyla & Ghoreishi-Madiseh, Seyed Ali & Sasmito, Agus P. & Hassani, Ferri P., 2018. "Effect of buoyancy-driven natural convection in a rock-pit mine air preconditioning system acting as a large-scale thermal energy storage mass," Applied Energy, Elsevier, vol. 221(C), pages 268-279.
    6. Moriah Bostian & Rolf Färe & Shawna Grosskopf & Tommy Lundgren & William L. Weber, 2018. "Time substitution for environmental performance: The case of Swedish manufacturing," Empirical Economics, Springer, vol. 54(1), pages 129-152, February.
    7. Xin Nie & Jianxian Wu & Han Wang & Lihua Li & Chengdao Huang & Weijuan Li & Zhuxia Wei, 2022. "Booster or Stumbling Block? The Role of Environmental Regulation in the Coupling Path of Regional Innovation under the Porter Hypothesis," Sustainability, MDPI, vol. 14(5), pages 1-20, March.
    8. Fulei Shi & Haiqing Cao & Chuansheng Wang & Cuiyou Yao, 2020. "A System Dynamics Model for Ecological Environmental Management in Coal Mining Areas in China," IJERPH, MDPI, vol. 17(6), pages 1-17, March.

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