IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v26y2024i2d10.1007_s10668-023-02929-3.html
   My bibliography  Save this article

Optimal allocation of water pollutant discharge permits based on Environmental Gini Coefficient (EGC): a case study of Qinhuai river basin in Nanjing, China

Author

Listed:
  • Bei Guan

    (Nanjing Research Institute of Ecology and Environmental Protection)

  • Xiuqiong Liang

    (College of Resources, Environment and Materials)

  • Yang Yang

    (Nanjing University)

  • Xiang Sun

    (College of Resources, Environment and Materials)

  • Jiawei Wang

    (College of Resources, Environment and Materials)

  • Danyi Wei

    (College of Resources, Environment and Materials)

  • Bin Wang

    (College of Resources, Environment and Materials)

  • Han Cheng

    (Nanjing Research Institute of Ecology and Environmental Protection)

Abstract

Under the constraint of water environmental carrying capacity, it is effective and insightful to control wastewater discharge and allocate water pollutant discharge permits for each pollution sources (or watershed control units) targeting at alleviating the pressure of water contamination. With a case study of Qinhuai river basin of Nanjing, China, water environmental capacity and top-down mandatory pollutants discharge reduction management were incorporated into water pollutant discharge permits decision system. In this study, a weighted multi-criteria environmental Gini coefficient method consisting of social (population), economic (gross value of industrial output), environmental (water environmental carrying capacity) and natural (land area) concerns was proposed to allocate the water pollutant discharge total phosphorus (TP) and NH3–N permits. Subsequently, based on the dual goals of minimum ECG under the constraint of water environmental carrying capacity and the limits of pollutants discharge reduction rate, the current discharge distribution, discharge permits distribution and discharge reduction distribution after allocation optimization of TP and NH3–N were obtained. The results showed that: (1) The water pollutant discharge (TP and NH3–N) permits exert a patchy configuration, and most of the watershed control units were suggested to reduce the emission by 60%. (2) After optimization, the Gini coefficients for NH3–N were lower, while the Gini coefficients for TP were increased slightly. (3) The total Gini coefficient for TP and NH3–N were all below 0.2, illustrating the water pollutant discharge permits are equity. The study shall be helpful to the policymakers to formulate total mass of pollutants control in environmental management and provide reference of further implementation of pollutant discharge permits trading system.

Suggested Citation

  • Bei Guan & Xiuqiong Liang & Yang Yang & Xiang Sun & Jiawei Wang & Danyi Wei & Bin Wang & Han Cheng, 2024. "Optimal allocation of water pollutant discharge permits based on Environmental Gini Coefficient (EGC): a case study of Qinhuai river basin in Nanjing, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(2), pages 5179-5198, February.
    • Handle: RePEc:spr:endesu:v:26:y:2024:i:2:d:10.1007_s10668-023-02929-3
    DOI: 10.1007/s10668-023-02929-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-023-02929-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10668-023-02929-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bosi, Stefano & Seegmuller, Thomas, 2006. "Optimal cycles and social inequality: What do we learn from the Gini index?," Research in Economics, Elsevier, vol. 60(1), pages 35-46, March.
    2. Druckman, A. & Jackson, T., 2008. "Measuring resource inequalities: The concepts and methodology for an area-based Gini coefficient," Ecological Economics, Elsevier, vol. 65(2), pages 242-252, April.
    3. Hu, Zhineng & Chen, Yazhen & Yao, Liming & Wei, Changting & Li, Chaozhi, 2016. "Optimal allocation of regional water resources: From a perspective of equity–efficiency tradeoff," Resources, Conservation & Recycling, Elsevier, vol. 109(C), pages 102-113.
    4. Jacobson, Arne & Milman, Anita D. & Kammen, Daniel M., 2005. "Letting the (energy) Gini out of the bottle: Lorenz curves of cumulative electricity consumption and Gini coefficients as metrics of energy distribution and equity," Energy Policy, Elsevier, vol. 33(14), pages 1825-1832, September.
    5. Yuan, Qiang & McIntyre, Neil & Wu, Yipeng & Liu, Yichao & Liu, Yi, 2017. "Towards greater socio-economic equality in allocation of wastewater discharge permits in China based on the weighted Gini coefficient," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 196-205.
    6. Patrick Moyes, 2007. "An extended Gini approach to inequality measurement," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(3), pages 279-303, December.
    7. Claudia Biancotti, 2006. "A polarization of inequality? The distribution of national Gini coefficients 1970–1996," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 4(1), pages 1-32, April.
    8. Saboohi, Y., 2001. "An evaluation of the impact of reducing energy subsidies on living expenses of households," Energy Policy, Elsevier, vol. 29(3), pages 245-252, February.
    9. Samuel Kotz & Christian Kleiber, 2002. "A characterization of income distributions in terms of generalized Gini coefficients," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 19(4), pages 789-794.
    10. Huiqin Jiang & Xinxiao Shao & Xiao Zhang & Jianqiang Bao, 2017. "A Study of the Allocation of Carbon Emission Permits among the Provinces of China Based on Fairness and Efficiency," Sustainability, MDPI, vol. 9(11), pages 1-17, November.
    11. Bertinelli, Luisito & Strobl, Eric & Zou, Benteng, 2008. "Economic development and environmental quality: A reassessment in light of nature's self-regeneration capacity," Ecological Economics, Elsevier, vol. 66(2-3), pages 371-378, June.
    12. Bing Zhang & Heng Liu & Qinqin Yu & Jun Bi, 2012. "Equity-based optimisation of regional water pollutant discharge amount allocation: a case study in the Tai Lake Basin," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 55(7), pages 885-900, October.
    13. Sun, Tao & Zhang, Hongwei & Wang, Yuan, 2013. "The application of information entropy in basin level water waste permits allocation in China," Resources, Conservation & Recycling, Elsevier, vol. 70(C), pages 50-54.
    14. Sun, Tao & Zhang, Hongwei & Wang, Yuan & Meng, Xiangming & Wang, Chenwan, 2010. "The application of environmental Gini coefficient (EGC) in allocating wastewater discharge permit: The case study of watershed total mass control in Tianjin, China," Resources, Conservation & Recycling, Elsevier, vol. 54(9), pages 601-608.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuan, Qiang & McIntyre, Neil & Wu, Yipeng & Liu, Yichao & Liu, Yi, 2017. "Towards greater socio-economic equality in allocation of wastewater discharge permits in China based on the weighted Gini coefficient," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 196-205.
    2. Sun, Tao & Zhang, Hongwei & Wang, Yuan & Meng, Xiangming & Wang, Chenwan, 2010. "The application of environmental Gini coefficient (EGC) in allocating wastewater discharge permit: The case study of watershed total mass control in Tianjin, China," Resources, Conservation & Recycling, Elsevier, vol. 54(9), pages 601-608.
    3. Meishu Wang & Hui Gong, 2018. "Imbalanced Development and Economic Burden for Urban and Rural Wastewater Treatment in China—Discharge Limit Legislation," Sustainability, MDPI, vol. 10(8), pages 1-12, July.
    4. Druckman, A. & Jackson, T., 2008. "Measuring resource inequalities: The concepts and methodology for an area-based Gini coefficient," Ecological Economics, Elsevier, vol. 65(2), pages 242-252, April.
    5. Xiao-jun Wang & Jian-yun Zhang & Shamsuddin Shahid & Amgad ElMahdi & Rui-min He & Xin-gong Wang & Mahtab Ali, 2012. "Gini coefficient to assess equity in domestic water supply in the Yellow River," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 17(1), pages 65-75, January.
    6. Zhang, Mingming & Liu, Jinghui & Liu, Liyun & Zhou, Dequn, 2023. "Inequality in urban household energy consumption for 30 Chinese provinces," Energy Policy, Elsevier, vol. 172(C).
    7. Meishu Wang & Hui Gong, 2019. "Expected Rural Wastewater Treatment Promoted by Provincial Local Discharge Limit Legislation in China," Sustainability, MDPI, vol. 11(10), pages 1-13, May.
    8. Jacqueline Hettel Tidwell & Abraham Tidwell & Steffan Nelson, 2018. "Surveying the Solar Power Gap: Assessing the Spatial Distribution of Emerging Photovoltaic Solar Adoption in the State of Georgia, U.S.A," Sustainability, MDPI, vol. 10(11), pages 1-16, November.
    9. Zhaojun Wang & Amanda M. Countryman & James J. Corbett & Mandana Saebi, 2021. "Economic and environmental impacts of ballast water management on Small Island Developing States and Least Developed Countries," Papers 2108.13315, arXiv.org.
    10. Wang, Qiang & Kwan, Mei-Po & Fan, Jie & Lin, Jian, 2021. "Racial disparities in energy poverty in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    11. Hellinton H. Takada & Celma O. Ribeiro & Oswaldo L. V. Costa & Julio M. Stern, 2020. "Gini and Entropy-Based Spread Indexes for Primary Energy Consumption Efficiency and CO 2 Emission," Energies, MDPI, vol. 13(18), pages 1-17, September.
    12. Chen, Haitao & Zhang, Bin & Wang, Zhaohua, 2022. "Hidden inequality in household electricity consumption: Measurement and determinants based on large-scale smart meter data," China Economic Review, Elsevier, vol. 71(C).
    13. Overland, Indra & Juraev, Javlon & Vakulchuk, Roman, 2022. "Are renewable energy sources more evenly distributed than fossil fuels?," Renewable Energy, Elsevier, vol. 200(C), pages 379-386.
    14. Tan, Kun & Zhao, Xiaoqing & Pu, Junwei & Li, Sinan & Li, Yuhao & Miao, Peipei & Wang, Qian, 2021. "Zoning regulation and development model for water and land resources in the Karst Mountainous Region of Southwest China," Land Use Policy, Elsevier, vol. 109(C).
    15. Sovacool, Benjamin K., 2011. "Conceptualizing urban household energy use: Climbing the "Energy Services Ladder"," Energy Policy, Elsevier, vol. 39(3), pages 1659-1668, March.
    16. Steinberger, Julia K. & Krausmann, Fridolin & Eisenmenger, Nina, 2010. "Global patterns of materials use: A socioeconomic and geophysical analysis," Ecological Economics, Elsevier, vol. 69(5), pages 1148-1158, March.
    17. Karbassi, Veis & Trotter, Philipp A. & Walther, Grit, 2023. "Diversifying the African energy system: Economic versus equitable allocation of renewable electricity and e-fuel production," Applied Energy, Elsevier, vol. 350(C).
    18. Sovacool, Benjamin K. & Kester, Johannes & Noel, Lance & de Rubens, Gerardo Zarazua, 2019. "Energy Injustice and Nordic Electric Mobility: Inequality, Elitism, and Externalities in the Electrification of Vehicle-to-Grid (V2G) Transport," Ecological Economics, Elsevier, vol. 157(C), pages 205-217.
    19. AZOMAHOU, Théophile & BOUCEKKINE, Raouf & NGUYEN-VAN, Phu, 2009. "Promoting clean technologies under imperfect competition," LIDAM Discussion Papers CORE 2009011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. Carmen Puerta & Ana Urrutia, 2012. "Lower and upper tail concern and the rank dependent social evaluation functions," Economics Bulletin, AccessEcon, vol. 32(4), pages 3250-3259.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:endesu:v:26:y:2024:i:2:d:10.1007_s10668-023-02929-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.