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Efficiency Evaluation of Atmospheric Pollutants Emission in Zhejiang Province China: A DEA-Malmquist Based Approach

Author

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  • Ying-yu Lu

    (Department of Public Course Teaching, Ningbo Polytechnic, Ningbo 315800, Zhejiang, China)

  • Yue He

    (School of International Business & Languages, Ningbo Polytechnic, Ningbo 315800, Zhejiang, China)

  • Bo Wang

    (School of International Business & Languages, Ningbo Polytechnic, Ningbo 315800, Zhejiang, China)

  • Shuang-shuang Ye

    (School of International Business & Languages, Ningbo Polytechnic, Ningbo 315800, Zhejiang, China)

  • Yidi Hua

    (School of International Business & Languages, Ningbo Polytechnic, Ningbo 315800, Zhejiang, China
    Institue of Environmental Economics Research, Ningbo Polytechnic, Ningbo 315800, Zhejiang, China)

  • Lei Ding

    (School of International Business & Languages, Ningbo Polytechnic, Ningbo 315800, Zhejiang, China
    Institue of Environmental Economics Research, Ningbo Polytechnic, Ningbo 315800, Zhejiang, China)

Abstract

In order to sustainably and reasonably evaluate the characteristics and efficiency of regional atmospheric environment, this paper calculated the atmospheric environmental efficiency and regional differences, which is based on the non-radial directional distance function DEA model, among 11 cities in Zhejiang Province from 2006 to 2016 in both static and dynamic dimensions. Compared with existing researches, the atmospheric environmental efficiency evaluation system constructed in this paper not only considered the development of regional economy, but also focused on the air quality output so as to constrain the emission of atmospheric pollutants. The results showed that the average value of the static efficiency of atmospheric environment in Zhejiang was 0.6824 over the past ten years, and there was still about 32 percentage difference from the production frontier. The room for improvement in pollution reduction and control was still huge. The pure technical efficiency was the main factor to impede the improvement of atmospheric environment’s static efficiency in Zhejiang. Meanwhile the dynamic efficiency of atmospheric environment in Zhejiang reached an average annual rate of 7.60%, with a cumulative increase of 93.28%. As well, there were significant urban differences in the growth rate, of which Hangzhou was the fastest, followed by Ningbo and Jiaxing. The improvement of atmospheric environmental efficiency was mainly driven by technological advancement and scale efficiency expansion. The distribution of 11 cities in the four high and low environmental efficiency matrices was relatively uniform, and there was no “Matthew Effect” of H/H or L/L polarization. In the future, Zhejiang needs to formulate corresponding measures to control the atmospheric pollution by fully considering the actual conditions at different cities, and effectively strengthen the environmental management exchanges and collaboration within the province to enhance the overall atmospheric environment efficiency.

Suggested Citation

  • Ying-yu Lu & Yue He & Bo Wang & Shuang-shuang Ye & Yidi Hua & Lei Ding, 2019. "Efficiency Evaluation of Atmospheric Pollutants Emission in Zhejiang Province China: A DEA-Malmquist Based Approach," Sustainability, MDPI, vol. 11(17), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:17:p:4544-:d:259689
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    References listed on IDEAS

    as
    1. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    2. Shi Wang & Hua Wang & Li Zhang & Jun Dang, 2019. "Provincial Carbon Emissions Efficiency and Its Influencing Factors in China," Sustainability, MDPI, vol. 11(8), pages 1-21, April.
    3. Banker, Rajiv D. & Thrall, R. M., 1992. "Estimation of returns to scale using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 62(1), pages 74-84, October.
    4. Jin Zhu & Dequn Zhou & Zhengning Pu & Huaping Sun, 2019. "A Study of Regional Power Generation Efficiency in China: Based on a Non-Radial Directional Distance Function Model," Sustainability, MDPI, vol. 11(3), pages 1-18, January.
    5. Zhuang Miao & Tomas Baležentis & Zhihua Tian & Shuai Shao & Yong Geng & Rui Wu, 2019. "Environmental Performance and Regulation Effect of China’s Atmospheric Pollutant Emissions: Evidence from “Three Regions and Ten Urban Agglomerations”," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(1), pages 211-242, September.
    6. Ronggang Zhang & Ching-Cheng Lu & Jen-Hui Lee & Ying Feng & Yung-Ho Chiu, 2019. "Dynamic Environmental Efficiency Assessment of Industrial Water Pollution," Sustainability, MDPI, vol. 11(11), pages 1-12, May.
    7. Richard Perkins & Eric Neumayer, 2008. "Fostering Environment Efficiency through Transnational Linkages? Trajectories of CO2 and SO2, 1980–2000," Environment and Planning A, , vol. 40(12), pages 2970-2989, December.
    8. Iftikhar, Yaser & Wang, Zhaohua & Zhang, Bin & Wang, Bo, 2018. "Energy and CO2 emissions efficiency of major economies: A network DEA approach," Energy, Elsevier, vol. 147(C), pages 197-207.
    9. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    10. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers," Economic Journal, Royal Economic Society, vol. 92(365), pages 73-86, March.
    11. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    12. Liang-han Ma & Jin-chi Hsieh & Yung-ho Chiu, 2019. "A Study on the Effects of Energy and Environmental Efficiency at China’s Provincial Level," Energies, MDPI, vol. 12(4), pages 1-13, February.
    13. Xiangyu Teng & Liang Chun Lu & Yung-ho Chiu, 2018. "Considering Emission Treatment for Energy-Efficiency Improvement and Air Pollution Reduction in China’s Industrial Sector," Sustainability, MDPI, vol. 10(11), pages 1-18, November.
    14. Lee, Taehwee & Yeo, Gi-Tae & Thai, Vinh V., 2014. "Environmental efficiency analysis of port cities: Slacks-based measure data envelopment analysis approach," Transport Policy, Elsevier, vol. 33(C), pages 82-88.
    15. Reinhard, Stijn & Knox Lovell, C. A. & Thijssen, Geert J., 2000. "Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA," European Journal of Operational Research, Elsevier, vol. 121(2), pages 287-303, March.
    16. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    17. Kapelko, M. & Horta, I.M. & Camanho, A.S. & Oude Lansink, A., 2015. "Measurement of input-specific productivity growth with an application to the construction industry in Spain and Portugal," International Journal of Production Economics, Elsevier, vol. 166(C), pages 64-71.
    18. Huang, Junbing & Du, Dan & Hao, Yu, 2017. "The driving forces of the change in China's energy intensity: An empirical research using DEA-Malmquist and spatial panel estimations," Economic Modelling, Elsevier, vol. 65(C), pages 41-50.
    19. Chen, Yao & Iqbal Ali, Agha, 2004. "DEA Malmquist productivity measure: New insights with an application to computer industry," European Journal of Operational Research, Elsevier, vol. 159(1), pages 239-249, November.
    20. Mariam Camarero & Juana Castillo & Andrés Picazo-Tadeo & Cecilio Tamarit, 2013. "Eco-Efficiency and Convergence in OECD Countries," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 55(1), pages 87-106, May.
    21. Akber Aman Shah & Desheng Wu & Vladmir Korotkov, 2019. "Are Sustainable Banks Efficient and Productive? A Data Envelopment Analysis and the Malmquist Productivity Index Analysis," Sustainability, MDPI, vol. 11(8), pages 1-19, April.
    22. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    23. Liu, Xiaozi & Heilig, Gerhard K. & Chen, Junmiao & Heino, Mikko, 2007. "Interactions between economic growth and environmental quality in Shenzhen, China's first special economic zone," Ecological Economics, Elsevier, vol. 62(3-4), pages 559-570, May.
    24. Sara Ilahi & Yongchang Wu & Muhammad Ahsan Ali Raza & Wenshan Wei & Muhammad Imran & Lyankhua Bayasgalankhuu, 2019. "Optimization Approach for Improving Energy Efficiency and Evaluation of Greenhouse Gas Emission of Wheat Crop using Data Envelopment Analysis," Sustainability, MDPI, vol. 11(12), pages 1-16, June.
    25. Matthias Klumpp, 2017. "Do Forwarders Improve Sustainability Efficiency? Evidence from a European DEA Malmquist Index Calculation," Sustainability, MDPI, vol. 9(5), pages 1-33, May.
    26. Fang, Hsin-Hsiung & Lee, Hsuan-Shih & Hwang, Shiuh-Nan & Chung, Cheng-Chi, 2013. "A slacks-based measure of super-efficiency in data envelopment analysis: An alternative approach," Omega, Elsevier, vol. 41(4), pages 731-734.
    27. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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    2. Lei Ding & Kunlun Chen & Yidi Hua & Hongan Dong & Anping Wu, 2020. "Investigating the Relationship between the Industrial Structure and Atmospheric Environment by an Integrated System: A Case Study of Zhejiang, China," Sustainability, MDPI, vol. 12(3), pages 1-21, February.
    3. Heng Zhang & Qian Chang & Sui Li & Jiandong Huang, 2022. "Determining the Efficiency of the Sponge City Construction Pilots in China Based on the DEA-Malmquist Model," IJERPH, MDPI, vol. 19(18), pages 1-17, September.
    4. Yingyu Lu & Bo Cao & Yidi Hua & Lei Ding, 2020. "Efficiency Measurement of Green Regional Development and Its Influencing Factors: An Improved Data Envelopment Analysis Framework," Sustainability, MDPI, vol. 12(11), pages 1-23, May.
    5. Haoran Bai & Nan Li, 2024. "Exploring Green Economic Efficiency Trends in Dominant Chinese Urban Agglomerations: A Super-Efficient SBM Model Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 10325-10348, September.
    6. Wenjie Zou & Liqin Zhang & Jieying Xu & Yufeng Xie & Huangxin Chen, 2022. "Spatial–Temporal Evolution Characteristics and Influencing Factors of Industrial Pollution Control Efficiency in China," Sustainability, MDPI, vol. 14(9), pages 1-18, April.
    7. Manli Cheng & Zhen Shao & Changhui Yang & Xiaoan Tang, 2019. "Analysis of Coordinated Development of Energy and Environment in China’s Manufacturing Industry under Environmental Regulation: A Comparative Study of Sub-Industries," Sustainability, MDPI, vol. 11(22), pages 1-20, November.

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