IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i20p4004-d278289.html
   My bibliography  Save this article

Identifying Driving Factors of Jiangsu’s Regional Sulfur Dioxide Emissions: A Generalized Divisia Index Method

Author

Listed:
  • Junliang Yang

    (School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Haiyan Shan

    (School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
    Weather Service Science Research Center, Nanjing University of Information Science & Technology, Nanjing 210044, China)

Abstract

The Chinese government has made some good achievements in reducing sulfur dioxide emissions through end-of-pipe treatment. However, in order to implement the stricter target of sulfur dioxide emission reduction during the 13th “Five-Year Plan” period, it is necessary to find a new solution as quickly as possible. Thus, it is of great practical significance to identify driving factors of regional sulfur dioxide emissions to formulate more reasonable emission reduction policies. In this paper, a distinctive decomposition approach, the generalized Divisia index method (GDIM), is employed to investigate the driving forces of regional industrial sulfur dioxide emissions in Jiangsu province and its three regions during 2004–2016. The contribution rates of each factor to emission changes are also assessed. The decomposition results demonstrate that: (i) the factors promoting the increase of industrial sulfur dioxide emissions are the economic scale effect, industrialization effect, and energy consumption effect, while technology effect, energy mix effect, sulfur efficiency effect, energy intensity effect, and industrial structure effect play a mitigating role in the emissions; (ii) energy consumption effect, energy mix effect, technology effect, sulfur efficiency effect, and industrial structure effect show special contributions in some cases; (iii) industrial structure effect and energy intensity effect need to be further optimized.

Suggested Citation

  • Junliang Yang & Haiyan Shan, 2019. "Identifying Driving Factors of Jiangsu’s Regional Sulfur Dioxide Emissions: A Generalized Divisia Index Method," IJERPH, MDPI, vol. 16(20), pages 1-20, October.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:20:p:4004-:d:278289
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/20/4004/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/16/20/4004/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shao, Shuai & Liu, Jianghua & Geng, Yong & Miao, Zhuang & Yang, Yingchun, 2016. "Uncovering driving factors of carbon emissions from China’s mining sector," Applied Energy, Elsevier, vol. 166(C), pages 220-238.
    2. Magacho, Guilherme R. & McCombie, John S.L. & Guilhoto, Joaquim J.M., 2018. "Impacts of trade liberalization on countries’ sectoral structure of production and trade: A structural decomposition analysis," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 70-77.
    3. Hu, Bin & Li, Zhengtao & Zhang, Lin, 2019. "Long-run dynamics of sulphur dioxide emissions, economic growth and energy efficiency in China," MPRA Paper 94588, University Library of Munich, Germany.
    4. Wang, H. & Ang, B.W., 2018. "Assessing the role of international trade in global CO2 emissions: An index decomposition analysis approach," Applied Energy, Elsevier, vol. 218(C), pages 146-158.
    5. Oliveira, Gilson Adamczuk & Tan, Kim Hua & Guedes, Bruno Turmina, 2018. "Lean and green approach: An evaluation tool for new product development focused on small and medium enterprises," International Journal of Production Economics, Elsevier, vol. 205(C), pages 62-73.
    6. Ling, Zaili & Huang, Tao & Li, Jixiang & Zhou, Sheng & Lian, Lulu & Wang, Jinxiang & Zhao, Yuan & Mao, Xiaoxuan & Gao, Hong & Ma, Jianmin, 2019. "Sulfur dioxide pollution and energy justice in Northwestern China embodied in West-East Energy Transmission of China," Applied Energy, Elsevier, vol. 238(C), pages 547-560.
    7. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    8. Vaninsky, Alexander, 2014. "Factorial decomposition of CO2 emissions: A generalized Divisia index approach," Energy Economics, Elsevier, vol. 45(C), pages 389-400.
    9. Zhou, Xiaoyong & Zhou, Dequn & Wang, Qunwei, 2018. "How does information and communication technology affect China's energy intensity? A three-tier structural decomposition analysis," Energy, Elsevier, vol. 151(C), pages 748-759.
    10. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    11. Wang, H. & Zhou, P., 2018. "Assessing Global CO2 Emission Inequality From Consumption Perspective: An Index Decomposition Analysis," Ecological Economics, Elsevier, vol. 154(C), pages 257-271.
    12. Liang, Wei & Gan, Ting & Zhang, Wei, 2019. "Dynamic evolution of characteristics and decomposition of factors influencing industrial carbon dioxide emissions in China: 1991–2015," Structural Change and Economic Dynamics, Elsevier, vol. 49(C), pages 93-106.
    13. Wang, Yuan & Han, Rong & Kubota, Jumpei, 2016. "Is there an Environmental Kuznets Curve for SO2 emissions? A semi-parametric panel data analysis for China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1182-1188.
    14. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    15. Liu, Qiaoling & Wang, Qi, 2015. "Reexamine SO2 emissions embodied in China's exports using multiregional input–output analysis," Ecological Economics, Elsevier, vol. 113(C), pages 39-50.
    16. Chen, Shuo & Li, Yiran & Yao, Qin, 2018. "The health costs of the industrial leap forward in China: Evidence from the sulfur dioxide emissions of coal-fired power stations," China Economic Review, Elsevier, vol. 49(C), pages 68-83.
    17. Peter Rafaj & Markus Amann & José Siri & Henning Wuester, 2014. "Changes in European greenhouse gas and air pollutant emissions 1960–2010: decomposition of determining factors," Climatic Change, Springer, vol. 124(3), pages 477-504, June.
    18. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaoyu Yang & Jianqiang Dong & Xiaopeng Guo, 2023. "Spatial Dependence of SO 2 Emissions and Energy Consumption Structure in Northern China," Sustainability, MDPI, vol. 15(3), pages 1-14, January.
    2. Jingyuan Li & Jinhua Cheng & Yang Wen & Jingyu Cheng & Zhong Ma & Peiqi Hu & Shurui Jiang, 2022. "The Cause of China’s Haze Pollution: City Level Evidence Based on the Extended STIRPAT Model," IJERPH, MDPI, vol. 19(8), pages 1-18, April.
    3. Wang, Yaxian & Zhao, Zhenli & Wang, Wenju & Streimikiene, Dalia & Balezentis, Tomas, 2023. "Interplay of multiple factors behind decarbonisation of thermal electricity generation: A novel decomposition model," Technological Forecasting and Social Change, Elsevier, vol. 189(C).

    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. Chen, Qingjuan & Wang, Qunwei & Zhou, Dequn & Wang, Honggang, 2023. "Drivers and evolution of low-carbon development in China's transportation industry: An integrated analytical approach," Energy, Elsevier, vol. 262(PB).
    2. Xiang, Xiwang & Ma, Minda & Ma, Xin & Chen, Liming & Cai, Weiguang & Feng, Wei & Ma, Zhili, 2022. "Historical decarbonization of global commercial building operations in the 21st century," Applied Energy, Elsevier, vol. 322(C).
    3. Zhang, Chi & Su, Bin & Zhou, Kaile & Sun, Yuan, 2020. "A multi-dimensional analysis on microeconomic factors of China's industrial energy intensity (2000–2017)," Energy Policy, Elsevier, vol. 147(C).
    4. Zhang, Danyang & Wang, Hui & Löschel, Andreas & Zhou, Peng, 2021. "The changing role of global value chains in CO2 emission intensity in 2000–2014," Energy Economics, Elsevier, vol. 93(C).
    5. Shi, Changfeng & Zhi, Jiaqi & Yao, Xiao & Zhang, Hong & Yu, Yue & Zeng, Qingshun & Li, Luji & Zhang, Yuxi, 2023. "How can China achieve the 2030 carbon peak goal—a crossover analysis based on low-carbon economics and deep learning," Energy, Elsevier, vol. 269(C).
    6. Wang, Miao & Feng, Chao, 2017. "Analysis of energy-related CO2 emissions in China’s mining industry: Evidence and policy implications," Resources Policy, Elsevier, vol. 53(C), pages 77-87.
    7. Shichun Xu & Wenwen Zhang & Qinbin Li & Bin Zhao & Shuxiao Wang & Ruyin Long, 2017. "Decomposition Analysis of the Factors that Influence Energy Related Air Pollutant Emission Changes in China Using the SDA Method," Sustainability, MDPI, vol. 9(10), pages 1-18, September.
    8. Yang, Xue & Su, Bin, 2019. "Impacts of international export on global and regional carbon intensity," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    9. Yan, Junna & Li, Yingzhu & Su, Bin & Ng, Tsan Sheng, 2022. "Contributors and drivers of Chinese energy use and intensity from regional and demand perspectives, 2012-2015-2017," Energy Economics, Elsevier, vol. 115(C).
    10. Banie Naser Outchiri, 2020. "Contributing to better energy and environmental analyses: how accurate are decomposition analysis results?," Cahiers de recherche 20-11, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    11. Zhang, Wei & Wang, Nan, 2021. "Decomposition of energy intensity in Chinese industries using an extended LMDI method of production element endowment," Energy, Elsevier, vol. 221(C).
    12. Qingyou Yan & Yaxian Wang & Tomas Baležentis & Yikai Sun & Dalia Streimikiene, 2018. "Energy-Related CO 2 Emission in China’s Provincial Thermal Electricity Generation: Driving Factors and Possibilities for Abatement," Energies, MDPI, vol. 11(5), pages 1-25, April.
    13. Boya Zhang & Shukuan Bai & Yadong Ning & Tao Ding & Yan Zhang, 2020. "Emission Embodied in International Trade and Its Responsibility from the Perspective of Global Value Chain: Progress, Trends, and Challenges," Sustainability, MDPI, vol. 12(8), pages 1-26, April.
    14. Wang, Enci & Su, Bin & Zhong, Sheng & Guo, Qinxin, 2022. "China's Embodied SO2 Emissions and Aggregate Embodied SO2 Intensities in Interprovincial and International Trade," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    15. Wen, Hong-xing & Chen, Zhe & Yang, Qian & Liu, Jin-yi & Nie, Pu-yan, 2022. "Driving forces and mitigating strategies of CO2 emissions in China: A decomposition analysis based on 38 industrial sub-sectors," Energy, Elsevier, vol. 245(C).
    16. Jana, Sebak Kumar & Lise, Wietze, 2023. "Carbon Emissions from Energy Use in India: Decomposition Analysis," MPRA Paper 117245, University Library of Munich, Germany.
    17. Yan, Junna & Su, Bin, 2020. "What drive the changes in China's energy consumption and intensity during 12th Five-Year Plan period?," Energy Policy, Elsevier, vol. 140(C).
    18. Zhong, Sheng, 2018. "Structural decompositions of energy consumption between 1995 and 2009: Evidence from WIOD," Energy Policy, Elsevier, vol. 122(C), pages 655-667.
    19. Rui Jiang & Peng Wu & Chengke Wu, 2022. "Driving Factors behind Energy-Related Carbon Emissions in the U.S. Road Transport Sector: A Decomposition Analysis," IJERPH, MDPI, vol. 19(4), pages 1-17, February.
    20. Liu, Xianmei & Peng, Rui & Zhong, Chao & Wang, Mingyue & Guo, Pibin, 2021. "What drives the temporal and spatial differences of CO2 emissions in the transport sector? Empirical evidence from municipalities in China," Energy Policy, Elsevier, vol. 159(C).

    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:gam:jijerp:v:16:y:2019:i:20:p:4004-:d:278289. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.