IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i8p2269-d223022.html
   My bibliography  Save this article

Regional Inequality and Influencing Factors of Primary PM Emissions in the Yangtze River Delta, China

Author

Listed:
  • Haibin Xia

    (School of Geographic Sciences, Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China)

  • Hui Wang

    (School of Resource, Environment and Earth Sciences, Yunnan University, Yunnan 650091, China)

  • Guangxing Ji

    (School of Geographic Sciences, Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China)

Abstract

In recent years, haze pollution has become more and more serious in the Yangtze River Delta (YRD). However, the impact mechanism of socio-economic factors on primary particulate matter (PM) emissions remains unclear. Based on the provincial primary PM emission data in the YRD from 1995 to 2014, this paper used Slope, Theil index, and Stochastic Impacts by Regression on Population, Affluence, and Technology (STIAPAT) models to quantitatively identify the regional differences of primary PM emissions and explore the key influencing factors. The results showed that primary fine particulate matter (PM 2.5 ), inhalable particulate (PM 10 ), and total suspended particulate (TSP) emissions all featured an upward trend of fluctuation over the study period. The regional differences in primary TSP emissions in the YRD region was gradually shrinking and the regional differences of primary PM 2.5 and PM 10 emissions presented a rising trend of fluctuation. The estimated coefficient of population size, energy structure, and fixed assets investment (FAI) were all significantly positive at the level of 1%. The negative effect of economic growth on energy PM emissions was significant under the level of 1%. The increase of foreign direct investment (FDI) had different effects on primary PM 2.5 , PM 10 , and TSP emissions. In addition, the influence of energy intensity on primary PM emission from energy consumption are mainly negative but not significant even under the level of 10%. These conclusions have guiding significance for the formulation of PM emission reduction policy without affecting YRD’s economic development.

Suggested Citation

  • Haibin Xia & Hui Wang & Guangxing Ji, 2019. "Regional Inequality and Influencing Factors of Primary PM Emissions in the Yangtze River Delta, China," Sustainability, MDPI, vol. 11(8), pages 1-14, April.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:8:p:2269-:d:223022
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/8/2269/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/8/2269/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liddle, Brantley, 2013. "Urban density and climate change: a STIRPAT analysis using city-level data," Journal of Transport Geography, Elsevier, vol. 28(C), pages 22-29.
    2. Shuai, Chenyang & Shen, Liyin & Jiao, Liudan & Wu, Ya & Tan, Yongtao, 2017. "Identifying key impact factors on carbon emission: Evidences from panel and time-series data of 125 countries from 1990 to 2011," Applied Energy, Elsevier, vol. 187(C), pages 310-325.
    3. 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.
    4. Lyu, Wanning & Yuan Li & Dabo Guan & Hongyan Zhao & Qiang Zhang & Zhu Liu, "undated". "Driving forces of Chinese primary air pollution emissions: an index decomposition analysis," Working Paper 428386, Harvard University OpenScholar.
    5. Meng, Jing & Liu, Junfeng & Guo, Shan & Huang, Ye & Tao, Shu, 2016. "The impact of domestic and foreign trade on energy-related PM emissions in Beijing," Applied Energy, Elsevier, vol. 184(C), pages 853-862.
    6. Wang, Changjian & Wang, Fei & Zhang, Xinlin & Yang, Yu & Su, Yongxian & Ye, Yuyao & Zhang, Hongou, 2017. "Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 51-61.
    7. Wang, Qiang & Wu, Shi-dai & Zeng, Yue-e & Wu, Bo-wei, 2016. "Exploring the relationship between urbanization, energy consumption, and CO2 emissions in different provinces of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1563-1579.
    8. Salim, Ruhul A. & Shafiei, Sahar, 2014. "Urbanization and renewable and non-renewable energy consumption in OECD countries: An empirical analysis," Economic Modelling, Elsevier, vol. 38(C), pages 581-591.
    9. Abdallh, Atif Awad & Abugamos, Hoda, 2017. "A semi-parametric panel data analysis on the urbanisation-carbon emissions nexus for the MENA countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1350-1356.
    10. Poumanyvong, Phetkeo & Kaneko, Shinji & Dhakal, Shobhakar, 2012. "Impacts of urbanization on national transport and road energy use: Evidence from low, middle and high income countries," Energy Policy, Elsevier, vol. 46(C), pages 268-277.
    11. Shi, Anqing, 2003. "The impact of population pressure on global carbon dioxide emissions, 1975-1996: evidence from pooled cross-country data," Ecological Economics, Elsevier, vol. 44(1), pages 29-42, February.
    12. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    13. Zhang, Chuanguo & Lin, Yan, 2012. "Panel estimation for urbanization, energy consumption and CO2 emissions: A regional analysis in China," Energy Policy, Elsevier, vol. 49(C), pages 488-498.
    14. Wang, Ping & Wu, Wanshui & Zhu, Bangzhu & Wei, Yiming, 2013. "Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China," Applied Energy, Elsevier, vol. 106(C), pages 65-71.
    15. Takahiro Akita, 2003. "Decomposing regional income inequality in China and Indonesia using two-stage nested Theil decomposition method," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 37(1), pages 55-77, February.
    16. Su, Yongxian & Chen, Xiuzhi & Li, Yong & Liao, Jishan & Ye, Yuyao & Zhang, Hongou & Huang, Ningsheng & Kuang, Yaoqiu, 2014. "China׳s 19-year city-level carbon emissions of energy consumptions, driving forces and regionalized mitigation guidelines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 231-243.
    17. Zhang, Chuanguo & Liu, Cong, 2015. "The impact of ICT industry on CO2 emissions: A regional analysis in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 12-19.
    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. Guangxing Ji & Junchang Huang & Yulong Guo & Dan Yan, 2022. "Quantitatively Calculating the Contribution of Vegetation Variation to Runoff in the Middle Reaches of Yellow River Using an Adjusted Budyko Formula," Land, MDPI, vol. 11(4), pages 1-12, April.
    2. Guangxing Ji & Huiyun Song & Hejie Wei & Leying Wu, 2021. "Attribution Analysis of Climate and Anthropic Factors on Runoff and Vegetation Changes in the Source Area of the Yangtze River from 1982 to 2016," Land, MDPI, vol. 10(6), pages 1-13, June.
    3. Liang Cheng & Long Li & Longqian Chen & Sai Hu & Lina Yuan & Yunqiang Liu & Yifan Cui & Ting Zhang, 2019. "Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period," IJERPH, MDPI, vol. 16(19), pages 1-25, September.

    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. Li, Ke & Lin, Boqiang, 2015. "Impacts of urbanization and industrialization on energy consumption/CO2 emissions: Does the level of development matter?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1107-1122.
    2. Vélez-Henao, Johan-Andrés & Font Vivanco, David & Hernández-Riveros, Jesús-Antonio, 2019. "Technological change and the rebound effect in the STIRPAT model: A critical view," Energy Policy, Elsevier, vol. 129(C), pages 1372-1381.
    3. Weibo Zhao & Dongxiao Niu, 2017. "Prediction of CO 2 Emission in China’s Power Generation Industry with Gauss Optimized Cuckoo Search Algorithm and Wavelet Neural Network Based on STIRPAT model with Ridge Regression," Sustainability, MDPI, vol. 9(12), pages 1-15, December.
    4. Wang, Qiang & Lin, Jian & Zhou, Kan & Fan, Jie & Kwan, Mei-Po, 2020. "Does urbanization lead to less residential energy consumption? A comparative study of 136 countries," Energy, Elsevier, vol. 202(C).
    5. Wang, Shaojian & Zeng, Jingyuan & Liu, Xiaoping, 2019. "Examining the multiple impacts of technological progress on CO2 emissions in China: A panel quantile regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 140-150.
    6. Zhou, Yang & Liu, Yansui & Wu, Wenxiang & Li, Yurui, 2015. "Effects of rural–urban development transformation on energy consumption and CO2 emissions: A regional analysis in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 863-875.
    7. Cui, Can & Shan, Yuli & Liu, Jianghua & Yu, Xiang & Wang, Hongtao & Wang, Zhen, 2019. "CO2 emissions and their spatial patterns of Xinjiang cities in China," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    8. Wang, Qiang & Wu, Shi-dai & Zeng, Yue-e & Wu, Bo-wei, 2016. "Exploring the relationship between urbanization, energy consumption, and CO2 emissions in different provinces of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1563-1579.
    9. Wang, Changjian & Wang, Fei & Zhang, Xinlin & Yang, Yu & Su, Yongxian & Ye, Yuyao & Zhang, Hongou, 2017. "Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 51-61.
    10. Hui Wang & Guangxing Ji & Jisheng Xia, 2019. "Analysis of Regional Differences in Energy-Related PM 2.5 Emissions in China: Influencing Factors and Mitigation Countermeasures," Sustainability, MDPI, vol. 11(5), pages 1-14, March.
    11. Pengyan Zhang & Jianjian He & Xin Hong & Wei Zhang & Chengzhe Qin & Bo Pang & Yanyan Li & Yu Liu, 2017. "Regional-Level Carbon Emissions Modelling and Scenario Analysis: A STIRPAT Case Study in Henan Province, China," Sustainability, MDPI, vol. 9(12), pages 1-15, December.
    12. Minda Ma & Liyin Shen & Hong Ren & Weiguang Cai & Zhili Ma, 2017. "How to Measure Carbon Emission Reduction in China’s Public Building Sector: Retrospective Decomposition Analysis Based on STIRPAT Model in 2000–2015," Sustainability, MDPI, vol. 9(10), pages 1-16, September.
    13. Liang, Xiaoying & Min Fan, & Xiao, Yuting & Yao, Jing, 2022. "Temporal-spatial characteristics of energy-based carbon dioxide emissions and driving factors during 2004–2019, China," Energy, Elsevier, vol. 261(PA).
    14. Jiancheng Qin & Hui Tao & Minjin Zhan & Qamar Munir & Karthikeyan Brindha & Guijin Mu, 2019. "Scenario Analysis of Carbon Emissions in the Energy Base, Xinjiang Autonomous Region, China," Sustainability, MDPI, vol. 11(15), pages 1-18, August.
    15. Maxwell Chukwudi Udeagha & Nicholas Ngepah, 2022. "Dynamic ARDL Simulations Effects of Fiscal Decentralization, Green Technological Innovation, Trade Openness, and Institutional Quality on Environmental Sustainability: Evidence from South Africa," Sustainability, MDPI, vol. 14(16), pages 1-35, August.
    16. Wang, Shaojian & Wang, Jieyu & Fang, Chuanglin & Feng, Kuishuang, 2019. "Inequalities in carbon intensity in China: A multi-scalar and multi-mechanism analysis," Applied Energy, Elsevier, vol. 254(C).
    17. Fei Wang & Changjian Wang & Jing Chen & Zeng Li & Ling Li, 2020. "Examining the determinants of energy-related carbon emissions in Central Asia: country-level LMDI and EKC analysis during different phases," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(8), pages 7743-7769, December.
    18. Qiu Chen & Haoran Yang & Wenguo Wang & Tianbiao Liu, 2019. "Beyond the City: Effects of Urbanization on Rural Residential Energy Intensity and CO 2 Emissions," Sustainability, MDPI, vol. 11(8), pages 1-21, April.
    19. Wang, Shaojian & Zeng, Jingyuan & Huang, Yongyuan & Shi, Chenyi & Zhan, Peiyu, 2018. "The effects of urbanization on CO2 emissions in the Pearl River Delta: A comprehensive assessment and panel data analysis," Applied Energy, Elsevier, vol. 228(C), pages 1693-1706.
    20. Dong, Kangyin & Hochman, Gal & Zhang, Yaqing & Sun, Renjin & Li, Hui & Liao, Hua, 2018. "CO2 emissions, economic and population growth, and renewable energy: Empirical evidence across regions," Energy Economics, Elsevier, vol. 75(C), pages 180-192.

    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:jsusta:v:11:y:2019:i:8:p:2269-:d:223022. 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.