IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v7y2015i10p14385-14407d57791.html
   My bibliography  Save this article

Spatial-Temporal Hotspot Pattern Analysis of Provincial Environmental Pollution Incidents and Related Regional Sustainable Management in China in the Period 1995–2012

Author

Listed:
  • Lei Ding

    (School of Environmental Studies, China University of Geosciences, Wuhan 430074, China)

  • Kun-Lun Chen

    (Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China
    Regional Development and Environmental Response Key Laboratory of Hubei Province, Wuhan 430062, China)

  • Ting Liu

    (School of Environmental Studies, China University of Geosciences, Wuhan 430074, China)

  • Sheng-Gao Cheng

    (School of Environmental Studies, China University of Geosciences, Wuhan 430074, China)

  • Xu Wang

    (School of Public Administration, China University of Geosciences, Wuhan 430074, China)

Abstract

Spatial-temporal hotspot pattern analysis of environmental pollution incidents provides an indispensable source of information for the further development of incident prevention measures. In this study, the spatial-temporal patterns of environmental pollution incidents in China in the period of 1995–2012 were analyzed, using the Spatial Getis-Ord statistic and an Improved Prediction Accuracy Index (IAPI). The results show that, in this period, the occurrence of environmental incidents exhibited a dynamic growth pattern but then dropped and continued to drop after the year 2006, which was considered a crucial turning point. Not coincidentally, this corresponds to the year when the State Council issued its National Environmental Emergency Plan , and following the examination of major incidents, special actions were taken to strengthen the control of incidents and emergency responses. The results from Getis-Ord General G statistical analysis show that the spatial agglomeration phenomenon was statistically significant after 1999 and that the level of spatial agglomeration was rising, while the Getis-Ord G i * statistical analysis reveals that environmental pollution incidents were mainly agglomerated in the Pan Yangtze River Delta and Pan Pearl River Delta regions. Accordingly, the spatial-temporal hotspot pattern based on the IAPI values at the provincial scale could be categorized into: stable hotspots, unstable hotspots, and cold-spot areas. The stable hotspots category was further divided into three subtypes: industrial distribution type, industrial transfer type, and extensive economic growth type. Finally, the corresponding measures for sustainable management were proposed: stable hotspots were classified as essential regions requiring the immediate prevention and control of environmental pollution incidents; unstable hotspots were characterized by their need for ongoing and continual prevention measures, and cold-spots were those areas that required strengthened environmental monitoring. Meanwhile, it was identified that a multi-level environmental pollution incident emergency response and regional (incident) joint control plan needed to be well prepared and carried out effectively. To prevent environmental pollution and the regional transfer of pollution from incidents, measures towards achieving regional environmental planning, environmental risk prevention, environmental emergency monitoring and adequate emergency responses must be efficiently implemented.

Suggested Citation

  • Lei Ding & Kun-Lun Chen & Ting Liu & Sheng-Gao Cheng & Xu Wang, 2015. "Spatial-Temporal Hotspot Pattern Analysis of Provincial Environmental Pollution Incidents and Related Regional Sustainable Management in China in the Period 1995–2012," Sustainability, MDPI, vol. 7(10), pages 1-23, October.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:10:p:14385-14407:d:57791
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/7/10/14385/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/7/10/14385/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wirtz, Kai W. & Baumberger, Nick & Adam, Susanne & Liu, Xin, 2007. "Oil spill impact minimization under uncertainty: Evaluating contingency simulations of the Prestige accident," Ecological Economics, Elsevier, vol. 61(2-3), pages 417-428, March.
    2. Guogang Wang & Mingli Wang & Jimin Wang & Chun Yang, 2015. "Spatio-Temporal Characteristics of Rural Economic Development in Eastern Coastal China," Sustainability, MDPI, vol. 7(2), pages 1-16, January.
    3. Nie, Huihua & Jiang, Minjie & Wang, Xianghong, 2013. "The impact of political cycle: Evidence from coalmine accidents in China," Journal of Comparative Economics, Elsevier, vol. 41(4), pages 995-1011.
    4. Ke Nie & Zhensheng Wang & Qingyun Du & Fu Ren & Qin Tian, 2015. "A Network-Constrained Integrated Method for Detecting Spatial Cluster and Risk Location of Traffic Crash: A Case Study from Wuhan, China," Sustainability, MDPI, vol. 7(3), pages 1-16, March.
    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. Chenlu Tao & Jinzhu Zhang & Baodong Cheng & Yu Liu, 2019. "An Assessment of the Impact of Spatial Agglomeration on the Quality of China’s Wood Processing Industry Products," Sustainability, MDPI, vol. 11(14), pages 1-17, July.

    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. Yihang Zhao & Chen Liang & Xinlong Zhang, 2021. "Positive or negative externalities? Exploring the spatial spillover and industrial agglomeration threshold effects of environmental regulation on haze pollution in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11335-11356, August.
    2. Thomas M. Koutsos & Georgios C. Menexes & Andreas P. Mamolos, 2021. "The Use of Crop Yield Autocorrelation Data as a Sustainable Approach to Adjust Agronomic Inputs," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    3. Yu, Haimiao & Chen, Hong & Long, Ruyin, 2017. "Mental fatigue, cognitive bias and safety paradox in chinese coal mines," Resources Policy, Elsevier, vol. 52(C), pages 165-172.
    4. Miao, Shuchao & Chi, Jing & Liao, Jing & Qian, Long, 2021. "How does religious belief promote farmer entrepreneurship in rural China?," Economic Modelling, Elsevier, vol. 97(C), pages 95-104.
    5. Yaxin Fan & Xinyan Zhu & Bing She & Wei Guo & Tao Guo, 2018. "Network-constrained spatio-temporal clustering analysis of traffic collisions in Jianghan District of Wuhan, China," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-23, April.
    6. Wang, Yuan & Hui, Eddie Chi-man, 2017. "Are local governments maximizing land revenue? Evidence from China," China Economic Review, Elsevier, vol. 43(C), pages 196-215.
    7. Yu, Yin & Chi, Jing, 2021. "Political embeddedness, media positioning and corporate social responsibility: Evidence from China," Emerging Markets Review, Elsevier, vol. 47(C).
    8. Mateusz Ciski & Krzysztof Rząsa & Marek Ogryzek, 2019. "Use of GIS Tools in Sustainable Heritage Management—The Importance of Data Generalization in Spatial Modeling," Sustainability, MDPI, vol. 11(20), pages 1-21, October.
    9. Yeran Sun & Yu Wang & Ke Yuan & Ting On Chan & Ying Huang, 2020. "Discovering Spatio-Temporal Clusters of Road Collisions Using the Method of Fast Bayesian Model-Based Cluster Detection," Sustainability, MDPI, vol. 12(20), pages 1-15, October.
    10. He, Dongwei & Wu, Yifan & Wang, Yifan & Xing, Xueyan, 2023. "Prudential regulation and bank performance: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    11. Liu, Dehai & Xiao, Xingzhi & Li, Hongyi & Wang, Weiguo, 2015. "Historical evolution and benefit–cost explanation of periodical fluctuation in coal mine safety supervision: An evolutionary game analysis framework," European Journal of Operational Research, Elsevier, vol. 243(3), pages 974-984.
    12. Xiaodong Xu & Jingping Liu & Ning Xu & Wei Wang & Hui Yang, 2018. "Quantitative Study on the Evolution Trend and Driving Factors of Typical Rural Spatial Morphology in Southern Jiangsu Province, China," Sustainability, MDPI, vol. 10(7), pages 1-20, July.
    13. Chu, Yin & Holladay, J. Scott & Qiu, Yun & Tian, Xian-Liang & Zhou, Maigeng, 2023. "Air Pollution and Mortality Impacts of Coal Mining: Evidence from Coalmine Accidents in China," GLO Discussion Paper Series 1302, Global Labor Organization (GLO).
    14. Xu, Gang & Wang, Xue & Wang, Ruiting & Yano, Go & Zou, Rong, 2021. "Anti-corruption, safety compliance and coal mine deaths: Evidence from China," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 458-488.
    15. Cheng, Maoyong & Meng, Yu & Jin, Justin Yiqiang, 2024. "The impact of political leader's absence on air quality," Energy Economics, Elsevier, vol. 134(C).
    16. Mingyu Kang & Anne Vernez Moudon & Haena Kim & Linda Ng Boyle, 2019. "Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS," IJERPH, MDPI, vol. 16(19), pages 1-14, September.
    17. Shenjun Yao & Jinzi Wang & Lei Fang & Jianping Wu, 2018. "Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China," Sustainability, MDPI, vol. 10(12), pages 1-11, December.
    18. Yusheng Liang & Fan Zhang & Kun Yang & Zhenqi Hu, 2022. "A Surface Crack Damage Evaluation Method Based on Kernel Density Estimation for UAV Images," Sustainability, MDPI, vol. 14(23), pages 1-17, December.
    19. Wang, Jianxiong & Zhou, Yonghong, 2021. "Impact of mass media on public awareness: The “Under the Dome” effect in China," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    20. Xi, Tianyang & Yao, Yang & Zhang, Muyang, 2018. "Capability and opportunism: Evidence from city officials in China," Journal of Comparative Economics, Elsevier, vol. 46(4), pages 1046-1061.

    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:7:y:2015:i:10:p:14385-14407:d:57791. 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.