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Sustainability 2015, 7(10), 14385-14407; doi:10.3390/su71014385

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

1
School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
2
Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China
3
Regional Development and Environmental Response Key Laboratory of Hubei Province, Wuhan 430062, China
4
School of Public Administration, China University of Geosciences, Wuhan 430074, China
*
Author to whom correspondence should be addressed.
Academic Editor: Marc A. Rosen
Received: 22 July 2015 / Revised: 19 October 2015 / Accepted: 20 October 2015 / Published: 26 October 2015
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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 Gi* 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. View Full-Text
Keywords: environmental pollution incident; the spatiotemporal hotspot model; spatial Getis-Ord Gi* statistic; improved prediction accuracy index (IAPI) environmental pollution incident; the spatiotemporal hotspot model; spatial Getis-Ord Gi* statistic; improved prediction accuracy index (IAPI)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Ding, L.; Chen, K.-L.; Liu, T.; Cheng, S.-G.; Wang, X. Spatial-Temporal Hotspot Pattern Analysis of Provincial Environmental Pollution Incidents and Related Regional Sustainable Management in China in the Period 1995–2012. Sustainability 2015, 7, 14385-14407.

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