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Analysis of spatial-temporal association and factors influencing environmental pollution incidents in China
Institution:1. College of Geomatics and Geoinformation, Guilin University of Technology, Guilin, 541006, China;2. Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin, 541006, China;3. Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China;1. School of Physical Education, China University of Geosciences, Wuhan 430074, China;2. Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China;3. Collage of Urban & Environmental Sciences, Central China Normal University, Wuhan 430079, China;4. Collage of Public Administration, Central China Normal University, Wuhan 430079, China;1. College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, PR China;2. Zhou Enlai School of Government, Nankai University, Tianjin, 300350, PR China;1. School of Environmental and Chemical Engineering, Shanghai University, Shanghai, 200444, China;2. Key Laboratory of Organic Compound Pollution Control Engineering, Ministry of Education, Shanghai, 200444, China;3. School of Economics, Shanghai University, Shanghai, 200444, China;4. Research Institute of Chemical Defense, Beijing, 102205, China;5. Department of Chemical and Environmental Engineering, University of California, Riverside, CA, 92521, USA
Abstract:Environmental risk refers to the possibility of environmental pollution events caused by natural causes or human activities. Environmental risks are transmitted through environmental media and can have destructive effects on human society and the natural environment. Understanding the current status and characteristics of environmental risks can effectively prevent and control environmental risks, which is essential for establishing the safety of ecological systems. Although many scholars have studied the environmental risk characteristics of different enterprises or regional scales and proposed corresponding control methods. However, the study of environmental risk characteristics in the national scale is still insufficient, which affects the accuracy of large-scale environmental impact assessment (EIA) and is not conducive to the formulation of the large-scale environmental management system. This paper attempts to use spatial statistical methods and geographically weighted regression (GWR) models to study the temporal and spatial evolution trends of environmental events in China and the spatial correlation characteristics of influencing factors and environmental events in different regions. The research results show that the focus of China's environmental risk is continuously shifting. At present, environmental pollution incidents are concentrated in the western region, and their spatial correlation with influencing factors varies from region to region. Spatial statistical analysis can help us understand the spatial characteristics of risk and identify the interrelationships of environmental risks in different areas. Therefore, spatial statistical analysis can provide a scientific basis for macro decision-making of large regional EIA and environmental risk management. In the future, it is recommended that the focus of environmental events in different regions should be different to reduce the risk of environmental events in China.
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