Spatial-temporal evolution and influencing factors of sudden environmental accidents in China from 2008 to 2022 - Jun Yan; Shi Yan; Shihan He; Xinying Wang; Xuemei Yang; Xu Li (PLoS ONE, 2026)
The spatiotemporal evolution characteristics and influencing factors of sudden environmental accidents are analyzed by employing exploratory spatial analysis and Pearson correlation analysis, based on the statistical data of sudden environmental accidents in 31 provinces, municipalities, and autonomous regions in China from 2008 to 2022. The results provide valuable insights for the prevention and treatment of sudden environmental pollution emergencies. The results showed that: (1) the total of sudden environmental accidents exhibited an inverted V shaped structure with 2013 as the turning point, showing an overall decreasing trend in China. (2) The seasons when the sudden environmental accidents occurred from the highest to lowest proportions were autumn (29.01%), summer (26.29%), spring (24.80%), and winter (20.19%). The months with the highest frequency were May and July, while October and December had the lowest. The dates with the most occurrences were the 5th, 7th, 4th, 2nd, 11th, and 9th, while the 31st, 30th, 29th, and 27th were the lowest. Regarding weekdays, Monday (16.56%), Wednesday (15.94%), and Thursday (14.38%) were the highest proportions, while Sunday (12.50%) was the lowest. (3) Spatial distribution revealed an overall imbalance, with the eastern coastal comprehensive economic zone being the highest frequency of environmental accidents, followed by the middle reaches of the Yellow River comprehensive economic zone, and the northeast comprehensive economic zone having the lowest. Provinces with the highest number of sudden environmental accidents were mainly in Shanghai (1129), Shaanxi Province (472), and Jiangsu Province (419). Based on the cold and hot spot analysis, H-H areas were mainly located in the southeast coastal regions, L-L areas were concentrated in the western and northeastern regions, and L-H areas were distributed in the central regions. (4) Pearson correlation analysis indicated that investment in the treatment of industrial pollution as percentage of GDP and secondary industry output value as Percentage of GDP were the main driving factors for sudden environmental accidents in China. Per capita GDP, pollutant emissions, and the total of letters and phone calls regarding environmental pollution had inhibitory effects on the occurrence of sudden environmental accidents, while single factors had relatively minor impacts. To effectively prevent and control sudden environmental accidents, it is necessary to improve the risk management system for sudden environmental accidents and strengthen monitoring and management of accident-prone industries, dates, and regions.