中国PM2.5污染时空趋势研究——基于贝叶斯时空统计视角

Studying Temporal and Spatial Trends of PM2.5 Pollution in China: Based on Bayesian Spatio-temporal Statistical Perspectives

以遥感反演的PM2.5 年均浓度数据为基础,研究了2000-2014年中国PM2.5 污染的时空演化趋势与特征。采用了基于多尺度嵌套空间统计单元的贝叶斯时空层次模型,并对多尺度嵌套空间统计单元构建的剖分阈值范围进行了扩展。研究表明:第一,2000-2014年,中国PM2.5 重度污染区域已形成“两团一带”的稳态空间结构,主要位于华北平原、长三角地区、四川盆地和新疆塔里木盆地等区域;第二,PM2.5 污染程度高于全国总体水平的区域面积占比为63.3%,但对应的暴露人口比例却高达92.5%;第三,2000-2014年,PM2.5 轻度污染的西部地区出现了较强的局部加重趋势,同时湖北、河南、山东、长三角地区北部和京津冀地区等PM2.5 重度污染区域也出现了局部增加趋势,并形成了“X”型空间结构,但PM2.5污染较重的四川盆地却呈现出下降的局部趋势。

Based on the remotely sensed PM2.5 annual average concentrations data,the spatio-temporal evolution trends and characteristics of PM2.5 pollution in China from 2000 to 2014 are researched.Bayesian space-time hierarchical model based on multi-scale nested spatial statistical units is employed,and the scope of the construction thresholds for the nested multi-scale spatial statistical units is extended.The results show that:firstly,the heavily polluted areas have formed a "two regiment and one belt" steady-state spatial structure,mainly locating in the North China Plain,the Yangtze River Delta region,the Sichuan Basin and the Xinjiang Tarim Basin.Secondly,the proportion of the areas with a higher pollution level than the national average is 63.3%,but the proportion of the corresponding exposed population is as high as 92.5%.Thirdly,a strong local aggravation trend occurred in the slightly polluted western regions from 2000 to 2014,while the areas with the severe PM2.5 pollution, i. e., Hubei,Henan,Shandong,Northern Yangtze River Delta and Beijing-Tianjin-Hebei,also experienced an increasing local trends,forming an "X" type spatial structure,but a declining local trend emerged in the heavily PM2.5 polluted Sichuan Basin area.