School of Statistics, Shanxi University of Finance and Economics, Wucheng Road 696, Taiyuan 030006, China.
College of Architecture and Civil Engineering, Taiyuan University of Technology, Yingze Street 79, Taiyuan 030024, China.
Environ Int. 2019 Jul;128:46-62. doi: 10.1016/j.envint.2019.04.026. Epub 2019 Apr 25.
Air pollution in the form of particulate matter (PM) is becoming one of the greatest current threats to human health on a global scale. This paper firstly presents a Bayesian space-time hierarch piecewise regression model (BSTHPRM) which can self-adaptively detect the transitions of local trends, accounting for spatial correlations. The spatiotemporal trends of the approximately anthropogenic PM removed natural dust (PM) concentrations and the corresponding population's PM exposure (PPME) in the global continent from 1998 to 2016 were investigated by the presented BSTHPRM. The total areas of the high and higher PM-polluted regions, whose spatial relative magnitude of PM pollution to the global continental overall level was between 1.89 and 14.68, accounted for about 13.4% of the global land area, and the corresponding exposed populations accounted for 56.0% of the global total population. The spatial heterogeneity of the global PM pollution increased generally from 1998 to 2016. The areas of hot, warm, and cold spots with increasing trends of PM concentration initially contracted and then later expanded. The local trends of the global continental PM concentrations and PPME can be parted into three changing stages, early, medium, and later stages, using the BSTHPRM. The area proportions of the regions experiencing a decreasing trend of PM concentrations and PPME were greater in the medium stage than in the early and later stages. The local trends of PM concentration and PPME in the two higher PM polluted areas, northern India and eastern and southern China, increased in the early stage and then decreased in the medium stage. In the later stage (recent years), northern India displayed a stronger increasing trend; nevertheless, the follow-up decreasing trend still occurred in eastern and southern China. In the first two stages, more than half of the areas in Europe experienced a decreasing trend of PM concentration and PPME; later, more than half of areas in Europe exhibited increasing trends in the later stage. North America and South America experienced a similar local trend of PPME to Europe. The PPME trend in Africa generally increased during the study period.
空气污染以颗粒物(PM)的形式成为当前全球范围内对人类健康的最大威胁之一。本文首先提出了一种贝叶斯时空层次分段回归模型(BSTHPRM),该模型可以自适应地检测局部趋势的转变,同时考虑到空间相关性。利用所提出的 BSTHPRM,研究了 1998 年至 2016 年全球大陆人为去除自然尘埃(PM)后,近似人为 PM 浓度(PM)和相应人口 PM 暴露(PPME)的时空趋势。全球高污染和更高污染地区的总面积占全球陆地面积的约 13.4%,这些地区的 PM 污染相对于全球大陆整体水平的空间相对幅度在 1.89 到 14.68 之间,相应的暴露人口占全球总人口的 56.0%。全球 PM 污染的空间异质性总体上从 1998 年到 2016 年增加。PM 浓度热点、暖点和冷点的空间范围最初收缩,然后扩大。利用 BSTHPRM,可将全球大陆 PM 浓度和 PPME 的局部趋势分为三个变化阶段,即早期、中期和后期。在中期阶段,经历 PM 浓度和 PPME 下降趋势的区域比例大于早期和后期阶段。印度北部和中国东部和南部两个高污染地区的 PM 浓度和 PPME 局部趋势在早期阶段增加,然后在中期阶段下降。在后期(近年),印度北部表现出更强的上升趋势;然而,中国东部和南部仍出现了后续的下降趋势。在前两个阶段,欧洲一半以上的地区经历了 PM 浓度和 PPME 的下降趋势,后期欧洲一半以上的地区出现了上升趋势。北美洲和南美洲与欧洲有类似的 PPME 局部趋势。非洲的 PPME 趋势在研究期间普遍增加。