Air pollution (e.g., PM2.5) has a negative effect on human health. Recently, the population-weighted annual mean PM2.5 concentration (PWAM) has been selected as an indicator 11.6.2 in Sustainable Development Goals (SDGs), for various countries to perfrom a long-term monitoring of population exposure to PM2.5 in cities. However, few studies have employed this indicator for a city-level analysis and also in a long-time series (e.g., for decades). To fill this research gap, this study investigates the long-term (2000-2020) variation of population exposure to PM2.5 in Eastern China (including 318 prefecture-level cities). Three categories of open geospatial data (including high-resolution and long-term PM2.5 and population data, and administrative boundary data of cities) are involved for analysis. We found that: 1) A considerable decrease has been observed for the PWAM during 2014-2020. 2) In 2020, the PWAM is for the first time lower than the interim target-1 (35 {\mu}g/m3) defined by the World Health Organization for 214 prefecture-level cities in Eastern China, which accounts for 67% of the total population. The results indicates a considerable improvement of air quality in Eastern China. More important, this study illustrates the feasibility of using open geospatial data to monitor the SDG indicator 11.6.2.
翻译:最近,人口加权的PM2.5年平均浓度(PWAM)被选为可持续发展目标(SDGs)中的一项指标11.6.2,供各国从长期监测城市人口接触PM2.5的情况中抽取,然而,很少有研究采用这一指标进行城市一级分析和长期系列分析(如数十年);为填补这一研究差距,本研究调查了中国东部地区214个县级城市(包括318个县级城市)人口接触PM2.5的长期(2000-2020年)的变化情况;涉及三类开放地理空间数据(包括高分辨率和长期PM2.5和人口数据以及城市行政边界数据)进行分析;我们发现:(1) 2014-2020年期间,PWAMM的这一指标明显下降。 2 2020年,PWAM首次低于世界卫生组织为中国东部地区214个县级城市(包括318个县级城市)确定的中期目标1(2000-2020年)(2000-2020年),这三类开放地理空间数据(包括高分辨率和长期PM2.5和城市人口数据以及城市行政边界数据),用于分析。我们发现:(1) 2014-2020年期间,PWAWAM明显降低了中国开放地理空间数据的质量。