代表性启发
中国
空气质量指数
空气监测
环境科学
质量评定
质量(理念)
地理
环境资源管理
环境工程
工程类
气象学
统计
可靠性工程
数学
评价方法
认识论
哲学
考古
作者
Heming Bai,Wenkang Gao,Dasa Gu,Jawad Hussain,Shuai Wang,Fanhua Kong,Yang Cao
摘要
Abstract The spatial representativeness (SR) of air quality monitoring sites is critical for ensuring that gathered data accurately reflect the broader area's air quality. Evaluating the SR of sites at a national scale and its long‐term trends is particularly important for countries like China, where both air quality and monitoring networks have changed dramatically over time. Here, we used 1‐km daily air pollutant concentrations from the China High Air Pollutants dataset to assess the yearly SR of state‐controlled sites in China from 2013 to 2022 for multiple pollutants. With the number of sites increasing from 460 in 2013 to 1,590 in 2022, our results showed that the total SR area of sites increased by 89% for PM 2.5 , 149% for PM 10 , and 2,190% for O 3 . While the number of sites mainly drove these increases, its impact varied at different phases. Interestingly, the rise in sites from 2020 to 2022 actually led to a decrease in the total SR area for PM 2.5 (−18,300 km 2 ) and PM 10 (−14,200 km 2 ). Additionally, we found that applying SR to pollution exposure assessments did not improve their accuracy at national and city levels when compared to the official method, which involves exposure calculation using arithmetic mean aggregation of monitoring sites. This was related to poor SR performance, with more than half of the population being uncovered by SR areas in more than 85% of Chinese cities. Nevertheless, we demonstrated the benefits of applying SR for city‐level air quality attainment.
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