长三角地区空气质量国控环境监测点空间代表性评价-以PM_2.5为例

In 2013, China has officially launched the monitoring of fine particle (PM_2.5) and other air pollutants in 113 key environmental protection cities and national environmental protection model cities. At present, the national ambient air quality monitoring network was established. To correctly upscale the observations obtained in these stations to the regional and global scale, it is necessary to understand the representativeness of the current monitoring network. Using the Yangtze River Delta as the study area, this paper calculated the multidimensional Euclidean distance between each pixel and the stations to determine the representativeness of the existing monitoring network. Eight variables related to PM_2.5, including proportion of secondary industry (POSI), gross domestic product (GDP), population (POP), wind speed (WDSP), precipitation (PRCP), air temperature (TEMP), enhanced vegetation index (EVI) and digital elevation model (DEM) were used to indicate the environmental characteristics of PM_2.5 with a spatial resolution of 1 km×1 km. In addition, the K-means clustering method was adopted to improve the spatial representativeness of the existing ambient air quality monitoring network. The results showed that: ① there were obvious differences among the representative area of 129 stations in the Yangtze River Delta. The Dianshan Lake station in Shanghai had the largest representative area(37933 km²), and the representative area of the Maigaoqiao station in Nanjing was only 4 km²; ② the monitoring stations in the Yangtze River Delta could well represent the PM_2.5 spatial distribution of the entire region, and the effective area (i.e. the area where the Euclidean distance between the pixels and the stations was lower than the average value) accounted for 63.23% of the total area; ③ the areas that were difficult to be represented mainly concentrated in the Taihu Lake and Hongze Lake, downtown area of Shanghai, the coastal areas of Chongming, and the southwestern mountainous areas in Zhejiang; ④ two additional stations were proposed in Shaoxing city and Quzhou city, which could improve the regional representativeness by 16.4%, especially in the hilly areas in Zhejiang Province.