Research on the optimization of air quality monitoring station layout based on spatial grid statistical analysis method.
In recent years, with the significant increase in urban development, it has become necessary to optimize the current air monitoring stations to reflect the quality of air in the environment. Highlighting the spatial representation of some air monitoring stations using Beijing's regional air monitoring station data from 2012 to 2014, the monthly mean particulate matter concentration (PM10) in the region was calculated and through the IDW interpolation method and spatial grid statistical method using GIS, the spatial distribution of PM10 concentration in the whole region was deduced. The spatial distribution variation of districts in Beijing using the gridding model was performed, and through the 3-year spatial analysis, PM10 concentration data including the variation and spatial overlay (1.5 km × 1.5 km cell resolution grid), the spatial distribution result obtained showed that the total PM10 concentration frequency variation exceeded the standard. It is very important to optimize the layout of the existing air monitoring stations by combining the concentration distribution of air pollutants with the spatial region using GIS.
['Li|Tianxin|T|', 'Zhou|Xing Chen|XC|', 'Ikhumhen|Harrison Odion|HO|', 'Difei|An|A|']
D000393:Air Pollutants D000397:Air Pollution D000068476:Beijing D004784:Environmental Monitoring D052638:Particulate Matter
grid Air monitoring station IDW interpolation regional statistics