The optimization of regional air quality monitoring network based on spatial analysis

Abstract

The main objective of the air quality monitoring network optimization is to obtain information as more as possible while minimizing the number of monitoring sites, with which the general statement of the air pollutants distribution and varying trends could be concluded. In this paper, the minimization of the ordinary kriging variance criterion is introduced, which means that the ordinary kriging variance of estimation errors of a certain point calculated with the sampling points is proposed as an evaluation index to express the uncertainty of that point. The simulated annealing algorithm has proved most effective for such optimization problem to minimize the kriging variance per-grid, and the best designing scheme can be yielded. Guangzhou urban area is selected as a case study area, with the remote sensing image retrieval results of NO2 and PM10 as the prior knowledge.