Regional Division of Air Quality Governance Based on Pseudo-Quantile Clustering with the View of Functional Data
In recent years,air pollution and quality problems have been widely concerned.Due to the large difference of air quality in China's major cities and obvious regional characteristics,it is of great practical significance to divide air quality regions and implement targeted air quality prevention and control measures to improve air quality in China's various regions.In this paper,based on the daily AIR quality AQI data of 312 prefecture-level cities from 2015 to 2019,pseudo-quantile clustering(Expectlie curve clustering and M-quantile functional data clustering)was used to study the air quality of each prefecture-level city and divide the air quality control regions.According to the two kinds of clustering results,9 different air quality control regions were finally divided,and pollution prevention measures were proposed according to the regional characteristics of each region.
expectile curvesM-quantilepseudo-quantilefunctional data clusteringair quality