Research on gasoline vehicle emission limits based on remote sensing monitoring data in Chengdu
To strengthen the control of mobile sources in Chengdu,the gasoline vehicle exhaust emission data from four remote sensing monitoring sites in Chengdu in 2021 was explored.An effective remote sensing monitoring data set was screened based on the monitoring circumstances and the vehicle operating states.The generalized Pareto distribution(GPD)function was used to fit the screened data set,and the Kolmogorov-Smirnov test(K-S test for short)was employed to determine the optimal fitting threshold as the pollutant emission limits.The results showed that:(1)the R2 of linear regression between the theoretical and empirical distributions was greater than 0.999,corroborating that the GPD function almost perfectly fitted the over threshold samples of remote sensing monitoring data set;(2)the CO,HC and NO emission limits(measured by volume fraction)determined by the K-S test were 2.9％,430× 10-6 and 1 400 × 10-6;(3)the determined pollutant emission limit was around the middle level of the local standard emission limits for several cities in China,indicating that the GPD function was applicable to determine the emission limits of remote sensing monitoring data,which provided a reference for the formulation of local standards in Chengdu.
generalized Pareto distribution functionextreme value estimationgasoline vehicleremote sensing monitoringhigh-emitting vehicles
NETL
NSTL
万方数据
维普
