Data quality evaluation and calibration of on-road remote sensing systems based on exhaust plumes  

作　　者：Shijie Liu Xinlu Zhang Linlin Ma Liqiang He Shaojun Zhang Miaomiao Cheng 

机构地区：[1]State Key Laboratory of Environmental Criteria and Risk Assessment,Chinese Research Academy of Environmental Sciences,Beijing 100012,China [2]Institute of Atmospheric Environment,Chinese Research Academy of Environmental Sciences,Beijing 100012,China [3]School of Environment,State Key Joint Laboratory of Environment Simulation and Pollution Control,Tsinghua University,Beijing 100084,China [4]State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex,Beijing 100084,China

出　　处：《Journal of Environmental Sciences》2023年第1期317-326,共10页环境科学学报（英文版）

基　　金：supported by National Key R&D Program of China(Nos.2019YFC0214800 and 2017YFC0212100);Beijing Municipal Science&Technology Commission(No.Z181100005418015)。

摘　　要：In recent years,with rapid increases in the number of vehicles in China,the contribution of vehicle exhaust emissions to air pollution has become increasingly prominent.To achieve the precise control of emissions,on-road remote sensing(RS)technology has been developed and applied for law enforcement and supervision.However,data quality is still an existing issue affecting the development and application of RS.In this study,the RS data from a cross-road RS system used at a single site(from 2012 to 2015)were collected,the data screening process was reviewed,the issues with data quality were summarized,a new method of data screening and calibration was proposed,and the effectiveness of the improved data quality control methods was finally evaluated.The results showed that this method reduces the skewness and kurtosis of the data distribution by up to nearly 67%,which restores the actual characteristics of exhaust diffusion and is conducive to the identification of actual clean and high-emission vehicles.The annual variability of emission factors of nitric oxide decreases by 60%-on average-eliminating the annual drift of fleet emissions and improving data reliability.

关 键 词：On-road remote sensing(RS) Data quality Spearman rank correlation Least-square regression with a non-zero intercept Cook value 

分 类 号：X513[环境科学与工程—环境工程] X87