Hu Qizhou, Bian Lishuang, Lin Juanjuan
School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, China.
Environ Monit Assess. 2021 May 7;193(6):330. doi: 10.1007/s10661-021-09111-0.
In this paper, the gas pollutants in motor vehicle exhaust are taken as the research object. The diagnostic index system of motor vehicle gas pollutants on environmental pollution is constructed, based on the environmental pollution caused by motor vehicle exhaust. The emission intensity of various types of vehicles was studied. The least-square method is used to construct the diagnostic functions of different types of vehicle gas pollutants; the vehicle emission factors of different types of motor vehicle gas pollutants are obtained. By exploring the spatial-temporal correlation of vehicle emissions under traffic conditions, uncertainty mathematical theory is used to establish a spatial-temporal diagnosis model of vehicle gas pollutants on environmental pollution, and multiple correlation coefficients are used to conduct accuracy test. The research results can not only determine the pollution problem of motor vehicle emissions to the environment but also effectively evaluate the emission level of gas pollutants in the exhaust gas of motor vehicles. The application results show that the spatial-temporal diagnostic model of vehicle gas pollutants for environmental pollution has better guiding significance and practical value in solving environmental pollution problems.
本文以机动车尾气中的气体污染物为研究对象。基于机动车尾气造成的环境污染,构建了机动车气体污染物对环境污染的诊断指标体系。研究了各类车辆的排放强度。采用最小二乘法构建不同类型车辆气体污染物的诊断函数;得到不同类型机动车气体污染物的车辆排放因子。通过探究交通条件下车辆排放的时空相关性,运用不确定性数学理论建立机动车气体污染物对环境污染的时空诊断模型,并采用复相关系数进行精度检验。研究结果不仅能确定机动车排放对环境的污染问题,还能有效评估机动车尾气中气体污染物的排放水平。应用结果表明,机动车气体污染物对环境污染的时空诊断模型在解决环境污染问题方面具有较好的指导意义和实用价值。