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基于MOVES模型的污染物排放相关性分析

Correlation Analysis of Pollutant Emission Based on MOVES Model
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摘要 道路机动车排放是大气污染物的重要来源,同时也是量化评价最困难的污染源之一。目前,国内主要利用MOVES模型进行道路机动车排放预测,但在参数本地化时进行地理区域选择方面缺少深入分析,基于太原实际的道路交通流信息,共选取8个相近地理区域,模拟得出机动车CO,CH_(4),NO_(x),PM_(2.5)污染物排放量,并运用SPSS进行污染物排放量与所选地理区域纬度和海拔相关性分析。结果显示:在纬度确定的情况下,海拔和污染物排放量不存在显著相关;在海拔确定的情况下,纬度和污染物CH 4,NO_(x),PM_(2.5)排放量不存在显著相关性,但与CO排放量存在显著相关性。 Road vehicle emission is the important contributor of air pollutants,and it is also one of the most difficult pollution sources to quantify.At present,the MOVES model is mainly used to predict road vehicle emissions in China,but in-depth analysis is lacking in the selection of geographical regions during parameter localization.Based on the actual road traffic flow information in Taiyuan,this paper selects a total of 8 similar geographical regions to simulate the emission of vehicle CO,CH_(4),NO_(x) and PM_(2.5) pollutants.The correlation between pollutant discharge and latitude and altitude of the selected geographical areas was analyzed based on SPSS.The results show:there is no significant correlation between altitude and pollutant discharge when latitude is determined;at a given altitude,latitude has no significant correlation with the emissions of pollutants CH 4,NO_(x) and PM_(2.5),but has significant correlation with those of CO.
作者 杨阳 刘敏 YANG Yang;LIU Min(School of Vehicle and Traffic Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China)
出处 《太原学院学报(自然科学版)》 2025年第1期47-54,共8页 Journal of TaiYuan University:Natural Science Edition
基金 山西省回国留学人员科研资助项目(2024-126)。
关键词 机动车排放 MOVES模型 SPSS软件 污染物排放相关性分析 motor vehicle emission MOVES model SPSS software pollutant emission correlation analysis
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