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重型柴油车实际道路氮氧化物和碳排放研究

Emissions of nitrogen oxides and carbon dioxide from heavy-duty diesel vehicles based on remote monitoring
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摘要 通过对20辆国五及国六重型柴油车排放远程监控数据分析,分别使用3B-MAW方法、总行程平均法以及功基窗口法对数据进行分析,获取了重型柴油车在实际道路上的NO_(x)和CO_(2)排放特征.数据分析结果表明国六重型柴油车实际道路NO_(x)排放显著低于国五重型柴油车,且二者在中/高负荷工况下的NO_(x)排放相比低负荷时亦有明显降低.但国六重型柴油车的CO_(2)排放却比国五重型柴油车高出10%左右,应引起广泛重视.按窗口功率比大小进行NO_(x)排放分析的3B-MAW方法,既能考虑到重型柴油车道路排放特点,又能兼顾SCR催化剂对NO_(x)排放控制的技术特点,适合用于进行重型柴油车排放远程监控数据评价分析. Heavy-duty vehicles have become one of the major NO_(x)pollution sources in China,as well as a key contributor of motor vehicles’CO_(2)emissions.Therefore,controlling NO_(x)and CO_(2)emissions from heavy-duty vehicles is the top priority in energy saving and emission reduction of motor vehicles.This paper investigated the real-road NO_(x)and CO_(2)emission features of heavy-duty diesel vehicles by analysing the remotely monitored emission data of some typical China-5 and China-6 diesel vehicles.The results show that the real-road NO_(x)emission level of China-6heavy-duty diesel vehicles is significantly lower than that of China-5 counterparts.However,the CO_(2)emission level is about 10%higher from China-6 heavy-duty vehicles than from China-5 counterparts.The 3B-MAW method for NO_(x)emission analysis based on window power ratios can take into account not only the real-road emission characteristics of heavy-duty diesel vehicles,but also the technical features of SCR catalysts for NO_(x)emission control,and is suitable for the evaluation of remote monitoring data of heavy-duty diesel vehicle emissions.
作者 葛子豪 尹航 徐龙 杨扬 吉喆 黄英 GE Zi-hao;YIN Hang;XU Long;YANG Yang;JI Zhe;HUANG Ying(Beijing Institute of Technology,Beijing 100081,China;Chinese Research Academy of Environmental Sciences,Beijing 100012,China;Weichai Power CO.Ltd.,Weifang 261062,China)
出处 《中国环境科学》 EI CAS CSCD 北大核心 2024年第2期646-653,共8页 China Environmental Science
基金 国家重点研发计划(2022YFC3701802) 国家自然科学基金资助项目(52272342) 青海省科技厅重大专项(2019-GX-A6)。
关键词 重型柴油车 远程排放监控 NO_(x)排放 CO_(2) heavy-duty diesel vehicles remote emission monitoring NO_(x)emissions CO_(2)
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