基于远程监测的北京市柴油车实际道路NOx与CO2排放特征

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Abstract The study adopted remote online monitoring technology to monitor the actual road operating parameters of typical diesel vehicles in Beijing, and conducted synchronous comparative tests with standard PEMS testing equipment to analyze the data consistency of remote online monitoring technology. A micro-operating mode division method applicable to Beijing's diesel vehicles was established based on the analysis, and the NO_x and CO₂ emission characteristics of typical diesel vehicles were analyzed based on micro-operating mode. The study results show that:1) the NO_x and CO₂ emissions rates of diesel vehicles monitored by remote online monitoring and PEMS testing data are both linearly fitted with R² higher than 0.99; 2) the micro-operating mode division of Beijing's diesel vehicles based on the established method conform to normal distribution, achieving the objective of uniformly dividing the vehicle's micro-operating conditions; 3) in different vehicle speed ranges, the NO_x and CO₂ emission factors of different types of vehicles show different trends, and the NO_x emission factor of vehicles with China VI emission standard is generally lower than that of vehicles with China V emission standard. The highest NO_x comprehensive emission factor belongs to China V heavy diesel vehicles, (7.63±0.57)g/km; as the tonnage increases, the CO₂ emission factor of diesel vehicles will increase to varying degrees and the CO₂ emission factor of China VI heavy diesel vehicles is relatively high, possibly due to the relatively complex after-treatment system of China VI vehicles increasing fuel consumption.

Key words： heavy-duty vehicles remote monitoring methods micro-operating mode division NO_x emission factor CO₂ emission factor

Received: 15 January 2023

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X511

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	FENG Qian
	LIU Bao-xian
	YANG Yan-yan
	ZHANG Shao-jun
	SHEN Xiu-e
	LU Yang
	WANG Peng-rui
	WU Ye

Cite this article:

FENG Qian,LIU Bao-xian,YANG Yan-yan等. Characteristics of actual road NO_x and CO₂ emissions from diesel vehicles in Beijing based on remote monitoring[J]. CHINA ENVIRONMENTAL SCIENCECE, 2023, 43(8): 4418-4426.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2023/V43/I8/4418

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