RESEARCH OF VEHICLE EMISSION CHARACTERISTICS IN ZHENGZHOU BASED ON HIGH-RESOLUTION DYNAMIC EMISSION INVENTORY

WANG Wennan; LIU Gege; WEI Hongge; REN Ge; HE Weinan; HU Yuxin; LIN Hong; FAN Yahui; YANG Yaohuan

doi:10.13205/j.hjgc.202410012

Volume 42 Issue 10

Oct. 2024

Turn off MathJax

Article Contents

Article Navigation > ENVIRONMENTAL ENGINEERING > 2024 > 42(10): 92-101

WANG Wennan, LIU Gege, WEI Hongge, REN Ge, HE Weinan, HU Yuxin, LIN Hong, FAN Yahui, YANG Yaohuan. RESEARCH OF VEHICLE EMISSION CHARACTERISTICS IN ZHENGZHOU BASED ON HIGH-RESOLUTION DYNAMIC EMISSION INVENTORY[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(10): 92-101. doi: 10.13205/j.hjgc.202410012

Citation:

WANG Wennan, LIU Gege, WEI Hongge, REN Ge, HE Weinan, HU Yuxin, LIN Hong, FAN Yahui, YANG Yaohuan. RESEARCH OF VEHICLE EMISSION CHARACTERISTICS IN ZHENGZHOU BASED ON HIGH-RESOLUTION DYNAMIC EMISSION INVENTORY[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(10): 92-101. doi: 10.13205/j.hjgc.202410012

Citation:

WANG Wennan, LIU Gege, WEI Hongge, REN Ge, HE Weinan, HU Yuxin, LIN Hong, FAN Yahui, YANG Yaohuan. RESEARCH OF VEHICLE EMISSION CHARACTERISTICS IN ZHENGZHOU BASED ON HIGH-RESOLUTION DYNAMIC EMISSION INVENTORY[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(10): 92-101. doi: 10.13205/j.hjgc.202410012

PDF( 5540 KB)

RESEARCH OF VEHICLE EMISSION CHARACTERISTICS IN ZHENGZHOU BASED ON HIGH-RESOLUTION DYNAMIC EMISSION INVENTORY

doi: 10.13205/j.hjgc.202410012

WANG Wennan¹,
LIU Gege^1,2,
WEI Hongge³,
REN Ge^{1,2
,
,},
HE Weinan^4,5,
HU Yuxin¹,
LIN Hong^1,2,
FAN Yahui³,
YANG Yaohuan⁶

1. Zhengzhou Institute of Metrology, Zhengzhou 450001, China;
2. National Institute of Metrology, Beijing 100029, China;
3. Zhengzhou Digital City Operation Management Center, Zhengzhou 450001, China;
4. Beijing Transportation Institute, Beijing 100073, China;
5. School of Environment, Tsinghua University, Beijing 100084, China;
6. Zhengzhou Big Data Development Co., Ltd., Zhengzhou 450001, China

Received Date: 2023-04-28
Available Online: 2024-11-30

Abstract

Abstract

To deeply understand the current situation of vehicle emissions in Zhengzhou and improve the level of mobile pollution sources management, a vehicular dynamic emission model based on the traffic flow characteristics and localized emission factors was established by integrating multi-source traffic big data, achieving the real-time calculation of on-road emission. Then a high spatio-temporal resolution on-road emission inventory in Zhengzhou was developed at the hourly and link level. The vehicle emission characteristics were analyzed by vehicle type, ring road, administrative division, and road type, and the measures for vehicle pollution control were proposed. The results showed that passenger cars were the major contributors to CO₂, CO, and HC emissions, while NO_x and PM emissions mainly came from trucks and coaches. The carbon emissions (including CO₂, CO, and HC) in Zhengzhou were mainly concentrated in the area of the 3rd Ring Road, with a gradually decreasing trend from downtown areas to urban fringes. The emissions of NO_x and PM were concentrated in ring roads with distinctive banding distribution. The analysis of the emission characteristics of administrative regions showed that the proportion of CO₂, CO, and HC emissions in Zhengdong New District and Jinshui District was more prominent, and NO_x and PM emissions in Zhongmu County and Xinzheng County were relatively heavier. Additionally, the CO₂ emission rate of urban expressways was as high as 3.66 t/(km·d), and the NO_x emission intensity on highways was the highest, at 0.017 t/(km·d). The research indicated that Zhengzhou could give priority to promoting green and low-carbon development in the downtown area and enhancing the level of truck pollution control, which contributed to the synergy of pollution and carbon emissions reduction from mobile sources and improvement of air quality.
- Zhengzhou,
- vehicular dynamic emission model,
- real-time calculation,
- high spatio-temporal resolution on-road emission inventory,
- vehicles,
- emission characteristics

FullText(HTML)

References(38)

References

[1]	ZHANG Q J, WU L, YANG Z W, et al. Characteristics of gaseous and particulate pollutants exhaust from logistics transportation vehicle on real-world conditions[J]. Transportation Research Part D: Transport and Environment, 2016, 43: 40-48.
[2]	柏洋洋, 何超, 李加强, 等. 基于GPS数据的重型柴油货车排放时空特征分析[J]. 环境工程,2023,41(4): 63-70 ,100.
[3]	刘佳泓, 刘胜楠, 刘茂辉, 等. 天津市环城某区小尺度VOCs排放清单及特征[J]. 环境工程, 2020, 38(8): 188-194 ,200.
[4]	ANENBERG S C, MILLER J,HENZE D K, et al. The global burden of transportation tailpipe emissions on air pollution-related mortality in 2010 and 2015[J]. Environmental Research Letters, 2019, 14(9):094012.
[5]	BAI X, CHEN H, OLIVER B G. The health effects of traffic-related air pollution: a review focused the health effects of going green[J]. Chemosphere, 2022, 289: 133082.
[6]	LELIEVELD J, EVANS J S, FNAIS M, et al. The contribution of outdoor air pollution sources to premature mortality on a global scale[J]. Nature, 2015, 525(7569): 367-371.
[7]	王计广, 桂华侨, 陈金潮, 等. 唐山市机动车排放清单与减排经济效益研究[J]. 中国环境科学, 2021, 41(11): 5114-5124.
[8]	MCDONALD B C, MCBRIDE Z C, MARTIN E W, et al. High-resolution mapping of motor vehicle carbon dioxide emissions[J]. Journal of Geophysical Research: Atmospheres, 2014, 119(9): 5283-5298.
[9]	PULIAFITO S E, ALLENDE D, PINTO S, et al. High resolution inventory of GHG emissions of the road transport sector in Argentina[J]. Atmospheric Environment, 2015, 101: 303-311.
[10]	SUN S D, JIN J X, XIA M, et al. Vehicle emissions in a middle-sized city of China: current status and future trends[J]. Environment International, 2020, 137: 105514.
[11]	孙世达, 金嘉欣, 吕建华,等. 基于精细化年均行驶里程建立机动车排放清单[J]. 中国环境科学, 2020, 40(5): 2018-2029.
[12]	ZHENG J Y, CHE W W, WANG X M, et al. Road-network-based spatial allocation of on-road mobile source emissions in the Pearl River Delta region, China, and comparisons with population-based approach[J]. Air Waste Manag Assoc, 2009, 59(12): 1405-1416.
[13]	JIANG P Y, ZHONG X, LI L Y. On-road vehicle emission inventory and its spatio-temporal variations in North China Plain[J]. Environmental Pollution, 2020, 267: 115639.
[14]	河南省统计局. 河南统计年鉴2022[M]. 北京: 中国统计出版社, 2023.
[15]	郑州市生态环境局. 关于郑州市机动车单双号限行建议的答复[EB/OL]. 郑州: 郑州市生态环境局官网(2021-04-10)[2021-09-28]. https://public.zhengzhou.gov.cn/D1101X/5927684.jhtml.
[16]	郑州市生态环境局. 关于对郑州市政协十四届二次会议第20190751号提案的答复[EB/OL]. 郑州: 郑州市生态环境局官网(2019-04-25 )[2019-11-19]. https://public.zhengzhou.gov.cn/D1102X/310635.jhtml.
[17]	卢轩, 张瑞芹, 韩跞锎. 郑州市VOCs组分排放清单及其臭氧生成潜势[J]. 环境科学, 2020, 41(10): 4426-4435.
[18]	GU X K, YIN S S, LU X, et al. Recent development of a refined multiple air pollutant emission inventory of vehicles in the Central Plains of China[J]. Journal of Environmental Sciences, 2019, 84: 80-96.
[19]	赵大地, 张宇, 史旭荣, 等. 河南省1 km分辨率机动车大气污染物排放清单[J]. 环境污染与防治, 2022, 44(4): 469-475.
[20]	GONG M M, YIN S S, GU X K, et al. Refined 2013-based vehicle emission inventory and its spatial and temporal characteristics in Zhengzhou, China[J]. Science of the Total Environment, 2017, 599/600: 1149-1159.
[21]	JING B, WU L, MAO H, et al. Development of a vehicle emission inventory with high temporal-spatial resolution based on NRT traffic data and its impact on air pollution in Beijing-Part 1: development and evaluation of vehicle emission inventory[J]. Atmospheric Chemistry & Physics Discussions, 2015, 15(13): 19239-19273.
[22]	ZHANG S J, NIU T L, WU Y, et al. Fine-grained vehicle emission management using intelligent transportation system data[J]. Environmental Pollution, 2018, 241: 1027-1037.
[23]	JING B Y, WU L, MAO H J, et al. Development of a vehicle emission inventory with high temporal-spatial resolution based on NRT traffic data and its impact on air pollution in Beijing-Part 1: development and evaluation of vehicle emission inventory[J]. Atmospheric Chemistry and Physics Discussions, 2016, 16(5): 3161-3170.
[24]	AERDE M V, RAKHA H. Multivariate calibration of single regime speed-flow-density relationships [road traffic management][C]//Vehicle Navigation & Information Systems Conference. IEEE, 1995.
[25]	US Environmental Protection Agency. MOVES2014a software design reference manual[EB/OL]. Washington DC: US EPA (2015-11). https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100NNKC.txt.
[26]	US Environmental Protection Agency. Exhaust emission rates for light-duty on-road vehicles in MOVES2014[EB/OL]. Washington DC: US EPA (2015-10). https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100NNVN.pdf.
[27]	US Environmental Protection Agency. Exhaust emission rates for heavy-duty on-road vehicles in MOVES2014[EB/OL]. Washington DC: US EPA (2015-11). https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100NO46.pdf.
[28]	WU Y, ZHANG S J, LI M L, et al. The challenge to NO_<em>x emission control for heavy-duty diesel vehicles in China[J]. Atmospheric Chemistry and Physics, 2012, 12(19): 9365-9379.
[29]	殷子渊, 张凯山. 典型城市轻型汽油车尾气排放模式分析[J]. 环境工程, 2021, 39(4): 64-71.
[30]	李加强, 葛蕴珊, 何超, 等. 发动机工况与行驶挡位对轻型汽油车道路排放的影响[J]. 环境工程, 2018, 36(12): 130-134 ,154.
[31]	黄志辉, 付明亮, 马东. 移动源排放清单测算方法[M]. 北京: 中国环境出版集团, 2021: 25-28.
[32]	刘亚飞, 赵永明, 李丽, 等. 基于高时空辨识度实时数据的重庆二环内外区域车流特征差异分析[J]. 环境科学研究, 2021, 34(7): 1602-1611.
[33]	Li Y X, LV C, YANG N, et al. A study of high temporal-spatial resolution greenhouse gas emissions inventory for on-road vehicles based on traffic speed-flow model: a case of Beijing[J]. Journal of Cleaner Production, 2020, 277: 1-21.
[34]	郑州市交通运输局. 郑州市交通运输委员会关于印发郑州市营运黄标车及老旧车淘汰工作实施方案的通知[EB/OL]. 郑州: 郑州市交通运输局官网(2015-08-31)[2015-12-29]. https://public.zhengzhou.gov.cn/07EBA/145588.jhtml.
[35]	河南省人民政府. 郑州发布市区道路交通管理措施通告货车挂车等车辆四环内通行有变[EB/OL]. 郑州: 河南省人民政府官网(2021-11-30)[2021-11-30]. https://www.henan.gov.cn/2021/11-30/2357319.html.
[36]	河南省人民政府. 关于印发河南省推广使用国家第六阶段标准车用乙醇汽油车用柴油工作方案的通知[EB/OL]. 郑州: 河南省人民政府官网(2018-06-20)[2018-07-06]. https://www.henan.gov.cn/2018/07-06/662874.html.
[37]	刘彬. 西安市机动车污染排放及其对空气质量的潜在影响[D]. 西安:陕西师范大学, 2022.
[38]	清华大学. 中国多尺度排放清单模型V1.4[EB/OL]. 北京: MEICModel官网 (2023-05). http://meicmodel.org.cn/.