Research on vehicle emission trajectory based on vehicle identification data
LIN Ying1,2,3, DING Hui1,2,3, LIU Yong-hong1,2,3, LIN Xiao-fang1,2,3, SHA Zhi-ren4, MIAO Shen-hua1,2,3, HUANG Wen-feng1,2,3
1. School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou 510006, China;
2. Guangdong Provincial Engineering Research Center for Traffic Environmental Monitoring and Control, Guangzhou 510275, China;
3. Guangdong Provincial Key Laboratory of Intelligent Transport System, Guangzhou 510275, China;
4. Guangdong Fundway Science and Technology Corporation Limited, Guangzhou 510275, China
To track the dynamic emission trajectory of an individual vehicle, a method for calculating the emission trajectory was established based on the second by second vehicle passing records from Electronic Police system. Taking the urban center of Xuancheng, Anhui Province as the study area, which has 123 road links, 44,672,343emission trajectories of 133,906 vehicles from May 10 to June 9 in 2018 were calculated using the operational parameters from the reconstructed trajectories, the technical parameters from the motor vehicle database, as well as the emission factors from International Vehicle Emission Model. The results show that, taxi contributed more to CO emissions and the emission intensity was high on the road links near points of interest. Bus and heavy-duty truck were the main sources of NOx emissions. The total amount of NOx emissions from bus on workday was nearly 1.3kg, which was about 7.5 times higher than that of the heavy-duty truck. For bus, the bus route was fixed and the temporal-spatial distribution of emissions showed a certain periodicity according to the bus frequency. The trajectory of light-duty truck was mainly determined by freight demand, which often travels during the day. On the other hand, the heavy-duty truck was more inclined to travel in the early morning. The commuting private car made regular travel during workdays, hence the pollutant emissions were relatively stable in the round-trip process. For the whole road network, the high emission intensity areas of CO and VOCs were concentrated in the central road network, while for NOx and PM, they were mainly distributed in the peripheral road network.
中华人民共和国环境保护部.中国机动车污染防治年报(2018版)[R]. 北京:中华人民共和国环境保护部, 2018. Ministry of Environmental Protection of the People's Republic of China. China Vehicle Environmental Management Annual Report (2018)[R]. Beijing:Ministry of Environmental Protection of the People's Republic of China, 2018.
[2]
单丽,江飞,贺晓婧,等.中国道路交通源大气污染的健康影响评估[J]. 中国环境管理, 2018,10(5):59-64. Shan L, Jiang F, He X J, et al. Health impact assessment of air pollution from road traffic sources in China[J]. Chinese Journal of Environmental Management, 2018,10(5):59-64.
[3]
宋兵跃,胡可臻,吴建平,等.不同交通模式下CO和NOx的暴露水平研究[J]. 中国环境科学, 2014,34(11):2734-2740. Song B Y, Hu K Z, Wu J P, et al. Exposure to CO and NOx in different transport modes[J]. China Environmental Science, 2014,34(11):2734-2740.
[4]
中华人民共和国国务院.国务院关于印发大气污染防治行动计划的通知[EB/OL]. http://www.gov.cn/zwgk/2013-09/12/content_2486773.htm, 2013-09-10/2019-08-01. The State Council of the People's Republic of China. Notice of the State Council on Issuing the Action Plan forPrevention and Control of Air Pollution[EB/OL]. http://www.gov.cn/zwgk/2013-09/12/content_2486773.htm, 2013-09-10/2019-08-01.
[5]
中华人民共和国生态环境部.关于印发《柴油货车污染治理攻坚战行动计划》的通知[EB/OL]. http://www.mee.gov.cn/xxgk2018/xxgk/xxgk03/201901/t20190104_688587.html, 2019-01-04/2019-08-01. Ministry of Ecology and Environment of the People's Republic of China. Notice on Issuing the Action Plan for Pollution Control of Diesel Trucks[EB/OL]. http://www.mee.gov.cn/xxgk2018/xxgk/xxgk03/201901/t20190104_688587.html, 2019-01-04/2019-08-01.
[6]
中华人民共和国环境保护部.关于印发全国机动车环境管理能力建设标准的通知[EB/OL]. http://www.mee.gov.cn/gkml/hbb/bwj/201411/t20141102_290976.htm, 2013-09-25/2019-08-01. Ministry of Environmental Protection of the People's Republic of China. Notice on Issuing the National Standards for Capacity Building of Motor Vehicle Environmental Management[EB/OL]. http://www.mee.gov.cn/gkml/hbb/bwj/201411/t20141102_290976.htm, 2013-09-25/2019-08-01.
[7]
杨博.机动车排放污染管理现状问题分析[J]. 建材与装饰, 2018, (39):224. Yang B. Analysis on the present situation and existing problems of vehicle emission pollution management[J]. Construction Materials & Decoration, 2018,(39):224.
[8]
高杰.机动车道路交通管理中的限制性政策探析[J]. 黔南民族师范学院学报, 2015,35(6):98-101. Gao J. The analysis of restrictive policies in the road traffic management of the motor vehicle[J]. Journal of Qiannan Normal College for Nationalities, 2015,35(6):98-101.
[9]
朱怡静.中外机动车管理政策对比分析[C].//《环境工程》编委会、工业建筑杂志社有限公司.《环境工程》2018年全国学术年会论文集(中册).《环境工程》编委会、工业建筑杂志社有限公司:《环境工程》编辑部, 2018:6. Zhu Y J. Vehicle regulation and policy comparisons between China and foreign countries[A].//Editorial Board of Environmental Engineering, Industrial Architecture Magazine Co., Ltd.:Papers Collection of 2018 National Academic Annual Conference of Environmental Engineering (Volume 2)[C]. Editorial Board of Environmental Engineering, Industrial Architecture Magazine Co., Ltd.:Environmental Engineering, 2018:6.
[10]
易兰,周忆南,李朝鹏,等.城市机动车限行政策对雾霾污染治理的成效分析[J]. 中国人口·资源与环境, 2018,28(10):81-87. Yi L, Zhou Y N, Li Z P, et al. Analysis of the effects of driving restriction policies in controlling haze pollution[J]. China Population, Resources and Environment, 2018,28(10):81-87.
[11]
刘跃军.完善机动车调控政策精细化管理水平的几点建议[A].//中国智能交通协会.第十三届中国智能交通年会大会论文集[C]. 中国智能交通协会:中国智能交通协会, 2018:7. Liu Y J. Some suggestions on improving the fine management of urban traffic policy[C]//China Intelligent Transportation Systems Association:Papers Collection of the 13th China Intelligent Transportation Annual Conference. China Intelligent Transportation Systems Association, 2018:7.
[12]
杨雯,王学军,张倩茹.基于高精度清单的京津冀机动车控污政策研究[J]. 中国环境科学, 2018,38(8):2803-2810. Yang W, Wang X J, Zhang Q R. Vehicle pollution control policy study on the Beijing-Tianjin-Hebei region, based on a high-precision emission inventory[J]. China Environmental Science, 2018,38(8):2803-2810.
[13]
孙世达,姜巍,高卫东.青岛市机动车排放清单与空间分布特征[J]. 中国环境科学, 2017,37(1):49-59. Sun S D, Jiang W, Gao W D. Vehicle emission inventory and spatial distribution in Qingdao[J]. China Environmental Science, 2017, 37(1):49-59.
[14]
Yang W, Yu C, Yuan W, et al. High-resolution vehicle emission inventory and emission control policy scenario analysis, a case in the Beijing-Tianjin-Hebei (BTH) region, China[J]. Journal of Cleaner Production, 2018,203:530-539.
[15]
中华人民共和国环境保护部.道路机动车大气污染物排放清单编制技术指南[Z]. 北京:中华人民共和国环境保护部, 2014. Ministry of Environmental Protection of the People's Republic of China. National Emission Inventory Guidebook for On-road Vehicles[Z]. Beijing:Ministry of Environmental Protection of the People's Republic of China, 2014.
[16]
Liu Y, Ma J, Li Li, et al. A high temporal-spatial vehicle emission inventory based on detailed hourly traffic data in a medium-sized city of China[J]. Environmental Pollution, 2018,236:324-333.
[17]
Zhang S, Niu T, Wu Ye, et al. Fine-grained vehicle emission management using intelligent transportation system data[J]. Environmental Pollution, 2018,241:1027-1037.
[18]
Wu K, Chen Y, Ma J, et al. Traffic and emissions impact of congestion charging in the central Beijing urban area:A simulation analysis[J]. Transportation Research Part D:Transport and Environment, 2017,51(3):203-215.
[19]
Pu Y, Yang C, Liu H, et al. Impact of license plate restriction policy on emission reduction in Hangzhou using a bottom-up approach[J]. Transportation Research Part D, 2015,34:281-292.
[20]
Samaras C, Tsokolis D, Toffolo S, et al. Improving fuel consumption and CO2 emissions calculations in urban areas by coupling a dynamic micro traffic model with an instantaneous emissions model[J]. Transportation Research Part D:Transport and Environment, 2018, 65(12):772-783.
[21]
Zhao Y, Sadek A W. Computationally-Efficient Approaches to Integrating the MOVES Emissions Model with Traffic Simulators[J]. Procedia Computer Science, 2013,19:882-887.
