考虑车辆类型变化的中国乘用车排放特征

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Abstract The paper introduced the Lotka-Volterra model to predict the trend of passenger car competition in China in the next 30years. Six pollutants of CHG, VOC, CO, SO₂, PM_2.5, and NO_x were included to update the life cycle list; then policy impact models and sensitivity models were established to evaluate the emission reduction effects of electrification, lightweight and clean policy scenarios. The main competitiveness of the passenger car market come from the competition between new energy and traditional energy. Blade electric passenger cars and hybrid passenger cars will develop in an S-shaped curve, meanwhile, the market share of gasoline passenger cars will be reduced from 92% to 1%. From the perspective of life cycle, blade electric passenger cars had the best emissions reduction benefits for CHG, VOC, and CO, which was 20%~85%. Gasoline and natural gas passenger cars had the best emissions reduction benefits for SO₂ and PM_2.5, which was 50.0%. In three scenarios, the tax subsidy policy was the most sensitive factor, and the optimal emission reduction scenario for CHG, VOC and CO was electrification scenario, the optimal emission reduction scenario for PM_2.5 and NO_x was clean scenario, and the optimal emission reduction scenario for SO₂ was lightweight scenario.

Key words： emission characteristics L-V model life cycle policy evaluation passenger car types

Received: 27 November 2020

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	Articles by authors
	GUO Dong
	YAN Wei
	TAN Xiao-chuan
	GAO Song
	GAO Xing-bang
	ZHANG Tong-qing

Cite this article:

GUO Dong,YAN Wei,TAN Xiao-chuan等. Emission characteristics of passenger cars in China considering the change of vehicle types[J]. CHINA ENVIRONMENTAL SCIENCECE, 2021, 41(7): 3138-3152.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2021/V41/I7/3138

[1]	2020年中国移动源环境管理年报——第Ⅰ部分机动车排放情况[J]. 环境保护, 2020,48(16):47-50. Annual report on environmental management of China Mobile in 2020-Part I motor vehicle emissions[J]. Environmental Protection, 2020,48(16):47-50.
[2]	焦燕青.新能源汽车扩散驱动因素及市场保有量预测研究[J]. 汽车实用技术, 2020,45(17):33-37. Jiao Y Q. Research on diffusion driving factors and market share prediction of new energy vehicles[J]. Automotive Practical Technology, 2020,45(17):33-37.
[3]	李寻,杨心怡,郭莉,等.基于系统动态扩散模型的新能源汽车数量预测[C]//品质交通与协同共治——2019年中国城市交通规划年会论文集.北京:中国城市规划学会城市交通规划学术委员会, 2019:3678-3690. Li X, Yang X Y, Guo L, et al. Prediction of the number of new energy vehicles based on the system dynamic diffusion model[C]//Quality transport and collaborative governance:Proceedings of the annual meeting of China urban transport planning in 2019. Beijing:Urban Transportation Planning Academic Committee of China Urban Planning Society, 2019:3678-3690.
[4]	谭涛,黄泽涛,林雁玲,等.大数据驱动的我国新能源汽车需求分析[J]. 可再生能源, 2020,38(7):967-971. Tan T, Huang Z T, Lin Y L, et al. Big data driven demand analysis of new energy vehicles in China[J]. Renewable Energy, 2020,38(7):967-971.
[5]	刘媛.新能源汽车销量的长期与短期预测[D]. 长春:吉林大学, 2020. Liu Y. Long term and short-term forecast of new energy vehicle sales[D]. Changchun:Jilin University, 2020.
[6]	白冰,赵红梅,张素梅,等.基于神经网络的东北地区秸秆焚烧预测[J]. 中国环境科学, 2020,40(12):5205-5212. Bai B, Zhao H M, Zhang S M, et al. Prediction of straw burning in Northeast China based on neural network[J]. China Environmental Science, 2020,40(12):5205-5212.
[7]	赵晓,常化振,彭思洋,等.中国生物质燃气产能及碳减排潜力[J]. 中国环境科学, 2018,38(8):3151-3159. Zhao X, Chang H Z, Peng S Y, et al. Biomass gas production capacity and carbon emission reduction potential in China[J]. China Environmental Science, 2018,38(8):3151-3159.
[8]	杨伟,李晓华,张海珍,等.基于L-V模型的重庆两江新区生产性服务业与现代制造业协同发展实证研究[J]. 西南师范大学学报(自然科学版), 2019,44(2):68-74. Yang W, Li X H, Zhang H Z, et al. An empirical study on the collaborative development of producer services and modern manufacturing industry in Liangjiang New Area of Chongqing based on L-V model[J]. Journal of Southwest Normal University (Natural Science Edition), 2019,44(2):68-74.
[9]	Xu F F, Gan W Z. On a Lotka-Volterra type competition model from river ecology[J]. Nonlinear Analysis:Real World Applications, 2019, 47:373-384.
[10]	陈蔚,段仲渊,宋家骅,等.城市机动车能耗排放核算平台建设——以深圳市为例[J]. 城市交通, 2018,16(5):64-70,78. Chen W, Duan Z Y, Song J H, et al. Construction of urban vehicle energy consumption and emission accounting platform:a case study of Shenzhen[J]. Urban Transportation, 2018,16(5):64-70,78.
[11]	周华,赵宏伟,吴蒙蒙,等.IVE模型中区间划分方法对排放因子估算的影响[J]. 中国环境科学, 2019,39(2):560-564. Zhou H, Zhao H W, Wu M M, et al. Effect of inter region partition method on emission factor estimation in IVE model[J]. China Environmental Science, 2019,39(2):560-564.
[12]	Feng J J, Zhang Y L, Song W, et al. Emissions of nitrogen oxides and volatile organic compounds from liquefied petroleum gas-fueled taxis under idle and cruising modes[J]. Environmental Pollution, 2020,267:115623.
[13]	Huang Y H, Yu Y, Yam Y, et al. Statistical evaluation of on-road vehicle emissions measurement using a dual remote sensing technique[J]. Environmental Pollution, 2020,267:115456.
[14]	Cornec C, Molden N, Reeuwijk M V, et al. Modelling of instantaneous emissions from diesel vehicles with a special focus on NOx:Insights from machine learning techniques[J]. Science of the Total Environment, 2020,737:139625.
[15]	杜强.基于近景摄影测量的车辆运行排放污染评估方法研究[J]. 环境科学与管理, 2019,44(3):145-148,157. Du Q. Study on assessment method of vehicle emission based on close range photogrammetry[J]. Environmental Science and Management, 2019,44(3):145-148,157.
[16]	胥耀方,于雷,宋国华.基于遗传算法的运行模式分布模型及排放测算[J]. 中国环境科学, 2016,36(12):3548-3559. Xu Y F, Yu L, Song G H. Operation mode distribution model and emission calculation based on genetic algorithm[J]. China Environmental Science, 2016,36(12):3548-3559.
[17]	Qiao Q Y, Zhao F Q, Liu Z W, et al. Life cycle greenhouse gas emissions of Electric Vehicles in China:Combining the vehicle cycle and fuel cycle[J]. Energy, 2019,177:222-233.
[18]	陈莎,孙中梅,李素梅,等.动态生命周期评价的研究与应用现状[J]. 中国环境科学, 2018,38(12):4764-4771. Chen S, Sun Z M, Li S M, et al. The research and application status of dynamic life cycle assessment[J]. China Environmental Science, 2018,38(12):4764-4771.
[19]	Zhang Q R, Tong P F, Liu M D, et al. A WRF-Chem model-based future vehicle emission control policy simulation and assessment for the Beijing-Tianjin-Hebei region, China[J]. Journal of Environmental Management, 2020,253:109751.
[20]	揭俐,王忠,余瑞祥.中国能源开采业碳排放脱钩效应情景模拟[J]. 中国人口·资源与环境, 2020,30(7):47-56. Jie L, Wang Z, Yu R X. Scenario simulation of decoupling effect of carbon emission in China's energy mining industry[J]. China's Population, Resources and Environment, 2020,30(7):47-56.
[21]	余志林,丁浩,王信敏.基于系统动力学的山东省油气产业能耗控制研究[J]. 中国人口·资源与环境, 2019,29(5):79-87. Yu Z L, Ding H, Wang X M. Study on energy consumption control of oil and gas industry in Shandong Province Based on system dynamics[J]. China Population, Resources and Environment, 2019,29(5):79-87.
[22]	Bellocchi S, Gambini M, Manno M, et al. Positive interactions between electric vehicles and renewable energy sources in CO2-reduced energy scenarios:The Italian case[J]. Energy, 2018,161:172-182.
[23]	Kawajiri K, Kobayashi M, Sakamoto K. Lightweight materials equal lightweight greenhouse gas emissions:A historical analysis of greenhouse gases of vehicle material substitution[J]. Journal of Cleaner Production, 2020,253:119805.
[24]	陈丽玲,雷智鹢,朱逸凡,等.基于改进L-V模型的多货种多港口竞合关系[J]. 长沙理工大学学报(自然科学版), 2018,15(3):40-47. Chen L L, Lei Z Y, Zhu Y F, et al. Competition cooperation relationship of multi cargo and multi port based on improved L-V model[J]. Journal of Changsha University of Technology (Natural Science Edition), 2018,15(3):40-47.
[25]	唐秋生,汪勇,聂化东.基于"灰色L-V"模型的综合交通竞合体系预判[J]. 公路工程, 2017,42(1):96-100,114. Tang Q S, Wang Y, Nie H D. Prediction of comprehensive traffic competition and cooperation system based on "Grey L-V" model[J]. Highway Engineering, 2017,42(1):96-100,114.
[26]	Montano M C, Lisena B. Diffusive Lotka-Volterra competition models on periodically evolving domains[J]. Journal of Mathematical Analysis and Applications, 2020,484(1).
[27]	郭栋,张洪浩,郑春燕,等.未来中国汽车类型发展预测及节能减排效益分析[J]. 系统工程理论与实践, 2016,36(6):1593-1599. Guo D, Zhang H H, Zheng C Y, et al. Prediction of future development of China's automobile types and analysis of energy saving and emission reduction benefits[J]. System Engineering Theory and Practice, 2016,36(6):1593-1599.
[28]	Gilmore E A, Patwardhan A. Passenger vehicles that minimize the costs of ownership and environmental damages in the Indian market[J]. Applied Energy, 2016,184:863-872.
[29]	Ren L, Zhou S, Ou X M. Life-cycle energy consumption and greenhouse-gas emissions of hydrogen supply chains for fuel-cell vehicles in China[J]. Energy, 2020,209:118482.
[30]	Peng T D, Ou X M, Yan X Y. Development and application of an electric vehicles life-cycle energy consumption and greenhouse gas emissions analysis model[J]. Chemical Engineering Research and Design, 2018,131:699-708.
[31]	国家统计局.中国能源统计年鉴2018[M]. 北京:中国统计出版社, 2018. National Bureau of statistics. China energy statistics yearbook 2018[M]. Beijing:China Statistics Press, 2018.
[32]	中国煤炭工业协会.2017中国煤炭工业发展研究报告[M]. 北京:中国经济出版社, 2018. China Coal Industry Association. 2017 China coal industry development research report[M]. Beijing:China Economic Publishing House, 2018.
[33]	《中国电力年鉴》编委会.2018中国电力年鉴[M]. 北京:中国电力出版社, 2018. "China Electric Power Yearbook" Editorial Board. 2018 China electric power yearbook[M]. Beijing:China Electric Power Press, 2018.
[34]	中国汽车技术研究中心,中国汽车工业协会.中国汽车工业年鉴[M]. 北京:《中国汽车工业年鉴》期刊社, 2018. China Automotive Technology Research Center, China Automotive Industry Association. China automotive industry yearbook[M]. Beijing:China Automotive Industry Yearbook, 2018.
[35]	徐建全,杨沿平.考虑回收利用过程的汽车产品全生命周期评价[J]. 中国机械工程, 2019,30(11):1343-1351. Xu J Q, Yang Y P. Life cycle assessment of automotive products considering recycling process[J]. China Mechanical Engineering, 2019,30(11):1343-1351.
[36]	汽车生命周期温室气体及大气污染物排放评价方法[R]. 北京:中国汽车工程学会, 2018. Evaluation method of greenhouse gas and air pollutant emissions in automobile life cycle[R]. Beijing:Chinese Society of Automotive Engineering, 2018.
[37]	欧训民,彭天铎,张茜.中国电动汽车的发展规模及其能源环境资源影响研究[M]. 北京:经济管理出版社, 2019. Ou X M, Peng T D, Zhang X. Research on the development scale of electric vehicles and its impact on energy, environment and resources in China[M]. Beijing:Economic Management Press, 2019.
[38]	欧训民,张希良.中国车用能源技术路线全生命周期分析[M]. 北京:清华大学出版社, 2019:10. Ou X M, Zhang X L. Life cycle analysis of China's automotive energy technology route[M]. Beijing:Tsinghua University press, 2019:10.
[39]	中国生态环境状况公报2019[R]. 北京:中华人民共和国生态环境部.2020. Bulletin of ecological environment in China 2019[R]. Beijing:Ministry of Ecological Environment of the People's Republic of China, 2020.
[40]	中国汽车低碳行动计划研究报告2020[R]. 天津:中汽数据有限公司, 2020. China automotive low-carbon action plan research report 2020[R] Tianjin:China Automotive Data Co., Ltd., 2020.
[41]	中华人民共和国国民经济和社会发展第十三个五年规划纲要[R]. 北京:国务院, 2016. Outline of the 13th five year plan for national economic and social development of the people's Republic of China[R]. Beijing:State Council, 2016.
[42]	安锋,康利平,秦兰芝,等.中国传统燃油汽车退出时间表研究[J]. 国际石油经济, 2019,27(5):1-8. An F, Kang L P, Qin L Z, et al. A study on the exit schedule of Chinese traditional fuel vehicles[J]. International Petroleum Economy, 2019, 27(5):1-8.
[43]	中华人民共和国统计局.中国统计年鉴2019[M]. 北京:中国统计出版社, 2019. Bureau of statistics of the people's Republic of China. China statistical yearbook 2019[M]. Beijing:China Statistics Press, 2019.
[44]	国家统计局.中国环境统计年鉴2018[M]. 北京:中国统计出版社, 2018. National Bureau of statistics. China environmental statistics yearbook 2018[M]. Beijing:China Statistics Press, 2018.
[45]	中国移动源环境管理年报2012~2018[R]. 北京:生态环境部, 2013-2019. China mobile source environmental management annual report 2012~2018[R]. Beijing:Ministry of Ecology and Environment, 2013-2019.
[46]	Galeotti M, Salini S, Verdolini E. Measuring environmental policy stringency:Approaches, validity, and impact on environmental innovation and energy efficiency[J]. Energy Policy, 2020,136:111052.
[47]	Emodi N V, Chaiechi T, Alam Beg A R. A techno-economic and environmental assessment of long-term energy policies and climate variability impact on the energy system[J]. Energy Policy, 2019,128:329-346.
[48]	王馨康,任胜钢,李晓磊.不同类型环境政策对我国区域碳排放的差异化影响研究[J]. 大连理工大学学报(社会科学版), 2018,39(2):55-64. Wang X K, Ren S G, Li X L. The impact of different types of environmental policies on regional carbon emissions in China[J]. Journal of Dalian University of Technology (Social Science Edition), 2018,39(2):55-64.
[49]	李美水,杨晓华.基于Sobol方法的SWMM模型参数全局敏感性分析[J]. 中国给水排水, 2020,36(17):95-102. Li M S, Yang X H. Global sensitivity analysis of SWMM model parameters based on Sobol method[J]. China Water & Wastewater, 2020,36(17):95-102.
[50]	电力发展"十四五规划"方案[R]. 北京:国家能源局综合司,2020. The Fourteenth five-year plan for electric power development[R]. Beijing:Comprehensive Department of National Energy Administration, 2020.
[51]	财政部,工业和信息化部,科技部,发展改革委. 关于进一步做好新能源汽车应用推广应用工作的通知[EB/OL]. http://www.gov.cn/xinwen/2014-02/08/content_2612978.htm/2014-02-08. Ministry of Finance, Ministry of Industry and Information Technology, Ministry of Science and Technology, National Development and Reform Commission. Notice on further promoting the application of new energy vehicles[EB/OL]. http://www.gov.cn/xinwen/2014-02/08/content_2612978.htm/2014-02-08.
[52]	中国制造2025[R]. 北京:国务院,2015. Made in China 2025[R]. Beijing:State Council, 2015.
[53]	杨冰融.基于多元线性回归与BP神经网络的乘用车市场预测模型[D]. 武汉:华中科技大学, 2017. Yang B R. Passenger car market forecast model based on multiple linear regression and BP neural network[D]. Wuhan:Huazhong University of Science and Technology, 2017.
[54]	李捷,刘森.基于Gompertz模型变换的中国乘用车保有量预测[J]. 汽车与配件, 2018,(35):68-69. Li J, Liu S. Prediction of China's passenger car ownership based on Gompertz model transformation[J]. Automobiles and Accessories, 2018(35):68-69.