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Ammonia in urban atmosphere can be substantially reduced by vehicle emission control:A case study in Shanghai, China

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Journal of Environmental Sciences 2023年第4期126卷 754-760页

作者： Can Wu Shaojun Lv Fanglin Wang Xiaodi Liu Jin Li Lang Liu Si Zhang Wei Du Shijie Liu Fan Zhang Jianjun Li Jingjing Meng Gehui Wang Key Lab of Geographic Information Science of the Ministry of Education School of Geographic SciencesEast China Normal UniversityShanghai 200062China Institute for Environmental and Climate Research Jinan UniversityGuangzhou 511443China School of Public Policy and Administration Northwestern Polytechnical UniversityXi’an 710061China State Key Laboratory of Loess and Quaternary Geology Institute of Earth EnvironmentChinese Academy of SciencesXi’an 710061China School of Environment and Planning Liaocheng UniversityLiaocheng 252000China Institute of Eco-Chongming Chenjia ZhenChongmingShanghai 202162China

To investigate the impact of emission controls on ammonia(NH_(3)) pollution in urban atmosphere, observation on NH_(3)(1 hr interval) was performed in Shanghai before, during and after the 2019 China International Import Expo (CIIE) event, along with measurements on inorganic ions, organic tracers and stable nitrogen isotope compositions of ammonium in PM_(2.5). NH_(3)during the CIIE period was 6.5±1.0μg/m^(3), which is 41% and 32% lower than that before and after the event, respectively. Such a decrease was largely ascribed to the emission controls in nonagricultural sources, of which contribution for measured NH_(3)in control phase abated by ~20% compared to that during uncontrol period. Molecular compositions of PAHs and hopanes further suggested a dominant role of the reduced vehicle emissions in the urban NH_(3)abatement during the CIIE period. Our results revealed that vehicle exhaust emission control is an effective way to mitigate NH_(3)pollution and improve air quality in Chinese urban areas.

关键词： Ammonia Non-agricultural sources vehicle emission stable nitrogen isotope Organic tracers

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MODELING THE CONGESTION COST AND vehicle emission WITHIN MULTIMODAL TRAFFIC NETWORK UNDER THE CONDITION OF EQUILIBRIUM

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Journal of Systems Science and Systems Engineering 2012年第4期21卷 385-402页

作者： Bingfeng SI Ming ZHONG Xiaobao YANG Ziyou GAO MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology Beijing Jiaotong University Department of Civil Engineering University of New BrunswickFrederictonN.B.Canada

Traditional system optimization models for traffic network focus on the treatment of congestion, which usually have an objective of minimizing the total travel time. However, the negative externality of congestion, such as environment pollution, is neglected in most cases. Such models fall short in taking Greenhouse Gas （GHG） emissions and its impact on climate change into consideration. In this paper, a social-cost based system optimization （SO） model is proposed for the multimodal traffic network considering both traffic congestion and corresponding vehicle emission. Firstly, a variation inequality model is developed to formulate the equilibrium problem for such network based on the analysis of travelers＇ combined choices. Secondly, the computational models of traffic congestion and vehicle emission of whole multimodal network are proposed based on the equilibrium link-flows and the corresponding travel times. A bi-level programming model, in which the social-cost based SO model is treated as the upper-level problem and the combined equilibrium model is processed as the lower-level problem, is then presented with its solution algorithm. Finally, the proposed models are illustrated through a simple numerical example. The study results confirm and support the idea of giving the priority to the development of urban public transport, which is an effective way to achieve a sustainable urban transportation.

关键词： Multimodal network vehicle emission system optimization bi-level programming

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Artificial neural network model for identifying taxi gross emitter from remote sensing data of vehicle emission

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Journal of Environmental Sciences 2007年第4期19卷 427-431页

作者： ZENG Jun GUO Hua-fang HU Yue-ming College of Automation Science and Engineering South China University of Technology Guangzhou 510640 China. Automation Engineering Research and Manufacture Center Guangdong Academy of Sciences Guangzhou 510070 China

vehicle emission has been the major source of air pollution in urban areas in the past two decades. This article proposes an artificial neural network model for identifying the taxi gross emitters based on the remote sensing data. After carrying out the field test in Guangzhou and analyzing various factors from the emission data, the artificial neural network modeling was proved to be an advisable method of identifying the gross emitters. On the basis of the principal component analysis and the selection of algorithm and architecture, the Back-Propagation neural network model with 8-17-1 architecture was established as the optimal approach for this purpose. It gave a percentage of hits of 93%. Our previous research result and the result from aggression analysis were compared, and they provided respectively the percentage of hits of 81.63% and 75%. This comparison demonstrates the potentiality and validity of the proposed method in the identification of taxi gross emitters.

关键词： vehicle emission remote sensing neural network principal component analysis regression analysis

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Projection pursuit model of vehicle emission on air pollution at intersections based on the improved bat algorithm

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Journal of Southeast University(English Edition) 2019年第3期35卷 389-392页

作者： Hu Qizhou Deng Wei Tan Minjia Bian Lishuang School of Automation Nanjing University of Science and TechnologyNanjing 210094China School of Transportation Southeast UniversityNanjing 210096China

The projection pursuit model is used to study the assessment of air pollution caused by vehicle emissions at intersections. Based on the analysis of the characteristics and regularities of vehicle emissions at intersections, a vehicle emission model based on projection pursuit is established, and the bat algorithm is used to solve the optimization function. The research results show that the projection pursuit model can not only measure the air pollution of vehicle emissions at intersections, but also effectively evaluate the level of vehicle exhaust emissions at intersections. Taking the air pollution caused by vehicle emissions at intersections as the research object and considering the influence factors of vehicle emissions on air pollution comprehensively, the evaluation index system of vehicle emissions at intersections on air pollution is constructed. Based on large data analysis, a prediction model of air pollution caused by vehicle emissions at intersections is constructed, and an improved bat algorithm is used to realize the assessment process. The application results show that the prediction model of vehicle emissions at intersections can define the degree of air pollution caused by vehicle emissions, and it has good guiding significance and practical value for solving the problem of air pollution caused by vehicle emissions.

关键词： intersection vehicle emission pollutants projection pursuit bat algorithm

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A remote sensing system of vehicle emissions based on tunable diode laser technology

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Journal of Environmental Sciences 2006年第1期18卷 154-157页

作者： ZENG Jun GUO Hua-fang HU Yue-ming College of Automation Science and Engineering South China University of Technology Guangzhou 510640 China

As being an effective real-time method of monitoring vehicle emissions on-road, a remote sensing system based on the tunable diode laser （TDL） technology was presented, and the key technologies were discussed. A field test in Guangzhou（Guangdong, China） was performed and was found that the factors, such as slope, instantaneous speed and acceleration, had significant influence on the detectable rate of the system. Based on the results, the proposal choice of testing site was presented.

关键词： remote sensing tunable diode laser vehicle emission detectable rate

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Characterization of on-road CO, HC and NO emissions for petrol vehicle fleet in China city

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2006年第7期7卷 532-541页

作者： GUO Hui ZHANG Qing-yu SHI Yao WANG Da-hui DING Shu-ying YAN Sha-sha Institute of Environmental Engineering Zhejiang University Hangzhou 310027 China Institute of Environmental Pollution Control Technology Zhejiang University Hangzhou 310028 China

vehicle emissions are a major source of air pollution in urban areas. The impact on urban air quality could be reduced if the trends of vehicle emissions are well understood. In the present study, the real-world emissions of vehicles were measured using a remote sensing system at five sites in Hangzhou, China from February 2004 to August 2005. More than 48000 valid gasoline powered vehicle emissions of carbon monoxide （CO）, hydrocarbons （HC） and nitrogen oxide （NO） were measured. The results show that petrol vehicle fleet in Hangzhou has considerably high CO emissions, with the average emission concentration of 2.71 %±0.02%, while HC and NO emissions are relatively lower, with the average emission concentration of （153.72±1.16）×10-6 and （233.53±1.80）×10-6, respectively. Quintile analysis of both average emission concentration and total amount emissions by model year suggests that in-use emission differences between well maintained and badly maintained vehicles are larger than the age-dependent deterioration of emissions. In addition, relatively new high polluting vehicles are the greatest contributors to fleet emissions with, for example, 46.55% of carbon monoxide fleet emissions being produced by the top quintile high emitting vehicles from model years 2000-2004. Therefore, fleet emissions could be significantly reduced if new highly polluting vehicles were subject to effective emissions testing followed by appropriate remedial action.

关键词： Remote sensing vehicle emission Characterization

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Potential emission reductions by converting agricultural residue biomass to synthetic fuels for vehicles and domestic cooking in China

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Particuology 2020年第2期18卷 40-47页

作者： Xiaoliang Wang SKent Hoekman Yang Han Judith CChow John G.Watson Xiaomeng Wu Ye Wu Dennis Schuetzle Robert Schuetzle Desert Research Institute 2215 Raggio PkwyRenoNV 89512USA School of Environment Tsinghua UniversityBeijing 100084China Greyrock Energy Inc.2020 L StreetSuite 120SacramentoCA 95811USA

vehicle exhaust and transported biomass burning emissions are important air pollution sources in many urban areas,and domestic cooking with biomass fuels causes indoor air pollution in many rural *** agricultural waste-generated synthetic fuels can reduce emissions both from vehicles and biomass *** estimate the potential benefits of synthetic diesel in Beijing,the emission factor model for the Beijing vehicle fleet was applied to estimate exhaust emissions for the 2015-2030 *** with 100%petroleum diesel,a 20%synthetic diesel blend reduced diesel fleet emissions by 24%for carbon monoxide,30%for total hydrocarbons,5.5%for nitrogen oxides,and 19%for fine particulate matter with an aerodynamic diameter of≤2.5μm(PM2.5)while using 100%synthetic diesel decreased emissions by 36%for carbon monoxide,48%for total hydrocarbons,10%for nitrogen oxides,and 34%for *** use of biomass for producing synthetic fuels rather than burning in the field also reduces air *** 60g of PM2.5 agricultural open-field burning emissions are avoided per liter of synthetic fuel *** solid crop residues with synthetic liquid fuels in household cooking would reduce PM2.5 emissions by more than 90%.

关键词： PM2.5 Air pollution vehicle emission Biomass burning Synthetic fuel Agricultural biomass

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Characteristics of the pollutant emissions in a tunnel of Shanghai on a weekday

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Journal of Environmental Sciences 2018年第9期30卷 136-149页

作者： Rui Li Ya Meng Hongbo Fu Liwu Zhang Xingnan Ye Jianmin Chen Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention Department of Environmental Science&EngineeringInstitute of Atmospheric SciencesFudan UniversityShanghai200433P.R.China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092P.R.China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and TechnologyNanjing 210044China

Tunnel displays a typical semi-closed environment, and multitudes of the pollutants tend to accumulate. The samples of gaseous pollutants and particulate matter （PM） were collected from the Xiangyin tunnel at Shanghai to investigate the characteristics of the pollutant emissions. The results indicated that both gaseous pollutants and PM exhibited much higher concentrations during the rush hours in the morning and at night due to vehicle emission. Two peaks of the PM concentration were observed in the scope of 0.7-1.1 and 3.3-4.7 μm, accounting for 14.6% and 20.3% of the total concentrations, respectively. Organic matter （OM）, EC, and many water-soluble ions were markedly higher at the rush hours in the morning than those at night, implicating comprehensive effects of vehicle types and traffic volume. The particle number concentrations exhibited two peaks at Aitken mode （25 nm and 100 rim） and accumulation mode （600 nm）, while the particle volume concentration displayed high values at the accumulation mode （100-500 nm） and coarse mode （2.5-4.0 μm）. The peak around 100 nm was detected in the morning rush hours, but it diminished with the decrease of the traffic volume. Individual-particle analysis revealed that main particles in the tunnel were Fe-rich particles, K-rich particles, mineral particles, Ca-S rich particles and A1-Si particles. The particles collected at the rush hours displayed marked different morphologies, element concentrations and particle sizes compared to the ones collected at the non-rush period. The data presented herein could shed a light on the feature of vehicle emissions.

关键词： Tunnel vehicle emission Size distribution Morphology

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