南京市机动车排气污染控制和管理对策

简述了南京市机动车排气污染控制和管理对策。对新机动车排气控制实施了新车上牌的环保注册登记目录制,鼓励生产厂家采用先进的排放控制技术,达到国家制定的排放控制目标和排放标准;对在用机动车排气控制实施检测／维护(I／M)制度,对尾气排放不达标车辆进行正常的维修和保养,保证其发动机处于正常技术状况;对高排放污染机动车辆,安装尾气净化装置,以改善机动车排放水平。定期检测中各类型车辆维护前后排气污染物削减结果表明,85％的高排放污染车辆能达标,且CO的削减率最高,达50％左右;定期检测中各类型车辆安装机内净化器前后排气污染物削减结果表明,二次补气机内净化器对CO的净化率为22．5％～30．0％,对HC的净化率为9．7％～30．0％;高能电子点火机内净化器对CO的净化率为5．4％～22．2％,对HC的净化率为17．2％～30．8％。不定期检测中,一些高排放污染车辆安装三元催化反应器后,其净化率可达80％～90％。     

遥测法用于道路车辆尾气排放状况分析——以乌鲁木齐市北京中路主干线道路为例

利用尾气遥感检测仪采集的2021年数据,分析乌鲁木齐市典型主干线道路有效车型的车辆数、尾气排放变化和累积贡献率等,摸清道路车辆尾气排放的污染物现状,同时也为机动车遥感检测标准限值的修订和老旧车辆的科学管理提供技术支撑。     

非分散红外法应用于在用柴油车NOx排放检测的研究

柴油车排放的NO_x量大且占比高,污染状况不容忽视。针对目前柴油车排放环保定期检验中缺少NO_x检测方法和标准的情况,采用非分散红外法对210辆柴油车NO_x排放进行实测。结果显示,加载减速检测工况中80%VelMaxHP工况点可用于柴油车NO_x排放检测,有利于识别高排放车辆。该方法的推广应用,将为今后柴油车后处理装置的效果监管和车辆NO_x实际排放的日常检测提供重要技术支撑。     

道路机动车活动水平调查及其污染物排放测算应用——上海案例研究

采用上海市车辆数据和机动车年检站实地调查方式获取车辆技术及分布,用GPS设备采集机动车行驶工况,通过交通流量录像的现场计数的方法获得道路车流分布。调查结果显示,在用汽车排放水平85％以上都达到或超过国Ⅱ标准;在低速、怠速工况区间内,社会车辆的比功率比例最低;道路轻型客车（含出租车）日平均车流量占总车流量的80％以上。机动车活动水平的详细调查将有助于上海实际道路机动车排放清单的精确计算,并获取主要的排放源及其影响因素。     

基于车载远程监控的重型柴油车NOx排放评估方法研究

对某重型车的实际道路行驶过程中远程排放监控的NOx数据和PEMS设备测试数据对比分析。结果表明,两者的一致性较好,远程监控的NOx数据用于表征车辆实际道路的NOx排放特征具备可信性和可行性。基于远程排放监控数据,使用短行程重构PEMS法,建立车辆工况曲线重构方法和基于功基窗口法的排放评估模型,对车辆在实际道路上的排放进行评估计算,并与PEMS测试结果对比验证。研究结果表明,该短行程重构模型能有效识别车辆排放变化和超标情况,可以作为国六标准在用重型车NOx排放监控的新方法和手段。     

新车免检新政实施后对高污染车的管理思路与对策的探讨

2014年9月1日起,国家试行6年以内的非营运轿车等车辆免检制度。大多数城市根据此规定,对于车辆的排放定期检验也同步实施6年免检。随着汽车保有量的快速增长,车辆尾气排放对大气环境的影响不容忽视。因此,地方环保部门应针对机动车污染排放的管理重点,从管理手段、管理体制机制、管理对策等方面进一步加强对高污染车辆的监管。     

汽车排放检测新技术研究

介绍了机动车排放检测新技术简易工况法的检测原理、检测方法、检测设备及其技术特点,通过进行怠速法、双怠速法、简易工况法的实车对比测试,证明了简易工况法比现行国家标准怠速法的技术更先进和有效,它能模拟实际路况反映汽车尾气排放的污染程度,能区分在用车中的高排放车、超标率和达标车,根据检测数据辅助不合格车辆进行有效的治理。以减低机动车污染物的排放,增强机动车的性能,配合I/M制度的实施。     

欧盟拟立法监测卡车二氧化碳排放

正人民日报消息欧洲理事会和欧洲议会近日就针对重型车辆的二氧化碳排放以及燃油消耗数据实施监控的法规草案初步达成一致。提出该草案的欧盟委员会表示,这将是欧盟首次对监测重型车辆二氧化碳排放进行立法。根据草案内容,"重型车辆"包括卡车、公共汽车以及客车等。欧盟所有成员国都必须对重型车辆的注册情况进行监测     

在用车污染物排放状况分析

为了有效地控制汽车尾气污染物的排放,我们依据90年汽车尾气的监测结果,分析了我国在用车辆污染物排放的变化,对国产车和进口车污染物排放状况进行了对比,并讨论了各     

江苏省机动车“天地车人”一体化监控系统建设研究

构建江苏省“天地车人”一体化监控系统,利用道路遥感监测、定期排放检验、路检路查和停放地监督抽测、重型柴油车远程排放监控等手段发现高排放车辆,通过系统检测与维护(I/M)制度,对机动车进行全天候、全方位实时监控及闭环管理,同时开展非道路移动机械的登记和管理,并对5000 t以上的加油站进行油气回收在线监控。通过大数据分析开展机动车排放数据的深入挖掘,以期为重污染天气的应急管理及政府决策提供有效技术支撑。     

不同类型机动车尾气挥发性有机化合物排放特征研究

机动车尾气主要成分包括一氧化碳、氮氧化物、碳氢化合物、铅及苯并[a]芘等.其中,挥发性有机化合物由于其对光化学烟雾的贡献及对人体健康的影响而成为近年来大气化学研究的热点.文章首次对北京市9种车辆、5种燃料在不同工况下排放挥发性有机化合物特征进行了定量研究.结果表明,车型、燃料、净化器及工况等因素对排放量产生影响,电喷车比化油器车排放低,其中,夏利比富康与奥迪排放量高;LPG与汽油车排放量最高,柴油车与CNG车排放最低.其中,-10#柴油车比0#柴油车排放更低;使用净化器可以降低挥发性有机化合物排放量;不同工况对排放量的影响随车型、燃料类型的不同而不同.因此,使用清洁燃料、安装净化器和使用电喷装置,可减少尾气中挥发性有机化合物含量.     

机动车尾气排放检测方法对比分析

通过怠速、双怠速法对机动车尾气检测试验和数据对比分析表明,不同车龄段的电喷型轿车采用怠速法检测尾气达标率在73.3%～93.5%之间;双怠速法检测尾气达标率在40.0%～82.6%之间.不同车龄段的化油器型轿车采用怠速法检测尾气达标率在25.0%～57.1%之间;双怠速法检测尾气达标率在18.8%～57.1%之间.指出双怠速法对化油器车辆尾气控制同样有效果,双怠速法对筛选高污染车辆比怠速法更严格和科学.     

上海市机动车污染实时排放预警系统设计与应用

研究上海市机动车污染的动态排放测算和网格化动态排放清单构建,在实时的交通数据和交通环境监测数据的基础上,结合交通模型、机动车排放清单模型等业务模型和算法,依托大数据存储、可视化和GIS等技术,开发了上海市机动车污染物实时排放预警系统,实现了上海市全市道路的机动车动态排放测算、交通环境政策实施情景模拟和网格化排放清单,更新频率为每30 min一次,包含PM、NO_x、CO、SO₂、VOCs等污染物和9种车型。系统建成后直接服务于首届中国国际进口博览会,为大气污染排放实时总量跟踪评估、污染源管控措施分析及监测成因分析等提供了有力的实时数据和技术支撑。     

典型街道环境空气质量分析

根据对深南东路环境空气的监测及车流量、气象条件的调查,分析机动车及气象因素对深圳市环境空气质量的影响。根据分析可知,机动车尾气是深圳市环境空气中污染物的主要来源,但污染程度不断变化的主要原因是风速,深圳市环境空气中污染物浓度与风速有着非常显著的负相关。     

2020年江苏省机动车排放污染分布特征及与大气质量耦合性研究

依据生态环境部2021年6月发布的《排放源统计调查产排污核算方法和系数手册》,结合本地实测数据,在对汽油车颗粒物(PM)排放系数进行测算的基础上,核算了2020年江苏省机动车PM、氮氧化物(NO_(X))、挥发性有机物(VOC_(S))的排放总量,分析了机动车排放污染分布特征及与大气质量的耦合关系。结果表明:2020年江苏省机动车PM、NO_(X)、VOC_(S)排放量分别为0.5×10^(4),3.71×10^(5),1.17×10^(5) t。从区域分布来看,苏州、南京、无锡3市的3项污染物排放总量及NO_(X)、VOC_(S)排放量均位列前3位,PM排放量位列前3位的是苏州、徐州、无锡。从车型、燃料类型和排放阶段来看,国Ⅳ及以下排放标准的汽油小型客车是机动车VOC_(S)排放控制的重点,国Ⅲ排放标准的重型柴油货车是机动车PM和NO_(X)排放控制的重点。分析区域机动车PM排放量与大气中PM_(2.5)来源解析结果的耦合关系,其间存在不同程度的正相关性,控制机动车污染对改善大气环境会产生积极成效,南京、徐州和盐城3市的成效会尤为明显。     

城市汽车尾气污染治理模式探讨

借鉴国内外 I/ M制度的经验 ,运用系统论、控制论的观点 ,创造性地提出有效治理城市汽车尾气污染应建立的六大体系 ,强调城市汽车尾气污染的控制应以尾气污染预前控制和过程控制为主 ,并以此构筑城市汽车尾气污染治理的新模式     

An evaluation of improvements in the air quality of Beijing arising from the use of new vehicle emission standards

An innovative approach of mean emission by vehicle type was used in this paper to assess the impact of new vehicle emission standards in Beijing, China during the period of 2000–2005. It was found that CO and NO_x emissions decreased by 48% and 23%, respectively, from Type O (before 2000) to Type I (year 2000) vehicles. The reductions from Type O to Type II (year 2002) vehicles were 85% and 73% for CO and NO_x, respectively. When all three types of vehicles (Types O, I and II) are combined, the annual per vehicle CO emissions decreased from 586 kg per vehicle per year in 2000 to 324 kg per vehicle per year in 2005, while that of NO_x decreased from 66.9 to 43.4 kg per vehicle per year, which was mainly resulted from the impact of stringent new vehicle emission standards implemented in years 2000 and 2002. However, the vehicle population increased by 70% during the same time period, which offset the impact of cleaner vehicles. Thus, the total vehicle emission decreased little for CO (885,000 tons in 2000, 837,000 tons in 2005) and even increased slightly for NO_x (101,000 and 112,000 tons in 2000 and 2005, respectively). The ambient concentrations of CO decreased significantly throughout 2000–2005, the same trend was not observed for NO₂. Correlation analysis (grey correlation and Pearson correlation) between the annual vehicle emissions and annual concentrations of CO, the annual NO_x emission and annual NO₂ concentration indicated that the implementation of new vehicle emission standards was associated with the abatement of ambient CO and NO₂ concentrations in Beijing.     

Characteristics and sources of atmospheric polycyclic aromatic hydrocarbons (PAHs) in Shanghai, China

A field campaign was conducted to measure and analyze 13 polycyclic aromatic hydrocarbons (PAHs) in six major zones in the city of Shanghai, P.R. China from August 2006 to April 2007. Ambient air samples were collected seasonally using passive air samplers, and gas chromatography–mass spectroscopy was used in this field campaign. The results showed that there was a sequence of 13 PAHs at Phen > FA > Pyr > Chr > Fl > An > BaA > BbFA > BghiP > IcdP > BkFA > BaP > DahA and the sum of these PAHs is 36.01 ± 10.85 ng/m³ in gas phase. FL, Phen, FA, Pyr, and Chr were the dominant PAHs in gas phase in the city. They contributed 90% of total PAHs in the gas phase. Proportion of measured PAHs with three, four, five, and six rings to total PAHs was 53%, 42%, 3%, and 2%, respectively. The highest concentration of ΣPAHs (the sum of 13 PAHs) occurred in the wintertime and the lowest was in the summer. This investigation suggested that traffic, wood combustion, and metal scrap burn emissions were dominant sources of the concentrations of PAHs in six city zones compared with coal burning and industry emissions. Further, the traffic emission sources of PAHs in the city were attributed mostly to gasoline-powered vehicles compared with diesel-powered vehicles. It was revealed that the seasonal changes in PAHs in the city depended on different source types. Metal scrap burn was found to be the major source of PAHs during the autumn, while the PAH levels in the atmosphere for winter and spring seasons were mainly influenced by wood and biomass combustion. Comparisons of PAHs among different city zones and with several other cities worldwide were also made and discussed.     

Application and Quality Assessment of an Instantaneous Vehicle Emission Model at Fleet Level

A developed instantaneous emission model is applied to predict emission factors for small vehicle fleets for quality assessment. Extensive vehicle measurements of pre-Euro-1 gasoline, Euro-3 gasoline, and Euro-2 diesel vehicles are available. The data were used to develop individual vehicle emission models for each car. The prediction quality for each vehicle category was determined by averaging the results obtained from the individual vehicle models. The results show that the prediction quality is improved in comparison with the individual vehicles, even with a small number of vehicles in a specific category. This indicates that the errors in the individual models are mainly random and that prediction quality, when applied to fleets of cars, is exceptionally high.     

Transport spatial model for the definition of green routes for city logistics centers

This paper presents a transport spatial decision support model (TSDSM) for carrying out the optimization of green routes for city logistics centers. The TSDSM model is based on the integration of the multi-criteria method of Weighted Linear Combination (WLC) and the modified Dijkstra algorithm within a geographic information system (GIS). The GIS is used for processing spatial data. The proposed model makes it possible to plan routes for green vehicles and maximize the positive effects on the environment, which can be seen in the reduction of harmful gas emissions and an increase in the air quality in highly populated areas. The scheduling of delivery vehicles is given as a problem of optimization in terms of the parameters of: the environment, health, use of space and logistics operating costs. Each of these input parameters was thoroughly examined and broken down in the GIS into criteria which further describe them. The model presented here takes into account the fact that logistics operators have a limited number of environmentally friendly (green) vehicles available. The TSDSM was tested on a network of roads with 127 links for the delivery of goods from the city logistics center to the user. The model supports any number of available environmentally friendly or environmentally unfriendly vehicles consistent with the size of the network and the transportation requirements.