New research assessing the effect of engine operating conditions on regulated emissions of a 4-stroke motorcycle by test bench measurements

In the latest years the effect of powered two-wheelers on air polluting emissions is generally noteworthy all over the world, notwithstanding advances in internal combustion engines allowed to reduce considerably both fuel consumption and exhaust emissions of SI engines. Nowadays, in fact, these vehicles represent common means of quotidian moving, serving to meet daily urban transport necessities with a significant environmental impact on air quality. Besides, the emissive behavior of the two-wheelers measured under fixed legislative driving standards (and not on the local driving conditions) might not be sufficiently representative of real world motorcycle riding.The purpose of this investigation is a deeper research on emissive levels of in-use motorcycles equipped with last generation SI engines under real world driving behavior. In order to analyze the effect of vehicle instantaneous speed and acceleration on emissive behavior, instantaneous emissions of CO, HC and NO_X were measured in the exhaust of a four-stroke motorcycle, equipped with a three-way catalyst and belonging to the Euro-3 legislative category. Experimental tests were executed on a chassis dynamometer bench in the laboratories of the National Research Council (Italy), during the Type Approval test cycle, at constant speed and under real-world driving cycles. This analytical-experimental investigation was executed with a methodology that improves vehicles emission assessment in comparison with the modeling approaches that are based on fixed legislative driving standards. The statistical processing results so obtained are very useful also in order to improve the database of emission models commonly used for estimating emissions from road transport sector, then they can be used to evaluate the environmental impact of last generation medium-size motorcycles under real driving behaviors.     

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。     

Integrated Traffic and Emission Simulation: a Model Calibration Approach Using Aggregate Information

Environmental impacts of road traffic have attracted increasing attention in project-level traffic planning and management. The conventional approach considers emission impact analysis as a separate process in addition to traffic modeling. This paper first introduces our research effort to integrate traffic, emission, and dispersion processes into a common distributed computational framework, which makes it efficient to quantify and analyze correlations among dynamic traffic conditions, emission impacts, and air quality consequences. A model calibration approach is particularly proposed when on-road or in-lab instantaneous emission measurements are not directly available. Microscopic traffic simulation is applied to generate dynamic vehicle states at the second-by-second level. Using aggregate emission estimation as standard reference, a numerical optimization scheme on the basis of a stochastic gradient approximation algorithm is applied to find optimal parameters for the dynamic emission model. The calibrated model has been validated on several road networks with traffic states generated by the same simulation model. The results show that with proper formulation of the optimization objective function, the estimated dynamic emission model can capture the trends of aggregate emission patterns of traffic fleets and predict local emission and air quality at higher temporal and spatial resolutions.     

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.     

An Evaluation of Microscopic Emission Models for Traffic Pollution Simulation Using On-board Measurement

As a result of the continuously increasing numbers of motor vehicles in metropolitan areas worldwide, road traffic emission levels have been recognized as a challenge during the planning and management of transportation. Experiments were conducted to collect on-road emission data using portable emission measurement systems in two Chinese cities in order to estimate real traffic emissions and energy consumption levels and to build computational models for operational transport environment projects. In total, dynamic pollutant emissions and fuel consumption levels from dozens of light duty vehicles, primarily from four different vehicle classes, were measured at a second-by-second level. Using the collected data, several microscopic emission models including CMEM, VT-Micro, EMIT, and POLY were evaluated and compared through calibration and validation procedures. Non-linear optimization methods are applied for the calibration of the CMEM and EMIT models. Numerical results show that the models can realize performance levels close to the CMEM model in most cases. The VT-Micro model shows advantages in its unanimous performance and ability to describe low emission profiles while the EMIT model has a clear physics basis and a simple model structure. Both of them can be applied when extensive emission computation is required in estimating environmental impacts resulting from dynamic road traffic.     

Emission Factors Determination of Euro III 1,200- to 1,400-cc Petrol Passenger Cars with a PLS Multivariate Regression Model

This paper presents emission factors of a class of passenger cars obtained by applying a statistical model developed to evaluate average emission factors based on driving cycle emission measurements. A multivariate regression method based on principal components, namely, the partial least squares (PLS) method, is applied to calculate the model. The method was applied to emission data from a sample of petrol Euro III 1,200- to 1,400-cc passenger cars taken from the ARTEMIS database. A vehicle effect analysis showed that vehicle effect is considerable, in some cases comparable to or greater than the driving cycle effect. Determination of emission factors is obviously affected by these aspects. Thus, the CO2 PLS model fit results are good, CO, HC and NOX more or less sufficient. PLS-predicted quantities were compared with corresponding quantities estimated by a multiple regression model (GLM) based on a quadratic polynomial equation of sub-cycle overall mean speed. GLM goodness of fit was poorer than PLS ones. A validation effort of models is in progress, which is considering the ARTEMIS database extended with tests performed within other national or international projects. In this way, an extended population of combinations of vehicles and driving cycles will provide a better calculation of models and emission factors.     

Multipoint source method in air pollution modelling of cold start emission

The paper presents a new method of air pollution modelling on a micro scale. For estimation of concentration of car exhaust pollutants, each car is treated as an instantaneous moving emission source. This approach enables us to model time and spatial changes of emission, especially during cold and cool start of an engine. These stages of engine work are a source of significant pollution concentration in urban areas. In this work, two models are proposed: one for the estimation of emission after cold start of the engine and another for the prediction of pollutant concentration. The first model (defined for individual exhaust gas pollutants) enables us to calculate the emission as a function of time after the cold or cool start, ambient temperature and average speed of motion. This model uses the HBEFA database. The second mathematical model is developed in order to calculate the pollutant dispersion and concentrations. The finite volume method is applied to discretise the set of partial differential equations describing wind flow and pollutant dispersion in the domain considered. Models presented in this paper can be called short-term models on a small spatial scale. The results of numerical simulation of pollutant emission and dispersion are also presented.     

南京市机动车排气监测与评价

通过对南京市机动车排气污染物的年检监测,表明南京市的汽油车、柴油车、摩托车排气合格率总体呈上升趋势,2002年全市机动车排气监测总合格率为99.9%,比1993年上升了8.6个百分点;汽车尾气达标率也呈上升趋势,2002年达83.8%,比1993年上升了2.6个百分点。对机动车排气路检结果表明,CO超标的车辆占84.4%,CO、HC两项指标都超标的车辆占31.1%。对各类汽油助力车排气监测结果表明,二冲程汽油助力车尾气中CO、HC排放量要高于四冲程汽油助力车的排放量。对各类正三轮摩托车排气抽检结果表明,大部分四冲程正三轮摩托车尾气排放污染物能达标,且排气管无碳烟;二冲程正三轮摩托车尾气中HC值偏高,排气管碳烟明显。     

机动车排放细颗粒物精细化源谱构建及应用

利用真空瓶现场采样并结合单颗粒气溶胶质谱（SPAMS）技术,对主流品牌汽油车和柴油车排放细颗粒物进行组分分析和源谱构建。结果表明：汽、柴油车尾气源谱特征整体较为相似,相似度均值达到0.88,均以碳和钙为主要特征组分;部分柴油车特征源谱中硫酸盐特征较为明显,碳组分中OC特征突出;汽油车源谱特征中磷酸盐特征相对突出,且碳组分中短链元素碳占比较高。根据建立的源谱进行实际道路观测,结合风速、风向等气象要素分析,2021年2月1日—24日观测点位对应的移动源占比为33.5%,其中汽油车贡献21.0%,柴油车贡献12.5%。     

最优化集成方法在城市臭氧数值预报中的应用研究

基于多模式(NAQPMS、CMAQ、CAMx、WRF-Chem)空气质量数值预报业务系统的滚动预报结果,结合站点观测资料,评估了最优化集成方法在城市臭氧数值预报中的可行性和预报效果。一年的评估结果表明:当训练期为15 d时,最优化集成方法能够得到相对较好的结果。总体而言,最优化集成方法对城市臭氧浓度变化趋势和浓度水平的预报效果明显优于单个模式,且在大部分城市优于多模式的最优预报,其预报值和观测的相关系数提高0.11以上,均方根误差降低约10μg/m~3;该方法对城市臭氧污染等级的预报能力也明显优于单个模式,特别是轻、中度污染。此外,在模拟偏差较大的城市,最优化集成方法对预报效果的改进更为显著;在模拟偏差较小的城市,该方法仍可进一步提升预报效果。     

汽油车尾气遥感检测结果统计分析与限值制定

选取汽油车尾气中CO、HC、NO等3种气态污染物，以稳态工况法为基准，与车辆实际行驶时的遥感测试结果比对，从而制定相应的排放控制限值。建议遥感检测法对于CO、HC、NO的限值，2001年10月1日前注册登记的汽油车分别为3．0％、1000×10-6、3500×10-6，2001年10月1日起注册登记的汽油车分别为2．0％、500×10-6、2000×10-6。提出当机动车所有人对检测结果有异议时，可在规定期限内至指定机构按年检方法复检。     

机动车排放尾气中挥发性有机污染物对环境空气质量影响初探

采用气相色谱/质谱检测技术,对汽油和柴油、汽油车和柴油车排放气体以及天津市环境空气中主要挥发性有机污染物(VOCs)的组成种类及比例进行探析.结果表明,机动车排放的尾气中主要有机污染物为芳香烃类、烷烃类和烯烃类化合物,其中芳香烃类含量最高;汽油车排放的芳香烃类化合物浓度高于柴油车排放的浓度;机动车尾气对交通区域空气质量的影响高于工厂区(非化工区)、生活小区和公园.     

春季广州城区空气中VOCs来源解析

2013年4月在广州市区对大气中挥发性有机化合物(VOCs)进行了观测,对其变化特征和来源进行了分析。结果表明,观测期间测得的VOC总平均混合比为41.35×10~(-9),表现为烷烃芳香烃烯烃炔烃;利用PMF解析出观测时段内影响广州市区的9个VOCs主要来源,各源占比情况依次为:LPG排放老化VOC汽油挥发石化、未知源汽油车排放油漆溶剂柴油车排放天然源;与机动车相关和工业相关的来源分别占到了大气VOCs的46.8%和21.0%。     

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。     

Assessment of Mexico��s program to use ethanol as transportation fuel: impact of 6% ethanol-blended fuel on emissions of light-duty gasoline vehicles

Recently, the Mexican government launched a national program encouraging the blending of renewable fuels in engine fuel. To aid the assessment of the environmental consequences of this move, the effect of gasoline fuel additives, ethanol and methyl tert-butyl ether, on the tailpipe and the evaporative emissions of Mexico sold cars was investigated. Regulated exhaust and evaporative emissions, such as carbon monoxide, non-methane hydrocarbons, and nitrogen oxides, and 15 unregulated emissions were measured under various conditions on a set of 2005?C2008 model light-duty vehicles selected based on sales statistics for the Mexico City metropolitan area provided by car manufacturers. The selected car brands are also frequent in Canada, the USA, and other parts of the world. This paper provides details and results of the experiment that are essential for evaluation of changes in the emission inventory, originating in the low-blend ethanol addition in light vehicle fuel.     

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、NOx、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。     

An Integrated Approach to Street Canyon Pollution Modelling

An integrated method for the prediction of the spatial pollution distribution within a street canyon directly from a microscopic traffic simulation model is outlined. The traffic simulation package Paramics is used to model the flow of vehicles in realistic traffic conditions on a real road network. This produces details of the amount of pollutant produced by each vehicle at any given time. The authors calculate the dispersion of the pollutant using a particle tracking diffusion method which is superimposed on a known velocity and turbulence field. This paper shows how these individual components may be integrated to provide a practical street canyon pollution model. The resulting street canyon pollution model provides isoconcentrations of pollutant within the road topography.     

Vehicular particulate matter emissions in road tunnels in Sao Paulo, Brazil

In the metropolitan area of S?o Paulo, Brazil, ozone and particulate matter (PM) are the air pollutants that pose the greatest threat to air quality, since the PM and the ozone precursors (nitrogen oxides and volatile organic compounds) are the main source of air pollution from vehicular emissions. Vehicular emissions can be measured inside road tunnels, and those measurements can provide information about emission factors of in-use vehicles. Emission factors are used to estimate vehicular emissions and are described as the amount of species emitted per vehicle distance driven or per volume of fuel consumed. This study presents emission factor data for fine particles, coarse particles, inhalable particulate matter and black carbon, as well as size distribution data for inhalable particulate matter, as measured in March and May of 2004, respectively, in the Janio Quadros and Maria Maluf road tunnels, both located in S?o Paulo. The Janio Quadros tunnel carries mainly light-duty vehicles, whereas the Maria Maluf tunnel carries light-duty and heavy-duty vehicles. In the Janio Quadros tunnel, the estimated light-duty vehicle emission factors for the trace elements copper and bromine were 261 and 220 microg km(-1), respectively, and 16, 197, 127 and 92 mg km(-1), respectively, for black carbon, inhalable particulate matter, coarse particles and fine particles. The mean contribution of heavy-duty vehicles to the emissions of black carbon, inhalable particulate matter, coarse particles and fine particles was, respectively 29, 4, 6 and 6 times higher than that of light-duty vehicles. The inhalable particulate matter emission factor for heavy-duty vehicles was 1.2 times higher than that found during dynamometer testing. In general, the particle emissions in S?o Paulo tunnels are higher than those found in other cities of the world.     

Assessment of New Vehicles Emissions Certification Standards in the Metropolitan Area of Mexico City

Light duty gasoline vehicles account for most of CO hydrocarbons and NOx emissions at the Metropolitan Area of Mexico City (MAMC). In order to ameliorate air pollution from the beginning of 2001, Tier 1 emission standards became mandatory for all new model year sold in the country. Car manufacturers in Mexico do not guarantee the performance of their exhaust emissions systems for a given mileage. The purpose of this study was to assess whether the Tier 1 vehicles will stand the certification values for at least 162000 km with the regular fuel available at the MAMC. Mileage accumulation and deterioration show that certified carbon monoxide emissions will stand for the useful life of the vehicles but in the case of non-methane hydrocarbons will be shorter by 40%, and nitrogen oxides emissions above the standard will be reached at one third of the accumulated kilometers. The effect of gasoline sulfur content, on the current in use Tier 1 vehicles of the MAMC and the impact on the emissions inventory in year 2010 showed that 31000 extra tons of NOx could be added to the inventory caused by the failure of the vehicles to control this pollutant at the useful life of vehicles.     

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.