浅论机动车尾气检测站系统构建之技术要求

随着机动车保有量的日益增长,全社会对机动车的尾气污染越来越关注,机动车尾气污染物检测也因此引起相关政府机关的重视。近年来,随着国家环保总局颁布了多项针对关于机动车尾气检测机构和系统的相关标准,各地区建设尾气检测站来治理当地机动车尾气污染的工作已提上议事日程。文章对机动车尾气检测站计算机控制系统存在的问题和错误认识逐一加以阐述和澄清,并提出注意事项和解决措施。     

广州市机动车尾气污染现状及控制措施

随着人口和经济的快速发展,广州市机动车数量急剧上升。本文通过对广州市机动车的保有量、构成和发展趋势进行调研分析,并对机动车尾气排放的特性和现状进行研究,根据广州市空气污染现状机动车的污染物排放因子和各类车型排放分担率进行研究分析。文章结合广州市的地方特点提出控制广州市机动车尾气污染的可行措施。     

基于MOVES模型的石家庄市机动车排放清单研究

机动车尾气污染给石家庄市空气污染带来的影响不容忽视,为有效缓解和控制石家庄市的交通污染现状,需要对交通污染物进行精确量化。文章结合实地调研数据,对MOVES模型的主要输入参数进行了本地化,结合行驶里程和保有量数据计算出了石家庄市机动车排放清单,并分析了机动车的排放分担率。     

高速公路路面径流及路侧水质污染研究

文章针对目前岩溶地区高速公路运营期路面径流及路侧水质的污染情况,以衡枣高速公路为实例进行研究,表明SS是公路路面径流的主要污染物,公路两侧水质污染离子浓度随着与公路距离的增加而呈降低趋势,并提出了相应的防治措施。     

高速公路两侧土壤中石油类物质污染的调查与分析

针对目前我国高速公路两侧土壤中出现的石油类物质污染情况,对土壤样进行分析研究,得出高速公路两侧土壤中石油类污染物含量发生变化的规律及原因,提出有效的整治措施。     

停车换乘策略环境效益的实例研究

停车换乘是解决城市交通污染问题的一种有效策略,其环境效益主要体现在机动车污染物减排和社会经济效益两方面。本文实地采集停车换乘设施现状数据并结合排放因子,估算了上海淞虹路站停车换乘设施一年HC、CO、NOx三种主要机动车污染物减排量以及由此带来的经济效益。     

停车换乘策略环境效益的实例研究

停车换乘是解决城市交通污染问题的一种有效策略,其环境效益主要体现在机动车污染物减排和社会经济效益两方面。本文实地采集停车换乘设施现状数据并结合排放因子,估算了上海淞虹路站停车换乘设施一年HC、CO、NOx三种主要机动车污染物减排量以及由此带来的经济效益。     

反映车辆污染物排放水平的指标研究

机动车排放受车辆类型、车龄、燃料类型、油品质量等多种因素的影响,这些因素也直接或间接反映车辆的污染物排放水平。本文系统梳理了反映单个车辆污染物排放水平的指标,并分为直接和间接指标两类,其中车辆的燃料类型、车辆大小、车龄、行驶里程、行驶速度以及车辆满足的环保排放标准等指标是间接指标,间接反映车辆的排放水平。车辆实时尾气排放检测结果是直接指标,能够直接反映车辆的污染物排放水平。反映车辆污染物排放水平的指标研究是车辆污染物排放研究的基础性研究,也是机动车污染减排的重要支撑。     

机动车尾气等离子体净化技术的现状与进展

本文针对机动车尾气中氮氧化物、一氧化碳、碳氢化合物等不同污染物成分,概括分析了各自等离子净化的机理,讨论了目前低温等离子体技术在机动车尾气净化应用中的研究现状,展望了光催化协同等离子体作用的一体式尾气净化技术的发展动向。     

基于实时交通流和环境污染物监测的环保道路评估方法

利用RFID检测器和车辆GPS等设备采集的多源数据,通过交通流信息融合计算得到交通流特征参数(路段流量、平均速度),由尾气排放模型计算路段各类机动车污染物排放,然后利用多尺度大气扩散模拟区域和道路空气污染物浓度,并在webgis系统上展示浓度分布。同时,以环境监测站数据作为区域固定源等其他污染源的污染模块,移动和固定源两大模块同时用于评估道路环保。评估指标选取实时交通流特性、环境污染物背景浓度值、道路基本信息、气象信息和其他因素五类。结果表明交通流和环境背景浓度是影响环保道路评估的重要指标。研究结果可为未来城市道路的合理规划及居民出行提供一定理论依据和工程参考价值。     

Spatial variation of roadside C2–C6 hydrocarbon concentrations during low wind speeds: Validation of CALINE4 and COPERT III modelling

The CALINE4 model is widely used to predict the effect of vehicle emissions on ambient concentrations close to roadways. It requires an evaluation of the rate at which different air pollutants are emitted by vehicles, taking into account things such as vehicle flow, velocity, type and age. For Europe the databases of the COmputer Program to calculate Emissions from Road Transport (COPERT) are combined with local vehicle details to obtain site-specific emission factors for dispersion modelling. The ability of CALINE4 to predict the spatial variation of hydrocarbon concentrations downwind of a motorway is assessed, as is the accuracy of COPERT III composite emission factors for several hydrocarbon compounds. The concentrations of seven traffic-associated compounds is found at three locations downwind and upwind of a motorway. Modelled and measured background-corrected downwind concentrations are compared on three bases: daily peak hour concentrations, mean concentrations, and a set of model evaluation parameters.     

Impact of Visible-Solar-Light-Driven photocatalytic pavement on air quality improvement

Photocatalytic pavement has attracted significant interest in the past decades by both the academia and industry for its ability of spontaneous cleaning of air pollutants, such as motor vehicle exhaust gas. Titanium dioxide (TiO₂) is used as the photocatalyst that is mixed into pavement materials or coated on the pavement to remove motor vehicle exhaust gases, e.g., carbon monoxide (CO), nitrogen oxides (NO_x), under the irradiation of the solar light. However, the pure TiO₂ additive only absorbs the light within the ultraviolet region due to its large bandgap. One approach to increase the ability of TiO₂ to the utilization of the full spectrum of the solar light is doping TiO₂. Therefore, this visible-solar-light-driven photocatalytic pavement embedded with doped-TiO₂ will exhibits a better cleaning efficiency of exhaust gas. This work conducted computational simulations of the cleaning efficiency on reducing exhaust gas NO₂ by photocatalytic pavement with doped-TiO₂, and its subsequent influence on the air quality in the surrounding environment. A three-dimensional model was developed for a section of pavement and its vicinal region. Effects of weather conditions, doped-TiO₂ coverages, road widths and traffic flow conditions on the removal of NO₂ and its influence to the adjacent environment were studied. Results indicate that visible-solar-light-driven photocatalytic pavement with doped-TiO₂ features a significantly higher removal efficiency of exhaust gas compared with the normal photocatalytic pavement. Moreover, the doped-TiO₂ embedded pavement is effective to remove NO₂ with different traffic densities and wind conditions, and consequently improve the air quality of the surrounding environment.     

The impacts of inter-vehicle spacing on in-vehicle air pollution concentrations in idling urban traffic conditions

The influence of inter-vehicle spacing on the in-vehicle air pollution exposure of car commuters in heavy traffic conditions was investigated, both experimentally and numerically. An experimental investigation was carried out into the effect, on in-vehicle air pollution exposure, of maintaining a distance of approximately 2 m to the preceding vehicle in congested idling traffic conditions compared to that of an identical vehicle maintaining a distance of approximately 1 m. In-vehicle VOC and PM_2.5 concentrations revealed that a 19–31% reduction in exposure at the larger inter-vehicle spacing. A computational fluid dynamics model was calibrated using the experimental data and used to prediction car exposure under different conditions by varying certain key parameters. Agreement between the experimental and predicted data of 82% was achieved. The results show a significant drop in pollutant concentrations occurred within the first 2 m of their emission from the preceding vehicles exhaust.     

Roadway determinants of bicyclist exposure to volatile organic compounds and carbon monoxide

Few studies have quantified relationships between bicyclist exposure to air pollution and roadway and traffic variables. As a result, transportation professionals are unable to easily estimate exposure differences among bicycle routes for network planning, design, and analysis. This paper estimates the effects of roadway and travel characteristics on bicyclist exposure concentrations, controlling for meteorology and background conditions. Concentrations of volatile organic compounds (VOC) and carbon monoxide (CO) are modeled using high-resolution data collected on-road. Results indicate that average daily traffic (ADT) provides a parsimonious way to characterize the impact of roadway characteristics on bicyclists’ exposure. VOC and CO exposure increase by approximately 2% per 1000 ADT, robust to different regression model specifications. Exposure on off-street facilities is higher than at a park, but lower than on-street riding – with the exception of a path through an industrial corridor with significantly higher exposure. VOC exposure is 20% higher near intersections. Traffic, roadway, and travel variables have more explanatory power in the VOC models than the CO model. The quantifications in this paper enable calculation of expected exposure differences among travel paths for planning and routing applications. The findings also have policy and design implications to reduce bicyclists’ exposure. Separation between bicyclists and motor vehicle traffic is a necessary but not sufficient condition to reduce exposure concentrations; off-street paths are not always low-exposure facilities.     

The influence of deposit control additives on exhaust CO and HC emissions from gasoline engines (case study: Tehran)

Air pollution is the most serious environmental problem in Tehran with exhaust emissions from spark-ignition engines accounting for a major part of problem. The formation and accumulation of deposits on the internal surfaces of engines could adversely affect the exhaust emission from vehicles. It is the perception that some of fuel additives can remove these deposits due to their detergency. The Iranian Department of Environment decarbonized more that 250,000 SI engine vehicles in Tehran with the goal of reducing exhaust CO and HC emissions from gasoline engine vehicles by engine deposit removal. Here, the influence of engine deposit removal by decarbonization on the exhaust CO and HC emissions from more than 500 gasoline engine vehicles is examined. It is found that the decarbonization process could reduce the exhaust CO and HC emissions, significantly. Emissions from Peykan and Pride vehicles decreased considerably after decarbonization.     

Vehicle inspection and maintenance,and air pollution in Mexico City

Information from the Mandatory Inspection and Maintenance (I/M) Program carried out in October 1996 and the first semester of 1998 provides a useful emission database for Mexico City. Carbon monoxide (CO) and hydrocarbon (HC) exhaust emission levels were measured for at least a million private and public transportation vehicles. Analysis of this database leads us to conclude that this information can be used to test anti-pollutant policies, and is useful as a performance quality index for vehicle manufacturers. Some of the results of this analysis include: the finding of a typical exhaust emission distribution curve for each vehicle manufacturer, with differences for each brand and model for the same manufacturer, the fact that not all new vehicles pass the I/M test; and public transportation vehicles in Mexico City have almost useless catalytic converters.     

Spin glass and the interactions of congestion and emissions: An exploratory step

This paper models traffic congestion formation on highways and roads by recognizing the centrality of dynamical systems and using concepts from complexity theory as imbedded in the spin glasses analogue. Further, it explores the concept of how an increase in air pollution caused by vehicle exhaust emission can be traced to traffic congestion, specifically to the acceleration/deceleration of vehicles on the roads. First, spin glass is introduced and then by applying the two-dimensional x − y Ising model and defining a Hamiltonian (based on Edwards-Anderson and Mattis models of spin glass systems) for a system of vehicles on the road, derivations are made of the specific friction of congestion and the bulk modulus of congestion using the Gibbs-Boltzmann statistic. Similarly using the interactions of vehicles with each other and the resulting accelerations and decelerations of vehicles as the basis for exhaust emissions, derivations are made of a specificity of exhaust emissions. These are analogues to the entropy models of thermodynamics. This series of derivations serves as an analytical model for detecting incidents of congestion and increase in air pollution due to exhaust emissions in transportation systems.     

Estimating near-road pollutant dispersion: A model inter-comparison

A model inter-comparison study to assess the abilities of steady-state Gaussian dispersion models to capture near-road pollutant dispersion has been carried out with four models (AERMOD, run with both the area-source and volume-source options to represent roadways, CALINE, versions 3 and 4, ADMS and RLINE). Two field tracer studies are used: the Idaho Falls tracer study and the Caltrans Highway 99 tracer study. Model performance measures are calculated using concentrations (observed and estimated) that are paired in time and space, since many of the health related questions involve outcomes associated with spatially and temporally distributed human activities. All four models showed an ability to estimate the majority of downwind concentrations within a factor of two of the observations. RLINE, AERMOD-V, and ADMS, also have the capability to predict concentrations upwind of the roadway that result from low-speed meandering of the plume. Generally, RLINE, ADMS, and AERMOD (both source types) had overall performance statistics that were broadly similar, while CALINE 3 and 4 both produced a larger degree of scatter in their concentration estimates. The models performed best for near-neutral conditions in both tracer studies, but had mixed results under convective and stable conditions.     

Identifying contributions of on-road motor vehicles to urban air pollution using travel demand model data

Ambient concentrations of pollutants are correlated with emissions, but the contribution to ambient air quality of on-road mobile sources is not necessarily equal to their contribution to regional emissions. This is true for several reasons such as the distribution of other pollution sources and regional topology, as well as meteorology. In this paper, using a dataset from a travel demand model for the Sacramento metropolitan area for 2005, regional vehicle emissions are disaggregated into hourly, gridded emission inventories, and transportation-related concentrations are estimated using an atmospheric dispersion model. Contributions of on-road motor vehicles to urban air pollution are then identified at a regional scale. The contributions to ambient concentrations are slightly higher than emission fractions that transportation accounts for in the region, reflecting that relative to other major pollution sources, mobile sources tend to have a close proximity to air quality monitors in urban areas. The contribution results indicate that the impact of mobile sources on PM₁₀ is not negligible, and mobile sources have a significant influence on both NO_x and VOC pollution that subsequently results in secondary particulate matter and ozone formation.     

Reducing emissions at land border crossings through queue reduction and expedited security processing

Vehicle border crossings between Mexico and the United States generate significant amounts of air pollution, which can pose health threats to personnel at the ports of entry (POEs) as well as drivers, pedestrians, and local inhabitants. Although these health risks could be substantial, there is little previous work quantifying detailed emission profiles at POEs. Using the Mariposa POE in Nogales, Arizona as a case study, light-duty and heavy-duty vehicle emissions were analyzed with the objective of identifying effective emission reduction strategies such as inspection streamlining, physical infrastructure improvements, and fuel switching. Historical traffic information as well as field data were used to establish a simulation model of vehicle movement in VISSIM. Four simulation scenarios with varied congestion levels were considered to represent real-world seasonal changes in traffic volume. Four additional simulations captured varying levels of expedited processing procedures. The VISSIM output was analyzed using the EPA’s MOVES emission simulation software for conventional air pollutants. For the highest congestion scenario, which includes a 200% increase in vehicle volume, total emissions increase by around 460% for PM_2.5 and NO_x, and 540% for CO, SO₂, GHGs, and NMHC over uncongested conditions for a two-hour period. Expedited processing and queue reduction can reduce emissions in this highest congestion scenario by as much as 16% for PM_2.5, 18% for NO_x, 20% for NMHC, 7% for SO₂ and 15% for GHGs and CO. Other potential mitigation strategies examined include fleet upgrades, fuel switching, and fuel upgrades. Adoption of some or all of these changes would not only reduce emissions at the Mariposa POE, but would have air-quality benefits for nearby populations in both the US and Mexico. Fleet-level changes could have far-reaching improvements in air quality on both sides of the border.