青岛市机动车污染物排放研究

青岛市机动车保有量快速增加,机动车污染物的大量排放对环境空气质量的影响日益突出.运用IVE模型计算了青岛市机动车污染物排放状况,并运用等标污染负荷法对不同机动车车型及其排放进行评估.研究表明:2014年青岛市机动车气态污染物排放量CO、VOCs、NOx、SO2分别为92.7、10.1、6.6、0.1万t/a,颗粒物PM10及PM2.5分别为0.09、0.08万t/a,小型载客汽车为主要的机动车污染物排放源,占机动车污染物排放总量的48%;大气污染物中CO、VOCs及NOx受机动车排放较为显著,贡献率分别为56.86%、48.86%和27.83%,SO2、PM10及PM2.5相对较小.在机动车保有量持续增长的情况下,发展绿色交通、提高燃油品质、开发清洁能源等措施可有效降低机动车污染物的排放.     

国际速递

欧洲批准欧Ⅴ欧Ⅵ标准2009年将开始实施欧洲议会12月13日通过了旨在限制汽车污染物排放的欧洲5号和欧洲6号标准。根据新标准,未来欧盟国家对本地生产及进口汽车的污染物排放量,特别是氮氧化物和颗粒物排放量的控制将日益严格。欧Ⅴ标准将于2009年9月1日开     

基于不同方法的省级机动车大气污染物排放清单研究——以江苏省为例

为了详细评估省级尺度机动车污染物排放特征,基于相同的车辆活动水平信息,分别采用COPERT模型和基于国内实测的排放因子数据建立了江苏省2012年机动车大气污染物排放清单。结果表明,由于排放因子的差异,基于国内实测的排放因子法估算氮氧化物(nitrogen oxides,NO_x)、一氧化碳(carbon monoxide,CO)、非甲烷挥发性有机物(non-methane volatile organic compounds,NMVOCs)、细颗粒物(particulate matter2.5,PM2.5)、黑碳(black carbon,BC)和有机碳(organic carbon,OC)排放量分别为COPERT模型结果的2.38、1.39、1.49、2.66、3.33和1.72倍。不同测试数据和模型结果的比较表明,COPERT模型可能对我国机动车CO、NO_x和NMVOC的排放因子有所低估,而不同测试的颗粒物排放因子结果不确定性较大。小型汽油客车对CO和NMVOC的排放贡献率分别为36%和23%;重型货车对NO_x、PM2.5和BC的贡献率都超过50%。基于COPERT模型计算结果和全省道路等级信息对机动车排放量进行空间分配,污染物排放主要集中在经济较为发达和路网较为密集的江苏南部地区;城际间高速路网对NO_x和颗粒物排放分布的影响较为明显。     

高海拔超长隧道通风烟雾、CO基准排放量折减率取值建议

为了避免高海拔超长隧道通风系统规模过大,建议对现行规范中汽车污染物基准排放量折减率取值进行修正。根据近年来我国汽车发动机排放标准的实施时间,提出用国Ⅳ以上车辆排放水平作为通风计算中2030年的汽车污染物排放基准值。选取多种国Ⅳ以上车型在海拔2 800 m的新疆地区进行排放量实测。结果表明:实际排放量与《细则》中2000年的计算排放量相比,国Ⅳ柴油车烟雾排放量减少了73%以上,国Ⅴ汽油车CO排放量减少了99%以上。建议将烟雾排放量的年折减率由2%提高至3.5%,将CO排放量的年折减率由2%提高至2.5%。     

谈太原市机动车污染及防治对策

利用太原市机动车排污量的统计数据、山西省和太原市成品油质量抽查及市区交通相关调查数据,依据机动车大气污染物排放清单编制指南等技术规范,分析了太原市机动车车型、油品硫含量、车速同污染物排放量之间的关系,提出了控制重型柴油车、加强油品质量管理和道路交通管理等方面的对策意见及推进机制,以尽快改善太原市的大气环境质量。     

2009—2013年宜春市大气污染特征及影响因素分析

目的了解宜春市当前空气质量状况,包括主要污染物及污染物的时间变化特征,预测宜春市空气质量未来的发展趋势,并探究其影响因素。方法利用空气综合污染指数和污染负荷系数法对宜春市2009—2013年大气日报数据进行处理和分析。结果 5年内,宜春市空气质量均在Ⅱ级以上,并以Ⅱ级为主,3种污染指标(PM10、NO2、SO2)里,PM10为主要污染指标,对综合污染指数贡献最大;各污染物污染负荷系数PM10>NO2>SO2;空气污染指数呈现季节性、年际变化趋势,如冬季高、夏季低,年际变化平缓,逐年呈不显著递增趋势。结论宜春市空气质量有逐渐变差的趋势,其主要影响因素为近几年迅速增加的机动车排放大量尾气、建筑业的迅猛发展等,有必要进行PM2.5站点的建设,以掌握宜春空气质量细颗粒物的动态变化。     

南昌红谷隧道通风及洞口污染物排放分析

通过对隧道需风量计算、通风网络模拟及现场风速测试,得到了隧道各匝道在不同车速条件下的通风量,分析了多匝道风量分配特性;采用隧道出口污染物扩散TOP模式,预测隧道出口不同风量条件下的污染物扩散情况,并实测了隧道出口污染物浓度,分析了洞口排风对敏感建筑附近环境的影响。研究表明,城市隧道通风计算中污染物CO基准排放量取值偏高,需风量计算值偏大。认为在相关标准编制及工程设计中应重视机动车尾气排放中NO_x的基准排放量和浓度控制值;对于多匝道隧道,可以通过诱导交通组织和调节分离匝道风量分配比例,降低距离敏感建筑物较近出口污染物浓度。     

水泥厂废气非正常排放的大气环境影响研究

众所周知,水泥厂对大气环境的污染主要是颗粒物、二氧化硫、氮氧化物,以氨水为还原剂的SNCR脱硝工艺,还存在氨的排放。2013年修订的《水泥工业大气污染物排放标准》新增了NH_3的控制指标,提高了颗粒物、NO_X排放控制要求。本文以某水泥厂为例,分析了废气非正常排放条件下,颗粒物、氮氧化物及氨的区域最大值的贡献值、占标率及对环境的影响,提出相应的治理措施。     

机动车尾气的检测技术与污染防治

随着我国经济的快速发展,机动车数量日益增多,其排放的尾气也不断增多,导致大气污染越来越严重,加剧环境问题。因此,为降低机动车尾气对环境污染的程度,需要做好机动车尾气的检测工作,较少机动车尾气的排放量,改善环境污染。本文主要是对机动车尾气的污染物及其危害,机动车排放有害气体的生成机理及机动车尾气的检测技术进行分析论述,希望能够更好地了解机动车尾气检测技术,从而更好地用于机动车尾气防治,减少环境污染。     

城市道路信控交叉口机动车排放分析

构建了基于VISSIM微观交通仿真与CMEM排放模型的城市交通污染物排放计算平台,计算了郑州市某干道交叉口机动车污染物排放情况,分析了信号控制方式对交叉口机动车污染物排放的影响,结果表明,采用感应信号控制可以减少交叉口区域内机动车污染物的排放。     

Assessing the co-benefits of greenhouse gas reduction: health benefits of particulate matter related inspection and maintenance programs in Bangkok, Thailand

Since the 1990s, the capital city of Thailand, Bangkok has been suffering from severe ambient particulate matter (PM) pollution mainly attributable to its wide use of diesel-fueled vehicles and motorcycles with poor emission performance. While the Thai government strives to reduce emissions from transportation through enforcing policy measures, the link between specific control policies and associated health impacts is inadequately studied. This link is especially important in exploring the co-benefits of greenhouse gas emissions reductions, which often brings reduction in other pollutants such as PM. This paper quantifies the health benefits potentially achieved by the new PM-related I/M programs targeting all diesel vehicles and motorcycles in the Bangkok Metropolitan Area (BMA). The benefits are estimated by using a framework that integrates policy scenario development, exposure assessment, exposure-response assessment and economic valuation. The results indicate that the total health damage due to the year 2000 PM emissions from vehicles in the BMA was equivalent to 2.4% of Thailand's GDP. Under the business-as-usual (BAU) scenario, total vehicular PM emissions in the BMA will increase considerably over time due to the rapid growth in vehicle population, even if the fleet average emission rates are projected to decrease over time as the result of participation of Thailand in post-Copenhagen climate change strategies. By 2015, the total health damage is estimated to increase by 2.5 times relative to the year 2000. However, control policies targeting PM emissions from automobiles, such as the PM-oriented I/M programs, could yield substantial health benefits relative to the BAU scenario, and serve as co-benefits of greenhouse gas control strategies. Despite uncertainty associated with the key assumptions used to estimate benefits, we find that with a high level confidence, the I/M programs will produce health benefits whose economic impacts considerably outweigh the expenditures on policy implementation.     

Impact of diesel policy banning on PM levels in urban areas

Increased use of diesel engine in on‐road vehicles presents a serious health concern, particularly in traffic‐congested urban areas. Diesel exhaust contains various gaseous and particulate pollutants, which, at high concentrations, pose adverse health effects. In this respect, various policy measures are being adopted worldwide to curtail emissions from diesel engines. This paper presents an assessment of diesel engine policy banning in the Greater Beirut Area. For this purpose, particulate matter levels in the air were measured after the ban and compared with concentrations reported prior to the ban. Health‐based socio‐economic benefits associated with improvement in air quality were then estimated using the long‐term decrease of particulate matter as an indicator.     

Estimating the contributions of mobile sources of PAH to urban air using real-time PAH monitoring.

Motor vehicles are a significant source of airborne polycyclic aromatic hydrocarbons (PAH) in many urban areas. Traditional approaches used in determining the relative contributions of individual vehicle types to the total amount of PAH in air have been based on the analysis of integrated samples of airborne particles and gases for the presence of chemical tracers indicative of the vehicles from which the chemicals derived. As an alternative, we have used a photoelectric aerosol sensor (PAS) capable of measuring PAH levels in real-time in the emissions plumes from motor vehicles. We placed the PAS near a traffic-light in Kenmore Square, a busy crossroads in downtown Boston (MA, USA). A video camera co-located at the site recorded the vehicles passing the sensor, and this record was correlated with the PAS data. During a 5-day monitoring period (approximately 59 h) in the summer of 1998, over 34,000 motor vehicles were counted and classified and over 24,000 PAS readings were recorded (frequency = 1/8.6 s). The composition of the vehicle population was 94% passenger vehicles, 1.4% buses, 2.6% small trucks, 1.3% medium trucks, 0.35% large trucks, and 0.45% garbage and construction trucks. In analyzing the PAS data, it was assumed that the highest PAS measurements--those that exceeded the 95% critical level of the 5-min moving average of all the PAS measurements--were indicative of primary vehicular emissions. We found that approximately 46% of the mass of particle-bound PAH (i.e. approximately 46% of the integrated area under the PAS signal vs. time plots) was attributable to primary emissions from motor vehicles passing the sensor. Of this, 35-61% was attributable to passenger vehicles (cars, pickup trucks, and sports utility vehicles) and 39-65% was attributable to non-passenger vehicles [buses (14-23%), small trucks (12-20%), medium trucks (8.4-14%), large trucks (2.9-4.8%) and garbage and construction trucks (1.9-3.2%)]. Our results suggest that on a per vehicle basis, buses and trucks--the majority of which run on diesel fuel--emitted greater amounts of particle-bound PAH than passenger vehicles. Overall, we found that real-time photoelectric aerosol sensing (in combination with video photography) is useful for estimating the contributions of airborne PAB from different vehicle types. Due to the physical constraints of our monitoring site and the high volumes of traffic, however, it was not possible to uniquely attribute PAS signals to individual vehicles.     

Remote sensing of PM, NO, CO and HC emission factors for on-road gasoline and diesel engine vehicles in Las Vegas, NV

A novel light detection and ranging-based remote sensing system was assembled and used to measure mass particulate matter (PM) emissions per unit of fuel burned from in-use on-road vehicles. A commercially available remote sensing system was concurrently used to measure emissions of carbon monoxide (CO), nitrogen oxide (NO) and hydrocarbons (HC). The two systems were used to measure 61,207 gasoline and 1180 diesel powered vehicle emissions in Las Vegas, NV from 4/4/2000 to 5/16/2002. Emission factors were related to vehicle age, weight class and fuel type by matching license IDs to the state registration data. Measurements of vehicle speed and acceleration permitted the analysis of emission factors by vehicle specific power (VSP). Average emission factors were calculated for light-duty (<3863 kg [8500 lbs]) gasoline vehicles (LDGV), light-duty diesel vehicles (LDDV), heavy-duty (>3863 kg [8500 lbs]) gasoline vehicles (HDGV) and heavy-duty diesel vehicles (HDDV). LDDV and HDDV emitted approximately 25 times more PM per mass of fuel than LDGV and HDGV. Sufficient numbers of LDGV were measured to relate VSP with CO, HC and NO emissions. No relationship was observed between PM emissions and VSP. PM emission factors from LDGV increased with vehicle age. Fuel-based emission factors measured by remote sensing were compared with MOBILE6 and PART5 emissions model factors. Good agreement was observed for HC emission factors for vehicles less than 20 years old. MOBILE6 CO emission factors were approximately 2 times greater than measured CO emission factors for vehicles less than 13 years old. Measured NO emission factors were approximately 50% greater than MOBILE6 factors for vehicles 7-15 years old but in good agreement for vehicles less than 7 years old. Measured PM emission factors showed a clear increase with vehicle age, however, PART5 uses only a single PM emission factor for LDGV less than 18 years old. The PM emission factors for the fleet of LDGV, HDGV, LDDV and HDDV were 0.06, 0.05, 1.6 and 1.5 g/kg, respectively.     

Emission factors and characteristics of criteria pollutants and volatile organic compounds (VOCs) in a freeway tunnel study

Carbon monoxide (CO), nitrogen oxide (NO(x)), hydrocarbon (HC), sulfur oxide (SO(2)), particulate matter <10 microm (PM(10)), and 57 VOC species of emissions were confirmed in a freeway tunnel in southern Taiwan. Emission factors were 1.89 (CO), 0.73 (NO(x)), 0.46 (HC), 0.02 (SO2) and 0.06 (PM(10)) g/km-vehicle for all vehicle fleets. Heavy-duty truck and trailer vehicles contributed 20% of the emissions on workdays and 9.5% on weekends in this study. Paraffins and aromatics were the main VOC groups in the tunnel. Isopentane, toluene, n-pentane, isoprene, 2,3-dimethylbutane, acetone, 2-methylpentane, 1-hexene, 1,2,4-trimethybenzene, 1-butene and propene emissions were the major VOC species. Their emission factors were over 10 mg/km-vehicle. Rainfall and high humidity in the tunnel could have reduced the VOC concentrations and increased the portion of aromatics. In addition to paraffins, olefins, and aromatic compounds, oxygenated compounds (i.e., acetone) were found. The pollutant ratios between the inside center and the outside of the tunnel were about 2-3 for CO, SO2, and PM(10) and 42 for NO(x). In addition, the emission factors of the vehicles could reflect real-world vehicle emissions on the highway and be used as baseline information for development of a vehicle control strategy.     

Experimental investigation on regulated and unregulated emissions of a diesel/methanol compound combustion engine with and without diesel oxidation catalyst

The use of methanol in combination with diesel fuel is an effective measure to reduce particulate matter (PM) and nitrogen oxides (NOx) emissions from in-use diesel vehicles. In this study, a diesel/methanol compound combustion (DMCC) scheme was proposed and a 4-cylinder naturally-aspirated direct-injection diesel engine modified to operate on the proposed combustion scheme. The effect of DMCC and diesel oxidation catalyst (DOC) on the regulated emissions of total hydrocarbons (THC), carbon monoxide (CO), NOx and PM was investigated based on the Japanese 13 Mode test cycle. Certain unregulated emissions, including methane, ethyne, ethene, 1,3-butadiene, BTX (benzene, toluene, xylene), unburned methanol and formaldehyde were also evaluated based on the same test cycle. In addition, the soluble organic fraction (SOF) in the particulate and the particulate number concentration and size distribution were investigated at certain selected modes of operation. The results show that the DMCC scheme can effectively reduce NOx, particulate mass and number concentrations, ethyne, ethene and 1,3-butadiene emissions but significantly increase the emissions of THC, CO, NO₂, BTX, unburned methanol, formaldehyde, and the proportion of SOF in the particles. After the DOC, the emission of THC, CO, NO₂, as well as the unregulated gaseous emissions, can be significantly reduced when the exhaust gas temperature is sufficiently high while the particulate mass concentration is further reduced due to oxidation of the SOF.     

Real-world operation conditions and on-road emissions of Beijing diesel buses measured by using portable emission measurement system and electric low-pressure impactor

On-road measurement is an effective method to investigate real-world emissions generated from vehicles and estimate the difference between engine certification cycles and real-world operating conditions. This study presents the results of on-road measurements collected from urban buses which propelled by diesel engine in Beijing city. Two widely used Euro III emission level buses and two Euro IV emission level buses were chosen to perform on-road emission measurements using portable emission measurement system (PEMS) for gaseous pollutant and Electric Low Pressure Impactor (ELPI) for particulate matter (PM) number emissions. The results indicate that considerable discrepancies of engine operating conditions between real-world driving cycles and engine certification cycles have been observed. Under real-world operating conditions, carbon monoxide (CO) and hydrocarbon (HC) emissions can easily meet their respective regulations limits, while brake specification nitrogen oxide (bsNO_x) emissions present a significant deviation from its corresponding limit. Compared with standard limits, the real-world bsNO_x emission of the two Euro III emission level buses approximately increased by 60% and 120% respectively, and bsNO_x of two Euro IV buses nearly twice standard limits because Selective Catalytic Reduction (SCR) system not active under low exhaust temperature. Particle mass were estimated via particle size distribution with the assumption that particle density and diameter is liner. The results demonstrate that nanometer size particulate matter make significant contribution to total particle number but play a minor role to total particle mass. It is suggested that specific certified cycle should be developed to regulate bus engines emissions on the test bench or use PEMS to control the bus emissions under real-world operating conditions.     

Actual car fleet emissions estimated from urban air quality measurements and street pollution models.

A method to determine emissions from the actual car fleet under realistic driving conditions has been developed. The method is based on air quality measurements, traffic counts and inverse application of street air quality models. Many pollutants are of importance for assessing the adverse impact of the air pollution, e.g. NO2, CO, lead, VOCs and particulate matter. Aromatic VOCs are of special great concern due to their adverse health effects. Measurements of benzene, toluene and xylenes were carried out in central Copenhagen since 1994. Significant correlation was observed between VOCs and CO concentrations, indicating that the petrol engine vehicles are the major sources of VOC air pollution in central Copenhagen. Hourly mean concentrations of benezene were observed to reach values of up to 20 ppb, what is critically high according to the WHOs recommendations. Based on inverse model calculation of dispersion of pollutants in street canyons, an average emission factor of benzene for the fleet of petrol fuelled vehicles was estimated to be 0.38 g/km in 1994 and 0.11 in 1997. This decrease was caused by the reduction of benzene content in Danish petrol since summer 1995 and increasing percentage of cars equipped with three-way catalysts. The emission factors for benzene for diesel-fuelled vehicles were low.     

Modelling instantaneous traffic emission and the influence of traffic speed limits

This paper considers the effect of active speed management on traffic-induced emissions. In particular, the traffic emissions caused by acceleration and deceleration of vehicles are modelled based on an instantaneous emission model integrated with a microscopic traffic simulation model. The emission model is based on empirical measurements which relate vehicle emission to the type, the instantaneous speed and acceleration of the vehicle. The traffic model captures the second-by-second speed and acceleration of individual vehicles travelling in a road network based on their individual driving style, the vehicle mechanics, and their interaction with other traffic and with traffic control in the network. The integrated model is applied to test a new technology to actively manage the driving speed of the vehicles in an urban network. Their impacts on vehicle emission in the network are assessed to give an indication of the relative effectiveness of the different technological designs and different levels of driver responses. The results show that, while the speed management has effectively reduced the average speed of the traffic, their impact on vehicle emissions is complex. For the study network, the frequent acceleration and deceleration movements in the network has significantly reduced the effect of the reduced average speed on emission. The net results are that the active speed management has no significant impact on pollutant emissions. The study suggests that the analysis of the environmental impacts of any traffic management and control policies is a complex issue and requires detailed analysis of not only their impact on average speeds but also on other aspects of vehicle operation such as acceleration and deceleration.     

A new method to compare vehicle emissions measured by remote sensing and laboratory testing: high-emitters and potential implications for emission inventories

A new method is presented which is designed to investigate whether laboratory test data used in the development of vehicle emission models adequately reflects emission distributions, and in particular the influence of high-emitting vehicles. The method includes the computation of a ‘high-emitter’ or ‘emission distribution’ correction factor for use in emission inventories. In order to make a valid comparison we control for a number of factors such as vehicle technology, measurement technique and driving conditions and use a variable called ‘Pollution Index’ (g/kg). Our investigation into one vehicle class has shown that laboratory and remote sensing data are substantially different for CO, HC and NO_x emissions, both in terms of their distributions as well as in their mean and 99-percentile values. Given that the remote sensing data has larger mean values for these pollutants, the analysis suggests that high-emitting vehicles may not be adequately captured in the laboratory test data.The paper presents two different methods for the computation of weighted correction factors for use in emission inventories based on laboratory test data: one using mean values for six ‘power bins’ and one using multivariate regression functions. The computed correction factors are substantial leading to an increase for laboratory-based emission factors with a factor of 1.7-1.9 for CO, 1.3-1.6 for HC and 1.4-1.7 for NO_x (actual value depending on the method). However, it also clear that there are points that require further examination before these correction factors should be applied. One important step will be to include a comparison with other types of validation studies such as tunnel studies and near-road air quality assessments to examine if these correction factors are confirmed. If so, we would recommend using the correction factors in emission inventories for motor vehicles.