我国轻型汽车污染物排放因子的测试研究

采用底盘测功机按ＥＣＥ－１５规程测试了我国１３辆（１２种）正在使用的轻型汽车的ＣＯ、ＨＣ和ＮＯｘ的排放量分别为８７．２５±５６．３１、１１．３６±５．１３和８．２０±６．６８ｇ／ｔｅｓｔ;在相同测试条件下,测试了其中１１种轻型车在不同车速匀速行驶时的ＣＯ、ＨＣ和ＮＯｘ排放因子．测试结果表明、轻型汽车污染物排放因子随车速的变化有良好的规律性．用统计方法拟合了轻型汽车污染物排放因子的车速变化系数的计算公式。当车速＜９０ｋｍ／ｈ时,轻型车ＣＯ、ＨＣ排放因子随车速的增加而减小,当车速＞９０ｋｍ／ｈ时,又略有增加,而ＮＯｘ排放因子随车速的增加而增大。     

中国机动车污染物排放因子及其修正方法研究

中国机动车污染物排放已成为影响空气质量的重要源。机动车污染的研究中,排放因子的确定是关键。根据机动车使用状况,车用燃料硫含量和行驶状况,运用MOBILE6．2的方法和原理确定了中国各类型机动车HC、CO、NOx的综合排放因子。小型汽油客车国0阶段CO、HC、NOx的综合排放因子分别为34．29g／km、3．45g／km和0．856g／km;国Ⅰ阶段CO、HC、NOx的综合排放因子分别为2．80g／km、0．25g/km和0．40g／km;国Ⅱ阶段CO、HC、NOx的综合排放因子分别为1．39g／km、0．16g／km和0．09g／km。     

Evaluation of the International Vehicle Emission （IVE） model with on-road remote sensing measurements

Intemational Vehicle Emissions （IVE） model funded by U.S. Environmental Protection Agency （USEPA） is designed to estimate emissions from motor vehicles in developing countries. In this study, the IVE model was evaluated by utilizing a dataset available from the remote sensing measurements on a large number of vehicles at five different sites in Hangzhou, China, in 2004 and 2005. Average fuel-based emission factors derived from the remote sensing measurements were compared with corresponding emission factors derived from IVE calculations for urban, hot stabilized condition. The results show a good agreement between the two methods for gasoline passenger cars＇ HC emission for all 1VE subsectors and technology classes. In the case of CO emissions, the modeled results were reasonably good, although systematically underestimate the emissions by almost 12%-50% for different technology classes. However, the model totally overestimated NOx emissions. The IVE NOx emission factors were 1.5-3.5 times of the remote sensing measured ones. The IVE model was also evaluated for light duty gasoline truck, heavy duty gasoline vehicles and motor cycles. A notable result was observed that the decrease in emissions from technology class State II to State I were overestimated by the IVE model compared to remote sensing measurements for all the three pollutants. Finally, in order to improve emission estimation, the adjusted base emission factors from local studies are strongly recommended to be used in the IVE model.     

机动车排放污染的速度-加速度耦合影响分析

利用OBS-2200车载测试系统,分别在高峰期、平峰期和低峰期的天津市典型路段进行了车载测试,并获得了碳氢化合物(HC)、一氧化碳(CO)和氮氧化物(NOx)等车辆排放的污染物的逐秒数据.结果显示在这3个时段内,车辆的加速度大都集中在-1.5~1.5m/s2,速度大都集中在0~70km/h,并且HC、CO和NOx的最高排放率为0.0673、0.706和0.0178g/s,都集中在高速(速度(v)>30km/h, 加速度(a)>0.5m/s2)工况范围内.通过拟合发现,HC、CO和NOx的排放率与比功率(Vehicle Specific Power,简称VSP)之间的拟合决定系数分别为0.71、0.86和0.85,相关性较高,说明VSP可以作为评价车辆排放率的一个重要参考性指标.     

乌鲁木齐市机动车排放清单研究

近年来随着乌鲁木齐市机动车数量的快速增加,致使机动车排放污染突出. 通过调查乌鲁木齐市2007年机动车的保有情况及技术水平分布,研究了各类型机动车的排放因子以及年均行驶里程,并测算了该市2007年机动车污染物排放总量、分区排放量及各类型机动车的分担率. 结果表明:2007年在乌鲁木齐市注册的各类型机动车排放的CO总量为11.09×104 t,HC总量为1.53×104 t,NO_x总量为2.73×104 t,PM总量为0.38×104 t;其中CO和HC排放主要集中在城区,NO_x和PM排放主要集中在外埠;在城区的机动车排放中,CO和HC排放以轻型载客汽车为主,NO_x排放以中重型公交车为主,PM排放以中、重型载货汽车为主.      

中国典型城市机动车排放演变趋势

选择中国12个典型城市建立1990~2009年机动车排放清单,分析各城市机动车排放历史演变趋势.结果显示,1990~2009年,研究各城市CO、VOCs、NOx和PM排放因子分别降低57%~81%、53%~78%、22%~74%和31%~76%.20年间,各城市CO和VOCs排放量总体在2000年后陆续达到增长峰值后开始下降,总量分别增长1.0倍和1.4倍;NOx和PM排放量总体保持持续增长,分别增长3.2倍和3.3倍.各城市汽油车是CO和VOCs排放主要贡献源,LDA-G、MDTB-G和HDTB-G对各城市机动车CO和VOCs排放的贡献和分别为约70%~90%和约50%~85%,其中LDA-G的排放贡献明显提高.LDA-G、MDTB-G、MDTB-D和HDTB-D贡献了80%~90%的NOx排放,其中MDTB-D和HDTB-D的排放贡献率从平均57.8%上升为72.7%.对于PM,MDTB-D和HDTB-D占排放的70%~90%.此外,部分城市摩托车排放的贡献不容忽视.     

杭州市机动车污染物排放清单的建立

基于调研的基础数据,运用修正后的IVE排放模型及GIS系统建立了杭州市2010年1km×1km的高时空分辨率的机动车排放清单.结果表明,2010年杭州市机动车污染物CO、HC、NOx、PM的年排放量分别为44.06,2.31,4.43,0.65万t,主要来自线源道路的排放.各车型污染物分担率各不相同,汽油乘用车和公交车排放CO和HC最大,柴油重型货车和公交车是NOx和PM排放的主要来源,两种燃油下的机动车排放差异十分明显.机动车污染排放与路网密集程度及道路长度密切相关,因此西湖区和江干区排放总量远远高出其他区域.机动车各污染物排放强度空间分布均呈现由城市中心向城市边缘的递减趋势,各污染物中心城区排放量占总排量的70%以上.机动车污染物排放日变化十分明显,与人群出行规律有极大的相关性.     

中国机动车排放清单的建立

以中国2002年各省统计年鉴中关于机动车及道路信息的数据为基础,并根据COPERTⅢ模型计算出的2002年中国各省区各种机动车类型在城区、郊区和高速公路3种行驶工况下的排放因子,应用GIS技术建立了40km×40km的高空间分辨率的中国机动车排放源清单.结果表明,2002年中国机动车排放CO、NO_x、NMVOC和PM₁₀的排放总量分别为2 815×10⁴、305×10⁴、461×10⁴和111×10⁴t,主要来源于摩托车和汽油小客车的排放.污染物排放量的空间分布显示出其排放集中于经济发达地区,10.8%、2.2%、9.7%和5.3%的国土面积分别排放了84%的CO、55%的NMVOC、48%的NO_x和48%的颗粒物,并呈现出东部高于西部、沿海高于内地的趋势,其中长江三角洲、珠江三角洲和京津地区的排放相对较强.     

重型柴油车实际道路油耗与排放模拟及其应用研究

基于实际行驶状态下重型车动力需求和传动系统变化规律,建立了重型柴油车整车的瞬态油耗和排放模拟方法,可实现整车发动机工况及油耗与排放的实时模拟.为验证模型的有效性,利用重型车车载排放测试手段,以柴油公交车为研究案例,模拟并验证了车辆在实际运营线路上的油耗与排放水平.公交车综合线路实测百公里油耗为16.38L,NOx、CO和THC排放因子分别为4.44、3.35、1.96g·km-1,模拟结果与实测值基本吻合,其油耗与排放因子与实测值之比均在1.06倍左右.模拟结果显示,实测公交车怠速、NOx控制区及其它区域工况点分别占32.6%、7.1%和60.4%,增加10t负载或提高1.5倍车速可使发动机负荷利用率上升,控制区比例上升至18.4%和18.8%,同时增加负载和提高车速,控制区工况可提高至33.9%.相应地,增加负载或提高车速情景分别使车辆油耗与排放上升至1.5～1.7倍和1.6～1.8倍,同时增加负载和提高车速,油耗与排放可增至2.5倍～3.0倍,控制区油耗与排放比例均有大幅度上升.总体上,该模型方法可以为评价和研究重型柴油车在实际道路上的能耗及其排放状况提供新的模拟方法和分析手段.     

城市机动车排放因子隧道试验研究

选取典型城市隧道进行机动车排放因子测试,应用隧道试验原理,通过连续48h的现场采样监测,获得了隧道内机动车排放污染物NO_x.CO、SO₂、PM₁₀、VOC和HC浓度、交通参数(车型、车速、交通流量)和气象参数(如风速、风量、温度、湿度)等实测数据.通过质量平衡计算出隧道内机动车NO_x.CO、SO₂、PM₁₀和HC的平均排放因子分别为1.379、15.404、0.142、0.637、1.857g·(km·辆)^-1.并在此基础上应用多元回归方法计算出8大类机动车各种排放污染物的单车排放因子.结果反映目前中国城市机动车污染物排放水平及各污染物排放特征.     

机动车排放车载实验及模型模拟研究

研究机动车的排放特征及获得排放因子,是建立机动车排放清单和制定相应控制策略的基础,而路上的机动车排放车载测试被认为是实验室台架测试的一个重要补充.本研究利用AVL DiGas 4000 light五气分析仪,在澳门典型路段上对7辆汽油轿车样本开展了尾气排放车载实验.研究发现安装电喷加三元催化转化系统的车辆(以下称电喷车)在气态污染物排放上比旧的化油器车有显著降低,化油器车HC、CO和NO排放的体积浓度平均值分别为227×10^-6、1.57%和1477×10^-6,而电喷车则分别为33×10^-6、0.21%和131×10^-6,约是前者的1/11～1/7.但电喷车在冷启动阶段会出现高排放;对电喷车的CO和NO排放浓度做算术平均,其绝对值主要由出现频率少的高浓度值所贡献.研究进一步估算了汽油轿车的排放因子,同时利用MOBILE5模型计算了澳门2000年汽油轿车的平均排放因子,模型计算值和实验数据估算结果的比值在59%～139%之间,如果仅比较年平均排放因子,这个比值则在68%～132%之间.结果表明,车辆采用电喷加催化转化系统,对控制污染物排放的作用显著,但催化设备存在冷启动时起燃缓慢的问题;对电喷车的技术改进,减少其在行驶过程中出现高浓度的污染物排放,将能进一步大大降低平均排放水平;应用修正的MOBILE5模型计算澳门地区汽油轿车的排放因子,结果是比较可信的.     

Real-world vehicle emission factors in Chinese metropolis city--Beijing

The dynamometer tests with different driving cycles and the real-world tests are presented. Results indicated the pollutants emission factors and fuel consumption factor with ECE15 EUDC driving cycle usually take the lowest value and with real wodd driving cycle occur the highest value, and different driving cycles will lead to significantly different vehicle emission factors with the same vehicle. Relative to the ECE15 EUDC driving cycle, the increasing rate of pollutant emission factors of CO, NOx and HC are - 0.42--2.99, - 0.32--0.81 and - 0.11--11 with FTP75 testing, 0.11--1.29, - 0.77--0.64 and 0.47--10.50 with Beijing 1997 testing and 0.25--1.83, 0.09--0.75 and - 0.58--1.50 with real wodd testing. Compared to the carburetor vehicles, the retrofit and MPI TWC vehicles‘ pollution emission factors decrease with different degree. The retrofit vehicle (Santana) will reduce 4.44%--58.44% CO, - 4.95%--36.79% NOx, -32.32%--33.89% HC, and -9.39%--14.29% fuel consumption, and especially that the MPI TWC vehicle will decrease CO by 82.48%--91.76%, NOx by 44.87%--92.79%, HC by 90.00%--93.89% and fuel consumption by 5.44%--10.55%. Vehicles can cause pollution at a very high rate when operated in high power modes; however, they may not often operate in these high power modes. In analyzing vehicle emissions, it describes the fraction of time that vehicles operate in various power modes. In Beijing, vehicles spend 90% of their operation in low power modes or decelerating.     

广州市机动车尾气排放特征研究

文章利用COPERT IV模型计算广州市机动车尾气排放因子,结合机动车保有量和构成,获得2008年广州市机动车尾气排放总量并对排放因子的速度敏感性,以及不同车型、不同排放标准、不同燃料类型机动车排放特征进行了分析。结果表明:2008年广州市机动车CO、NOX、VOC和PM的排放总量分别为138 772.42 t、80 868.69 t、24 907.26 t和3 171.97 t。摩托车和小客车是CO和VOC的主要贡献车型,贡献率总和分别达到78.31%和70.52%;而作为NOX和PM的主要贡献车型,大客车和重型货车的贡献率总和分别达到78.94%和83.72%。国0标准机动车排放水平高于其他排放标准的车型,CO和VOC的排放分担率接近于保有量比例的2倍。汽油车是CO和VOC的主要贡献车型,其排放贡献率超过80%;而PM排放主要以柴油车为主;柴油车的NOX排放总量高,接近于汽油车的2倍。     

Variation of spatio-temporal distribution of on-road vehicle emissions based on real-time RFID data

High-resolution vehicular emissions inventories are important for managing vehicular pollution and improving urban air quality. This study developed a vehicular emission inventory with high spatio-temporal resolution in the main urban area of Chongqing, based on real-time traffic data from 820 RFID detectors covering 454 roads, and the differences in spatio-temporal emission characteristics between inner and outer districts were analysed. The result showed that the daily vehicular emission intensities of CO, hydrocarbons, PM_2.5, PM₁₀, and NOx were 30.24, 3.83, 0.18, 0.20, and 8.65 kg/km per day, respectively, in the study area during 2018. The pollutants emission intensities in inner district were higher than those in outer district. Light passenger cars (LPCs) were the main contributors of all-day CO emissions in the inner and outer districts, from which the contributors of NOx emissions were different. Diesel and natural gas buses were major contributors of daytime NOx emissions in inner districts, accounting for 40.40%, but buses and heavy duty trucks (HDTs) were major contributors in outer districts. At nighttime, due to the lifting of truck restrictions and suspension of buses, HDTs become the main NOx contributor in both inner and outer districts, and its three NOx emission peak hours were found, which are different to the peak hours of total NOx emission by all vehicles. Unlike most other cities, bridges and connecting channels are always emission hotspots due to long-time traffic congestion. This knowledge will help fully understand vehicular emissions characteristics and is useful for policymakers to design precise prevention and control measures.     

杭州市区机动车污染物排放特征及分担率

选取杭州市区绕城高速、快速路、主干道和民用支路4种典型道路进行工况测试,建立了2010年机动车CO、HC、NOx和PM10排放清单,获得了分车型、燃料类型、排放标准以及道路类型的机动车污染物排放分担率.结果表明,杭州市机动车的污染物排放分担率差别显著,乘用车、出租车和公交车是CO和HC排放的主要来源,重型货车和公交车是NOx和PM10排放的主要来源,且乘用车的NOx排放分担率也较大;柴油车的NOx和PM10的排放分担率远大于其保有量的贡献率,是其排放的主要来源,汽油车是CO和HC排放的主要来源;占保有量30%的国0和国I车辆,对CO、HC、NOx和PM10排放分担率分别为67%、69%、58%和82%;主干道是机动车CO、HC和NOx排放的主要来源,其排放分担率分别为66%、65%和64%,民用支路是PM10排放的主要来源,分担率为55%.     

基于浮动车数据的机动车排放实时测算模型

根据浮动车检测技术可针对单车采集,所收集数据中的平均速度按照采样间隔连续的特点,利用道路实测数据建立了面向其应用的轻型车尾气排放实时测算模型.模型中引入平均速度增量(ASI)指标对平均速度进行细分,并以其来反映相同平均速度下的排放变化.结果表明,与实测数据相比,模型对CO2的计算误差在10%以内;NOx、HC和CO的计算误差在15%以内.同时提出了模型使用方法,可以实现对路网中交通尾气污染的实时测算和动态评估.     

Real-world fuel efficiency and exhaust emissions of light-duty diesel vehicles and their correlation with road conditions

The real-world fuel efficiency and exhaust emission profiles of CO, HC and NO_x for light-duty diesel vehicles were investigated. Using a portable emissions measurement system, 16 diesel taxies were tested on different roads in Macao and the data were normalized with the vehicle specific power bin method. The 11 Toyota Corolla diesel taxies have very good fuel economy of (5.9 ± 0.6) L/100 km, while other five diesel taxies showed relatively high values at (8.5 ± 1.7) L/100 km due to the variation in transmission systems and emission control strategies. Compared to similar Corolla gasoline models, the diesel cars confirmed an advantage of ca. 20% higher fuel efficiency. HC and CO emissions of all the 16 taxies are quite low, with the average at (0.05 ± 0.02) g/km and (0.38 ± 0.15) g/km, respectively. The average NO_x emission factor of the 11 Corolla taxies is (0.56 ± 0.17) g/km, about three times higher than their gasoline counterparts. Two of the three Hyundai Sonata taxies, configured with exhaust gas recirculation (EGR) + diesel oxidation catalyst (DOC) emission control strategies, indicated significantly higher NO₂ emissions and NO₂/NO_x ratios than other diesel taxies and consequently trigger a concern of possibly adverse impacts on ozone pollution in urban areas with this technology combination. A clear and similar pattern for fuel consumption and for each of the three gaseous pollutant emissions with various road conditions was identified. To save energy and mitigate CO₂ emissions as well as other gaseous pollutant emissions in urban area, traffic planning also needs improvement.     

富康车实测尾气排放数据分析

利用OEM系统收集富康车在实际路况上的实时尾气排放数据,得出3种主要污染物NOx、CO、HC的排放因子及测试车辆的百公里耗油量,并将排放因子同MOBIEM6模型预测的排放因子进行对比,最后对OEM技术在我国的应用进行初步探讨.     

基于情景分析的北京市机动车污染排放控制研究

为了研究未来北京市机动车排放控制措施的减排效果,本文基于情景分析法,以2010年为基准年,通过设置3类控制措施情景,估算2011~2020年不同情景下北京市机动车常规污染物排放量,并在基准情景基础上,估算污染物减排量,分析控制措施对不同类型机动车的减排贡献.结果表明,尽管未来北京市机动车保有量会有较大增长,实施机动车排放控制措施仍可取得显著的减排效果.单一措施中,淘汰高排放车减排量最大.其中,淘汰轻型客车可有效减少CO的排放,减排贡献率为89.4%;淘汰重型客车可对NOx、HC和PM10达到有效削减,其贡献率分别为65.5%、55.8%、93.4%.实施新的排放标准对重型柴油车的排放也有明显控制效果,且4种污染物都能得到有效削减.综合实施各种措施的效果最为显著,2020年对CO、NOx、HC、PM10的削减效果分别达到46.4%、42.1%、8.6%和50.6%.     

On-road pollutant emission and fuel consumption characteristics of buses in Beijing

On-road emission and fuel consumption (FC) levels for Euro III and IV buses fueled on diesel and compressed natural gas (CNG) were compared, and emission and FC characteristics of buses were analyzed based on approximately 28,700 groups of instantaneous data obtained in Beijing using a portable emissions measurement system (PEMS). The experimental results revealed that NOx and PM emissions from CNG buses were decreased by 72.0% and 82.3% respectively, compared with Euro IV diesel buses. Similarly, these emissions were reduced by 75.2% and 96.3% respectively, compared with Euro III diesel buses. In addition, CO2, CO, HC, NOx, PM emissions and FC of Euro IV diesel buses were reduced by 26.4%, 75.2%, 73.6%, 11.4%, 79.1%, and 26.0%, respectively, relative to Euro III diesel buses. The CO2, CO, HC, NOx, PM emissions and FC factors all decreased with bus speed increased, while increased as bus acceleration increased. At the same time, the emission/FC rates as well as the emission/FC factors exhibited a strong positive correlation with the vehicle specific power (VSP). They all were the lowest when VSP < 0, and then rapidly increased as VSP increased. Furthermore, both the emission/FC rates and emission/FC factors were the highest at accelerations, higher at cruise speeds, and the lowest at decelerations for non-idling buses. These results can provide a base reference to further estimate bus emission and FC inventories in Beijing.