珠江三角洲机动车挥发性有机物排放化学成分谱研究

根据珠三角地区机动车挥发性有机物排放(VOCs)贡献特征,选取在用轻型汽油车、轻型柴油车、液化石油气(LPG)出租车和摩托车,采用底盘测功机及实际道路测试,获取了以上车型尾气排放的VOCs化学成分(59种非甲烷碳氢化合物)特征谱.轻型汽油车以及摩托车的尾气组成中芳香烃含量最高,其次为烷烃;苯系物、异戊烷以及乙烯占轻型汽油车尾气VOCs组成的54.5%;苯系物、异戊烷以及乙炔占摩托车尾气组成的54.6%.轻型柴油车的尾气组成中烷烃比例最高,其次是芳香烃和烯炔烃.除了苯和甲苯,正十一烷、正十二烷、正癸烷、乙烯、丙烯、1-丁烯亦在柴油车尾气中占有重要比例(41.2%).LPG出租车尾气组成以丙烷、正丁烷、异丁烷为主,并伴有较高比例的1,2,4-三甲基苯、1,2,3-三甲基苯和甲苯.与类似研究比较结果表明:由于在油品、排放标准及采样与分析方法等方面的差异,机动车排放源成分谱相关研究结果仍存在一定的差异性,建议对机动车成分谱研究在尾气采样与分析方法等方面进行规范化和标准化.     

轻型汽油车VOCs排放特征和排放因子台架测试研究

为研究轻型汽油车尾气中VOCs的排放特征和排放因子,按照《轻型汽车污染物排放限值及测量方法》(中国Ⅲ、Ⅳ阶段)中要求,采用底盘测功机对国内现有不同品牌轻型汽车进行台架试验,并利用3级冷阱预浓缩GC-MS方法对尾气样品中VOCs物种进行定量分析.结果表明,尾气样品中共有68种VOCs被定量检出,其中芳香烃种类最多,占38.7%,烷烃占29.8%,烯烃(包含炔烃)占27.1%.不同品牌轻型车源排放谱特征基本吻合.轻型汽车的总VOCs排放因子为0.01~0.46g/km,前3位物种分别为乙烯、甲苯和苯.     

不同车型的颗粒物及其重金属排放分担率研究

机动车保有量的持续增长使道路交通成为城市颗粒物排放的主要贡献源,颗粒污染物富含各种重金属,对人体健康与环境保护都构成了极大的威胁。为探究不同车型对颗粒物总排放量以及不同排放物的分担率,文章选取福州市金鸡山隧道路段作为研究区域进行研究。结果表明,总车型占比为2.77%的大型客车、重型货车、轻型货车,贡献了74.43%的尾气颗粒物排放;小型客车贡献91.36%的制动颗粒物排放以及91.59%的轮胎颗粒物排放,而仅贡献8.94%的尾气颗粒物排放。根据隧道路段颗粒物排放量及机动车排放成分谱,计算出颗粒物中34种元素的排放量共计1 075.24 g/d,占颗粒物总质量(2 181.71 g/d)的49.28%;小型客车的重金属元素排放占总重金属排放的89.08%,其中尾气、制动和轮胎的颗粒物排放分别占0.28%、90.28%和9.44%;57.72%的非金属元素则来自大型客车、重型货车和轻型货车,其中尾气、制动和轮胎排放分别占96.30%、2.34%和1.36%。占比仅为2.77%的大型客车、重型货车和轻型货车为道路尾气污染物的主要贡献源,而保有量巨大的小型客车(89.63%)则主要以制动、轮胎排放的方式排放颗粒物及重金属污染物。     

轻型汽油车尾气PM2.5的排放特征

为研究轻型汽油车尾气PM_2.5的排放特征,利用整车测试台架和颗粒物稀释采样系统,对12辆轻型汽油车尾气的PM_2.5进行了采集,并进一步分析了PM_2.5排放因子及其碳质组分——OC(有机碳)和EC(元素碳)的排放特征;在此基础上,参考文献研究结果,计算了我国轻型汽油车分阶段PM_2.5排放因子,结合活动水平数据估算轻型汽油车PM_2.5排放量.结果表明:测试的国Ⅰ前~国Ⅳ轻型汽油车PM_2.5平均排放因子分别为(73.2±3.8)(50.5±45.4)(34.7±18.4)(22.6±10.3)和(1.0±0.2)mg/km,随排放阶段升级而显著降低.OC是轻型汽油车尾气PM_2.5中的主要碳质组分,在TC(总碳)中所占比例超过90%. 2012年我国轻型汽油车PM_2.5排放量为21 828.7 t,占机动车颗粒物排放总量的3.5%,其中仅占轻型汽油车保有量17%的国Ⅰ及以前车辆排放了约43%的PM_2.5. 研究显示,轻型汽油车尤其是国Ⅰ及国Ⅰ前车辆颗粒物排放不容忽视,在机动车颗粒物减排工作中应给予足够重视.      

机动车尾气VOCs排放特征及影响因素研究进展

机动车尾气排放是城市大气挥发性有机物(VOCs)的重要来源之一,深入了解机动车尾气VOCs排放特征及其影响因素可以为其污染治理提供重要理论依据。台架试验和车载测试是研究尾气污染物排放特征的关键方法,该文主要综述了机动车尾气VOCs的实验研究进展,阐述了不同测试方法下的机动车尾气VOCs排放特征,对比了不同研究得到的VOCs排放因子及组分特征,包括燃料与车辆类型、排放标准、运行工况、启动方式、累计行驶里程及燃油组分等不同因素对VOCs排放的影响,并提出OVOCs组分的分析测定、机动车驾驶行为减排和生物质燃料的应用是未来研究重点关注的方向。     

香港城区汽车行驶工况的研究

对香港的汽车行驶工况进行了研究。将一套喇嘛攻尾气排放浓度的测量系统安装在一辆轻型车上，选择两个代表性路线研究了香港地区的模式，得出了一个基于实际汽车速度的行驶工况，这个行驶工况与美国、日本、欧洲已有的行驶工况有很大不同，建议香港地区车辆排放检测法规中采用该行驶工况。     

在用汽油和柴油车排放颗粒物的粒径分布特征实测

分别选取国3～国5轻型汽油车9辆和重型柴油车15辆采用实验室底盘测功机和全流稀释定容采样系统(CVS)开展了汽柴油车尾气颗粒物排放因子实测和粒径分布比较,分析并比较了行驶工况和排放控制水平对汽柴油车尾气颗粒物排放因子和粒径分布的影响.结果表明,轻型汽油车和重型柴油车的颗粒数量单位燃料平均排放因子分别为(4.1±4.0)×10¹⁴ kg^-1和(5.7±4.3)×10¹⁵ kg^-1,重型柴油车颗粒数量排放因子是轻型汽油车的(14±7)倍.轻型汽油车超高速工况下颗粒物数量排放因子显著高于其他工况,颗粒数排放因子达到(5.1±5.0)×10¹³ km^-1,分别是低速、中速和中速工况的11.7、 14.1和7.3倍,重型柴油车高速工况颗粒数排放因子分别是低速和中速工况的2.5倍和1.4倍,且增长的颗粒物主要为核模态颗粒.国3～国5排放控制水平下汽油车颗粒物数量排放因子分别为(2.7±1.7)×10¹³、(2.6±1.3)×10¹³     

现实工况下挖掘机尾气排放特征分析

为量化挖掘机在实际施工作业中尾气排放特征,研究选取成都市不同建设工地在用的8台挖掘机,利用便携式尾气测量系统对其进行现实工况下的尾气排放测量,测试按挖掘机的不同作业特点分怠速、行走和作业进行.测量的尾气排放污染物包括CO、HC、NO和PM_2.5.结果表明,挖掘机的尾气排放随工况的不同而不同,怠速时NO排放平稳,行走和作业时排放速率波动较大.满足不同尾气排放标准的挖掘机,其尾气排放也有所不同,例如,国Ⅱ阶段的挖掘机与国Ⅰ阶段的挖掘机相比,其在怠速、行走、作业工况下尾气排放的NO分别减小8%、35%和5%,PM_2.5分别降低88%、87%和80%.另外,本研究中挖掘机尾气排放的实测结果与我国非道路机械尾气排放因子技术指南中推荐的用于排放清单估算的排放因子相比,也均有显著不同.这说明,开展非道路机械尾气排放现实工况下的测量,对于提高尾气排放清单精准度具有重要作用.     

轻型汽油车尾气OC和EC排放因子实测研究

选取27辆国3~国5轻型汽油车采用实验室底盘测功机和全流稀释定容采样系统(CVS)开展了尾气颗粒物中有机碳(OC)和无机碳(EC)组分的排放因子实测,分析了启动条件、行驶工况和喷油方式对轻型汽油车OC和EC排放的影响.结果表明,国3~国5轻型汽油车OC平均排放因子分别为(2.09±1.03)、(1.59±0.78)和(0.75±0.31)mg·km-1,EC平均排放因子分别为(1.98±1.42)、(1.57±1.80)和(0.65±0.49)mg·km-1,二者均随排放标准的提升呈显著下降趋势,OC/EC值分别为1.54±0.92、1.53±0.91以及1.47±0.66.OC1、OC2以及EC1和EC2是轻型汽油车排放的最主要碳质组分,分别占15.0%、20.6%、22.2%和21.7%.冷启动条件下轻型汽油车OC和EC排放约为热启动的1.4和1.8倍;高速工况下轻型汽油车OC和EC排放因子约为城区工况的2倍和4倍;缸内直喷(GDI)发动机的OC排放因子与进气道喷射(PFI)发动机接近,但EC排放因子约是后者的1.7倍,随着我国轻型汽油车中GDI发动机日渐普及,其EC排放应当引起密切关注.     

机动车实用路况法的研究

提出1种检测在用轻型汽油车尾气排放的新方法——机动车实用路况法（Vehicle Road Available Method,VRAM）,它采用 AVL Digas4000五气分析仪测量尾气各成份浓度,根据具体车型设定充量系数和时间差等参数,所得计算结果与汽车排放总量分析系统（Vehicle Mass Analysis System,VMAS）测量结果具有良好的相关性。作为对该方法可行性的验证,将在用轻型汽油车分类后,选取6种代表性车型进行了试验验证。指出人为因素、环境因素对实用路况法（VRAM）的相关性影响较大,但成本和便利性上的优势使得这种方法仍具有极强的实用价值。     

Modeling and predicting low-speed vehicle emissions as a function of driving kinematics

An instantaneous emission model was developed to model and predict the real driving emissions of the low-speed vehicles. The emission database used in the model was measured by using portable emission measurement system (PEMS) under actual traffic conditions in the rural area, and the characteristics of the emission data were determined in relation to the driving kinematics (speed and acceleration) of the low-speed vehicle. The input of the emission model is driving cycle, and the model requires instantaneous vehicle speed and acceleration levels as input variables and uses them to interpolate the pollutant emission rate maps to calculate the transient pollutant emission rates, which will be accumulated to calculate the total emissions released during the whole driving cycle. And the vehicle fuel consumption was determined through the carbon balance method. The model predicted the emissions and fuel consumption of an in-use low-speed vehicle type model, which agreed well with the measured data.     

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.     

遥感法用于车辆实际道路行驶污染状况评估

为了评估满足不同排放标准的在用车在实际道路行驶条件下的污染状况,以2013年3-11月间在北京市朝阳区收集的16.5×104组在用汽油车排放遥感测试大数据为基础,对北京市的在用车实际道路排放水平进行分析和评价.结果表明:新车排放标准升级明显降低了在用车的CO、HC和NO平均排放浓度.从国Ⅰ/国Ⅱ到国Ⅲ以及从国Ⅲ到国Ⅳ/国Ⅴ,每次标准升级使得在用车的CO排放浓度平均降低12%~15%,HC和NO排放浓度分别降低13%和40%左右.与2003年相比,北京市2013年机动车CO、HC和NO排放的平均浓度分别下降了52.1%、82.1%和65.3%,排放标准升级带来的减排效果十分明显.未来排放标准升级过程中应当强化对在用车实际驾驶过程排放的监管,同时积极引导老旧车辆的淘汰更新,加大对排放造假行为的执法和处罚力度.      

Development of database of real-world diesel vehicle emission factors for China

A database of real-world diesel vehicle emission factors, based on type and technology, has been developed following tests on more than 300 diesel vehicles in China using a portable emission measurement system. The database provides better understanding of diesel vehicle emissions under actual driving conditions. We found that although new regulations have reduced real-world emission levels of diesel trucks and buses significantly for most pollutants in China,NO_x emissions have been inadequately controlled by the current standards, especially for diesel buses, because of bad driving conditions in the real world. We also compared the emission factors in the database with those calculated by emission factor models and used in inventory studies. The emission factors derived from COPERT (Computer Programmer to calculate Emissions from Road Transport) and MOBILE may both underestimate real emission factors, whereas the updated COPERT and PART5 (Highway Vehicle Particulate Emission Modeling Software) models may overestimate emission factors in China. Real-world measurement results and emission factors used in recent emission inventory studies are inconsistent, which has led to inaccurate estimates of emissions from diesel trucks and buses over recent years. This suggests that emission factors derived from European or US-basedmodels will not truly represent real-world emissions in China. Therefore, it is useful and necessary to conduct systematic real-world measurements of vehicle emissions in China in order to obtain the optimum inputs for emission inventory models.     

我国重型柴油货车黑碳排放影响因素分析

柴油车的黑碳排放对空气质量和气候变化有重要影响,但我国柴油车黑碳排放清单编制仍有较大局限性. 为进一步提高柴油车黑碳排放清单编制精度,采用整车转毂台架和热光折射的方法研究不同排放标准、行驶工况和负载状况对重型柴油货车黑碳排放的影响. 结果表明:我国排放标准升级对重型柴油货车的黑碳排放有重要影响,从国Ⅰ、国Ⅱ排放标准升级到国Ⅲ、国Ⅳ和国Ⅴ排放标准,黑碳在颗粒物中的占比由41%左右逐步提至72%左右. 行驶工况对重型柴油货车的黑碳排放也有一定影响,车辆在C-WTVC (中国重型商用车燃料消耗量测试工况)下的黑碳排放占比较VECC (重型车典型道路行驶工况)下高5%~10%. 与半载状态相比,重型柴油货车在满载状态下黑碳排放占比更高,国Ⅲ、国Ⅳ重型柴油货车满载状态下黑碳排放占比较半载状态高7%~8%,国Ⅱ重型柴油货车满载状态下黑碳排放占比较半载状态高15%左右. 研究显示,柴油货车黑碳排放清单编制要综合考虑排放标准、驾驶特征、负荷状况等对黑碳排放的影响,不宜使用固定系数利用颗粒物排放因子外推黑碳排放因子.      

基于低温工况速度变化的CAL3QHC模型修正

我国寒冷地区冬季具有交通拥挤严重、车辆加减速频率和怠速比例高、行驶工况恶劣、排放集中不易扩散等特点。针对上述特点,引入加减速排放参数改进CAL3QHC模型,在低温条件下利用台架实验对各类基础排放率进行修正,并根据实地调查寒冷地区城市道路交通特征修正IVE模型得到NO_x和PM的单车综合排放因子、加速排放因子和减速排放因子。通过对哈尔滨冬季实地调查和车载实验分析,对修正模型NO_x和PM的预测进行检验。研究结果表明,修正后的模型NO_x和PM的相对误差减小了9.2%和19.4%。     

Influence of driving cycles on exhaust emissions and fuel consumption of gasoline passenger car in Bangkok

The influence of different driving cycles on their exhaust emissions and fuel consumption rate of gasoline passenger car was investigated in Bangkok based on the actual measurements obtained from a test vehicle driving on a standard chassis dynamometer. A newly established Bangkok driving cycle (BDC) and the European driving cycle (EDC) which is presently adopted as the legislative cycle for testing automobiles registered in Thailand were used. The newly developed BDC is constructed using the driving characteristic data obtained from the real on-road driving tests along selected traffic routes. A method for selecting appropriate road routes for real driving tests is also introduced. Variations of keyed driving parameters of BDC with different driving cycles were discussed. The results showed that the HC and CO emission factors of BDC are almost two and four times greater than those of EDC, respectively. Although the difference in the NOx emission factor is small, the value from BDC is still greater than that of EDC by 10%. Under BDC, the test vehicle consumes fuel about 25% more than it does under EDC. All these differences are mainly attributed to the greater proportion of idle periods and higher fluctuations of vehicle speed in the BDC cycle. This result indicated that the exhausted emissions and fuel consumption of vehicles obtained from tests under the legislative modal-type driving cycle (EDC) are significantly different from those actually produced under real traffic conditions especially during peak periods.     

基于远程数据的重型柴油车实际道路碳排放测算准确度

利用车载排放测试系统(PEMS),对3辆加装有车载诊断系统(OBD)远程监控设备的重型柴油车进行实际道路排放测试,以获取车辆实际道路基于电子控制器单元(ECU)的OBD远程油耗数据,分析碳排放结果的准确性及其影响因素.研究发现,基于碳平衡法获取的ECU油耗换算CO₂与车载排放测量系统(PEMS)直接测量的CO₂排放结果存在差异,二者偏差平均为2.06%.对影响ECU碳排放计算的关键因素(ECU油耗量和ECU行驶距离)的准确性进行了分析,发现ECU油耗的偏差均在3%以内,而ECU测量距离的平均偏差为2.41%.ECU油耗和行驶距离的准确度会受到车速、加速度和整个行程动态的影响.当车辆低速行驶时,其准确度较低.     

中国道路交通二氧化碳排放达峰路径研究

为研究我国道路交通行业CO₂排放未来控制路径,结合未来经济社会和货物运输发展状况、运输结构、能源结构和能效结构变化,采用行驶里程法分析了我国道路交通CO₂排放现状、未来变化趋势及主要驱动因素. 结果表明:①采用行驶里程法计算道路交通行业CO₂排放量相对合理,2019年全国汽车CO₂排放量为9.52×108 t,比油耗法所得结果高20%左右,二者存在差异的主要原因为交通油耗统计数据偏低. ②从车型看,重型货车和小型客车是汽车CO₂排放的主要来源,分别占39.7%、38.2%;从燃料种类看,汽油、柴油、其他燃料(天然气、醇类燃料等)CO₂排放量分别占42.8%、52.5%、4.7%. ③道路交通CO₂排放预计于“十五五”末达峰,峰值在12.2×108～13.9×108 t之间,达峰后有2～3年的平台期. ④推广新能源车是道路交通CO₂排放控制的主要驱动因素,其次为能效提升,运输结构调整在前期有一定的贡献,2025年上述措施对道路交通CO₂减排量占比分别为56%、34%和10%左右,2030年分别为55%、40%和5%左右. 研究显示,加大新能源汽车推广力度,持续降低新生产燃油车碳排放强度,推进运输结构调整,可有效降低道路交通CO₂排放.