环境科学  2023, Vol. 44 Issue (7): 3771-3778   PDF    
机动车尾气碳质气溶胶排放因子及其稳定碳同位素特征
于鸣媛1,2, 王谦3, 付明亮4,5, 戈畅1,2, 谢锋1,2, 曹芳1,2, 章炎麟1,2     
1. 南京信息工程大学应用气象学院, 南京 210044;
2. 南京信息工程大学教育部气候与环境变化国际合作联合实验室大气环境中心, 南京 210044;
3. 江苏省南通环境监测中心, 南通 226007;
4. 中国环境科学研究院国家环境保护机动车污染控制与模拟重点实验室, 北京 100012;
5. 中国环境科学研究院生态环境部机动车排污监控中心, 北京 100012
摘要: 机动车尾气是大气碳质气溶胶的重要人为来源, 其排放因子与稳定碳同位素组成是重要的基础数据. 选取多辆不同类型在用机动车, 进行多种工况、冷/热条件下启动的台架试验, 收集各测试阶段尾气分析其碳质组分含量与稳定碳同位素比值, 并探讨其影响因素.结果表明, 总碳排放因子大小为: 重型柴油车>轻型柴油车>轻型汽油车, 轻型天然气车虽然在低速与中速阶段排放因子极低, 但高速行驶阶段可达到重型柴油车的排放水平.各型车冷启动的排放因子均高于热启动, NEDC工况的排放因子整体低于WLTC工况, 应与其测试车速有关.汽油车和天然气车各测试阶段排放有机碳(OC) 均远高于元素碳(EC), 柴油车OC与EC排放因子相近, 各类车辆OC/EC都随测试车速的提高而上升.稳定碳同位素EC重于OC, 同位素比值大小关系均呈现: 汽油车 < 天然气车 < 轻型柴油车 < 重型柴油车, 现有源解析的稳定碳同位素源谱较难反映汽油车与天然气车特征.在排放治理与源解析工作中, 应注意替代燃料的使用与机动车老化过程所造成的排放因子与同位素特征值的变化影响.
关键词: 机动车尾气      排放因子      有机碳(OC)      元素碳(EC)      稳定碳同位素      底盘测功机     
Emission Factors of Carbonaceous Aerosol and Stable Carbon Isotope for In-use Vehicles
YU Ming-yuan1,2 , WANG Qian3 , FU Ming-liang4,5 , GE Chang1,2 , XIE Feng1,2 , CAO Fang1,2 , ZHANG Yan-lin1,2     
1. School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China;
2. Atmospheric Environment Center, Joint Laboratory for International Cooperation on Climate and Environmental Change, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China;
3. Jiangsu Province Nantong Environmental Monitoring Center, Nantong 226007, China;
4. State Environmental Protection Key Laboratory of Vehicle Emission Control and Simulation, Chinese Research Academy of Environmental Sciences, Beijing 100012, China;
5. Vehicle Emission Control Center, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Abstract: Vehicle exhaust is an important anthropogenic source of atmospheric carbonaceous aerosols; of which, the emission factors and stable carbon isotope composition are important basic data. In-use motor vehicles of different types were selected to conduct dynamometer tests using different test cycles and under cold/hot start conditions. The exhaust of each test stage was collected to analyze the carbonaceous components and stable carbon isotopes and to discuss the influencing factors. The total carbon emission factors follow the order: heavy-duty diesel vehicles>light-duty diesel vehicles>light-duty gasoline vehicles. Although the emission factors of light-duty natural gas vehicles were very low at the low- and medium-speed stages, they were similar to those of heavy-duty diesel vehicles at the high-speed stage. The emission factors of cold start were higher than those of hot start, and the emission factors of the NEDC test cycle were lower than those of WLTC (which should be related to the driving speed). The emission factors of organic carbon (OC) of gasoline and natural gas vehicles were much higher than those of elemental carbon (EC) in every test stage. The emission factors of OC and EC of diesel vehicles were similar. The OC/EC of all types of vehicles increased with the increase in driving speed. Stable carbon isotopes in EC were higher than those in OC. The stable carbon isotope in different vehicles follow the order: light-duty gasoline vehicles < light-duty natural gas vehicles < light-duty diesel vehicles < heavy-duty diesel vehicles. The results revealed that the source signatures of stable carbon isotope in vehicles used in current source apportionment could not well represent gasoline vehicles and natural gas vehicles. In future emission control and source apportionment, attention should be paid to the changes in emission factors and isotope signatures caused by the use of natural gas and the aging of motor vehicles.
Key words: motor vehicle exhaust      emission factor      organic carbon(OC)      elemental carbon(EC)      stable carbon isotope      chassis dynamometer     

碳质气溶胶(total carbon, TC)包含有机碳(organic carbon, OC)和元素碳(elemental carbon, EC), 是大气细颗粒物中的重要组分(约占20%~50%), 对环境、气候以及人体健康均有重要影响[1~3].机动车尾气是碳质气溶胶的重要人为来源之一[4~6], 准确识别机动车尾气中碳质气溶胶的构成, 是优化排放清单、进行针对性管控以及开展大气污染物来源解析等的重要基础工作[7~9].碳质气溶胶是机动车尾气颗粒物中的首要组分(约占50%~90%)[10, 11], 然而其排放因子受到燃料类型、车辆类型、启动条件和行驶工况等因素影响[11~13].因而有必要针对各类影响因素测定排放因子, 充实排放清单的基础数据库.对于机动车尾气排放因子的测定, 常用手段包括发动机测功[11, 14]、道路试验[15, 16]和隧道试验[17, 18]等.发动机测功方法尽管并非实际道路测试, 但其测试条件更为可控, 可得到特定车型、特定行驶工况以及特定环境下的排放因子, 因而对于排放因子的精细化研究十分有利[19, 20].

碳同位素技术是对碳质气溶胶进行来源解析的一项准确可靠的手段[21~26], 该方法根据不同燃料的稳定同位素比值(δ13C)的差异, 以及不同的燃烧条件下产生的同位素分馏, 解析出燃煤、机动车、C3与C4植物对大气样品的贡献.典型源排放碳质气溶胶的δ13C值, 是利用同位素技术展开解析的重要基础数据, 因燃料特征、燃烧条件等存在地域差异, 进行本土的源排放试验与测试工作对建立同位素数据库尤为重要[22, 27, 28]. 2007年刘刚等[29]在杭州随机选取机动车, 测试OC与EC的δ13C值, 陈颖军等[28]分析了不同车型排放TC与EC的δ13C值, 石磊等[30]与Guo等[31]分别测定了南京机动车TC与EC的δ13C值, 为排放源δ13C数据库的建立提供了重要数据.然而上述研究均通过采集机动车排气管内累积的烟尘进行同位素分析, 尚缺乏可直接指示排放到大气中颗粒物δ13C的证据, 另外随着机动车排放标准与油品质量的改变, 在用各类机动车的尾气颗粒物δ13C数据库亟待更新.

针对以上现状, 本研究选取不同燃料类型、重量类型与排放标准的在用车辆共12辆, 采用发动机测功方法进行冷/热启动与多种工况测试, 收集各个测试阶段尾气的细颗粒物(PM2.5)进行碳质气溶胶含量测定与稳定碳同位素分析, 以期服务于排放清单的更新、机动车尾气排放的控制与气溶胶源解析研究.

1 材料与方法 1.1 试验车辆

本研究的台架试验于2019年3~5月在厦门进行, 共选取12辆在用车辆, 其中轻型汽油车、轻型柴油车和改装的天然气出租车各2辆, 重型柴油车6辆, 详细信息如表 1所示.两辆轻型汽油车符合国家第五阶段机动车污染物排放标准(简称国五标准), 其他车辆均符合国四标准.

表 1 试验车辆基本信息 Table 1 Basic information of test vehicles

1.2 测试方法

所有车辆均采用底盘测功机和全流定容稀释(constant volume sampling, CVS)系统进行测试, 测试系统如图 1所示.轻型车采用AVL 48″ 4WD底盘测功机和AVL LE汽油/柴油排放测试系统(AMA i60、CVS i60、PASS i60和BMD&DVE 150), 重型车采用Burke 75″ HD底盘测功机和AVL HD分析系统(AMAi60HD、CVSi60 HD和PSSi60HD).轻型车辆测试工况为全球轻型车统一测试循环(worldwide harmonized light-duty driving test cycle, WLTC)[32], 该循环全程共1800 s, 包括低速阶段(589 s)、中速阶段(433 s)、高速阶段(455 s)和超高速阶段(323 s), 依次标记为L、M和H(高速和超高速阶段合并采样).重型车测试工况为C-WTVC(China worldwide transient vehicle cycle)[33], 是以世界统一的重型商用车辆瞬态车辆循环(world transient vehicle cycle, WTVC)为基础, 调整加速度和减速度形成的驾驶循环.该循环全程共1800 s, 包含城区阶段(900 s)、乡村阶段(468 s)和高速阶段(432 s), 依次标记为p1、p2和p3, 城区阶段存在频繁的加速与减速, 高速阶段车速较为稳定.采用WLTC工况和C-WTVC工况测试的车辆均分别在冷/热启动条件下进行重复测试与采样, 以对比启动条件对碳质气溶胶排放的影响.另为研究不同测试工况的差异, 对于轻型车辆采用新欧洲驾驶循环(new European driving cycle, NEDC)在热启动条件下进行重复测试, 该循环由城区阶段(ECE, p1)和市郊阶段(EUDC, p2)组成, 全程共1180 s.

图 1 测试系统示意 Fig. 1 Schematic diagram of the test system

测试前1 d将测试车辆驶入恒温恒湿的环境室(室温24℃, 相对湿度66%)中停放12 h以上, 测试前使用标准气通入稀释管路对测试仪器校准.测试时, 将机动车排气管接通稀释管路, 先后进行冷/热启动测试, 冷/热启动测试之间进行管路清洗与后一工况的预热.采样前将42 mm标准圆形石英滤膜放入马弗炉中400 ℃烧4 h以控制空白, 采用颗粒物采集系统分三路对各工况的尾气进行分阶段采集, 采样流速40 L·min-1, 采样后将滤膜放入聚四氟乙烯膜盒中置于冰箱冷藏.

1.3 碳质组分与同位素分析方法

PM2.5中的碳质组分采用美国Sunset Lab公司Model-4型全自动半连续式OC/EC分析仪进行测定, 升温程序选用稍作改动后的NIOSH 5040方法.测样开始前和结束后用标准蔗糖溶液进行外标校正, 采用内外标联合校正确保仪器具有较高的精准度, 其检出限为0.5 μg.

选取一辆轻型汽油车(因含碳量过低及膜量不足等原因, 只选取LG2)、两辆天然气出租车、两辆轻型柴油车和两辆重型柴油车(HD1和HD6)进行稳定碳同位素分析.分析方法采用OC/EC分析仪与光腔衰荡光谱(G2201-i, Picarro)联用, 该方法曾用于测试北京环境大气样品, 准确度优于0.1‰[34].

2 结果与讨论 2.1 TC排放因子

对于各个工况下的测试, 收集各测试阶段尾气测定其碳质气溶胶含量, 结合行驶里程获得对应的排放因子, 然后对测试里程进行加权平均, 得到该工况下的平均排放因子.TC测试结果如表 2所示, 所有测试车辆中, 轻型汽油车的TC排放因子最低, 冷/热启动条件下分别为(6.1±5.9)mg·km-1和(2.0±1.1)mg·km-1.轻型柴油车的TC排放因子[(40.6±28.0)mg·km-1和(34.6±9.1)mg·km-1]整体上低于重型柴油车[(52.3±24.6)mg·km-1和(45.7±21.3)mg·km-1], 应与发动机排量和整车重量等有关.与以往研究相比[10, 11, 35~39], 本研究的柴油车排放因子略低, 应与测试车辆对应的排放标准有关, 而汽油车排放因子略高.天然气车的尾气在以往研究中得到关注较少, 对排放因子的测试更侧重于CO和NOx[40, 41], 本研究测试发现天然气车TC排放因子很高, 热启动条件下[(43.1±22.3)mg·km-1]接近重型柴油车, 冷启动条件下[(96.5±12.8)mg·km-1]远高于重型柴油车, 在机动车排放控制工作中不可忽视.

表 2 各类车辆的TC排放因子/mg·km-1 Table 2 Emission factors of TC/mg·km-1

图 2图 3为测试车辆碳质气溶胶排放因子在测试工况各个阶段的分布.两辆国五轻型汽油车的TC排放因子在各个阶段均维持较低水平, 变化范围为1.2~18.4 mg·km-1.两辆轻型柴油车TC排放因子差异较大, 可能与里程有关:里程较短的LD1排放因子随测试速度加快而逐渐升高, 里程较长的LD2在3个测试阶段中排放因子均比较高[42~44].天然气出租车的TC排放因子在3个测试阶段中变化最大, 低速与中速阶段排放因子较低, 高速与超高速阶段排放因子显著升高, 最高值可达152.1 mg·km-1.2辆测试车辆均呈现此变化特征, 说明并非由车辆故障或测试问题导致, 推测可能与车辆较长的行驶里程引起的性能变化有关.6辆重型柴油车在3个测试阶段的排放因子变化呈现相似的趋势, 从城区阶段到郊区阶段再到高速阶段, 随着行驶速度的逐渐提高, 排放因子逐渐降低.在冷(热)启动条件下, 3个测试阶段的平均TC排放因子(mg·km-1)分别为162.7±71.2(143.1±65.0)、46.3±26.2(38.8±14.8)和24.9±13.6(22.2±14.9).重型柴油车在城区阶段的TC排放因子远高于其他两个阶段, 应与该测试阶段频繁的刹车与启动有关.

图 2 轻型车WLTC工况下各测试阶段碳质气溶胶排放因子 Fig. 2 Emission factors of carbonaceous aerosols for light-duty vehicles in each stage of the WLTC test cycle

图 3 重型柴油车各测试阶段的碳质气溶胶排放因子 Fig. 3 Emission factors of carbonaceous aerosols for heavy-duty diesel vehicles in each stage of the C-WTVC test cycle

对于车辆的冷/热启动测试, 冷启动测试后会进行相应测试工况的预热, 预热后立即进行热启动测试.各测试车辆的各个测试阶段, TC排放因子在冷启动阶段整体上高于热启动阶段, 轻型汽油车、轻型柴油车、天然气出租车和重型柴油车冷启动排放因子分别约为热启动的300%、118%、224%和115%.这与以往研究的结论较为一致[45], 主要由两方面原因导致:①冷启动时燃料温度较低, 燃烧室中燃料汽化不足从而产生不完全燃烧; ②低温导致催化转化器的活性较低, 无法高效对尾气进行处理.

对6辆轻型车重复进行NEDC工况下的热启动测试, 结果如表 2图 4所示.轻型汽油车在两种工况下的TC排放因子接近, 轻型柴油车的TC排放因子在NEDC工况下约为WLTC工况下的60%, 天然气出租车的TC排放因子在两种工况下差别最大, NEDC工况下低于WLTC工况的10%.这是因为对于WLTC工况, 各类测试车辆TC排放因子的最高值均出现在测试速度最高的第3阶段, 而NEDC两个测试工况的行驶速度均低于WLTC的第3阶段, 因而无法反映对应的排放状况.说明NEDC工况的测试会低估污染物的排放, 尤其是对于高速行驶阶段的排放.

图 4 轻型车NEDC工况下各测试阶段碳质气溶胶排放因子 Fig. 4 Emission factors of carbonaceous aerosols for light-duty vehicles in each stage of the NEDC test cycle

2.2 OC和EC排放因子

图 2图 3中的TC排放因子也包含了不同碳质组分的信息.轻型汽油车的TC主要由OC构成(占比超过95%), 而EC排放量非常低, WLTC工况的冷热启动条件下分别为(0.3±0.3)mg·km-1和(0.1±0.1)mg·km-1, NEDC工况下无EC检出.天然气出租车所排放的OC在TC中占比超过98%, EC排放因子在WLTC工况的冷热启动条件下分别为(1.9±1.5)mg·km-1和(0.2±0.1)mg·km-1, NEDC工况下低于0.1 mg·km-1.与汽油车和天然气出租车不同, 柴油车的OC排放因子整体上低于EC排放因子.轻型柴油车在两种工况下的EC排放因子均约为OC的两倍, 重型柴油车在冷启动条件下EC排放因子高出OC约50%[(31.0±15.8)mg·km-1和(21.3±13.0)mg·km-1], 热启动条件下OC排放因子变化不大[(20.2±16.6)mg·km-1], 而EC排放因子降低[(25.4±8.0)mg·km-1], 二者差距从而缩小.

整体而言, 测试车辆的OC排放因子从高到低依次为:天然气出租车>重型柴油车>轻型柴油车>轻型汽油车, EC排放因子从高到低依次为:重型柴油车>轻型柴油车≫天然气出租车>轻型汽油车, 冷启动与热启动条件下均呈现此分布规律.OC/EC比值如表 3所示, 柴油车OC/EC均低于1(EC占主导); 轻型汽油车OC/EC较高, 但较低的EC检出量可能导致该数据误差较大; 天然气出租车的OC/EC最高, 冷启动条件下与Wang等[46]研究的结果相近, 热启动条件下的值高于现有大部分研究, 应由EC排放量较少、且高速与超高速阶段排放大量OC所导致.

表 3 各类车辆尾气的OC/EC值 Table 3 OC-to-EC ratios of each type of vehicle

对于不同的测试阶段, WLTC工况下的测试车辆的OC和EC排放因子从低速到高速阶段均呈现上升趋势(EC含量过低的除外), 重型柴油车的OC和EC排放因子在3个测试阶段中均呈现下降趋势, 这与TC排放因子的变化趋势一致. 对于重型柴油车, 从城区阶段到高速阶段, OC与EC比值(OC/EC)均呈现上升趋势, 冷启动条件下从(0.11±0.15)~(0.69±0.92), 热启动条件下从(0.35±0.52)~(0.91±1.34), 说明与高速阶段相比, 城区阶段存在较多的燃料不完全燃烧情况. 另外, 采样期间未考虑环境空气中挥发性有机物的影响, 可能为OC的测量引入误差.

2.3 碳质气溶胶中的稳定同位素构成

测试车辆的δ13C分析结果如图 5所示, TC、OC和EC的δ13C值分别为(-27.89±4.09)‰ (范围: -35.19‰~-19.78‰, 下同)、(-28.13±3.83)‰(-34.58‰~-19.49‰)和-25.25‰±3.02‰(-32.04‰~-20.72‰), TC与OC的δ13C值范围相近, 而EC的δ13C偏重.Widory等[47]测定液体燃料燃烧排放TC的δ13C为-28‰~-26‰, 陈颖军等[28]分析了汽油车与柴油车的尾气管内壁烟尘样品, TC与EC的δ13C分别为(-25.75±0.32)‰和(-25.17±0.40)‰, 石磊等[30]采用相似的方法测定TC的δ13C范围为-26.32‰~-23.57‰.本研究的分析结果与之相比, 同位素均值较为接近但数值范围更大, 这一方面说明通过分析尾气管烟尘的方法可以一定程度上获得可信的稳定碳同位素结果, 同时也表明燃料、车型、行驶方式等因素的确会对尾气稳定碳同位素比值造成不可忽视的影响.

图 5 各类测试车辆排放TC、OC和EC中的稳定碳同位素比值 Fig. 5 Stable carbon isotope in TC, OC, and EC for each type of vehicle

燃料类型的差异对尾气碳质气溶胶的δ13C影响显著, 以TC为例, 汽油车δ13C值最低, 为(-32.25±2.27)‰, 其次为天然气车[(-30.69±2.44)‰], 柴油车δ13C值较高, 轻型柴油车和重型柴油车的δ13C分别为(-25.85±2.55)‰和(-23.45±1.68)‰.OC与EC的δ13C值呈现相似分布, 尽管由于汽油车和天然气车EC排放量较低而导致部分样品无法满足同位素分析需求, 依然呈现柴油车的δ13C显著高于其他车型的分布特征.目前利用碳同位素进行源解析研究中[21, 27], 所采用的机动车源稳定同位素特征值与本研究测试的柴油车相近, 高于汽油车和天然气车, 其解析结果应存在一定的误差.

各工况各测试阶段OC和EC的δ13C分析结果如图 6所示, 基本特征为:①同车型、同测试阶段内, EC-δ13C略重于OC-δ13C; ②随着测试车速的增加, δ13C逐渐变重; ③冷/热条件下启动对尾气δ13C几乎无影响.与其他化石燃料相比, 天然气的δ13C最低[47], 一定程度上可以解释较轻的天然气车尾气, 然而在不同的测试阶段中(尤其是WLTC工况的高速阶段)OC-δ13C出现较大变动, 应与排放因子的急剧增长(图 2)相关.两辆轻型柴油车中, LD2的δ13C整体高于LD1, 推测与行驶里程有关, LD2里程较长, 发动机性能与尾气处理装置有效性均劣于LD1, 因而碳质气溶胶排放量与δ13C均接近重型柴油车.两辆重型柴油车δ13C特征相近.尽管轻型汽油车和天然气车的有效样品数量较少且δ13C值跨度较大, 但其OC和EC的δ13C值均低于柴油车, 因而进行环境样品(尤其是城市环境样品)源解析时应考虑这一因素.

图 6 测试车辆各测试阶段排放的OC和EC中稳定碳同位素比值 Fig. 6 Stable carbon isotope in OC and EC in each stage of test cycles

3 结论

(1) 总碳排放因子呈现重型柴油车>轻型柴油车>轻型汽油车的特征, 轻型天然气车虽然在低速与中速阶段排放因子极低, 但高速行驶阶段可达到重型柴油车的排放水平.各型车冷启动的排放因子均高于热启动, NEDC工况的排放因子整体低于WLTC工况.

(2) 汽油车和天然气车各测试阶段排放OC均远高于元素碳EC(OC/TC>95%), 柴油车OC与EC排放因子相近, 各类车辆OC/EC都随测试车速的提高而上升.

(3) TC稳定碳同位素比值大小为:汽油车[(-32.25±2.27)‰] < 天然气车[(-30.69±2.44)‰] < 轻型柴油车[(-25.85±2.55)‰] < 重型柴油车[(-23.45±1.68)‰].EC与OC分布特征与此类似, EC重于OC.另外, 车辆老化对碳质气溶胶排放因子和稳定碳同位素特征均有影响.

参考文献
[1] 曹军骥, 占长林. 黑碳在全球气候和环境系统中的作用及其在相关研究中的意义[J]. 地球科学与环境学报, 2011, 33(2): 177-184.
Cao J J, Zhan C L. Research significance and role of black carbon in the global climate and environmental systems[J]. Journal of Earth Sciences and Environment, 2011, 33(2): 177-184.
[2] Wu X F, Vu T V, Shi Z B, et al. Characterization and source apportionment of carbonaceous PM2.5 particles in China-A review[J]. Atmospheric Environment, 2018, 189: 187-212. DOI:10.1016/j.atmosenv.2018.06.025
[3] Li J, Carlson B E, Yung Y L, et al. Scattering and absorbing aerosols in the climate system[J]. Nature Reviews Earth & Environment, 2022, 3(6): 363-379.
[4] Xu H R, Ren Y A, Zhang W X, et al. Updated global black carbon emissions from 1960 to 2017: improvements, trends, and drivers[J]. Environmental Science & Technology, 2021, 55(12): 7869-7879.
[5] Jing B Y, Wu L, Mao H J, et al. Development of a vehicle emission inventory with high temporal-spatial resolution based on NRT traffic data and its impact on air pollution in Beijing-Part 1: development and evaluation of vehicle emission inventory[J]. Atmospheric Chemistry and Physics, 2016, 16(5): 3161-3170. DOI:10.5194/acp-16-3161-2016
[6] Zheng B, Tong D, Li M, et al. Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions[J]. Atmospheric Chemistry and Physics, 2018, 18(19): 14095-14111. DOI:10.5194/acp-18-14095-2018
[7] Lv Z F, Wang X T, Deng F Y, et al. Source-receptor relationship revealed by the halted traffic and aggravated haze in Beijing during the COVID-19 lockdown[J]. Environmental Science & Technology, 2020, 54(24): 15660-15670.
[8] 谢锋, 林煜棋, 宋文怀, 等. 南京北郊黑碳气溶胶分布特征及来源[J]. 环境科学, 2020, 41(10): 4392-4401.
Xie F, Lin Y Q, Song W H, et al. Distribution characteristics and source of black carbon aerosols in the northern suburbs of Nanjing[J]. Environmental Science, 2020, 41(10): 4392-4401.
[9] Wu Y, Zhang S J, Hao J M, et al. On-road vehicle emissions and their control in China: a review and outlook[J]. Science of the Total Environment, 2017, 574: 332-349. DOI:10.1016/j.scitotenv.2016.09.040
[10] Wu B B, Shen X B, Cao X Y, et al. Carbonaceous composition of PM2.5 emitted from on-road China Ⅲ diesel trucks in Beijing, China[J]. Atmospheric Environment, 2015, 116: 216-224. DOI:10.1016/j.atmosenv.2015.06.039
[11] Hao Y Z, Gao C J, Deng S X, et al. Chemical characterisation of PM2.5 emitted from motor vehicles powered by diesel, gasoline, natural gas and methanol fuel[J]. Science of the Total Environment, 2019, 674: 128-139. DOI:10.1016/j.scitotenv.2019.03.410
[12] 黄成, 胡磬遥, 鲁君. 轻型汽油车尾气OC和EC排放因子实测研究[J]. 环境科学, 2018, 39(7): 3110-3117.
Huang C, Hu Q Y, Lu J. Measurements of OC and EC emission factors for light-duty gasoline vehicles[J]. Environmental Science, 2018, 39(7): 3110-3117.
[13] 王瑞宁, 胡磬遥, 任洪娟, 等. 在用汽油和柴油车排放颗粒物的粒径分布特征实测[J]. 环境科学, 2020, 41(3): 1151-1157.
Wang R N, Hu Q Y, Ren H J, et al. Particle size distribution of PM emission from in-use gasoline and diesel vehicles[J]. Environmental Science, 2020, 41(3): 1151-1157.
[14] Suarez-Bertoa R, Astorga C. Impact of cold temperature on Euro 6 passenger car emissions[J]. Environmental Pollution, 2018, 234: 318-329. DOI:10.1016/j.envpol.2017.10.096
[15] Tang G Z, Wang S B, Du B C, et al. Study on pollutant emission characteristics of different types of diesel vehicles during actual road cold start[J]. Science of the Total Environment, 2022, 823. DOI:10.1016/j.scitotenv.2022.153598
[16] Huang H, Zhang J J, Hu H, et al. On-road emissions of fine particles and associated chemical components from motor vehicles in Wuhan, China[J]. Environmental Research, 2022, 210. DOI:10.1016/j.envres.2022.112900
[17] Zhang R Q, Li S, Fu X W, et al. Emissions and light absorption of carbonaceous aerosols from on-road vehicles in an urban tunnel in south China[J]. Science of the Total Environment, 2021, 790. DOI:10.1016/j.scitotenv.2021.148220
[18] Li X L, Feng J L, Li Y J, et al. Size-fractionated nonpolar organic compounds of traffic aerosol emissions in a highway tunnel[J]. Environmental Pollution, 2022, 293. DOI:10.1016/j.envpol.2021.118501
[19] 唐荣志, 谭瑞, 王辉, 等. 缸内直喷汽油车颗粒物排放特征及影响因素[J]. 环境科学学报, 2020, 40(3): 846-853.
Tang R Z, Tan R, Wang H, et al. Physical and chemical characterization of particle emissions from gasoline direct injection vehicle and its influencing factors[J]. Acta Scientiae Circumstantiae, 2020, 40(3): 846-853.
[20] 李家琛, 葛蕴珊, 王浩浩, 等. 缸内直喷汽油车颗粒物化学组分特征[J]. 环境科学, 2022, 43(12): 5464-5469.
Li J C, Ge Y S, Wang H H, et al. Chemical characterizations of particles from direct-injection gasoline vehicles[J]. Environmental Science, 2022, 43(12): 5464-5469.
[21] Cao J J, Chow J C, Tao J, et al. Stable carbon isotopes in aerosols from Chinese cities: influence of fossil fuels[J]. Atmospheric Environment, 2011, 45(6): 1359-1363. DOI:10.1016/j.atmosenv.2010.10.056
[22] 姜帆, 刘俊文, 黄志炯, 等. 黑碳气溶胶的稳定和放射性碳同位素研究进展[J]. 科学通报, 2020, 65(35): 4095-4106.
Jiang F, Liu J W, Huang Z J, et al. Progress of the stable carbon and radiocarbon isotopes of black carbon aerosol[J]. Chinese Science Bulletin, 2020, 65(35): 4095-4106.
[23] 黄汝锦, 郭洁, 倪海燕, 等. 西安冬季元素碳气溶胶的碳同位素组成及来源变化[J]. 矿物岩石地球化学通报, 2019, 38(6): 1073-1080.
Huang R J, Guo J, Ni H Y, et al. Carbon isotope composition and source analysis of element carbon aerosol in winter of Xi'an[J]. Bulletin of Mineralogy, Petrology and Geochemistry, 2019, 38(6): 1073-1080.
[24] Vernooij R, Dusek U, Popa M E, et al. Stable carbon isotopic composition of biomass burning emissions-implications for estimating the contribution of C3 and C4 plants[J]. Atmospheric Chemistry and Physics, 2022, 22(4): 2871-2890.
[25] Ni H Y, Huang R J, Yao P, et al. Organic aerosol formation and aging processes in Beijing constrained by size-resolved measurements of radiocarbon and stable isotopic 13C[J]. Environment International, 2022, 158. DOI:10.1016/j.envint.2021.106890
[26] Zhao Z Z, Cao J J, Zhang T, et al. Stable carbon isotopes and levoglucosan for PM2.5 elemental carbon source apportionments in the largest city of Northwest China[J]. Atmospheric Environment, 2018, 185: 253-261.
[27] Andersson A, Deng J J, Du K, et al. Regionally-varying combustion sources of the January 2013 severe haze events over Eastern China[J]. Environmental Science & Technology, 2015, 49(4): 2038-2043.
[28] 陈颖军, 蔡伟伟, 黄国培, 等. 典型排放源黑碳的稳定碳同位素组成研究[J]. 环境科学, 2012, 33(3): 673-678.
Chen Y J, Cai W W, Huang G P, et al. Stable carbon isotope of black carbon from typical emission sources in China[J]. Environmental Science, 2012, 33(3): 673-678.
[29] 刘刚, 姚祁芳, 杨辉. 汽车尾气烟尘中有机碳和元素碳的稳定同位素组成[J]. 环境与健康杂志, 2008, 25(9): 822-823.
[30] 石磊, 郭照冰, 姜文娟, 等. 南京地区大气PM2.5潜在污染源硫碳同位素组成特征[J]. 环境科学, 2016, 37(1): 22-27.
Shi L, Guo Z B, Jiang W J, et al. Investigations on sulfur and carbon isotopic compositions of potential polluted sources in atmospheric PM2.5 in Nanjing region[J]. Environmental Science, 2016, 37(1): 22-27.
[31] Guo Z B, Jiang W J, Chen S L, et al. Stable isotopic compositions of elemental carbon in PM1.1 in north suburb of Nanjing Region, China[J]. Atmospheric Research, 2016, 168: 105-111.
[32] Sileghem L, Bosteels D, May J, et al. Analysis of vehicle emission measurements on the new WLTC, the NEDC and the CADC[J]. Transportation Research Part D: Transport and Environment, 2014, 32: 70-85.
[33] Hu Y D, Yang F Y, Ouyang M G. Fuel consumption analysis and optimizing of a heavy duty dual motor coaxial series-parallel hybrid lorry under C-WTVC[J]. SAE Technical Paper, 2017. DOI:10.4271/2017-01-2359
[34] Lin Y C, Zhang Y L, Xie F, et al. Development of a monitoring system for semicontinuous measurements of stable carbon isotope ratios in atmospheric carbonaceous aerosols: optimized methods and application to field measurements[J]. Analytical Chemistry, 2020, 92(21): 14373-14382.
[35] Wu B B, Shen X B, Cao X Y, et al. Characterization of the chemical composition of PM2.5 emitted from on-road China Ⅲ and China Ⅳ diesel trucks in Beijing, China[J]. Science of the Total Environment, 2016, 551-552: 579-589.
[36] Yang H H, Dhital N B, Wang L C, et al. Chemical characterization of fine particulate matter in gasoline and diesel vehicle exhaust[J]. Aerosol and Air Quality Research, 2019, 19(6): 1439-1449.
[37] Alves C A, Lopes D J, Calvo A I, et al. Emissions from light-duty diesel and gasoline in-use vehicles measured on chassis dynamometer test cycles[J]. Aerosol and Air Quality Research, 2015, 15(1): 99-116.
[38] 何立强, 胡京南, 祖雷, 等. 国Ⅰ~国Ⅲ重型柴油车尾气PM2.5及其碳质组分的排放特征[J]. 环境科学学报, 2015, 35(3): 656-662.
He L Q, Hu J N, Zu L, et al. Emission characteristics of exhaust PM2.5 and its carbonaceous components from China Ⅰ to China Ⅲ heavy-duty diesel vehicles[J]. Acta Scientiae Circumstantiae, 2015, 35(3): 656-662.
[39] Hao Y Z, Deng S X, Qiu Z W, et al. Chemical characterization of PM2.5 emitted from China Ⅳ and China Ⅴ light-duty vehicles in China[J]. Science of the Total Environment, 2021, 783. DOI:10.1016/j.scitotenv.2021.147101
[40] 马志磊, 何超, 刘学渊, 等. 轻型车燃用汽油/天然气的高原道路排放特征[J]. 重庆理工大学学报(自然科学版), 2022, 36(1): 294-302.
Ma Z L, He C, Liu X Y, et al. Emission characteristics of light-duty vehicle fueled with gasoline/CNG on plateau road[J]. Journal of Chongqing University of Technology (Natural Science), 2022, 36(1): 294-302.
[41] 赵琛, 王军方, 付明亮, 等. 重型天然气车实际道路排放特征与机理研究[J]. 环境科学研究, 2022, 35(7): 1573-1580.
Zhao C, Wang J F, Fu M L, et al. Real world driving emission characteristics and mechanism of heavy duty liquefied natural gas vehicles[J]. Research of Environmental Sciences, 2022, 35(7): 1573-1580.
[42] Liu H, Qi L J, Liang C S, et al. How aging process changes characteristics of vehicle emissions? A review[J]. Critical Reviews in Environmental Science and Technology, 2019, 50(17): 1796-1828.
[43] Bishop G A, Stedman D H, Burgard D A, et al. High-mileage light-duty fleet vehicle emissions: their potentially overlooked importance[J]. Environmental Science & Technology, 2016, 50(10): 5405-5411.
[44] Li J C, Ge Y S, Wang X, et al. Evaporative emission characteristics of high-mileage gasoline vehicles[J]. Environmental Pollution, 2022, 303. DOI:10.1016/j.envpol.2022.119127
[45] Liu Q, Liu J P, Fu J Q, et al. Comparative study on combustion and thermodynamics performance of gasoline direct injection (GDI) engine under cold start and warm-up NEDC[J]. Energy Conversion and Management, 2019, 181: 663-673.
[46] Wang B, Lau Y S, Huang Y H, et al. Chemical and toxicological characterization of particulate emissions from diesel vehicles[J]. Journal of Hazardous Materials, 2021, 405. DOI:10.1016/j.jhazmat.2020.124613
[47] Widory D. Combustibles, fuels and their combustion products: a view through carbon isotopes[J]. Combustion Theory and Modelling, 2006, 10(5): 831-841.