Characterization, reactivity, source apportionment, and potential source areas of ambient volatile organic compounds in a typical tropical city

Based on one-year observation, the concentration, sources, and potential source areas of volatile organic compounds (VOCs) were comprehensively analyzed to investigate the pollution characteristics of ambient VOCs in Haikou, China. The results showed that the annual average concentration of total VOCs (TVOCs) was 11.4 ppbV, and the composition was dominated by alkanes (8.2 ppbV, 71.4%) and alkenes (1.3 ppbV, 20.5%). The diurnal variation in the concentration of dominant VOC species showed a distinct bimodal distribution with peaks in the morning and evening. The greatest contribution to ozone formation potential (OFP) was made by alkenes (51.6%), followed by alkanes (27.2%). The concentrations of VOCs and nitrogen dioxide (NO₂) in spring and summer were low, and it was difficult to generate high ozone (O₃) concentrations through photochemical reactions. The significant increase in O₃ concentrations in autumn and winter was mainly related to the transmission of pollutants from the northeast. Traffic sources (40.1%), industrial sources (19.4%), combustion sources (18.6%), solvent usage sources (15.5%) and plant sources (6.4%) were identified as major sources of VOCs through the positive matrix factorization (PMF) model. The southeastern coastal areas of China were identified as major potential source areas of VOCs through the potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models. Overall, the concentration of ambient VOCs in Haikou was strongly influenced by traffic sources and long-distance transport, and the control of VOCs emitted from vehicles should be strengthened to reduce the active species of ambient VOCs in Haikou, thereby reducing the generation of O₃.     

大连市夏季VOCs化学反应活性及来源

为了解大连市环境空气挥发性有机物（VOCs）污染特征及来源,基于2020年6~8月高时间分辨率VOCs在线观测数据,对大连市大气VOCs的浓度水平、组成特征、反应活性及来源情况进行了分析.结果表明φ（VOCs）的平均值为（10.21±5.71）×10^-9,其中烷烃占比为66.35%,烯烃为11.89%,炔烃为7.75%,芳香烃为14.01%.VOCs和NO_x呈现夜间高,白天低的特征,而O₃变化趋势相反.综合考虑物种活性,确定甲苯、乙烯、间/对-二甲苯、1-己烯、正丁烷、异戊烷、正戊烷和异戊二烯是影响大连市大气VOCs的关键物种,优先控制烯烃和芳香烃类化合物的排放是改善大连市夏季O₃污染的关键.PMF源解析结果显示交通源（26.38%）、燃烧源（22.75%）、工业排放源（17.09%）、溶剂使用源（14.59%）、天然源（11.72%）和其他（7.47%）为监测期间VOCs的主要来源,交通源和燃烧源排放是大连市夏季O₃防控的重点污染源.     

成都市臭氧生成敏感性分析及控制策略的制定

利用OZIPR模式结合经验动力学建模方法(EKMA)模拟成都市2017年O_3生成过程并绘制EKMA曲线,模拟过程采用CB05机理描述系统的动力学机理,结果表明,成都市O_3生成处于VOCs控制区,同时存在NO_x单独减少的不利效应,O3控制策略应对VOCs进行减排或同时减排VOCs和NO_x.选取5种VOCs和NO_x减排比例进行计算,分析结果发现,VOCs与NO_x减排量呈线性关系:VOCs=0.77NO_x+0.18.成都市"十二五"规划中NO_x减排目标为19.13%,代入上式计算后知,VOCs需减排33%才能使O_3最大小时浓度达到环境空气质量的二级标准.利用臭氧生成潜势(OFP)计算14种VOCs人为排放源对O_3生成的贡献,结果显示,对OFP具有主要贡献的有8种排放源,将33%的VOCs减排目标分配到这8种排放源中,可得各排放源的VOCs减排目标:移动源11.88%、溶剂使用源10.23%、能源民用燃烧3.3%、化工行业2.97%、露天秸秆焚烧1.49%、餐饮0.83%、汽油蒸汽0.63%、建材行业0.59%.     

Characteristics of ambient volatile organic compounds during spring O3 pollution episode in Chengdu, China

Surface ozone (O₃) has become a critical pollutant impeding air quality improvement in many Chinese megacities. Chengdu is a megacity located in Sichuan Basin in southwest China, where O₃ pollution occurs frequently in both spring and summer. In order to understand the elevated O₃ during spring in Chengdu, we conducted sampling campaign at three sites during O₃ pollution episodes in April. Volatile organic compounds (VOCs) compositions at each site were similar, and oxygenated VOCs (OVOCs) concentrations accounted for the highest proportion (35%-45%), followed by alkanes, alkens (including acetylene), halohydrocarbons, and aromatics. The sensitivity of O₃ to its precursors was analyzed using an observation based box model. The relative incremental reactivity of OVOCs was larger than other precursors, suggesting that they also played the dominant role in O₃ formation. Furthermore, the positive matrix factorization model was used to identify the dominant emission sources and to evaluate their contribution to VOCs in the city. The main sources of VOCs in spring were from combustion (27.75%), industrial manufacturing (24.17%), vehicle exhaust (20.35%), and solvent utilization (18.35%). Discussions on VOCs and NO_x reduction schemes suggested that Chengdu was typical in the VOC-limited regime, and VOC emission reduction would help to prevent and control O₃. The analysis of emission reduction scenarios based on VOCs sources showed that the emission reduction ratio of VOCs to NO₂ needs to reach more than 3 in order to achieve O₃ prevention. Emission reduction from vehicular exhaust source and solvent utilization source may be more effective.     

The levels, sources and reactivity of volatile organic compounds in a typical urban area of Northeast China

Air concentrations of volatile organic compounds (VOCs) were continually measured at a monitoring site in Shenyang from 20 August to 16 September 2017. The average concentrations of alkanes, alkenes, aromatics and carbonyls were 28.54, 6.30, 5.59 and 9.78 ppbv, respectively. Seven sources were identified by the Positive Matrix Factorization model based on the measurement data of VOCs and CO. Vehicle exhaust contributed the most (36.15%) to the total propene-equivalent concentration of the measured VOCs, followed by combustion emission (16.92%), vegetation emission and secondary formation (14.33%), solvent usage (10.59%), petrochemical industry emission (9.89%), petrol evaporation (6.28%), and liquefied petroleum gas (LPG) usage (5.84%). Vehicle exhaust, solvent usage and combustion emission were found to be the top three VOC sources for O₃ formation potential, accounting for 34.52%, 16.55% and 11.94%, respectively. The diurnal variation of the total VOCs from each source could be well explained by their emission characteristics, e.g., the two peaks of VOC concentrations from LPG usage were in line with the cooking times for breakfast and lunch. Wind rose plots of the VOCs from each source could reveal the possible distribution of the sources around the monitoring site. The O₃ pollution episodes during the measurement period were found to be coincident with the elevation of VOCs, which was mainly due to the air parcel from the southeast direction where petrochemical industry emission was found to be dominant, suggesting that the petrochemical industry emission from the southeast was probably a significant cause of O₃ pollution in Shenyang.     

Temporal variations and source apportionment of volatile organic compounds at an urban site in Shijiazhuang, China

Shijiazhuang, the city with the worst air quality in China, is suffering from severe ozone pollution in summer. As the key precursors of ozone generation, it is necessary to control the Volatile Organic Compounds (VOCs) pollution. To have a better understanding of the pollution status and source contribution, the concentrations of 117 ambient VOCs were analyzed from April to August 2018 in an urban site in Shijiazhuang. Results showed that the monthly average concentration of total VOCs was 66.27 ppbv, in which, the oxygenated VOCs (37.89%), alkanes (33.89%), and halogenated hydrocarbons (13.31%) were the main composite on. Eight major sources were identified using Positive Matrix Factorization modeling with an accurate VOCs emission inventory as inter-complementary methods revealed that the petrochemical industry (26.24%), other industrial sources (15.19%), and traffic source (12.24%) were the major sources for ambient VOCs in Shijiazhuang. The spatial distributions of major industrial activities emissions were identified by using geographic information statistics system, which illustrated the VOCs was mainly from the north and southeast of Shijiazhuang. The inverse trajectory analysis using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and Potential Source Contribution Function (PSCF) clearly demonstrated the features of pollutant transport to Shijiazhuang. These findings can provide references for local governments regarding control strategies to reduce VOCs emissions.     

北京怀柔O3污染过程初始VOCs浓度特征及来源分析

为了解北京怀柔区夏季典型O₃污染过程中初始VOCs（挥发性有机物）浓度（以φ计）的特征,识别其关键物种及主要来源,于2016年8月3-11日在中国科学院大学雁栖湖校区教学楼顶开展强化观测,利用光化学物种比值法和连续反应模型法测算观测期间大气初始φ（VOCs）,采用MIR（最大增量反应活性）法估算初始VOCs的OFP（O₃生成潜势）,识别关键物种,并应用PMF（正交矩阵因子）模型对初始VOCs的来源进行解析.结果表明:北京怀柔区O₃污染过程中初始φ（VOCs）平均值为25.27×10-9,如忽略化学损失,φ（VOCs）将被低估约18.6%.初始VOCs的总OFP值为144.6×10-9,VOCs物种对总OFP贡献率的顺序依次为醛酮类>烯烃>芳香烃>烷烃,异戊二烯、乙醛、己醛、间/对-二甲苯、甲苯、乙烯、丙烯、1,2,4-三甲苯、丁酮、1,3,5-三甲苯是怀柔区O₃形成的关键活性物种.PMF解析结果显示,机动车尾气源对初始φ（VOCs）的贡献率（23.5%）最高,其次是溶剂使用源（18.3%）、植物排放源（18.1%）、工业过程源（17.6%）、生物质燃烧源（12.1%）和煤炭燃烧源（10.5%）.研究显示,在北京怀柔区典型O₃污染过程中,减少机动车尾气源、溶剂使用源、上风向工业过程源的排放是控制怀柔区VOCs的有效措施,而控制异戊二烯、乙醛、己醛、间/对-二甲苯、甲苯等关键活性物种则是有效抑制VOCs排放对O₃生成贡献的重要手段.      

南昌市2021年春季大气VOCs污染特征和来源分析

2021年2～4月,利用AQMS-900VCM大气挥发性有机物在线监测系统对南昌市经济技术开发区大气中114种挥发性有机化合物(VOCs)进行了在线观测,分析了春季南昌市大气中VOCs浓度水平、日变化,估算了各种VOCs的臭氧生成潜势(OFP),并基于PMF模型探讨了 VOCs的来源.结果表明,南昌市经济技术开发区20...     

三亚市大气VOCs污染特征、臭氧生成潜势及来源解析

为探究热带地区环境空气中挥发性有机物(VOCs)的污染特征,利用三亚市2019年VOCs在线监测数据,全面分析了VOCs的污染特征、来源以及对O₃的影响.结果表明:①总挥发性有机物(TVOCs)日均体积分数范围为2.05×10-9~19.74×10-9,且以烷烃(71.4%)和烯烃(20.5%)为主.②VOCs优势物种丙烷、正丁烷、乙烷、异丁烷、乙烯、乙炔、苯和甲苯的体积分数日变化均呈早晚双峰的特征;φ(异戊二烯)呈白天显著高于夜间的特征,其季节性变化规律与光照变化基本一致.③对臭氧生成潜势(OFP)贡献最大的是烯烃(70.6%),其中异戊二烯的OFP贡献率(41.9%)最大,其次是烷烃(19.9%).④春夏季φ(NO₂)和φ(VOCs)均较低,难以通过光化学反应生成较高的φ(O₃),秋冬季φ(O₃)显著升高主要与东北方向污染物传输有关.⑤正交矩阵因子模型(PMF)解析结果表明,VOCs来源分别为交通源(46.52%)、溶剂使用源(18.25%)、植物源(12.36%)、工业源(11.99%)和燃烧源(10.88%).研究显示,三亚市环境空气中φ(VOCs)受交通源排放影响较大,应加强管制以削减环境空气中VOCs活性较大的物种,从而减少O₃的生成.      

基于CAMx-OSAT方法的西宁臭氧来源解析

利用青海省西宁市2018—2019年O₃浓度高值时期监测数据,结合CAMx-OSAT方法从控制型、分类排放源、区域贡献3个方面定量剖析西宁的O₃污染来源.结果表明：西宁O₃浓度整体为VOCs控制,主城四区（城东区、城西区、城北区、城中区）尤其突出,且夏季较为显著;2018年和2019年VOCs的贡献占比分别为9.76%和8.91%;而周边区县由NO_x和VOCs共同控制.除背景场外,工业源对西宁O₃生成的贡献最高,其在2018年和2019年模拟期的贡献占比分别为52.22%和47.24%,其次为交通源.模拟期内,本地源和外地传输的贡献比值约为2：1,西宁的O₃以本地生成为主.本地源中,主城四区是O₃生成的主要区域来源,占比约为32.26%;外地传输中,海东是主要贡献区.因此,为降低西宁本地O₃污染浓度,应在夏季日间时段控制主城区工业源及交通源的VOCs排放,并加强与海东的联防联控.     

Atmospheric gaseous organic acids in winter in a rural site of the North China Plain

Organic acids are important contributors to the acidity of atmospheric precipitation,but their existence in the Chinese atmosphere is largely unclear.In this study,twelve atmospheric gaseous organic acids,including C₁-C₉ alkanoic acids,methacrylic acid,pyruvic acid,and benzoic acid,were observed in the suburb of Wangdu,Hebei Province,a typical rural site in the northern China plain from 16^th December,2018 to 22^nd January,2019,using a Vocus@Proton-Trans...     

上海市城区VOCs的年变化特征及其关键活性组分

2010年在上海市城区开展了为期一年的连续观测,采用自动在线GC-FID方法定量测试了大气中56个VOCs物种的浓度.结果发现,上海市城区大气VOCs的全年小时体积分数为(2.47~301.48)×10^-9,平均体积分数为(26.45±23.36)×10^-9,其中,烷烃占46.72%,芳香烃占33.18%,烯烃占11.33%,乙炔占8.76%.T/B(甲苯/苯)为3.51±2.40,表明气团除受机动车影响外,受溶剂、油气和LPG挥发等其他VOCs排放的影响也比较突出;E/E(乙烷/乙炔)为0.98±0.68,表明气团存在老化现象,且春冬季节气团光化学年龄相对较短,夏秋季节光化学年龄相对较长.VOCs的浓度水平和组成在不同风向风速影响下存在一定差异,西南部石化和化工企业排放的VOCs对城区的影响明显,其主要物种为芳香烃和烯烃;该地区气团的OH消耗速率常数(K^OH)为8.05×10^-12 cm³·分子^-1·s^-1,平均VOCs最大O₃增量反应活性(4.00 mol·mol^-1)与乙烯相当,平均反应活性较强;对OH消耗速率(L^OH)贡献率最大的是烯烃(42.21%)和芳香烃(40.83%),对臭氧生成潜势(OFP)贡献率最大的是芳香烃(62.75%)和烯烃(21.70%),VOCs的关键活性组分是二甲苯、甲苯、乙苯、乙烯、丙烯、反-2-丁烯及异戊二烯.     

黄冈市大气挥发性有机物污染特征、来源及对臭氧生成的影响

基于黄冈市城区大气挥发性有机物（VOCs）离线采样数据和常规空气污染物、气象在线监测数据,分析了黄冈市大气VOC组分和体积分数特征,并利用正交矩阵因子分解（PMF）模型和耦合MCM机制的光化学反应箱式模型（PBM-MCM）分别分析了臭氧（O₃）污染高发期VOCs的来源及臭氧生成敏感性.结果表明,φ（TVOCs）平均值为（21.57±3.13）×10^-9,且呈现出冬春高、夏秋低的季节性特征,其中烷烃（49.9%）和烯烃（16.4%）的占比最大.PMF解析结果显示黄冈市大气VOCs主要来源为：燃料燃烧源（27.8%）、机动车排放源（19.9%）、溶剂使用源（15.7%）、工业卤代烃排放源（12.1%）、化工企业排放源（10.5%）、自然源（7.8%）和柴油车排放源（6.2%）.在人为源中,溶剂使用、燃料燃烧和化工企业排放的VOCs对大气环境中O₃生成的贡献较大,贡献了O₃生成的60.9%,故对O₃污染防控应优先管控这3种人为源.通过相对增量反应性（RIR）和经验动力学方法（EKMA）曲线分析,观测期间黄冈市O₃生成处于VOCs控制区,且间/对-二甲苯、乙烯、1-丁烯和甲苯等VOCs对O₃生成比较敏感,应重点削减以上VOCs的排放.     

长沙大气中VOCs研究

应用大气采样罐采样技术和色谱-质谱联用（GC-MS）技术,对2008年长沙市大气中76种挥发性有机物（VOCs）的组分及其质量浓度水平进行测试,比较了各组分对臭氧产生的影响潜势,同时对其主要来源进行简单分析.结果表明,长沙大气总VOCs在上午和下午的浓度分别是38.4×10-9（体积分数）和22.7×10-9（体积分数）,下午大气中VOCs浓度显著低于上午;季节变化呈现VOCs冬季浓度远高于夏季VOCs浓度,组分中以卤代烃最高,烷烃、芳烃次之,烯烃最低,OH消耗速率最高的物质是间、对二甲苯（10.71×10-9 C,碳单位体积比,下同）;其次为1,2,4-三甲苯（6.04×10-9 C）和1,3,5-三甲苯（2.23×10-9 C）.芳烃对大气O3生成贡献最大（66%）,其次是烯烃（26%）,烷烃最低（8%）.高浓度的异戊烷和丙烷说明了机动车排放和液化石油气是VOCs来源之一,苯/甲苯的特征比值接近0.8,远高于机动车尾气排放特征比值0.5;说明溶剂和涂料挥发是其主要来源之一.     

鹤壁市大气挥发性有机物源排放清单研究

采用排放系数法与“自下而上”的活动水平数据收集方法,建立了鹤壁市化石燃料固定燃烧源、工艺过程源、溶剂使用源、储存运输源、废弃物处理源等固定源、移动源、餐饮油烟和生物质燃烧等面源的VOCs排放清单.结果表明：鹤壁市2017年VOCs排放总量为8829.7t.其中,工艺过程源排放量最大（3052.5t）,占VOCs总排放量的32%;其次是移动源（2712.8t）和溶剂使用源（1447.1t）,分别占总排放量的29%和15%;从空间分布看,浚县的VOCs排放量最大（3444.0t）,其次为淇滨区（1519.4t）、山城区（1516.0t）、淇县（1103.8t）和鹤山区（1041.9t）;其中,机动车（1932.0t）、建材冶金（903.6t）、化学制品制造（829.6t）、橡塑（646.8t）等VOCs排放量较大.对比河南省省会郑州市、同为煤炭资源型城市焦作市,鹤壁市的VOCs排放总量是郑州市的1/11,焦作市的1/3.但鹤壁市单位面积的VOCs排放量较大,是郑州市的1/3,焦作市的1/2,且鹤壁市单位GDP的VOCs排放量与郑州市和焦作市非常接近.说明鹤壁市VOCs排放总量低,但排放强度较高,仍需要加大减排力度.根据本清单的研究结果,建议鹤壁市可着重加强工艺过程源和移动源的减排,重点减排区域为浚县、鹤山区和淇滨区的交汇地带,重点减排机动车、建材冶金、化学制品制造等;此外,还应关注橡塑、餐饮油烟、工业生物质锅炉等行业的VOCs排放.     

成都市城区大气VOCs季节污染特征及来源解析

为研究成都市城区大气VOCs季节变化特征,本研究在2018年12月至2019年11月对VOCs组分进行监测,并对VOCs的浓度水平、各化学组成、化学反应活性和来源进行分析.结果表明,成都市城区春、夏、秋和冬季VOCs的平均体积分数分别为32.29×10~(-9)、 36.25×10~(-9)、 40.92×10~(-9)和49.48×10~(-9),冬季的浓度明显高于其他季节,春季和夏季的浓度水平相差不大,各季节VOCs的组分浓度水平有所差异,冬季烷烃占总VOCs的比例最大,可能受机动车排放的影响较明显;夏季和秋季含氧(氮)挥发性有机物占比远高于春、冬季,一次源的挥发排放和二次转化的生成贡献较大;成都市城区不同季节大气中VOCs平均浓度排名靠前的关键组分基本无变化,主要是C_2～C_4的烷烃、乙烯、乙炔及二氯甲烷等,可能受机动车尾气、油气挥发、溶剂使用和LPG燃料等影响明显,夏季丙酮以及乙酸乙酯等含氧有机物浓度贡献突出;根据·OH消耗速率和OFP计算可知关键活性物种主要为间/对-二甲苯、乙烯、丙烯、1-己烯、甲苯、异戊烷和正丁烷等,这些物种应该优先减排和控制;四季VOCs源解析结果显示:春、夏季温度较秋、冬季高,光照更强,PMF明显解析出天然源和二次排放贡献,同时,由于夏季温度较高,解析出油气挥发占9%;秋、冬季占比增加的源主要为机动车尾气和燃烧源,燃烧源的排放占比在25%左右,另餐饮源的排放占比在9%左右.     

南京北郊VOCs对臭氧和二次有机气溶胶潜在贡献的研究

2013年3月1日~2014年2月28日采用GC5000在线气相色谱仪对南京北郊大气环境中的挥发性有机物(VOCs)进行了为期一年的连续监测,分析了VOCs的组成特征及季节、日变化规律,并结合PMF受体模型,采用最大增量反应活性(MIR)系数及气溶胶生成系数(FAC)分析了VOCs及其各来源的O3和SOA生成潜势.结果显示,南京北郊大气环境中TVOCs小时平均体积分数为45.63×10-9,TVOCs及各组分浓度呈现秋冬季高、夏季低的季节变化特征和双峰结构的日变化规律.SOA总生成量约为2.07μg/m3,芳香烃对其贡献率最大,占95.93%,其中的苯系物是生成SOA的优势物种;烯烃对OFP的贡献最大,接近65%;烷烃虽为VOCs的优势组分,却并非OFP和SOA的主要贡献者.不同季节VOCs的受体模型解析结果显示,工业排放和汽车尾气是南京北郊最主要的VOCs来源.富含苯系物的VOCs来源对SOA的贡献最大,对OFP贡献最大的则为富含乙、丙烯及异戊二烯的VOCs来源;春、秋、冬三季汽车尾气及工业排放(包括石化工业)二源对大气中的VOCs浓度、SOA的贡献及OFP的贡献影响最为显著,而夏季溶剂使用及植物源对SOA及OFP的贡献不容忽视.     

郑州市少数民族运动会期间O3及VOCs污染特征的演变和评估

基于近地面观测的常规污染六参数、气象数据和在线VOCs数据,以臭氧及其前体物VOCs为研究重点,评估了民运会期间采取的污染管控措施对郑州市空气质量的影响.结果表明,2019年民运会管控期间污染物六参数相较上年同期均呈现降低趋势,其中PM_2.5和PM₁₀浓度分别降低了16.2%和25.1%,但是臭氧日最大8 h浓度均值的降幅仅为3.7%,且臭氧为首要污染物的天数超过90%.就臭氧前体物VOCs而言,民运会期间PAMS浓度（26.21×10^-9）低于历史同期;利用PMF模型解析出6个因子,依次为机动车尾气（28%）、LPG（21%）、燃烧（16%）、工业（15%）、溶剂（15%）和植物排放（5%）;空气保障期间,对燃烧源和工业源的管控较为明显.     

天津市2017年移动源高时空分辨率排放清单

移动源已成为城市地区大气污染的主要贡献源.已有研究多关注道路移动源（机动车）或非道路移动源（工程机械、农业机械、船舶、铁路内燃机车和民航飞机）中单一源类的排放,欠缺对移动源总体排放特征的把握.本研究提出了移动源高时空分辨率排放清单的构建方法,据此建立了天津市2017年移动源排放清单,并分析其排放构成与时空特征.结果表明,天津市移动源CO、VOCs、NO_x和PM₁₀的排放量分别为18.30、6.42、14.99和0.84万t.道路移动源是CO和VOCs的主要贡献源,占比分别为85.38%和86.60%.非道路移动源是NO_x和PM₁₀的主要贡献源,占比分别为57.32%和66.95%.从时间变化来看,移动源所有污染物排放在2月均为最低,CO和VOCs在10月排放最高,而NO_x和PM₁₀则在8月排放最高.节假日（如春节和国庆节等）对移动源排放的时间变化影响显著.从空间分布来看,CO和VOCs排放主要集中于城区和车流量大的公路（高速路和国道）上,NO_x和PM₁₀在城区与港区均具有较高排放强度.污染物的空间分布差异是由其主要贡献源的空间位置决定的.本研究可为天津市大气污染的精细化管控和空气质量模拟提供数据支撑,同时可为其他地区移动源排放清单的建立提供方法参考.     

我国机动车排放VOCs及其大气环境影响

挥发性有机化合物(volatile organic compounds,VOCs)作为大气中主要污染物之一,是O3和二次有机气溶胶(secondary organic aerosol,SOA)的重要前体物.为全面了解我国城市机动车排放VOCs对空气质量的影响,本文系统介绍了我国部分城市大气中VOCs的源解析最新成果,并分车型、分燃料综述了我国机动车VOCs的排放因子、成分谱及其对二次污染的贡献,以期为未来机动车VOCs排放和控制提供数据和理论支持.研究发现,机动车是我国城市大气VOCs的最大源,平均贡献率为36.8%;摩托车和轻型汽油车是主要排放车型.机动车尾气排放VOCs对城市O3和SOA生成都有重要贡献,随着排放标准提升和运行工况改善,机动车排放因子和臭氧生成潜势(ozone formation potentials,OFPs)明显降低,成分谱以芳香烃和烯烃等活性组分为主,对二次污染的贡献较大.