典型城市臭氧污染源贡献及控制策略费效评估

东莞是珠三角O_3污染最严重的城市,使用RSM/CMAQ(曲面响应模型)法分析了珠三角区域人为排放的NO_x和VOCs对东莞市O_3浓度变化源贡献.2014基准年分析结果表明,扣除模型域外区域传输及天然源排放对O_3本底浓度贡献(41.00%)后,东莞本地VOCs排放对O_3贡献最大(18.50%),珠三角区域NO_x减排率13%时可持续降低东莞市O_3浓度.进一步使用ABa CAS-SE(空气污染控制成本效益与达标评估系统)对2017、2020、2025东莞市3个未来年O_3污染控制情景进行了费效评估.评估结果显示,NO_x和VOCs控制比例相对较低的2017年控制情景人体健康效益/区域控制成本比约为1.1;而控制比例相对较高的2025年东莞O_3达标情景效益成本比仅为0.1.这说明,在高减排率情景下,以末端治理为主的控制措施经济可行性较差,需综合采取产业/能源结构调整、清洁生产等措施实现NO_x和VOCs的大比例减排,实现东莞O_3的稳定达标.今后将进一步研究NO_x和VOCs减排对PM_(2.5)环境浓度及健康效益影响,开展多目标污染物协同控制费效评估.     

基于曲面响应建模的PM2.5可控人为源贡献解析

以东莞市PM_(2.5)重污染月份为例,使用强力法(Brute Force)和RSM/CMAQ曲面响应模型法分别解析了珠三角地区人为源排放对东莞PM_(2.5)的贡献,以及区域传输的可控人为源SO_2、NO_x和一次颗粒物(PM)在不同控制比例下(25%、50%、75%和100%)对东莞PM_(2.5)的累积浓度贡献.强力法研究结果表明,2014年1月珠三角地区人为源二次转化对东莞市PM_(2.5)的贡献(约58.10%)大于一次PM排放贡献(约41.90%),其中,人为源NH_3排放贡献最大,约占总量的21.66%.RSM/CMAQ动态源贡献结果显示,东莞市PM_(2.5)的人为可控源排放贡献(SO_2、NO_x和一次PM)占比为82.17%,受本地排放影响较大,且叠加区域排放的影响;一次PM减排对PM_(2.5)环境浓度的贡献高于仅减排SO_2和NO_x.在减排比例较低时,一次PM减排可有效削减东莞市PM_(2.5)浓度;随控制比例加大,二次前体物(SO_2和NO_x)减排对东莞市PM_(2.5)浓度削减率的影响加大.进一步使用HYSPLIT模式和轨迹聚类分析方法研究了2014年1月东莞市PM_(2.5)污染传输过程.结果显示,该时段共有6条长、短距离污染传输路径,污染物主要来自东莞市东、东北及东南方向,途经其上风向区域(惠州、深圳和广州等)传输至东莞;惠州是各主导上风向出现频率最高的城市,因而其区域传输对东莞PM_(2.5)的贡献也较大,深圳次之.     

常熟市大气污染特征、健康风险评价及潜在源分析

利用常熟市2018—2020年空气质量自动监测站点的常规大气污染物数据对空气质量及主要污染物变化特征进行分析,并利用大气污染与健康暴露评价模型分析常熟市近年来大气健康风险特征,同时结合HYSPLIT后向轨迹模型,综合运用轨迹聚类及PSCF分析方法,计算不同季节影响常熟市城区的主要气流输送路径及常熟市O₃的主要潜在源区。结果表明：2018—2020年,常熟市空气质量明显改善,AQI达标天逐年增多,中重度以上污染天呈明显减少趋势,SO₂、PM_2.5、NO₂、PM₁₀浓度均呈下降趋势,大气污染防治效果显著。PM_2.5与O₃仍是影响常熟市空气质量的主要因素,其中O₃对于空气质量影响逐年增强。PM_2.5季节变化特征明显,冬季浓度最高,夏季最低;O₃浓度春夏季较高,冬季最低。常熟市大气污染物的健康风险同污染物特征分布趋于一致,具有显著的时间分布特征。颗粒物对人体健康的相对风险值处于较低水平,呈逐年降低趋势;而O₃的健康风险威胁总体上高于颗粒物,且在近两年逐渐上升,夏季对人体健康威胁风险等级达适中级别,造成死亡率/发病率的相对风险增加3%—5.1%。后向轨迹聚类分析结果表明常熟市夏季受南与东南方向气流影响较大,二者在夏季总气流轨迹中的占比高达66.21%。潜在源分析结果表明,常熟地区对人体健康威胁较大的O₃潜在源区广泛,主要分布在江苏北部、安徽南部、浙江东部地区,同时还存在部分广东地区的远距离输送。     

南京地区一次臭氧污染过程的行业排放贡献研究

采用WRF-CHEM模式对南京地区春季一次臭氧(O_3)污染过程进行了模拟及行业排放贡献分析.此次O_3污染过程发生在2015年5月22—26日,南京地区一直处于地面高压控制的晴好天气之下,并于25日达到O_3污染的峰值.模拟与观测的一致性指数IOA达到0.89,表征本次O_3污染过程的模拟与观测结果的一致性较高.通过5类排放源(工业源、农业源、居住源、交通源、生物源)的敏感性试验,探究各行业排放源中O_3前体物对近地面O_3浓度的相对贡献.结果表明工业源在白天为持续正贡献,且在午后16:00时达到峰值,而交通源、居住源和农业源的贡献随气温的升高在白天由负贡献转为正贡献,并在18:00时左右达到峰值.在夜晚,O_3则主要通过交通源排放的大量NO进行滴定消耗.在高O_3浓度(≥200μg·m~(-3))时,各人为排放源均为正贡献,工业源的贡献最大,达到50μg·m~(-3),在低O_3浓度(200μg·m~(-3))时,交通源、居住源和农业源呈负贡献.生物源在人为排放源主导的南京城区O_3污染过程中的贡献几乎为零.考虑到O_3生成机制的复杂性,对于南京地区,减少工业源排放是控制O_3污染的关键.     

成都市典型有机溶剂使用行业VOCs组成成分谱及臭氧生成潜势研究

选取成都市5大典型有机溶剂使用行业——包装印刷业、人造板制造业、家具制造业、制鞋业和化学品制造业具有代表性的15家企业测定挥发性有机物(VOCs)排放组分,并对其不同组分的臭氧生成潜势(OFP)进行分析.研究结果表明:不同行业排放的VOCs之间存在较大差异,包装印刷业和人造板制造业主要排放含氧VOCs(OVOCs),家具制造业主要排放芳香烃和OVOCs,制鞋业和化学品制造业主要排放OVOCs、芳香烃和烷烃;芳香烃是化学反应活性最强的组分,对臭氧的生成贡献普遍较大,其中贡献最大的邻二甲苯及间二甲苯的OFP值分别为92.13 mg·m~(-3)和89.65 mg·m~(-3),二者占总OFP的40%;五大典型有机溶剂使用行业中,家具制造业对O_3生成的贡献最大,OFP贡献率为34.59%.     

Ambient volatile organic compounds pollution in China

Owing to rapid economic and industrial development, China has been suffering from degraded air quality and visibility. Volatile organic compounds (VOCs) are important precursors to the formation of ground-level ozone and hence photochemical smog. Some VOCs adversely affect human health. Therefore, VOCs have recently elicited public concern and given new impetus to scientific interest. China is now implementing a series of polices to control VOCs pollution. The key to formulating policy is understanding the ambient VOCs pollution status. This paper mainly analyzes the species, levels, sources, and spatial distributions of VOCs in ambient air. The results show that the concentrations of ambient VOCs in China are much higher than those of developed countries such as the United States and Japan, especial benzene, which exceeds available standards. At the same time, the ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP) of various VOCs are calculated. Aromatics and alkenes have much higher OFPs, while aromatics have higher SOAFP. The OFPs of ambient VOCs in the cities of Beijing, Guangzhou and Changchun are very high, and the SOAFP of ambient VOCs in the cities of Hangzhou, Guangzhou and Changchun are higher.     

合肥市O3污染时空变化特征及影响因素分析

为掌握合肥市大气环境中O_3的时空变化特征及其影响因素,对合肥市2013—2015年空气质量监测数据和气象参数进行系统的分析.结果表明,合肥市O_3污染在夏、秋季节有逐渐加重的趋势,尤其是城市中心区域,呈显著的季节特征和日单峰性;O_3易在风速小于3.3 m·s-1、相对湿度介于50%~60%、地面气压低于1020 h Pa和日平均气温介于25~28℃的气象条件下出现浓度峰值;合肥市O_3浓度与NO2和VOCs分别存在显著的负相关和正相关关系,其中,烯烃、烷烃、芳香烃和炔烃对O_3生成潜势(OFP)的贡献值依次增大.O_3浓度可通过前一日O_3浓度、相对湿度、平均气温、PM2.5、当日8:00风速、平均气压及NO2等参数建立良好的统计预报模型,非标准化可决系数R2高达0.559.     

Uncertainty analysis of emission estimates in the RAINS integrated assessment model

Uncertainty is a critical issue for all models that attempt to quantify the necessary emission reductions that are required to meet environmental quality targets. This paper discusses a methodology specifically developed to analyse the uncertainties in the emission estimates with the regional air pollution information and simulation (RAINS) integrated assessment model, considering the uncertainties in the model parameters themselves. Overall, it was found that a typical range of uncertainties for modeled national emissions of sulfur dioxide, nitrogen oxides and ammonia in Europe lies between 10 and 30%. In general, the uncertainties are strongly dependent on the potential for error compensation. This compensation potential is larger (and uncertainties are smaller) if calculated emissions are composed of a larger number of equal-sized source categories, where the errors in input parameters are not correlated with each other. Thus, estimates of the national total emissions are generally more certain than estimates of sectoral emissions. A sensitivity analysis with respect to the uncertainty in input parameters showed that the actual uncertainties are critically influenced by the specific situation (pollutant, year, country). However, the emission factor is an important contributor to the uncertainty in estimates of historical emissions, while uncertainty in the activity data dominates the future estimates.     

北京地区SO2、NOx、O3和PM2.5变化特征的城郊对比分析

2006-01-01～2006-12-31在北京上甸子区域大气本底站和城区宝联环境观测站连续观测了SO2、NOx、O3和PM2.5的浓度,分析了北京城区和郊区的季节变化及日变化的差异,并结合风向讨论了城区污染对于大气本底的影响.结果表明,①NOx、SO2浓度在采暖季城郊差异最大,城区是本底的4～6倍,城郊O3有一致的浓度变化.本底站PM2.5在4、5月达到100μg/m3以上,是年平均的2～3倍;②NOx和SO2的日变化在城区表现为双峰型,在09:00前后和22:00前后形成高值,郊区表现为单峰型,在22:00前后出现高值.郊区O3的日变化峰值滞后于城区大约2 h.PM2.5日变化规律表现得较不规则;③西南风条件下本底各污染物浓度明显受城区输送影响而升高,东北风条件下干洁气团的影响比较明显.     

Size distribution, directional source contributions and pollution status of PM from Chengdu, China during a long-term sampling campaign

Long-term and synchronous monitoring of PM₁₀ and PM_2.5 was conducted in Chengdu in China from 2007 to 2013. The levels, variations, compositions and size distributions were investigated. The sources were quantified by two-way and three-way receptor models (PMF2, ME2-2way and ME2-3way). Consistent results were found: the primary source categories contributed 63.4% (PMF2), 64.8% (ME2-2way) and 66.8% (ME2-3way) to PM₁₀, and contributed 60.9% (PMF2), 65.5% (ME2-2way) and 61.0% (ME2-3way) to PM_2.5. Secondary sources contributed 31.8% (PMF2), 32.9% (ME2-2way) and 31.7% (ME2-3way) to PM₁₀, and 35.0% (PMF2), 33.8% (ME2-2way) and 36.0% (ME2-3way) to PM_2.5. The size distribution of source categories was estimated better by the ME2-3way method. The three-way model can simultaneously consider chemical species, temporal variability and PM sizes, while a two-way model independently computes datasets of different sizes. A method called source directional apportionment (SDA) was employed to quantify the contributions from various directions for each source category. Crustal dust from east-north-east (ENE) contributed the highest to both PM₁₀ (12.7%) and PM_2.5 (9.7%) in Chengdu, followed by the crustal dust from south-east (SE) for PM₁₀ (9.8%) and secondary nitrate & secondary organic carbon from ENE for PM_2.5 (9.6%). Source contributions from different directions are associated with meteorological conditions, source locations and emission patterns during the sampling period. These findings and methods provide useful tools to better understand PM pollution status and to develop effective pollution control strategies.     

PM2.5 source apportionment in a French urban coastal site under steelworks emission influences using constrained non-negative matrix factorization receptor model

The constrained weighted-non-negative matrix factorization(CW-NMF) hybrid receptor model was applied to study the influence of steelmaking activities on PM_(2.5)(particulate matter with equivalent aerodynamic diameter less than 2.5 μm) composition in Dunkerque,Northern France. Semi-diurnal PM_(2.5)samples were collected using a high volume sampler in winter 2010 and spring 2011 and were analyzed for trace metals, water-soluble ions, and total carbon using inductively coupled plasma – atomic emission spectrometry(ICP-AES),ICP- mass spectrometry(ICP-MS), ionic chromatography and micro elemental carbon analyzer. The elemental composition shows that NO_3~-, SO_4~(2-), NH_4~+and total carbon are the main PM_(2.5)constituents. Trace metals data were interpreted using concentration roses and both influences of integrated steelworks and electric steel plant were evidenced. The distinction between the two sources is made possible by the use Zn/Fe and Zn/Mn diagnostic ratios. Moreover Rb/Cr, Pb/Cr and Cu/Cd combination ratio are proposed to distinguish the ISW-sintering stack from the ISW-fugitive emissions. The a priori knowledge on the influencing source was introduced in the CW-NMF to guide the calculation. Eleven source profiles with various contributions were identified: 8 are characteristics of coastal urban background site profiles and 3 are related to the steelmaking activities. Between them,secondary nitrates, secondary sulfates and combustion profiles give the highest contributions and account for 93% of the PM_(2.5)concentration. The steelwork facilities contribute in about 2%of the total PM_(2.5)concentration and appear to be the main source of Cr, Cu, Fe, Mn, Zn.     

基于响应曲面法的臭氧生成敏感性分析

准确判断臭氧(O₃)生成敏感性对O₃污染成因分析和防控对策的制定至关重要.首次利用响应曲面方法设计最优试验方案,基于盒子模式模拟结果,快速量化O₃对其前体物变化的响应.结果表明,CO对O₃有正贡献,NO_x和VOCs与O₃呈现显著非线性关系,当φ(VOCs)与[φ(NO_x)-13.75]比值大于4.17时,为NO_x控制区,小于4.17时,为VOCs控制区;烯烃为影响O₃生成的关键VOCs组分,当φ(烯烃)与[φ(NO_x)-15]比值小于1.10且φ(烯烃)<35×10^-9时,烯烃有利于O₃的生成.响应曲面法在多因素和其交互作用对O₃生成影响的研究中取得了良好效果,为高效判断O₃敏感性提供了新的思路和方法.     

成都市一次典型空气重污染过程特征及成因分析

为了研究成都市冬季空气重污染过程的成因,以2015年12月26日—2016年1月6日成都市一次典型重污染天气过程为例,基于HYSPLIT后向轨迹模式结合全球资料同化系统(Global Data Assimilation System,GDAS)气象数据和成都市7个监测站的AQI、PM_(2.5)、PM10、NO2质量浓度数据,使用气象分析、轨迹聚类(Cluster Analysis)、潜在源贡献因子法(Potential Source Contribution Function,PSCF)和浓度权重轨迹法(Concentration Weighted Trajectory,CWT),分析了此次过程的气象特征、轨迹输送特征和污染物潜在来源分布.结果表明,此次污染天气过程是以PM_(2.5)为主要污染物,其次为PM10、NO2.2015年12月30日14:00左右是此次污染天气过程各站点PM_(2.5)、PM10浓度到达峰值的时刻.缺少北方冷空气南下,四川盆地内空气水平运动弱,以及扩散条件差的静稳天气形势是导致此次大气污染过程成都市污染物累积的原因,而冷空气活动是改善这种天气形势的关键.污染过程辐射逆温层的形成对当时污染物浓度增长有促进作用,但随着每日生消、加强减弱,其并不是最终导致重污染天气形成的关键因素.川东北的广元、绵阳、德阳等地区和成都本地及其南向的眉山、雅安等地区是此次过程主要的潜在源区,这些地区人口较密集,工业较发达,且沿地形走向而分布.     

Identification and elucidation of anthropogenic source contribution in PM10 pollutant: Insight gain from dispersion and receptor models

Source apportionment study of PM₁₀ (Particulate Matter) in a critically polluted area of Jharia coalfield, India has been carried out using Dispersion model, Principle Component Analysis (PCA) and Chemical Mass Balance (CMB) techniques. Dispersion model Atmospheric Dispersion Model (AERMOD) was introduced to simplify the complexity of sources in Jharia coalfield. PCA and CMB analysis indicates that monitoring stations near the mining area were mainly affected by the emission from open coal mining and its associated activities such as coal transportation, loading and unloading of coal. Mine fire emission also contributed a considerable amount of particulate matters in monitoring stations. Locations in the city area were mostly affected by vehicular, Liquid Petroleum Gas (LPG) & Diesel Generator (DG) set emissions, residential, and commercial activities. The experimental data sampling and their analysis could aid understanding how dispersion based model technique along with receptor model based concept can be strategically used for quantitative analysis of Natural and Anthropogenic sources of PM₁₀.     

植物叶表尘及重金属对城市大气颗粒物污染的指示与评估

城市大气颗粒物污染问题日渐突出,目前主要依靠大气站点的直接观测数据反映污染的即时状况,而植物叶表尘及重金属的监测为评价大气颗粒物阶段性污染状况提供了新的途径.本研究通过分析北京交通带和公园共7个样点的臭椿(Ailanthus altissima)、槐(Sophora japonica)、北京杨(Populus beijingensis)、榆树(Ulmus pumila)、紫叶李(Prunus cerasifera f.atropurpurea)等5种常见绿化树种的叶表尘及重金属Cd、Cr、Cu、Mn、Ni、Pb、Zn含量,并计算尘金属综合累积指数(MAI),进而与邻近站点大气颗粒物观测数据对比并进行统计分析,尝试量化评价植物所处环境的大气颗粒物及尘重金属综合污染状况.结果表明:采用榆树叶表尘可量化评价大气可吸入颗粒物PM10的月均质量浓度,相对误差为1.2%~10.6%;臭椿叶表尘可量化评价大气细颗粒物PM2.5的月均质量浓度和月均空气质量指数(AQI),相对误差分别为0.18%~3.7%和0.26%~5.7%.MAI值可指示大气尘重金属综合污染状况,本研究中京承高速和朝阳公园大气尘重金属综合污染较重,其次为念坛公园、望京公园和玉蜓桥,最轻为岳各庄桥和麋鹿苑.     

Synergistic impacts of anthropogenic and biogenic emissions on summer surface O3 in East Asia

A factor separation technique and an improved regional air quality model (RAQM) were applied to calculate synergistic contributions of anthropogenic volatile organic compounds (AVOCs),biogenic volatile organic compounds (BVOCs) and nitrogen oxides (NOx) to daily maximum surface O3(O3DM) concentrations in East Asia in summer (June to August 2000).The summer averaged synergistic impacts of AVOCs and NOx are dominant in most areas of North China,with a maximum of 60 ppbv,while those of BVOCs and NOx are notable only in some limited areas with high BVOC emissions in South China,with a maximum of 25 ppbv.This result implies that BVOCs contribute much less to summer averaged O3DM concentrations than AVOCs in most areas of East Asia at a coarse spatial resolution (1×1) although global emissions of BVOCs are much greater than those of AVOCs.Daily maximum total contributions of BVOCs can approach 20 ppbv in North China,but they can reach 40 ppbv in South China,approaching or exceeding those in some developed countries in Europe and North America.BVOC emissions in such special areas should be considered when O3 control measures are taken.Synergistic contributions among AVOCs,BVOCs and NOx significantly enhance O3 concentrations in the Beijing-Tianjin-Tangshan region and decrease them in some areas in South China.Thus,the total contributions of BVOCs to O3DM vary significantly from day to day and from location to location.This result suggests that O3 control measures obtained from episodic studies could be limited for long-term applications.     

A case study of development and application of a streamlined control and response modeling system for PM2.5 attainment assessment in China

This article describes the development and application of a streamlined air control and response modeling system with a novel response surface modeling-linear coupled fitting method and a new module to provide streamlined model data for PM_(2.5) attainment assessment in China.This method is capable of significantly reducing the dimensions required to establish a response surface model,as well as capturing more realistic response of PM_(2.5) to emission changes with a limited number of model simulations.The newly developed module establishes a data link between the system and the Software for Model Attainment Test—Community Edition(SMAT-CE),and has the ability to rapidly provide model responses to emission control scenarios for SMAT-CE using a simple interface.The performance of this streamlined system is demonstrated through a case study of the Yangtze River Delta(YRD) in China.Our results show that this system is capable of reproducing the Community Multi-Scale Air Quality(CMAQ) model simulation results with maximum mean normalized error 3.5%.It is also demonstrated that primary emissions make a major contribution to ambient levels of PM_(2.5) in January and August(e.g.,more than50%contributed by primary emissions in Shanghai),and Shanghai needs to have regional emission control both locally and in its neighboring provinces to meet China's annual PM_(2.5)National Ambient Air Quality Standard.The streamlined system provides a real-time control/response assessment to identify the contributions of major emission sources to ambient PM_(2.5)(and potentially O_3 as well) and streamline air quality data for SMAT-CE to perform attainment assessments.     

廊坊市夏季臭氧体积分数影响因素及生成敏感性

基于廊坊市夏季近地面O_3体积分数及其前体物VOCs和NO_x体积分数数据,结合气温、风速风向、总云量和太阳辐射强度等气象资料,分析了O_3体积分数的日变化规律以及气象因素对其的影响;利用VOCs/NO_x比值法和EKMA曲线法分析了O_3的生成敏感性.结果表明:(1)廊坊市夏季O_3生成速率及其体积分数与太阳辐射强度为显著正相关,皮尔森相关系数r分别为0.61和0.48,其中O_3生成速率和太阳辐射强度都在12:00左右达到峰值,而O_3体积分数在16:00达到峰值,滞后太阳辐射强度峰值4 h;(2)O_3生成速率及其体积分数与气温呈正相关,皮尔森相关系数分别为0.44和0.68;与总云量呈负相关,皮尔森相关系数分别为-0.24和-0.45;(3)风向为偏西风、偏南风或东南风时,廊坊市夏季O_3体积分数易出现高值;(4)廊坊市夏季整体处于VOCs控制区,O_3体积分数的最优控制措施为短期内优先削减VOCs,中长期协同减排NO_x和VOCs.     

石家庄市臭氧污染的时空演变格局和潜在源区

基于石家庄市46个国控、省控环境自动监测站在2019年4—10月的大气O₃-8 h和O₃-1 h浓度数据,在对其进行反距离加权插值(IDW)的基础上,分析了石家庄市域5—9月O₃浓度月度和时域空间演变格局,并结合全球资料同化系统(GDAS)气象资料和大气污染物数据(PM_2.5、NO₂、PM₁₀、SO₂及CO),进行了空间自相关和后向轨迹分析,探讨了石家庄市O₃污染的空间积聚特征和潜在源区分布.结果表明:(1)石家庄市域大气O₃稳定程度较低,5—9月变动呈以6月为峰值的单峰型态势,时域变化呈以15:00—16:00为峰值的单峰型趋势;(2)5—9月O₃浓度为207～260μg·m^-3,呈中西部高、外围区域低的空间格局;O₃质量浓度在0:00—6:00呈西北至东南向降幅逐渐增加的趋势,在6:00—12:00和12:00—15:00...     

重庆市典型城区PM2.5含碳气溶胶季节变化和来源解析

于2015年10月、12月和2016年3月、8月在重庆大学A区采集秋、冬、春、夏4个季节PM_2.5样品,观察其微观形貌,分析含碳气溶胶及其碳组分的浓度水平,并探讨其季节变化及进行来源解析.结果表明,重庆沙坪坝区PM_2.5中有机碳（OC）、元素碳（EC）、烟灰（char）和烟炱（soot）的年均质量浓度分别为20.66、6.16、5.42和0.74 μg·m^-3.OC季节变化显著,冬季最高,夏季最低;EC秋季最高,冬季最低,但与其它季节相差不大;char表现为秋季 > 春季 > 冬季 > 夏季;soot表现为秋季 > 夏季 > 春季 > 冬季.正定矩阵因子（PMF）解析出3个因子,分别代表生物质/煤燃烧和道路扬尘的混合源（52.7%）、汽油机动车排放源（22.9%）和柴油机动车排放源（24.4%）.机动车尾气是秋、春和夏3个季节含碳气溶胶的主要来源,冬季主要受煤炭/生物质燃烧和道路扬尘混合源的影响.秋季污染事件可能是因为本地及周边城市汽油车通行量增加,冬季污染事件可能是本地煤炭/生物质燃烧排放增加和周边农村地区输入的共同作用,春季污染事件可能与来自西北方向的沙尘长距离传输有关.