济南市环境空气VOCs污染特征及来源识别

对济南市2010年6月至2012年5月环境空气中56种挥发性有机污染物(VOCs)进行在线气相色谱监测,研究其污染特征并识别其主要来源。结果表明,该期间总挥发性有机化合物(TVOCs)变化规律基本一致,其平均浓度水平夏季冬季秋季春季;TVOCs浓度的日变化趋势呈双峰分布,与早晚交通高峰相吻合;济南市城区环境空气中VOCs的主要物种是C3~C5的烷烃、丙烯、顺-2-丁烯、甲苯和间、对二甲苯等;不同季节环境空气中VOCs的主要物种基本一致,夏季烯烃所占比重高于其他季节;烷烃、烯烃与TVOCs的浓度日变化趋势相似,呈明显的双峰状,而芳香烃浓度日变化规律双峰特征不明显。济南市城区VOCs的主要来源为汽车尾气、工业源、燃烧源。     

郑州市环境空气中挥发性有机物的组成及分布特点

初步探查研究了郑州市不同功能区环境空气中挥发性有机物(VOCs)的种类组成及TVOC和苯系物浓度分布特点,共检测出221种VOCs.交通密集区VOCs污染较重,汽车尾气是目前VOCs主要来源.     

菏泽市环境空气中VOCs污染特征研究

为研究菏泽市环境空气中VOCs的污染特征,参照EPA TO-15方法对菏泽市环境空气中的VOCs进行分析,并对VOCs的组成、浓度状况、来源和对臭氧生成潜势的贡献等进行探讨。结果表明,该市环境空气中共定性检出挥发性有机物82种,其中烷烃和苯系物分别占有机物种类的29%、22%,VOCs平均浓度为25.6μg/m3。监测期间,环境空气中的VOCs主要来自汽车尾气排放、汽油蒸汽、液态石油的挥发,其中交通尾气排放是该区域监测期间的主要排放源。烷烃、芳烃是对菏泽市环境空气中臭氧生成潜势贡献较大的关键活性组分,其对臭氧生产潜势的贡献率分别为32.6%、49.9%。     

基于城市大气挥发性有机物特征分析的数据质量评估方法及案例

城市大气挥发性有机物(VOCs)监测是空气质量监测网的重要组成部分,而数据质量控制和质量保证是VOCs监测的基础。基于8次中国城市大气VOCs外场监测,通过挖掘VOCs浓度、组成和化学活性的内在规律,对VOCs监测数据质量进行评估并总结方法。分析结果显示:城市大气乙烷和苯等长寿命组分具有明显的背景浓度,且区域背景值较为接近,可以用来诊断长寿命VOCs组分浓度异常偏低或偏高现象。而示踪组分的季节(日)变化规律可以用来识别VOCs组分定性问题(如夏季大气异戊二烯和烷基硝酸酯浓度日变化规律应反映植被排放和光化学反应特征)。另外,在气团混合均匀的情况下,VOCs浓度波动与其活性之间存在负相关,这一规律可以用来核查数据准确性或局地源影响。     

天津市大气中挥发性有机物的组成及分布特点

参照美国EPA TO17的方法研究天津市不同功能区大气中挥发性有机物(VOCs)冬夏季中的组成及浓度水平,共检出62种挥发性有机物,冬季VOCs浓度水平低于夏季;苯系物稳定存在于各功能区且所占比例最高;VOCs的主要来源是机动车尾气。     

泰州市夏季大气典型VOCs污染特征及健康风险评估

于2019年8—9月,采用大气预浓缩-气相色谱质谱联用仪(GC-MS)对泰州市3个监测点位环境空气中57种挥发性有机物(VOCs)进行分析,并开展了VOCs组成特征、臭氧生成潜势(OFP)、VOCs来源及健康风险评价研究。结果表明:3个点位环境空气中φ(VOCs)范围为1.3×10^(-9)~46.9×10^(-9),平均值为8.5×10^(-9)。烷烃在VOCs中所占比例最大。各点位φ(VOCs)平均值依次为:工业园区>公园路>天德湖公园。公园路点位VOCs中苯系物受汽车尾气排放影响较大,天德湖公园和工业园区点位除了受汽车尾气排放影响,还受到有机溶剂和涂料的挥发影响,主要受本地污染主导。OFP中贡献最大的物质为乙烯,OFP值为5.5μg/m^(3),其次为烷烃。健康风险评价结果显示,各点位VOCs非致癌类风险均较低,处于安全范围内。各点位夏季环境空气中苯对人体均具有一定致癌风险。     

北仑区域噪声自动监测的适用性研究

对北仑区域内的三套噪声自动监测点位从数据的准确性和代表性两方面进行了探讨,并提出了存在的问题和改进的建议。     

青岛市环境空气中VOCs的污染特征及化学反应活性

利用2012年青岛市挥发性有机物(VOCs)监测数据,系统分析了VOCs的污染特征、来源和化学反应活性。结果表明,青岛市VOCs浓度处于较低水平,且烷烃是VOCs的主要组分,占60%以上。夏、秋季的VOCs浓度高于春、冬季,且9月的浓度高于其他月份,日变化呈现"两峰一谷"趋势,与交通早晚高峰对应。VOCs各组分均表现出周末效应,说明机动车源和工业源的重要影响,优势物种的相关性分析进一步证明了这一点。对比各组分的OH消耗速率,得出烯烃的臭氧生成贡献高于烷烃和芳香烃,控制机动车尾气、溶剂挥发、化石工业等VOCs排放源将有利于降低大气中的臭氧浓度。     

嘉善夏季典型时段大气VOCs的臭氧生成潜势及来源解析

2016年8—9月对长三角南部区域嘉善的大气中挥发性有机化合物(VOCs)变化特征、臭氧生成潜势、臭氧生成控制敏感性和来源进行了研究。结果表明,观测期间VOCs总平均值为27.3×10-9,表现为烷烃卤代烃含氧有机物芳香烃烯烃炔烃;VOCs浓度变化较大,早晚出现峰值,与风速呈负相关的关系,与温度没有明显相关性。VOCs的臭氧生成潜势表现为芳香烃烯烃烷烃含氧有机物卤代烃炔烃。甲苯等10种物质对臭氧生成潜势的贡献达到63%。夏季典型时段臭氧生成对VOCs较敏感,属于VOCs控制区。观测期间测得对VOCs浓度贡献较大的物种来源于溶剂涂料和工业排放。     

成渝地区典型中小城市VOCs污染特征、臭氧生成潜势及来源分析

为了解成渝地区中小城市VOCs污染特征及其来源，选取该区域典型代表城市-遂宁市为研究对象，利用2019年不同时间不同功能区106种VOCs离线观测数据，研究了该市VOCs污染水平和时空特征，分析了VOCs主要成分及其对臭氧的影响，并进行了源解析。结果显示：(1)遂宁市大气中VOCs平均体积分数为39.4×10^-9,8月的浓度较高，其空间排序为工业区>城郊区≈文教区。(2)OVOCs和烷烃是VOCs主要组分，占比达73.4%,且不受时间和空间限制；工业区不同组分浓度均高于城郊区和文教区，城郊区和文教区的同组分占比相差较小；丙酮和乙烷是VOCs中体积分数最大的物种，占总体积分数的37.8%。(3)VOCs组分对OFP贡献率顺序为烯烃>芳香烃>OVOCs>烷烃>炔烃>卤代烃>有机硫，前4类组分对OFP贡献率达97.6%,烯烃对OFP贡献率不仅每日最大，而且还呈现“城郊区>文教区>工业区”空间分布态势；异戊二烯、乙烯是OFP最大的物种，在不同功能区其OFP均高于其他物种，是遂宁市臭氧防治关注重点。(4)VOCs排放源及...     

Characterizations of volatile organic compounds during high ozone episodes in Beijing,China

Air samples were collected in Beijing from June through August 2008, and concentrations of volatile organic compounds (VOCs) in those samples are here discussed. This sampling was performed to increase understanding of the distributions of their compositions, illustrate the overall characteristics of different classes of VOCs, assess the ages of air masses, and apportion sources of VOCs using principal compound analysis/absolute principal component scores (PCA/APCS). During the sampling periods, the relative abundance of the four classes of VOCs as determined by the concentration-based method was different from that determined by the reactivity approach. Alkanes were found to be most abundant (44.3–50.1%) by the concentration-based method, but aromatic compounds were most abundant (38.2–44.5%) by the reactivity approach. Aromatics and alkenes contributed most (73–84%) to the ozone formation potential. Toluene was the most abundant compound (11.8–12.7%) during every sampling period. When the maximum incremental reactivity approach was used, propene, toluene, m,p-xylene, 1-butene, and 1,2,4-trimethylbenzene were the five most abundant compounds during two sampling periods. X/B, T/B, and E/B ratios in this study were lower than those found in other cities, possibly due to the aging of the air mass at this site. Four components were extracted from application of PCA to the data. It was found that the contribution of vehicle exhaust to total VOCs accounted for 53% of VOCs, while emissions due to the solvent use contributed 33% of the total VOCs. Industrial sources contributed 3% and biogenic sources contributed 11%. The results showed that vehicle exhausts (i.e., unburned vehicle emissions + vehicle internal engine combustion) were dominant in VOC emissions during the experimental period. The solvent use made the second most significant contribution to ambient VOCs.     

南通市夏季VOCs污染特征与来源研究

运用大气挥发性有机物(VOCs)快速在线连续自动监测系统,于2018年7月对南通市区环境空气中VOCs进行观测,分析VOCs的浓度状况、组成特征、对臭氧生成潜势的贡献及主要来源。结果表明:观测期间共检出100种VOCs,总挥发性有机物(TVOCs)的平均体积分数为(38. 18±23. 63)×10^-9,各物种体积分数从大到小顺序依次为烷烃>含氧有机物>芳香烃>卤代烃>烯、炔烃;芳烃和烯烃是最主要的活性物种,间/对二甲苯、甲苯、邻二甲苯等是VOCs的关键活性组分;利用PMF模型解析得到VOCs的主要污染来源是工业排放与溶剂使用、机动车尾气排放、燃料挥发排放和生物源排放。     

Characterization of Volatile Organic Compounds (VOCs) and Their Sources in the Air of Izmir, Turkey

Air samples were collected in Izmir, Turkey at two (suburban and urban) sites during three sampling programs in 2002 and 2004 to determine the ambient concentrations of several monoaromatic, chlorinated and oxygenated volatile organic compounds (VOCs). Samples were analyzed for 60 VOCs using gas chromatography/mass spectrometry and 28 compounds were detected in most samples. On the average, urban air VOC concentrations were about four times higher than those measured at the suburban site. Toluene (40.6%) was the most abundant compound in suburban site and was followed by benzene (7.4%), o,m-xylene (6.5%), and 1,2-dichloroethane (5.1%). In urban site, toluene (30.5%), p-xylene (14.9%), o,m-xylene (11.4%), and ethyl benzene (7.2%) were the dominating compounds in summer. In winter, toluene (31.1%), benzene (23.9%), 1,2-dichloroethane (9.5%), and o,m-xylene (8.2%) were the most abundant compounds. Receptor modeling (positive matrix factorization) has been performed to estimate the contribution of specific source types to ambient concentrations. Six source factors (gasoline vehicle exhaust, diesel vehicle exhaust+residential heating, paint production/application, degreasing, dry cleaning, and an undefined source) were extracted from the samples collected in the urban site. Three source factors (gasoline vehicle exhaust, diesel vehicle exhaust, and paint production/application) were identified for the suburban site.     

杭州市大气污染物排放清单及特征

以杭州市区为研究区域,通过调查整合多套污染源数据库及其他统计资料,研究文献报道及模型计算的各种污染源排放因子,获得杭州市区各行业PM10、PM2.5、SO2、NOx、CO、VOCs、NH3等污染物的排放量,建立了杭州市区2010年1 km×1 km大气污染物排放清单。结果表明,2010年杭州市区PM10、PM2.5、SO2、NOx、CO、VOCs和NH3的排放总量分别为7.96×104、4.02×104、7.23×104、8.98×104、73.90×104、39.56×104、3.32×104t。从排放源的行业分布来看,机动车尾气排放是杭州市区大气污染物最重要排放源之一,对PM10、PM2.5、NOx、CO和VOCs的贡献分别达到14.4%、27.1%、40.3%、21.4%、31.1%。道路扬尘、电厂锅炉、工业炉窑、植被、畜禽养殖对不同污染物分别有着重要贡献,道路扬尘对PM10和PM2.5的贡献分别为44.6%和20.0%、电厂锅炉对SO2和NOx的贡献分别为37.0%和25.7%、工业炉窑对CO的贡献为41.5%、植被排放对VOCs的贡献为27.1%、畜禽养殖对NH3的贡献为76.5%。从空间分布来看,萧山区和余杭区对SO2、NH3和植被排放BVOC的贡献要显著高于主城区;而主城区机动车对PM2.5、NOx和VOCs的贡献分别达到36.3%、56.0%和47.4%,较市区范围内显著增加,表明机动车尾气排放已成为杭州主城区大气污染最重要的来源之一。     

VOCs走航观测在城市污染源排查中的应用

为推进城市空气质量精细化管理工作的实施,实现VOCs污染源精准排查,2019年3-4月,利用单光子电离飞行时间质谱对青岛市重点区域进行了VOCs走航观测。在排查到的污染源中,工业区的VOCs浓度较生活区整体偏高,且生活区、工业区夜间的VOCs浓度均较白天高。VOCs各类组分中,生活区白天苯系物、卤代烃、烯烃、烷烃的占比均在20%左右,夜间苯系物占比明显升高;工业区苯系物在白天和夜间的占比均最高,其他组分相对较小。浓度较高的前10位VOCs物种中,生活区白天烯烃物种占主导,夜间烷烃物种的比重明显增加;工业区苯系物、烯烃物种在白天和夜间的比重均较大,烷烃物种较小。生活区VOCs的污染源主要为机动车尾气排放和油品挥发,工业区主要为企业排放。烯烃和苯系物臭氧生成贡献较烷烃高,特别是丁烯、戊烯、己烯、甲苯、二甲苯/乙苯、三甲苯贡献显著,建议作为优控物种重点管控。     

A combined analysis to identify airborne PM10 sources

A two step procedure that combines an air dispersion model with a receptor model was used to identify the key sources that contribute to air levels of suspended particulate matter. The contribution to PM(10) concentrations measured at four monitoring sites in San Nicolas, Argentina, of the following sources, a thermal power plant, an integrated steel mill, motor vehicle exhaust fumes, and finally dust from paved and unpaved roads, have been analysed. Moreover, an air dispersion model was used to estimate the contribution of the thermal power plant, emissions of which have been described in depth by means of hourly fuel consumption and specific emission factors. The ratio "apportionment coefficient" was introduced to relate the contribution of this source to the measured 24 h PM(10) concentrations by analysing the frequency of occurrence of connecting winds between the power plant and each monitoring site. In San Nicolas 70% of the PM(10) sampled at three of the four monitoring sites could be attributed to the power plant in those scenarios where winds connected the facility's tall point sources with the sampling locations. The contribution to the measured PM(10) levels of the rest of the sources that are present in the analysed area was confirmed by way of receptor models. For this purpose, the multielemental composition of 41 samples was determined by Wavelength Dispersive X-ray Fluorescence analysis. In order to ascertain the underlying correlations between PM(10) samples and potential sources, Principal Component Analysis was performed on the standard matrix of composition profiles, which comprises the measured PM(10) samples being enlarged with the composition profiles of the potential contributing sources. The diagonalization of the covariance matrix was used as a screening procedure to differentiate the most likely contributing sources from those that were not significant.     

大连市秋冬季环境空气中VOCs特征及臭氧生成潜势分析

对大连市2015年秋冬季环境空气中VOCs进行采样分析,获得其组成、含量、昼夜和季节变化规律,分析不同类别VOCs的来源,并计算不同VOCs物种的臭氧生成潜势（OFP）。结果表明：大连市环境空气中秋季VOCs平均体积浓度（55.81×10^-9）略高于冬季（42.66×10^-9）;秋季VOCs以羰基化合物和烷烃为主,而冬季VOCs以烷烃和烯炔烃为主。大连环境空气中光化学反应的主要VOCs类别为羰基化合物、烯炔烃和芳香烃,主要物种为丙烷、乙烷、正丁烷和乙烯。羰基化合物含量高与机动车尾气及医院大量试剂的使用有关,烷烃主要来源于汽油车与液化石油气（LPG）燃烧排放,芳香烃主要由机动车排放贡献。各类别VOCs的组分含量与其OFP并不一致,大连市环境空气中各类VOCs的OFP由高到低依次为羰基化合物>芳香烃>烯炔烃>烷烃。     

Location and Characterization of Emission Sources for Airborne Volatile Organic Compounds Inside a Refinery in Taiwan

This study aimed to locate VOC emission sources and characterized their emitted VOCs. To avoid interferences from vehicle exhaust, all sampling sites were positioned inside the refinery. Samples, taken with canisters, were analyzed by GC–MS according to TO-14 method. The survey period extended from Febrary 2004 to December 2004, sampling twice per season. To interpret a large number of VOC data was a rather difficult task. This study featured using ordinary application software, Excel and Surfer, instead of expensive one like GIS, to overcome it. Consolidating data into a database on Excel facilitated retrieval, statistical analysis and presentation in the form of either table or graph. The cross analysis of the data suggested that the abundant VOCs were alkanes, alkenes, aromatics and cyclic HCs. Emission sources were located by mapping the concentration distribution of these four types of VOCs in terms of contour maps on Surfer. During eight surveys, five emission sources were located and their VOCs were characterized.     

沈阳市环境空气中挥发性有机物污染特征及来源解析

基于2019年沈阳市4个不同功能区挥发性有机物(VOCs)小时分辨率的在线监测数据,分析了环境空气中VOCs的污染特征及来源。结果表明,观测期间沈阳市环境空气中VOCs日平均体积分数为(31.5±13.3)×10~(-9),4个功能区VOCs体积分数均呈现出冬季明显大于夏季的特征;工业区环境空气中VOCs体积分数明显高于其他功能区。商业交通居民混合区、文化居民混合区、郊区VOCs体积分数呈现明显双峰结构,工业区双峰结构不明显。工业区VOCs以新鲜排放为主,而其他3个区域为老化气团的传输。工业区春、夏季环境空气中VOCs来源包括燃料挥发源(26.90%)、溶剂与涂料源(17.69%)、燃烧源(16.40%)、化工源(15.69%)、交通源(7.57%)和炼油炼焦源(4.15%)。秋、冬季VOCs的来源包括燃烧源(30.77%)、溶剂与涂料源(20.26%)、燃料挥发源(18.79%)、化工源(11.54%)、炼油炼焦源(9.34%)和交通源(5.51%)。     

典型化工园区大气中挥发性有机物污染调查

对常州市某典型化工园区大气中挥发性有机物(VOCs)污染状况进行了调查。结果表明,该化工园区大气中检出挥发性有机物共有58种,组分有芳香烃、饱和烷烃、卤代烃、烯烃、醛酯类化合物及其他类;苯、甲苯、乙苯、二甲苯为主要挥发性有机污染物,质量浓度为1.0~194μg/m~3;均未超出参考标准的限值。背景点位和园区点位大气中主要ρ总(VOCs)在秋冬季最高,敏感点大气VOCs随季节变化也较为明显;园区T1和T2ρ总(VOCs)年均值高于敏感点位,背景点位年均值最低;园区点位除了汽车尾气排放之外,溶剂的挥发和生产工艺中污染物的排放也增加了大气中苯系物的浓度,同时也对敏感点位和对照点位的大气质量产生了一定的影响。