Spatial gradients and source apportionment of volatile organic compounds near roadways

Concentrations of 55 volatile organic compounds (VOCs) (C₂–C₁₂) are reported near a highway in Raleigh, NC. Thirty-minute samples were collected at eight locations, ranging from approximately 10–100 m perpendicular from the roadway. The highest concentrations of VOCs were generally measured closest to the roadway, and concentrations decreased exponentially with increasing distance from the roadway. The highest mean concentration for individual VOCs were for ethylene (3.10 ppbv) (mean concentration at x = 13 m), propane (2.27 ppbv), ethane (1.91 ppbv), isopentane (1.54 ppbv), toluene (0.95 ppbv), and n-butane (0.89 ppbv). Concentrations at the nearest roadway location (x = 13 m) were generally between 2.0 and 1.5 times those from the farthest roadway location (x = 92 m). The data were apportioned into four source categories using the EPA Chemical Mass Balance Model (CMB8.2): motor vehicle exhaust, compressed natural gas, propane gas, and evaporative gasoline. The majority of the VOCs resulted from motor vehicle exhaust (67 ± 12%) (% of total VOC at x = 13 m ± S.D.). Compressed natural gas, propane gas, and evaporative gasoline accounted for approximately 15%, 7% and 1% of the total VOC emissions, respectively, at x = 13 m.     

Comparison of receptor models for source apportionment of volatile organic compounds in Beijing, China

Identifying the sources of volatile organic compounds (VOCs) is key to reducing ground-level ozone and secondary organic aerosols (SOAs). Several receptor models have been developed to apportion sources, but an intercomparison of these models had not been performed for VOCs in China. In the present study, we compared VOC sources based on chemical mass balance (CMB), UNMIX, and positive matrix factorization (PMF) models. Gasoline-related sources, petrochemical production, and liquefied petroleum gas (LPG) were identified by all three models as the major contributors, with UNMIX and PMF producing quite similar results. The contributions of gasoline-related sources and LPG estimated by the CMB model were higher, and petrochemical emissions were lower than in the UNMIX and PMF results, possibly because the VOC profiles used in the CMB model were for fresh emissions and the profiles extracted from ambient measurements by the two-factor analysis models were "aged".     

Levels and composition of volatile organic compounds on commuting routes in Detroit, Michigan

Vehicle emissions can constitute a major share of ambient concentrations of many volatile organic compounds (VOCs) and other air pollutants in urban areas. Especially high concentrations may occur at curbsides, vehicle cabins, and other microenvironments. Such levels are not reflected by monitoring at fixed sites. This study reports on measurements of VOCs made from buses and cars in Detroit, MI. A total of 74 adsorbent tube samples were collected on 40 trips and analyzed by GC-MS for 77 target compounds. Three bus routes, selected to include residential, commercial and heavily industrialized areas, were sampled simultaneously on four sequential weeks during morning and afternoon rush hour periods. Nineteen compounds were regularly detected and quantified, the most prevalent of which included hexane/2-methyl pentane (15.6±5.8 μg m⁻³), toluene (10.2±7.9 μg m⁻³), m,p-xylene (6.8±4.7 μg m⁻³), benzene (4.5±3.0 μg m⁻³), 1,2,4-trimethylbenzene (4.0±2.6 μg m⁻³), o-xylene (2.2±1.6 μg m⁻³), and ethylbenzene (2.1±1.5 μg m⁻³). VOC levels in bus interiors and outdoor levels along the roadway were similar. Despite the presence of large industrial sources, route-to-route variation was small, but temporal variation was large and statistically significant. VOC compositions and trends indicate the dominance of vehicle sources over the many industrial sources in Detroit with the possible exceptions of styrene and several chlorinated VOCs. In-bus levels exceeded concentrations at fixed site monitors by a factor of 2–4. VOC concentrations in Detroit traffic are generally comparable to levels measured elsewhere in the US and Canada, but considerably lower than measured in Asia and Europe.     

室内环境中挥发性有机物释放过程的数学模型

根据组成结构,将室内环境中释放挥发性有机物(VOCs)的建筑装饰材料划分为单层干材料、单层湿材料、多层组合材料等类型,总结了这三种材料的VOCs释放特征、传输过程和数学模型研究现状,分析了模型的特点和适用范围,指出了模型研究发展的趋势,对应用中模型的选择提出了指导性建议.     

室内空气中挥发性有机物采样方法进展

介绍了近年来室内空气中挥发性有机物的各种采样方法及适用范围，其中重点介绍了美国环保署最新版的TO－17方法和J.Pawliszyn发明的固相微萃取法（SPME），并对一系列的采样方法进行了比较，阐述了这些方法在国内外的应用及研究进展，同时讨论了这些方法的局限性。     

太湖水源地水体中半挥发性有机物的监测

太湖某水源地水样经C18柱富集、气相色谱-质谱法(GC-MS)分离,定性测定其中的有机物.在丰水期、平水期、枯水期分别采样,在检测到的近百种有机化合物中有40种出现频率很高,同时运用内标法对其进行相对含量的比较,结果表明脂肪族化合物、邻苯二甲酸酯、2,6-二叔丁基-4-甲基苯酚和异氰尿酸三甲酯的相对含量较高,值得引起关注.     

The diffusion and sorption of volatile organic compounds through kaolinitic clayey soils

Laboratory experiments to estimate the effective molecular diffusion coefficient (D(e)) and sorption coefficient (K(d)) for volatile organic compounds through natural clayey soils were conducted using diffusion testing apparatus. The compounds tested were methyl ethyl ketone (MEK), toluene and trichloroethylene (TCE). The D(e) and K(d) values were determined by a curve fitting procedure. The compound losses, and the effects of porous disks used in the apparatus were significant. The transport of MEK was faster than that of TCE and toluene because of the lower sorption to the soils. The D(e) values of all the compounds were of the order of 10(-10) m(2)/s and smaller than the diffusion coefficient in pure aqueous solution at infinite dilution (D(0)), due to the tortuosity of the samples. The effects of the sample thickness on the parameter determination were not significant. Comparison to the K(d) values estimated from batch sorption tests and from organic carbon content (f(oc))-based predictions showed that the diffusion test results were intermediate between those from the other two methods. The diffusion tests use compacted soil samples and should be more relevant to in situ conditions, but the reliability of the tests is affected by large compound losses that cause uncertainties in their interpretation. It is recommended that more than one method be used to assess K(d) values.     

南京市大气气溶胶中颗粒物和正构烷烃特征及来源分析

于2002年夏季（7月）和冬季（12月）采集南京市5个功能区的大气气溶胶（PM2．5和PM10）样品，对两个季节不同功能区颗粒物及其颗粒物中正构烷烃的分布特征和污染来源进行了分析。结果表明，南京市大气颗粒物含量冬季高于夏季，细颗粒高于粗颗粒。正构烷烃的变化规律同颗粒物一致，且主要分布在细颗粒物上。根据各个功能区正构烷烃（C15-C32）的CPI（CPI1、CPI2和CPI3）结果，可知南京市大气气溶胶中正构烷烃由生物源和人为源共同排放产生。％waxCn的结果表明生物源对气溶胶中正构烷烃的贡献率为20％～43％，对南京市大气颗粒物的贡献率为1．66％～4．76％。     

气相色谱法分离和测定合成革用胶粘剂中的挥发性有机物

对合成革用胶粘剂中的发挥有机成份进行了色谱分离，并测定了胶粘剂中的9种挥发性有机物，方法的加标回收率为89.4%～102.8%，变异系数为1.2%～5.0%。     

PM composition and source reconciliation in Mexico City

PM_2.5 and PM₁₀ were collected during 24-h sampling intervals from March 1st to 31st, 2006 during the MILAGRO campaign carried out in Mexico City's northern region, in order to determine their chemical composition, oxidative activity and the estimation of the source contributions during the sampling period by means of the chemical mass balance (CMB) receptor model. PM_2.5 concentrations ranged from 32 to 70 μg m⁻³ while that of PM10 did so from 51 to 132 μg m⁻³. The most abundant chemical species for both PM fractions were: OC, EC, SO₄²⁻, NO₃⁻, NH₄⁺, Si, Fe and Ca. The majority of the PM mass was comprised of carbon, up to about 52% and 30% of the PM2.5 and PM10, respectively. PM2.5 constituted more than 50% of PM10. The redox activity, assessed by the dithiothreitol (DTT) assay, was greater for PM_2.5 than for PM₁₀, and did not display significant differences during the sampling period. The PM_2.5 source reconciliation showed that in average, vehicle exhaust emissions were its most important source in an urban site with a 42% contribution, followed by re-suspended dust with 26%, secondary inorganic aerosols with 11%, and industrial emissions and food cooking with 10% each. These results had a good agreement with the Emission Inventory. In average, the greater mass concentration occurred during O₃S that corresponds to a wind shift initially with transport to the South but moving back to the North. Taken together these results show that PM chemical composition, oxidative potential, and source contribution is influenced by the meteorological conditions.     

Transient analysis of volatile organic compound concentrations for estimating emission rates

While emission rates of volatile organic compounds (VOCs) have been obtained for building materials, furnishings and processes in chambers, field measurements are more difficult. Procedures to estimate emission rates using transient analysis of VOC concentrations are described and applied in a two-story classroom/office building. The analysis employs semi-real-time VOC concentrations determined with a portable GC/FID and simultaneous air change rate measurements using tracer gas decay. The results of the analysis yield consistent values of emission rates for building materials ranging from 0.20 to 0.40 mg m⁻² h⁻¹ when normalized by floor area. Occupancy-related emissions were more difficult to estimate and covered a wider range from roughly 0.1 to 1.5 mg m⁻² h⁻¹. The test data were also analyzed in an attempt to determine sink parameters, but these efforts were not particularly successful. Furthermore, in these tests, the inclusion of sink effects did not significantly impact the estimated emission rates. While this paper offers a transient analysis approach that may lead to improved field estimates of VOC emission rates, it is not presented as a definitive methodology. Nevertheless, transient analysis has potential for use in other buildings, but simultaneous air change rate measurements are critical in its application in estimating VOC emission rates in the field.     

沈阳市固定燃烧源挥发性有机化合物2007年排放清单研究

挥发性有机化合物(VOCs)与.OH的反应是对流层臭氧形成的重要化学过程,是导致城市光化学烟雾的根本原因。为建立沈阳市固定燃烧源VOCs排放清单,选取了电力热力行业、钢铁行业和秸秆燃烧3个主要排放源进行研究。结果表明:(1)2007年,沈阳市固定燃烧源VOCs排放总量为8 544.539 t,其中排放量最大的是秸秆燃烧,为6 317.115 t;其次是电力热力行业,为2 225.780 t;最小的是钢铁行业,为1.644 t。(2)沈阳市各区县固定燃烧源VOCs排放量由大到小排序依次为新民市、法库县、东陵区、康平县、辽中县、于洪区、苏家屯区、大东区、沈北新区、铁西区、沈河区、皇姑区、和平区;VOCs排放强度由大到小排序依次为大东区、沈河区、铁西区、东陵区、皇姑区、和平区、于洪区、苏家屯区、法库县、康平县、辽中县、沈北新区、新民市。     

空气中挥发性有机物监测技术的研究进展

讨论了空气中挥发性有机化合物（VOCs）的监测分析方法研究进展。重点介绍了空气中VOCs的采集、分析和测定；简要叙述了样品前处理的新方法--固相微萃取法（SPME）与其它前处理方法的研究概况。     

GIS-based source identification and apportionment of diffuse water pollution: perfluorinated compound pollution in the Tokyo Bay basin

To efficiently reduce perfluorinated compound (PFC) pollution, it is important to have an understanding of PFC sources and their contribution to the pollution. In this study, source identification of diffuse water pollution by PFCs was conducted using a GIS-based approach. Major components of the source identification were collection of the monitoring data and preparation of the corresponding geographic information that was extracted from a constructed GIS database. The spatially distributed pollution factors were then explored by multiple linear regression analysis, after which they were visually expressed using GIS. Among the 35 PFC homologues measured in a survey of the Tokyo Bay basin, 18 homologues were analyzed. Pollution by perfluorooctane sulfonate (PFOS) was explained well by the percentage of arterial traffic area in the basin, and the 84% variance of the measured PFOS concentration was explained by two geographic variables, arterial traffic area and population. Source apportionment between point and nonpoint sources was conducted based on the results of the analysis. The contribution of PFOS from nonpoint sources was comparable to that from point sources in several major rivers flowing into Tokyo Bay. Source identification and apportionment using the GIS-based approach was shown to be effective, especially for ubiquitous types of pollution, such as PFC pollution.     

车内空气中挥发性有机物的研究

采用热脱附-气相色谱/质谱联用法对4辆处于静止状态下的车辆内部空气中挥发性有机物（VOCs）进行了研究,共定性检出了48种有机物,其中C6～C9之间的组分较多;并对VOCs的总浓度进行了定量,1#～4#车分别为1846、2289、1104和3146 μg/m^3;其中BTEX占VOCs总量的20%～30%;车内VOCs浓度与温度及车辆使用年限密切相关.     

Sources of organic aerosol: Positive matrix factorization of molecular marker data and comparison of results from different source apportionment models

This paper presents results from positive matrix factorization (PMF) of organic molecular marker data to investigate the sources of organic carbon (OC) in Pittsburgh, Pennsylvania. PMF analysis of 21 different combinations of input species found essentially the same seven factors with distinctive source-class-specific groupings of molecular markers. To link factors with source classes we directly compare PMF factor profiles with actual source profiles. Six of the PMF factors appear related to primary emissions from sources such as motor vehicles, biomass combustion, and food cooking. Each primary factor contributed between 5% and 10% of the annual-average OC with the exception of the cooking related factor which contributed 20% of the OC. However, the contribution of the cooking factor was sensitive to the specific combinations of input species. PMF could not differentiate between gasoline and diesel emissions, but the aggregate contribution of primary emissions from these two source classes is estimated to be less than 10% of the annual-average OC. One factor appears related to secondary organic aerosol based on its substantial contribution to biogenic oxidation products. This secondary factor contributed more than 50% of the summertime average OC. Reasonable agreement was observed between the PMF results and those of a previously published chemical mass balance (CMB) analysis of the same molecular marker dataset. Individual PMF factors are correlated with specific CMB sources, but systematic biases exist between the two estimates. These biases were generally within the uncertainty of the two estimates, but there is also evidence that PMF is not cleanly differentiating between source classes.     

车内空气中挥发性有机物的研究

采用热脱附-气相色谱/质谱联用法对4辆处于静止状态下的车辆内部空气中挥发性有机物(VOCs)进行了研究,共定性检出了48种有机物,其中C6~C9之间的组分较多;并对VOCs的总浓度进行了定量,1#~4#车分别为1846、2289、1104和3146μg/m3;其中BTEX占VOCs总量的20%~30%;车内VOCs浓度与温度及车辆使用年限密切相关。     

PM10 and PM2.5 source apportionment in the Barcelona Metropolitan area, Catalonia, Spain

Levels of total suspended particles, PM10, PM2.5 and PM1 were continuously monitored at an urban kerbside in the Metropolitan area of Barcelona from June 1999 to June 2000. The results show that hourly levels of PM2.5 and PM1 are consistent with the daily cycle of gaseous pollutants emitted by traffic, whereas TSP and PM10 do not follow the same trend, at least in the diurnal period. The PM2.5/PM10 ratio is dependent on the traffic emissions, whereas additional contribution sources for the >10 μm fraction must be taken into account in the diurnal period. Different PM10 and PM2.5 source apportionment techniques were compared. A methodology based on the chemical determination of 83% of both PM10 and PM2.5 masses allowed us to quantify the marine (4% in PM10 and <1% in PM2.5), crustal (26% in PM10 and 8% in PM2.5) and anthropogenic (54% in PM10 and 73% in PM2.5) loads. Peaks of crustal contribution to PM10 (up to 44% of the PM10 mass) were recorded under Saharan air mass intrusions. A different seasonal trend was observed for levels of sulphate and nitrate, probably as a consequence of the different thermodynamic behaviour of these PM species and the higher summer oxidation rate of SO₂.     

Exposure of population and microenvironmental distributions of volatile organic compound concentrations in the EXPOLIS study

Determination of volatile organic compounds (VOCs) formed one part of the EU-EXPOLIS project in which the exposure of European urban populations to particles and gaseous pollutants was studied. The EXPOLIS study concentrated on 30 target VOCs selected on the basis of environmental and health significance and usability of the compounds as markers of pollution sources. In the project, 201 subjects in Helsinki, 50 in Athens, 50 in Basel, 50 in Milan and, 50 in Oxford and 50 in Prague were selected for the final exposure sample. The microenvironmental and personal exposure concentrations of VOCs were the lowest in Helsinki and Basel, while the highest concentrations were measured in Athens and Milan; Oxford and Prague were in between. In all cities, home indoor air was the most significant exposure agent. Workplace indoor air concentrations measured in this study were generally lower than the home indoor concentrations and home outdoor air played a minor role as an exposure agent. When estimating the measured personal exposure concentrations using the measured concentrations and time fractions spent at home indoors, at home outdoors, and at the workplace, it could be concluded that these three microenvironments do not fully explain the personal exposure. Other important sources for personal exposure must be encountered, the most important being traffic/transportation and other indoor environments not measured in this study.