北京城市雨水、树冠水和地表径流中有机氯农药的污染特征

对北京降雨过程中雨水、树冠水、地表径流等介质中有机氯农药(OCPs)的污染特征进行了研究,研究的污染物包括六氯苯(HCB)、六六六(HCH)和滴滴涕(DDT)。结果显示,在雨水、树冠水和地表径流中,HCH含量最高(几何平均浓度分别为11.1、21.6和25.1 ng/L),其次是HCB(几何平均浓度分别为3.71、3.54和5.91 ng/L)和DDT(几何平均浓度分别为2.64、4.66和10.6 ng/L)。对地表径流样品中所测的OCPs组分浓度与径流水质参数和气象参数的相关分析显示,所测各OCPs组分浓度与pH呈显著负相关,与径流的溶解性有机碳含量呈显著正相关,降雨量和雨前晴天数对不同组分OCPs的影响并不完全相同。平均贡献率的计算表明,雨水是城市地表径流中OCPs的一个重要来源,树冠水的贡献也不可忽视。     

Source apportionment of suspended particulate matter at two traffic junctions in Mumbai,India

Very high concentration of suspended particulate matter (SPM) is observed at traffic junctions in India. Factor analysis-multiple regression (FA-MR), a receptor modelling technique has been used for quantitative apportionment of the sources contributing to the SPM at two traffic junctions (Sakinaka and Gandhinagar) in Mumbai, India. Varimax rotated factor analysis identified (qualitative) five possible sources; road dust, vehicular emissions, marine aerosols, metal industries and coal combustion. A quantitative estimation by FA-MR model indicated that road dust contributed to 41%, vehicular emissions to 15%, marine aerosols to 15%, metal industries to 6% and coal combustion to 6% of the SPM observed at Sakinaka traffic junction. The corresponding figures for Gandhinagar traffic junction are 33%, 18%, 15%, 8% and 11%, respectively. Due to limitation in source marker elements analysed about 16% of the remaining SPM at these two traffic junctions could not be apportioned to any possible sources by this technique. Of the observed lead in the SPM, FA-MR apportioned 62% to vehicular emissions, 17% to road dust, 11% to metal industries, 7% to coal combustion and 3% to marine aerosols at Gandhinagar traffic junction and about a similar apportionment for lead in SPM at Sakinaka traffic junction.     

Source characterisation of road dust based on chemical and mineralogical composition

Road dust contain potentially toxic pollutants originating from a range of anthropogenic sources common to urban land uses and soil inputs from surrounding areas. The research study analysed the mineralogy and morphology of dust samples from road surfaces from different land uses and background soil samples to characterise the relative source contributions to road dust. The road dust consist primarily of soil derived minerals (60%) with quartz averaging 40-50% and remainder being clay forming minerals of albite, microcline, chlorite and muscovite originating from surrounding soils. About 2% was organic matter primarily originating from plant matter. Potentially toxic pollutants represented about 30% of the build-up. These pollutants consist of brake and tire wear, combustion emissions and fly ash from asphalt. Heavy metals such as Zn, Cu, Pb, Ni, Cr and Cd primarily originate from vehicular traffic while Fe, Al and Mn primarily originate from surrounding soils. The research study confirmed the significant contribution of vehicular traffic to dust deposited on urban road surfaces.     

A composite receptor and dispersion model approach for estimation of effective emission factors for vehicles

It is difficult to estimate vehicular emission factors at traffic junctions for use in dispersion modelling studies. Firstly, because the vehicles are in various modes of operation and secondly, it is difficult to delineate the effects of other contributing sources, mainly the effects of road dust and deposited constituents, which are very prominent at traffic junctions in India. Factor analysis-multiple regression (FA-MR), a receptor modelling technique has been used in this study for apportioning the contributing sources. The measurement data consist of one year's temporal variation of suspended particulate matter (SPM), analysed for its trace metal constituents, and two gaseous components NO₂ and SO₂ at two traffic junctions in Mumbai (India). FA-MR apportioned 40% of the observed SPM to road dust and 15% to vehicular sources. Of the total Pb observed in the SPM, FA-MR apportioned 60% to vehicular sources and 20% to road dust. The field-observed vehicular counts, meteorological parameters and road geometry were used in California line source dispersion model to estimate the effective vehicular emission factor for Pb at one traffic junction. This derived emission factor was used to predict the Pb concentration at second (independent observation) traffic junction. The result was found to be more satisfactory than using default emission factors obtained from literature. Similarly, effective vehicular emission factor for NO₂ was also evaluated for one site and tested for predicting concentrations at the other site.     

Size- and density-distributions and sources of polycyclic aromatic hydrocarbons in urban road dust

Polycyclic aromatic hydrocarbons (PAHs) present in size- and density-fractionated road dust were measured to identify the important fractions in urban runoff and to analyse their sources. Road dust was collected from a residential area (Shakujii) and a heavy traffic area (Hongo Street). The sampling of road dust from the residential area was conducted twice in different seasons (autumn and winter). The collected road dust was separated into three or four size-fractions and further fractionated into light (<1.7 g/cm3) and heavy (>1.7 g/cm3) fractions by using cesium chloride solution. Light particles constituted only 4.0+/-1.4%, 0.69+/-0.03% and 3.4+/-1.0% of the road dust by weight for Shakujii (November), Shakujii (February) and Hongo Street, respectively but contained 28+/-10%, 33+/-3% and 44+/-8% of the total PAHs, respectively. The PAH contents in the light fractions were 1-2 orders of magnitude higher than those in the heavy fractions. In the light fractions, the 12PAH contents in February were significantly higher than the 12PAH contents in November (P<0.01), whereas in the heavy fractions, no significant difference was found (P>0.05). Cluster analysis revealed that there was a significant difference in the PAH profiles between locations rather than between size-fractions, density-fractions and sampling times. Multiple regression analysis indicated that asphalt/pavement was the major source of Shakujii road dust, and that tyre and diesel vehicle exhaust were the major sources of finer and coarser fractions collected from Hongo Street road dust, respectively.     

Concentrations and source apportionment of PM10 and associated elemental and ionic species in a lignite-burning power generation area of southern Greece

Ambient concentrations of PM₁₀ and associated elemental and ionic species were measured over the cold and the warm months of 2010 at an urban and two rural sites located in the lignite-fired power generation area of Megalopolis in Peloponnese, southern Greece. The PM₁₀ concentrations at the urban site (44.2?±?33.6 μg m^?3) were significantly higher than those at the rural sites (23.7?±?20.4 and 22.7?±?26.9 μg m^?3). Source apportionment of PM₁₀ and associated components was accomplished by an advanced computational procedure, the robotic chemical mass balance model (RCMB), using chemical profiles for a variety of local fugitive dust sources (power plant fly ash, flue gas desulfurization wet ash, feeding lignite, infertile material from the opencast mines, paved and unpaved road dusts, soil), which were resuspended and sampled through a PM₁₀ inlet onto filters and then chemically analyzed, as well as of other common sources such as vehicular traffic, residential oil combustion, biomass burning, uncontrolled waste burning, marine aerosol, and secondary aerosol formation. Geological dusts (road/soil dust) were found to be major PM₁₀ contributors in both the cold and warm periods of the year, with average annual contribution of 32.6 % at the urban site vs. 22.0 and 29.0 % at the rural sites. Secondary aerosol also appeared to be a significant source, contributing 22.1 % at the urban site in comparison to 30.6 and 28.7 % at the rural sites. At all sites, the contribution of biomass burning was most significant in winter (28.2 % at the urban site vs. 14.6 and 24.6 % at the rural sites), whereas vehicular exhaust contribution appeared to be important mostly in the summer (21.9 % at the urban site vs. 11.5 and 10.5 % at the rural sites). The highest contribution of fly ash (33.2 %) was found at the rural site located to the north of the power plants during wintertime, when winds are favorable. In the warm period, the highest contribution of fly ash was found at the rural site located to the south of the power plants, although it was less important (7.2 %). Moderate contributions of fly ash were found at the urban site (5.4 and 2.7 % in the cold and the warm period, respectively). Finally, the mine field was identified as a minor PM₁₀ source, occasionally contributing with lignite dust and/or deposited wet ash dust under dry summer conditions, with the summertime contributions ranging between 3.1 and 11.0 % among the three sites. The non-parametric bootstrapped potential source contribution function analysis was further applied to localize the regions of sources apportioned by the RCMB. For the majority of sources, source regions appeared as being located within short distances from the sampling sites (within the Peloponnesse Peninsula). More distant Greek areas of the NNE sector also appeared to be source regions for traffic emissions and secondary calcium sulfate dust.     

Comparison of the physical and chemical characteristics of fine road dust at different urban sites

The size distribution and chemical components of a fine fraction (<2.5 μm) of road dust collected at urban sites in Korea (Gwangju) and Mongolia (Ulaanbaatar) where distinct urban characteristics exist were measured. A clear bimodal size distribution was observed for the resuspended fine road dust at the urban sites in Korea. The first mode peaked at 100–110 nm, and the second peak was observed at 435–570 nm. Ultrafine mode (~30 nm) was found for the fine road dust at the Mongolia site, which was significantly affected by residential coal/biomass burning. The contribution of the water-soluble ions to the fine road dust was higher at the sites in Mongolia (15.8–16.8%) than at those in Korea (1.2–4.8%). Sulfate and chloride were the most dominant ionic species for the fine road dust in Mongolia. As (arsenic) was also much higher for the Mongolian road dust than the others. The sulfate, chloride, and As mainly come from coal burning activity, suggesting that coal and biomass combustion in Mongolia during the heating season should affect the size and chemical components of the fine road dust. Cu (copper) and Zn (zinc), carbonaceous particles (organic carbon [OC] and elemental carbon [EC]) increased at sites in Korea, suggesting that the fine road dust at these sites was significantly affected by the high volume of traffic (engine emission and brake/tire wear). Our results suggest that chemical profiles for road dust specific to certain sites should be applied to more accurately apportion road dust source contributing to the ambient particulate matter.

Implications: Size and chemical characteristics of fine road dust at sites having distinct urban characteristics were examined. Residential coal and biomass burning and traffic affected physiochemical properties of the fine road dust. Different road dust profiles at different sites should be needed to determine the ambient PM2.5 sources more accurately.     

Sources of fine particulate species in ambient air over lake Champlain Basin, VT

This study is a part of an ongoing investigation of the types and locations of emission sources that contribute fine particulate air contaminants to Underhill, VT. The air quality monitoring data used for this study are from the Interagency Monitoring of Protected Visual Environments network for the period of 2001-2003 for the Underhill site. The main source-receptor modeling techniques used are the positive matrix factorization (PMF) and potential source contribution function (PSCF). This new study is intended as a comparison to a previous study of the 1988-1995 Underhill data that successfully revealed a total of 11 types of emission sources with significant contributions to this rural site. This new study has identified a total of nine sources: nitrate-rich secondary aerosol, wood smoke, East Coast oil combustion, automobile emission, metal working, soil/dust, sulfur-rich aerosol type I, sulfur-rich aerosol type II, and sea salt/road salt. Furthermore, the mass contributions from the PMF identified sources that correspond with sampling days with either good or poor visibility were analyzed to seek possible correlations. It has been shown that sulfur-rich aerosol type I, nitrate aerosol, and automobile emission are the most important contributors to visibility degradation. Soil/dust and sea salt/road salt also have an added effect.     

Assessment of source apportionment by Positive Matrix Factorization analysis on fine and coarse urban aerosol size fractions

This study was conducted in order to investigate the differences observed in source profiles in the urban environment, when chemical composition parameters from different aerosol size fractions are subjected to factor analysis. Source apportionment was performed in an urban area where representative types of emission sources are present. PM₁₀ and PM₂ samples were collected within the Athens Metropolitan area and analysed for trace elements, inorganic ions and black carbon. Analysis by two-way and three-way Positive Matrix Factorization was performed, in order to resolve sources from data obtained for the fine and coarse aerosol fractions. A difference was observed: seven factors describe the best solution in PMF3 while six factors in PMF2. Six factors derived from PMF3 analysis correspond to those described by the PMF2 solution for the fine and coarse particles separately. These sources were attributed to road dust, marine aerosol, soil, motor vehicles, biomass burning, and oil combustion. The additional source resolved by PMF3 was attributed to a different type of road dust. Combustion sources (oil combustion and biomass burning) were correctly attributed by PMF3 solely to the fine fraction and the soil source to the coarse fraction. However, a motor vehicle's contribution to the coarse fraction was found only by three-way PMF. When PMF2 was employed in PM₁₀ concentrations the optimum solution included six factors. Four source profiles corresponded to the previously identified as vehicles, road dust, biomass burning and marine aerosol, while two could not be clearly identified. Source apportionment by PMF2 analysis based solely on PM₁₀ aerosol composition data, yielded unclear results, compared to results from PMF2 and PMF3 analyses on fine and coarse aerosol composition data.     

Land Use-related Chemical Composition of Street Sediments in Beijing

BACKGROUND: More than 10 million people are currently living in Beijing. This city faces severe anthropogenic air pollution caused by an intense vehicle increase (11% per year in China), coal combusting power plants, heavy industry, huge numbers of household and restaurant cookers, and domestic heating stoves. Additionally, each year dust storms are carrying particulate matter from the deserts of Gobi and Takla Makan towards Beijing, especially in spring. Other geogenic sources of particulate matter which contribute to the air pollution are bare soils, coal heaps and construction sites occurring in and around Beijing. Streets function as receptor surfaces for atmospheric dusts. Thus, street sediments consist of particles of different chemical compositions from many different sources, such as traffic, road side soils and industry. METHODS: Distributions and concentrations of various chemical elements in street sediments were investigated along a rural-urban transect in Beijing, China. Chemical elements were determined with X-ray fluorescence analysis. Factor analysis was used to extract most important element sources contributing to particulate pollution along a main arterial route of the Chinese capital. RESULTS AND DISCUSSION: The statistical evaluation of the data by factor analysis identifies three main anthropogenic sources responsible for the contamination of Beijing street sediments. The first source is a steel factory in the western part of Beijing. From this source, Mn, Fe, and Ti were emitted into the atmosphere through chimneys and by wind from coal heaps used as the primary energy source for the factory. The second source is a combination of traffic, domestic heating and some small factories in the center of Beijing discharging Cu, Pb, Zn and Sn. Calcium and Cr characterize a third anthropogenic element source of construction materials such as concrete and mortar. Beside the anthropogenic contamination, some elements like Y, Zr, Nb, Ce, and Rb are mainly derived from natural soils and from the deserts. This is supported by mineral phase analysis, which showed a clear imprint of material in road dusts coming from the West-China deserts. CONCLUSIONS: Our results clearly show that the chemical composition of urban road dusts can be used to identify distinct sources responsible for their contamination. The study demonstrates that the chemistry of road dusts is an important monitor to assess the contamination in the urban environment. Chemical composition of street sediments in Beijing comprises the information of different sources of atmospheric particles. RECOMMENDATIONS AND OUTLOOK: This study is only a small contribution to the understanding of substance fluxes related to Beijing's dust. More effort is required to assess Beijing's dust fluxes, since the dust harms the living quality of the inhabitants. Especially the measurable superimposing of long scale transported dust from dry regions with the anthropogenic polluted urban dust makes investigations of Beijing's dust scientifically valuable.     

Characteristics of re-suspended road dust and its impact on the atmospheric environment in Beijing

A sampling campaign of re-suspended road dust samples from 53 sites that could cover basically the entire Beijing, soil samples from the source regions of dust storm in August 2003, and aerosol samples from three representative sites in Beijing from December 2001 to September 2003, was carried out to investigate the characteristics of re-suspended road dust and its impact on the atmospheric environment. Ca, S, Cu, Zn, Ni, Pb, and Cd were far higher than its crustal abundances and Ca²⁺, SO₄²⁻, Cl⁻, K⁺, Na⁺, NO₃⁻ were major ions in re-suspended road dust. Al, Ti, Sc, Co, and Mg in re-suspended road dust were mainly originated from crustal source, while Cu, Zn, Ni, and Pb were mainly derived from traffic emissions and coal burning, and Fe, Mn, and Cd were mainly from industrial emissions, coal combustion and oil burning. Ca²⁺ and SO₄²⁻ mainly came from construction activities, construction materials and secondary gas-particle conversions, Cl⁻ and Na⁺ were derived from industrial wastewater disposal and chemical industrial emissions, and NO₃⁻ and K⁺ were from vehicle emissions, photochemical reactions of NO_X, biomass and vegetable burning. The contribution of mineral aerosol from inside Beijing to the total mineral aerosols was ∼30% in spring of 2002, ∼70% in summer of 2002, ∼80% in autumn of 2003, ∼20% in PM₁₀ and ∼50% in PM_2.5, in winter of 2002. The pollution levels of the major pollution species, Ca, S, Cu, Zn, Ni, Pb, Fe, Mn, and Cd in re-suspended road dust reached ∼76%, ∼87%, ∼75%, ∼80%, ∼82%, ∼90%, ∼45%, ∼51%, and ∼94%, respectively. Re-suspended road dust from the traffic and construction activities was one of the major sources of pollution aerosols in Beijing.     

Characterisation for some emission sources in CMB calculation for Mae Moh area, Thailand

Particulate samples of agricultural waste burning, straw burning, forest leaf burning, heavy duty truck emission, paved road dust, soil, agricultural soil, coal, electrostatic precipitator ash, and emission from stack power plant were collected from the Mae Moh area. Chemical compositions of sampling filters were analysed to determine the particulate matter source profiles. The analysis included ICP-MS for elemental compositions, ion chromatography for water soluble ions and CHNS/O for carbon species. In all biomass burning profiles organic carbon (OC) was higher during smouldering phase, while elemental carbon (EC) was higher during flaming phase. Results relating to biomass emission during flaming stage showed increase in K⁺. Organic and elemental carbons were the most abundant in biomass burning and truck exhaust. The abundance of EC was much lower, and the abundance of OC was much higher in biomass burning relative to truck exhaust emission. Al, K, Mg, Ca, and Fe were presented with high abundance in road dust, soil, coal, fly ash and stack samples. The differences in chemical compositions were not sufficient to distinguish geological material and fugitive dust sources. Fly ash profile differed from the others since OC and EC were not detected. Na and Zn were most abundant in stack samples. These findings served as a starting point for source contribution study. For future application of source apportionment using the CMB modelling technique, these source profiles should be appropriately grouped and selected to generate reliable outcomes.     

Source apportionment of polycyclic aromatic hydrocarbons in surface soil in Tianjin, China

Principal component analysis and multiple linear regression were applied to apportion sources of polycyclic aromatic hydrocarbons (PAHs) in surface soils of Tianjin, China based on the measured PAH concentrations of 188 surface soil samples. Four principal components were identified representing coal combustion, petroleum, coke oven plus biomass burning, and chemical industry discharge, respectively. The contributions of major sources were quantified as 41% from coal, 20% from petroleum, and 39% from coking and biomass, which are compatible with PAH emissions estimated based on fuel consumption and emission factors. When the study area was divided into three zones with distinctive differences in soil PAH concentration and profile, different source features were unveiled. For the industrialized Tanggu-Hangu zone, the major contributors were cooking (43%), coal (37%) and vehicle exhaust (20%). In rural area, however, in addition to the three main sources, biomass burning was also important (13%). In urban-suburban zone, incineration accounted for one fourth of the total.     

Sources of Fine Particulate Species in Ambient Air over Lake Champlain Basin,VT

Abstract

This study is a part of an ongoing investigation of the types and locations of emission sources that contribute fine particulate air contaminants to Underhill, VT. The air quality monitoring data used for this study are from the Interagency Monitoring of Protected Visual Environments network for the period of 2001–2003 for the Underhill site. The main source-receptor modeling techniques used are the positive matrix factorization (PMF) and potential source contribution function (PSCF). This new study is intended as a comparison to a previous study of the 1988–1995 Underhill data that successfully revealed a total of 11 types of emission sources with significant contributions to this rural site. This new study has identified a total of nine sources: nitrate-rich secondary aerosol, wood smoke, East Coast oil combustion, automobile emission, metal working, soil/dust, sulfur-rich aerosol type I, sulfur-rich aerosol type II, and sea salt/road salt. Furthermore, the mass contributions from the PMF identified sources that correspond with sampling days with either good or poor visibility were analyzed to seek possible correlations. It has been shown that sulfur-rich aerosol type I, nitrate aerosol, and automobile emission are the most important contributors to visibility degradation. Soil/dust and sea salt/road salt also have an added effect.     

Source,distribution, and health risk assessment of polycyclic aromatic hydrocarbons in urban street dust from Tianjin,China

To better assess and understand potential health risk of urban residents exposed to urban street dust, the total concentration, sources, and distribution of 16 polycyclic aromatic hydrocarbons (PAHs) in 87 urban street dust samples from Tianjin as a Chinese megacity that has undergone rapid urbanization were investigated. In the meantime, potential sources of PAHs were identified using the principal component analysis (PCA), and the risk of residents’ exposure to PAHs via urban street dust was calculated using the Incremental Lifetime Cancer Risk (ILCR) model. The results showed that the total PAHs (∑PAHs) in urban street dust from Tianjin ranged from 538 μg kg^?1 to 34.3 mg kg^?1, averaging 7.99 mg kg^?1. According to PCA, the two to three- and four to six-ring PAHs contributed 10.3 and 89.7 % of ∑PAHs, respectively. The ratio of the sum of major combustion specific compounds (ΣCOMB)?/?∑PAHs varied from 0.57 to 0.79, averaging 0.64. The ratio of Ant/(Ant?+?Phe) varied from 0.05 to 0.41, averaging 0.10; Fla/(Fla?+?Pyr) from 0.40 to 0.68, averaging 0.60; BaA/(BaA?+?Chry) from 0.29 to 0.51, averaging 0.38; and IcdP/(IcdP?+?BghiP) from 0.07 to 0.37, averaging 0.22. The biomass combustion, coal combustion, and traffic emission were the main sources of PAHs in urban street dust with the similar proportion. According to the ILCR model, the total cancer risk for children and adults was up to 2.55?×?10^?5 and 9.33?×?10^?5, respectively.     

Emission inventory and sources of polycyclic aromatic hydrocarbons in the atmosphere at a suburban area in Taiwan

The application of a chemical mass balance air pollution model to ambient measurements of polycyclic aromatic hydrocarbons (PAHs) is presented. Sixteen air samples were collected at seven sites in a suburban area in Taiwan and analyzed for the concentration of 21 compounds between July 2001 and September 2001. Each ambient sample was evaluated for the PAH contribution from six sources (heavy oil combustion, natural gas combustion, coal combustion, diesel combustion, vehicles and municipal solid waste incinerator). Average predictions agree well with the emission inventory. By this method, the average contributions are 49%, 14%, 22%, 12%, and 2% from vehicles, heavy oil combustion, natural gas combustion, coal combustion and diesel combustion at these seven receptors. By far, vehicles are the major PAH emission sources and municipal solid waste incinerator is a minor contributor. The calculated result of particulate PAHs is compared with that of total (gaseous and particulate) PAHs. The estimate based on total PAHs is better than the estimate based on particulate PAHs only. Contributions of eight low reactive PAHs for the same emission sources and receptors were calculated. Atmospheric reactivity seems not a problem for source apportionment in this study.     

Source apportionment of ambient total suspended particulates and coarse particulate matter in urban areas of Jiaozuo, China

Approximately 750 total suspended particulates (TSPs) and coarse particulate matter (PM10) filter samples from six urban sites and a background site and >210 source samples were collected in Jiaozuo City during January 2002 to April 2003. They were analyzed for mass and abundances of 25 chemical components. Seven contributive sources were identified, and their contributions to ambient TSP/PM10 levels at the seven sites in three seasons (spring, summer, and winter days) and a "whole" year were estimated by a chemical mass balance (CMB) receptor model. The spatial TSP average was high in spring and winter days at a level of approximately 530 microg/m(3) and low in summer days at 456 microg/m(3); however, the spatial PMo0 average exhibited little variation at a level of approximately 325 microg/m(3), and PM10-to-TSP ratios ranged from 0.58 to 0.81, which suggested heavy particulate matter pollution existing in the urban areas. Apportionment results indicated that geological material was the largest contributor to ambient TSP/PM10 concentrations, followed by dust emissions from construction activities, coal combustion, secondary aerosols, vehicle movement, and other industrial sources. In addition, paved road dust and re-entrained dust were also apportioned to the seven source types and found soil, coal combustion, and construction dust to be the major contributors.     

Size distribution of polycyclic aromatic hydrocarbons in urban and suburban sites of Beijing, China

PAHs in five-stage size segregated aerosol particles were investigated in 2003 at urban and suburban sites of Beijing. The total concentration of 17 PAHs ranged between 0.84 and 152 ng m(-3), with an average of 116 ng m(-3), in urban area were 1.1-6.6 times higher than those measured in suburban area. It suggested a serious pollution level of PAHs in Beijing. PAHs concentrations increased with decreasing the ambient temperature. Approximately 68.4-84.7% of PAHs were adsorbed on particles having aerodynamic diameter 2.0 microm. Nearly bimodal distribution was found for PAHs with two and three rings, more than four rings PAHs, however, followed unimodal distribution. The overall mass median diameter (MMD) for PAHs decreased with increasing molecular weight. Diagnostic ratios and normalized distribution of PAHs indicated that the PAHs in aerosol particles were mainly derived from fossil fuel combustion. Coal combustion for domestic heating was probably major contributor to the higher PAHs loading in winter, whereas PAHs in other seasons displayed characteristic of mixed source of gasoline and diesel vehicle exhaust. Biomass burning and road dust are minor contributors to the PAHs composition of these aerosol particles. Except for source emission, other factors, such as meteorological condition, photochemical decay, and transportation from source to the receptor site, should to be involved in the generation of the observed patterns.     

潞城市大气PM_（10）中化学元素分布特征

利用ICP-AES分析了潞城市采暖期和非采暖期4个不同功能区PM10样品中16种化学元素,对不同元素的时空分布特征进行了研究,并采用富集因子和主成分分析初步研究了潞城市PM10中元素的主要来源。结果表明,潞城市PM10中重金属污染较为严重,且各元素在采暖期的平均浓度均明显高于非采暖期。PM10中Ca、V、Cr、As、Ni、Mn、Cu、Zn、Al和Pb的富集因子EF〉10,主要来源于人为污染;而Na、Mg、Si、Fe和K的EF〈10,除部分来自人为活动外,主要来自土壤风沙等自然来源。主成分分析结果显示,潞城市PM10中元素的主要来源按贡献率大小依次为：煤烟尘和工业粉尘50.39%,自然源34.37%和机动车尾气15.24%。     

Source apportionment of the carcinogenic potential of polycyclic aromatic hydrocarbons (PAH) associated to airborne PM10 by a PMF model

In order to perform a study of the carcinogenic potential of polycyclic aromatic hydrocarbons (PAH), benzo(a)pyrene equivalent (BaP-eq) concentration was calculated and modelled by a receptor model based on positive matrix factorization (PMF). Nineteen PAH associated to airborne PM10 of Zaragoza, Spain, were quantified during the sampling period 2001–2009 and used as potential variables by the PMF model. Afterwards, multiple linear regression analysis was used to quantify the potential sources of BaP-eq. Five sources were obtained as the optimal solution and vehicular emission was identified as the main carcinogenic source (35 %) followed by heavy-duty vehicles (28 %), light-oil combustion (18 %), natural gas (10 %) and coal combustion (9 %). Two of the most prevailing directions contributing to this carcinogenic character were the NE and N directions associated with a highway, industrial parks and a paper factory. The lifetime lung cancer risk exceeded the unit risk of 8.7?×?10^?5 per ng/m³ BaP in both winter and autumn seasons and the most contributing source was the vehicular emission factor becoming an important issue in control strategies.