Source apportionment of population representative samples of PM(2.5) in three European cities using structural equation modelling

Apportionment of urban particulate matter (PM) to sources is central for air quality management and efficient reduction of the substantial public health risks associated with fine particles (PM(2.5)). Traffic is an important source combustion particles, but also a significant source of resuspended particles that chemically resemble Earth's crust and that are not affected by development of cleaner motor technologies. A substantial fraction of urban ambient PM originates from long-range transport outside the immediate urban environment including secondary particles formed from gaseous emissions of mainly sulphur, nitrogen oxides and ammonia. Most source apportionment studies are based on small number of fixed monitoring sites and capture well population exposures to regional and long-range transported particles. However, concentrations from local sources are very unevenly distributed and the results from such studies are therefore poorly representative of the actual exposures. The current study uses PM(2.5) data observed at population based random sampled residential locations in Athens, Basle and Helsinki with 17 elemental constituents, selected VOCs (xylenes, trimethylbenzenes, nonane and benzene) and light absorbance (black smoke). The major sources identified across the three cities included crustal, salt, long-range transported inorganic and traffic sources. Traffic was associated separately with source categories with crustal (especially Athens and Helsinki) and long-range transported chemical composition (all cities). Remarkably high fractions of the variability of elemental (R(2)>0.6 except for Ca in Basle 0.38) and chemical concentrations (R(2)>0.5 except benzene in Basle 0.22 and nonane in Athens 0.39) are explained by the source factors of an SEM model. The RAINS model that is currently used as the main tool in developing European air quality management policies seems to capture the local urban fraction (the city delta term) quite well, but underestimates crustal particle levels in the three cities of the current study. Utilizing structural equation modelling parallel with traditional principal component analysis (PCA) provides an objective method to determine the number of factors to be retained in a model and allows for formal hypotheses testing.     

Comparative PM10-PM2.5 source contribution study at rural, urban and industrial sites during PM episodes in Eastern Spain

In this study a set of 340 PM10 and PM2.5 samples collected throughout 16 months at rural, an urban kerbside and an industrial background site (affected by the emissions from the ceramic manufacture and other activities) were interpreted. On the regional scale, the main PM10 sources were mineral dust (mainly Al2O3, Fe, Ti, Sr, CaCO3, Mg, Mn and K), emissions derived from power generation (SO4=, V, Zn and Ni), vehicle exhausts (organic and elemental carbon, NO3- and trace elements) and marine aerosol (Na, Cl and Mg). The latter was not identified in PM2.5. At the industrial site, additional PM10 sources were identified (tile covering in the ceramic production, petrochemical emissions and bio-mass burning from a large orange tree cultivation area). The contribution of each PM source to PM10 and PM2.5 levels experiences significant variations depending on the type of PM episode (Local-urban mainly in autumn-winter, regional mainly in summer, African or Atlantic episode), which are discussed in this study. The results show that it would be very difficult to meet the EU limit values for PM10 established for 2010. The annual mean PM levels are 22.0 microg PM10/m3 at the rural and 49.5 microg PM10/m3 and 33.9 microg PM2.5/m3 at the urban site. The natural contribution in this region, estimated at 6 microg/m3 of natural mineral dust (resulting from the African events and natural resuspension) and 2 microg/m3 of marine aerosol, accounts for 40% of the 2010 EU annual limit value (20 microg PM10/m3). Mineral dust concentrations at the urban and industrial sites are higher than those at the rural site because of the urban road dust and the ceramic-production contributions, respectively. At the urban site, the vehicle exhaust contribution (17 microg/m3) alone is very close to the 2010 EU PM10 limit value. At the rural site, the African dust is the main contributor to PM10 levels during the highest daily mean PM10 events (100th-97th percentile range). At the urban site, the vehicle exhaust product is the main contributor to PM10 and PM2.5 levels during the highest daily mean PM events (100th-85th percentile range). Mineral dust concentrations during African dust events accounts for 20-30 microg/m3 in PM10 and 10-15 microg/m3 in PM2.5. During non-African dust events, mineral dust derived from anthropogenic activities (e.g. urban road dust) is also a significant contributor to PM10, but not to PM2.5.     

A combined analysis of backward trajectories and aerosol chemistry to characterise long-range transport episodes of particulate matter: the Madrid air basin, a case study

This study has investigated the influence of synoptic weather patterns and long-range transport episodes on the concentration levels of airborne particulate matter (TSP, PM10 and PM2.5) and some major ions (SO(4)(2-), NO(3)(-) and NH(4)(+)) at a background rural station in central Spain. Air mass back-trajectories arriving at the site in 1999-2005 have been analysed by statistical methods. First, cluster analysis was used to group trajectories into 8 clusters depending on their direction and speed. Meteorological scenarios associated to each cluster have been obtained and interpreted. Then, the incidence of different air mass transport patterns on particle concentrations and composition recorded at this station was evaluated. This evaluation included PM10 and PM2.5 concentrations and chemical composition data, obtained at three representative sites of the Madrid air basin during sampling campaigns carried out in the course of the 1999-2005 period. Finally, a residence time analysis of trajectories was also performed to detect remote sources and transport pathways. Significantly elevated concentrations of TSP and PM10 were observed for Northern African flows as a consequence of the transport of mineral dust. Significant inter-cluster differences were also observed for PM2.5 and secondary inorganic compounds, with the highest concentrations associated with low baric gradient situations and Southern European flows. The residence time analysis confirmed that current TSP and PM10 concentrations in central Spain are likely to be influenced significantly by long-range transport of desert dust from different desert regions in North Africa. Furthermore, emissions from continental Europe with a high time of residence in the western and central areas of the Mediterranean basin, seem to significantly influence PM2.5 and secondary inorganic aerosol concentrations in this region.     

Identification of atmospheric volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs) and carbonyl compounds in Hong Kong

Volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs) and carbonyl compounds are the major organic pollutants in the atmosphere. Emissions from motor vehicles have been one of the primary pollution sources in the metropolitan area of Hong Kong. A 12-month monitoring program for VOCs, PAHs and carbonyl compounds was performed at a roadside urban station at Hong Kong Polytechnic University (HKPU) in order to determine the correlations of each selected pollutant. The monitoring program ran from 16 April 1999 to 10 April 2000 for a period of 1 year, and a 2-week winter intensive sampling was carried out during January 2000. Traditionally, emission sources are identified from organic compounds in air particulates. Since many of the gaseous and particulate phases of organic compounds are from the same sources, correlations between the major exhausts are to be expected. Therefore, it would be more effective to apportion the sources using the combined gaseous and particulate phases of organic compounds. Correlations of selected pollutants within two other toxic air pollutants (TAPs) monitoring stations in Tsuen Wan (TW) and Central/Western (CW) were analyzed. Good correlations were found between pollutants that came from vehicle exhaust, especially in intensive sampling periods at HKPU roadside station. This was because the washing out effect for particulates during rainy days and photochemical degradation during high solar radiation were minimized in wintertime.     

Temporal variations and spatial distribution of ambient PM2.2 and PM10 concentrations in Dhaka, Bangladesh

Concentrations and characteristics of airborne particulate matter (PM(10), PM(2.2) and BC) on air quality have been studied at two air quality-monitoring stations in Dhaka, the capital of Bangladesh. One site is at the Farm Gate area, a hot spot with very high pollutant concentrations because of its proximity to major roadways. The other site is at a semi-residential area located at the Atomic Energy Centre, Dhaka Campus, (AECD) with relatively less traffic. The samples were collected using a 'Gent' stacked filter unit in two fractions of 0-2.2 mum and 2.2-10 mum sizes. Samples of fine (PM(2.2)) and coarse (PM(2.2-10)) airborne particulate matter fractions collected from 2000 to 2003 were studied. It has been observed that fine particulate matter has a decreasing trend, from prior year measurements, because of Government policy interventions like phase-wise plans to take two-stroke three-wheelers off the roads in Dhaka and finally banned from January 1, 2003. Other policy interventions were banning of old buses and trucks to ply on Dhaka city promotion of the using compressed natural gas (CNG), introducing air pollution control devices in vehicles, etc. It was found that both local (mostly from vehicular emissions) and possibly some regional emission sources are responsible for high PM(2.2) and BC concentrations in Dhaka. PM(2.2), PM(2.2-10) and black carbon concentration levels depend on the season, wind direction and wind speed. Transport related emissions are the major source of BC and long-range transportation from fossil fuel related sources and biomass burning could be another substantial source of BC.     

Sources of polycyclic aromatic hydrocarbons (PAHs) in street dust in a tropical Asian mega-city, Bangkok, Thailand

We collected samples of roadside air, automobile exhaust soot, tires, asphalt, and used engine oil in a tropical Asian mega-city, Bangkok, Thailand, and analyzed them for polycyclic aromatic hydrocarbons (PAHs) and hopanes. The concentrations and compositions of PAHs and hopanes were utilized to identify the sources of PAHs in street dust, in which high concentrations of PAHs were reported in our previous study. Weight-based concentrations of total PAHs had the following order: gasoline-powered vehicle soot (2600+/-2900 microg/g; n=4)>diesel-powered vehicle soot (115+/-245 microg/g; n=7) approximately roadside aerosols (101+/-35 microg/g; n=5) approximately used engine oil (97+/-65 microg/g; n=4) approximately tire wear particles (82+/-41 microg/g; n=5)>asphalt (2.3+/-1.6 microg/g; n=3)>street dust (1.1+/-0.8 microg/g; n=10). In cluster analysis, all the source materials fell into different clusters from that in which street dust fell, indicating that multiple source materials contribute to PAHs in the street dust. Multiple regression analysis of PAH profiles and diagnostics of hopane compositions identified tire debris as the major contributor of PAHs to street dust, followed by diesel vehicle exhaust.     

The contribution from distant dust sources to the atmospheric particulate matter loadings at XiAn, China during spring

Mass concentration data for PM(10) (particulate matter, PM, less than 10 mum) combined with an air mass back-trajectory clustering technique, a potential source contribution function (PSCF) model, and a concentration-weighted trajectory (CWT) method were used to evaluate the transport pathways and sources of XiAn PM(10) in spring 2001 to 2003. Three dust source areas: "Northwesterly Sources," "Northerly Sources," and a "Loess Plateau Source" and an anthropogenic "Southerly Source" contributing to the high particulate matter concentrations at XiAn were identified using these methods. The CWT method provided more compelling information on dust sources than the PSCF model, but there are clear advantages to using multiple interpretive tools. A comparison of the major dust transport pathways shows differences for XiAn versus Beijing, with "Northwesterly Sources" more important for XiAn and arid and semi-arid regions in Mongolia more important for Beijing.     

城市主干道交通与景观协调规划设计方法研究

城市主干道交通与景观协调规划设计方法 ,从规划设计的角度出发 ,针对目前主干道交通设施设计与道路景观设施设计分离的现状 ,通过对城市主干道各部分包括道路断面、中央分隔带、机非分隔带、人非分隔带、路侧绿化带等的优化设计 ,力求使道路交通与城市景观达到最佳的协调 ,形成道路沿线动态的风景线     

Long-term visibility trends in one highly urbanized, one highly industrialized, and two rural areas of Taiwan

Visibility trends on the island of Taiwan were investigated employing visibility and meteorological (1961-2003), and air pollutant (1994-2003) data from one highly urbanized center (Taipei), one highly industrialized center (Kaohsiung), and two rural centers (Hualien and Taitung). Average annual visibility (1961-2003) was significantly higher at the rural centers. Unlike at the other centers, visibility in Taipei improved between 1992 (6.6 km) and 2003 (9.9 km), and this can be linked to the construction and expansion of a mass transit rail system in Taipei, the use of which has helped reduce emissions of traffic related air pollutants, particles, and NO2. This has left Kaohsiung with the lowest annual visibility since 1994, despite its 1961-2003 average being superior to that of Taipei. Precipitation lowers visibility, as demonstrated by the all-centers correlation coefficient for visibility and precipitation of -0.92. Hence, frequency of precipitation is one of the factors contributing to the average annual visibility number. The poorest air quality category ('episode'), most commonly experienced in Taipei and Kaohsiung, was characterized by relatively high concentrations of PM10 and NOx at those centers, with comparatively high atmospheric pressure and comparatively low visibility and wind speed. Excepting O3, pollutant concentrations were slightly higher during weekdays, although there was no consistent, significant difference in weekday-weekend visibility. Principal component analysis demonstrated that visibility was markedly reduced in Taipei, Kaohsiung, and Hualien by increased vehicular emissions, road traffic dust, and industrial activity, but not in Taitung, where visibility was as a result superior to that at the other centers and degradation in visibility was likely a response to long-range transport of pollutants rather than local sources. Optimal empirical regression models indicated a negative impact on visibility for each of PM10, SO2 and NO2, particularly so for PM10, and validity of these models for Taipei, Kaohsiung, and Hualien was confirmed by correlation coefficients of simulated and observed average visibility of 0.63-0.72 for daily visibility and 0.85-0.88 for monthly visibility. For Taitung these figures were only 0.46 and 0.50, respectively, indicating that simulations for Taitung should include long-range transport as a pollutant source.     

Non-exhaust emissions of PM and the efficiency of emission reduction by road sweeping and washing in the Netherlands

From research on PM_2.5 and PM₁₀ in 2007/2008 in the Netherlands, it was concluded that the coarse fraction (PM_2.5-10) attributed 60% and 50% respectively, to the urban-regional and street-urban increments of PM₁₀. Contrary to Scandinavian and Mediterranean countries which exhibit significant seasonal variation in the coarse fraction of particulate matter (PM), in the Netherlands the coarse fraction in PM at a street location is rather constant during the year. Non-exhaust emissions by road traffic are identified as the main source for coarse PM in urban areas. Non-exhaust emissions mainly originate from re-suspension of accumulated deposited PM and road wear related particles, while primary tire and brake wear hardly contribute to the mass of non-exhaust emissions. However, tire and brake wear can clearly be identified in the total mass through the presence of the heavy metals: zinc, a tracer for tire wear and copper, a tracer for brake wear.The efficiency of road sweeping and washing to reduce non-exhaust emissions in a street-canyon in Amsterdam was investigated. The increments of the coarse fraction at a kerbside location and a housing façade location versus the urban background were measured at days with and without sweeping and washing. It was concluded that this measure did not significantly reduce non-exhaust emissions.     

Indoor/outdoor relationships for PM2.5 and associated carbonaceous pollutants at residential homes in Hong Kong - case study

Six residences were selected (two roadside, two urban, and two rural) to evaluate the indoor-outdoor characteristics of PM(2.5) (aerodynamic diameter <2.5 microm) carbonaceous species in Hong Kong during March and April 2004. Twenty-minute-averaged indoor and outdoor PM(2.5) concentrations were recorded by DustTrak samplers simultaneously at each site for 3 days to examine diurnal variability of PM(2.5) mass concentrations and their indoor-to-outdoor (I/O) ratios. Daily (24-h average) indoor/outdoor PM(2.5) samples were collected on pre-fired quartz-fiber filters with battery-powered portable mini-volume samplers and analyzed for organic and elemental carbon (OC, EC) by thermal/optical reflectance (TOR) following the Interagency Monitoring of Protected Visual Environments (IMPROVE) protocol. The average indoor and outdoor concentrations of 24 h PM(2.5) were 56.7 and 43.8 microg/m(3), respectively. The short-term PM(2.5) profiles indicated that the penetration of outdoor particles was an important contributor to indoor PM(2.5), and a household survey indicated that daily activities were also sources of episodic peaks in indoor PM(2.5). The average indoor OC and EC concentrations of 17.1 and 2.8 microg/m(3), respectively, accounted for an average of 29.5 and 5.2%, respectively, of indoor PM(2.5) mass. The average indoor OC/EC ratios were 5.8, 9.1, and 5.0 in roadside, urban, and rural areas, respectively; while average outdoor OC/EC ratios were 4.0, 4.3, and 4.0, respectively. The average I/O ratios of 24 h PM(2.5), OC, and EC were 1.4, 1.8, and 1.2, respectively. High indoor-outdoor correlations (r(2)) were found for PM(2.5) EC (0.96) and mass (0.81), and low correlations were found for OC (0.55), indicative of different organic carbon sources indoors. A simple model implied that about two-thirds of carbonaceous particles in indoor air are originated from outdoor sources. PRACTICAL IMPLICATIONS: Indoor particulate pollution has received more attentions in Asia. This study presents a case study regarding the fine particulate matter and its carbonaceous compositions at six residential homes in Hong Kong. The characteristics and relationship of atmospheric organic and elemental carbon were discussed indoors and outdoors. The distribution of eight carbon fractions was first reported in indoor samples to interpret potential sources of indoor carbonaceous particles. The data set can provide significant scientific basis for indoor air quality and epidemiology study in Hong Kong and China.     

Aerosol optical depth, aerosol composition and air pollution during summer and winter conditions in Budapest

The dependence of aerosol optical depth (AOD) on air particulate concentrations in the mixing layer height (MLH) was studied in Budapest in July 2003 and January 2004. During the campaigns gaseous (CO, SO(2), NO(x), O(3)), solid components (PM(2.5), PM(10)), as well as ionic species (ammonium, sulfate and nitrate) were measured at several urban and suburban sites. Additional data were collected from the Budapest air quality monitoring network. AOD was measured by a ground-based sun photometer. The mixing layer height and other common meteorological parameters were recorded. A linear relationship was found between the AOD and the columnar aerosol burden; the best linear fit (R(2)=0.96) was obtained for the secondary sulfate aerosol due to its mostly homogeneous spatial distribution and its optically active size range. The linear relationship is less pronounced for the PM(2.5) and PM(10) fractions since local emissions are very heterogeneous in time and space. The results indicate the importance of the mixing layer height in determining pollutant concentrations. During the winter campaign, when the boundary layer decreases to levels in between the altitudes of the sampling stations, measured concentrations showed significant differences due to different local sources and long-range transport. In the MLH time series unexpected nocturnal peaks were observed. The nocturnal increase of the MLH coincided with decreasing concentrations of all pollutants except for ozone; the ozone concentration increase indicates nocturnal vertical mixing between different air layers.     

Seasonal variations and mass closure analysis of particulate matter in Hong Kong

The chemical characteristics of ambient particulate matters in urban and rural areas of Hong Kong were determined in this study. A monitoring program starting from November 2000 to February 2001 (winter) and June 2001 to August 2001 (summer) for PM10 and PM2.5 was performed at three monitoring stations in Hong Kong. Twenty-four-hour PM10 and PM2.5 samples were collected once every 6 days at two urban sites, PolyU and KT, and every 12 days at a background site, HT, with Hi-Vol samplers. High concentrations of OC, EC (except in PolyU), water-soluble ions and elements were observed in winter among the three sampling sites for PM10 and PM2.5 fractions. Seasonal variations were significant in background HT. Dilution effect due to the increase in mixing depth and precipitation in summer reduced the concentrations of particulate matters. Long-range transport could contribute to the higher concentrations of particulate matter in the winter. Chemical mass closure calculations were performed for PM10 and PM2.5 observed. Mass closure improved when separate factors (1.4 and 1.9 respectively) were used to convert water-soluble organic carbon (WSOC) and water-insoluble organic carbon (WINSOC) into corresponding organic masses. The urban sites showed high percentages of water-soluble ions in winter and high percentages of carbonaceous species in summer. Better results were obtained for the chemical mass closure analysis in winter than in summer. High temperature and solar radiation in summer increased the rate of the complex photochemical reaction in the atmosphere. Therefore the chemical mass closure analysis would underestimate the volatized species and secondary aerosols during summer.     

Source apportionment of indoor residential fine particulate matter using land use regression and constrained factor analysis

Source contributions to urban fine particulate matter (PM(2.5) ) have been modelled using land use regression (LUR) and factor analysis (FA). However, people spend more time indoors, where these methods are less explored. We collected 3-4- day samples of nitrogen dioxide and PM(2.5) inside and outside of 43 homes in summer and winter, 2003-2005, in and around Boston, Massachusetts. Particle filters were analysed for black carbon and trace element concentrations using reflectometry, X-ray fluorescence (XRF), and high-resolution inductively coupled mass spectrometry (ICP-MS). We regressed indoor against outdoor concentrations modified by ventilation, isolating the indoor-attributable fraction, and then applied constrained FA to identify source factors in indoor concentrations and residuals. Finally, we developed LUR predictive models using GIS-based outdoor source indicators and questionnaire data on indoor sources. FA using concentrations and residuals reasonably separated outdoor (long-range transport/meteorology, fuel oil/diesel, road dust) from indoor sources (combustion, smoking, cleaning). Multivariate LUR regression models for factors from concentrations and indoor residuals showed limited predictive power, but corroborated some indoor and outdoor factor interpretations. Our approach to validating source interpretations using LUR methods provides direction for studies characterizing indoor and outdoor source contributions to indoor cocentrations. PRACTICAL IMPLICATIONS: By merging indoor-outdoor modeling, factor analysis, and LUR-style predictive regression modeling, we have added to previous source apportionment studies by attempting to corroborate factor interpretations. Our methods and results support the possibility that indoor exposures may be modeled for epidemiologic studies, provided adequate sample size and variability to identify indoor and outdoor source contributions. Using these techniques, epidemiologic studies can more clearly examine exposures to indoor sources and indoor penetration of source-specific components, reduce exposure misclassification, and improve the characterization of the relationship between particle constituents and health effects.     

Source apportionment of PM(2.5) and selected hazardous air pollutants in Seattle

The potential benefits of combining the speciated PM(2.5) and VOCs data in source apportionment analysis for identification of additional sources remain unclear. We analyzed the speciated PM(2.5) and VOCs data collected at the Beacon Hill in Seattle, WA between 2000 and 2004 with the Multilinear Engine (ME-2) to quantify source contributions to the mixture of hazardous air pollutants (HAPs). We used the 'missing mass', defined as the concentration of the measured total particle mass minus the sum of all analyzed species, as an additional variable and implemented an auxiliary equation to constrain the sum of all species mass fractions to be 100%. Regardless of whether the above constraint was implemented and/or the additional VOCs data were included with the PM(2.5) data, the models identified that wood burning (24%-31%), secondary sulfate (20%-24%) and secondary nitrate (15%-20%) were the main contributors to PM(2.5). Using only PM(2.5) data, the model distinguished two diesel features with the 100% constraint, but identified only one diesel feature without the constraint. When both PM(2.5) and VOCs data were used, one additional feature was identified as the major contributor (26%) to total VOC mass. Adding VOCs data to the speciated PM(2.5) data in source apportionment modeling resulted in more accurate source contribution estimates for combustion related sources as evidenced by the less 'missing mass' percentage in PM(2.5). Using the source contribution estimates, we evaluated the validity of using black carbon (BC) as a surrogate for diesel exhaust. We found that BC measured with an aethalometer at 370 nm and 880 nm had reasonable correlations with the estimated concentrations of diesel particulate matters (r>0.7), as well as with the estimated concentrations of wood burning particles during the heating seasons (r=0.56-0.66). This indicates that the BC is not a unique tracer for either source. The difference in BC between 370 and 880 nm, however, correlated well exclusively with the estimated wood smoke source (r=0.59) and may be used to separate wood smoke from diesel exhaust. Thus, when multiple BC related sources exist in the same monitoring environment, additional data processing or modeling of the BC measurements is needed before these measurements could be used to represent the diesel exhaust.     

PM2.5 chemical composition in Hong Kong: urban and regional variations

Chemically speciated PM2.5 measurements were made at roadside, urban, and rural background sites in Hong Kong for 1 year during 2000/2001 to determine the spatial and temporal variations of PM2.5 mass and chemical composition in this highly populated region. Annual average PM2.5 concentrations at the urban and rural sites were 34.1 and 23.7 microg m(-3), respectively, approximately 50-100% higher than the United States' annual average National Ambient Air Quality Standard (NAAQS) of 15 microg m(-3). Daily PM2.5 concentrations exceeded the U.S. 24-h NAAQS of 65 microg m(-3) on 19 days, reaching 131+/-8 microg m(-3) at the roadside site on 02/28/2001. Carbonaceous aerosol is the largest contributor to PM2.5 mass (explaining 52-75% of PM2.5 mass at the two urban sites and 32% at the background site), followed by ammonium sulfate (ranging from 23% to 37% at the two urban sites and 51% at the background site). Ammonium sulfate and crustal concentrations showed more uniform spatial distributions, while the largest urban-rural contrasts found in carbonaceous aerosol (likely due to emissions from on-road gasoline and diesel vehicles). Marine influences accounted for 7% of the mass at the background site (more than twice as much as at the two urban sites). Ternary diagrams are utilized to illustrate the different spatial patterns.     

Source apportionment of PM10 and PM2.5 in Milan (Italy) using receptor modelling

In this paper a source apportionment of particulate matter pollution in the urban area of Milan (Italy) is given. Results of PM10 and PM2.5 mass and elemental concentrations from a 1-year monitoring campaign are presented. Mean annual and daily PM10 levels are compared with the limits of the EU Air Quality Directive EC/30/1999 and the results show that the limit values established would not be met in the urban area of Milan or the large surrounding area. Moreover, high levels of PM2.5 are registered and this fraction constitutes a high portion of the PM10 mass. In Milan the winter period is characterised by a high degree of air pollution due to a greater contribution of emissions and to adverse meteorological and thermodynamic conditions of the atmosphere. The application of multivariate techniques and receptor modelling (PCFA, APCFA) to the whole data-set led to the identification of the main emitting sources and to the source apportionment of PM10 and PM2.5 in Milan. The most important sources were identified as 'soil dust', 'traffic', 'industry' and 'secondary compounds' for PM10 and as 'soil dust', 'anthropogenic' and 'secondary compounds' for PM2.5, explaining the greatest part of the total variance (91% and 75%, respectively).     

PM10 speciation and determination of air quality target levels. A case study in a highly industrialized area of Spain

The paper shows how PM speciation studies allow the evaluation of the strategies to be followed to diminish PM pollution in highly industrialized areas with a large number of potential pollution sources. Evolution of levels and speciation of PM10 in the ceramic producing area of Castelló (East Spain) was studied from April 2002 until December 2005. PM10 levels were measured at one rural (Borriana-rural), two suburban (Almassora and Onda) and three urban (Borriana-urban, L'Alcora and Vila-real) sites, all influenced by the ceramics industry. Average PM10 levels varied between 27 and 36 microg/m3 for the study period. Evaluation of 1996-2005 PM data from Onda shows a clear decrease of PM levels since the beginning of 2002. Summer peak levels and winter minima occurred at both rural and suburban sites, whereas urban sites had no clear seasonal trend, with high PM10 episodes being due variously to local, regional, and African dust intrusion events. PM10 chemical analysis at four of the sites showed the dominant constituent to be mineral matter, exceeding by 5-12 microg/m3 the usual ranges of annual mineral loadings in PM10 at comparable Spanish urban or regional background sites with no industrial influence. Given current PM10 loadings, we recommend a lowering target of 3-5 microg/m3 of the annual mean at the urban sites, which should be achievable given available emission abatement techniques.     

Source apportionment of PM(10) and PM(2.5) using positive matrix factorization and chemical mass balance in Izmir, Turkey

Atmospheric particulate matter (PM) fractions (PM(10) and PM(2.5)) were sampled concurrently between June 2004 and May 2005 at two sites (urban and suburban) in Izmir, Turkey. The elemental composition of PM (Al, Ba, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Sr, V, and Zn) was determined using inductively coupled plasma-optical emission spectrometer. Elemental compositions of several PM sources were also characterized. Positive matrix factorization (PMF) and chemical mass balance modeling (CMB) were applied to determine the PM sources and their contributions to air concentrations. The major contributors to PM were fossil fuel burning, traffic emissions, mineral industries and marine salt according to the PMF results. However, undetermined parts were more than 40%. On the other hand, the contributions to PM could be determined completely by CMB, and the dominant contributor was traffic with >70% at the two sites. Fossil fuel burning, mineral industries, marine salt and natural gas-fired power plant were the minor contributors.     

Assessment of inorganic content of PM(2.5) particles sampled in a rural area north-east of Hanoi, Vietnam

Atmospheric aerosols from seven rural sites in northern Vietnam, east of Hanoi, were sampled and analyzed. The aim of the study was to evaluate trace elemental and black carbon (BC) concentrations in fine particles (PM(2.5)) and to investigate the influence of the Pha Lai power plant and other pollution sources on regional air quality. Seven measurement stations were set up at selected rural sites and a campaign consisting of 12 two-day measurement periods was conducted from the end of May until the end of October 2000. At each location a pair of samplers was installed consisting of a cyclone loaded with Teflon filters and a modified Millipore air monitoring cartridge loaded with glass fibre filters. The obtained samples were analyzed for trace elements by Energy Dispersive X-ray Fluorescence (EDXRF), while a black smoke detector was used for BC analysis. Seventeen trace elements were analyzed; Br, Ca, Cl, Cr, Cu, Fe, K, Mn, Ni, Pb, Rb, S, Se, Sr, Ti, V and Zn and their concentrations evaluated. The results showed that BC, Ca, Cl, Fe, K and S dominated in the sampled atmospheric aerosols. The measured concentrations of the potentially hazardous trace elements Cr, Mn, Ni and Pb were all below the limits defined by Vietnamese standards of ambient air quality. Statistical evaluations indicated that coal and heavy fuel oil combustion were major sources of atmospheric pollutants in the area and that biomass burning and road transport had a marked influence on regional air quality. It was concluded that the Pha Lai power plant was the major source of coal combustion emissions. Trace element emissions originating from river transportation were suggested as another major source of atmospheric pollutants. The results indicate that the elemental concentrations in PM(2.5) are strongly influenced by seasonal variations. Further measurements are required to identify the impact of long-range transported continental air masses on the air quality of the investigated rural area.