A review of polychlorinated biphenyls (PCBs) pollution in indoor air environment

Polychlorinated biphenyls (PCBs) were widely used in industrial production due to the unique physical and chemical properties. As a kind of persistent organic pollutants, the PCBs would lead to environment pollution and cause serious problems for human health. Thus, they have been banned since the 1980s due to the environment pollution in the past years. Indoor air is the most direct and important environment medium to human beings; thus, the PCBs pollution research in indoor air is important for the protection of human health. This paper introduces the industrial application and potential harm of PCBs, summarizes the sampling, extracting, and analytical methods of environment monitoring, and compares the indoor air levels of urban areas with those of industrial areas in different countries according to various reports. This paper can provide a basic summary for PCBs pollution control in the indoor air environment.

Implications: The review of PCBs pollution in indoor air in China is still limited. In this paper, we introduce the industrial application and potential harm of PCBs, summarize the sampling, extracting, and analytical methods of environment monitoring, and compare the indoor air levels of urban areas with industrial areas in different countries according to various reports.     

Mapping air quality zones for coastal urban centers

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land–sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year’s worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates.

Implications: A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land–sea breeze effects that can be used to manage local air quality in areas of similar microclimates.     

The use of wind fields in a land use regression model to predict air pollution concentrations for health exposure studies

A methodology is developed to include wind flow effects in land use regression (LUR) models for predicting nitrogen dioxide (NO₂) concentrations for health exposure studies. NO₂ is widely used in health studies as an indicator of traffic-generated air pollution in urban areas. Incorporation of high-resolution interpolated observed wind direction from a network of 38 weather stations in a LUR model improved NO₂ concentration estimates in densely populated, high traffic and industrial/business areas in Toronto-Hamilton urban airshed (THUA) of Ontario, Canada. These small-area variations in air pollution concentrations that are probably more important for health exposure studies may not be detected by sparse continuous air pollution monitoring network or conventional interpolation methods. Observed wind fields were also compared with wind fields generated by Global Environmental Multiscale-High resolution Model Application Project (GEM-HiMAP) to explore the feasibility of using regional weather forecasting model simulated wind fields in LUR models when observed data are either sparse or not available. While GEM-HiMAP predicted wind fields well at large scales, it was unable to resolve wind flow patterns at smaller scales. These results suggest caution and careful evaluation of regional weather forecasting model simulated wind fields before incorporating into human exposure models for health studies. This study has demonstrated that wind fields may be integrated into the land use regression framework. Such integration has a discernable influence on both the overall model prediction and perhaps more importantly for health effects assessment on the relative spatial distribution of traffic pollution throughout the THUA. Methodology developed in this study may be applied in other large urban areas across the world.     

Spatial variation of airborne pollutant concentrations in Brisbane,Australia and its potential impact on population exposure assessment

Spread of air pollution sources and non-uniform mixing conditions in urban or regional air sheds often result in spatial variation of pollutant concentrations over different parts of the air sheds. A comprehensive understanding of this variation of concentrations is imperative for informed planning, monitoring and assessment in a range of critical areas including assessment of monitoring network efficiency or assessment of population exposure variation as a function of the location in the city. The aims of this work were to study the citywide variability of pollutants as measured by “urban background” type monitoring stations and to interpret the results in relation to the applicability of the data to population exposure assessments and the network efficiency. A comparison between ambient concentrations of NO_x, ozone and PM₁₀ was made for three stations in the Brisbane air shed network. The best correlated between the three stations were ozone concentrations followed by NO_x concentration, with the worst correlations observed for PM₁₀. With a few exceptions correlations of all pollutants between the stations were statistically significant. Marginally better were the correlations for the lower concentrations of pollutants that represent urban background, over the correlations for higher concentrations, representing peak values. Implications of these findings on application of the monitoring data to air-quality management, as well as the need for further investigations has been discussed.     

A Survey Technique for Determining The Representativeness of Urban Air Monitoring Stations With Respect to Carbon Monoxide

An air quality survey technique for measuring the horizontal spatial variation of carbon monoxide concentrations in urban areas is described; it was used to determine how representative an urban air monitoring station is of concentrations throughout the city.

The survey technique was applied in San Jose, Calif., where 1128 samples were collected over a six-month period and were compared with the values recorded simultaneously at the urban air monitoring station. All samples were collected at “breathing height” within a 13-square-mile grid which included the downtown area as well as surrounding residential and industrial locations. Three basic sampling strategies were employed to answer specific questions about the distribution of carbon monoxide concentration: (7) walking sampling, in which samples were obtained while walking along the sidewalks of congested downtown streets, (2) random spatial sampling, in which samples were collected at randomly selected points in the urban grid, and (3) specialized sampling in the immediate vicinity of the air monitoring station.

The results indicate that pedestrians on downtown streets in San Jose can be exposed to concentrations above the federal air quality standards without these values being observed at the air monitoring station. There also is evidence that, at any instant of time, similar values of carbon monoxide exist throughout this city (within a 13-square mile area), provided that measurements are not made in close proximity to streets. Furthermore, the higher concentrations observed in the immediate vicinity of streets decrease quite rapidly with increasing horizontal distance from these streets.

These findings, in the view of the authors, raise serious doubts as to whether it is possible to determine if air quality standards as currently defined are actually being met in urban areas using data from present-day air monitoring stations.     

Interactive design of urban level air quality monitoring network

An interactive optimization method for designing an air quality monitoring network in an urban area is proposed. The main purpose is to determine representative areas of monitoring stations rather than their precise locations. Two topologies are introduced to define similarities among pre-divided uniform meshes. The first is derived from the differences of long-term averages of pollutant concentrations between every two meshes and used in the Ward method clustering. The second is obtained by the cross-impacts between pairs of meshes and used as a constraint in the clustering process. Participation of specialists in the optimization process is allowed in such a way that they can modify the second topology by taking account of economic and physical conditions as well as inaccuracy of simulation models. This technique is applied to the NO_x monitoring network of Kyoto, Japan.     

Long-term assessment of particulate matter using CHIMERE model

Particulate matter (PM) and aerosols have became a critical pollutant and object of several research applications, due to their increasing levels, especially in urban areas, causing air pollution problems and thus effects on human health. The main purpose of this study is to perform a first long-term air quality assessment for Portugal, regarding aerosols and PM pollution. The CHIMERE chemistry-transport model, forced by the MM5 meteorological fields, was applied over Portugal for 2001 year, with 10 km horizontal resolution, using an emission inventory obtained from a spatial top-down disaggregation of the 2001 national inventory database. The evaluation model exercise shows a model trend to overestimate particulate pollution episodes (peaks) at urban sites, especially in winter season. This could be due to an underprediction of the winter model vertical mixing and also to an overestimation of PM emissions. Simulated inorganic components (ammonium and sulfate) and secondary organic aerosols (SOA) were compared to measurements taken at Aveiro (northwest coast of Portugal). An underestimation of the three components was verified. However, the model is able to predict their seasonal variation. Nevertheless, as a first approach, and despite the complex topography and coastal location of Portugal affected by sea salt natural aerosols emissions, the results obtained show that the model reproduces the PM levels, temporal evolution, and spatial patterns. The concentration maps reveal that the areas with high PM values are covered by the air quality monitoring network.     

Assessment of traffic-related air pollution in two street canyons in Paris: implications for exposure studies

The small-scale spatial variability of air pollution observed in urban areas has created concern about the representativeness of measurements used in exposure studies. It is suspected that limit values for traffic-related pollutants may be exceeded near busy streets, although respected at urban background sites. In order to assess spatial concentration gradients and identify weather conditions that might induce air pollution episodes in urban areas, different sampling and modelling techniques were studied.Two intensive monitoring campaigns were carried out in typical street canyons in Paris during winter and summer. Steep cross-road and vertical concentration gradients were observed within the canyons, in addition to large differences between roadside and background levels. Low winds and winds parallel to the street axis were identified as the worst dispersion conditions. The correlation between the measured compounds gave an insight into their sources and fate. An empirical relationship between CO and benzene was established. Two relatively simple mathematical models and an algorithm describing vertical pollutant dispersion were used. The combination of monitoring and modelling techniques proposed in this study can be seen as a reliable and cost-effective method for assessing air quality in urban micro-environments. These findings may have important implications in designing monitoring studies to support investigation on the health effects of traffic-related air pollution.     

A multi-objective assessment of an air quality monitoring network using environmental,economic, and social indicators and GIS-based models

In the United States, air pollution is primarily measured by Air Quality Monitoring Networks (AQMN). These AQMNs have multiple objectives, including characterizing pollution patterns, protecting the public health, and determining compliance with air quality standards. In 2006, the U.S. Environmental Protection Agency issued a directive that air pollution agencies assess the performance of their AQMNs. Although various methods to design and assess AQMNs exist, here we demonstrate a geographic information system (GIS)-based approach that combines environmental, economic, and social indicators through the assessment of the ozone (O₃) and particulate matter (PM10) networks in Maricopa County, Arizona. The assessment was conducted in three phases: (1) to evaluate the performance of the existing networks, (2) to identify areas that would benefit from the addition of new monitoring stations, and (3) to recommend changes to the AQMN. A comprehensive set of indicators was created for evaluating differing aspects of the AQMNs’ objectives, and weights were applied to emphasize important indicators. Indicators were also classified according to their sustainable development goal. Our results showed that O₃ was well represented in the county with some redundancy in terms of the urban monitors. The addition of weights to the indicators only had a minimal effect on the results. For O₃, urban monitors had greater social scores, while rural monitors had greater environmental scores. The results did not suggest a need for adding more O₃ monitoring sites. For PM10, clustered urban monitors were redundant, and weights also had a minimal effect on the results. The clustered urban monitors had overall low scores; sites near point sources had high environmental scores. Several areas were identified as needing additional PM10 monitors. This study demonstrates the usefulness of a multi-indicator approach to assess AQMNs. Network managers and planners may use this method to assess the performance of air quality monitoring networks in urban regions.

Implications:The U.S. Environmental Protection Agency issued a directive in 2006 that air pollution agencies assess the performance of their AQMNs; as a result, we developed a GIS-based, multi-objective assessment approach that integrates environmental, economic, and social indicators, and demonstrates its use through assessing the O₃ and PM₁₀ monitoring networks in the Phoenix metropolitan area. We exhibit a method of assessing network performance and identifying areas that would benefit from new monitoring stations; also, we demonstrate the effect of adding weights to the indicators. Our study shows that using a multi-indicator approach gave detailed assessment results for the Phoenix AQMN.     

Stochastic analysis of concentration field in a wake region

Introduction  

Identifying geographic locations in urban areas from which air pollutants enter the atmosphere is one of the most important information needed to develop effective mitigation strategies for pollution control.     

Ambient Oxidant Exposure andHealth Costs in the United States—1973

The body of information presented in this paper is directed to policy makers and administrators involved in the evaluation and assessment of damages caused by oxidant air pollution on human health and welfare and of possible benefits of control.

To provide a comparison of some of the benefits that can be obtained by reducing photochemical oxidant levels, estimated health costs were derived from data relating adverse health effects to hourly oxidant concentrations. Hourly oxidant or ozone concentrations were measured at approximately 400 monitoring stations scattered throughout the U.S. Most of these sites were located in major urban areas or in other areas where high oxidant concentrations prevailed. Estimates of populations at risk and per capita health costs were generated for those areas where oxidant data was available.

During the period 1971-1973, nearly two-thirds of the U.S. population resided in areas where the hourly primary standard for oxidants of 160 µg/m³ was exceeded. The total annual health cost attributable to oxidants was estimated to range from $120 to over $240 million in the U.S.     

Assessing the spatial distribution of nitrogen dioxide in London,Ontario

Land use regression (LUR) models have been widely used to characterize the spatial distribution of urban air pollution and estimate exposure in epidemiologic studies. However, spatial patterns of air pollution vary greatly between cities due to local source type and distribution. London, Ontario, Canada, is a medium-sized city with relatively few and isolated industrial point sources, which allowed the study to focus on the contribution of different transportation sectors to urban air pollution. This study used LUR models to estimate the spatial distribution of nitrogen dioxide (NO₂) and to identify local sources influencing NO₂ concentrations in London, ON. Passive air sampling was conducted at 50 locations throughout London over a 2-week period in May–June 2010. NO₂ concentrations at the monitored locations ranged from 2.8 to 8.9 ppb, with a median of 5.2 ppb. Industrial land use, dwelling density, distance to highway, traffic density, and length of railways were significant predictors of NO₂ concentrations in the final LUR model, which explained 78% of NO₂ variability in London. Traffic and dwelling density explained most of the variation in NO₂ concentrations, which is consistent with LUR models developed in other Canadian cities. We also observed the importance of local characteristics. Specifically, 17% of the variation was explained by distance to highways, which included the impacts of heavily traveled corridors transecting the southern periphery of the city. Two large railway yards and railway lines throughout central areas of the city explained 9% of NO₂ variability. These results confirm the importance of traditional LUR variables and highlight the importance of including a broader array of local sources in LUR modeling. Finally, future analyses will use the model developed in this study to investigate the association between ambient air pollution and cardiovascular disease outcomes, including plaque burden, cholesterol, and hypertension.

Implications: Monitoring and modeling of NO₂ throughout the city of London represents an important step toward assessing air pollution health effects in a mid-sized Canadian city. The study supports the introduction of railways to LUR modeling of NO₂. Railways explained approximately 9% of the variability in ambient NO₂ concentrations in London, which suggests that local sources captured by land-use indicators may contribute to the efficacy of LUR models. These findings provide insights relevant to other medium and smaller sized cities with similar land use and transportation infrastructure. Furthermore, London is a central hub for medical research and treatment in southwestern Ontario, with facilities such as the Robarts Research Institute, London Regional Cancer Program (LRCP), and Stroke Prevention & Atherosclerosis Research Centre (SPARC). The models developed in this study will provide estimates of exposure for future analyses examining air pollution health effects in this data-rich population.     

Personal exposure to fine particulate matter concentrations in central business district of a tropical coastal city

In the present study, personal exposure to fine particulate matter (particulate matter with an aerodynamic diameter <2.5 μm [PM_2.5]) concentrations in an urban hotspot (central business district [CBD]) was investigated. The PM monitoring campaigns were carried out at an urban hotspot from June to October 2015. The personal exposure monitoring was performed during three different time periods, i.e., morning (8 a.m.?9 a.m.), afternoon (12.30 p.m.–1.30 p.m.), and evening (4 p.m.–5 p.m.), to cover both the peak and lean hour activities of the CBD. The median PM_2.5 concentrations were 38.1, 34.9, and 40.4 µg/m³ during the morning, afternoon, and evening hours on the weekends. During weekdays, the median PM_2.5 concentrations were 59.5, 29.6, and 36.6 µg/m³ in the morning, afternoon, and evening hours, respectively. It was observed that the combined effect of traffic emissions, complex land use, and micrometeorological conditions created localized air pollution hotspots. Furthermore, the total PM_2.5 lung dose levels for an exposure duration of 1 hr were 8.7 ± 5.7 and 12.3 ± 5.2 µg at CBD during weekends and weekdays, respectively, as compared with 2.5 ± 0.8 µg at the urban background (UB). This study emphasizes the need for mobile measurement for short-term personal exposure assessment complementing the fixed air quality monitoring.

Implications: Personal exposure monitoring at an urban hotspot indicated space and time variation in PM concentrations that is not captured by the fixed air quality monitoring networks. The short-term exposure to higher concentrations can have a significant impact on health that need to be considered for the health risk–based air quality management. The study emphasizes the need of hotspot-based monitoring complementing the already existing fixed air quality monitoring in urban areas. The personal exposure patterns at hotspots can provide additional insight into sustainable urban planning.     

Assessment of ambient air quality in the port of Naples

Two experimental monitoring campaigns were carried out in 2012 to investigate the air quality in the port of Naples, the most important in southern Italy for traffic of passengers and one of the most important for goods. Therefore, it represents an important air pollution source located close to the city of Naples. The concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and BTEX (benzene, toluene, ethylbenzene, and xylenes) in the air were measured at 15 points inside the Naples port area through the use of passive samplers. In addition, a mobile laboratory was positioned in a fixed point inside the port area to measure continuous concentration of pollutants together with particulate matter, ambient parameters, and wind direction and intensity. The pollution levels monitored were compared with those observed in the urban area of Naples and in other Mediterranean ports. Even though the observation time was limited, measured concentrations were also compared with limit values established by European legislation. All the measured pollutants were below the limits with the exception of nitrogen dioxide: its average concentration during the exposition time exceeded the yearly limit value. A spatial analysis of data, according to the measured wind direction and intensity, provided information about the effects that ship emissions have on ambient air quality in the port area. The main evidence indicates that ship emissions influence sulfur dioxide concentration more than any other pollutants analyzed.

Implications: Two monitoring campaigns were carried out to measure BTEX, SO₂, NO₂, and PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) air concentrations in the port of Naples. NO₂ hourly average and PM₁₀ daily average comply with European legislative standards. Spatial variation of pollutants long the axis corresponding to the prevailing wind direction seems to indicate a certain influence of ship emissions for SO₂. For NO₂ and PM₁₀, a correlation between concentrations in the harbor and those measured by the air quality monitoring stations sited in the urban area of Naples was observed, indicating a possible contribution of the near road traffic to the air pollution in the port of Naples.     

Large-Scale Weather Influences on Community Air Pollution Potential in the United States

This paper describes the large-scale weather features that typically are associated with relatively rapid and slow atmospheric dispersion. Specific examples for some well-known air pollution incidents are illustrated and discussed. Particular attention is paid to the features of quasi-stagnating anticyclones, the typical weather system associated with persistent and extensive areas of sluggish dispersion. On the large scale, the basic quantitative parameters of dispersion over urban areas are the mixing height and the wind speed averaged through that height. These parameters are defined and discussed. Mean morning and afternoon mixing heights and wind speeds are presented for four locations across the United States, illustrating their diurnal, seasonal, and spatial variations. Also for these four locations, data are given on the climatological occurrence of periods during which critical values of the basic parameters were not exceeded. The spatial distributions of mixing heights and average wind speeds during a well-documented air pollution episode are presented.     

Assessment of trace metal air pollution in Paris using slurry-TXRF analysis on cemetery mosses

Mosses are useful, ubiquitous accumulation biomonitors and as such can be used for biomonitoring surveys. However, the biomonitoring of atmospheric pollution can be compromised in urban contexts if the targeted biomonitors are regularly disturbed, irregularly distributed, or are difficult to access. Here, we test the hypothesis that cemeteries are appropriate moss sampling sites for the evaluation of air pollution in urban areas. We sampled mosses growing on gravestones in 21 urban and peri-urban cemeteries in the Paris metropolitan area. We focused on Grimmia pulvinata (Hedwig) Smith, a species abundantly found in all studied cemeteries and very common in Europe. The concentration of Al, As, Br, Ca, Ce, Cl, Cr, Cu, Fe, K, Mn, Ni, V, P, Pb, Rb, S, Sr, Ti, and Zn was determined by a total reflection X-ray fluorescence technique coupled with a slurry sampling method (slurry-TXRF). This method avoids a digestion step, reduces the risk of sample contamination, and works even at low sample quantities. Elemental markers of road traffic indicated that the highest polluted cemeteries were located near the highly frequented Parisian ring road and under the influence of prevailing winds. The sites with the lowest pollution were found not only in the peri-urban cemeteries, adjoining forest or farming landscapes, but also in the large and relatively wooded cemeteries located in the center of Paris. Our results suggest that (1) slurry-TXRF might be successfully used with moss material, (2) G. pulvinata might be a good biomonitor of trace metals air pollution in urban context, and (3) cemetery moss sampling could be a useful complement for monitoring urban areas.

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Graphical abstract We tested the hypothesis that cemeteries are appropriate moss sampling sites for the evaluation of air pollution in urban areas. We sampled 110 moss cushions (Grimmia pulvinata) growing on gravestones in 21 urban and peri-urban cemeteries in the Paris metropolitan area. The concentration of 20 elements in mosses was determined by a total reflection X-ray fluorescence technique coupled with a slurry sampling method. Statistical analysis revealed that: - Urbanized Parisian areas crossed by traffic roads have the highest polluted cemeteries with a strong influence of main wind direction on the distribution of air pollutants - As expected, small cemeteries with low tree density were heavily polluted - Less obvious, large green spaces such as large cemeteries (Père Lachaise, Montmartre, Montparnasse) in the center of a dense metropolis like Paris present the same level of atmospheric trace metal pollution as cemeteries in less urbanized areas or nearing a very large forest. This suggests that even in densely urbanized areas, there is more spatial variability in pollution distribution than usually assumed and that large urban areas with low traffic and green filters such as trees are likely to intercept air pollutants

     

Environmental forensic investigation of the air pollution from a cement manufacturing unit

Abstract

Cement manufacturing is a process that results in the emission of significant quantities of suspended particulate matter (SPM) to the ambient air. An environmental forensic investigation was carried out in the surroundings of a major cement manufacturing unit at a place called Coimbatore in the southern Indian state of Tamil Nadu. The investigation was carried out to identify the contribution of the cement manufacturing unit to the SPM concentration of the surrounding air environment. The sampling points’ selection and sample collection were done following the principles outlined in the INTERPOL Manual for Pollution Crime Forensic Investigation. On-site monitoring of the air samples was carried out using Mini Laser Aerosol Spectrometer (GRIMM, Mini-LAS Model 11R). The instrument was capable of measuring particles ranging from 0.25 to 32 µm and classifying them into 31 size channels. The test results at majority of the monitoring locations were well above the limits specified in the National Ambient Air Quality Standards of India. Microscopic studies of the dust samples were carried out for surface texture and particle shape. The spatial distribution of particles was analysed using geographic information system (GIS) for the visual identification of the extent of the pollution by keeping the cement factory as the focal point. The results from the GIS and microscopic analysis established the role of the cement factory in the particulate matter pollution of its surroundings, specifically in the areas North-West of the factory. The successfully adopted procedure can serve as a guideline for the environmental forensic investigation of similar pollution incidences.     

Measurement of Photochemical Air Pollution with a Sensitive Monitoring Plant

With newly developed monitoring techniques, investigators used the sensitive tobacco variety, Bel-W3, as a monitor for photochemical air pollution at different locations within 75 miles of Cincinnati, Ohio. Observations during the summers of 1966 through 1968 revealed almost daily injury to monitoring plants, fairly uniform total seasonal injury at all locations, and a marked variation in both oxidant and injury from one season to another within the city. The relationship between oxidant level and injury was not found to be consistent.     

Development of Criteria for Siting Air Monitoring Stations

A critical problem arises if one attempts to compare data from air monitoring stations in different cities, because there are so many differences in monitoring site locations. Some air monitoring stations are on the 6 th and 8 th floors of tall buildings in downtown areas; some are at ground level beside streets with heavy traffic; some are in residential areas with little traffic or industry; and some are in suburban or nonurban areas. Unfortunately, there is ample evidence that the location of a monitoring station relative to nearby sources (such as highways) affects the values observed at the station, particularly for carbon monoxide and other vehicular pollutants. Thus, a standardized system of site selection, such as the one proposed here, appears essential to improve the comparability and meaningfulness of data obtained from different air monitoring stations throughout the Nation.     

Using PM10 geochemical maps for defining the origin of atmospheric pollution in Andalusia (Southern Spain)

In this work we present a detailed study of atmospheric PM₁₀ pollution in Andalusia (Southern Spain) based on geochemical maps. The study includes determination of PM₁₀ levels and bulk chemical composition with samples from 17 representative monitoring stations (rural, urban background, traffic hot spot, and urban zones with industrial influence) during 2007. The knowledge of background levels and concentrations of relevant chemical compounds and elements allows the quantification of the main sources of pollution in relevant cities and sites of ecological interest.In comparison to other stations in Spain and mainland Europe, PM₁₀ in Andalusia is characterized by high levels of crustal matter and secondary inorganic components (SIC). This has been attributed to the following causes: 1) High road traffic and industrial emissions, 2) High frequency of North African air mass outbreaks contributing between 3 and 4 μg m^?3 in western Andalusia and 4–7 μg m^?3 in eastern Andalusia, and 3) Climate factors such as low rainfall, dry soils favouring resuspension, and high photochemical activity.Atmospheric particulate matter in urban areas located in the vicinity of industrial estates is enriched in secondary inorganic compounds and metals. Three main hot spots have been identified according their high trace element concentrations: Huelva (As, Cu, Zn, Se, and Bi), Strait of Gibraltar (V, Ni, Cr, and Co) and Bailén (V and Ni). The transport of pollutants from cities and industrial estates to areas of ecological interest (e.g. Doñana National Park) has been found to cause the increase in background levels in a number of trace elements (e.g. As) in the air. An important outcome of this study is that geochemical maps of atmospheric matter are a powerful tool for illustrating spatial variation patterns of geochemical components and identifying specific pollution hot spots.