Characterizing air pollution in two low-income neighborhoods in Accra, Ghana

Sub-Saharan Africa has the highest rate of urban population growth in the world, with a large number of urban residents living in low-income "slum" neighborhoods. We conducted a study for an initial assessment of the levels and spatial and/or temporal patterns of multiple pollutants in the ambient air in two low-income neighborhoods in Accra, Ghana. Over a 3-week period we measured (i) 24-hour integrated PM(10) and PM(2.5) mass at four roof-top fixed sites, also used for particle speciation; (ii) continuous PM(10) and PM(2.5) at one fixed site; and (iii) 96-hour integrated concentration of sulfur dioxide (SO(2)) and nitrogen dioxide (NO(2)) at 30 fixed sites. We also conducted seven consecutive days of mobile monitoring of PM(10) and PM(2.5) mass and submicron particle count. PM(10) ranged from 57.9 to 93.6 microg/m(3) at the four sites, with a weighted average of 71.8 microg/m(3) and PM(2.5) from 22.3 to 40.2 microg/m(3), with an average of 27.4 microg/m(3). PM(2.5)/PM(10) ratio at the four fixed sites ranged from 0.33 to 0.43. Elemental carbon (EC) was 10-11% of PM(2.5) mass at all four measurement sites; organic matter (OM) formed slightly less than 50% of PM(2.5) mass. Cl, K, and S had the largest elemental contributions to PM(2.5) mass, and Cl, Si, Ca, Fe, and Al to coarse particles. SO(2) and NO(2) concentrations were almost universally lower than the US-EPA National Ambient Air Quality Standards (NAAQS), with virtually no variation across sites. There is evidence for the contributions from biomass and traffic sources, and from geological and marine non-combustion sources to particle pollution. The implications of the results for future urban air pollution monitoring and measurement in developing countries are discussed.     

Elemental composition and sources of fine and ultrafine ambient particles in Erfurt,Germany

We present the first results of a source apportionment for the urban aerosol in Erfurt, Germany, for the period 1995-1998. The analysis is based on data of particle number concentrations (0.01-2.5 microm; mean 1.8 x 10(4) cm(-3), continuous), the concentration of the ambient gases SO(2), NO, NO(2) and CO (continuous), particle mass less than 2.5 microm (PM(2.5)) and less than 10 microm (PM(10)) (Harvard Impactor sampling, mean PM(2.5) 26.3 micro/m(3), mean PM(10) 38.2 microg/m(3)) and the size fractionated concentrations of 19 elements (impactor sampling 0.05-1.62 microm, PIXE analysis). We determined: (a) the correlations between (i) the 1- and 24-h average concentrations of the gaseous pollutants and the particle number as well as the particle mass concentration and (ii) between the 24-h elemental concentrations; (b) Crustal Enrichment Factors for the PIXE elements using Si as reference element; and (c) the diurnal pattern of the measured pollutants on weekdays and on weekends. The highly correlated PIXE elements Si, Al, Ti and Ca having low enrichment factors were identified as soil elements. The strong correlation of particle number concentrations with NO, which is considered to be typically emitted by traffic, and the striking similarity of their diurnal variation suggest that a sizable fraction of the particle number concentration is associated with emission from vehicles. Besides NO and particle number concentrations other pollutants such as NO(2), CO as well as the elements Zn and Cu were strongly correlated and appear to reflect motor vehicle traffic. Sulfur could be a tracer for coal combustion, however, it was not correlated with any of the quoted elements. Highly correlated elements V and Ni have similar enrichment factors and are considered as tracers for oil combustion.     

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.     

Particulate matter and carbon monoxide multiple regression models using environmental characteristics in a high diesel-use area of Baguio City, Philippines

In Baguio City, Philippines, a mountainous city of 252,386 people where 61% of motor vehicles use diesel fuel, ambient particulate matter <2.5 microm (PM(2.5)) and <10 microm (PM(10)) in aerodynamic diameter and carbon monoxide (CO) were measured at 30 street-level locations for 15 min apiece during the early morning (4:50-6:30 am), morning rush hour (6:30-9:10 am) and afternoon rush hour (3:40-5:40 pm) in December 2004. Environmental observations (e.g. traffic-related variables, building/roadway designs, wind speed and direction, etc.) at each location were noted during each monitoring event. Multiple regression models were formulated to determine which pollution sources and environmental factors significantly affect ground-level PM(2.5), PM(10) and CO concentrations. The models showed statistically significant relationships between traffic and early morning particulate air pollution [(PM(2.5)p=0.021) and PM(10) (p=0.048)], traffic and morning rush hour CO (p=0.048), traffic and afternoon rush hour CO (p=0.034) and wind and early morning CO (p=0.044). The mean early morning, street-level PM(2.5) (110+/-8 microg/m3; mean+/-1 standard error) was not significantly different (p-value>0.05) from either rush hour PM(2.5) concentration (morning=98+/-7 microg/m3; afternoon=107+/-5 microg/m3) due to nocturnal inversions in spite of a 100% increase in automotive density during rush hours. Early morning street-level CO (3.0+/-1.7 ppm) differed from morning rush hour (4.1+/-2.3 ppm) (p=0.039) and afternoon rush hour (4.5+/-2.2 ppm) (p=0.007). Additionally, PM(2.5), PM(10), CO, nitrogen dioxide (NO2) and select volatile organic compounds were continuously measured at a downtown, third-story monitoring station along a busy roadway for 11 days. Twenty-four-hour average ambient concentrations were: PM(2.5)=72.9+/-21 microg/m3; CO=2.61+/-0.6 ppm; NO2=27.7+/-1.6 ppb; benzene=8.4+/-1.4 microg/m3; ethylbenzene=4.6+/-2.0 microg/m3; p-xylene=4.4+/-1.9 microg/m3; m-xylene=10.2+/-4.4 microg/m3; o-xylene=7.5+/-3.2 microg/m3. The multiple regression models suggest that traffic and wind in Baguio City, Philippines significantly affect street-level pollution concentrations. Ambient PM(2.5) levels measured are above USEPA daily (65 microg/m3) and Filipino/USEPA annual standards (15 microg/m3) with concentrations of a magnitude rarely seen in most countries except in areas where local topography plays a significant role in air pollution entrapment. The elevated pollution concentrations present and the diesel-rich nature of motor vehicle emissions are important pertaining to human exposure and health information and as such warrant public health concern.     

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.     

Can one use ambient air concentration data to estimate personal and population exposures to particles? An approach within the European EXPOLIS study

The objective of this paper is to devise a way to facilitate the use of fixed air monitors data in order to assess population exposure. A weighting scheme that uses the data from different monitoring sites and takes into account the time-activity patterns of the study population is proposed. PM2.5 personal monitoring data were obtained within the European EXPOLIS study, in Grenoble, France (40 adult non-smoking volunteers, winter 1997). Volunteers carried PM2.5 personal monitors during 48 h and filled in time-activity diaries. Workplaces and places of residence were classified into two categories using a Geographic Information System (GIS): some volunteers' life environments are seen as best represented by PM10 ambient air monitors located in urban background sites; others by monitors situated close to high traffic density sites (proximity sites). Measurements from the Grenoble fixed monitoring network using a TEOM PM10 sampler were available across the same period for these two types of sites (PM10block and PM10prox). These data were used to compute a translator parameter deltai that forces the measured PM2.5 personal exposures (PM2.5persoi) to equate the average PM10 urban ambient air concentrations ([PM10back + PM10prox]/2) measured the same days. Average deltai was 4.2 microg/m3 (CI95%[-3.4; 11.9]), with true average PM2.5 personal exposure being 36.2 microg/m3 (28.2; 44.1). PM10 ambient levels at the proximity site and at the background site were respectively PM10prox = 43.8 microg/m3 (37.1; 50.6) and PM10back = 37.0 microg/m3 (31.8; 42.3). In order to assess the consistency of this approach, six scenarios of 'proximity' and 'background' environments were accommodated, according to traffic intensity and road distance. Deltai was estimated for the entire EXPOLIS population and for subgroups, using terciles based on the percentage of time spent in proximity by each subject. Other similar studies need to be conducted in different urban settings, and with other pollutants, in order to assess the generalizability of this simple approach to estimate population exposures from air quality surveillance data.     

Current asthma and respiratory symptoms among pupils in Shanghai, China: influence of building ventilation, nitrogen dioxide, ozone, and formaldehyde in classrooms

We investigated 10 naturally ventilated schools in Shanghai, in winter. Pupils (13-14 years) in 30 classes received a questionnaire, 1414 participated (99%). Classroom temperatures were 13-21 degrees C (mean 17 degrees C), relative air humidity was 36-82% (mean 56%). The air exchange rate was 2.9-29.4 ac/h (mean 9.1), because of window opening. Mean CO2 exceeded 1000 ppm in 45% of the classrooms. NO2 levels were 33-85 microg/m3 indoors, and 45-80 microg/m3 outdoors. Ozone were 1-9 microg/m3 indoors and 17-28 microg/m3 outdoors. In total, 8.9% had doctors' diagnosed asthma, 3.1% wheeze, 23.0% daytime breathlessness, 2.4% current asthma, and 2.3% asthma medication. Multiple logistic regression was applied. Observed indoor molds was associated with asthma attacks [odds ratio (OR) = 2.40: P < 0.05]. Indoor temperature was associated with daytime breathlessness (OR = 1.26 for 1 C; P < 0.001), and indoor CO2 with current asthma (OR = 1.18 for 100 ppm; P < 0.01) and asthma medication (OR = 1.15 for 100 ppm; P < 0.05). Indoor NO2 was associated with current asthma (OR = 1.51 for 10 microg/m3; P < 0.01) and asthma medication (OR = 1.45 for 10 microg/m3; P < 0.01). Outdoor NO2 was associated with current asthma (OR = 1.44 for 10 microg/m3; P < 0.05). Indoor and outdoor ozone was negatively associated with daytime breathlessness. In conclusion, asthma symptoms among pupils in Shanghai can be influenced by lack of ventilation and outdoor air pollution from traffic. Practical Implications Most urban schools in Asia are naturally ventilated buildings, often situated in areas with heavy ambient air pollution from industry or traffic. The classes are large, and window opening is the only way to remove indoor pollutants, but this results in increased exposure to outdoor air pollution. There is a clear need to improve the indoor environment in these schools. Building dampness and indoor mold growth should be avoided, and the concept of mechanical ventilation should be introduced. City planning aiming to situate new schools away from roads with heavy traffic should be considered.     

Childhood cat allergen exposure in three European countries: The AIRALLERG study

INTRODUCTION: Cat allergen is a major cause of morbidity among sensitised asthma patients, but little is known about distribution of cat allergen exposure and its determinants in homes. METHODS: We measured cat allergen and potential determinants of cat allergen levels in more than 1000 homes. House dust was collected from children's mattresses and living room floors in approximately 360 homes in The Netherlands, Sweden and Germany and analysed for Fel d 1 in one central laboratory. Exposure was expressed both in concentration (ng/g) and in loads (ng/m2). RESULTS: Levels on mattresses were similar in Sweden and Germany but higher on Dutch mattresses. Dutch floors had higher concentrations than Swedish floors, which had higher concentrations than German floors. The differences in load were less clear. Cat allergen on mattress and floor were moderately to highly correlated. The most important variable quantifying cat allergen variation was the presence of a cat. Floor cover type and last time that floor was vacuumed were important in all three countries. The ratio of cat allergen loads between mattresses from homes with and without cats was higher for Sweden and Germany than for The Netherlands. This is likely related to higher prevalence of cat ownership in The Netherlands which leads to more contamination of homes in which cats were never held. Dust samples from 27-35% of mattresses from homes without cats contained more than 1000 ng/g cat allergen. CONCLUSION: With the exception of cat ownership and floor cover, questionnaire data on housing characteristics did not accurately predict cat allergen in the home.     

Factors affecting individual exposure to NO2 in Genoa (northern Italy)

The individual exposure to nitrogen dioxide (NO2) of 89 volunteers living in Genoa, a large port city of northern Italy, was investigated with personal passive diffusion tubes in February-March 2000. The data were related to NO2 concentration in the kitchen and bedroom as measured by static samplers. Volunteers included students, workers and housewives living in three areas of Genoa differing by street traffic and industrial plant location. The kitchen samples showed higher (47.00+/-16.5 microg/m3) NO2 concentrations than those from the bedroom (24.78+/-9.8 microg/m3); overall indoor NO2 concentrations were lower in the Eastern area of Genoa, where outdoor pollution is lower. Students were the volunteer group with the lowest exposure rate (24.9+/-7.8 microg/m3 vs. 44.3+/-10.1 microg/m3 for workers and 40.0+/-13.4 microg/m3 for housewives). This difference is related to the fact that students spend more time indoors, where pollution levels are lower. The main household characteristics which were shown to affect personal NO2 exposure were (a) the presence of a chimney equipped with an active aspiration device in the kitchen and (b) the heating system.     

Spatial and temporal variation of particle number concentration in Augsburg, Germany

Epidemiological studies on health effects of outdoor air pollution are largely based on a single monitoring site to estimate the exposure of people living in urban areas. For such an approach two aspects are important: the temporal correlation and the spatial variation of the absolute levels of concentrations measured at different sites in an urban area. Whereas many studies have shown small spatial variability of fine particles in urban areas, little is known on how well a single monitoring station could represent the temporal and spatial variation of ultrafine particles across urban areas. In our study we investigated the temporal and spatial variation of particle number concentration (PNC) at four background sites in Augsburg, Germany. Two of them were influenced by traffic, one was placed in the outskirts of the city. The average PNC levels at two urban background sites with traffic impact were 16,943 cm(-3) and 20,702 cm(-3), respectively, compared to 11,656 cm(-3) at the urban background site without traffic impact (ratio 1.5 to 1.8). The Spearman correlation coefficients between the monitoring sites were high (r>0.80). The pronounced differences in absolute PNC levels suggest that the use of a single monitoring station in long-term epidemiological studies must be insufficient to attribute accurate exposure levels of PNC to all study subjects. On the other hand, the high temporal correlations of PNC across the city area of Augsburg implicate that in epidemiological time-series studies the use of one single ambient monitoring site is an adequate approach for characterizing exposure to ultrafine particles.     

Increase of platinum group element concentrations in soils and airborne dust in an urban area in Germany

Since 1993, all new cars sold in the European Union had to be fitted with catalytic converters. Undoubtedly, these measures brought about a great progress concerning traffic emission controls. However, this technology also led to new emissions. A rapid accumulation of the catalytic active noble metals Pt, Pd, and Rh in the environment was observed and concern arose about potential environmental and health risks. This work aimed at a contribution to a monitoring of platinum group element (PGE) emission and accumulation by comparing analytical data, all generated in 1999 and in 2005 in an urban area in Germany. Oriented at the 1999 sampling strategy, soil and airborne dust samples were taken in 2005 at the same sampling sites located mainly close to heavily used roads in the region of Braunschweig. For the enrichment of the analytes, conditioned soil samples as well as loaded glass fiber filters from air sampling were transferred to the nickel sulphide fire assay. For analyses, the ICP-MS technique was applied. High Pt, Pd, and Rh concentrations were detected especially in top soil layers (0-2 cm) directly at the roadsides or on center strips. At one road outside the city, where traffic moved with a constant speed of about 80 km/h, maximum concentrations in soil were found to be 50.4 microg/kg for Pt, 43.3 microg/kg for Pd, and 10.7 microg/kg for Rh. PGE concentrations were the highest close to that road and exponentially declined with growing distance. At a second road, where vehicles run with a constant speed of 50 km/h, the highest concentrations were detected in the center strip soil: 88.9 microg/kg (Pt), 77.8 microg/kg (Pd), and 17.6 microg/kg (Rh). At a third crowded street in the centre of Braunschweig with stop and go traffic, the highest soil concentrations were determined, namely 261 microg/kg for Pt, 124 microg/kg for Pd and 38.9 microg/kg for Rh. The sampling of airborne dust at this roadside revealed for Pt 159 pg/m(3) air or 1730 microg/kg dust, for Pd 37.8 pg/m(3) air or 410 microg/kg dust, and for Rh 10.0 pg/m(3) air or 110 microg/kg dust. A comparison of analytical results of 2005 with those of 1999 revealed a distinct increase of PGE concentrations in soils closely along heavy traffic roads by a factor of 2.1 to 8.9; once even a factor of 15 was determined. The findings also document, that especially Pt and Rh concentrations were elevated in airborne dust.     

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.     

Spatial analysis of annual air pollution exposure and mortality

The aim of this study was to relate ambient air pollution levels to mortality in Auckland, New Zealand. We used urban airshed modelling and GIS-based techniques to quantify long-term exposure to ambient air pollution levels and associated mortality. After adjusting for age, sex, ethnicity, socio-economic status, and urban/rural domicile there was a 1.3% (95%CI: 1-1.5%) increase in non-external cause mortality, and 1.8% (95%CI: 1.5-2.1%) increase in circulatory and respiratory causes per 1 microg/m(3) increase in annual average NO(2). Based on these exposure-response relationships and applying an annual average threshold of 13 microg/m(3), the average annual (for 1996-1999) number of people estimated to die from non-external causes and circulatory and respiratory causes attributable to air pollution in Auckland is 268 (95% range: 227-310) (3.9% of total all cause deaths) and 203 (95% range: 169-237) (5.9% of total circulatory and respiratory deaths) per year, respectively. The number of attributable deaths found in this study are consistent with a previous New Zealand risk assessment using a different methodology, and is approximately twice the number of people dying from motor vehicle accidents in the region, which is on average (1996-1999) 103 per year. The GIS-based exposure maps identify high exposure areas for policy developers and planners in a simple and realistic manner. Taken together with overseas studies the study provides additional evidence that long-term exposure to poor air quality, even at levels below current standards, is a hazard to the public health.     

Indoor and outdoor personal exposure to benzene in Athens, Greece

OBJECTIVE: To evaluate the exposure of urban inhabitants to atmospheric benzene in Athens, Greece. METHODS: Fifty non-smoker volunteers from selected occupational groups and their homes were monitored by passive air samplers for six 5-day periods during a year. An activity diary was completed during each sampling period and relevant data were collected by a questionnaire at the beginning of the study. Additional data on urban levels on benzene were also available. RESULTS: Average benzene home and personal levels in six monitoring campaigns varied between 6.0-13.4 and 13.1-24.6 microg/m(3), respectively. Urban levels varied between 15.4 and 27.9 microg/m(3) with an annual mean of 20.4 microg/m(3). Wind speed seems to determine largely home levels and personal exposure. Proximity to busy road holds also an important influence on indoor benzene levels. Adjusted for seasonal or climate variation, other significant prognostic factors of personal exposure were home levels, total time spent outdoors and transportation mean. Time spent outdoors explains the strong relationship between occupation and personal levels of exposure. Wind had similar effect in clearing indoor and urban pollution in Athens; lessen personal exposure and home levels about 2-2.5 microg/m(3) per 1 m/s increase in speed. CONCLUSIONS: Factors related to climate (use of non-absorbent materials for wall and floor covering and frequent ventilation) might be one explanation for homes' high clearing rate. Our exposure pattern, which suggests that outdoors work give the greater contribution to benzene exposure of Athens citizens, is uncommon in northern towns of Europe. Policy makers have to take in account these differences in establishing guidelines for ambient benzene exposure.     

Particulate matter exposure along designated bicycle routes in Vancouver, British Columbia

An instrumented bicycle was used to elucidate particulate matter exposures along bicycle routes passing through a variety of land uses over 14 days during summer and fall in a mid-latitude traffic dominated urban setting. Overall, exposures were low or comparable to those found in studies elsewhere (mean PM(2.5) and PM(10) concentrations over each daily bicycle traverse varied between 7-34 microg m(-3) and 26-77 microg m(-3) respectively). Meteorological factors were responsible for significant day-to-day variability with PM(2.5) positively correlated with air temperature, PM(10) negatively correlated with precipitation, and ultrafine particles negatively correlated with both air temperature and wind speed. On individual days, land use and proximity to traffic were factors significantly affecting exposure along designated bicycle routes. While concentrations of PM(2.5) were found to be relatively spatially uniform over the length of the study route, PM(10) showed a more heterogeneous spatial distribution. Specifically, construction sites and areas susceptible to the suspension of road dust have higher concentrations of coarse particles. Ultrafine particles were also heterogeneously distributed in space, with areas with heavy traffic volumes having the highest concentrations. Observations show qualitative agreement in terms of spatial patterns with a land-use regression (LUR) model for annual PM(2.5) concentrations.     

Sources and concentrations of indoor nitrogen dioxide in Hamburg (west Germany) and Erfurt (east Germany)

Here we report indoor and outdoor concentrations of NO2 for Erfurt and Hamburg and assess the contribution of the most important indoor sources (e.g. the presence of gas cooking ranges, smoking) and outdoor sources (traffic exhaust emissions). We examined the relative contribution of the different sources of NO2 to the total indoor NO2 levels in Erfurt and Hamburg. NO2 indoor concentrations in Hamburg were slightly higher than those in Erfurt (i.e. living room: 15 microg m(-3) for Erfurt and 17 microg m(-3) for Hamburg). A linear regression model including the variables, place of residence, season and outdoor NO2 levels, location of the home within the city, housing and occupant characteristics accounted for 38% of the NO2 variance. The most important predictors of indoor NO2 concentrations were gas in cooking followed by other characteristics, such as ventilation or outdoor NO2 level. Residences in which gas was used for cooking, or in which occupants smoked, had substantially higher indoor NO2 concentrations (41 or 18% increase, respectively). An increase in the outdoor NO2 concentration from the 25th to the 75th-percentile (17 microg m(-3)) was associated with a 33% increase in the living room NO2 concentration. Multiple regression analysis for both cities separately illustrated that use of gas for cooking was the major indoor source of NO2. This variable caused a similar increase in the indoor NO2 levels in each city (43% in Erfurt and 47% in Hamburg). However, outdoor sources of NO2 (motor vehicle traffic) contributed more to indoor NO2 levels in Hamburg than in Erfurt.     

Concentration and chemical characteristics of PM2.5 in Beijing, China: 2001-2002

Weekly PM2.5 samples were simultaneously collected at a semi-residential (Tsinghua University) and a downtown (Chegongzhuang) site in Beijing from August 2001 through September 2002. The ambient mass concentration and chemical composition of PM2.5 were determined. Analyses including elemental composition, water-soluble ions, and organic and elemental carbon were performed. The annual average concentrations of PM2.5 were 96.5 microg m(-3) and 106.9 microg m(-3) at CGZ and HU site, respectively. More than 80% of the PM2.5 mass concentrations were explained by carbonaceous species, secondary particles, crustal matters and trace elements at the two sites. Carbonaceous species were the most abundant components, constituting about 45% and 48% of the total PM2.5 mass concentrations at CGZ and THU site, respectively. SO4(2-), NO3- and NH4+ were three major ions, accounting for 37%, 23% and 20%, respectively, of the total mass of inorganic water-soluble ions.     

Elemental carbon and respirable particulate matter in the indoor air of apartments and nursery schools and ambient air in Berlin (Germany)

This study was performed to examine exposure to typical carcinogenic traffic air pollutants in the city center of an urban area. In all, 123 apartments and 74 nursery schools were analyzed with and without tobacco smoke interference and the households in two measuring periods. Simultaneously, the air outside 61 apartment windows as well as the average daily traffic volume were measured. Elemental carbon (EC), the marker for particulate diesel exhaust and respirable particulate matter (RPM) were determined. The thermographic EC analysis was conducted with and without prior solvent extraction of the soluble carbon fraction. Comparison of these two thermographic EC measurements clearly showed that method-related differences in the results, especially for indoor measurements, when high background loads of organic material were present (e.g. tobacco smoke), existed. Solvent extraction prior to EC determination was therefore appropriate. For the first winter measuring period, the EC concentration levels without solvent extraction in the indoor air were about 50% higher than those measured in the spring/summer period. In the second measuring period (i.e. spring/summer), the median EC concentrations after solvent extraction were 1.9 microg/m3 for smokers' apartments and 2.1 microg/m3 for non-smokers' apartments, with RPM concentrations of 57 and 27 microg/m3, respectively. Nursery schools showed high concentrations with median values of 53 microg/m3 for RPM and 2.9 microg/m3 for EC after solvent extraction. A significant correlation between the fine dust and EC concentrations (after solvent extraction) in the indoor and ambient air was determined. Outdoor EC values were also correlated with the average daily traffic volume. The EC ratios between indoor and ambient concentration showed a median of 0.8 (range: 0.3-4.2) in non-smoker households and 0.9 (range: 0.4-1.5) in smoker apartments. Furthermore, the EC/RPM ratio in indoor and ambient air was 0.01-0.15 (median 0.06) and 0.04-0.37 (median 0.09), respectively. PRACTICAL IMPLICATIONS: In the absence of indoor sources a significant correlation with regard to respirable particulate matter (RPM) and elemental carbon concentrations between the indoor and ambient air of apartments was observed. The high degree of certainty resulting from this correlation underscores the importance of ambient air concentrations for indoor air quality. In nursery schools we found higher concentrations of RPM. An explanation of these results could be the high number of occupants in the room, their activity and the cleaning intensity.     

Source characterization using compound composition and stable carbon isotope ratio of PAHs in sediments from lakes, harbor, and shipping waterway

Molecular compositions and compound specific stable carbon isotope ratios of polycyclic aromatic hydrocarbons (PAH) isolated from sediments were used to characterize possible sources of contamination at an urban lake, a harbor, a shipping waterway, and a relatively undisturbed remote lake in the northwest United States. Total PAH concentrations in urban lake sediments ranged from 66.0 to 16,500 microg g(-1) dry wt. with an average of 2600 microg g(-1), which is approximately 50, 100, and 400 times higher on average than PAH in harbor (48 microg g(-1) on average), shipping waterway (26 microg g(-1)), and remote lake (7 microg g(-1)) sediments, respectively. The PAH distribution patterns, methyl phenanthrene/phenanthrene ratios, and a pyrogenic index at the sites suggest a pyrogenic origin for PAHs. Source characterization using principal component analysis and various molecular indices including C2-dibenzothiophenes/C2-phenanthrenes, C3-dibenzothiophenes/C3-phenanthrenes, and C2-chrysenes/C2-phenanthrenes ratios, was able to differentiate PAH deposited in sediments from the four sites. The uniqueness of the source of the sediment PAHs from urban lake was also illustrated by compound specific stable carbon isotope analysis. It was concluded that urban lake sediments are accumulating PAH from sources that are unique from contamination detected at nearby sites in the same watershed.     

A regression-based method for mapping traffic-related air pollution: application and testing in four contrasting urban environments

Accurate, high-resolution maps of traffic-related air pollution are needed both as a basis for assessing exposures as part of epidemiological studies, and to inform urban air-quality policy and traffic management. This paper assesses the use of a GIS-based, regression mapping technique to model spatial patterns of traffic-related air pollution. The model--developed using data from 80 passive sampler sites in Huddersfield, as part of the SAVIAH (Small Area Variations in Air Quality and Health) project--uses data on traffic flows and land cover in the 300-m buffer zone around each site, and altitude of the site, as predictors of NO2 concentrations. It was tested here by application in four urban areas in the UK: Huddersfield (for the year following that used for initial model development), Sheffield, Northampton, and part of London. In each case, a GIS was built in ArcInfo, integrating relevant data on road traffic, urban land use and topography. Monitoring of NO2 was undertaken using replicate passive samplers (in London, data were obtained from surveys carried out as part of the London network). In Huddersfield, Sheffield and Northampton, the model was first calibrated by comparing modelled results with monitored NO2 concentrations at 10 randomly selected sites; the calibrated model was then validated against data from a further 10-28 sites. In London, where data for only 11 sites were available, validation was not undertaken. Results showed that the model performed well in all cases. After local calibration, the model gave estimates of mean annual NO2 concentrations within a factor of 1.5 of the actual mean (approx. 70-90%) of the time and within a factor of 2 between 70 and 100% of the time. r2 values between modelled and observed concentrations are in the range of 0.58-0.76. These results are comparable to those achieved by more sophisticated dispersion models. The model also has several advantages over dispersion modelling. It is able, for example, to provide high-resolution maps across a whole urban area without the need to interpolate between receptor points. It also offers substantially reduced costs and processing times compared to formal dispersion modelling. It is concluded that the model might thus be used as a means of mapping long-term air pollution concentrations either in support of local authority air-quality management strategies, or in epidemiological studies.