Personal exposure of children to air pollution

Changes over recent decades in outdoor concentrations of air pollutants are well documented. However, the impacts of air pollution on an individual's health actually relate not to these outdoor concentrations but to their personal exposure in the different locations in which they spend time. Assessing how personal exposures differ from outdoor concentrations, and how they have changed over recent decades, is challenging. This review focuses on the exposure of children, since they are a particularly sensitive group. Much of children's time is spent indoors, and childhood exposure is closely related to concentrations in the home, at school, and in transport. For this reason, children's personal exposures to air pollutants differ significantly from both those of adults and from outdoor concentrations. They depend on a range of factors, including urbanisation, energy use, building design, travel patterns, and activity profiles; analysis of these factors can identify a wider range of policy measures to reduce children's exposure than direct emission control. There is a very large variation in personal exposure between individual children, caused by differences in building design, indoor and outdoor sources, and activity patterns. Identifying groups of children with high personal exposure, and their underlying causes, is particularly important in regions of the world where emissions are increasing, but there are limited resources for environmental and health protection. Although the science of personal exposure assessment, with the associated measurement and modelling techniques, has developed to maturity in North America and western Europe over the last 50 years, there is an urgent need to apply this science in other parts of the world where the effects of air pollution are now much more serious.     

Long-term personal exposure to PM2.5, soot and NOx in children attending schools located near busy roads,a validation study

Several studies have investigated the health of children attending schools located near busy roads. In this study, we have measured personal exposure to traffic-related pollutants in children to validate exposure classification based on school location. Personal exposure to PM_2.5, soot, NO_x and NO₂ was measured during four 48-h periods. The study involved 54 children attending four different schools, two of which were located within 100 m of a major road (one ring road and one freeway) and the other two were located at a background location in the city of Utrecht, The Netherlands. Outdoor monitoring was conducted at all school sites, during the personal measurements. A questionnaire was administered on time activity patterns and indoor sources at home. The outdoor concentration of soot was 74% higher at the freeway school compared to its matched background school. Personal exposure to soot was 30% higher. For NO_x the outdoor concentration was 52% higher at the freeway school compared to its background school. The personal concentration of NO_x was 37% higher for children attending the freeway school. Differences were smaller and insignificant for PM_2.5 and NO₂. No elevated personal exposure to air pollutants was found for the children attending the school near the ring road. We conclude that the school's proximity to a freeway can be used as a valid estimate of exposure in epidemiological studies on the effects of the traffic-related air pollutants soot and NO_x in children.     

Journey-time exposure to particulate air pollution

Journey-time exposures to particulate air pollution were investigated in Leicester, UK, between January and March 2005. Samples of TSP, PM₁₀, PM_2.5, and PM₁ were simultaneously collected using light scattering devices whilst journeys were made by walking an in-car. Over a period of two months, 33 pairs of walking and in-car measurements were collected along two circular routes. Average exposures while walking were seen to be higher than those found in-car for each of the particle fractions: average walking to in-car ratios were 1.2 (± 0.6), 1.5 (± 0.6), 1.3 (± 0.6), and 1.4 (± 0.6) μg m⁻³ for coarse (TSP–PM₁₀), intermediate (PM₁₀–PM_2.5), fine (PM_2.5–PM₁), and very fine particles (PM₁), respectively. Correlations between walking and in-car exposures were seen to be weak for coarse particles (r=0.10, p=0.58), moderate for the intermediate particles (r=0.49, p<0.01) but strong for fine (r=0.89, p<0.01) and very fine (r=0.90, P<0.01) particles. PM₁₀ exposures while walking were on average 70% higher than a nearby roadside fixed-site monitor whilst in-car exposures were 25% higher than the same fixed-site monitor. Particles with an aerodynamic diameter of less than 2.5 μm were seen to be highly correlated between walking and in-car particle exposures and a rural fixed-site monitor about 30 km south of Leicester.     

Changed vegetation composition in coniferous forests near to motorways in Southern Germany: the effects of traffic-born pollution

To estimate the effect of traffic emissions on the vegetation composition of coniferous forests near to motorways, three transects of 520 m length were studied by analysing vegetation composition, soil parameters and deposition data in the Munich-area, Southern Germany. The detected patterns suggest that motorways have an impact on the vegetation composition in the neighbourhood of roads. Depending on the wind direction, the influences of the motorways reaches up to 230 m on downwind side and up to 80 m on upwind side. The vegetation is mainly affected by the deposition of nitrogen deriving from fuel combustion and by basic substances added to road salt. By monitoring vegetation changes near to motorways, it is possible to estimate the areas where harmful alterations of the ecosystem can be expected.     

Assessment of air pollution impact

Several essential steps of air quality assessment are described, including identification, prediction, and evaluation of critical variables and potential changes of air quality. A coal-reconversion power plant in New York was selected as an example to illustrate the assessment.     

Personal exposure to particulate air pollution in transport microenvironments

Personal measurements of exposure to particulate air pollution (PM₁₀, PM_2.5, PM₁) were simultaneously made during walking and in-car journeys on two suburban routes in Northampton, UK, during the winter of 1999/2000. Comparisons were made between concentrations found in each transport mode by particle fraction, between different particle fractions by transport mode, and between transport microenvironments and a fixed-site monitor located within the study area. High levels of correlation were seen between walking and in-car concentrations for each of the particle fractions (PM₁₀: r²=0.82; PM_2.5: r²=0.98; PM₁: r²=0.99). On an average, PM₁₀ concentrations were 16% higher inside the car than for the walker, but there were no difference in average PM_2.5 and PM₁ concentrations between the two modes. High PM_2.5:PM₁₀ ratios (0.6–0.73) were found to be associated with elevated sulphate levels. The PM_2.5:PM₁₀ and PM₁:PM_2.5 ratios were shown to be similar between walking and in-car concentrations. Concentrations of PM₁₀ were found to be more closely related between transport mode than either mode was with concentrations recorded at the fixed-site (roadside) monitor. The fixed-site monitor was shown to be a poor marker for PM₁₀ concentrations recorded during walking and in-car on a route over 1 km away.     

Modeling traffic air pollution in street canyons in New York City for intra-urban exposure assessment in the US Multi-Ethnic Study of atherosclerosis and air pollution

We evaluated the Danish AirGIS air quality and exposure model system using air quality measurement data from New York City in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Measurements were used from three US EPA Air Quality System (AQS) monitoring stations and a comprehensive MESA Air measurement campaign including about 150 different locations and about 650 samples of about 2 week measurements of NO_x, NO₂ and PM_2.5. AirGIS is a deterministic exposure model system based on the dispersion models Operational Street Pollution Model (OSPM) and the Urban Background Model (UBM). The UBM model reproduced the annual levels within 1–26% depending on station and pollutant at the three urban background EPA monitor stations, and generally reproduced well the seasonal and diurnal variation. The full model with OSPM and UBM reproduced the MESA Air measurements with a correlation coefficient of r² = 0.51 for NO_x, r² = 0.28 for NO₂ and r² = 0.73 for PM_2.5.     

Vascular function and short-term exposure to fine particulate air pollution

Exposure to fine particulate air pollution has been implicated as a risk factor for cardiopulmonary disease and mortality. Proposed biological pathways imply that particle-induced pulmonary and systemic inflammation play a role in activating the vascular endothelium and altering vascular function. Potential effects of fine particulate pollution on vascular function are explored using controlled chamber exposure and uncontrolled ambient exposure. Research subjects included four panels with a total of 26 healthy nonsmoking young adults. On two study visits, at least 7 days apart, subjects spent 3 hr in a controlled-exposure chamber exposed to 150-200 microg/m3 of fine particles generated from coal or wood combustion and 3 hr in a clean room, with exposure and nonexposure periods alternated between visits. Baseline, postexposure, and post-clean room reactive hyperemia-peripheral arterial tonometry (RH-PAT) was conducted. A microvascular responsiveness index, defined as the log of the RH-PAT ratio, was calculated. There was no contemporaneous vascular response to the few hours of controlled exposure. Declines in vascular response were associated with elevated ambient exposures for the previous 2 days, especially for female subjects. Cumulative exposure to real-life fine particulate pollution may affect vascular function. More research is needed to determine the roles of age and gender, the effect of pollution sources, the importance of cumulative exposure over a few days versus a few hours, and the lag time between exposure and response.     

Spatially differentiated and source-specific population exposure to ambient urban air pollution

Models assessing exposure to air pollution often focus on macro-scale estimates of exposure to all types of sources for a particular pollutant across an urban study area. While results based on these models may aid policy makers in identifying larger areas of elevated exposure risk, they often do not differentiate the proportion of population exposure attributable to different polluting sources (e.g. traffic or industrial). In this paper, we introduce a population exposure modeling system that integrates air dispersion modeling, Geographic Information Systems (GIS), and population exposure techniques to spatially characterize a source-specific exposure to ambient air pollution for an entire urban population at a fine geographical scale. By area, total population exposure in Dallas County in 2000 was more attributable to vehicle polluting sources than industrial polluting sources at all levels of exposure. Population exposure was moderately correlated with vehicle sources (r = 0.440, p < 0.001) and weakly with industrial sources (r = 0.069, p = 0.004). Population density was strongly correlated with total exposure (r = 0.896, p < 0.001) but was not significantly correlated with individual or combined sources. The results of this study indicate that air quality assessments must incorporate more than industrial or vehicle polluting sources-based population exposure values alone, but should consider multiple sources. The population exposure modeling system proposed in this study shows promise for use by municipal authorities, policy makers, and epidemiologists in evaluating and controlling the quality of the air in the process of urban planning and mitigation measures.     

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.     

Assessment of population exposure to particulate matter pollution in Chongqing, China

To determine the population exposure to PM(10) in Chongqing, China, we developed an indirect model by combining information on the time activity patterns of various demographic subgroups with estimates of the PM(10) concentrations in different microenvironments (MEs). The spatial and temporal variations of the exposure to PM(10) were illustrated in a geographical information system (GIS). The population weighted exposure (PWE) for the entire population was 229, 155 and 211 microg/m(3), respectively, in winter, summer and as the annual average. Indoor PM(10) level at home was the largest contributor to the PWE, especially for the rural areas where high pollution levels were found due to solid fuels burning. Elder people had higher PM(10) exposure than adults and youth, due to more time spent in indoor MEs. The highest health risk due to particulate was found in the city zone and northeast regions, suggesting that pollution abatement should be prioritized in these areas.     

Model experiments on the nature of air pollution transport near buildings

The paper describes wind tunnel experiments with rectangular blocks in uniform smooth and turbulent air flow to simulate the transport of windborne atmospheric pollutants near buildings. Dispersal is dominated by the flow in the areodynamic wakes of the blocks. Using light extinction apparatus, measurements were made of the time constant (t_d) of the decay of the amount of smoke in the separation bubble following abrupt removal of the smoke source, and of the bubble length (X). These quantities were expressed as H( Ut_d/S, where U is the air velocity and S the block dimension) and X/S respectively, found to be unique functions of the free-stream turbulence parameter, A( l_fK^1/2_f/SU, where l_f and k_f are the length scale and kinetic energy respectively of the free-stream turbulence), for cubic blocks in the ranges l_f/S ? 0.6 and k_f^1/2/U ?, 0.15. Visual observation of tracer smoke indicated the onset of re-attachment of the separated flow on the top and side faces of the cubes at relatively low levels of free-stream turbulence, coinciding with sharply varying behaviour in H and X/S. Measurements were also made of H and X/S for square-faced blocks of various lengthwise aspect ratios, and for cubic blocks at various angles of incidence to the flow.From consideration of the turbulent transport of entities of an atmospheric pollutant across the boundary of the wake bubble behind a building, an expression is derived for the mean concentration level that can build up inside the bubble for a source of known strength and location. It contains the two terms H and X/S which explicitly embody the complicated fluid mechanical properties of the near wake.     

Modeling the impacts of traffic emissions on air toxics concentrations near roadways

The dispersion formulation incorporated in the U.S. Environmental Protection Agency's AERMOD regulatory dispersion model is used to estimate the contribution of traffic-generated emissions of select VOCs – benzene, 1,3-butadiene, toluene – to ambient air concentrations at downwind receptors ranging from 10-m to 100-m from the edge of a major highway in Raleigh, North Carolina. The contributions are computed using the following steps: 1) Evaluate dispersion model estimates with 10-min averaged NO data measured at 7 m and 17 m from the edge of the road during a field study conducted in August, 2006; this step determines the uncertainty in model estimates. 2) Use dispersion model estimates and their uncertainties, determined in step 1, to construct pseudo-observations. 3) Fit pseudo-observations to actual observations of VOC concentrations measured during five periods of the field study. This provides estimates of the contributions of traffic emissions to the VOC concentrations at the receptors located from 10 m to 100 m from the road. In addition, it provides estimates of emission factors and background concentrations of the VOCs, which are supported by independent estimates from motor vehicle emissions models and regional air quality measurements. The results presented in the paper demonstrate the suitability of the formulation in AERMOD for estimating concentrations associated with mobile source emissions near roadways. This paper also presents an evaluation of the key emissions and dispersion modeling inputs necessary for conducting assessments of local-scale impacts from traffic emissions.     

Assessment of traffic-related air pollution in the urban streets before and during the 2008 Beijing Olympic Games traffic control period

In order to investigate the air quality and the abatement of traffic-related pollution during the 2008 Olympic Games, we select 12 avenues in the urban area of Beijing to calculate the concentrations of PM₁₀, CO, NO₂ and O₃ before and during the Olympic traffic controlling days, with the OSPM model.Through comparing the modeled results with the measurement results on a representative street, the OSPM model is validated as sufficient to predict the average concentrations of these pollutants at street level, and also reflects their daily variations well, i.e. CO presents the similar double peaks as the traffic flow, PM₁₀ concentration is influenced by other sources. Meanwhile, the model predicts O₃ to stay less during the daytime and ascend in the night, just opposite to NO₂, which reveals the impact of photochemical reactions. In addition, the predicted concentrations on the windward side often exceed the leeward side, indicating the impact of the special street shape, as well as the wind.The comparison between the predicted street concentrations before and during the Olympic traffic control period shows that the overall on-road air quality was improved effectively, due to the 32.3% traffic flow reduction. The concentrations of PM₁₀, CO and NO₂ have reduced from 142.6 μg m⁻³, 3.02 mg m⁻³ and 118.7 μg m⁻³ to 102.0 μg m⁻³, 2.43 mg m⁻³ and 104.1 μg m⁻³. However, the different pollutants show diverse changes after the traffic control. PM₁₀ decreases most, and the reduction effect focusing on the first half-day even clears the morning peak, whereas CO and NO₂ have even reductions to minify the daily fluctuations on the whole. Opposite to the other pollutants, ozone shows an increase of concentration. The average reduction rate of PM₁₀, CO, NO₂ and O₃ are respectively 28%, 19.3%, 12.3% and −25.2%. Furthermore, the streets in east, west, south and north areas present different air quality improvements, probably induced by the varied background pollution in different regions around Beijing, along with the impact of wind force. This finding suggests the pollution control in the surrounding regions, not only in the urban area.     

Benzene exposure and the effect of traffic pollution in Copenhagen,Denmark

Benzene is a carcinogenic compound, which is emitted from petrol-fuelled cars and thus is found ubiquitous in all cities. As part of the project Monitoring of Atmospheric Concentrations of Benzene in European Towns and Homes (MACBETH) six campaigns were carried out in the Municipality of Copenhagen, Denmark. The campaigns were distributed over 1 year. In each campaign, the personal exposure to benzene of 50 volunteers (non-smokers living in non-smoking families) living and working in Copenhagen was measured. Simultaneously, benzene was measured in their homes and in an urban network distributed over the municipality. The Radiello diffusive sampler was applied to sample 5 days averages of benzene and other hydrocarbons. Comparison of the results with those from a BTX-monitor showed excellent agreement. The exposure and the concentrations in homes and in the urban area were found to be close to log-normal distribution. The annual averages of the geometrical mean values were 5.22, 4.30 and 2.90 μg m⁻³ for personal exposure, home concentrations and urban concentrations, respectively. Two main parameters are controlling the general level of benzene in Copenhagen: firstly, the emission from traffic and secondly, dispersion due to wind speed. The general level of exposure to benzene and home concentrations of benzene were strongly correlated with the outdoor level of benzene, which indicated that traffic is an important source for indoor concentrations of benzene and for the exposure to benzene.