Meta-Analysis of Time-Series Studies of Air Pollution and Mortality: Effects of Gases and Particles and the Influence of Cause of Death,Age, and Season

Abstract

A comprehensive, systematic synthesis was conducted of daily time-series studies of air pollution and mortality from around the world. Estimates of effect sizes were extracted from 109 studies, from single- and multipollutant models, and by cause of death, age, and season. Random effects pooled estimates of excess all-cause mortality (single-pollutant models) associated with a change in pollutant concentration equal to the mean value among a representative group of cities were 2.0% (95% CI 1.5-2.4%) per 31.3 μg/m³ particulate matter (PM) of median diameter <10 μm (PM₁₀); 1.7% (1.2-2.2%) per 1.1 ppm CO; 2.8% (2.1-3.5%) per 24.0 ppb NO₂; 1.6% (1.1-2.0%) per 31.2 ppb O₃; and 0.9% (0.7-1.2%) per 9.4 ppb SO₂ (daily maximum concentration for O₃, daily average for others). Effect sizes were generally reduced in multipollutant models, but remained significantly different from zero for PM₁₀ and SO₂. Larger effect sizes were observed for respiratory mortality for all pollutants except O₃. Heterogeneity among studies was partially accounted for by differences in variability of pollutant concentrations, and results were robust to alternative approaches to selecting estimates from the pool of available candidates. This synthesis leaves little doubt that acute air pollution exposure is a significant contributor to mortality.     

Daily mortality in the Philadelphia metropolitan area and size-classified particulate matter

Time-series of daily mortality data from May 1992 to September 1995 for various portions of the seven-county Philadelphia, PA, metropolitan area were analyzed in relation to weather and a variety of ambient air quality parameters. The air quality data included measurements of size-classified PM, SO4(2-), and H+ that had been collected by the Harvard School of Public Health, as well as routine air pollution monitoring data. Because the various pollutants of interest were measured at different locations within the metropolitan area, it was necessary to test for spatial sensitivity by comparing results for different combinations of locations. Estimates are presented for single pollutants and for multiple-pollutant models, including gaseous pollutants and mutually exclusive components of PM (PM2.5 and coarse particles, SO4(2-) and non-SO4(2-) portions of total suspended particulate [TSP] and PM10), measured on the day of death and the previous day. We concluded that associations between air quality and mortality were not limited to data collected in the same part of the metropolitan area; that is, mortality for one part may be associated with air quality data from another, not necessarily neighboring, part. Significant associations were found for a wide variety of gaseous and particulate pollutants, especially for peak O3. Using joint regressions on peak O3 with various other pollutants, we found that the combined responses were insensitive to the specific other pollutant selected. We saw no systematic differences according to particle size or chemistry. In general, the associations between daily mortality and air pollution depended on the pollutant or the PM metric, the type of collection filter used, and the location of sampling. Although peak O3 seemed to exhibit the most consistent mortality responses, this finding should be confirmed by analyzing separate seasons and other time periods.     

A study of the association between daily mortality and ambient air pollutant concentrations in Pittsburgh, Pennsylvania

We have studied the possible association of daily mortality with ambient pollutant concentrations (PM10, CO, O3, SO2, NO2, and fine [PM2.5] and coarse PM) and weather variables (temperature and dew point) in the Pittsburgh, PA, area for two age groups--less than 75, and 75 and over--for the 3-year period of 1989-1991. Correlation functions among pollutant concentrations show important seasonal dependence, and this fact necessitates the use of seasonal models to better identify the link between ambient pollutant concentrations and daily mortality. An analysis of the seasonal model results for the younger-age group reveals significant multicollinearity problems among the highly correlated concentrations of PM10, CO, and NO2 (and O3 in spring and summer), and calls into question the rather consistent results of the single- and multi-pollutant non-seasonal models that show a significant positive association between PM10 and daily mortality. For the older-age group, dew point consistently shows a significant association with daily mortality in all models. Collinearity problems appear in the multi-pollutant seasonal and non-seasonal models such that a significant, positive PM10 coefficient is accompanied by a significant, negative coefficient of another ambient pollutant, and the identity of this other pollutant changes with season. The PM2.5 data set is half that of PM10. Identical-model runs for both data sets reveal instability in the pollutant coefficients, especially for the younger age group. The concern for the instability of the pollutant coefficients due to a small signal-to-noise ratio makes it impossible to ascertain credibly the relative associations of the fine- and coarse-particle modes with daily mortality. In this connection, we call for caution in the interpretation of model results for causal inference when the models use fully or partially estimated PM values to fill large data gaps.     

Effects of instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, Georgia

Data from the U.S. Environmental Protection Agency Air Quality System, the Southeastern Aerosol Research and Characterization database, and the Assessment of Spatial Aerosol Composition in Atlanta database for 1999 through 2002 have been used to characterize error associated with instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, GA. These data are being used in time series epidemiologic studies in which associations of acute respiratory and cardiovascular health outcomes and daily ambient air pollutant levels are assessed. Modified semivariograms are used to quantify the effects of instrument precision and spatial variability on the assessment of daily metrics of ambient gaseous pollutants (SO2, CO, NOx, and O3) and fine particulate matter ([PM2.5] PM2.5 mass, sulfate, nitrate, ammonium, elemental carbon [EC], and organic carbon [OC]). Variation because of instrument imprecision represented 7-40% of the temporal variation in the daily pollutant measures and was largest for the PM2.5 EC and OC. Spatial variability was greatest for primary pollutants (SO2, CO, NOx, and EC). Population-weighted variation in daily ambient air pollutant levels because of both instrument imprecision and spatial variability ranged from 20% of the temporal variation for O3 to 70% of the temporal variation for SO2 and EC. Wind     

Application and evaluation of two air quality models for particulate matter for a southeastern U.S. episode

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29-July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O3), particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 microm (PM10) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O3 and PM than CMAQ. Both models tend to predict O3 values that are higher than those observed. For observed O3 values above 60 ppb, O3 performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O3 values above 40 ppb. Both models predict similar amounts of sulfate (SO4(2-)) and organic matter, and both predict SO4(2-) to be the largest contributor to PM2.5. PMCAMx generally predicts higher amounts of ammonium (NH4+), nitrate (NO3-), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO3-, NH4+, and BC than observed, which degrades its performance. For PM10 and PM2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37-43% and -33-4% for CMAQ and 50-59% and 7-30% for PMCAMx. Both models predict the largest MNGEs for NO3- (98-104% for CMAQ 138-338% for PMCAMx). The inaccurate NO3- predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.     

Effect of the fine fraction of particulate matter versus the coarse mass and other pollutants on daily mortality in Santiago, Chile

Daily counts of non-accidental deaths in Santiago, Chile, from 1988 to 1996 were regressed on six air pollutants--fine particles (PM2.5), coarse particles (PM10-2.5), CO, SO2, NO2, and O3. Controlling for seasonal and meteorological conditions was done using three different models--a generalized linear model, a generalized additive model, and a generalized additive model on previously filtered data. Single- and two-pollutant models were tested for lags of 1-5 days and the average of the previous 2-5 days. The increase in mortality associated with the mean levels of air pollution varied from 4 to 11%, depending on the pollutants and the way season of the year was considered. The results were not sensitive to the modeling approaches, but different effects for warmer and colder months were found. Fine particles were more important than coarse particles in the whole year and in winter, but not in summer. NO2 and CO were also significantly associated with daily mortality, as was O3 in the warmer months. No consistent effect was observed for SO2. Given particle composition in Santiago, these results suggest that combustion-generated pollutants, especially from motor vehicles, may be associated with increased mortality. Temperature was closely associated with mortality. High temperatures led to deaths on the same day, while low temperatures lead to deaths from 1 to 4 days later.     

Air pollution and hospital admissions for diseases of the circulatory system in three U.S. metropolitan areas

Generalized additive models were used to analyze the time series of daily hospital admissions for cardiovascular and cerebrovascular diseases over the period of 1987-1995 in three major metropolitan areas--Cook County, IL; Los Angeles County, CA; and Maricopa County, AZ--in the United States. In Cook and Maricopa Counties, admissions information was only available for the elderly (ages 65 and over), while in Los Angeles County, admissions information was available for all ages. In Cook County, daily monitoring information was available on PM10, CO, SO2, NO2, and O3. In Los Angeles and Maricopa Counties, monitoring information was available daily on the gases, and information on PM10 was available every sixth day. In Los Angeles County, information on PM2.5 was also available every sixth day. In Cook and Los Angeles Counties, associations were found between each pollutant, with the exception of O3, and admissions for cardiovascular disease, with the gases showing the strongest associations. In two-pollutant models with PM and one of the gases, the effect of the gases remained stable, while the effect of PM became unstable and insignificant. In Maricopa County, the gases, with the exception of O3, were weakly associated with hospital admissions for cardiovascular disease, while PM was not. In two-pollutant models with two of CO, SO2, and NO2, the pattern of results is heterogeneous in the three counties. In all three counties, only weak evidence of any association between air pollution and cerebrovascular admissions was found.     

Daily mortality and air pollution in The Netherlands

We studied the association of daily mortality with short-term variations in the ambient concentrations of major gaseous pollutants and PM in the Netherlands. The magnitude of the association in the four major urban areas was compared with that in the remainder of the country. Daily cause-specific mortality counts, air quality, temperature, relative humidity, and influenza data were obtained from 1986 to 1994. The relationship between daily mortality and air pollution was modeled using Poisson regression analysis. We adjusted for potential confounding due to long-term and seasonal trends, influenza epidemics, ambient temperature and relative humidity, day of the week, and holidays, using generalized additive models. Influenza episodes were associated with increased mortality up to 3 weeks later. Daily mortality was significantly associated with the concentration of all air pollutants. An increase in the PM10 concentration by 100 micrograms/m3 was associated with a relative risk (RR) of 1.02 for total mortality. The largest RRs were found for pneumonia deaths. Ozone had the most consistent, independent association with mortality. Particulate air pollution (e.g., PM10, black smoke [BS]) was not more consistently associated with mortality than were the gaseous pollutants SO2 and NO2. Aerosol SO4(-2), NO3-, and BS were more consistently associated with total mortality than was PM10. The RRs for all pollutants were substantially larger in the summer months than in the winter months. The RR of total mortality for PM10 was 1.10 for the summer and 1.03 for the winter. There was no consistent difference between RRs in the four major urban areas and the more rural areas.     

Defining the photochemical contribution to particulate matter in urban areas using time-series analysis

The objective of this project is to demonstrate how the ambient air measurement record can be used to define the relationship between O3 (as a surrogate for photochemistry) and secondary particulate matter (PM) in urban air. The approach used is to develop a time-series transfer-function model describing the daily PM10 (PM with less than 10 microm aerodynamic diameter) concentration as a function of lagged PM and current and lagged O3, NO or NO2, CO, and SO2. Approximately 3 years of daily average PM10, daily maximum 8-hr average O3 and CO, daily 24-hr average SO2 and NO2, and daily 6:00 a.m.-9:00 a.m. average NO from the Aerometric Information Retrieval System (AIRS) air quality subsystem are used for this analysis. Urban areas modeled are Chicago, IL; Los Angeles, CA; Phoenix, AZ; Philadelphia, PA; Sacramento, CA; and Detroit, MI. Time-series analysis identified significant autocorrelation in the O3, PM10, NO, NO2, CO, and SO2 series. Cross correlations between PM10 (dependent variable) and gaseous pollutants (independent variables) show that all of the gases are significantly correlated with PM10 and that O3 is also significantly correlated lagged up to two previous days. Once a transfer-function model of current PM10 is defined for an urban location, the effect of an O3-control strategy on PM concentrations is estimated by calculating daily PM10 concentrations with reduced O3 concentrations. Forecasted summertime PM10 reductions resulting from a 5 percent decrease in ambient O3 range from 1.2 microg/m3 (3.03%) in Chicago to 3.9 microg/m3 (7.65%) in Phoenix.     

Short-term effects of gaseous pollutants on cause-specific mortality in Wuhan, China

In Asia, limited studies have been published on the association between daily mortality and gaseous pollutants of nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2). Our previous studies in Wuhan, China, demonstrated long-term air pollution effects. However, no study has been conducted to determine mortality effects of air pollution in this region. This study was to determine the acute mortality effects of the gaseous pollutants in Wuhan, a city with 7.5 million permanent residents during the period from 2000 to 2004. There are approximately 4.5 million residents in Wuhan who live in the city's core area of 201 km2, where air pollution levels are highest, and pollution ranges are wider than the majority of the cities in the published literature. We used the generalized additive model to analyze pollution, mortality, and covariate data. We found consistent NO2 effects on mortality with the strongest effects on the same day. Every 10-microg/m3 increase in NO2 daily concentration on the same day was associated with an increase in nonaccidental (1.43%; 95% confidence interval [CI]: 0.87-1.99%), cardiovascular (1.65%; 95% CI: 0.87-2.45%), stroke (1.49%; 95% CI: 0.56-2.43%), cardiac (1.77%; 95% CI: 0.44-3.12%), respiratory (2.23%; 95% CI: 0.52-3.96%), and cardiopulmonary mortality (1.60%; 95% CI: 0.85-2.35%). These effects were stronger among the elderly than among the young. Formal examination of exposure-response curves suggests no-threshold linear relationships between daily mortality and NO2, where the NO2 concentrations ranged from 19.2 to 127.4 microg/m3. SO2 and O3 were not associated with daily mortality. The exposure-response relationships demonstrated heterogeneity, with some curves showing nonlinear relationships for SO2 and O3. We conclude that there is consistent evidence of acute effects of NO2 on mortality and suggest that a no-threshold linear relationship exists between NO2 and mortality.     

The Aerosol Research and Inhalation Epidemiology Study (ARIES): PM2.5 mass and aerosol component concentrations and sampler intercomparisons

The Aerosol Research and Inhalation Epidemiology Study (ARIES) was designed to provide high-quality measurements of PM2.5, its components, and co-varying pollutants for an air pollution epidemiology study in Atlanta, GA. Air pollution epidemiology studies have typically relied on available data on particle mass often collected using filter-based methods. Filter-based PM2.5 sampling is susceptible to both positive and negative errors in the measurement of aerosol mass and particle-phase component concentrations in the undisturbed atmosphere. These biases are introduced by collection of gas-phase aerosol components on the filter media or by volatilization of particle phase components from collected particles. As part of the ARIES, we collected daily 24-hr PM2.5 mass and speciation samples and continuous PM2.5 data at a mixed residential-light industrial site in Atlanta. These data facilitate analysis of the effects of a wide variety of factors on sampler performance. We assess the relative importance of PM2.5 components and consider associations and potential mechanistic linkages of PM2.5 mass concentrations with several PM2.5 components. For the 12 months of validated data collected to date (August 1, 1998-July 31, 1999), the monthly average Federal Reference Method (FRM) PM2.5 mass always exceeded the proposed annual average standard (12-month average = 20.3 +/- 9.5 micrograms/m3). The particulate SO4(2-) fraction (as (NH4)2SO4) was largest in the summer and exceeded 50% of the FRM mass. The contribution of (NH4)2SO4 to FRM PM2.5 mass dropped to less than 30% in winter. Particulate NO3- collected on a denuded nylon filter averaged 1.1 +/- 0.9 micrograms/m3. Particle-phase organic compounds (as organic carbon x 1.4) measured on a denuded quartz filter sampler averaged 6.4 +/- 3.1 micrograms/m3 (32% of FRM PM2.5 mass) with less seasonal variability than SO4(2-).     

Summer-time distribution of air pollutants in Sequoia National Park, California

Concentrations of air pollutants were monitored during the May November 1999 period on a network of forested sites in Sequoia National Park, California. Measurements were conducted with: (1) active monitors for nitric oxide (NO), nitrogen dioxide (NO2) and ozone (O3); (2) honeycomb denuder/filter pack systems for nitric acid vapor (HNO3), nitrous acid vapor (HNO2), ammonia (NH3), sulfur dioxide (SO2), particulate nitrate (NO3-), ammonium (NH4+), and sulfate (SO4(2-)); and (3) passive samplers for O3, HNO3 and NO2. Elevated concentrations of O3 (seasonal means 41-71 ppb), HNO3 (seasonal means 0.4-2.9 microg/m3), NH3 (seasonal means 1.6-4.5 microg/m3), NO3 (1.1-2.0 microg/m3) and NH4+ (1.0-1.9 microg/m3) were determined. Concentrations of other pollutants were low. With increasing elevation and distance from the pollution source area of O3, NH3 and HNO3 concentrations decreased. Ammonia and NH4+ were dominant N pollutants indicating strong influence of agricultural emissions on forests and other ecosystems of the Sequoia National Park.     

A new multipollutant, no-threshold air quality health index based on short-term associations observed in daily time-series analyses

Air quality indices currently in use have been criticized because they do not capture additive effects of multiple pollutants, or reflect the apparent no-threshold concentration-response relationship between air pollution and health. We propose a new air quality health index (AQHI), constructed as the sum of excess mortality risk associated with individual pollutants from a time-series analysis of air pollution and mortality in Canadian cities, adjusted to a 0-10 scale, and calculated hourly on the basis of trailing 3-hr average pollutant concentrations. Extensive sensitivity analyses were conducted using alternative combinations of pollutants from single and multipollutant models. All formulations considered produced frequency distributions of the daily maximum AQHI that were right-skewed, with modal values of 3 or 4, and less than 10% of values at 7 or above on the 10-point scale. In the absence of a gold standard and given the uncertainty in how to best reflect the mix of pollutants, we recommend a formulation based on associations of nitrogen dioxide, ozone, and particulate matter of median aerodynamic diameter less than 2.5 microm with mortality from single-pollutant models. Further sensitivity analyses revealed good agreement of this formulation with others based on alternative sources of coefficients drawn from published studies of mortality and morbidity. These analyses provide evidence that the AQHI represents a valid approach to formulating an index with the objective of allowing people to judge the relative probability of experiencing adverse health effects from day to day. Together with health messages and a graphic display, the AQHI scale appears promising as an air quality risk communication tool.     

The impact of frequency and duration of air quality monitoring: Atlanta, GA, data modeling of air pollution and mortality

The purpose of this analysis is threefold. We first examine the extent to which a longer series of data improves our understanding of air pollution on human mortality in the Atlanta, GA, area by updating the findings presented in Klemm and Mason (J. Air Waste Manage. Assoc. 2000, 50, 1433-1439) and Klemm et al. (Inhal. Toxicol. 2004, 16 (Suppl 1), 131-141) with 7.5 additional years of data. We explore estimated effects on two age groups (<65 and 65+) and four categories of cause of death. Second, we investigate how enlarging the geographic area of inquiry influences the estimated effects. Third, because some air quality (AQ) measures are monitored less frequently than daily, we investigate the extent to which AQ measurement frequency can influence estimates of relationships with human mortality. Our analytical approach employs a Poisson regression model using generalized linear modeling in S-Plus to estimate the relationship between daily AQ measures and daily mortality counts. We show that the estimated effects and their associated t values vary by year for nine AQ measures (particulate matter with aerodynamic diameter < or =2.5 microm [PM2.5], elemental carbon [EC], organic carbon [OC], NO3, SO4, O3, NO2, CO, and SO2). Several of the estimated AQ effects show downward trends during the 9-year period of study. The estimated effects tend to be strongest for the AQ measurement during the day of death and tend to decrease with additional lags. Enlarging the geographic area from two to four counties in the metropolitan area decreased the estimated effects, perhaps partly due to the fact that the measurement site is located in one of the two original counties. Estimated effects utilizing data as if the AQ were only measured every 3rd or every 6th day each week or twice per week vary from lower to higher than that estimated with daily measurements, although the t values are lower, as expected.     

A Study of the Association between Daily Mortality and Ambient Air Pollutant Concentrations in Pittsburgh,Pennsylvania

ABSTRACT

We have studied the possible association of daily mortality with ambient pollutant concentrations (PM₁₀, CO, O₃, SO₂, NO₂, and fine [PM_{2 5}] and coarse PM) and weather variables (temperature and dew point) in the Pittsburgh, PA, area for two age groups—less than 75, and 75 and over—for the 3-year period of 1989-1991. Correlation functions among pollutant concentrations show important seasonal dependence, and this fact necessitates the use of seasonal models to better identify the link between ambient pollutant concentrations and daily mortality. An analysis of the seasonal model results for the younger-age group reveals significant multicollinearity problems among the highly correlated concentrations of PM₁₀, CO, and NO₂ (and O₃ in spring and summer), and calls into question the rather consistent results of the single- and multi-pollutant non-seasonal models that show a significant positive association between PM₁₀ and daily mortality. For the older-age group, dew point consistently shows a significant association with daily mortality in all models. Collinearity problems appear in the multi-pollutant seasonal and non-seasonal models such that a significant, positive PM₁₀ coefficient is accompanied by a significant, negative coefficient of another ambient pollutant, and the identity of this other pollutant changes with season. The PM₂₅ data set is half that of PM₁₀. Identical-model runs for both data sets reveal instability in the pollutant coefficients, especially for the younger age group. The concern for the instability of the pollutant coefficients due to a small signal-to-noise ratio makes it impossible to ascertain credibly the relative associations of the fine- and coarse-particle modes with daily mortality. In this connection, we call for caution in the interpretation of model results for causal inference when the models use fully or partially estimated PM values to fill large data gaps.     

Single and interactive effects of low levels of O3, SO2 and NO2 on the growth and yield of spring rape

During three consecutive seasons (1987-1989), the effects of low-levels of O3, SO2 and NO2 singly and in all possible combinations (NO2 in 1988 and 1989 only) on growth and yield of potted plants of spring rape (Brassica napus L. var. napus, 'callypso') were investigated by means of factorial fumigation experiments in open-top chambers. Plants were exposed from the early vegetative stage of development until seed harvest, to charcoal-filtered air (CF; control) and CF which was supplemented for 8-h per day (8.00-16.00) with O3, for 16-h per day with NO2 (16.00-8.00) and continuously with SO2. Including the controls, the 24-h daily mean concentrations [microg m(-3)] ranged between 6-44 (O3), 9-88 (SO2) and 10-43 (NO2). The corresponding daily mean concentrations during the time of fumigation were 10-121 and 11-60 microg m(-3) for O3 and NO2, respectively. Single effects of O3 on growth and yield parameters were mostly negative and the magnitude of this effect was dependent on the season. O3 reduced plant dry weight by 11.3-18.6% and yield of seeds by 11.4-26.9%. While medium levels of SO2 stimulated the weight of pods up to 33%, higher concentrations (88 microg m(-3)) caused a decline of yield of 12.3%. From the significant interactive effects which were observed, it could be established that SO2 and NO2 alone mostly acted positively, but that their interaction with each other and especially with O3 was antagonistic, as some of the detrimental effects of O3 were mitigated by these pollutants. An important antagonistic effect between SO2 and O3 or NO2 was observed on yield. While 56 microg m(-3) SO2 increased yield by 9.9% compared to the control treatment, it aggravated the yield loss caused by O3 from -16.18% to -21.4%, and it reduced the yield stimulation caused by NO2 from +11.8% to +4.2%. Leaf area was the only parameter which was negatively affected by all pollutants, their joint action being synergistic.     

Assessing the relationship between personal particulate and gaseous exposures of senior citizens living in Baltimore, MD

We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (> 64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM2.5, PM10, SO4(2-), O3, NO2, SO2, and exhaust-related VOCs. Results of this study showed that longitudinal associations between ambient PM2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM2.5 exposures and resulting personal-ambient associations. Associations between personal PM2.5 exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM2.5 sources. Evidence for this was provided by SO4(2-) measurements, which can be thought of as a tracer for ambient PM2.5. For SO4(2-), personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM2.5 sources to personal PM2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments. Results also indicate that the potential for confounding by PM2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM2.5 exposures were not significantly correlated with personal exposures to PM2.5-10, PM2.5 of non-ambient origin, O3, NO2, and SO2. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM2.5 epidemiologic studies are unlikely to be due to confounding by the PM2.5 co-pollutants measured in this study.     

Spatial heterogeneity of PM10 and O3 in São Paulo, Brazil, and implications for human health studies

Developing exposure estimates is a challenging aspect of investigating the health effects of air pollution. Pollutant levels recorded at centrally located ambient air quality monitors in a community are commonly used as proxies for population exposures. However, if ample intraurban spatial variation in pollutants exists, city-wide averages of concentrations may introduce exposure misclassification. We assessed spatial heterogeneity of particulate matter with an aerodynamic diameter < or = 10 microm (PM10) and ozone (O3) and evaluated implications for epidemiological studies in S?o Paulo, Brazil, using daily (24-hr) and daytime (12-hr) averages and 1-hr daily maximums of pollutant levels recorded at the regulatory monitoring network. Monitor locations were also analyzed with respect to a socioeconomic status index developed by the municipal government. Hourly PM10 and O3 data for the Sāo Paulo Municipality and Metropolitan Region (1999-2006) were used to evaluate heterogeneity by comparing distance between monitors with pollutants' correlations and coefficients of divergence (CODs). Both pollutants showed high correlations across monitoring sites (median = 0.8 for daily averages). CODs across sites averaged 0.20. Distance was a good predictor of CODs for PM10 (p < 0.01) but not O3, whereas distance was a good predictor of correlations for O3 (p < 0.01) but not PM10. High COD values and low temporal correlation indicate a spatially heterogeneous distribution of PM10. Ozone levels were highly correlated (r > or = 0.75), but high CODs suggest that averaging over O3 levels may obscure important spatial variations. Of municipal districts in the highest of five socioeconomic groups, 40% have > or = 1 monitor, whereas districts in the lowest two groups, representing half the population, have no monitors. Results suggest that there is a potential for exposure misclassification based on the available monitoring network and that spatial heterogeneity depends on pollutant metric (e.g., daily average vs. daily 1-hr maximum). A denser monitoring network or alternative exposure methods may be needed for epidemiological research. Findings demonstrate the importance of considering spatial heterogeneity and differential exposure misclassification by subpopulation.     

Review of Singapore's air quality and greenhouse gas emissions: current situation and opportunities

Singapore has many environmental accomplishments to its credit. Accessible data on air quality indicates that all criteria pollutants satisfy both U.S. Environmental Protection Agency (EPA) and World Health Organization (WHO) air quality standards and guidelines, respectively. The exception is PM2.5 (particles with an aerodynamic diameter < or = 2.5 microm), which is not currently considered a criteria pollutant in Singapore but may potentially be the major local air pollution problem and cause for health concern. Levels of other airborne pollutants as well as their physical and chemical processes associated with local formation, transformation, dispersion, and deposition are not known. According to available emission inventories, Singapore contribution to the total atmospheric pollution and carbon budget at the regional and global scales is small. Emissions per unit gross domestic product (GDP) are low compared with other countries, although Singapore's per-capita GDP and per-capita emissions are among the highest in the world. Some information is available on health effects, but the impacts on the ecosystem and the complex interactions of air pollution and climate change at a regional level are also unknown. This article reviews existing available information on atmospheric pollution and greenhouse gas emissions and proposes a multipollutant approach to greenhouse gas mitigation and local air quality. Singapore, by reducing its per-capita emissions, increasing the availability of information (e.g., through regularly publishing hourly and/or daily PM2.5 concentrations) and developing a research agenda in this area, would likely be seen to be a model of a high-density, livable, and sustainable city in Southeast Asia and other tropical regions worldwide.     

Screening and Scenarios of Traffic Emissions at Trier,Germany

SCOPE AND BACKGROUND: In the course of the European Council Directive on permissible air pollutant limit values, valid starting from 2005 there is an urgent call for action, particularly for fine dust (PM10). Current investigations (Junk & Helbig 2003, Reuter & Baumüller 2003) show that the limit values in certain places in congested areas are exceeded. Only if it is possible to locate these Hot Spots purposeful measures to reduce the ambient air pollution can be conducted. For an efficient identification of these Hot Spots numerical computer models or establishing special measurements networks are too expensive. Using the statistical model STREET 5.0 (KTT 2003) a cost-effective screening of the air pollution situation caused by the traffic can be done. METHODS: STREET is based on the 3-dimensional micro-scale non-hydrostatic flow- and dispersion model MISCAM (Eichhorn 1989). The results of over 100.000 different calculations with MISCAM are stored in a Database and used to calculate the emissions with STREET. In collaboration with the city council of Trier more than 150 streets were investigated, mapped, and calculated. A special urban climate measuring network supplies the necessary meteorological input data about the wind field and precipitation events in the valley of the Moselle. Information about road width and road orientation as well as building density was derived from aerial photographs. Traffic censuses and mobile air pollutants measurements supplied the remaining input data. We calculated the mean annual air pollutant concentrations for NO2, CO, SO2, O3, benzene as well as PM10. RESULTS: A comparison of the model results with the values obtained from the stations of the central emission measuring network of Rhineland-Palatinate (ZIMEN, annual report 2002) shows very good agreements. The model was not only used to calculate the annual air pollutant but also for urban planning and management. The absolute level of the air pollutant is mainly dependent on the amount of traffic in the street canyons. Therefore four different case-scenarios with varying quantity of traffic were calculated and interpreted for each street. The results of the calculation show that on the basis of the mean values for both NO2 and benzene, it is not to be expected that the limits PERSPECTIVES: Furthermore the model can be used to find the maximum tolerable numbers of cars for a street without exceeding the air pollutant thresholds.