Background:The assessment of air pollution exposure using only community average concentrations may lead to measurement error that lowers estimates of the health burden attributable to poor air quality. To test this hypothesis, we modeled the association between air pollution and mortality using sma

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Spatial analysis of air pollution and mortality in Los Angeles.

We conducted an extended follow-up and spatial analysis of the American Cancer Society (ACS) Cancer Prevention Study II (CPS-II) cohort in order to further examine associations between long-term exposure to particulate air pollution and mortality in large U.S. cities. The current study sought to clarify outstanding scientific issues that arose from our earlier HEI-sponsored Reanalysis of the original ACS study data (the Particle Epidemiology Reanalysis Project). Specifically, we examined (1) how ecologic covariates at the community and neighborhood levels might confound and modify the air pollution-mortality association; (2) how spatial autocorrelation and multiple levels of data (e.g., individual and neighborhood) can be taken into account within the random effects Cox model; (3) how using land-use regression to refine measurements of air pollution exposure to the within-city (or intra-urban) scale might affect the size and significance of health effects in the Los Angeles and New York City regions; and (4) what exposure time windows may be most critical to the air pollution-mortality association. The 18 years of follow-up (extended from 7 years in the original study [Pope et al. 1995]) included vital status data for the CPS-II cohort (approximately 1.2 million participants) with multiple cause-of-death codes through December 31, 2000 and more recent exposure data from air pollution monitoring sites for the metropolitan areas. In the Nationwide Analysis, the influence of ecologic covariate data (such as education attainment, housing characteristics, and level of income; data obtained from the 1980 U.S. Census; see Ecologic Covariates sidebar on page 14) on the air pollution-mortality association were examined at the Zip Code area (ZCA) scale, the metropolitan statistical area (MSA) scale, and by the difference between each ZCA value and the MSA value (DIFF). In contrast to previous analyses that did not directly include ecologic covariates at the ZCA scale, risk estimates increased when ecologic covariates were included at all scales. The ecologic covariates exerted their greatest effect on mortality from ischemic heart disease (IHD), which was also the health outcome most strongly related with exposure to PM2.5 (particles 2.5 microm or smaller in aerodynamic diameter), sulfate (SO4(2-)), and sulfur dioxide (SO2), and the only outcome significantly associated with exposure to nitrogen dioxide (NO2). When ecologic covariates were simultaneously included at both the MSA and DIFF levels, the hazard ratio (HR) for mortality from IHD associated with PM2.5 exposure (average concentration for 1999-2000) increased by 7.5% and that associated with SO4(2-) exposure (average concentration for 1990) increased by 12.8%. The two covariates found to exert the greatest confounding influence on the PM2.5-mortality association were the percentage of the population with a grade 12 education and the median household income. Also in the Nationwide Analysis, complex spatial patterns in the CPS-II data were explored with an extended random effects Cox model (see Glossary of Statistical Terms at end of report) that is capable of clustering up to two geographic levels of data. Using this model tended to increase the HR estimate for exposure to air pollution and also to inflate the uncertainty in the estimates. Including ecologic covariates decreased the variance of the results at both the MSA and ZCA scales; the largest decrease was in residual variation based on models in which the MSA and DIFF levels of data were included together, which suggests that partitioning the ecologic covariates into between-MSA and within-MSA values more completely captures the sources of variation in the relationship between air pollution, ecologic covariates, and mortality. Intra-Urban Analyses were conducted for the New York City and Los Angeles regions. The results of the Los Angeles spatial analysis, where we found high exposure contrasts within the Los Angeles region, showed that air pollution-mortality risks were nearly 3 times greater than those reported from earlier analyses. This suggests that chronic health effects associated with intra-urban gradients in exposure to PM2.5 may be even larger between ZCAs within an MSA than the associations between MSAs that have been previously reported. However, in the New York City spatial analysis, where we found very little exposure contrast between ZCAs within the New York region, mortality from all causes, cardiopulmonary disease (CPD), and lung cancer was not elevated. A positive association was seen for PM2.5 exposure and IHD, which provides evidence of a specific association with a cause of death that has high biologic plausibility. These results were robust when analyses controlled (1) the 44 individual-level covariates (from the ACS enrollment questionnaire in 1982; see 44 Individual-Level Covariates sidebar on page 22) and (2) spatial clustering using the random effects Cox model. Effects were mildly lower when unemployment at the ZCA scale was included. To examine whether there is a critical exposure time window that is primarily responsible for the increased mortality associated with ambient air pollution, we constructed individual time-dependent exposure profiles for particulate and gaseous air pollutants (PM2.5 and SO2) for a subset of the ACS CPS-II participants for whom residence histories were available. The relevance of the three exposure time windows we considered was gauged using the magnitude of the relative risk (HR) of mortality as well as the Akaike information criterion (AIC), which measures the goodness of fit of the model to the data. For PM2.5, no one exposure time window stood out as demonstrating the greatest HR; nor was there any clear pattern of a trend in HR going from recent to more distant windows or vice versa. Differences in AIC values among the three exposure time windows were also small. The HRs for mortality associated with exposure to SO2 were highest in the most recent time window (1 to 5 years), although none of these HRs were significantly elevated. Identifying critical exposure time windows remains a challenge that warrants further work with other relevant data sets. This study provides additional support toward developing cost-effective air quality management policies and strategies. The epidemiologic results reported here are consistent with those from other population-based studies, which collectively have strongly supported the hypothesis that long-term exposure to PM2.5 increases mortality in the general population. Future research using the extended Cox-Poisson random effects methods, advanced geostatistical modeling techniques, and newer exposure assessment techniques will provide additional insight.

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Extended follow-up and spatial analysis of the American Cancer Society study linking particulate air pollution and mortality.

Review of relationship between indoor and outdoor particles: I/O ratio, infiltration factor and penetration factor

Results of recent research show that particulate matter (PM) composition and size vary widely with both space and time. Despite the variability in PM characteristics, which are believed to influence human health risks, the observed relative health risk estimates per unit PM mass falls within a narrow range of values. Furthermore, no single chemical species appears to dominate health effects; rather the effects appear to be due to a combination of species. Non-PM factors such as socioeconomic status and lifestyle are also believed to affect the health risk, although accounting for these confounding factors is challenging. Airborne PM is also responsible for a number of effects aside from human health, such as alterations in visibility and climate. Because the PM problem is associated with a range of societal issues such as energy production and economic development, making progress on reducing the effects of PM will require integrated strategies that bring together scientists and decision makers from diffe...

https://www.tandfonline.com/doi/pdf/10.1080/02786820500191348

Airborne Particulate Matter and Human Health: A Review

Motivated by growing considerations of the scale, severity, and risks associated with human exposure to indoor particulate matter, this work reviewed existing literature to: (i) identify state-of-the-art experimental techniques used for personal exposure assessment; (ii) compare exposure levels reported for domestic/school settings in different countries (excluding exposure to environmental tobacco smoke and particulate matter from biomass cooking in developing countries); (iii) assess the contribution of outdoor background vs indoor sources to personal exposure; and (iv) examine scientific understanding of the risks posed by personal exposure to indoor aerosols. Limited studies assessing integrated daily residential exposure to just one particle size fraction, ultrafine particles, show that the contribution of indoor sources ranged from 19% to 76%. This indicates a strong dependence on resident activities, source events and site specificity, and highlights the importance of indoor sources for total personal exposure. Further, it was assessed that 10-30% of the total burden of disease from particulate matter exposure was due to indoor-generated particles, signifying that indoor environments are likely to be a dominant environmental factor affecting human health. However, due to challenges associated with conducting epidemiological assessments, the role of indoor-generated particles has not been fully acknowledged, and improved exposure/risk assessment methods are still needed, together with a serious focus on exposure control.

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Indoor aerosols: from personal exposure to risk assessment

The Relationship of Indoor, Outdoor and Personal Air (RIOPA) study was designed to investigate residential indoor, outdoor and personal exposures to several classes of air pollutants, including volatile organic compounds, carbonyls and fine particles (PM2.5). Samples were collected from summer, 1999 to spring, 2001 in Houston (TX), Los Angeles (CA) and Elizabeth (NJ). Indoor, outdoor and personal PM2.5 samples were collected at 212 nonsmoking residences, 162 of which were sampled twice. Some homes were chosen due to close proximity to ambient sources of one or more target analytes, while others were farther from sources. Median indoor, outdoor and personal PM2.5 mass concentrations for these three sites were 14.4, 15.5 and 31.4 microg/m3, respectively. The contributions of ambient (outdoor) and nonambient sources to indoor and personal concentrations were quantified using a single compartment box model with measured air exchange rate and a random component superposition (RCS) statistical model. The median contribution of ambient sources to indoor PM2.5 concentrations using the mass balance approach was estimated to be 56% for all study homes (63%, 52% and 33% for California, New Jersey and Texas study homes, respectively). Reasonable variations in model assumptions alter median ambient contributions by less than 20%. The mean of the distribution of ambient contributions across study homes agreed well for the mass balance and RCS models, but the distribution was somewhat broader when calculated using the mass balance model with measured air exchange rates.

Influence of ambient (outdoor) sources on residential indoor and personal PM2.5 concentrations: analyses of RIOPA data.

The Relationship of Indoor, Outdoor and Personal Air (RIOPA) Study was undertaken to evaluate the contribution of outdoor sources of air toxics, as defined in the 1990 Clean Air Act Amendments, to indoor concentrations and personal exposures. The concentrations of 18 volatile organic compounds (VOCs), 17 carbonyl compounds, and fine particulate matter mass (PM(2.5)) were measured using 48-h outdoor, indoor and personal air samples collected simultaneously. PM2.5 mass, as well as several component species (elemental carbon, organic carbon, polyaromatic hydrocarbons and elemental analysis) were also measured; only PM(2.5) mass is reported here. Questionnaires were administered to characterize homes, neighborhoods and personal activities that might affect exposures. The air exchange rate was also measured in each home. Homes in close proximity (<0.5 km) to sources of air toxics were preferentially (2:1) selected for sampling. Approximately 100 non-smoking households in each of Elizabeth, NJ, Houston, TX, and Los Angeles, CA were sampled (100, 105, and 105 respectively) with second visits performed at 84, 93, and 81 homes in each city, respectively. VOC samples were collected at all homes, carbonyls at 90% and PM(2.5) at 60% of the homes. Personal samples were collected from nonsmoking adults and a portion of children living in the target homes. This manuscript provides the RIOPA study design and quality control and assurance data. The results from the RIOPA study can potentially provide information on the influence of ambient sources on indoor air concentrations and exposure for many air toxics and will furnish an opportunity to evaluate exposure models for these compounds.

Relationship of Indoor, Outdoor and Personal Air (RIOPA) study: study design, methods and quality assurance/control results

UNLABELLED: Fourier transform infrared (FTIR) spectra of outdoor, indoor, and personal fine particulate matter (PM(2.5)) samples were collected during the Relationship of Indoor, Outdoor, and Personal Air (RIOPA) study. FTIR spectroscopy provides functional group information about the entire PM(2.5) sample without any chemical preparation. It is particularly important to characterizing the poorly understood organic fraction of PM(2.5). To our knowledge this is the first time that FTIR spectroscopy has been applied to a PM(2.5) exposure study. The results were used to chemically characterize indoor air and personal exposure. Sulfate was strongest in outdoor samples, which is consistent with the generally accepted understanding that sulfate is of outdoor origin. Absorbances attributed to soil dust were also seen in many outdoor and some indoor and personal samples. Inorganic nitrate absorbances were a common feature of many California and some New Jersey samples. Carbonyl absorbances showed substantial variation in strength, number of peaks, and wave number shift between samples, indicating variability in composition and sources. Absorbances attributed to aliphatic hydrocarbon and amide functional groups were enhanced in many personal and indoor samples, which suggested the influence of indoor sources in these homes. We speculate that meat cooking is one possible source of particulate amides. PRACTICAL IMPLICATIONS: To our knowledge this is the first time that FTIR spectroscopy has been used to characterize the composition of indoor and personal PM(2.5). The presence of sulfate, nitrate, ammonium, soil dust and a number of organic functional groups are all detected in one analysis on filter samples without extraction or other sample preparation. Differences between indoor and outdoor spectra are used to identify spectral features due to indoor-generated PM(2.5). Particularly interesting are the much larger aliphatic absorbances, shifts in carbonyl absorbances, and occasional small amide absorbances found in indoor and personal spectra but rarely in outdoor spectra. These observations are important because organics make up a large portion of PM(2.5) mass and their composition and properties are poorly characterized. The properties and behavior of organic compounds in airborne particles are often predicted based on their functional group composition. This analysis begins the development of a better understanding of the functional group composition of indoor and personal PM(2.5) and how it differs from that of outdoor PM(2.5). Eventually this will lead to an improved understanding of the properties, behavior and effects of PM(2.5) of indoor and outdoor origin.

William Cui

Papers

Influence of ambient (outdoor) sources on residential indoor and personal PM2.5 concentrations: analyses of RIOPA data.

Relationship of Indoor, Outdoor and Personal Air (RIOPA) study: study design, methods and quality assurance/control results

Functional group characterization of indoor, outdoor, and personal PM2.5: results from RIOPA