Research Report (Health Effects Institute)[JOURNAL]
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200 papers
Part 4. Effects of subchronic diesel engine emissions exposure on plasma markers in rodents: report on 1- and 3-month exposures in the ACES bioassay.
Conklin DJ, Kong M, HEI Health Review Committee
Res Rep Health Eff Inst · 2012 Sep · PMID 23156843
Although epidemiologic and experimental studies suggest that exposure to diesel exhaust (DE*) emissions causes adverse cardiovascular effects, neither the specific components of DE nor the mechanisms by which DE exposure...
Although epidemiologic and experimental studies suggest that exposure to diesel exhaust (DE*) emissions causes adverse cardiovascular effects, neither the specific components of DE nor the mechanisms by which DE exposure could induce cardiovascular dysfunction and exacerbate cardiovascular disease (CVD) are known. Moreover, because the advance of new technologies has resulted in cleaner fuels and decreased engine emissions, there is even more uncertainty about the relationship between DE exposure and cardiovascular health effects. To address this ever-changing baseline of engine emissions, we tested for exposure-, sex- and duration-dependent alterations in plasma markers following subchronic exposure of mice and rats to DE emissions from a 2007-compliant diesel engine. Many plasma markers--several recognized as known human CVD risk factors--were measured in the plasma of rodents exposed to 1 or 3 months of air (the control) or DE emissions. Few changes in plasma markers resulted from exposure to DE, although significant exposure-level-dependent increases in total cholesterol and high-density lipoprotein (HDL) cholesterol were observed in male rats after 1 month of DE exposure, an effect that was neither sustained nor observed in any other group. These data indicate that DE emissions from a 2007-compliant diesel engine as tested in this study had little adverse effect on CVD markers in rodents.
Part 3. Assessment of genotoxicity and oxidative stress after exposure to diesel exhaust from U.S. 2007-compliant diesel engines: report on 1- and 3-month exposures in the ACES bioassay.
Hallberg LM, Ward JB, Hernandez C … +3 more , Ameredes BT, Wickliffe JK, HEI Health Review Committee
Res Rep Health Eff Inst · 2012 Sep · PMID 23156842
Human health hazards due to diesel exhaust (DE*) exposure have been associated with both solvent and combustion components. In the past, diesel engine exhaust components have been linked to increased mutagenicity in cult...
Human health hazards due to diesel exhaust (DE*) exposure have been associated with both solvent and combustion components. In the past, diesel engine exhaust components have been linked to increased mutagenicity in cultures of Salmonella typhimurium and mammalian cells (Tokiwa and Ohnishi 1986). In addition, DE has been shown to increase both the incidence of tumors and the induction of 8-hydroxy-deoxyguanosine adducts (8-OHdG) in ICR mice (Ichinose et al. 1997). Furthermore, DE is composed of a complex mixture of polycyclic aromatic hydrocarbons (PAHs) and particulates. One such PAH, 3-nitrobenzanthrone (3-NBA), has been identified in DE and found in urban air. 3-NBA has been observed to induce micronucleus formation in DNA of human hepatoma cells (Lamy et al. 2004). The purpose of the current research, which is part of the Advanced Collaborative Emissions Study (ACES), a multidisciplinary program being carried out by the Health Effects Institute and the Coordinating Research Council, is to determine whether improvements in the engineering of heavy-duty diesel engines reduce the oxidative stress and genotoxic risk associated with exposure to DE components. To this end, the genotoxicity and oxidative stress of DE from an improved diesel engine was evaluated in bioassays of tissues from Wistar Han rats and C57BL/6 mice exposed to DE. Genotoxicity was measured as strand breaks using an alkaline-modified comet assay. To correlate possible DNA damage found by the comet assay, measurement of DNA-adduct formation was evaluated by a competitive enzyme-linked immunosorbent assay (ELISA) to determine the levels of free 8-OHdG found in the serum of the animals exposed to DE. 8-OHdG is a specific modified base indicating an oxidative type of DNA damage to DNA nucleotides. In addition, a thiobarbituric acid reactive substances (TBARS) assay was used to assess oxidative stress and damage in the form of lipid peroxidation in the hippocampus region of the brains of DE-exposed animals. Results from the comet assay showed no significant differences in rats between the control and exposed groups (P = 0.53, low exposure; P = 0.92, medium exposure; P = 0.77, high exposure) after 1 month of DE exposure. There were no differences between sexes in the responses of rats to these exposures. Likewise, there were no significant differences found after 3 months of exposure. Similarly, no significant differences were found between the mice exposed for 1 and 3 months to DE, nor were any differences found between sexes. Measurements of 8-OHdG in both mice and rats showed no significant difference among DE exposure groups (P = 0.46, mice; P = 0.86, rats). In mice, measured 8-OHdG was lower in the 3-month group than the 1-month group. In rats, the inverse was true. In mice, no significant differences in the levels of lipid peroxidation, as measured by TBARS, were found between the controls and DE exposure groups (P = 0.92), nor were there any differences between sexes. In rats, comparisons between the control and low-exposure groups approached significance, but no significant differences were found between the other DE exposure groups. Additionally, in rats, there were no significant differences between the 1- and 3-month DE exposure groups.
Part 2. Assessment of genotoxicity after exposure to diesel exhaust from U.S. 2007-compliant diesel engines: report on 1- and 3-month exposures in the ACES bioassay.
Bemis JC, Torous DK, Dertinger SD … +1 more , HEI Health Review Committee
Res Rep Health Eff Inst · 2012 Sep · PMID 23156841
Micronucleus (MN*) formation is a well-established endpoint in genetic toxicology; studies designed to examine MN formation in vivo have been conducted for decades. Conditions that cause double-strand breaks or disrupt t...
Micronucleus (MN*) formation is a well-established endpoint in genetic toxicology; studies designed to examine MN formation in vivo have been conducted for decades. Conditions that cause double-strand breaks or disrupt the proper segregation of chromosomes during division result in an increase in MN frequency. Thus this endpoint is commonly employed in preclinical studies designed to assess the potential risks of human exposure to a myriad of chemical and physical agents, including inhaled diesel exhaust (DE). As part of the Advanced Collaborative Emissions Study (ACES) this investigation examined the potential of inhaled DE to induce chromosome damage in chronically exposed rodents. The ACES design included exposure of both rats and mice to DE derived from 2007-compliant heavy-duty engines. The exposure conditions consisted of air control and dilutions of DE resulting in three levels of exposure. At specified times, blood samples were collected, fixed, and shipped by the bioassay staff to Litron Laboratories for further processing and analysis. Significant improvements have been made to MN scoring by using objective, automated methods such as flow cytometry, which allows for the detection of micronucleated reticulocytes (MN-RET), micronucleated normochromatic erythrocytes (MN-NCE), and reticulocytes (RETs) in peripheral blood samples from mice and rats. By using a simple staining procedure coupled with rapid and efficient analysis, many more cells were examined in less time than was possible in traditional, microscopy-based MN assays. Thus, for each sample, 20,000 RETs were scored for the presence of MN. In the chronic-exposure bioassay, blood samples were obtained from independent groups of exposed animals at specific time points throughout the course of the entire study. This automated method is supported by numerous regulatory guidelines and meets the requirements for an Organization of Economic Cooperation and Development (OECD)-compliant assay for genotoxicity. Statistical approaches employed analysis of variance (ANOVA) to compare effects of sex, exposure condition, and duration, as well as their interactions. This initial assessment of MN was performed on both mouse and rat blood samples from the 1-month and 3-month exposures. The data from mice demonstrate the well established, sex-based difference in MN-RET and MN-NCE frequencies regularly observed in this species, with females exhibiting slightly lower frequencies. There were no sex-based differences observed in rats. An examination of the mean frequencies across the exposure groups and durations of exposure did not show an appreciable induction of MN at the 1- or 3-month exposures in either species. Further statistical analyses did not reveal any significant exposure-related effects. An examination of the potential genotoxic effects of DE is clearly valuable as part of a large-scale chronic-exposure bioassay. The data and observations from the 1-and 3-month exposure studies will eventually be combined with the results from the 1- and 2-year exposure studies to provide a comprehensive examination of chronic exposure to DE in a rodent model. This examination of chromosome damage serves an important role in the context of the entire ACES bioassay, which was designed to assess the safety of diesel combustion engines.
Part 1. Biologic responses in rats and mice to subchronic inhalation of diesel exhaust from U.S. 2007-compliant engines: report on 1-, 3-, and 12-month exposures in the ACES bioassay.
Mcdonald JD, Doyle-Eisele M, Gigliotti A … +7 more , Miller RA, Seilkop S, Mauderly JL, Seagrave J, Chow J, Zielinska B, HEI Health Review Committee
Res Rep Health Eff Inst · 2012 Sep · PMID 23156840
The Health Effects Institute and its partners conceived and funded a program to characterize the emissions from heavy-duty diesel engines compliant with the 2007 and 2010 on-road emissions standards in the United States...
The Health Effects Institute and its partners conceived and funded a program to characterize the emissions from heavy-duty diesel engines compliant with the 2007 and 2010 on-road emissions standards in the United States and to evaluate indicators of lung toxicity in rats and mice exposed repeatedly to diesel exhaust (DE*) from 2007-compliant engines. The preliminary hypothesis of this Advanced Collaborative Emissions Study (ACES) was that 2007-compliant on-road diesel emissions ". . . will not cause an increase in tumor formation or substantial toxic effects in rats and mice at the highest concentration of exhaust that can be used . . . although some biological effects may occur." This hypothesis is being tested at the Lovelace Respiratory Research Institute (LRRI) by exposing rats by chronic inhalation as a carcinogenicity bioassay, measuring indicators of pulmonary toxicity in rats after 1, 3, 12, and 24-30 months of exposure (final time point depends on the survival of animals), and measuring similar indicators of pulmonary toxicity in mice after 1 and 3 months of exposure. This report provides results of exposures through 3 months in rats and mice. Emissions from a 2007-compliant, 500-horsepower-class engine and aftertreatment system operated on a variable-duty cycle were used to generate the animal inhalation test atmospheres. Four treatment groups were exposed to one of three concentrations (dilutions) of exhaust combined with crankcase emissions, or to clean air as a negative control. Dilutions of exhaust were set to yield average integrated concentrations of 4.2, 0.8, and 0.1 ppm nitrogen dioxide (NO2). Exposure atmospheres were analyzed by daily measurements of key components and periodic detailed physical-chemical characterizations. Exposures were conducted 16 hr/dy (overnight), 5 dy/wk. Rats were evaluated for hematology, serum chemistry, bronchoalveolar lavage (BAL), lung cell proliferation, and histopathology after 1 month of exposure, and the same indicators plus pulmonary function after 3 months. Mice were evaluated for BAL, lung cell proliferation, and respiratory tract histopathology after 1 month of exposure, and the same indicators plus hematology and serum chemistry after 3 months. Samples from both species were collected for ancillary studies performed by investigators who were not at LRRI and were funded separately. Exposures were accomplished as planned, with average integrated exposure concentrations within 20% of the target dilutions. The major components were the gaseous inorganic compounds, nitrogen monoxide (NO), NO2, and carbon monoxide (CO). Minor components included low concentrations of diesel particulate matter (DPM) and volatile and semivolatile organic compounds (VOCs and SVOCs). There were no exposure-related differences in mortality or clinically evident morbidity. Among the more than 100 biologic response variables evaluated, the majority showed no significant difference from control as a result of exposure to DE. There was evidence of early lung changes in the rats, accompanied by a number of statistically significant increases in inflammatory and oxidative stress indicators, and some evidence of subtle changes in pulmonary function. In general, statistically significant effects were observed only at the highest exposure level. The mice did not have the same responses as the rats, but did have small but statistically significant increases in lavage neutrophils and the cytokine IL-6 at 1 month (but not at 3 months). These findings suggest that the rats were more sensitive than mice to the subchronic exposures.
Allergic inflammation in the human lower respiratory tract affected by exposure to diesel exhaust.
Riedl MA, Diaz-Sanchez D, Linn WS … +7 more , Gong H, Clark KW, Effros RM, Miller JW, Cocker DR, Berhane KT, HEI Health Review Committee
Res Rep Health Eff Inst · 2012 Feb · PMID 22852485
To improve understanding of human health risks from exposure to diesel exhaust particles (DEP*), we tested whether immunologic effects previously observed in the human nose also occur in the lower airways. Our overall hy...
To improve understanding of human health risks from exposure to diesel exhaust particles (DEP*), we tested whether immunologic effects previously observed in the human nose also occur in the lower airways. Our overall hypothesis was that cell influx and production of cytokines, chemokines, immunoglobulin E (IgE), and other mediators, which would be measurable in sputum and blood, occur in people with asthma after realistic controlled exposures to diesel exhaust (DE). In Phase 1 we tested for direct effects of DE in subjects with clinically undifferentiated mild asthma. In Phase 2 we tested whether DE exposure would exacerbate response to inhaled cat allergen in subjects with both asthma and cat sensitivity. The exposure facility was a controlled-environment chamber supplied with DE from an idling medium-duty truck with ultra-low-sulfur fuel and no catalytic converter. We exposed volunteers for 2 hours with intermittent exercise to exhaust with DEP mass concentration near 100 microg/m3. Exposures to nitrogen dioxide (NO2) near 0.35 ppm (similar to its concentration in DE) and to filtered air (FA) served as controls. Blood was drawn before exposure on day 1 and again the next morning (day 2). Sputum was induced only on day 2. Bronchial reactivity was measured -1 hour after exposure ended. Supplementary endpoints included measures of blood coagulation status, cardiopulmonary physiology, and symptoms. Each phase employed 15 subjects with asthma; 3 subjects participated in both phases. In Phase 1, airway reactivity was measured with inhaled methacholine; in Phase 2, with inhaled cat allergen. We found little biologic response to DE exposure compared with exposure to control atmospheres. In Phase 1, interleukin 4 (IL-4) in sputum showed an estimated 1.7-fold increase attributable to DE exposure, which was close to statistical significance; airway resistance increased modestly but significantly on day 2 after DE exposure; and nonspecific symptom scores increased significantly during DE exposure. In Phase 2, indicators of airway inflammation in sputum showed a possibly meaningful response: polymorphonuclear leukocytes (PMNs) and eosinophils increased after DE exposure, whereas macrophages decreased. IgE in sputum and the bronchoconstrictive response to cat allergen varied significantly between atmospheres, but not in patterns consistent with our primary hypothesis. Symptom score changes relatable to DE exposure were smaller than those in Phase 1 and not statistically significant. Controlled exposures, lasting 2 hours with intermittent exercise, to diluted DE at a particle mass concentration of 100 microg/m3 did not evoke clear and consistent lower-airway or systemic immunologic or inflammatory responses in mildly asthmatic subjects, with or without accompanying challenge with cat allergen. Likewise, these DE exposures did not significantly increase nonspecific or allergen-specific bronchial reactivity. A few isolated statistically significant or near-significant changes were observed during and after DE exposure, including increases in nonspecific symptoms (e.g., headache, nausea) suggestive of subtle, rapid-onset systemic effects. It is possible the lower respiratory tract is more resistant than the nose to adjuvant effects of diesel particles on allergic inflammation, so that no meaningful effects occur under exposure conditions like these. Alternatively, the experimental conditions may have been near a threshold for finding effects. That is, important lower respiratory effects may occur but may be detectable experimentally with slightly higher DEP concentrations, longer exposures, more invasive testing (e.g., bronchoalveolar lavage), or more susceptible subjects. However, ethical and practical barriers to such experiments are considerable.
Assessing the impact of a wood stove replacement program on air quality and children's health.
Noonan CW, Ward TJ, Navidi W … +4 more , Sheppard L, Bergauff M, Palmer C, HEI Health Review Committee
Res Rep Health Eff Inst · 2011 Dec · PMID 22852484
Many rural mountain valley communities experience elevated ambient levels of fine particulate matter (PM*) in the winter, because of contributions from residential wood-burning appliances and sustained temperature invers...
Many rural mountain valley communities experience elevated ambient levels of fine particulate matter (PM*) in the winter, because of contributions from residential wood-burning appliances and sustained temperature inversion periods during the cold season. A wood stove change-out program was implemented in a community heavily affected by wood-smoke-derived PM2.5 (PM < or = 2.5 microm in aerodynamic diameter). The objectives of this study were to evaluate the impact of this intervention program on ambient and indoor PM2.5 concentrations and to identify possible corresponding changes in the frequency of childhood respiratory symptoms and infections and illness-related school absences. Over 1100 old wood stoves were replaced with new EPA-certified wood stoves or other heating sources. Ambient PM2.5 concentrations were 30% lower in the winter after the changeout program, compared with baseline winters, which brought the community's ambient air within the PM2.5 standards of the U.S. Environmental Protection Agency (U.S. EPA). The installation of a new wood stove resulted in an overall reduction in indoor PM2.5 concentrations in a small sample of wood-burning homes, but the effects were highly variable across homes. Community-level reductions in wood-smoke-derived PM2.5 concentration were associated with decreased reports of childhood wheeze and of other childhood respiratory health conditions. The association was not limited to children living in homes with wood stoves nor does it appear to be limited to susceptible children (e.g., children with asthma). Community-level reductions in wood-smoke-derived PM2.5 concentration were also associated with lower illness-related school absences among older children, but this finding was not consistent across all age-groups. This community-level intervention provided a unique opportunity to prospectively observe exposure and outcome changes resulting from a targeted air pollution reduction strategy.
Effects of short-term exposure to air pollution on hospital admissions of young children for acute lower respiratory infections in Ho Chi Minh City, Vietnam.
HEI Collaborative Working Group on Air Pollution, Poverty, and Health in Ho Chi Minh City, Le TG, Ngo L … +6 more , Mehta S, Do VD, Thach TQ, Vu XD, Nguyen DT, Cohen A
Res Rep Health Eff Inst · 2012 Jun · PMID 22849236
There is emerging evidence, largely from studies in Europe and North America, that economic deprivation increases the magnitude of morbidity and mortality related to air pollution. Two major reasons why this may be true...
There is emerging evidence, largely from studies in Europe and North America, that economic deprivation increases the magnitude of morbidity and mortality related to air pollution. Two major reasons why this may be true are that the poor experience higher levels of exposure to air pollution, and they are more vulnerable to its effects--in other words, due to poorer nutrition, less access to medical care, and other factors, they experience more health impact per unit of exposure. The relations among health, air pollution, and poverty are likely to have important implications for public health and social policy, especially in areas such as the developing countries of Asia where air pollution levels are high and many live in poverty. The aims of this study were to estimate the effect of exposure to air pollution on hospital admissions of young children for acute lower respiratory infection (ALRI*) and to explore whether such effects differed between poor children and other children. ALRI, which comprises pneumonia and bronchiolitis, is the largest single cause of mortality among young children worldwide and is responsible for a substantial burden of disease among young children in developing countries. To the best of our knowledge, this is the first study of the health effects of air pollution in Ho Chi Minh City (HCMC), Vietnam. For these reasons, the results of this study have the potential to make an important contribution to the growing literature on the health effects of air pollution in Asia. The study focused on the short-term effects of daily average exposure to air pollutants on hospital admissions of children less than 5 years of age for ALRI, defined as pneumonia or bronchiolitis, in HCMC during 2003, 2004, and 2005. Admissions data were obtained from computerized records of Children's Hospital 1 and Children's Hospital 2 (CH1 and CH2) in HCMC. Nearly all children hospitalized for respiratory illnesses in the city are admitted to one of these two pediatric hospitals. Daily citywide 24-hour average concentrations of particulate matter (PM) < or =10 microm in aerodynamic diameter (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2) and 8-hour maximum average concentrations of ozone (O3) were estimated from the HCMC Environmental Protection Agency (HEPA) ambient air quality monitoring network. Daily meteorologic information including temperature and relative humidity were collected from KTTV NB, the Southern Regional Hydro-Meteorological Center. An individual-level indicator of socioeconomic position (SEP) was based on the degree to which the patient was exempt from payment according to hospital financial records. A group-level indicator of SEP was based on estimates of poverty prevalence in the districts of HCMC in 2004, obtained from a poverty mapping project of the Institute of Economic Research in HCMC, in collaboration with the General Statistics Office of Vietnam and the World Bank. Poverty prevalence was defined using the poverty line set by the People's Committee of HCMC of 6 million Vietnamese dong (VND) annual income. Quartiles of district-level poverty prevalence were created based on poverty prevalence estimates for each district. Analyses were conducted using both time-series and case-crossover approaches. In the absence of measurement error, confounding, and other sources of bias, the two approaches were expected to provide estimates that differed only with regard to precision. For the time-series analyses, the unit of observation was daily counts of hospital admissions for ALRI. Poisson regression with smoothing functions for meteorologic variables and variables for seasonal and long-term trends was used. Case-crossover analyses were conducted using time-stratified selection of controls. Control days were every 7th day from the date of admission within the same month as admission. Large seasonal differences were observed in pollutant levels and hospital admission patterns during the investigation period for HCMC. Of the 15,717 ALRI admissions occurring within the study period, 60% occurred in the rainy season (May through October), with a peak in these admissions during July and August of each year. Average daily concentrations for PM10, O3, NO2, and SO2 were 73, 75, 22, and 22 microg/m3, respectively, with higher pollutant concentrations observed in the dry season (November through April) compared with the rainy season. As the time between onset of illness and hospital admission was thought to range from 1 to 6 days, it was not possible to specify a priori a single-day lag. We assessed results for single-day lags from lag 0 to lag 10, but emphasize results for an average of lag 1-6, since this best reflects the case reference period. Results were robust to differences in temperature lags with lag 0 and the average lag (1-6 days); results for lag 0 for temperature are presented. Results differed markedly when analyses were stratified by season, rather than simply adjusted for season. ALRI admissions were generally positively associated with ambient levels of PM10, NO2, and SO2 during the dry season (November-April), but not the rainy season (May-October). Positive associations between O3 and ALRI admissions were not observed in either season. We do not believe that exposure to air pollution could reduce the risk of ALRI in the rainy season and infer that these results could be driven by residual confounding present within the rainy season. The much lower correlation between NO2 and PM10 levels during the rainy season provides further evidence that these pollutants may not be accurate indicators of exposure to air pollution from combustion processes in the rainy season. Results were generally consistent across time-series and case-crossover analyses. In the dry season, risks for ALRI hospital admissions with average pollutant lag (1-6 days) were highest for NO2 and SO2 in the single-pollutant case-crossover analyses, with excess risks of 8.50% (95% CI, 0.80-16.79) and 5.85% (95% CI, 0.44-11.55) observed, respectively. NO2 and SO2 effects remained higher than PM10 effects in both the single-pollutant and two-pollutant models. The two-pollutant model indicated that NO2 confounded the PM10 and SO2 effects. For example, PM10 was weakly associated with an excess risk in the dry season of 1.25% (95% CI, -0.55 to 3.09); after adjusting for SO2 and O3, the risk estimate was reduced but remained elevated, with much wider confidence intervals; after adjusting for NO2, an excess risk was no longer observed. Though the effects seem to be driven by NO2, the statistical limitations of adequately addressing collinearity, given the high correlation between PM10 and NO2 (r = 0.78), limited our ability to clearly distinguish between PM10 and NO2 effects. In the rainy season, negative associations between PM10 and ALRI admissions were observed. No association with O3 was observed in the single-pollutant model, but O3 exposure was negatively associated with ALRI admissions in the two-pollutant model. There was little evidence of an association between NO2 and ALRI admissions. The single-pollutant estimate from the case-crossover analysis suggested a negative association between NO2 and ALRI admissions, but this effect was no longer apparent after adjustment for other pollutants. Although associations between SO2 and ALRI admissions were not observed in the rainy season, point estimates for the case-crossover analyses suggested negative associations, while time-series (Poisson regression) analyses suggested positive associations--an exception to the general consistency between case-crossover and time-series results. Results were robust to differences in seasonal classification. Inclusion of rainfall as a continuous variable and the seasonal reclassification of selected series of data did not influence results. No clear evidence of station-specific effects could be observed, since results for the different monitoring stations had overlapping confidence intervals. In the dry season, increased concentrations of NO2 and SO2 were associated with increased hospital admissions of young children for ALRI in HCMC. PM10 could also be associated with increased hospital admissions in the dry season, but the high correlation of 0.78 between PM10 and NO2 levels limits our ability to distinguish between PM10 and NO2 effects. Nevertheless, the results support the presence of an association between combustion-source pollution and increased ALRI admissions. There also appears to be evidence of uncontrolled negative confounding within the rainy season, with higher incidence of ALRI and lower pollutant concentrations overall. Exploratory analyses made using limited historical and regional data on monthly prevalence of respiratory syncytial virus (RSV) suggest that an unmeasured, time-varying confounder (RSV, in this case) could have, in an observational study like this one, created enough bias to reverse the observed effect estimates of pollutants in the rainy season. In addition, with virtually no RSV incidence in the dry season, these findings also lend some credibility to the notion that RSV could influence results primarily in the rainy season. Analyses were not able to identify differential effects by individual-level indicators of SEP, mainly due to the small number of children classified as poor based on information in the hospitals' financial records. Analyses assessing differences in effect by district-level indicator of SEP did not indicate a clear trend in risk across SEP quartiles, but there did appear to be a slightly higher risk among the residents of districts with the highest quartile of SEP. As these are the districts within the urban center of HCMC, results could be indicative of increased exposures for residents living within the city center. (ABSTRACT TRUNCATED)
Assessment and statistical modeling of the relationship between remotely sensed aerosol optical depth and PM2.5 in the eastern United States.
Paciorek CJ, Liu Y, HEI Health Review Committee
Res Rep Health Eff Inst · 2012 May · PMID 22838153
Research in scientific, public health, and policy disciplines relating to the environment increasingly makes use of high-dimensional remote sensing and the output of numerical models in conjunction with traditional obser...
Research in scientific, public health, and policy disciplines relating to the environment increasingly makes use of high-dimensional remote sensing and the output of numerical models in conjunction with traditional observations. Given the public health and resultant public policy implications of the potential health effects of particulate matter (PM*) air pollution, specifically fine PM with an aerodynamic diameter < or = 2.5 pm (PM2.5), there has been substantial recent interest in the use of remote-sensing information, in particular aerosol optical depth (AOD) retrieved from satellites, to help characterize variability in ground-level PM2.5 concentrations in space and time. While the United States and some other developed countries have extensive PM monitoring networks, gaps in data across space and time necessarily occur; the hope is that remote sensing can help fill these gaps. In this report, we are particularly interested in using remote-sensing data to inform estimates of spatial patterns in ambient PM2.5 concentrations at monthly and longer time scales for use in epidemiologic analyses. However, we also analyzed daily data to better disentangle spatial and temporal relationships. For AOD to be helpful, it needs to add information beyond that available from the monitoring network. For analyses of chronic health effects, it needs to add information about the concentrations of long-term average PM2.5; therefore, filling the spatial gaps is key. Much recent evidence has shown that AOD is correlated with PM2.5 in the eastern United States, but the use of AOD in exposure analysis for epidemiologic work has been rare, in part because discrepancies necessarily exist between satellite-retrieved estimates of AOD, which is an atmospheric-column average, and ground-level PM2.5. In this report, we summarize the results of a number of empirical analyses and of the development of statistical models for the use of proxy information, in particular satellite AOD, in predicting PM2.5 concentrations in the eastern United States. We analyzed the spatiotemporal structure of the relationship between PM2.5 and AOD, first using simple correlations both before and after calibration based on meteorology, as well as large-scale spatial and temporal calibration to account for discrepancies between AOD and PM2.5. We then used both raw and calibrated AOD retrievals in statistical models to predict PM2.5 concentrations, accounting for AOD in two ways: primarily as a separate data source contributing a second likelihood to a Bayesian statistical model, as well as a data source on which we could directly regress. Previous consideration of satellite AOD has largely focused on the National Aeronautics and Space Administration (NASA) moderate resolution imaging spectroradiometer (MODIS) and multiangle imaging spectroradiometer (MISR) instruments. One contribution of our work is more extensive consideration of AOD derived from the Geostationary Operational Environmental Satellite East Aerosol/Smoke Product (GOES GASP) AOD and its relationship with PM2.5. In addition to empirically assessing the spatiotemporal relationship between GASP AOD and PM2.5, we considered new statistical techniques to screen anomalous GOES reflectance measurements and account for background surface reflectance. In our statistical work, we developed a new model structure that allowed for more flexible modeling of the proxy discrepancy than previous statistical efforts have had, with a computationally efficient implementation. We also suggested a diagnostic for assessing the scales of the spatial relationship between the proxy and the spatial process of interest (e.g., PM2.5). In brief, we had little success in improving predictions in our eastern-United States domain for use in epidemiologic applications. We found positive correlations of AOD with PM2.5 over time, but less correlation for long-term averages over space, unless we used calibration that adjusted for large-scale discrepancy between AOD and PM2.5 (see sections 3, 4, and 5). Statistical models that combined AOD, PM2.5 observations, and land-use and meteorologic variables were highly predictive of PM2.5 observations held out of the modeling, but AOD added little information beyond that provided by the other sources (see sections 5 and 6). When we used PM2.5 data estimates from the Community Multiscale Air Quality model (CMAQ) as the proxy instead of using AOD, we similarly found little improvement in predicting held-out observations of PM2.5, but when we regressed on CMAQ PM2.5 estimates, the predictions improved moderately in some cases. These results appeared to be caused in part by the fact that large-scale spatial patterns in PM2.5 could be predicted well by smoothing the monitor values, while small-scale spatial patterns in AOD appeared to weakly reflect the variation in PM2.5 inferred from the observations. Using a statistical model that allowed for potential proxy discrepancy at both large and small spatial scales was an important component of our modeling. In particular, when our models did not include a component to account for small-scale discrepancy, predictive performance decreased substantially. Even long-term averages of MISR AOD, considered the best, albeit most sparse, of the AOD products, were only weakly correlated with measured PM2.5 (see section 4). This might have been partly related to the fact that our analysis did not account for spatial variation in the vertical profile of the aerosol. Furthermore, we found evidence that some of the correlation between raw AOD and PM2.5 might have been a function of surface brightness related to land use, rather than having been driven by the detection of aerosol in the AOD retrieval algorithms (see sections 4 and 7). Difficulties in estimating the background surface reflectance in the retrieval algorithms likely explain this finding. With regard to GOES, we found moderate correlations of GASP AOD and PM2.5. The higher correlations of monthly and yearly averages after calibration reflected primarily the improved large-scale correlation, a necessary result of the calibration procedure (see section 3). While the results of this study's GOES reflectance screening and surface reflection correction appeared sensible, correlations of our proposed reflectance-based proxy with PM2.5 were no better than GASP AOD correlations with PM2.5 (see section 7). We had difficulty improving spatial prediction of monthly and yearly average PM2.5 using AOD in the eastern United States, which we attribute to the spatial discrepancy between AOD and measured PM2.5, particularly at smaller scales. This points to the importance of paying attention to the discrepancy structure of proxy information, both from remote-sensing and deterministic models. In particular, important statistical challenges arise in accounting for the discrepancy, given the difficulty in the face of sparse observations of distinguishing the discrepancy from the component of the proxy that is informative about the process of interest. Associations between adverse health outcomes and large-scale variation in PM2.5 (e.g., across regions) may be confounded by unmeasured spatial variation in factors such as diet. Therefore, one important goal was to use AOD to improve predictions of PM2.5 for use in epidemiologic analyses at small-to-moderate spatial scales (within urban areas and within regions). In addition, large-scale PM2.5 variation is well estimated from the monitoring data, at least in the United States. We found little evidence that current AOD products are helpful for improving prediction at small-to-moderate scales in the eastern United States and believe more evidence for the reliability of AOD as a proxy at such scales is needed before making use of AOD for PM2.5 prediction in epidemiologic contexts. While our results relied in part on relatively complicated statistical models, which may be sensitive to modeling assumptions, our exploratory correlation analyses (see sections 3 and 5) and relatively simple regression-style modeling of MISR AOD (see section 4) were consistent with the more complicated modeling results. When assessing the usefulness of AOD in the context of studying chronic health effects, we believe efforts need to focus on disentangling the temporal from the spatial correlations of AOD and PM2.5 and on understanding the spatial scale of correlation and of the discrepancy structure. While our results are discouraging, it is important to note that we attempted to make use of smaller-scale spatial variation in AOD to distinguish spatial variations of relatively small magnitude in long-term concentrations of ambient PM2.5. Our efforts pushed the limits of current technology in a spatial domain with relatively low PM2.5 levels and limited spatial variability. AOD may hold more promise in areas with higher aerosol levels, as the AOD signal would be stronger there relative to the background surface reflectance. Furthermore, for developing countries with high aerosol levels, it is difficult to build statistical models based on PM2.5 measurements and land-use covariates, so AOD may add more incremental information in those contexts. More generally, researchers in remote sensing are involved in ongoing efforts to improve AOD products and develop new approaches to using AOD, such as calibration with model-estimated vertical profiles and the use of speciation information in MISR AOD; these efforts warrant continued investigation of the usefulness of remotely sensed AOD for public health research.
Assessment of the health impacts of particulate matter characteristics.
Bell ML, HEI Health Review Committee
Res Rep Health Eff Inst · 2012 Jan · PMID 22393584
While numerous studies have demonstrated that shortterm exposure to particulate matter (PM*) is associated with adverse health effects, the characteristics of PM that cause harm are not well understood, and PM toxicity m...
While numerous studies have demonstrated that shortterm exposure to particulate matter (PM*) is associated with adverse health effects, the characteristics of PM that cause harm are not well understood, and PM toxicity may vary by its chemical composition. This study investigates whether spatial and temporal patterns in PM health effect estimates based on total mass can be explained by spatial and temporal heterogeneity in the chemical composition of the particles. A database of 52 chemical components of PM with an aerodynamic diameter < or = 2.5 pm (PM2.5) was constructed for 187 U.S. counties, for 2000 through 2005, based on data from U.S. Environmental Protection Agency (U.S. EPA) monitoring networks. Components that covary with PM2.5 total mass and/or are large contributors to PM2.5, total mass were identified using actual and seasonally detrended data. Using Bayesian hierarchical modeling, seasonal and temporal variation in PM2.5 and the risk of total, cardiovascular, and respiratory hospital admissions were investigated for persons > or = 65 years in 202 U.S. counties for 1999 through 2005. Seasonal variation was investigated using three model structures with different underlying assumptions about the relationship between PM2.5 and hospitalizations. The findings of this study indicate higher effects in winter for both causes of hospitalization, and higher effects in the Northeast for cardiovascular admissions, although 53% of the counties were in this region. Higher PM2.5 effect estimates for cardiovascular or respiratory hospitalizations were observed in seasons and counties with a higher PM2.5 content of nickel (Ni), vanadium (V), or EC. Mortality effect estimates for PM with an aerodynamic diameter < or = 10 pm (PM10) were higher in seasons and counties with higher PM2.5 Ni content. The association between the Ni content of PM2.5 and effect estimates for cardiovascular hospitalization was robust to adjustment by EC, V, or both EC and V. An interquartile range (IQR) increase in the fraction of PM2.5 that is Ni was associated with a 14.9% (PI, 3.4-26.4) increase in the relative rates of cardiovascular hospital admissions associated with PM2.5 total mass adjusted for EC and V. No associations were observed between PM total mass health effect estimates and community-level variables for socioeconomic status, racial composition, or urbanicity. Communities with a higher prevalence of central AC had lower PM2.5 effect estimates for cardiovascular hospital admissions. The findings of this study indicate strong spatial and temporal variation in the chemical composition of the particle mixture and in the regional and seasonal variation in health effect estimates for PM2.5 total mass. The chemical composition of particles partially explained the heterogeneity of effect estimates. Observed associations could be related to the components themselves, to other components, or to a combination of components that share similar sources. The findings do not exclude the possibility that other components or characteristics of PM are harmful. The limitations of this study include the use of community-level aggregated data for exposure and for the variables used to investigate alternate hypotheses. Also, particle components and chemical forms (e.g., ammonium sulfate) not measured in the U.S. EPA database were not included. PM10 results in particular should be viewed with caution as the time frame of measurement and PM size fraction are different for the chemical composition and health effects data. A better understanding of the particular chemical components or sources that are most harmful to health can help decision-makers develop more targeted air pollution regulations and can aid in understanding the biological mechanisms by which air pollution-related health effects occur, thereby informing future research.
Pulmonary particulate matter and systemic microvascular dysfunction.
Nurkiewicz TR, Porter DW, Hubbs AF … +13 more , Stone S, Moseley AM, Cumpston JL, Goodwill AG, Frisbee SJ, Perrotta PL, Brock RW, Frisbee JC, Boegehold MA, Frazer DG, Chen BT, Castranova V, HEI Health Review Committee
Res Rep Health Eff Inst · 2011 Dec · PMID 22329339
Pulmonary particulate matter (PM) exposure has been epidemiologically associated with an increased risk of cardiovascular morbidity and mortality, but the mechanistic foundations for this association are unclear. Exposur...
Pulmonary particulate matter (PM) exposure has been epidemiologically associated with an increased risk of cardiovascular morbidity and mortality, but the mechanistic foundations for this association are unclear. Exposure to certain types of PM causes changes in the vascular reactivity of several macrovascular segments. However, no studies have focused upon the systemic microcirculation, which is the primary site for the development of peripheral resistance and, typically, the site of origin for numerous pathologies. Ultrafine PM--also referred to as nanoparticles, which are defined as ambient and engineered particles with at least one physical dimension less than 100 nm (Oberdorster et al. 2005)--has been suggested to be more toxic than its larger counterparts by virtue of a larger surface area per unit mass. The purpose of this study was fourfold: (1) determine whether particle size affects the severity of postexposure microvascular dysfunction; (2) characterize alterations in microvascular nitric oxide (NO) production after PM exposure; (3) determine whether alterations in microvascular oxidative stress are associated with NO production, arteriolar dysfunction, or both; and (4) determine whether circulating inflammatory mediators, leukocytes, neurologic mechanisms, or a combination of these play a fundamental role in mediating pulmonary PM exposure and peripheral microvascular dysfunction. To achieve these goals, we created an inhalation chamber that generates stable titanium dioxide (TiO2) aerosols at concentrations up to 20 mg/m3. TiO2 is a well-characterized particle devoid of soluble metals. Sprague Dawley and Fischer 344 (F-344) rats were exposed to fine or nano-TiO2 PM (primary count modes of approximately 710 nm and approximately 100 nm in diameter, respectively) at concentrations of 1.5 to 16 mg/m3 for 4 to 12 hours to produce pulmonary loads of 7 to 150 microg in each rat. Twenty-four hours after pulmonary exposure, the following procedures were performed: the spinotrapezius muscle was prepared for in vivo microscopy, blood samples were taken from an arterial line, and various tissues were harvested for histologic and immunohistochemical analyses. Some rats received a bolus dose of cyclophosphamide 3 days prior to PM exposure to deplete circulating neutrophils and bronchoalveolar lavage (BAL) was performed in separate groups of rats exposed to identical TiO2 loads. No significant differences in BAL fluid composition based on PM size or load were found in these rats. Plasma levels of interleukin (IL)-2, IL-18, IL-13, and growth-related oncogene (GRO) (also known as keratinocyte-derived-chemokine [KC]) were altered after PM exposure. In rats exposed to fine TiO2, endothelium-dependent arteriolar dilation was significantly decreased, and this dysfunction was robustly augmented in rats exposed to nano-TiO2. This effect was not related to an altered smooth-muscle responsiveness to NO because arterioles in both groups dilated comparably in response to the NO donor sodium nitroprusside (SNP). Endogenous microvascular NO production was similarly decreased after inhalation of either fine or nano-TiO2 in a dose-dependent manner. Microvascular oxidative stress was significantly increased among both exposure groups. Furthermore, treatment with antioxidants (2,2,6,6-tetramethylpiperdine-N-oxyl [TEMPOL] plus catalase), the myeloperoxidase (MPO) inhibitor 4-aminobenzoic hydrazide (ABAH), or the nicotinamide adenine dinucleotide phosphate oxidase (NADPH oxidase) inhibitor apocynin partially restored NO production and normalized arteriolar function in both groups. Neutrophil depletion restored dilation in PM-exposed rats by as much as 42%. Coincubation of the spinotrapezius muscle with the fast sodium (Na+) channel antagonist tetrodotoxin (TTX) restored arteriolar dilation by as much as 54%, suggesting that sympathetic neural input may be affected by PM exposure. The results of these experiments indicate that (1) the size of inhaled PM dictates the intensity of systemic microvascular dysfunction; (2) this arteriolar dysfunction is characterized by a decreased bioavailability of endogenous NO; (3) the loss of bioavailable NO after PM exposure is at least partially caused by elevations in local oxidative stress, MPO activity, NADPH oxidase activity, or a combination of these responses; and (4) circulating neutrophils and sympathetic neurogenic mechanisms also appear to be involved in the systemic microvascular dysfunction that follows PM exposure. Taken together, these mechanistic studies support prominent hypotheses that suggest peripheral vascular effects associated with PM exposure are due to the activation of inflammatory mechanisms, neurogenic mechanisms, or both.
The London low emission zone baseline study.
Kelly F, Armstrong B, Atkinson R … +9 more , Anderson HR, Barratt B, Beevers S, Cook D, Green D, Derwent D, Mudway I, Wilkinson P, HEI Health Review Committee
Res Rep Health Eff Inst · 2011 Nov · PMID 22315924
On February 4, 2008, the world's largest low emission zone (LEZ) was established. At 2644 km2, the zone encompasses most of Greater London. It restricts the entry of the oldest and most polluting diesel vehicles, includi...
On February 4, 2008, the world's largest low emission zone (LEZ) was established. At 2644 km2, the zone encompasses most of Greater London. It restricts the entry of the oldest and most polluting diesel vehicles, including heavy-goods vehicles (haulage trucks), buses and coaches, larger vans, and minibuses. It does not apply to cars or motorcycles. The LEZ scheme will introduce increasingly stringent Euro emissions standards over time. The creation of this zone presented a unique opportunity to estimate the effects of a stepwise reduction in vehicle emissions on air quality and health. Before undertaking such an investigation, robust baseline data were gathered on air quality and the oxidative activity and metal content of particulate matter (PM) from air pollution monitors located in Greater London. In addition, methods were developed for using databases of electronic primary-care records in order to evaluate the zone's health effects. Our study began in 2007, using information about the planned restrictions in an agreed-upon LEZ scenario and year-on-year changes in the vehicle fleet in models to predict air pollution concentrations in London for the years 2005, 2008, and 2010. Based on this detailed emissions and air pollution modeling, the areas in London were then identified that were expected to show the greatest changes in air pollution concentrations and population exposures after the implementation of the LEZ. Using these predictions, the best placement of a pollution monitoring network was determined and the feasibility of evaluating the health effects using electronic primary-care records was assessed. To measure baseline pollutant concentrations before the implementation of the LEZ, a comprehensive monitoring network was established close to major roadways and intersections. Output-difference plots from statistical modeling for 2010 indicated seven key areas likely to experience the greatest change in concentrations of nitrogen dioxide (NO2) (at least 3 microg/m3) and of PM with an aerodynamic diameter < or = 10 microm (PM10) (at least 0.75 microg/m3) as a result of the LEZ; these suggested that the clearest signals of change were most likely to be measured near roadsides. The seven key areas were also likely to be of importance in carrying out a study to assess the health outcomes of an air quality intervention like the LEZ. Of the seven key areas, two already had monitoring sites with a full complement of equipment, four had monitoring sites that required upgrades of existing equipment, and one required a completely new installation. With the upgrades and new installations in place, fully ratified (verified) pollutant data (for PM10, PM with an aerodynamic diameter < or = 2.5 microm [PM2.5], nitrogen oxides [NOx], and ozone [O3] at all sites as well as for particle number, black smoke [BS], carbon monoxide [CO], and sulfur dioxide [SO2] at selected sites) were then collected for analysis. In addition, the seven key monitoring sites were supported by other sites in the London Air Quality Network (LAQN). From these, a robust set of baseline air quality data was produced. Data from automatic and manual traffic counters as well as automatic license-plate recognition cameras were used to compile detailed vehicle profiles. This enabled us to establish more precise associations between ambient pollutant concentrations and vehicle emissions. An additional goal of the study was to collect baseline PM data in order to test the hypothesis that changes in traffic densities and vehicle mixes caused by the LEZ would affect the oxidative potential and metal content of ambient PM10 and PM2.5. The resulting baseline PM data set was the first to describe, in detail, the oxidative potential and metal content of the PM10 and PM2.5 of a major city's airshed. PM in London has considerable oxidative potential; clear differences in this measure were found from site to site, with evidence that the oxidative potential of both PM10 and PM2.5 at roadside monitoring sites was higher than at urban background locations. In the PM10 samples this increased oxidative activity appeared to be associated with increased concentrations of copper (Cu), barium (Ba), and bathophenanthroline disulfonate-mobilized iron (BPS Fe) in the roadside samples. In the PM2.5 samples, no simple association could be seen, suggesting that other unmeasured components were driving the increased oxidative potential in this fraction of the roadside samples. These data suggest that two components were contributing to the oxidative potential of roadside PM, namely Cu and BPS Fe in the coarse fraction of PM (PM with an aerodynamic diameter of 2.5 microm to 10 microm; PM(2.5-10)) and an unidentified redox catalyst in PM2.5. The data derived for this baseline study confirmed key observations from a more limited spatial mapping exercise published in our earlier HEI report on the introduction of the London's Congestion Charging Scheme (CCS) in 2003 (Kelly et al. 2011a,b). In addition, the data set in the current report provided robust baseline information on the oxidative potential and metal content of PM found in the London airshed in the period before implementation of the LEZ; the finding that a proportion of the oxidative potential appears in the PM coarse mode and is apparently related to brake wear raises important issues regarding the nature of traffic management schemes. The final goal of this baseline study was to establish the feasibility, in ethical and operational terms, of using the U.K.'s electronic primary-care records to evaluate the effects of the LEZ on human health outcomes. Data on consultations and prescriptions were compiled from a pilot group of general practices (13 distributed across London, with 100,000 patients; 29 situated in the inner London Borough of Lambeth, with 200,000 patients). Ethics approvals were obtained to link individual primary-care records to modeled NOx concentrations by means of post-codes. (To preserve anonymity, the postcodes were removed before delivery to the research team.) A wide range of NOx exposures was found across London as well as within and between the practices examined. Although we observed little association between NOx exposure and smoking status, a positive relationship was found between exposure and increased socioeconomic deprivation. The health outcomes we chose to study were asthma, chronic obstructive pulmonary disease, wheeze, hay fever, upper and lower respiratory tract infections, ischemic heart disease, heart failure, and atrial fibrillation. These outcomes were measured as prevalence or incidence. Their distributions by age, sex, socioeconomic deprivation, ethnicity, and smoking were found to accord with those reported in the epidemiology literature. No cross-sectional positive associations were found between exposure to NOx and any of the studied health outcomes; some associations were significantly negative. After the pilot study, a suitable primary-care database of London patients was identified, the General Practice Research Database responsible for giving us access to these data agreed to collaborate in the evaluation of the LEZ, and an acceptable method of ensuring privacy of the records was agreed upon. The database included about 350,000 patients who had remained at the same address over the four-year period of the study. Power calculations for a controlled longitudinal analysis were then performed, indicating that for outcomes such as consultations for respiratory illnesses or prescriptions for asthma there was sufficient power to identify a 5% to 10% reduction in consultations for patients most exposed to the intervention compared with patients presumed to not be exposed to it. In conclusion, the work undertaken in this study provides a good foundation for future LEZ evaluations. Our extensive monitoring network, measuring a comprehensive set of pollutants (and a range of particle metrics), will continue to provide a valuable tool both for assessing the impact of LEZ regulations on air quality in London and for furthering understanding of the link between PM's composition and toxicity. Finally, we believe that in combination with our modeling of the predicted population-based changes in pollution exposure in London, the use of primary-care databases forms a sound basis and has sufficient statistical power for the evaluation of the potential impact of the LEZ on human health.
Personal and ambient exposures to air toxics in Camden, New Jersey.
Lioy PJ, Fan Z, Zhang J … +15 more , Georgopoulos P, Wang SW, Ohman-Strickland P, Wu X, Zhu X, Harrington J, Tang X, Meng Q, Jung KH, Kwon J, Hernandez M, Bonnano L, Held J, Neal J, HEI Health Review Committee
Res Rep Health Eff Inst · 2011 Aug · PMID 22097188
Personal exposures and ambient concentrations of air toxics were characterized in a pollution "hot spot" and an urban reference site, both in Camden, New Jersey. The hot spot was the city's Waterfront South neighborhood;...
Personal exposures and ambient concentrations of air toxics were characterized in a pollution "hot spot" and an urban reference site, both in Camden, New Jersey. The hot spot was the city's Waterfront South neighborhood; the reference site was a neighborhood, about 1 km to the east, around the intersection of Copewood and Davis streets. Using personal exposure measurements, residential ambient air measurements, statistical analyses, and exposure modeling, we examined the impact of local industrial and mobile pollution sources, particularly diesel trucks, on personal exposures and ambient concentrations in the two neighborhoods. Presented in the report are details of our study design, sample and data collection methods, data- and model-analysis approaches, and results and key findings of the study. In summary, 107 participants were recruited from nonsmoking households, including 54 from Waterfront South and 53 from the Copewood-Davis area. Personal air samples were collected for 24 hr and measured for 32 target compounds--11 volatile organic compounds (VOCs*), four aldehydes, 16 polycyclic aromatic hydrocarbons (PAHs), and particulate matter (PM) with an aerodynamic diameter < or = 2.5 microm (PM2.5). Simultaneously with the personal monitoring, ambient concentrations of the target compounds were measured at two fixed monitoring sites, one each in the Waterfront South and Copewood-Davis neighborhoods. To understand the potential impact of local sources of air toxics on personal exposures caused by temporal (weekdays versus weekend days) and seasonal (summer versus winter) variations in source intensities of the air toxics, four measurements were made of each subject, two in summer and two in winter. Within each season, one measurement was made on a weekday and the other on a weekend day. A baseline questionnaire and a time diary with an activity questionnaire were administered to each participant in order to obtain information that could be used to understand personal exposure to specific air toxics measured during each sampling period. Given the number of emission sources of air toxics in Waterfront South, a spatial variation study consisting of three saturation-sampling campaigns was conducted to characterize the spatial distribution of VOCs and aldehydes in the two neighborhoods. Passive samplers were used to collect VOC and aldehyde samples for 24- and 48-hr sampling periods simultaneously at 22 and 16 grid-based sampling sites in Waterfront South and Copewood-Davis, respectively. Results showed that measured ambient concentrations of some target pollutants (mean +/- standard deviation [SD]), such as PM2.5 (31.3 +/- 12.5 microg/m3), toluene (4.24 +/- 5.23 microg/m3), and benzo[a]pyrene (0.36 +/- 0.45 ng/m3), were significantly higher (P < 0.05) in Waterfront South than in Copewood-Davis, where the concentrations of PM2.5, toluene, and benzo[a]pyrene were 25.3 +/- 11.9 microg/m3, 2.46 +/- 3.19 microg/m3, and 0.21 +/- 0.26 ng/m3, respectively. High concentrations of specific air toxics, such as 60 microg/m3 for toluene and 159 microg/m3 for methyl tert-butyl ether (MTBE), were also found in areas close to local stationary sources in Waterfront South during the saturation-sampling campaigns. Greater spatial variation in benzene, toluene, ethylbenzene, and xylenes (known collectively as BTEX) as well as of MTBE was observed in Waterfront South than in Copewood-Davis during days with low wind speed. These observations indicated the significant impact of local emission sources of these pollutants and possibly of other pollutants emitted by individual source types on air pollution in Waterfront South. (Waterfront South is a known hot spot for these pollutants.) There were no significant differences between Waterfront South and Copewood-Davis in mean concentrations of benzene or MTBE, although some stationary sources of the two compounds have been reported in Waterfront South. Further, a good correlation (R > 0.6) was found between benzene and MTBE in both locations. These results suggest that automobile exhausts were the main contributors to benzene and MTBE air pollution in both neighborhoods. Formaldehyde and acetaldehyde concentrations were found to be high in both neighborhoods. Mean (+/- SD) concentrations of formaldehyde were 20.2 +/- 19.5 microg/m3 in Waterfront South and 24.8 +/- 20.8 microg/m3 in Copewood-Davis. A similar trend was observed for the two compounds during the saturation-sampling campaigns. The results indicate that mobile sources (i.e., diesel trucks) had a large impact on formaldehyde and acetaldehyde concentrations in both neighborhoods and that both are aldehyde hot spots. The study also showed that PM2.5, aldehydes, BTEX, and MTBE concentrations in both Waterfront South and Copewood-Davis were higher than ambient background concentrations in New Jersey and than national average concentrations, indicating that both neighborhoods are in fact hot spots for these pollutants. Higher concentrations were observed on weekdays than on weekend days for several compounds, including toluene, ethylbenzene, and xylenes (known collectively as TEX) as well as PAHs and PM2.5. These observations showed the impact on ambient air pollution of higher traffic volumes and more active industrial and commercial operations in the study areas on weekdays. Seasonal variations differed by species. Concentrations of TEX, for example, were found to be higher in winter than in summer in both locations, possibly because of higher emission rates from automobiles and reduced photochemical reactivity in winter. In contrast, concentrations of MTBE were found to be significantly higher in summer than in winter in both locations, possibly because of higher evaporation rates from gasoline in summer. Similarly, concentrations of heavier PAHs, such as benzo[a]pyrene, were found to be higher in winter in both locations, possibly because of higher emission rates from mobile sources, the use of home heating, and the reduced photochemical reactivity of benzo[a]pyrene in winter. In contrast, concentrations of lighter PAHs were found to be higher in summer in both locations, possibly because of volatilization of these compounds from various surfaces in summer. In addition, higher concentrations of formaldehyde were observed in summer than in winter, possibly because of significant contributions from photochemical reactions to formaldehyde air pollution in summer. Personal concentrations of toluene (25.4 +/- 13.5 microg/m3) and acrolein (1.78 +/- 3.7 microg/m3) in Waterfront South were found to be higher than those in the Copewood-Davis neighborhood (13.1 +/- 15.3 microg/m3 for toluene and 1.27 +/- 2.36 microg/m3 for acrolein). However, personal concentrations for most of the other compounds measured in Waterfront South were found to be similar to or lower than those than in Copewood-Davis. (For example, mean +/- SD concentrations were 4.58 +/- 17.3 microg/m3 for benzene, 4.06 +/- 5.32 microg/m3 for MTBE, 16.8 +/- 15.5 microg/m3 for formaldehyde, and 0.40 +/- 0.94 ng/m3 for benzo[a]pyrene in Waterfront South and 9.19 +/- 34.0 microg/m3 for benzene, 6.22 +/- 19.0 microg/m3 for MTBE, 16.0 +/- 16.7 microg/m3 for formaldehyde, and 0.42 +/- 1.08 ng/m3 for benzo[a]pyrene in Copewood-Davis.) This was probably because many of the target compounds had both outdoor and indoor sources. The higher personal concentrations of these compounds in Copewood-Davis might have resulted in part from higher exposure to environmental tobacco smoke (ETS) of subjects from Copewood-Davis. The Spearman correlation coefficient (R) was found to be high for pollutants with significant outdoor sources. The R's for MTBE and carbon tetrachloride, for example, were > 0.65 in both Waterfront South and Copewood-Davis. The R's were moderate or low (0.3-0.6) for compounds with both outdoor and indoor sources, such as BTEX and formaldehyde. A weaker association (R < 0.5) was found for compounds with significant indoor sources, such as BTEX, formaldehyde, PAHs, and PM2.5. The correlations between personal and ambient concentrations of MTBE and BTEX were found to be stronger in Waterfront South than in Copewood-Davis, reflecting the significant impact of local air pollution sources on personal exposure to these pollutants in Waterfront South. Emission-based ambient concentrations of benzene, toluene, and formaldehyde and contributions of ambient exposure to personal concentrations of these three compounds were modeled using atmospheric dispersion modeling and Individual Based Exposure Modeling (IBEM) software, respectively, which were coupled for analysis in the Modeling Environment for Total Risk (MENTOR) system. The compounds were associated with the three types of dominant sources in the two neighborhoods: industrial sources (toluene), exhaust from gasoline-powered motor vehicles (benzene), and exhaust from diesel-powered motor vehicles (formaldehyde). Subsequently, both the calculated and measured ambient concentrations of each of the three compounds were separately combined with the time diaries and activity questionnaires completed by the subjects as inputs to IBEM-MENTOR for estimating personal exposures from ambient sources. Modeled ambient concentrations of benzene and toluene were generally in agreement with the measured ambient concentrations within a factor of two, but the values were underestimated at the high-end percentiles. The major local (neighborhood) contributors to ambient benzene concentrations were from mobile sources in the study areas; both mobile and stationary (point and area) sources contributed to the ambient toluene concentrations. This finding can be used as guidance for developing better emission inventories to characterize, through modeling, the ambient concentrations of air toxics in the study areas. (ABSTRACT TRUNCATED)
Air toxics exposure from vehicle emissions at a U.S. border crossing: Buffalo Peace Bridge Study.
Spengler J, Lwebuga-Mukasa J, Vallarino J … +4 more , Melly S, Chillrud S, Baker J, Minegishi T
Res Rep Health Eff Inst · 2011 Jul · PMID 21913504
The Peace Bridge in Buffalo, New York, which spans the Niagara River at the east end of Lake Erie, is one of the busiest U.S. border crossings. The Peace Bridge plaza on the U.S. side is a complex of roads, customs inspe...
The Peace Bridge in Buffalo, New York, which spans the Niagara River at the east end of Lake Erie, is one of the busiest U.S. border crossings. The Peace Bridge plaza on the U.S. side is a complex of roads, customs inspection areas, passport control areas, and duty-free shops. On average 5000 heavy-duty diesel trucks and 20,000 passenger cars traverse the border daily, making the plaza area a potential "hot spot" for emissions from mobile sources. In a series of winter and summer field campaigns, we measured air pollutants, including many compounds considered by the U.S. Environmental Protection Agency (EPA*) as mobile-source air toxics (MSATs), at three fixed sampling sites: on the shore of Lake Erie, approximately 500 m upwind (under predominant wind conditions) of the Peace Bridge plaza; immediately downwind of (adjacent to) the plaza; and 500 m farther downwind, into the community of west Buffalo. Pollutants sampled were particulate matter (PM) < or = 10 microm (PM10) and < or = 2.5 microm (PM2.5) in aerodynamic diameter, elemental carbon (EC), 28 elements, 25 volatile organic compounds (VOCs) including 3 carbonyls, 52 polycyclic aromatic hydrocarbons (PAHs), and 29 nitrogenated polycyclic aromatic hydrocarbons (NPAHs). Spatial patterns of counts of ultrafine particles (UFPs, particles < 0.1 microm in aerodynamic diameter) and of particle-bound PAH (pPAH) concentrations were assessed by mobile monitoring in the neighborhood adjacent to the Peace Bridge plaza using portable instruments and Global Positioning System (GPS) tracking. The study was designed to assess differences in upwind and downwind concentrations of MSATs, in areas near the Peace Bridge plaza on the U.S. side of the border. The Buffalo Peace Bridge Study featured good access to monitoring locations proximate to the plaza and in the community, which are downwind with the dominant winds from the direction of Lake Erie and southern Ontario. Samples from the lakeside Great Lakes Center (GLC), which is upwind of the plaza with dominant winds, were used to characterize contaminants in regional air masses. On-site meteorologic measurements and hourly truck and car counts were used to assess the role of traffic on UFP counts and pPAH concentrations. The array of parallel and perpendicular residential streets adjacent to the plaza provided a grid on which to plot the spatial patterns of UFP counts and pPAH concentrations to determine the extent to which traffic emissions from the Peace Bridge plaza might extend into the neighboring community. For lake-wind conditions (southwest to northwest) 12-hour integrated daytime samples showed clear evidence that vehicle-related emissions at the Peace Bridge plaza were responsible for elevated downwind concentrations of PM2.5, EC, and benzene, toluene, ethylbenzene, and xylenes (BTEX), as well as 1,3-butadiene and styrene. The chlorinated VOCs and aldehydes were not differentially higher at the downwind site. Several metals (aluminum, calcium, iron, copper, and antimony) were two times higher at the site adjacent to the plaza as they were at the upwind GLC site on lake-wind sampling days. Other metals (beryllium, sodium, magnesium, potassium, titanium, manganese, cobalt, strontium, tin, cesium, and lanthanum) showed significant increases downwind as well. Sulfur, arsenic, selenium, and a few other elements appeared to be markers for regional transport as their upwind and downwind concentrations were correlated, with ratios near unity. Using positive matrix factorization (PMF), we identified the sources for PAHs at the three fixed sampling sites as regional, diesel, general vehicle, and asphalt volatilization. Diesel exhaust at the Peace Bridge plaza accounted for approximately 30% of the PAHs. The NPAH sources were identified as nitrate (NO3) radical reactions, diesel, and mixed sources. Diesel exhaust at the Peace Bridge plaza accounted for 18% of the NPAHs. Further evidence for the impact of the Peace Bridge plaza on local air quality was found when the differences in 10-minute average UFP counts and pPAH concentrations were calculated between pairs of sites and displayed by wind direction. With winds from approximately 160 degrees through 220 degrees, UFP counts adjacent to the plaza were 10,000 to 20,000 particles/cm3 higher than those upwind of the plaza. A similar pattern was displayed for pPAH concentrations adjacent to the plaza, which were between 10 and 20 ng/m3 higher than those at the upwind GLC site. Regression models showed better correlation with traffic variables for pPAHs than for UFPs. For pPAHs, truck counts and car counts had significant positive correlations, with similar magnitudes for the effects of trucks and cars, despite lower truck counts. Examining all traffic variables, including traffic counts and counts divided by wind speed, the multivariate regression analysis had an adjusted coefficient of determination (R2) of 0.34 for pPAHs, with all terms significant at P < 0.002. Study staff members traversed established routes in the neighborhood while carrying instruments to record continuous UFP and pPAH values. They also carried a GPS, which was used to provide location-specific time-stamped data. Analyses using a geographic information system (GIS) demonstrated that emissions at the Peace Bridge plaza, at times, affected ambient air quality over several blocks (a few hundred meters). Under lake-wind conditions, overall spatial patterns in UFP and pPAH levels were similar for summer and winter and for morning and afternoon sampling sessions. The Buffalo Peace Bridge Study demonstrated that a concentration of motor vehicles resulted in elevated levels of mobile-source-related emissions downwind, to distances of 300 m to 600 m. The study provides a unique data set to assess interrelationships among MSATs and to ascertain the impact of heavy-duty diesel vehicles on air quality.
Role of neprilysin in airway inflammation induced by diesel exhaust emissions.
Wong SS, Sun NN, Fastje CD … +7 more , Witten ML, Lantz RC, Lu B, Sherrill DL, Gerard CJ, Burgess JL, HEI Health Review Committee
Res Rep Health Eff Inst · 2011 Jun · PMID 21877416
In this study, we examined the role of neprilysin (NEP), a key membrane-bound endopeptidase, in the inflammatory response induced by diesel exhaust emissions (DEE) in the airways through a number of approaches: in vitro,...
In this study, we examined the role of neprilysin (NEP), a key membrane-bound endopeptidase, in the inflammatory response induced by diesel exhaust emissions (DEE) in the airways through a number of approaches: in vitro, animal, and controlled human exposure. Our specific aims were (1) to examine the role of NEP in inflammatory injury induced by diesel exhaust particles (DEP) using Nep-intact (wild-type) and Nep-null mice; (2) to examine which components of DEP are associated with NEP downregulation in vitro; (3) to determine the molecular impact of DEP exposure and decreased NEP expression on airway epithelial cells' gene expression in vitro, using a combination of RNA interference (RNAi) and microarray approaches; and (4) to evaluate the effects on NEP activity of human exposure to DEE. We report four main results: First, we found that exposure of normal mice to DEP consisting of standard reference material (SRM) 2975 via intratracheal installation can downregulate NEP expression in a concentration-dependent manner. The changes were accompanied by increases in the number of macrophages and epithelial cells, as well as proinflammatory cytokines, examined in bronchoalveolar lavage (BAL) fluid and cells. Nep-null mice displayed increased and/or additional inflammatory responses when compared with wild-type mice, especially in response to exposure to the higher dose of DEP that we used. These in vivo findings suggest that loss of NEP in mice could cause increased susceptibility to injury or exacerbate inflammatory responses after DEP exposure via release of specific cytokines from the lungs. Second, we found evidence, using in vitro studies, that downregulation of NEP by DEP in cultured human epithelial BEAS-2B cells was mostly attributable to DEP-adsorbed organic compounds, whereas the carbonaceous core and transition metal components of DEP had little or no effect on NEP messenger RNA (mRNA) expression. This NEP downregulation was not a specific response to DEP or its contents because the change also occurred after exposure to urban dust (SRM 1649a), which differs in physical and chemical composition from DEP. Third, we also collected the transcriptome profiles of the concentration-effects of SRM 2975 in cultured BEAS-2B cells through a 2 X 3 factorial design. DEP exposure upregulated 151 genes and downregulated 59 genes. Cells with decreased NEP expression (accomplished by transfecting an NEP-specific small interfering RNA [siRNA]) substantially altered the expression of genes (upregulating 17 and downregulating 14) associated with DNA/protein binding, calcium channel activities, and the cascade of intracellular signaling by cytokines. Data generated from the combined RNAi and microarray approaches revealed that there is a complex molecular cascade mediated by NEP in different subcellular compartments, possibly influencing the inflammatory response. Fourth, in a controlled human exposure study, we observed significant increases in soluble NEP in sputum after acute exposure to DEE, with an average net increase of 31%. We speculate that the change in NEP activity in sputum, if confirmed in larger epidemiologic investigations at ambient exposure levels to DEE, may provide a useful endpoint and promote insight into the mechanism of DEE-induced airway alterations.
The impact of the congestion charging scheme on air quality in London. Part 2. Analysis of the oxidative potential of particulate matter.
Kelly F, Anderson HR, Armstrong B … +8 more , Atkinson R, Barratt B, Beevers S, Derwent D, Green D, Mudway I, Wilkinson P, HEI Health Review Committee
Res Rep Health Eff Inst · 2011 Apr · PMID 21830497
There is growing scientific consensus that the ability of inhaled particulate matter (PM*) to elicit oxidative stress both at the air-lung interface and systemically might underpin many of the acute and chronic respirato...
There is growing scientific consensus that the ability of inhaled particulate matter (PM*) to elicit oxidative stress both at the air-lung interface and systemically might underpin many of the acute and chronic respiratory and cardiovascular responses observed in exposed populations. In the current study (which is part two of a two-part HEI study of a congestion charging scheme [CCS] introduced in London, United Kingdom, in 2003), we tested the hypothesis that the reduction in vehicle numbers and changes in traffic composition resulting from the introduction of the CCS would result in decreased concentrations of traffic-specific emissions, both from vehicle exhaust and other sources (brake wear and tire wear), and an associated reduction in the oxidative potential of PM with an aerodynamic diameter < or = 10 microm (PM10). To test this hypothesis, we obtained, extracted, and analyzed tapered element oscillating microbalance (TEOM) PM10 filters from six monitoring sites within, bordering, or outside the area of the congestion charging zone (CCZ) for the 3 years before and after the introduction of the scheme. In addition, from January 2005, TEOM PM10 filters were obtained from an additional 10 sites outside the zone in order to perform the first-ever assessment of within-city spatial variability in the oxidative potential of PM10. Although London's PM10 was found to have remarkably high oxidative potential, it varied markedly between the studied sites, with evidence of increased potential at roadside locations compared with urban background locations. This difference appeared to reflect increased concentrations of copper (Cu), barium (Ba), and bioavailable iron (Fe) in PM10 collected at the roadside sites. PM10's oxidative potential after the introduction of the CCS did not change at the one urban background site within the zone. Yet compositional changes in PM10 were noted at the same site, including significant decreases in Cu and zinc (Zn) content, probably reflecting brake and tire wear (compared with increases in these metals at all sites outside the zone in the 3 years since the scheme's introduction). This pattern of results is consistent with observations of increased vehicle use throughout London in recent years and decreases in the number of vehicles entering the zone since the scheme's introduction.
The impact of the congestion charging scheme on air quality in London. Part 1. Emissions modeling and analysis of air pollution measurements.
Kelly F, Anderson HR, Armstrong B … +8 more , Atkinson R, Barratt B, Beevers S, Derwent D, Green D, Mudway I, Wilkinson P, HEI Health Review Committee
Res Rep Health Eff Inst · 2011 Apr · PMID 21830496
On February 17, 2003, a congestion charging scheme (CCS*) was introduced in central London along with a program of traffic management measures. The scheme operated Monday through Friday, 7 AM to 6 PM. This program result...
On February 17, 2003, a congestion charging scheme (CCS*) was introduced in central London along with a program of traffic management measures. The scheme operated Monday through Friday, 7 AM to 6 PM. This program resulted in an 18% reduction in traffic volume and a 30% reduction in traffic congestion in the first year (2003). We developed methods to evaluate the possible effects of the scheme on air quality: We used a temporal-spatial design in which modeled and measured air quality data from roadside and background monitoring stations were used to compare time periods before (2001-2002) and after (2003-2004) the CCS was introduced and to compare the spatial area of the congestion charging zone (CCZ) with the rest of London. In the first part of this project, we modeled changes in concentrations of oxides of nitrogen (NOx), nitrogen dioxide (NO2), and PM10 (particles with a mass median aerodynamic diameter < or = 10 microm) across the CCZ and in Greater London under different traffic and emission scenarios for the periods before and after CCS introduction. Comparing model results within and outside the zone suggested that introducing the CCS would be associated with a net 0.8-microg/m3 decrease in the mean concentration of PM10 and a net 1.7-ppb decrease in the mean concentration of NOx within the CCZ. In contrast, a net 0.3-ppb increase in the mean concentration of NO2 was predicted within the zone; this was partly explained by an expected increase in primary NO2 emissions due to the introduction of particle traps on diesel buses (one part of the improvements in public transport associated with the CCS). In the second part of the project, we established a CCS Study Database from measurements obtained from the London Air Quality Network (LAQN) for air pollution monitors sited to measure roadside and urban background concentrations. Fully ratified (validated) 15-minute mean carbon monoxide (CO), nitric oxide (NO), NO2, NOx, PM10, and PM2.5 data from each chosen monitoring site for the period from February 17, 2001, to February 16, 2005, were transferred from the LAQN database. In the third part of our project, these data were used to compare geometric means for the 2 years before and the 2 years after the CCS was introduced. Temporal changes within the CCZ were compared with changes, over the same period, at similarly sited (roadside or background) monitors in a control area 8 km distant from the center of the CCZ. The analysis was confined to measurements obtained during the hours and days on which the scheme was in operation and focused on pollutants derived from vehicles (NO, NO2, NOx, PM10, and CO). This set of analyses was based on the limited data available from within the CCZ. When compared with data from outside the zone, we did not find evidence of temporal changes in roadside measurements of NOx, NO, and NO2, nor in urban background concentrations of NOx. (The latter result, however, concealed divergent trends in NO, which fell, and NO2, which rose.) Although based upon fewer stations, there was evidence that background concentrations of PM10 and CO fell within the CCZ compared with outside the zone. We also analyzed the trends in background concentrations for all London monitoring stations; as distance from the center of the CCZ increased, we found some evidence of an increasing gradation in NO and PM10 concentrations before versus after the intervention. This suggests a possible intermediate effect on air quality in the area immediately surrounding the CCZ. Although London is relatively well served with air quality monitoring stations, our study was restricted by the availability of only a few monitoring sites within the CCZ, and only one of those was at a roadside location. The results derived from this single roadside site are not likely to be an adequate basis for evaluating this complex urban traffic management scheme. Our primary approach to assessing the impact of the CCS was to analyze the changes in geometric mean pollutant concentrations in the 2 years before and 2 years after the CCS was introduced and to compare changes at monitoring stations within the CCZ with those in a distant control area (8 km from the CCZ center) unlikely to be influenced by the CCS. We saw this as the most robust analytical approach with which to examine the CCS Study Database, but in the fourth part of the project we did consider three other approaches: ethane as an indicator of pollution dispersion; the cumulative sum (CUSUM) statistical technique; and bivariate polar plots for local emissions. All three were subsequently judged as requiring further development outside of the scope of this study. However, despite their investigative nature, each technique provided useful information supporting the main analyses. The first method used ethane as a dispersion indicator to remove the inherent variability in air pollutant concentrations caused by changes in meteorology and atmospheric dispersion. The technique had the potential to ascertain more accurately the likely impacts of the CCS on London's air quality. Although this novel method appeared promising over short time periods, a number of concerns arose about whether the spatial and temporal variability of ethane over longer time periods would be representative of meteorologic conditions alone. The major strength of CUSUM, the second method, is that it can be used to identify the approximate timing of changes that may have been caused by the CCS. This ability is weakened, however, by the effects of serial correlation (the correlation of data among measurements in successive time intervals) within air pollution data that is caused by seasonality and long-term meteorologic trends. The secure interpretation of CUSUM requires that the technique be adapted to take proper account of the underlying correlation between measurements without the use of smoothing functions that would obscure a stepped change in concentrations. Although CUSUM was not able to provide a quantitative estimation of changes in pollution levels arising from the introduction of the CCS, the strong signals that were identified were considered in the context of other results from the study. The third method, bivariate polar plots, proved useful. The plots revealed important characteristics of the data from the only roadside monitoring site within the CCZ and highlighted the importance of considering prevailing weather conditions when positioning a roadside monitor. The technique would benefit from further development, however, in transforming the qualitative assessment of change into a quantitative assessment and including an estimate of uncertainty. Research is ongoing to develop this method in air-quality time-series studies. Overall, using a range of measurement and modeling approaches, we found evidence of small changes in air quality after introduction of the CCS. These include small decreases in PM10, NO, and CO. The possibility that some of these effects might reflect more general changes in London's air quality is suggested by the findings of somewhat similar changes in geometric means for weekends, when the CCS was not operating. However, since some evidence suggests that the CCS also had an impact on traffic volume on weekends, the CCS remains as one possible explanation for the observed pattern of changes in pollutant concentrations. In addition, the CCS was just one of a number of traffic and emission reduction schemes introduced in London over the 4-year study period; if the other measures had an impact in central London, they might partly explain our findings. Although not the aim of this study, it is important to consider how the trends we observed might be translated into health effects. For example, given that London already has NO2 concentrations in excess of the permitted limit value, we do not know what the effects of an increase in NO2 created by diesel-exhaust after-treatment for particles might mean for health. Further, although it is not likely that NO affects health, the decrease in NO concentrations is likely associated with an increase in ozone concentrations (a pollutant associated with health effects), as has been seen in recent years in London. These and other similar issues require further investigation. Although the CCS is a relatively simple traffic management scheme in the middle of a major urban environment, analyzing its possible impact on air quality was found to be far from straightforward. Using a range of modeling and monitoring approaches to address the impact of the scheme revealed that each technique has its own advantages and limitations. The placement of monitoring sites and the availably of traffic count data were also identified as key issues. The most compelling lesson we take away from this study is that such work is impossible to undertake without a coherent multi-disciplinary team of skilled researchers. In conclusion, our study suggests that the introduction of the CCS in 2003 was associated with small temporal changes in air pollutant concentrations in central London compared with outer areas. However, attributing the cause of these changes to the CCS alone is not appropriate because the scheme was introduced at a time when other traffic and emissions interventions, which might have had a more concentrated effect in central London, were also being implemented.
Part 2. Time-series study on air pollution and mortality in Delhi.
Rajarathnam U, Sehgal M, Nairy S … +5 more , Patnayak RC, Chhabra SK, Kilnani, Ragavan KV, HEI Health Review Committee
Res Rep Health Eff Inst · 2011 Mar · PMID 21648204
INTRODUCTION: Air pollution concentrations in most of the megacities in India exceed the air quality guidelines recommended by the World Health Organization and may adversely affect human health in these cities. Particul...
INTRODUCTION: Air pollution concentrations in most of the megacities in India exceed the air quality guidelines recommended by the World Health Organization and may adversely affect human health in these cities. Particulate matter (PM) is the pollutant of concern in many Indian cities, particularly in the capital city of Delhi, In recent years, several actions have been taken to address the growing air pollution problem in Delhi and other Indian cities; however, few studies have been designed to assess the health effects of air pollution in Indian cities. To bridge the gap in scientific knowledge and add evidence to the ongoing studies in other Asian cities, a retrospective time-series study on air pollution and mortality in Delhi was initiated under the HEI Public Health and Air Pollution in Asia (PAPA) program. APPROACH: The study used retrospective time-series data of air quality and of naturally-occurring deaths recorded in Delhi to identify changes in the daily all-natural-cause mortality rate that could be attributed to changes in air quality. The 3-year study period included the years 2002 through 2004. The methodology involved: (1) collecting data on ambient air quality for major pollutants from all monitoring stations in Delhi; (2) collecting meteorologic data (temperature, humidity, and visibility); (3) collecting daily mortality records from the Registrar of Births and Deaths; (4) statistically analyzing the data using the common protocol for Indian PAPA studies, which included city-specific modifications. RESULTS AND IMPLICATIONS: The study findings showed that increased concentrations of PM with an aerodynamic diameter < or = 10 microg/m3 (PM10) and of nitrogen dioxide (NO2) were associated with increased all-natural-cause mortality. It was found that every 10-microg/m3 change in PM10 was associated with only a 0.15% increase in total all-natural-cause mortality. When NO2 alone was considered in the model, daily all-natural-cause mortality increased 0.84% for every 10-microg/m3 increase in NO2 concentration. No significant effect was observed for changes in sulfur dioxide (SO2) concentrations. The study provides insight into the link between air pollution and mortality in local populations and contributes information to the existing body of knowledge.
Part 1. Short-term effects of air pollution on mortality: results from a time-series analysis in Chennai, India.
Balakrishnan K, Ganguli B, Ghosh S … +5 more , Sankar S, Thanasekaraan V, Rayudu VN, Caussy H, HEI Health Review Committee
Res Rep Health Eff Inst · 2011 Mar · PMID 21648203
This report describes the results of a time-series analysis of the effect of short-term exposure to particulate matter with an aerodynamic diameter < or = 10 pm (PM10) on mortality in metropolitan Chennai, India (formerl...
This report describes the results of a time-series analysis of the effect of short-term exposure to particulate matter with an aerodynamic diameter < or = 10 pm (PM10) on mortality in metropolitan Chennai, India (formerly Madras). This was one of three sites in India chosen by HEI as part of its Public Health and Air Pollution in Asia (PAPA) initiative. The study involved integration and analysis of retrospective data for the years 2002 through 2004. The data were obtained from relevant government agencies in charge of routine data collection. Data on meteorologic confounders (including temperature, relative humidity, and dew point) were available on all days of the study period. Data on mortality were also available on all days, but information on cause-of-death (including accidental deaths) could not be reliably ascertained. Hence, only all-cause daily mortality was used as the major outcome for the time-series analyses. Data on PM10, nitrogen dioxide (NO2), and sulfur dioxide (SO2) were limited to a much smaller number of days, but spanned the full study period. Data limitations resulting from low sensitivity of gaseous pollutant measurements led to using only PM10 in the main analysis. Of the eight operational ambient air quality monitor (AQM) stations in the city, seven met the selection criteria set forth in the common protocol developed for the three PAPA studies in India. In addition, all raw data used in the analysis were subjected to additional quality assurance (QA) and quality control (QC) criteria to ensure the validity of the measurements. Two salient features of the PM10 data set in Chennai were a high percentage of missing readings and a low correlation among daily data recorded by the AQMs. The latter resulted partly because each AQM had a small footprint (approximate area over which the air pollutant measurements recorded in the AQM are considered valid), and partly because of differences in source profiles among the 10 zones within the city. The zones were defined by the Chennai Corporation based on population density. Alternative exposure series were developed to control for these data features. We first developed exposure series based on data from single AQMs and multiple AQMs. Because neither was found to satisfactorily represent population exposures, we subsequently developed an exposure series that disaggregated pollutant data to individual zones within the city boundary. The zonal series, despite some uncertainties, was found to best represent population exposures among other available choices. The core model was thus a zonal model developed using disaggregated mortality and pollutant data from individual zones. We used quasi-Poisson generalized additive models (GAMs) with smooth functions of time, temperature, and relative humidity modeled using penalized splines. The degrees of freedom (df) for these confounders were selected to maximize the precision with which the relative risk for PM10 was estimated. This is a deviation from the traditional approaches to degrees of freedom selection, which usually aim to optimize overall model fit. Our approach led to the use of 8 df/year for time, 6 df/year for temperature, and 5 df/year for relative humidity. The core model estimated a 0.44% (95% confidence interval [CI] = 0.17 to 0.71) increase in daily all-cause mortality per 10-pg/m3 increase in daily average PM10 concentrations. Extensive sensitivity analyses compared models constructed using alternative exposure series and contributions of model parameters to the core model with regard to confounder degrees of freedom, alternative lags for exposure and meteorologic confounders, inclusion of outliers, seasonality, inclusion of multiple pollutants, and stratification by sex and age. The sensitivity analyses showed that our estimates were robust to a range of specifications and were also comparable to estimates reported in previous time-series studies: PAPA, the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), Air Pollution and Health: A European Approach (APHEA), and Air Pollution and Health: A European and North American Approach (APHENA). While the approaches developed in previous studies served as the basis for our model development, the present study has new refinements that have allowed us to address specific data limitations (such as missing measurements and small footprints of air pollution monitors). The methods developed in the study may allow better use of routine data for time-series analysis in a broad range of settings where similar exposure and data-related issues prevail. We hope that the estimates derived in this study, although somewhat tentative, will facilitate local environmental management initiatives and spur future studies.
Concentrations of air toxics in motor vehicle-dominated environments.
Fujita EM, Campbell DE, Zielinska B … +2 more , Arnott WP, Chow JC
Res Rep Health Eff Inst · 2011 Feb · PMID 21608416
We at the Desert Research Institute (DRI*) measured volatile organic compounds (VOCs), including several mobile-source air toxics (MSATs), particulate matter with a mass mean aerodynamic diameter < or = 2.5 pm (PM2.5), b...
We at the Desert Research Institute (DRI*) measured volatile organic compounds (VOCs), including several mobile-source air toxics (MSATs), particulate matter with a mass mean aerodynamic diameter < or = 2.5 pm (PM2.5), black carbon (BC), nitrogen oxides (NOx), particulate matter (PM), and carbon monoxide (CO) on highways in Los Angeles County during summer and fall 2004, to characterize the diurnal and seasonal variations in measured concentrations related to volume and mix of traffic. Concentrations of on-road pollutants were then compared to corresponding measurements at fixed monitoring sites. The on-road concentrations of CO and MSATs were higher in the morning under stable atmospheric conditions and during periods of higher traffic volumes. In contrast, BC concentrations, measured as particulate light absorption, were higher on truck routes during the midday sampling periods despite more unstable atmospheric conditions. Compared to the measurements at the three near-road sites, the 1-hour averages of on-road BC concentrations were as much as an order of magnitude higher. The peak 1-minute average concentrations were two orders of magnitude higher for BC and were between two and six times higher for PM2.5 mass. The on-road concentrations of benzene, toluene, ethylbenzene, and xylenes (BTEX) during the summer were 3.5 +/- 0.7 and 1.2 +/- 0.6 times higher during morning and afternoon commuting periods, respectively, compared to annual average 24-hour concentrations measured at air toxic monitoring network sites. These ratios were higher during the fall, with smaller diurnal differences (4.8 +/- 0.7 and 3.9 +/- 0.6 for morning and afternoon commuting periods, respectively). Ratios similar to those for BTEX were obtained for 1,3-butadiene (BD) and styrene. On-road concentrations of formaldehyde and acetaldehyde were up to two times higher than at air toxics monitoring sites, with fall ratios slightly higher than summer ratios. Chemical mass balance (CMB) receptor model calculations attributed the sum of BTEX almost exclusively to gasoline engine exhaust for on-road samples and all but 5% to 10% of the BTEX at the three near-road sites. CMB analysis attributed 46% to 52% (+/- 7) of the ambient total particulate carbon (TC) at the three near-road sites to diesel exhaust and 10% to 17% (+/- 7) to gasoline exhaust; it attributed about 90% of the ambient elemental carbon (EC) concentrations (measured as refractory carbon using the thermal evolution method) to diesel exhaust. Diesel particulate carbon (DPC) concentrations were estimated by multiplying the mean ratio of TC to EC from the source-dominated ambient samples collected on road on Terminal Island (1.30 +/- 0.28), which is located between the Long Beach and Los Angeles ports, with the measured ambient EC concentrations at the three near-road sites. DPC estimates from EC measurements correlate well with the diesel source contributions calculated with the CMB model. The indication from these apportionments that BC or EC is a good surrogate for diesel exhaust is further supported by the positive correlation of on-road BC concentrations with volumes of truck traffic. Traffic counts have been used in past health assessment studies as surrogates for estimating near-road exposure concentrations with appropriate weighting for proximity to the road. However, the results of this study show that it is necessary to account for the proportion of diesel trucks to total vehicular traffic because of the disproportionate contribution of diesel exhaust to BC and to directly emitted PM. Alternatively, easily measured pollutants such as CO and BC can serve as reasonable surrogates for MSATs (e.g., BTEX and BD) and DPC, respectively. Measuring CO and BC is a reasonably cost-effective approach to quantifying hot-spot exposure concentrations of MSATs that is perhaps more accurate than what is possible using only data from regional air quality monitoring stations or air quality modeling results.
Part 5. Public health and air pollution in Asia (PAPA): a combined analysis of four studies of air pollution and mortality.
Wong CM, Vichit-Vadakan N, Vajanapoom N … +39 more , Ostro B, Thach TQ, Chau PY, Chan EK, Chung RY, Ou CQ, Yang L, Peiris JS, Thomas GN, Lam TH, Wong TW, Hedley AJ, Kan H, Chen B, Zhao N, London SJ, Song G, Chen G, Zhang Y, Jiang L, Qian Z, He Q, Lin HM, Kong L, Zhou D, Liang S, Zhu Z, Liao D, Liu W, Bentley CM, Dan J, Wang B, Yang N, Xu S, Gong J, Wei H, Sun H, Qin Z, HEI Health Review Committee
Res Rep Health Eff Inst · 2010 Nov · PMID 21446215
BACKGROUND: In recent years, Asia has experienced rapid economic growth and a deteriorating environment caused by the increasing use of fossil fuels. Although the deleterious effects of air pollution from fossil-fuel com...
BACKGROUND: In recent years, Asia has experienced rapid economic growth and a deteriorating environment caused by the increasing use of fossil fuels. Although the deleterious effects of air pollution from fossil-fuel combustion have been demonstrated in many Western nations, few comparable studies have been conducted in Asia. Time-series studies of daily mortality in Asian cities can contribute important new information to the existing body of knowledge about air pollution and health. Not only can these studies verify important health effects of air pollution in local regions in Asia, they can also help determine the relevance of existing air pollution studies to mortality and morbidity for policymaking and environmental controls. In addition, the studies can help identify factors that might modify associations between air pollution and health effects in various populations and environmental conditions. Collaborative multicity studies in Asia-especially when designed, conducted, and analyzed using a common protocol-will provide more robust air pollution effect estimates for the region as well as relevant, supportable estimates of local adverse health effects needed by environmental and public-health policymakers. SPECIFIC OBJECTIVES: The Public Health and Air Pollution in Asia (PAPA*) project, sponsored by the Health Effects Institute, consisted of four studies designed to assess the effects of air pollution on mortality in four large Asian cities, namely Bangkok, in Thailand, and Hong Kong, Shanghai, and Wuhan, in China. In the PAPA project, a Common Protocol was developed based on methods developed and tested in NMMAPS, APHEA, and time-series studies in the literature to help ensure that the four studies could be compared with each other and with previous studies by following an established protocol. The Common Protocol (found at the end of this volume) is a set of prescriptive instructions developed for the studies and used by the investigators in each city. It is flexible enough to allow for adjustments in methods to optimize the fit of health-effects models to each city's data set. It provides the basis for generating reproducible results in each city and for meta-estimates from combined data. By establishing a common methodology, factors that might influence the differences in results from previous studies can more easily be explored. Administrative support was provided to ensure that the highest quality data were used in the analysis. It is anticipated that the PAPA results will contribute to the international scientific discussion of how to conduct and interpret time-series studies of air pollution and will stimulate the development of high-quality routine systems for recording daily deaths and hospital admissions for time-series analysis. METHODS: Mortality data were retrieved from routine databases with underlying causes of death coded using the World Health Organization (WHO) International Classification of Diseases, 9th revision or 10th revision (ICD-9, ICD-10). Air quality measurements included nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter with aerodynamic diameter < or = 10 microm (PM10), and ozone (O3) and were obtained from several fixed-site air monitoring stations that were located throughout the metropolitan areas of the four cities and that met the standards of procedures for quality assurance and quality control carried out by local government units in each city. Using the Common Protocol, an optimized core model was established for each city to assess the effects of each of the four air pollutants on daily mortality using generalized linear modeling with adjustments for time trend, seasonality, and other time-varying covariates by means of a natural-spline smoothing function. The models were adjusted to suit local situations by correcting for influenza activity, autocorrelation, and special weather conditions. Researchers in Hong Kong, for example, used influenza activity based on frequency of respiratory mortality; researchers in Hong Kong and Shanghai used autoregressive terms for daily outcomes at lag days; and researchers in Wuhan used additional smoothing for periods with extreme weather conditions. RESULTS AND DISCUSSION: For mortality due to all natural (nonaccidental) causes at all ages, the effects of air pollutants per 10-microg/m3 increase in concentration was found to be higher in Bangkok than in the three Chinese cities, with the exception of the effect of NO2 in Wuhan. The magnitude of the effects for cardiovascular and respiratory mortality were generally higher than for all natural mortality at all ages. In addition, the effects associated with PM10 and O3 in all natural, cardiovascular; and respiratory mortality were found to be higher in Bangkok than in the three Chinese cities. The explanation for these three findings might be related to consistently higher daily mean temperatures in Bangkok, variations in average time spent outdoors by the susceptible populations, and the fact that less air conditioning is available and used in Bangkok than in the other cities. However, when pollutant concentrations were incorporated into the excess risk estimates through the use of interquartile range (IQR), the excess risk was more comparable across the four cities. We found that the increases in effects among older age groups were greater in Bangkok than in the other three cities. After excluding data on extremely high concentrations of PM10 in Bangkok, the effect estimate associated with PM10 concentrations decreased in Bangkok (suggesting a convex relationship between risk and PM10, where risk levels off at high concentrations) instead of increasing, as it did in the other cities. This leveling off of effect estimates at high concentrations might be related to differences in vulnerability and exposure of the population to air pollution as well as to the sources of the air pollutant. IMPLICATIONS OF THE STUDY: The PAPA project is the first coordinated Asian multicity air pollution study ever published; this signifies the beginning of an era of cooperation and collaboration in Asia, with the development of a common protocol for coordination, data management, and analysis. The results of the study demonstrated that air pollution in Asia is a significant public health burden, especially given the high concentrations of pollutants and high-density populations in major cities. When compared with the effect estimates reported in the research literature of North America and Western Europe, the study's effect estimates for PM10 were generally similar and the effect estimates for gaseous pollutants were relatively higher. In Bangkok, however, a tropical city where total exposures to outdoor pollution might be higher than in most other cities, the observed effects were greater than those reported in the previous (i.e., Western) studies. In general, the results suggested that, even though social and environmental conditions across Asia might vary, it is still generally appropriate to apply to Asia the effect estimates for other health outcomes from previous studies in the West. The results also strongly support the adoption of the global air quality guidelines recently announced by WHO.
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