Mitchel Klein

Effects of anthropogenic emissions on aerosol formation from isoprene and monoterpenes in the southeastern United States

Significance Atmospheric secondary organic aerosol has substantial impacts on climate, air quality, and human health. However, the formation mechanisms of secondary organic aerosol remain uncertain, especially on how anthropogenic pollutants (from human activities) control aerosol formation from biogenic volatile organic compounds (emitted by vegetation) and the magnitude of anthropogenic influences. Although possible mechanisms have been proposed based on laboratories studies, a coherent understanding of anthropogenic−biogenic interactions in ambient environments has not emerged. Here, we provide direct observational evidence that secondary organic aerosol formed from biogenic isoprene and monoterpenes is greatly mediated by anthropogenic SO2 and NOx emissions based on integrated ambient measurements and laboratory studies. Secondary organic aerosol (SOA) constitutes a substantial fraction of fine particulate matter and has important impacts on climate and human health. The extent to which human activities alter SOA formation from biogenic emissions in the atmosphere is largely undetermined. Here, we present direct observational evidence on the magnitude of anthropogenic influence on biogenic SOA formation based on comprehensive ambient measurements in the southeastern United States (US). Multiple high-time-resolution mass spectrometry organic aerosol measurements were made during different seasons at various locations, including urban and rural sites in the greater Atlanta area and Centreville in rural Alabama. Our results provide a quantitative understanding of the roles of anthropogenic SO2 and NOx in ambient SOA formation. We show that isoprene-derived SOA is directly mediated by the abundance of sulfate, instead of the particle water content and/or particle acidity as suggested by prior laboratory studies. Anthropogenic NOx is shown to enhance nighttime SOA formation via nitrate radical oxidation of monoterpenes, resulting in the formation of condensable organic nitrates. Together, anthropogenic sulfate and NOx can mediate 43–70% of total measured organic aerosol (29–49% of submicron particulate matter, PM1) in the southeastern US during summer. These measurements imply that future reduction in SO2 and NOx emissions can considerably reduce the SOA burden in the southeastern US. Updating current modeling frameworks with these observational constraints will also lead to more accurate treatment of aerosol formation for regions with substantial anthropogenic−biogenic interactions and consequently improve air quality and climate simulations.

Short-term associations between ambient air pollutants and pediatric asthma emergency department visits.

RATIONALE Certain outdoor air pollutants cause asthma exacerbations in children. To advance understanding of these relationships, further characterization of the dose-response and pollutant lag effects are needed, as are investigations of pollutant species beyond the commonly measured criteria pollutants. OBJECTIVES Investigate short-term associations between ambient air pollutant concentrations and emergency department visits for pediatric asthma. METHODS Daily counts of emergency department visits for asthma or wheeze among children aged 5 to 17 years were collected from 41 Metropolitan Atlanta hospitals during 1993-2004 (n = 91,386 visits). Ambient concentrations of gaseous pollutants and speciated particulate matter were available from stationary monitors during this time period. Rate ratios for the warm season (May to October) and cold season (November to April) were estimated using Poisson generalized linear models in the framework of a case-crossover analysis. MEASUREMENTS AND MAIN RESULTS Both ozone and primary pollutants from traffic sources were associated with emergency department visits for asthma or wheeze; evidence for independent effects of ozone and primary pollutants from traffic sources were observed in multipollutant models. These associations tended to be of the highest magnitude for concentrations on the day of the emergency department visit and were present at relatively low ambient concentrations. CONCLUSIONS Even at relatively low ambient concentrations, ozone and primary pollutants from traffic sources independently contributed to the burden of emergency department visits for pediatric asthma.

Fine Particle Sources and Cardiorespiratory Morbidity: An Application of Chemical Mass Balance and Factor Analytical Source-Apportionment Methods

Background Interest in the health effects of particulate matter (PM) has focused on identifying sources of PM, including biomass burning, power plants, and gasoline and diesel emissions that may be associated with adverse health risks. Few epidemiologic studies, however, have included source-apportionment estimates in their examinations of PM health effects. We analyzed a time-series of chemically speciated PM measurements in Atlanta, Georgia, and conducted an epidemiologic analysis using data from three distinct source-apportionment methods. Objective The key objective of this analysis was to compare epidemiologic findings generated using both factor analysis and mass balance source-apportionment methods. Methods We analyzed data collected between November 1998 and December 2002 using positive-matrix factorization (PMF), modified chemical mass balance (CMB-LGO), and a tracer approach. Emergency department (ED) visits for a combined cardiovascular (CVD) and respiratory disease (RD) group were assessed as end points. We estimated the risk ratio (RR) associated with same day PM concentrations using Poisson generalized linear models. Results There were significant, positive associations between same-day PM2.5 (PM with aero-dynamic diameter ≤ 2.5 μm) concentrations attributed to mobile sources (RR range, 1.018–1.025) and biomass combustion, primarily prescribed forest burning and residential wood combustion, (RR range, 1.024–1.033) source categories and CVD-related ED visits. Associations between the source categories and RD visits were not significant for all models except sulfate-rich secondary PM2.5 (RR range, 1.012–1.020). Generally, the epidemiologic results were robust to the selection of source-apportionment method, with strong agreement between the RR estimates from the PMF and CMB-LGO models, as well as with results from models using single-species tracers as surrogates of the source-apportioned PM2.5 values. Conclusions Despite differences among the source-apportionment methods, these findings suggest that modeled source-apportioned data can produce robust estimates of acute health risk. In Atlanta, there were consistent associations across methods between PM2.5 from mobile sources and biomass burning with both cardiovascular and respiratory ED visits, and between sulfate-rich secondary PM2.5 with respiratory visits.

Neighborhood Poverty and Racial Differences in ESRD Incidence

Poverty is associated with increased risk of ESRD, but its contribution to observed racial differences in disease incidence is not well-defined. To explore the contribution of neighborhood poverty to racial disparity in ESRD incidence, we analyzed a combination of US Census and ESRD Network 6 data comprising 34,767 patients that initiated dialysis in Georgia, North Carolina, or South Carolina between January 1998 and December 2002. Census tracts were used as the geographic units of analysis, and the proportion of the census tract population living below the poverty level was our measure of neighborhood poverty. Incident ESRD rates were modeled using two-level Poisson regression, where race, age and gender were individual covariates (level 1), and census tract poverty was a neighborhood covariate (level 2). Neighborhood poverty was strongly associated with higher ESRD incidence for both blacks and whites. Increasing poverty was associated with a greater disparity in ESRD rates between blacks and whites, with the former at greater risk. This raises the possibility that blacks may suffer more from lower socioeconomic conditions than whites. The disparity persisted across all poverty levels. The reasons for increasingly higher ESRD incidence among US blacks as neighborhood poverty increases remain to be explained.

Multipollutant modeling issues in a study of ambient air quality and emergency department visits in Atlanta

Multipollutant models are frequently used to differentiate roles of multiple pollutants in epidemiologic studies of ambient air pollution. In the presence of differing levels of measurement error across pollutants under consideration, however, they can be biased and as misleading as single-pollutant models. Their appropriate interpretation depends on the relationships among the pollutant measurements and the outcomes in question. In situations where two or more pollutant variables may be acting as surrogates for the etiologic agent(s), multipollutant models can help identify the best surrogate, but the risk estimates may be influenced by inclusion of a second variable that is not itself an independent risk factor for the outcome in question. In this paper, these issues will be illustrated in the context of an ongoing study of emergency visits in Atlanta. Emergency department visits from 41 of 42 hospitals serving the 20-county Atlanta metropolitan area for the period 1993–2004 (n=10,206,389 visits) were studied in relation to ambient pollutant levels, including speciated particle measurements from an intensive monitoring campaign at a downtown station starting in 1998. Relative to our earlier publications, reporting results through 2000, the period for which the speciated data are available is now tripled (6 years in length). Poisson generalized linear models were used to examine outcome counts in relation to 3-day moving average concentrations of pollutants of a priori interest (ozone, nitrogen dioxide, carbon monoxide, sulfur dioxide, oxygenated hydrocarbons, PM10, coarse PM, PM2.5, and the following components of PM2.5: elemental carbon, organic carbon, sulfate, and water-soluble transition metals). In the present analysis, we report results for two outcome groups: a respiratory outcomes group and a cardiovascular outcomes group. For cardiovascular visits, associations were observed with CO, NO2, and PM2.5 elemental carbon and organic carbon. In multipollutant models, CO was the strongest predictor. For respiratory visits, associations were observed with ozone, PM10, CO, and NO2 in single-pollutant models. In multipollutant models, PM10 and ozone persisted as predictors, with ozone the stronger predictor. Caveats and considerations in interpreting the multipollutant model results are discussed.

Ambient Air Pollution and Preterm Birth: A Time-series Analysis

Background: An emerging body of evidence suggests that ambient levels of air pollution during pregnancy are associated with preterm birth. Methods: To further investigate these relationships we used vital record data to construct a retrospective cohort of 476,489 births occurring between 1994 and 2004 in 5 central counties of metropolitan Atlanta. Using a time-series approach, we examined aggregated daily counts of preterm birth in relation to ambient levels of carbon monoxide, nitrogen dioxide, sulfur dioxide, ozone, particulate matter <10 &mgr;m in diameter (PM10), particulate matter <2.5 &mgr;m in diameter (PM2.5), and speciated PM measurements. Daily pollutant levels in 5-county Atlanta were characterized using a population-weighted spatial average of air quality monitors in the study area. We also examined ambient concentrations at individual monitors in analyses limited to mothers with residential geocodes within 4 miles of each monitor. Relationships between average pollution levels during 3 gestational windows of interest were modeled using Poisson generalized linear models. Results were adjusted for seasonal and long-term time trends. Results: Although most results were null, there were 3 positive associations between ambient pollution levels and preterm birth in the 4-mile capture-area analyses. Daily preterm birth rates were associated with average NO2 concentrations in the preceding 6 weeks and with average PM2.5 sulfate and PM2.5 water-soluble metal concentrations in the preceding week. Conclusions: Results provide limited support for late-pregnancy effects of ambient air pollution on preterm birth.

Menstrual cycle characteristics: associations with fertility and spontaneous abortion.

Background: Epidemiologists often use menstrual cycle patterns as indicators of endocrine function in environmental and occupational studies, yet few studies have considered whether menstrual cycle characteristics are associated with fertility or pregnancy outcome. Methods: We prospectively studied 470 women to determine whether cycle length or bleed length were associated with fertility or spontaneous abortion. Women completed daily diaries with information on menstrual bleeding, intercourse, birth control use, and covariates. For each menstrual cycle, women collected at least 2 urine samples, which were assayed for human chorionic gonadotropin to define early pregnancies. Women were followed for 1 year or until the end of a clinical pregnancy. Results: Cycles with lengths of 30 to 31 days preceded cycles with the highest fecundity. Shorter cycles were less likely to be followed by conception (fecundity ratio [FR] = 0.6; 95% confidence interval [CI] = 0.4–1.0). Compared with 30- to 31-day cycles, conceptions after shorter and longer cycles were more likely to be spontaneously aborted (for shorter cycles, odds ratio [OR] = 3.0 [95% CI = 0.9–9.6] and for longer cycles, OR = 3.0 [0.9–10.6]). Cycles with 5 days of menstrual bleeding had the highest fecundity. Cycles with up to 4 days of bleeding had lower fecundity (for bleed lengths of 4 days, FR = 0.5 [0.3–0.8] and for bleed lengths less than 4 days, FR = 0.6 [0.3–0.9]). Spontaneous abortion was less likely after bleeds greater than 5 days (OR = 0.4 [0.1–1.1]) when compared with 5-day bleeds. Conclusions: Menstrual cycle characteristics appear to be associated with fertility and spontaneous abortion.

Ambient pollen concentrations and emergency department visits for asthma and wheeze

BACKGROUND Previous studies report associations between aeroallergen exposure and asthma exacerbations. Aeroallergen burdens and asthma prevalence are increasing worldwide and are projected to increase further with climate change, highlighting the importance of understanding population-level relationships between ambient pollen concentrations and asthma. OBJECTIVE We sought to examine short-term associations between ambient concentrations of various pollen taxa and emergency department (ED) visits for asthma and wheeze in the Atlanta metropolitan area between 1993 and 2004. METHODS We assessed associations between the 3-day moving average (lag 0-1-2) of Betulaceae (except Alnus species), Cupressaceae, Quercus species, Pinaceae (except Tsuga species), Poaceae, and Ambrosia species pollen concentrations and daily asthma and wheeze ED visit counts, controlling for covarying pollen taxa and ambient pollutant concentrations. RESULTS We observed a 2% to 3% increase in asthma- and wheeze-related ED visits per SD increase in Quercus species and Poaceae pollen and a 10% to 15% increased risk on days with the highest concentrations (comparing the top 5% of days with the lowest 50% of days). An SD increase in Cupressaceae concentrations was associated with a 1% decrease in ED visits. The association for Quercus species pollen was strongest for children aged 5 to 17 years. Effects of Ambrosia species pollen on asthma exacerbations were difficult to assess in this large-scale temporal analysis because of possible confounding by the steep increase in circulating rhinoviruses every September. CONCLUSION Poaceae and Quercus species pollen contribute to asthma morbidity in Atlanta. Altered Quercus species and Poaceae pollen production caused by climate change could affect allergen-induced asthma morbidity in the southeastern United States.

Reactive Oxygen Species Generation Linked to Sources of Atmospheric Particulate Matter and Cardiorespiratory Effects.

Exposure to atmospheric fine particulate matter (PM2.5) is associated with cardiorespiratory morbidity and mortality, but the mechanisms are not well understood. We assess the hypothesis that PM2.5 induces oxidative stress in the body via catalytic generation of reactive oxygen species (ROS). A dithiothreitol (DTT) assay was used to measure the ROS-generation potential of water-soluble PM2.5. Source apportionment on ambient (Atlanta, GA) PM2.5 was performed using the chemical mass balance method with ensemble-averaged source impact profiles. Linear regression analysis was used to relate PM2.5 emission sources to ROS-generation potential and to estimate historical levels of DTT activity for use in an epidemiologic analysis for the period of 1998-2009. Light-duty gasoline vehicles (LDGV) exhibited the highest intrinsic DTT activity, followed by biomass burning (BURN) and heavy-duty diesel vehicles (HDDV) (0.11 ± 0.02, 0.069 ± 0.02, and 0.052 ± 0.01 nmol min(-1) μg(-1)source, respectively). BURN contributed the largest fraction to total DTT activity over the study period, followed by LDGV and HDDV (45, 20, and 14%, respectively). DTT activity was more strongly associated with emergency department visits for asthma/wheezing and congestive heart failure than PM2.5. This work provides further epidemiologic evidence of a biologically plausible mechanism, that of oxidative stress, for associations of adverse health outcomes with PM2.5 mass and supports continued assessment of the utility of the DTT activity assay as a measure of ROS-generating potential of particles.

Seasonality of birth and implications for temporal studies of preterm birth.

Background: A strength of time-series analyses is the inherent control of individual-level risk factors that do not vary temporally. However, in studies of adverse pregnancy outcomes, risk factors considered time-invariant at the individual level may vary seasonally when aggregated into a pregnancy risk set. To illustrate, we describe the seasonal patterns of birth in Atlanta and demonstrate how these patterns could lead to confounding in time-series studies of seasonally-varying exposures and preterm birth. Methods: The study cohort included all births in 20-county metropolitan Atlanta delivered during the period 1994–2004 (n = 715,875). We assessed the seasonal patterns of estimated conception and birth for the full cohort and for subgroups stratified by sociodemographic factors. Based on the observed patterns, we quantified the degree of potential confounding created by (1) differences in the gestational age distribution in the risk set across calendar months and (2) differences in the sociodemographic composition of the risk set across calendar months. Results: The overall seasonal pattern of birth was characterized by a peak in August–September and troughs in April–May and November–January. Seasonal patterns differed among racial and ethnic groups, maternal education levels, and marital status. As a consequence of these seasonal patterns, systematic seasonal differences in the gestational age distribution and the sociodemographic composition of the risk set led to differences in expected rates of preterm birth across calendar months. Conclusions: Time-series investigations of seasonally-varying exposures and adverse pregnancy outcomes should consider the potential for bias due to seasonal heterogeneity in the risk set.