Journal of the Air & Waste Management Association (1995)
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J Air Waste Manag Assoc · May 2015
Respiratory hospitalizations in association with fine PM and its components in New York State.
Despite observed geographic and temporal variation in particulate matter (PM)-related health morbidities, only a small number of epidemiologic studies have evaluated the relation between PM2.5 chemical constituents and respiratory disease. Most assessments are limited by inadequate spatial and temporal resolution of ambient PM measurements and/or by their approaches to examine the role of specific PM components on health outcomes. In a case-crossover analysis using daily average ambient PM2.5 total mass and species estimates derived from the Community Multiscale Air Quality (CMAQ) model and available observations, we examined the association between the chemical components of PM (including elemental and organic carbon, sulfate, nitrate, ammonium, and other remaining) and respiratory hospitalizations in New York State. We evaluated relationships between levels (low, medium, high) of PM constituent mass fractions, and assessed modification of the PM2.5-hospitalization association via models stratified by mass fractions of both primary and secondary PM components. In our results, average daily PM2.5 concentrations in New York State were generally lower than the 24-hr average National Ambient Air Quality Standard (NAAQS). Year-round analyses showed statistically significant positive associations between respiratory hospitalizations and PM2.5 total mass, sulfate, nitrate, and ammonium concentrations at multiple exposure lags (0.5-2.0% per interquartile range [IQR] increase). Primarily in the summer months, the greatest associations with respiratory hospitalizations were observed per IQR increase in the secondary species sulfate and ammonium concentrations at lags of 1-4 days (1.0-2.0%). Although there were subtle differences in associations observed between mass fraction tertiles, there was no strong evidence to support modification of the PM2.5-respiratory disease association by a particular constituent. We conclude that ambient concentrations of PM2.5 and secondary aerosols including sulfate, ammonium, and nitrate were positively associated with respiratory hospitalizations, although patterns varied by season. Exposure to specific fine PM constituents is a plausible risk factor for respiratory hospitalization in New York State. ⋯ The association between ambient concentrations of PM2.5 components has been evaluated in only a small number of epidemiologic studies with refined spatial and temporal scale data. In New York State, fine PM and several of its constituents, including sulfate, ammonium, and nitrate, were positively associated with respiratory hospitalizations. Results suggest that PM species relationships and their influence on respiratory endpoints are complex and season dependent. Additional work is needed to better understand the relative toxicity of PM species, and to further explore the role of co-pollutant relationships and exposure prediction error on observed PM-respiratory disease associations.
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J Air Waste Manag Assoc · May 2015
Health benefits of air pollution abatement policy: Role of the shape of the concentration-response function.
There is strong evidence that fine particulate matter (aerodynamic diameter<2.5 μm; PM2.5) air pollution contributes to increased risk of disease and death. Estimates of the burden of disease attributable to PM2.5 pollution and benefits of reducing pollution are dependent upon the shape of the concentration response (C-R) functions. Recent evidence suggests that the C-R function between PM2.5 air pollution and mortality risk may be supralinear across wide ranges of exposure. Such results imply that incremental pollution abatement efforts may yield greater benefits in relatively clean areas than in highly polluted areas. The role of the shape of the C-R function in evaluating and understanding the costs and health benefits of air pollution abatement policy is explored. There remain uncertainties regarding the shape of the C-R function, and additional efforts to more fully understand the C-R relationships between PM2.5 and adverse health effects are needed to allow for more informed and effective air pollution abatement policies. Current evidence, however, suggests that there are benefits both from reducing air pollution in the more polluted areas and from continuing to reduce air pollution in cleaner areas. ⋯ Estimates of the benefits of reducing PM2.5 air pollution are highly dependent upon the shape of the PM2.5-mortality concentration-response (C-R) function. Recent evidence indicates that this C-R function may be supralinear across wide ranges of exposure, suggesting that incremental pollution abatement efforts may yield greater benefits in relatively clean areas than in highly polluted areas. This paper explores the role of the shape of the C-R function in evaluating and understanding the costs and health benefits of PM2.5 air pollution abatement.
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J Air Waste Manag Assoc · May 2015
Exploring the modeling of spatiotemporal variations in ambient air pollution within the land use regression framework: Estimation of PM10 concentrations on a daily basis.
Estimation of daily average exposure to PM10 (particulate matter with an aerodynamic diameter<10 μm) using the available fixed-site monitoring stations (FSMs) in a city poses a great challenge. This is because typically FSMs are limited in number when considering the spatial representativeness of their measurements and also because statistical models of citywide exposure have yet to be explored in this context. This paper deals with the later aspect of this challenge and extends the widely used land use regression (LUR) approach to deal with temporal changes in air pollution and the influence of transboundary air pollution on short-term variations in PM10. Using the concept of multiple linear regression (MLR) modeling, the average daily concentrations of PM10 in two European cities, Vienna and Dublin, were modeled. Models were initially developed using the standard MLR approach in Vienna using the most recently available data. Efforts were subsequently made to (i) assess the stability of model predictions over time; (ii) explores the applicability of nonparametric regression (NPR) and artificial neural networks (ANNs) to deal with the nonlinearity of input variables. The predictive performance of the MLR models of the both cities was demonstrated to be stable over time and to produce similar results. However, NPR and ANN were found to have more improvement in the predictive performance in both cities. Using ANN produced the highest result, with daily PM10 exposure predicted at R2=66% for Vienna and 51% for Dublin. In addition, two new predictor variables were also assessed for the Dublin model. The variables representing transboundary air pollution and peak traffic count were found to account for 6.5% and 12.7% of the variation in average daily PM10 concentration. The variable representing transboundary air pollution that was derived from air mass history (from back-trajectory analysis) and population density has demonstrated a positive impact on model performance. ⋯ The implications of this research would suggest that it is possible to produce a model of ambient air quality on a citywide scale using the readily available data. Most European cities typically have a limited FSM network with average daily concentrations of air pollutants as well as available meteorological, traffic, and land-use data. This research highlights that using these data in combination with advanced statistical techniques such as NPR or ANNs will produce reasonably accurate predictions of ambient air quality across a city, including temporal variations. Therefore, this approach reduces the need for additional measurement data to supplement existing historical records and enables a lower-cost method of air pollution model development for practitioners and policy makers.
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J Air Waste Manag Assoc · Apr 2014
Toward verifying fossil fuel CO2 emissions with the CMAQ model: motivation, model description and initial simulation.
Motivated by the question of whether and how a state-of-the-art regional chemical transport model (CTM) can facilitate characterization of CO2 spatiotemporal variability and verify CO2 fossil-fuel emissions, we for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate CO2. This paper presents methods, input data, and initial results for CO2 simulation using CMAQ over the contiguous United States in October 2007. Modeling experiments have been performed to understand the roles of fossil-fuel emissions, biosphere-atmosphere exchange, and meteorology in regulating the spatial distribution of CO2 near the surface over the contiguous United States. Three sets of net ecosystem exchange (NEE) fluxes were used as input to assess the impact of uncertainty of NEE on CO2 concentrations simulated by CMAQ. Observational data from six tall tower sites across the country were used to evaluate model performance. In particular, at the Boulder Atmospheric Observatory (BAO), a tall tower site that receives urban emissions from Denver CO, the CMAQ model using hourly varying, high-resolution CO2 fossil-fuel emissions from the Vulcan inventory and Carbon Tracker optimized NEE reproduced the observed diurnal profile of CO2 reasonably well but with a low bias in the early morning. The spatial distribution of CO2 was found to correlate with NO(x), SO2, and CO, because of their similar fossil-fuel emission sources and common transport processes. These initial results from CMAQ demonstrate the potential of using a regional CTM to help interpret CO2 observations and understand CO2 variability in space and time. The ability to simulate a full suite of air pollutants in CMAQ will also facilitate investigations of their use as tracers for CO2 source attribution. This work serves as a proof of concept and the foundation for more comprehensive examinations of CO2 spatiotemporal variability and various uncertainties in the future. ⋯ Atmospheric CO2 has long been modeled and studied on continental to global scales to understand the global carbon cycle. This work demonstrates the potential of modeling and studying CO2 variability at fine spatiotemporal scales with CMAQ, which has been applied extensively, to study traditionally regulated air pollutants. The abundant observational records of these air pollutants and successful experience in studying and reducing their emissions may be useful for verifying CO2 emissions. Although there remains much more to further investigate, this work opens up a discussion on whether and how to study CO2 as an air pollutant.
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J Air Waste Manag Assoc · Jul 2013
Hazardous airborne carbonyls emissions in industrial workplaces in China.
A pilot hazardous airborne carbonyls study was carried out in Hong Kong and the Mainland of China. Workplace air samples in 14 factories of various types of manufacturing and industrial operations were collected and analyzed for a panel of 21 carbonyl compounds. The factories can be classified into five general categories, including food processing, electroplating, textile dyeing, chemical manufacturer, and petroleum refinery. Formaldehyde was invariably the most abundant carbonyl compound among all the workplace air samples, accounting for 22.0-44.0% of the total measured amount of carbonyls on a molar basis. Acetone was also found to be an abundant carbonyl in workplace settings; among the selected industrial sectors, chemical manufacturers' workplaces had the highest percentage (an average of 42.6%) of acetone in the total amount of carbonyls measured in air. Benzaldehyde accounted for an average of 20.5% of the total amount of detected carbonyls in electroplating factories, but its contribution was minor in other industrial workplaces. Long-chain aliphatic carbonyls (C6-C10) accounted for a large portion (37.2%) of the total carbonyls in food-processing factories. Glyoxal and methylglyoxal existed at variable levels in the selected workplaces, ranging from 0.2% to 5.5%. The mixing ratio of formaldehyde ranged from 8.6 to 101.2 ppbv in the sampled workplaces. The observed amount of formaldehyde in two paint and wax manufacturers and food-processing factories exceeded the World Health Organization (WHO) air quality guideline of 81.8 ppbv. Carcinogenic risks of chronic exposure to formaldehyde and acetaldehyde by the workers were evaluated. The lifetime cancer hazard risks associated with formaldehyde exposure to male and female workers ranged from 2.01 x 10(-5) to 2.37 x 10(-4) and 2.68 x 10(-5) to 3.16 x 10(-4), respectively. Such elevated risk values suggest that the negative health impact of formaldehyde exposure represents a valid concern, and proper actions should be taken to protect workers from such risks. ⋯ Many carbonyl species (e.g., formaldehyde, acetaldehyde, and acrolein) are air toxins and they pose public healt risks. The scope of this investigation covers 21 types of carbonyls based on samples collected from 14 different workplaces. Findings of the study will not only provide a comprehensive assessment of indoor air quality with regard to workers' healthy and safety, but also establish a theoretical foundation for future formulation of intervention strategies to reduce occupational carbonyl exposures. No similar study has been carried out either in Hong Kong or the Mainland of China.