Dataset Information

A comparison of hourly with annual air pollutant emissions: Implications for estimating acute exposure and public health risk.

ABSTRACT: Health risks from air pollutants are evaluated by comparing chronic (i.e., an average over 1 yr or greater) or acute (typically 1-hr) exposure estimates with chemical- and duration-specific reference values or standards. When estimating long-term pollutant concentrations via exposure modeling, facility-level annual average emission rates are readily available as model inputs for most air pollutants. In contrast, there are far fewer facility-level hour-by-hour emission rates available for many of these same pollutants. In this report, we first analyze hour-by-hour emission rates for total reduced sulfur (TRS) compounds from eight kraft pulp mill operations. This data set is used to demonstrate discrepancies between estimating exposure based on a single TRS emission rate that has been calculated as the mean of all operating hours of the year, as opposed to reported hourly emission rates. A similar analysis is then performed using reported hourly emission rates for sulfur dioxide (SO2) and oxides of nitrogen (NOx) from three power generating units from a U.S. power plant. Results demonstrate greater variability at kraft pulp mill operations, with ratios of reported hourly to average hourly TRS emissions ranging from less than 1 to greater than 160 during routine facility operations. Thus, if fluctuations in hourly emission rates are not accounted for, over- or underestimates of hourly exposure, and thus acute health risk, may occur. In addition to this analysis, we also demonstrate an additional challenge when assessing health risk based on hourly exposures: the lack of human health reference values based on 1-hr exposures. Implications: Largely due to the lack of reported hourly emission rate data for many air pollutants, an hourly average emission rate (calculated from an annual emission rate) is often used when modeling the potential for acute health risk. We calculated ratios between reported hourly and hourly average emission rates from pulp and paper mills and a U.S. power plant to demonstrate that if not considered, hourly fluctuations in emissions could result in an over- or underestimation of exposure and risk. We also demonstrate the lack of 1-hr human health reference values meant to be protective of the general population, including children.

SUBMITTER: Stewart MJ

PROVIDER: S-EPMC7374520 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A comparison of hourly with annual air pollutant emissions: Implications for estimating acute exposure and public health risk.

Stewart Michael J MJ Hirtz James J Woodall George M GM Weitekamp Chelsea A CA Spence Kelley K

Journal of the Air & Waste Management Association (1995) 20190522 7

Health risks from air pollutants are evaluated by comparing chronic (i.e., an average over 1 yr or greater) or acute (typically 1-hr) exposure estimates with chemical- and duration-specific reference values or standards. When estimating long-term pollutant concentrations via exposure modeling, facility-level annual average emission rates are readily available as model inputs for most air pollutants. In contrast, there are far fewer facility-level hour-by-hour emission rates available for many of ...[more]

PMID: 30870104

Similar Datasets

Project description:Vehicle emissions represent one of the most important air pollution sources in most urban areas, and elevated concentrations of pollutants found near major roads have been associated with many adverse health impacts. To understand these impacts, exposure estimates should reflect the spatial and temporal patterns observed for traffic-related air pollutants. This paper evaluates the spatial resolution and zonal systems required to estimate accurately intraurban and near-road exposures of traffic-related air pollutants. The analyses use the detailed information assembled for a large (800 km2) area centered on Detroit, Michigan, USA. Concentrations of nitrogen oxides (NOx) due to vehicle emissions were estimated using hourly traffic volumes and speeds on 9,700 links representing all but minor roads in the city, the MOVES2010 emission model, the RLINE dispersion model, local meteorological data, a temporal resolution of 1 hr, and spatial resolution as low as 10 m. Model estimates were joined with the corresponding shape files to estimate residential exposures for 700,000 individuals at property parcel, census block, census tract, and ZIP code levels. We evaluate joining methods, the spatial resolution needed to meet specific error criteria, and the extent of exposure misclassification. To portray traffic-related air pollutant exposure, raster or inverse distance-weighted interpolations are superior to nearest neighbor approaches, and interpolations between receptors and points of interest should not exceed about 40 m near major roads, and 100 m at larger distances. For census tracts and ZIP codes, average exposures are overestimated since few individuals live very near major roads, the range of concentrations is compressed, most exposures are misclassified, and high concentrations near roads are entirely omitted. While smaller zones improve performance considerably, even block-level data can misclassify many individuals. To estimate exposures and impacts of traffic-related pollutants accurately, data should be geocoded or estimated at the most-resolved spatial level; census tract and larger zones have little if any ability to represent intraurban variation in traffic-related air pollutant concentrations. These results are based on one of the most comprehensive intraurban modeling studies in the literature and results are robust. Recommendations address the value of dispersion models to portray spatial and temporal variation of air pollutants in epidemiology and other studies; techniques to improve accuracy and reduce the computational burden in urban scale modeling; the necessary spatial resolution for health surveillance, demographic, and pollution data; and the consequences of low resolution data in terms of exposure misclassification.

Project description:UNLABELLED:Geostatistical interpolation methods to estimate individual exposure to outdoor air pollutants can be used in pregnancy cohorts where personal exposure data are not collected. Our objectives were to a) develop four assessment methods (citywide average (CWA); nearest monitor (NM); inverse distance weighting (IDW); and ordinary Kriging (OK)), and b) compare daily metrics and cross-validations of interpolation models. We obtained 2008 hourly data from Mexico City's outdoor air monitoring network for PM10, PM2.5, O3, CO, NO2, and SO2 and constructed daily exposure metrics for 1,000 simulated individual locations across five populated geographic zones. Descriptive statistics from all methods were calculated for dry and wet seasons, and by zone. We also evaluated IDW and OK methods' ability to predict measured concentrations at monitors using cross validation and a coefficient of variation (COV). All methods were performed using SAS 9.3, except ordinary Kriging which was modeled using R's gstat package. Overall, mean concentrations and standard deviations were similar among the different methods for each pollutant. Correlations between methods were generally high (r=0.77 to 0.99). However, ranges of estimated concentrations determined by NM, IDW, and OK were wider than the ranges for CWA. Root mean square errors for OK were consistently equal to or lower than for the IDW method. OK standard errors varied considerably between pollutants and the computed COVs ranged from 0.46 (least error) for SO2 and PM10 to 3.91 (most error) for PM2.5. OK predicted concentrations measured at the monitors better than IDW and NM. Given the similarity in results for the exposure methods, OK is preferred because this method alone provides predicted standard errors which can be incorporated in statistical models. The daily estimated exposures calculated using these different exposure methods provide flexibility to evaluate multiple windows of exposure during pregnancy, not just trimester or pregnancy-long exposures. IMPLICATIONS:Many studies evaluating associations between outdoor air pollution and adverse pregnancy outcomes rely on outdoor air pollution monitoring data linked to information gathered from large birth registries, and often lack residence location information needed to estimate individual exposure. This study simulated 1,000 residential locations to evaluate four air pollution exposure assessment methods, and describes possible exposure misclassification from using spatial averaging versus geostatistical interpolation models. An implication of this work is that policies to reduce air pollution and exposure among pregnant women based on epidemiologic literature should take into account possible error in estimates of effect when spatial averages alone are evaluated.

Project description:Air pollution contributes significantly to global increases in mortality, particularly within urban environments. Limited knowledge exists on the mechanisms underlying health effects resulting from exposure to pollutant mixtures similar to those occurring in ambient air. In order to clarify the mechanisms underlying exposure effects, toxicogenomic analyses are used to evaluate genomewide transcript responses and map these responses to molecular networks.We compared responses induced by exposure to primary pollutants and photochemically altered (PCA) pollutant mixtures representing urban atmospheres to test our hypothesis that exposures to PCA pollutants would show increased modulation of inflammation-associated genes and pathways relative to primary air pollutants.We used an outdoor environmental irradiation chamber to expose human lung epithelial cells to mixtures representing either primary or PCA pollutants for 4 hr. Transcriptional changes were assessed using microarrays and confirmed using quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) on a subset of genes.We found a large difference in the cellular responses to the two pollutant exposures: Primary air pollutants altered the expression levels of 19 genes, whereas PCA pollutants altered 709 genes. Functional and molecular analyses of the altered genes revealed novel pathways, such as hepatocyte nuclear factor 4?, potentially regulating the pollutant responses. Chemical component analysis characterized and confirmed the photochemical transformation of primary air pollutants into PCA air pollutants.Our study shows that the photochemical transformation of primary air pollutants produces altered mixtures that cause significantly greater biological effects than the primary pollutants themselves. These findings suggest that studying individual air pollutants or primary pollutant mixtures may greatly underestimate the adverse health effects caused by air pollution.

Dataset Information

A comparison of hourly with annual air pollutant emissions: Implications for estimating acute exposure and public health risk.

Publications

A comparison of hourly with annual air pollutant emissions: Implications for estimating acute exposure and public health risk.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets