National Estimates of Outdoor Air Toxics Concentrations
Open accessAbstract
The Clean Air Act identifies 189 hazardous air pollutants (HAPs), or "air toxics," associated with a wide range of adverse human health effects. The U.S. Environmental Protection Agency has conducted a modeling study with the Assessment System for Population Exposure Nationwide (ASPEN) to gain a greater understanding of the spatial distribution of concentrations of these HAPs resulting from contributions of multiple emission sources. The study estimates year 1990 long-term outdoor concentrations of 148 air toxics for each census tract in the continental United States, utilizing a Gaussian air dispersion modeling approach. Ratios of median national modeled concentrations to estimated emissions indicate that emission totals without consideration of emission source type can be a misleading indicator of air quality. The results also indicate priorities for improvements in modeling methodology and emissions identification. Model performance evaluation suggests a tendency for underprediction of observed concentrations, which is likely due, at least in part, to a number of limitations of the Gaussian modeling formulation. Emissions estimates for HAPs have a high degree of uncertainty and contribute to discrepancies between modeled and monitored concentration estimates. The model's ranking of concentrations among monitoring sites is reasonably good for most of the gaseous HAPs evaluated, with ranking accuracy ranging from 66 to 100%.
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Similar exposure assessment methods for different air pollutant compounds are heterogeneous in terms of internal validity.
“The justification for this was based on empirical evidence demonstrating that similar exposure assessment methods for different air pollutant compounds are heterogeneous in terms of their internal validity [32, 33].”
From A Systematic Review and Meta-Analysis of Multiple Airborne Pollutants and Autism Spectrum Disorder (2016) · cites this paper as [32]
Initial exposure assessment risk of bias ratings for NATA data were assigned as probably low for higher confidence, probably high for medium confidence, and high for lower confidence.
““probably high” for those with “medium” confidence (i.e., coke oven emissions, vinyl chloride, chloroform, ethylene dibromide, etc.), and “high” for those with “lower” confidence (i.e., arsenic compounds, beryllium compounds, cadmium compounds, lead compounds, etc.).”
From A Systematic Review and Meta-Analysis of Multiple Airborne Pollutants and Autism Spectrum Disorder (2016) · cites this paper as [62]
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Sources of variability in ambient air toxics monitoring data
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- Authors
- Rosenbaum, A. S., Axelrad, D. A., Woodruff, T. J., Wei, Y.-H., Ligocki, M. P., & Cohen, J. P.
- Affiliations
- Environmental Protection Agency (US)
- a ICF Consulting , San Rafael , California , USA
- Venue
- Journal of the Air & Waste Management Association
- Publisher
- Informa UK Limited
- Published
- 1999-10
- Volume
- 49
- Issue
- 10
- Pages
- 1138-1152
- ISSN
- 1047-3289 (ISSN-L)
- 1096-2247
- 2162-2906
- OpenAlex
- W2047205424
- Cited by
- 103
- References
- 11
- Citations by year
- 2024: 1 · 2023: 1 · 2021: 1 · 2020: 1 · 2019: 4 · 2018: 2 · 2017: 1 · 2016: 2 · 2015: 4 · 2014: 2 · 2013: 5 · 2012: 2
- FWCI
- 9.19
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the Air & Waste Management Association (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Toxic Organic Pollutants Impact
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Atmospheric chemistry and aerosols
- Keywords
- hazardous air pollutants, population exposure, aspen, emission source contributions, emission uncertainty, model evaluation, Clean Air Act, air quality modeling
- MeSH terms
- Air Pollutants, Models, Theoretical, United States, Hazardous Substances
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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