Methods for Quantifying Source‐Specific Air Pollution Exposure to Serve Epidemiology, Risk Assessment, and Environmental Justice
Abstract Identifying sources of air pollution exposure is crucial for addressing their health impacts and associated inequities. Researchers have developed modeling approaches to resolve source‐specific exposure for application in exposure assessments, epidemiology, risk assessments, and environment...
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| Format: | Article |
| Language: | English |
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American Geophysical Union (AGU)
2024-11-01
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| Series: | GeoHealth |
| Online Access: | https://doi.org/10.1029/2024GH001188 |
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| _version_ | 1846151936179437568 |
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| author | Xiaorong Shan Joan A. Casey Jenni A. Shearston Lucas R. F. Henneman |
| author_facet | Xiaorong Shan Joan A. Casey Jenni A. Shearston Lucas R. F. Henneman |
| author_sort | Xiaorong Shan |
| collection | DOAJ |
| description | Abstract Identifying sources of air pollution exposure is crucial for addressing their health impacts and associated inequities. Researchers have developed modeling approaches to resolve source‐specific exposure for application in exposure assessments, epidemiology, risk assessments, and environmental justice. We explore six source‐specific air pollution exposure assessment approaches: Photochemical Grid Models (PGMs), Data‐Driven Statistical Models, Dispersion Models, Reduced Complexity chemical transport Models (RCMs), Receptor Models, and Proximity Exposure Estimation Models. These models have been applied to estimate exposure from sources such as on‐road vehicles, power plants, industrial sources, and wildfires. We categorize these models based on their approaches for assessing emissions and atmospheric processes (e.g., statistical or first principles), their exposure units (direct physical measures or indirect measures/scaled indices), and their temporal and spatial scales. While most of the studies we discuss are from the United States, the methodologies and models are applicable to other countries and regions. We recommend identifying the key physical processes that determine exposure from a given source and using a model that sufficiently accounts for these processes. For instance, PGMs use first principles parameterizations of atmospheric processes and provide source impacts exposure variability in concentration units, although approaches within PGMs for source attribution introduce uncertainties relative to the base model and are difficult to evaluate. Evaluation is important but difficult—since source‐specific exposure is difficult to observe, the most direct evaluation methods involve comparisons with alternative models. |
| format | Article |
| id | doaj-art-c84de2a29c114f7bb9ce9fa87b4c7609 |
| institution | Kabale University |
| issn | 2471-1403 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | GeoHealth |
| spelling | doaj-art-c84de2a29c114f7bb9ce9fa87b4c76092024-11-27T03:42:28ZengAmerican Geophysical Union (AGU)GeoHealth2471-14032024-11-01811n/an/a10.1029/2024GH001188Methods for Quantifying Source‐Specific Air Pollution Exposure to Serve Epidemiology, Risk Assessment, and Environmental JusticeXiaorong Shan0Joan A. Casey1Jenni A. Shearston2Lucas R. F. Henneman3Department of Civil, Environmental, and Infrastructure Engineering College of Engineering and Computing George Mason University Fairfax VA USADepartment of Environmental and Occupational Health Sciences School of Public Health University of Washington Seattle WA USADepartment of Environmental Science, Policy, & Management School of Public Health University of California Berkeley Berkeley CA USADepartment of Civil, Environmental, and Infrastructure Engineering College of Engineering and Computing George Mason University Fairfax VA USAAbstract Identifying sources of air pollution exposure is crucial for addressing their health impacts and associated inequities. Researchers have developed modeling approaches to resolve source‐specific exposure for application in exposure assessments, epidemiology, risk assessments, and environmental justice. We explore six source‐specific air pollution exposure assessment approaches: Photochemical Grid Models (PGMs), Data‐Driven Statistical Models, Dispersion Models, Reduced Complexity chemical transport Models (RCMs), Receptor Models, and Proximity Exposure Estimation Models. These models have been applied to estimate exposure from sources such as on‐road vehicles, power plants, industrial sources, and wildfires. We categorize these models based on their approaches for assessing emissions and atmospheric processes (e.g., statistical or first principles), their exposure units (direct physical measures or indirect measures/scaled indices), and their temporal and spatial scales. While most of the studies we discuss are from the United States, the methodologies and models are applicable to other countries and regions. We recommend identifying the key physical processes that determine exposure from a given source and using a model that sufficiently accounts for these processes. For instance, PGMs use first principles parameterizations of atmospheric processes and provide source impacts exposure variability in concentration units, although approaches within PGMs for source attribution introduce uncertainties relative to the base model and are difficult to evaluate. Evaluation is important but difficult—since source‐specific exposure is difficult to observe, the most direct evaluation methods involve comparisons with alternative models.https://doi.org/10.1029/2024GH001188 |
| spellingShingle | Xiaorong Shan Joan A. Casey Jenni A. Shearston Lucas R. F. Henneman Methods for Quantifying Source‐Specific Air Pollution Exposure to Serve Epidemiology, Risk Assessment, and Environmental Justice GeoHealth |
| title | Methods for Quantifying Source‐Specific Air Pollution Exposure to Serve Epidemiology, Risk Assessment, and Environmental Justice |
| title_full | Methods for Quantifying Source‐Specific Air Pollution Exposure to Serve Epidemiology, Risk Assessment, and Environmental Justice |
| title_fullStr | Methods for Quantifying Source‐Specific Air Pollution Exposure to Serve Epidemiology, Risk Assessment, and Environmental Justice |
| title_full_unstemmed | Methods for Quantifying Source‐Specific Air Pollution Exposure to Serve Epidemiology, Risk Assessment, and Environmental Justice |
| title_short | Methods for Quantifying Source‐Specific Air Pollution Exposure to Serve Epidemiology, Risk Assessment, and Environmental Justice |
| title_sort | methods for quantifying source specific air pollution exposure to serve epidemiology risk assessment and environmental justice |
| url | https://doi.org/10.1029/2024GH001188 |
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