Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models
| Autor: | Forrest Lacey, Seohyun Choi, Narasimhan K. Larkin, Patrick L. Kinney, Ambarish Vaidyanathan, Daven K. Henze, Randall V. Martin, Arlene M. Fiore, Frank R. Freedman, Yufei Zou, James T. Kelly, Minghui Diao, Xiaomeng Jin, Mohammad Z. Al-Hamdan, Aaron van Donkelaar, Tracey Holloway, Susan O'Neill |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
medicine.medical_specialty
010504 meteorology & atmospheric sciences Fine particulate 010501 environmental sciences Management Monitoring Policy and Law Models Biological complex mixtures 01 natural sciences Article Air Pollution Environmental health Epidemiology medicine Humans Waste Management and Disposal Air quality index 0105 earth and related environmental sciences Air Pollutants Health risk assessment Atmospheric models Public health Environmental Exposure Risk factor (computing) Environmental science Particulate Matter Satellite Environmental Monitoring |
| Zdroj: | Journal of the Air & Waste Management Association. 69:1391-1414 |
| ISSN: | 2162-2906 1096-2247 |
| Popis: | Fine particulate matter (PM(2.5)) is a well-established risk factor for public health. To support both health risk assessment and epidemiological studies, data are needed on spatial and temporal patterns of PM(2.5) exposures. This review article surveys publicly available exposure datasets for surface PM(2.5) mass concentrations over the contiguous U.S., summarizes their applications and limitations, and provides suggestions on future research needs. The complex landscape of satellite instruments, model capabilities, monitor networks, and data synthesis methods offers opportunities for research development, but would benefit from guidance for new users. Guidance is provided to access publicly available PM(2.5) datasets, to explain and compare different approaches for dataset generation, and to identify sources of uncertainties associated with various types of datasets. Three main sources used to create PM(2.5) exposure data are: ground-based measurements (especially regulatory monitoring), satellite retrievals (especially aerosol optical depth, AOD), and atmospheric chemistry models. We find inconsistencies among several publicly available PM(2.5) estimates, highlighting uncertainties in the exposure datasets that are often overlooked in health effects analyses. Major differences among PM(2.5) estimates emerge from the choice of data (ground-based, satellite, and/or model), the spatiotemporal resolutions, and the algorithms used to fuse data sources. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|