The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Observed relationships of ozone air pollution with temperature and emissions
Open accessAbstract
Higher temperatures caused by increasing greenhouse gas concentrations are predicted to exacerbate photochemical smog if precursor emissions remain constant. We perform a statistical analysis of 21 years of ozone and temperature observations across the rural eastern U.S. The climate penalty factor is defined as the slope of the ozone/temperature relationship. For two precursor emission regimes, before and after 2002, the climate penalty factor was consistent across the distribution of ozone observations. Prior to 2002, ozone increased by an average of ∼3.2 ppbv/°C. After 2002, power plant NO x emissions were reduced by 43%, ozone levels fell ∼10%, and the climate penalty factor dropped to ∼2.2 ppbv/°C. NO x controls are effective for reducing photochemical smog and might lessen the severity of projected climate change penalties. Air quality models should be evaluated against these observations, and the climate penalty factor metric may be useful for evaluating the response of ozone to climate change.
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Metadata
- Authors
- Bloomer, B. J., Stehr, J. W., Piety, C. A., Salawitch, R. J., & Dickerson, R. R.
- Venue
- Geophysical Research Letters
- Publisher
- American Geophysical Union (AGU)
- Published
- 2009-05
- Volume
- 36
- Issue
- 9
- ISSN
- 0094-8276 (ISSN-L)
- 1944-8007
- OpenAlex
- W2056236906
- Cited by
- 351
- References
- 17
- FWCI
- 6.38
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Bloomer, B. J., Stehr, J. W., Piety, C. A., Salawitch, R. J., & Dickerson, R. R. (2009). Observed relationships of ozone air pollution with temperature and emissions. Geophysical Research Letters. https://doi.org/10.1029/2009gl037308
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
