Articles | Volume 18, issue 16
https://doi.org/10.5194/acp-18-12123-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-18-12123-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Aug 2018
Research article |
| 22 Aug 2018
| 22 Aug 2018
Average versus high surface ozone levels over the continental USA: model bias, background influences, and interannual variability
Jean J. Guo
CORRESPONDING AUTHOR
Department of Earth and Environmental Sciences and Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA
Arlene M. Fiore
Department of Earth and Environmental Sciences and Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA
Lee T. Murray
Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA
NASA Goddard Institute for Space Studies, New York, NY, USA
now at: Department of Earth and Environmental Sciences, University of Rochester, Rochester, NY, USA
Daniel A. Jaffe
University of Washington, School of STEM, Bothell, WA and Department of Atmospheric Science, Seattle, WA, USA
Jordan L. Schnell
NOAA Geophysical Fluid Dynamics Laboratory, Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, USA
now at: Department of Earth and Planetary Sciences, Northwestern University, Chicago, IL, USA
Charles T. Moore
WESTAR and WRAP, Fort Collins, CO, USA
George P. Milly
Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA
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27 citations as recorded by crossref.
- A new method for assessing the efficacy of emission control strategies H. Luo et al. 10.1016/j.atmosenv.2018.11.010
- Estimating US Background Ozone Using Data Fusion T. Skipper et al. 10.1021/acs.est.0c08625
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- Modeling stratospheric intrusion and trans-Pacific transport on tropospheric ozone using hemispheric CMAQ during April 2010 – Part 2: Examination of emission impacts based on the higher-order decoupled direct method S. Itahashi et al. 10.5194/acp-20-3397-2020
- Local production, downward and regional transport aggravated surface ozone pollution during the historical orange-alert large-scale ozone episode in eastern China Y. Zhang et al. 10.1007/s10311-022-01421-0
- Constraining long-term NOx emissions over the United States and Europe using nitrate wet deposition monitoring networks A. Christiansen et al. 10.5194/acp-24-4569-2024
- AMORE-Isoprene v1.0: a new reduced mechanism for gas-phase isoprene oxidation F. Wiser et al. 10.5194/gmd-16-1801-2023
- The adsorption of NO2, SO2, and O3 molecules on the Al-doped stanene nanotube: a DFT study N. Karimi et al. 10.1007/s00894-022-05296-4
- Changes in US background ozone associated with the 2011 turnaround in Chinese NOx emissions K. Miyazaki et al. 10.1088/2515-7620/ac619b
- High-resolution modeling of the distribution of surface air pollutants and their intercontinental transport by a global tropospheric atmospheric chemistry source–receptor model (GNAQPMS-SM) Q. Ye et al. 10.5194/gmd-14-7573-2021
- Spatial and temporal variations of surface background ozone in China analyzed with the grid-stretching capability of GEOS-Chem High Performance X. Ye et al. 10.1016/j.scitotenv.2024.169909
- Urban canopy height ozone distribution in a Chinese inland city: Effects of anthropogenic NO emissions Y. Guan et al. 10.1016/j.scitotenv.2023.167448
- Early bird or early worm? First-mover (dis)advantages and the success of web-based social enterprises J. Halberstadt et al. 10.1016/j.techfore.2022.121784
- Assessing CMAQ model discrepancies in a heavily polluted air basin using UAV vertical profiles and sensitivity analyses Z. Zhu et al. 10.1039/D4EA00004H
- Large contribution of biomass burning emissions to ozone throughout the global remote troposphere I. Bourgeois et al. 10.1073/pnas.2109628118
- Changes in the Relative Importance of Biogenic Isoprene and Soil NOx Emissions on Ozone Concentrations in Nonattainment Areas of the United States J. Geddes et al. 10.1029/2021JD036361
- Perspectives of ozone induced neuropathology and memory decline in Alzheimer's disease: A systematic review of preclinical evidences A. Singh S et al. 10.1016/j.envpol.2022.120136
- Climate Change Penalty to Ozone Air Quality: Review of Current Understandings and Knowledge Gaps T. Fu & H. Tian 10.1007/s40726-019-00115-6
- Observational-based assessment of contributions to maximum ozone concentrations in the western United States D. Parrish et al. 10.1080/10962247.2022.2050962
- Estimating background contributions and US anthropogenic enhancements to maximum ozone concentrations in the northern US D. Parrish & C. Ennis 10.5194/acp-19-12587-2019
- Characterizing sources of high surface ozone events in the southwestern US with intensive field measurements and two global models L. Zhang et al. 10.5194/acp-20-10379-2020
- Enhanced summertime background ozone by anthropogenic emissions – Implications on ozone control policy and health risk assessment M. Kang et al. 10.1016/j.atmosenv.2023.120116
- Data‐ and Model‐Based Urban O3 Responses to NOx Changes in China and the United States X. Chen et al. 10.1029/2022JD038228
- Technical note: An assessment of the performance of statistical bias correction techniques for global chemistry–climate model surface ozone fields C. Staehle et al. 10.5194/acp-24-5953-2024
- Magnitude, trends, and impacts of ambient long-term ozone exposure in the United States from 2000 to 2015 K. Seltzer et al. 10.5194/acp-20-1757-2020
- Using machine learning to improve the estimate of U.S. background ozone F. Hosseinpour et al. 10.1016/j.atmosenv.2023.120145
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Latest update: 22 Nov 2024
Short summary
We use the GEOS-Chem model to estimate the influence from anthropogenic and background sources to ozone over the USA. Novel findings include the point that year-to-year background variability on the 10 highest observed ozone days is driven mainly by natural sources and not international or intercontinental pollution transport. High positive model biases during summer are associated with regional ozone production. The EPA 3-year average metric falls short of its aim to remove natural variability.
We use the GEOS-Chem model to estimate the influence from anthropogenic and background sources...
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