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Attribution of ground-level ozone to anthropogenic and natural sources of NO x and reactive carbon in a global chemical transport model
Open accessPreprint — published as 10.5194/acp-20-10707-2020
Abstract
Abstract. We perform a source attribution for tropospheric and ground-level ozone using a novel technique which accounts separately for the contributions of the two chemically distinct emitted precursors (reactive carbon and oxides of nitrogen) to the chemical production of ozone in the troposphere. By tagging anthropogenic emissions of these precursors according to the geographical region from which they are emitted, we determine source/receptor relationships for ground-level ozone. Our methodology reproduces earlier results obtained through other techniques for ozone source attribution, and also delivers additional information about the modelled processes responsible for intercontinental transport of ozone, which is especially strong during the spring months. The current generation of chemical transport models used to support international negotiations aimed at reducing the intercontinental transport of ozone show especially strong inter-model differences in simulated springtime ozone. Current models also simulate a large range of different responses of surface ozone to methane, one of the major precursors of ground-level ozone. Using our novel source attribution technique, we show that emissions of NOx from international shipping over the high seas play a disproportionately strong role in our model system to the hemispheric-scale response of surface ozone to changes in methane, as well as to the springtime maximum in intercontinental transport of ozone and its precursors. We recommend a renewed focus on improvement of the representation of the chemistry of ship NOx emissions in current-generation models. We demonstrate the utility of ozone source attribution as a powerful model diagnostic tool, and recommend that similar source attribution techniques become a standard part of future model inter-comparison studies.
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“Moreover, CH4 and NO𝑋 participate in a chain reaction that leads to the dissolution of CH4 and formation of the O3 (Butler et al., 2020).”
From Decoding methane concentration in Alberta oil sands: A machine learning exploration (2025) · cites this paper as Butler et al., 2020
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Self-citation
Metadata
- Authors
- Butler, T., Lupascu, A., & Nalam, A.
- Affiliations
- Research Institute for Sustainability at GFZ (DE)
- Corresponding author
- Butler, Tim
- Venue
- Atmospheric chemistry and physics
- Publisher
- Copernicus GmbH
- Published
- 2020-05-20
- Volume
- 20
- Issue
- 17
- Pages
- 10707-10731
- ISSN
- 1680-7316 (ISSN-L)
- OpenAlex
- W3028207660
- Cited by
- 101
- References
- 80
- Citations by year
- 2026: 12 · 2025: 17 · 2024: 27 · 2023: 20 · 2022: 19 · 2021: 6
- FWCI
- 3.69
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
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- Funders
- Bundesministerium für Bildung und Forschung
- Brandenburger Staatsministerium für Wissenschaft, Forschung und Kultur
- Topics
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Atmospheric chemistry and aerosols
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Atmospheric Ozone and Climate
- Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric and Environmental Gas Dynamics
- Keywords
- surface ozone, nitrogen oxides, reactive carbon, source-receptor relationships, ship emissions, methane, tropospheric chemistry
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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