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Modelling future changes in surface ozone: a parameterized approach

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Modelling future changes in surface ozone: a parameterized approach. / Wild, O.; Fiore, A. M.; Shindell, D. T. et al.
In: Atmospheric Chemistry and Physics , Vol. 12, No. 4, 21.02.2012, p. 2037-2054.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Wild, O, Fiore, AM, Shindell, DT, Doherty, RM, Collins, WJ, Dentener, FJ, Schultz, MG, Gong, S, MacKenzie, IA, Zeng, G, Hess, P, Duncan, BN, Bergmann, DJ, Szopa, S, Jonson, JE, Keating, TJ & Zuber, A 2012, 'Modelling future changes in surface ozone: a parameterized approach', Atmospheric Chemistry and Physics , vol. 12, no. 4, pp. 2037-2054. https://doi.org/10.5194/acp-12-2037-2012

APA

Wild, O., Fiore, A. M., Shindell, D. T., Doherty, R. M., Collins, W. J., Dentener, F. J., Schultz, M. G., Gong, S., MacKenzie, I. A., Zeng, G., Hess, P., Duncan, B. N., Bergmann, D. J., Szopa, S., Jonson, J. E., Keating, T. J., & Zuber, A. (2012). Modelling future changes in surface ozone: a parameterized approach. Atmospheric Chemistry and Physics , 12(4), 2037-2054. https://doi.org/10.5194/acp-12-2037-2012

Vancouver

Wild O, Fiore AM, Shindell DT, Doherty RM, Collins WJ, Dentener FJ et al. Modelling future changes in surface ozone: a parameterized approach. Atmospheric Chemistry and Physics . 2012 Feb 21;12(4):2037-2054. doi: 10.5194/acp-12-2037-2012

Author

Wild, O. ; Fiore, A. M. ; Shindell, D. T. et al. / Modelling future changes in surface ozone: a parameterized approach. In: Atmospheric Chemistry and Physics . 2012 ; Vol. 12, No. 4. pp. 2037-2054.

Bibtex

@article{70fe210031b94f6b9390d3385dca10a2,
title = "Modelling future changes in surface ozone: a parameterized approach",
abstract = "This study describes a simple parameterization to estimate regionally averaged changes in surface ozone due to past or future changes in anthropogenic precursor emissions based on results from 14 global chemistry transport models. The method successfully reproduces the results of full simulations with these models. For a given emission scenario it provides the ensemble mean surface ozone change, a regional source attribution for each change, and an estimate of the associated uncertainty as represented by the variation between models. Using the Representative Concentration Pathway (RCP) emission scenarios as an example, we show how regional surface ozone is likely to respond to emission changes by 2050 and how changes in precursor emissions and atmospheric methane contribute to this. Surface ozone changes are substantially smaller than expected with the SRES A1B, A2 and B2 scenarios, with annual global mean reductions of as much as 2 ppb by 2050 vs. increases of 4-6 ppb under SRES, and this reflects the assumptions of more stringent precursor emission controls under the RCP scenarios. We find an average difference of around 5 ppb between the outlying RCP 2.6 and RCP 8.5 scenarios, about 75% of which can be attributed to differences in methane abundance. The study reveals the increasing importance of limiting atmospheric methane growth as emissions of other precursors are controlled, but highlights differences in modelled ozone responses to methane changes of as much as a factor of two, indicating that this remains a major uncertainty in current models.",
keywords = "TROPOSPHERIC OZONE, CLIMATE-CHANGE, AIR-QUALITY, EMISSIONS, POLLUTION, GASES, STABILIZATION, TRANSPORT, AEROSOLS, PATHWAY",
author = "O. Wild and Fiore, {A. M.} and Shindell, {D. T.} and Doherty, {R. M.} and Collins, {W. J.} and Dentener, {F. J.} and Schultz, {M. G.} and S. Gong and MacKenzie, {I. A.} and G. Zeng and P. Hess and Duncan, {B. N.} and Bergmann, {D. J.} and S. Szopa and Jonson, {J. E.} and Keating, {T. J.} and A. Zuber",
year = "2012",
month = feb,
day = "21",
doi = "10.5194/acp-12-2037-2012",
language = "English",
volume = "12",
pages = "2037--2054",
journal = "Atmospheric Chemistry and Physics ",
issn = "1680-7316",
publisher = "Copernicus GmbH (Copernicus Publications) on behalf of the European Geosciences Union (EGU)",
number = "4",

}

RIS

TY - JOUR

T1 - Modelling future changes in surface ozone: a parameterized approach

AU - Wild, O.

AU - Fiore, A. M.

AU - Shindell, D. T.

AU - Doherty, R. M.

AU - Collins, W. J.

AU - Dentener, F. J.

AU - Schultz, M. G.

AU - Gong, S.

AU - MacKenzie, I. A.

AU - Zeng, G.

AU - Hess, P.

AU - Duncan, B. N.

AU - Bergmann, D. J.

AU - Szopa, S.

AU - Jonson, J. E.

AU - Keating, T. J.

AU - Zuber, A.

PY - 2012/2/21

Y1 - 2012/2/21

N2 - This study describes a simple parameterization to estimate regionally averaged changes in surface ozone due to past or future changes in anthropogenic precursor emissions based on results from 14 global chemistry transport models. The method successfully reproduces the results of full simulations with these models. For a given emission scenario it provides the ensemble mean surface ozone change, a regional source attribution for each change, and an estimate of the associated uncertainty as represented by the variation between models. Using the Representative Concentration Pathway (RCP) emission scenarios as an example, we show how regional surface ozone is likely to respond to emission changes by 2050 and how changes in precursor emissions and atmospheric methane contribute to this. Surface ozone changes are substantially smaller than expected with the SRES A1B, A2 and B2 scenarios, with annual global mean reductions of as much as 2 ppb by 2050 vs. increases of 4-6 ppb under SRES, and this reflects the assumptions of more stringent precursor emission controls under the RCP scenarios. We find an average difference of around 5 ppb between the outlying RCP 2.6 and RCP 8.5 scenarios, about 75% of which can be attributed to differences in methane abundance. The study reveals the increasing importance of limiting atmospheric methane growth as emissions of other precursors are controlled, but highlights differences in modelled ozone responses to methane changes of as much as a factor of two, indicating that this remains a major uncertainty in current models.

AB - This study describes a simple parameterization to estimate regionally averaged changes in surface ozone due to past or future changes in anthropogenic precursor emissions based on results from 14 global chemistry transport models. The method successfully reproduces the results of full simulations with these models. For a given emission scenario it provides the ensemble mean surface ozone change, a regional source attribution for each change, and an estimate of the associated uncertainty as represented by the variation between models. Using the Representative Concentration Pathway (RCP) emission scenarios as an example, we show how regional surface ozone is likely to respond to emission changes by 2050 and how changes in precursor emissions and atmospheric methane contribute to this. Surface ozone changes are substantially smaller than expected with the SRES A1B, A2 and B2 scenarios, with annual global mean reductions of as much as 2 ppb by 2050 vs. increases of 4-6 ppb under SRES, and this reflects the assumptions of more stringent precursor emission controls under the RCP scenarios. We find an average difference of around 5 ppb between the outlying RCP 2.6 and RCP 8.5 scenarios, about 75% of which can be attributed to differences in methane abundance. The study reveals the increasing importance of limiting atmospheric methane growth as emissions of other precursors are controlled, but highlights differences in modelled ozone responses to methane changes of as much as a factor of two, indicating that this remains a major uncertainty in current models.

KW - TROPOSPHERIC OZONE

KW - CLIMATE-CHANGE

KW - AIR-QUALITY

KW - EMISSIONS

KW - POLLUTION

KW - GASES

KW - STABILIZATION

KW - TRANSPORT

KW - AEROSOLS

KW - PATHWAY

UR - http://www.scopus.com/inward/record.url?scp=84868673342&partnerID=8YFLogxK

U2 - 10.5194/acp-12-2037-2012

DO - 10.5194/acp-12-2037-2012

M3 - Journal article

VL - 12

SP - 2037

EP - 2054

JO - Atmospheric Chemistry and Physics

JF - Atmospheric Chemistry and Physics

SN - 1680-7316

IS - 4

ER -