Modelling Arctic lower-tropospheric ozone: processes controlling seasonal variations
<p>Previous assessments on modelling Arctic tropospheric ozone (O<span class="inline-formula"><sub>3</sub></span>) have shown that most atmospheric models continue to experience difficulties in simulating tropospheric O<span class="inline-formula"...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-08-01
|
| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://acp.copernicus.org/articles/25/8355/2025/acp-25-8355-2025.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849329465280167936 |
|---|---|
| author | W. Gong S. R. Beagley K. Toyota H. Skov J. H. Christensen A. Lupu D. Pendlebury J. Zhang U. Im Y. Kanaya A. Saiz-Lopez R. Sommariva R. Sommariva P. Effertz P. Effertz J. W. Halfacre N. Jepsen R. Kivi T. K. Koenig K. Müller C. Nordstrøm I. Petropavlovskikh I. Petropavlovskikh P. B. Shepson W. R. Simpson S. Solberg R. M. Staebler D. W. Tarasick R. Van Malderen M. Vestenius |
| author_facet | W. Gong S. R. Beagley K. Toyota H. Skov J. H. Christensen A. Lupu D. Pendlebury J. Zhang U. Im Y. Kanaya A. Saiz-Lopez R. Sommariva R. Sommariva P. Effertz P. Effertz J. W. Halfacre N. Jepsen R. Kivi T. K. Koenig K. Müller C. Nordstrøm I. Petropavlovskikh I. Petropavlovskikh P. B. Shepson W. R. Simpson S. Solberg R. M. Staebler D. W. Tarasick R. Van Malderen M. Vestenius |
| author_sort | W. Gong |
| collection | DOAJ |
| description | <p>Previous assessments on modelling Arctic tropospheric ozone (O<span class="inline-formula"><sub>3</sub></span>) have shown that most atmospheric models continue to experience difficulties in simulating tropospheric O<span class="inline-formula"><sub>3</sub></span> in the Arctic, particularly in capturing the seasonal variations at coastal sites, primarily attributed to the lack of representation of surface bromine<span id="page8356"/> chemistry in the Arctic. In this study, two independent chemical transport models (CTMs), DEHM (Danish Eulerian Hemispheric Model) and GEM-MACH (Global Environmental Multi-scale – Modelling Air quality and Chemistry), were used to simulate Arctic lower-tropospheric O<span class="inline-formula"><sub>3</sub></span> for the year 2015 at considerably higher horizontal resolutions (25 and 15 km, respectively) than the large-scale models in the previous assessments. Both models include bromine chemistry but with different mechanistic representations of bromine sources from snow- and ice-covered polar regions: a blowing-snow bromine source mechanism in DEHM and a snowpack bromine source mechanism in GEM-MACH. Model results were compared with a suite of observations in the Arctic, including hourly observations from surface sites and mobile platforms (buoys and ships) and ozonesonde profiles, to evaluate models' ability to simulate Arctic lower-tropospheric O<span class="inline-formula"><sub>3</sub></span>, particularly in capturing the seasonal variations and the key processes controlling these variations.</p>
<p>Both models are found to behave quite similarly outside the spring period and are able to capture the observed overall surface O<span class="inline-formula"><sub>3</sub></span> seasonal cycle and synoptic-scale variabilities, as well as the O<span class="inline-formula"><sub>3</sub></span> vertical profiles in the Arctic. GEM-MACH (with the snowpack bromine source mechanism) was able to simulate most of the observed springtime ozone depletion events (ODEs) at the coastal and buoy sites well, while DEHM (with the blowing-snow bromine source mechanism) simulated much fewer ODEs. The present study demonstrates that the springtime O<span class="inline-formula"><sub>3</sub></span> depletion process plays a central role in driving the surface O<span class="inline-formula"><sub>3</sub></span> seasonal cycle in central Arctic, and that the bromine-mediated ODEs, while occurring most notably within the lowest few hundred metres of air above the Arctic Ocean, can induce a 5 %–7 % of loss in the total pan-Arctic tropospheric O<span class="inline-formula"><sub>3</sub></span> burden during springtime. The model simulations also showed an overall enhancement in the pan-Arctic O<span class="inline-formula"><sub>3</sub></span> concentration due to northern boreal wildfire emissions in summer 2015; the enhancement is more significant at higher altitudes. Higher O<span class="inline-formula"><sub>3</sub></span> excess ratios (<span class="inline-formula">Δ</span>O<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M13" display="inline" overflow="scroll" dspmath="mathml"><mrow><msub><mi/><mn mathvariant="normal">3</mn></msub><mo>/</mo><mi mathvariant="normal">Δ</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="21pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="6d8b7ce649b9583697286396b19d37dc"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-8355-2025-ie00001.svg" width="21pt" height="14pt" src="acp-25-8355-2025-ie00001.png"/></svg:svg></span></span>CO) found aloft compared to near the surface indicate greater photochemical O<span class="inline-formula"><sub>3</sub></span> production efficiency at higher altitudes in fire-impacted air masses. The model simulations further indicated an enhancement in NO<span class="inline-formula"><sub><i>y</i></sub></span> in the Arctic due to wildfires; a large portion of NO<span class="inline-formula"><sub><i>y</i></sub></span> produced from the wildfire emissions is found in the form of PAN that is transported to the Arctic, particularly at higher altitudes, potentially contributing to O<span class="inline-formula"><sub>3</sub></span> production there.</p> |
| format | Article |
| id | doaj-art-165a8d7c3aa84ffa8a0c3d0744cbaec6 |
| institution | Kabale University |
| issn | 1680-7316 1680-7324 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj-art-165a8d7c3aa84ffa8a0c3d0744cbaec62025-08-20T03:47:16ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242025-08-01258355840510.5194/acp-25-8355-2025Modelling Arctic lower-tropospheric ozone: processes controlling seasonal variationsW. Gong0S. R. Beagley1K. Toyota2H. Skov3J. H. Christensen4A. Lupu5D. Pendlebury6J. Zhang7U. Im8Y. Kanaya9A. Saiz-Lopez10R. Sommariva11R. Sommariva12P. Effertz13P. Effertz14J. W. Halfacre15N. Jepsen16R. Kivi17T. K. Koenig18K. Müller19C. Nordstrøm20I. Petropavlovskikh21I. Petropavlovskikh22P. B. Shepson23W. R. Simpson24S. Solberg25R. M. Staebler26D. W. Tarasick27R. Van Malderen28M. Vestenius29Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, M3H 5T4, CanadaAir Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, M3H 5T4, CanadaAir Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, M3H 5T4, CanadaDepartment of Environmental Science, iClimate, Aarhus University, Roskilde, 4000, DenmarkDepartment of Environmental Science, iClimate, Aarhus University, Roskilde, 4000, DenmarkAir Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, M3H 5T4, CanadaAir Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, M3H 5T4, CanadaAir Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, M3H 5T4, CanadaDepartment of Environmental Science, iClimate, Aarhus University, Roskilde, 4000, DenmarkResearch Institute for Global Change (RIGC), Japan Agency for Marine–Earth Science and Technology (JAMSTEC), Yokohama 2360001, JapanDepartment of Atmospheric Chemistry and Climate, Institute of Physical Chemistry Blas Cabrera, CSIC, Madrid, 28006, SpainSchool of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UKSchool of Chemistry, University of Leicester, Leicester, UKCooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USANational Oceanic and Atmospheric Administration Global Monitoring Laboratory, Boulder, CO 80305, USAWolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, YO10 5DD, UKResearch and Development, Danish Meteorological Institute, 2100 Copenhagen, DenmarkSpace and Earth Observation Centre, Finnish Meteorological Institute, Tähteläntie 62, 99600 Sodankylä, FinlandDivision of Environment and Sustainability, The Hong Kong University of Science and Technology, 999077, Hong Kong SAR, ChinaAlfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research, Telegrafenberg A43, 14473 Potsdam, GermanyDepartment of Environmental Science, iClimate, Aarhus University, Roskilde, 4000, DenmarkCooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USANational Oceanic and Atmospheric Administration Global Monitoring Laboratory, Boulder, CO 80305, USAThe School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794, USADepartment of Chemistry, Biochemistry, and Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK 99775-6160, USANorwegian Institute for Air Research (NILU), Kjeller, NorwayAir Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, M3H 5T4, CanadaAir Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, M3H 5T4, CanadaRoyal Meteorological Institute of Belgium (KMI), Solar-Terrestrial Centre of Excellence, Brussels, BelgiumAtmospheric Composition Research, Finnish Meteorological Institute, Air Quality Expert services, 00101 Helsinki, Finland<p>Previous assessments on modelling Arctic tropospheric ozone (O<span class="inline-formula"><sub>3</sub></span>) have shown that most atmospheric models continue to experience difficulties in simulating tropospheric O<span class="inline-formula"><sub>3</sub></span> in the Arctic, particularly in capturing the seasonal variations at coastal sites, primarily attributed to the lack of representation of surface bromine<span id="page8356"/> chemistry in the Arctic. In this study, two independent chemical transport models (CTMs), DEHM (Danish Eulerian Hemispheric Model) and GEM-MACH (Global Environmental Multi-scale – Modelling Air quality and Chemistry), were used to simulate Arctic lower-tropospheric O<span class="inline-formula"><sub>3</sub></span> for the year 2015 at considerably higher horizontal resolutions (25 and 15 km, respectively) than the large-scale models in the previous assessments. Both models include bromine chemistry but with different mechanistic representations of bromine sources from snow- and ice-covered polar regions: a blowing-snow bromine source mechanism in DEHM and a snowpack bromine source mechanism in GEM-MACH. Model results were compared with a suite of observations in the Arctic, including hourly observations from surface sites and mobile platforms (buoys and ships) and ozonesonde profiles, to evaluate models' ability to simulate Arctic lower-tropospheric O<span class="inline-formula"><sub>3</sub></span>, particularly in capturing the seasonal variations and the key processes controlling these variations.</p> <p>Both models are found to behave quite similarly outside the spring period and are able to capture the observed overall surface O<span class="inline-formula"><sub>3</sub></span> seasonal cycle and synoptic-scale variabilities, as well as the O<span class="inline-formula"><sub>3</sub></span> vertical profiles in the Arctic. GEM-MACH (with the snowpack bromine source mechanism) was able to simulate most of the observed springtime ozone depletion events (ODEs) at the coastal and buoy sites well, while DEHM (with the blowing-snow bromine source mechanism) simulated much fewer ODEs. The present study demonstrates that the springtime O<span class="inline-formula"><sub>3</sub></span> depletion process plays a central role in driving the surface O<span class="inline-formula"><sub>3</sub></span> seasonal cycle in central Arctic, and that the bromine-mediated ODEs, while occurring most notably within the lowest few hundred metres of air above the Arctic Ocean, can induce a 5 %–7 % of loss in the total pan-Arctic tropospheric O<span class="inline-formula"><sub>3</sub></span> burden during springtime. The model simulations also showed an overall enhancement in the pan-Arctic O<span class="inline-formula"><sub>3</sub></span> concentration due to northern boreal wildfire emissions in summer 2015; the enhancement is more significant at higher altitudes. Higher O<span class="inline-formula"><sub>3</sub></span> excess ratios (<span class="inline-formula">Δ</span>O<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M13" display="inline" overflow="scroll" dspmath="mathml"><mrow><msub><mi/><mn mathvariant="normal">3</mn></msub><mo>/</mo><mi mathvariant="normal">Δ</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="21pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="6d8b7ce649b9583697286396b19d37dc"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-8355-2025-ie00001.svg" width="21pt" height="14pt" src="acp-25-8355-2025-ie00001.png"/></svg:svg></span></span>CO) found aloft compared to near the surface indicate greater photochemical O<span class="inline-formula"><sub>3</sub></span> production efficiency at higher altitudes in fire-impacted air masses. The model simulations further indicated an enhancement in NO<span class="inline-formula"><sub><i>y</i></sub></span> in the Arctic due to wildfires; a large portion of NO<span class="inline-formula"><sub><i>y</i></sub></span> produced from the wildfire emissions is found in the form of PAN that is transported to the Arctic, particularly at higher altitudes, potentially contributing to O<span class="inline-formula"><sub>3</sub></span> production there.</p>https://acp.copernicus.org/articles/25/8355/2025/acp-25-8355-2025.pdf |
| spellingShingle | W. Gong S. R. Beagley K. Toyota H. Skov J. H. Christensen A. Lupu D. Pendlebury J. Zhang U. Im Y. Kanaya A. Saiz-Lopez R. Sommariva R. Sommariva P. Effertz P. Effertz J. W. Halfacre N. Jepsen R. Kivi T. K. Koenig K. Müller C. Nordstrøm I. Petropavlovskikh I. Petropavlovskikh P. B. Shepson W. R. Simpson S. Solberg R. M. Staebler D. W. Tarasick R. Van Malderen M. Vestenius Modelling Arctic lower-tropospheric ozone: processes controlling seasonal variations Atmospheric Chemistry and Physics |
| title | Modelling Arctic lower-tropospheric ozone: processes controlling seasonal variations |
| title_full | Modelling Arctic lower-tropospheric ozone: processes controlling seasonal variations |
| title_fullStr | Modelling Arctic lower-tropospheric ozone: processes controlling seasonal variations |
| title_full_unstemmed | Modelling Arctic lower-tropospheric ozone: processes controlling seasonal variations |
| title_short | Modelling Arctic lower-tropospheric ozone: processes controlling seasonal variations |
| title_sort | modelling arctic lower tropospheric ozone processes controlling seasonal variations |
| url | https://acp.copernicus.org/articles/25/8355/2025/acp-25-8355-2025.pdf |
| work_keys_str_mv | AT wgong modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT srbeagley modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT ktoyota modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT hskov modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT jhchristensen modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT alupu modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT dpendlebury modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT jzhang modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT uim modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT ykanaya modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT asaizlopez modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT rsommariva modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT rsommariva modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT peffertz modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT peffertz modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT jwhalfacre modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT njepsen modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT rkivi modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT tkkoenig modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT kmuller modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT cnordstrøm modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT ipetropavlovskikh modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT ipetropavlovskikh modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT pbshepson modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT wrsimpson modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT ssolberg modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT rmstaebler modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT dwtarasick modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT rvanmalderen modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations AT mvestenius modellingarcticlowertroposphericozoneprocessescontrollingseasonalvariations |