Limitations in representation of physical processes prevent successful simulation of PM<sub>2.5</sub> during KORUS-AQ
<p>High levels of fine particulate matter (<span class="inline-formula">PM<sub>2.5</sub></span>) pollution in East Asia often exceed local air quality standards. Observations from the Korea–United States Air Quality (KORUS-AQ) field campaign in May and June 20...
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2022-06-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://acp.copernicus.org/articles/22/7933/2022/acp-22-7933-2022.pdf |
| _version_ | 1818214198170091520 |
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| author | K. R. Travis J. H. Crawford G. Chen C. E. Jordan C. E. Jordan B. A. Nault H. Kim J. L. Jimenez P. Campuzano-Jost J. E. Dibb J.-H. Woo Y. Kim S. Zhai X. Wang E. E. McDuffie G. Luo F. Yu S. Kim I. J. Simpson D. R. Blake L. Chang M. J. Kim |
| author_facet | K. R. Travis J. H. Crawford G. Chen C. E. Jordan C. E. Jordan B. A. Nault H. Kim J. L. Jimenez P. Campuzano-Jost J. E. Dibb J.-H. Woo Y. Kim S. Zhai X. Wang E. E. McDuffie G. Luo F. Yu S. Kim I. J. Simpson D. R. Blake L. Chang M. J. Kim |
| author_sort | K. R. Travis |
| collection | DOAJ |
| description | <p>High levels of fine particulate matter (<span class="inline-formula">PM<sub>2.5</sub></span>) pollution in East Asia often exceed local air quality standards. Observations from the
Korea–United States Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through
a combination of long-range transport and favorable meteorological conditions that enhanced local production of <span class="inline-formula">PM<sub>2.5</sub></span>. Atmospheric models often have difficulty simulating <span class="inline-formula">PM<sub>2.5</sub></span> chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate <span class="inline-formula">PM<sub>2.5</sub></span> composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by <span class="inline-formula">−</span>64 % but overestimates nitrate by <span class="inline-formula">+</span>36 %. The largest underestimate in sulfate occurs during the pollution event, for which models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by <span class="inline-formula">+</span>100 % against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of 5 increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape, resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as <span class="inline-formula">NH<sub>3</sub></span> could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by <span class="inline-formula">NO<sub>2</sub></span> hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in <span class="inline-formula">N<sub>2</sub>O<sub>5</sub></span> hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by <span class="inline-formula">NO</span>. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model's inability to simulate the buildup of <span class="inline-formula">PM<sub>2.5</sub></span> during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of <span class="inline-formula">SO<sub>2</sub></span> is added to the model, which previously only considered aqueous production of sulfate from <span class="inline-formula">SO<sub>2</sub></span> in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the <span class="inline-formula">SO<sub>2</sub></span> simulation, implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to <span class="inline-formula">PM<sub>2.5</sub></span>. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of <span class="inline-formula">SO<sub>2</sub></span> decreases the fraction of <span class="inline-formula">PM<sub>2.5</sub></span> attributable to long-range transport from 66 % to 54 %. Locally produced sulfate increased from 1 % to 25 % of locally produced <span class="inline-formula">PM<sub>2.5</sub></span>, implying that local emissions controls could have a larger effect than previously thought. However, this additional uptake of <span class="inline-formula">SO<sub>2</sub></span> is coupled to the model nitrate prediction, which affects the aerosol liquid water abundance and chemistry driving sulfate–nitrate–ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of <span class="inline-formula">SO<sub>2</sub></span> to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and this results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate <span class="inline-formula">+</span> nitrate <span class="inline-formula">+</span> ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on <span class="inline-formula">PM<sub>2.5</sub></span> in South Korea to ensure continued air quality improvements.</p> |
| first_indexed | 2024-12-12T06:16:22Z |
| format | Article |
| id | doaj.art-9f84fd0588d74363ae04242ed44a6cbe |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-12-12T06:16:22Z |
| publishDate | 2022-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-9f84fd0588d74363ae04242ed44a6cbe2022-12-22T00:35:01ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242022-06-01227933795810.5194/acp-22-7933-2022Limitations in representation of physical processes prevent successful simulation of PM<sub>2.5</sub> during KORUS-AQK. R. Travis0J. H. Crawford1G. Chen2C. E. Jordan3C. E. Jordan4B. A. Nault5H. Kim6J. L. Jimenez7P. Campuzano-Jost8J. E. Dibb9J.-H. Woo10Y. Kim11S. Zhai12X. Wang13E. E. McDuffie14G. Luo15F. Yu16S. Kim17I. J. Simpson18D. R. Blake19L. Chang20M. J. Kim21NASA Langley Research Center, Hampton, VA, USANASA Langley Research Center, Hampton, VA, USANASA Langley Research Center, Hampton, VA, USANASA Langley Research Center, Hampton, VA, USANational Institute of Aerospace, Hampton, VA, USACenter for Aerosol and Cloud Chemistry, Aerodyne Research Inc., 45 Manning Road, Billerica, MA, USADepartment of Environmental Health Sciences, Graduate School of Public Health, Seoul National University, Seoul 08826, KoreaCooperative Institute for Research in the Environmental Sciences, University of Colorado, Boulder, Colorado, USACooperative Institute for Research in the Environmental Sciences, University of Colorado, Boulder, Colorado, USAEarth System Research Center, University of New Hampshire, Durham, NH, USADepartment of Civil and Environmental Engineering, Konkuk University, Seoul, Republic of KoreaEnergy, Climate, and Environment (ECE) Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, AustriaJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USASchool of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong SAR, ChinaDepartment of Energy, Environmental, and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USAAtmospheric Sciences Research Center, University at Albany, Albany, NY, USAAtmospheric Sciences Research Center, University at Albany, Albany, NY, USADepartment of Earth System Science, University of California, Irvine, Irvine, CA, USADepartment of Chemistry, University of California, Irvine, California, USADepartment of Chemistry, University of California, Irvine, California, USAAir Quality Research Division, National Institute of Environmental Research, Incheon, Republic of KoreaDivision of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA<p>High levels of fine particulate matter (<span class="inline-formula">PM<sub>2.5</sub></span>) pollution in East Asia often exceed local air quality standards. Observations from the Korea–United States Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of <span class="inline-formula">PM<sub>2.5</sub></span>. Atmospheric models often have difficulty simulating <span class="inline-formula">PM<sub>2.5</sub></span> chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate <span class="inline-formula">PM<sub>2.5</sub></span> composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by <span class="inline-formula">−</span>64 % but overestimates nitrate by <span class="inline-formula">+</span>36 %. The largest underestimate in sulfate occurs during the pollution event, for which models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by <span class="inline-formula">+</span>100 % against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of 5 increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape, resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as <span class="inline-formula">NH<sub>3</sub></span> could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by <span class="inline-formula">NO<sub>2</sub></span> hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in <span class="inline-formula">N<sub>2</sub>O<sub>5</sub></span> hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by <span class="inline-formula">NO</span>. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model's inability to simulate the buildup of <span class="inline-formula">PM<sub>2.5</sub></span> during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of <span class="inline-formula">SO<sub>2</sub></span> is added to the model, which previously only considered aqueous production of sulfate from <span class="inline-formula">SO<sub>2</sub></span> in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the <span class="inline-formula">SO<sub>2</sub></span> simulation, implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to <span class="inline-formula">PM<sub>2.5</sub></span>. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of <span class="inline-formula">SO<sub>2</sub></span> decreases the fraction of <span class="inline-formula">PM<sub>2.5</sub></span> attributable to long-range transport from 66 % to 54 %. Locally produced sulfate increased from 1 % to 25 % of locally produced <span class="inline-formula">PM<sub>2.5</sub></span>, implying that local emissions controls could have a larger effect than previously thought. However, this additional uptake of <span class="inline-formula">SO<sub>2</sub></span> is coupled to the model nitrate prediction, which affects the aerosol liquid water abundance and chemistry driving sulfate–nitrate–ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of <span class="inline-formula">SO<sub>2</sub></span> to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and this results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate <span class="inline-formula">+</span> nitrate <span class="inline-formula">+</span> ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on <span class="inline-formula">PM<sub>2.5</sub></span> in South Korea to ensure continued air quality improvements.</p>https://acp.copernicus.org/articles/22/7933/2022/acp-22-7933-2022.pdf |
| spellingShingle | K. R. Travis J. H. Crawford G. Chen C. E. Jordan C. E. Jordan B. A. Nault H. Kim J. L. Jimenez P. Campuzano-Jost J. E. Dibb J.-H. Woo Y. Kim S. Zhai X. Wang E. E. McDuffie G. Luo F. Yu S. Kim I. J. Simpson D. R. Blake L. Chang M. J. Kim Limitations in representation of physical processes prevent successful simulation of PM<sub>2.5</sub> during KORUS-AQ Atmospheric Chemistry and Physics |
| title | Limitations in representation of physical processes prevent successful simulation of PM<sub>2.5</sub> during KORUS-AQ |
| title_full | Limitations in representation of physical processes prevent successful simulation of PM<sub>2.5</sub> during KORUS-AQ |
| title_fullStr | Limitations in representation of physical processes prevent successful simulation of PM<sub>2.5</sub> during KORUS-AQ |
| title_full_unstemmed | Limitations in representation of physical processes prevent successful simulation of PM<sub>2.5</sub> during KORUS-AQ |
| title_short | Limitations in representation of physical processes prevent successful simulation of PM<sub>2.5</sub> during KORUS-AQ |
| title_sort | limitations in representation of physical processes prevent successful simulation of pm sub 2 5 sub during korus aq |
| url | https://acp.copernicus.org/articles/22/7933/2022/acp-22-7933-2022.pdf |
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