Preprints
https://doi.org/10.5194/acp-2021-946
https://doi.org/10.5194/acp-2021-946

  07 Jan 2022

07 Jan 2022

Review status: this preprint is currently under review for the journal ACP.

Limitations in representation of physical processes prevent successful simulation of PM2.5 during KORUS-AQ

Katherine R. Travis1, James H. Crawford1, Gao Chen1, Carolyn E. Jordan1,2, Benjamin A. Nault3, Hwajin Kim4, Jose L. Jimenez5, Pedro Campuzano-Jost5, Jack E. Dibb6, Jung-Hun Woo7, Younha Kim8, Shixian Zhai9, Xuan Wang10, Erin E. McDuffie11, Gan Luo12, Fangqun Yu12, Saewung Kim13, Isobel J. Simpson14, Donald R. Blake14, Limseok Chang15, and Michelle J. Kim16 Katherine R. Travis et al.
  • 1NASA Langley Research Center, Hampton, VA, USA
  • 2National Institute of Aerospace, Hampton, VA, USA
  • 3Center for Aerosol and Cloud Chemistry, Aerodyne Research Inc. 45 Manning Road Billerica, MA, USA
  • 4Department of Environmental Health Sciences, Graduate School of Public Health, Seoul National University, Seoul 08826, Korea
  • 5Cooperative Institute for Research in the Environmental Sciences, University of Colorado, Boulder, Colorado, USA
  • 6Earth System Research Center, University of New Hampshire, Durham, NH, USA
  • 7Department of Civil and Environmental Engineering, Konkuk University, Seoul, Republic of Korea
  • 8Energy, Climate, and Environment (ECE) Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
  • 9John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
  • 10City University of Hong Kong, Kowloon, HK
  • 11Department of Energy, Environmental, and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
  • 12Atmospheric Sciences Research Center, University at Albany, Albany, NY, USA
  • 13University of California, Irvine, Irvine, CA, USA
  • 14Department of Chemistry, University of California, Irvine, California, USA
  • 15Air Quality Research Division, National Institute of Environmental Research, Incheon, Republic of Korea
  • 16Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA

Abstract. High levels of fine particulate matter (PM2.5) 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 PM2.5. Atmospheric models often have difficulty simulating PM2.5 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 PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. In the surface level, the model underestimates campaign average sulfate aerosol by −64 % but overestimates nitrate aerosol by 36 %. The largest underestimate in sulfate occurs during the pollution event in conditions of high relative humidity, where models typically struggle to generate the high 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 +100 % against aircraft observations. We hypothesize that this is due to a missing sink, which we implement here as a factor of five 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 NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 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 NO. 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 PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally-produced sulfate increased from 1 % to 46 % of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 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 SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and 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 boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.

Katherine R. Travis et al.

Status: open (until 18 Feb 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Katherine R. Travis et al.

Katherine R. Travis et al.

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Short summary
The 2016 Korea United States-Air Quality (KORUS-AQ) field campaign provided a unique set of observations to improve our understanding of PM2.5 pollution in South Korea. Models typically have errors in simulating PM2.5 in this region, which is of concern for the development of control measures. We use KORUS-AQ observations to improve our understanding of the mechanisms driving PM2.5 and the implications of model errors for determining PM2.5 that is attributable to local or foreign sources.
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