气候变化领域集成服务门户(CCPortal): Limitations in representation of physical processes prevent successful simulation of PM2.5 during KORUS-AQ

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DOI	10.5194/acp-22-7933-2022
	Limitations in representation of physical processes prevent successful simulation of PM2.5 during KORUS-AQ
	Travis, Katherine R.; Crawford, James H.; Chen, Gao; Jordan, Carolyn E.; Nault, Benjamin A.; Kim, Hwajin; Jimenez, Jose L.; Campuzano-Jost, Pedro; Dibb, Jack E.; Woo, Jung-Hun; Kim, Younha; Zhai, Shixian; Wang, Xuan; McDuffie, Erin E.; Luo, Gan; Yu, Fangqun; Kim, Saewung; Simpson, Isobel J.; Blake, Donald R.; Chang, Limseok; Kim, Michelle J.
发表日期	2022
ISSN	1680-7316
EISSN	1680-7324
起始页码	7933
结束页码	7958
卷号	22 期号:12 页码:26
英文摘要	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 longrange 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. At the surface, the model underestimates sulfate by -64 % but overestimates nitrate by +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 +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 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 25 % of locally produced PM2.5, implying that local emissions controls could 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 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 + 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.
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000813039500001
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/273736
作者单位	National Aeronautics & Space Administration (NASA); NASA Langley Research Center; National Institute for Aerospace; Aerodyne Research; Seoul National University (SNU); University of Colorado System; University of Colorado Boulder; University System Of New Hampshire; University of New Hampshire; Konkuk University; International Institute for Applied Systems Analysis (IIASA); Harvard University; City University of Hong Kong; Washington University (WUSTL); State University of New York (SUNY) System; State University of New York (SUNY) Albany; University of California System; University of California Irvine; University of California System; University of California Irvine; National Institute of Environmental Research (NIER), Republic of Korea; California Institute of Technology
推荐引用方式 GB/T 7714	Travis, Katherine R.,Crawford, James H.,Chen, Gao,et al. Limitations in representation of physical processes prevent successful simulation of PM2.5 during KORUS-AQ[J],2022,22(12):26.
APA	Travis, Katherine R..,Crawford, James H..,Chen, Gao.,Jordan, Carolyn E..,Nault, Benjamin A..,...&Kim, Michelle J..(2022).Limitations in representation of physical processes prevent successful simulation of PM2.5 during KORUS-AQ.ATMOSPHERIC CHEMISTRY AND PHYSICS,22(12),26.
MLA	Travis, Katherine R.,et al."Limitations in representation of physical processes prevent successful simulation of PM2.5 during KORUS-AQ".ATMOSPHERIC CHEMISTRY AND PHYSICS 22.12(2022):26.