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DOI10.1016/j.atmosenv.2020.118182
Characteristics of HONO and its impact on O3 formation in the Seoul Metropolitan Area during the Korea-US Air Quality study
Gil J.; Kim J.; Lee M.; Lee G.; Ahn J.; Lee D.S.; Jung J.; Cho S.; Whitehill A.; Szykman J.; Lee J.
发表日期2021
ISSN1352-2310
卷号247
英文摘要Photolysis of nitrous acid (HONO) is recognized as an early-morning source of OH radicals in the urban air. During the Korea–US Air Quality (KORUS-AQ) campaign, HONO was measured using quantum cascade - tunable infrared laser differential absorption spectrometer (QC-TILDAS) at Olympic Park in Seoul from 17 May, 2016 to 14 June, 2016. The HONO concentration was in the range of 0.07–3.46 ppbv, with an average of 0.93 ppbv. Moreover, it remained high from 00:00–05:00 LST. During this time, the mean concentration was higher during the high-O3 episodes (1.82 ppbv) than the non-episodes (1.20 ppbv). In the morning, the OH radicals that were produced from HONO photolysis were 50% higher (0.95 pptv) during the high-O3 episodes than the non-episodes. Diurnal variations in HOx and O3 concentrations were simulated by the F0AM model, which revealed a difference of ~20 ppbv in the daily maximum O3 concentrations between the high-O3 episodes and non-episodes. Furthermore, the HONO concentration increased with an increase in relative humidity (RH) up to 80%; the highest HONO was associated with the top 10% NO2 in each RH group, confirming that NO2 is one of the main precursors of HONO. At night, the conversion ratio of NO2 to HONO was estimated to be 0.88×10−2 h−1; this ratio was found to increase with an increase in RH. The Aitken mode particles (30–120 nm), which act as catalyst surfaces, exhibited a similar tendency with a conversion ratio that increased along with RH, indicating the coupling of surfaces with HONO conversion. Using an artificial neural network (ANN) model, HONO concentrations were successfully simulated with measured variables (r2 = 0.66 as an average of five models). Among these variables, NOx, aerosol surface area, and RH were found to be the main factors affecting the ambient HONO concentrations. The results reveal that RH facilitates the conversion of NO2 to HONO by constraining the availability of aerosol surfaces. This study demonstrates the coupling of HONO with the HOx-O3 cycle in the Seoul Metropolitan Area (SMA) and provides practical evidence of the heterogeneous formation of HONO by employing the ANN model. © 2021 The Author(s)
英文关键词Aerosols; Air quality; Free radicals; Metropolitan area networks; Neural networks; Nitrogen oxides; Photolysis; Aerosol surface area; Artificial neural network models; Differential absorption; Diurnal variation; Heterogeneous formation; Mean concentrations; Seoul metropolitan area; Tunable infrared laser; Inorganic acids
语种英语
来源期刊Atmospheric Environment
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/169025
作者单位Department of Earth and Environmental Science, Korea University, Seoul, South Korea; Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, South Korea; National Institute of Environmental Research (NIER), Incheon, South Korea; Department of Chemistry, Yonsei University, Seoul, South Korea; Korea Research Institute of Standards and Science (KRISS), Daejeon, South Korea; Seoul Research Institute of Public Health and Environment, Seoul, South Korea; U.S, Environmental Protection Agency, Research Triangle Park, Durham, United States; School of Mechanical Engineering, Korea University of Technology and Education, Cheonan, South Korea
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Gil J.,Kim J.,Lee M.,et al. Characteristics of HONO and its impact on O3 formation in the Seoul Metropolitan Area during the Korea-US Air Quality study[J],2021,247.
APA Gil J..,Kim J..,Lee M..,Lee G..,Ahn J..,...&Lee J..(2021).Characteristics of HONO and its impact on O3 formation in the Seoul Metropolitan Area during the Korea-US Air Quality study.Atmospheric Environment,247.
MLA Gil J.,et al."Characteristics of HONO and its impact on O3 formation in the Seoul Metropolitan Area during the Korea-US Air Quality study".Atmospheric Environment 247(2021).
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