HONO Measurement in Seoul during Summer 2018 and its Impact on Photochemistry

Gil, Junsu; Son, Jiyoung; Kang, Sung-Gu; Park, Joonhyoung; Lee, Meehye; Jeon, Eunmi; Shim, Mihee

doi:10.5572/kosae.2020.36.5.579

Cited by 7 publications

(5 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The average mixing ratio of HONO in winter was approximately 1.43 times higher than that in summer, and that of HNO 3 in summer was approximately 7.2 times higher than that in winter. The levels of mixing ratio of HONO in this study were higher than those observed by Chang et al (2008) in Gwangju (0.5 ppbv in spring) and those measured by Gil et al (2020) in Seoul (0.28 ppbv in summer) [14,32]. Ahn et al ( 2013) measured HNO 3 in Seoul as 0.83 ppbv, which is higher than that in this study at Daejeon in winter (0.72 ppbv) but lower than that in summer (0.1 ppbv) [33].…”

Section: Data Overviewcontrasting

confidence: 80%

“…Despite the importance of HONO in atmospheric chemistry, detailed research on the reaction mechanisms of HONO in the atmosphere is lacking. This is because the yet-to-be-identified reactions during discharge and the homogeneous and heterogeneous reaction processes have complex effects on HONO concentrations [7,13,14].…”

Section: Introductionmentioning

confidence: 99%

“…Gil et al (2020) used the parallel plate diffusion scrubber-ion chromatograph (PPDS-IC) system to measure the HNO 3 concentrations in the atmosphere [14]. In addition, the OH generation rate of HNO 3 was calculated using the Framework for 0-D Atmospheric Modeling (F0AM) model, a 0-D box model, by comparing photochemical pollution case days with non-case days according to O 3 concentration.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Study on the Formation Reactions and Conversion Mechanisms of HONO and HNO3 in the Atmosphere of Daejeon, Korea

Kim,

Lee,

Choi

et al. 2024

Atmosphere

View full text Add to dashboard Cite

Nitrogen oxides (NOX) in the atmosphere cause oxidation reactions with photochemical radicals and volatile organic compounds, leading to the accumulation of ozone (O3). NOX constitutes a significant portion of the NOy composition, with nitrous acid (HONO) and nitric acid (HNO3) following. HONO plays a crucial role in the reaction cycle of NOX and hydrogen oxides. The majority of HNO3 reduction mechanisms result from aerosolization through heterogeneous reactions, having adverse effects on humans and plants by increasing secondary aerosol concentrations in the atmosphere. The investigation of the formation and conversion mechanisms of HONO and HNO3 is important; however, research in this area is currently lacking. In this study, we observed HONO, HNO3, and their precursor gases were observed in the atmosphere using parallel-plate diffusion scrubber-ion chromatography. A 0-D box model simulated the compositional distribution of NOy in the atmosphere. The formation reactions and conversion mechanisms of HONO and HNO3 were quantified using reaction equations and reaction coefficients. Among the various mechanisms, dominant mechanisms were identified, suggesting their importance. According to the calculation results, the produce of HONO was predominantly attributed to heterogeneous reactions, excluding an unknown source. The sink processes were mainly governed by photolysis during daytime and reactions with OH radicals during nighttime. HNO3 showed dominance in its production from N2O5, and in its conversion mechanisms primarily involving aerosolization and deposition.

show abstract

Section: Data Overviewcontrasting

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Study on the Formation Reactions and Conversion Mechanisms of HONO and HNO3 in the Atmosphere of Daejeon, Korea

Kim,

Lee,

Choi

et al. 2024

Atmosphere

View full text Add to dashboard Cite

show abstract

“…Detailed information about F0AM can be found in (https://sites.google.com/site/wolfegm/models) and in previous works published elsewhere (Wolfe et al, 2016;Gil et al, 2020). When the F0AM model is run without HONO, it is not able to reproduce the concentration and diel cycle of the observed O3 (Figure 8).…”

Section: Operation and Application Of Rndv10mentioning

confidence: 99%

“…Modeling studies have also shown that the lack of NOy measurements hinder a comprehensive understanding of the heterogeneous reactions (Anderson et al, 2014;Wang et al, 2017b;Chen et al, 2018). HONO, one of the NOy species, is an early morning source of OH radicals in the urban atmosphere (Brandenburger et al, 1998;Xing et al, 2019;Alicke et al, 2002;Ryan et al, 2018;Gil et al, 2020;Xue et al, 2020). Thus, there has been a steady effort to determine the atmospheric level of HONO using various methods such as a long path absorption photometer (LOPAP) (Kleffmann et al, 2006;Xue et al, 2019), chemical ionization mass spectrometry (CIMS) (Levy et al, 2014;Roberts et al, 2010), ion chromatography (IC) (VandenBoer et al, 2014;Gil et al, 2020;Ye et al, 2016;Xu et al, 2019), and quantum cascade tunable infrared laser differential absorption spectrometry (QC-TILDAS) (Lee et al, 2011;Gil et al, 2021).…”

mentioning

confidence: 99%

Simulation Model of Reactive Nitrogen Species in an Urban Atmosphere using a Deep Neural Network: RND v1.0

Gil

Lee

Kim

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. Nitrous acid (HONO), one of the reactive nitrogen oxides (NOy), plays an important role in the formation of ozone (O3) and fine aerosols (PM2.5) in the urban atmosphere. In this study, a simulation model of Reactive Nitrogen species using Deep neural network model (RND) was constructed to calculate the HONO mixing ratios through a deep learning technique using measured variables. A Python-based Deep Neural Network (DNN) was trained, validated, and tested with HONO measurement data obtained in Seoul during the warm months from 2016 to 2019. A k-fold cross validation and test results confirmed the performance of RND v1.0 with an Index Of Agreement (IOA) of 0.79 ~ 0.89 and a Mean Absolute Error (MAE) of 0.21 ~ 0.31 ppbv. The RNDV1.0 adequately represents the main characteristics of HONO and thus, RND v1.0 is proposed as a supplementary model for calculating the HONO mixing ratio in a high- NOx environment.

show abstract

Exploring the long-term variations and high concentration episodes of peroxyacetyl nitrate in Megacity Seoul

Savic,

Gil,

Cha

et al. 2024

Atmospheric Environment

View full text Add to dashboard Cite

HONO Measurement in Seoul during Summer 2018 and its Impact on Photochemistry

Cited by 7 publications

References 27 publications

A Study on the Formation Reactions and Conversion Mechanisms of HONO and HNO3 in the Atmosphere of Daejeon, Korea

A Study on the Formation Reactions and Conversion Mechanisms of HONO and HNO3 in the Atmosphere of Daejeon, Korea

Simulation Model of Reactive Nitrogen Species in an Urban Atmosphere using a Deep Neural Network: RND v1.0

Exploring the long-term variations and high concentration episodes of peroxyacetyl nitrate in Megacity Seoul

Contact Info

Product

Resources

About