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> Publications for KORUS-AQ
Publication Citation
Lennartson, E.
,
et al.
(2018),
Diurnal variation of aerosol optical depth and PM2.5 in South Korea: a synthesis from AERONET, satellite (GOCI), KORUS-AQ observation, and the WRF-Chem model
,
Atmos. Chem. Phys., 18
, 15125-15144, doi:10.5194/acp-18-15125-2018.
Marshak, A.
,
et al.
(2023),
Aerosol Properties in Cloudy Environments from Remote Sensing Observations
,
Bull. Am. Meteorol. Soc., 102
, E2177-E2197, doi:10.1175/BAMS-D-20-0225.1.
Miller, D.
, and
W. H. Brune
(2022),
Investigating the Understanding of Oxidation Chemistry Using 20 Years of Airborne OH and HO2 Observations
,
J. Geophys. Res., 127
, e2021JD035368, doi:10.1029/2021JD035368.
Miyazaki, K.
,
et al.
(2019),
Balance of Emission and Dynamical Controls on Ozone During the Korea-United States Air Quality Campaign From Multiconstituent Satellite Data Assimilation
,
J. Geophys. Res.
.
Nault, B.
,
et al.
(2018),
Secondary organic aerosol production from local emissions dominates the organic aerosol budget over Seoul, South Korea, during KORUS-AQ
,
Atmos. Chem. Phys., 18
, 17769-17800, doi:10.5194/acp-18-17769-2018.
Nault, B.
,
et al.
(2021),
Secondary organic aerosols from anthropogenic volatile organic compounds contribute substantially to air pollution mortality
,
Atmos. Chem. Phys., 21
, 11201-11224, doi:10.5194/acp-21-11201-2021.
Oak, Y. J.,
et al.
(2019),
Evaluation of simulated O3 production efficiency during the KORUS-AQ campaign: Implications for anthropogenic NOx emissions in Korea
,
Elem Sci Anth, 7
, 56, doi:10.1525/elementa.394.
Oak, Y. J.,
et al.
(2022),
Evaluation of Secondary Organic Aerosol (SOA) Simulations for Seoul, Korea
,
J. Adv. Modeling Earth Syst.
.
Park, R.
,
et al.
(2021),
Multi-model intercomparisons of air quality simulations for the KORUS-AQ campaign
,
Elementa: Science of the Anthropocene, 9
, doi:10.1525/elementa.2021.00139.
Peterson, D. A.,
et al.
(2020),
Meteorology influencing springtime air quality, pollution transport, and visibility in Korea
,
air quality, pollution transport, and visibility in Korea. Elem Sci, 7
, 57, doi:10.1525/elementa.395.
Romer, P.
,
et al.
(2018),
Cite This: Environ. Sci. Technol. 2018, 52, 13738−13746 pubs.acs.org/est Constraints on Aerosol Nitrate Photolysis as a Potential Source of HONO and NOx
,
Environ. Sci. Technol.
, doi:10.1021/acs.est.8b03861.
Schroeder, J. R.
,
et al.
(2020),
Observation-based modeling of ozone chemistry in the Seoul metropolitan area during the Korea-United States Air Quality Study (KORUS-AQ)
,
Elem Sci Anth, 8
, doi:10.1525/elementa.400.
SimpsonA, I. J.,
et al.
(2022),
CFC-11 measurements in China, Nepal, Pakistan, Saudi Arabia and South Korea (1998–2018): Urban, landfill fire and garbage burning sources
,
Environmental Chemistry, 18
, 370-392, doi:10.1071/EN21139.
Souri, A.
,
et al.
(2020),
An inversion of NOx and non-methane volatile organic compound (NMVOC) emissions using satellite observations during the KORUS-AQ campaign and implications for surface ozone over East Asia
,
Atmos. Chem. Phys., 20
, 9837-9854, doi:10.5194/acp-20-9837-2020.
Souri, A.
,
et al.
(2020),
Revisiting the effectiveness of HCHO/NO2 ratios for inferring ozone sensitivity to its precursors using high resolution airborne remote sensing observations in a high ozone episode during the KORUS-AQ campaign
,
Atmos. Environ., 224
, 117341, doi:10.1016/j.atmosenv.2020.117341.
Star, T.,
et al.
(2018),
4STAR_codes: 4STAR processing codes
,
Zenodo
, doi:10.5281/zenodo.1492912.
Sullivan, J.
,
et al.
(2019),
Taehwa Research Forest: a receptor site for severe domestic pollution events in Korea during 2016
,
Atmos. Chem. Phys., 19
, 5051-5067, doi:10.5194/acp-19-5051-2019.
Tang, W.,
et al.
(2019),
Source Contributions to Carbon Monoxide Concentrations During KORUS‐AQ Based on CAM‐chem Model Applications
,
J. Geophys. Res.
.
Tang, W.,
et al.
(2020),
Assessing Measurements of Pollution in the Troposphere (MOPITT) carbon monoxide retrievals over urban versus non-urban regions
,
Atmos. Meas. Tech., 13
, 1337-1356, doi:10.5194/amt-13-1337-2020.
Tang, W.,
et al.
(2021),
Assessing sub-grid variability within satellite pixels over urban regions using airborne mapping spectrometer measurements
,
Atmos. Meas. Tech., 14
, 4639-4655, doi:10.5194/amt-14-4639-2021.
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