<p><strong>Abstract.</strong> An intensive field campaign was conducted in a downwind area of the Asian continental outflow (Daejeon, Korea) during winter 2014 to characterize the spectral optical properties of severe haze and Asian dust episodes. High concentrations of PM<sub>10</sub> (particulate matter with a diameter ≤ 10 µm) and light scattering coefficients at 550 nm, σ<sub><i>s,550</i></sub>, were observed during a long-range transport (LRT) haze episode (PM<sub>10</sub> = 163.9 ± 25.0 μg/m<sup>3</sup>; σ<sub><i>s,550</i></sub> = 503.4 ± 60.5 Mm<sup>−1</sup>) and Asian dust episode (PM<sub>10</sub> = 211.3 ± 57.5 μg/m<sup>3</sup>; σ<sub><i>s,550</i></sub> = 560.9 ± 151 Mm<sup>−1</sup>). During the LRT haze episode, no significant change in the relative contribution of PM<sub>2.5</sub> (particulate matter with a diameter ≤ 2.5 µm) chemical components was observed as particles accumulated under stagnant atmospheric conditions (January 13−17, 2014), suggesting that the increase in PM<sub>2.5</sub> mass concentration was caused mainly by the accumulation of LRT pollutants. On the other hand, a gradual decrease in Ångström exponent (<i>Å</i>), gradual increase in single scattering albedo (ω) and mass scattering efficiency (MSE) were observed during the stagnant period, possibly due to an increase in particle size. During the Asian dust episode, a low PM<sub>2.5</sub>/PM<sub>10</sub> ratio and <i>Å</i>(450/700) were observed with average values of 0.59 ± 0.06 and 1.08 ± 0.14, respectively, which were higher than those during the LRT haze episode (0.75 ± 0.06 and 1.39 ± 0.05, respectively), indicating that PM<sub>2.5</sub>/PM<sub>10</sub> mass ratios and <i>Å</i>(450/700) can be used as tracers to distinguish aged LRT haze and Asian dust under the Asian continental outflow.</p>

Abstract. To validate the Geostationary Environment Monitoring Spectrometer (GEMS), the GEMS Map of Air Pollution (GMAP) campaign was conducted during 2020–2021 by integrating Pandora Asia Network, aircraft, and in situ measurements. In the present study, GMAP-2020 measurements were applied to evaluate urban air quality and explore the synergy of Pandora column (PC) NO2 measurements and surface in situ (SI) NO2 measurements for Seosan, South Korea, where large point source (LPS) emissions are densely clustered. Due to the difficulty of interpreting the effects of LPS emissions on air quality downwind of Seosan using SI monitoring networks alone, we explored the combined analysis of both PC-NO2 and SI-NO2 measurements. Agglomerative hierarchical clustering using vertical meteorological variables combined with PC-NO2 and SI-NO2 yielded three distinct conditions: synoptic wind-dominant (SD), mixed (MD), and local wind-dominant (LD). These results suggest meteorology-dependent correlations between PC-NO2 and SI-NO2. Overall, yearly daytime mean (11:00–17:00 KST) PC-NO2 and SI-NO2 statistical data showed good linear correlations (R=∼0.73); however, the differences in correlations were largely attributed to meteorological conditions. SD conditions characterized by higher wind speeds and advected marine boundary layer heights suppressed fluctuations in both PC-NO2 and SI-NO2, driving a uniform vertical NO2 structure with higher correlations, whereas under LD conditions, LPS plumes were decoupled from the surface or were transported from nearby cities, weakening correlations through anomalous vertical NO2 gradients. The discrepancies suggest that using either PC-NO2 or SI-NO2 observations alone involves a higher possibility of uncertainty under LD conditions or prevailing transport processes. However, under MD conditions, both pollution ventilation due to high surface wind speeds and daytime photochemical NO2 loss contributed to stronger correlations through a decline in both PC-NO2 and SI-NO2 towards noon. Thus, Pandora Asia Network observations collected over 13 Asian countries since 2021 can be utilized for detailed investigation of the vertical complexity of air quality, and the conclusions can be also applied when performing GEMS observation interpretation in combination with SI measurements.

This study investigates the uncertainties associated with estimates of the long-range transport SO2 (LRT-SO2) flow rate calculated hourly using Geostationary Environment Monitoring Spectrometer (GEMS) synthetic radiances. These radiances were simulated over the Korean Peninsula and the surrounding regions using inputs from the GEOS-Chem model for January, April, July, and October 2016. The LRT-SO2 calculation method, which requires SO2 vertical column densities, wind data, and planetary boundary layer information, was used to quantify the effects of the SO2 slant column density (SCD) retrieval error and uncertainties in wind data on the accuracy of the LRT-SO2 estimates. The effects were estimated for simulations of three anthropogenic and three volcanic SO2 transport events. When there were no errors in the GEMS SO2 SCD and wind data, the average true LRT-SO2 flow rates (standard deviation) and those calculated for these events were 1.17 (± 0.44) and 1.21 (±0.44) Mg/h, respectively. However, the averages of the true LRT-SO2 flow rates and those calculated for the three anthropogenic (volcanic) SO2 events were 0.61 (1.17) and 0.64 (1.20) Mg/h, respectively, in the presence of GEMS SO2 SCD errors. In the presence of both errors in the GEMS SO2 SCD and wind data, the averages of the true LRT-SO2 flow rates and those calculated for the three anthropogenic (volcanic) SO2 events were 0.61 (1.17) and 0.61 (1.04) Mg/h, respectively. This corresponds to differences of 2.1% to 23.1% between the simulated and true mean LRT-SO2 flow rates. The mean correlation coefficient (R), intercept, and slope between the true and simulated LRT-SO2 flow rates were 0.51, 0.43, and 0.45 for the six simulated events, respectively. This study demonstrates that SO2 SCD accuracy is an important factor in improving estimates of LRT-SO2 flow rates.

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Abstract. The Geostationary Environmental Monitoring Spectrometer (GEMS) is a UV–visible spectrometer onboard the GEO-KOMPSAT-2B satellite launched into geostationary orbit in February 2020. To evaluate GEMS NO2 column data, comparison was carried out using NO2 vertical column density (VCD) measured using direct-sunlight observations by the Pandora spectrometer system at four sites in Seosan, South Korea, during November 2020 to January 2021. Correlation coefficients between GEMS and Pandora NO2 data at four sites ranged from 0.35 to 0.48, with root mean square errors (RMSEs) from 4.7 × 1015 molec. cm-2 to 5.5 × 1015 molec. cm-2 for cloud fraction (CF) < 0.7. Higher correlation coefficients of 0.62–0.78 with lower RMSEs from 3.3 × 1015 molec. cm-2 to 4.3 × 1015 molec. cm-2 were found with CF < 0.3, indicating the higher sensitivity of GEMS to atmospheric NO2 in less-cloudy conditions. Overall, GEMS NO2 column data tend to be lower than those of Pandora due to differences in representative spatial coverage, with a large negative bias under high-CF conditions. With correction for horizontal representativeness in Pandora measurement coverage, the correlation coefficients range from 0.69 to 0.81 with RMSEs from 3.2 × 1015 molec. cm-2 to 4.9 × 1015 molec. cm-2 were achieved for CF < 0.3, showing the better correlation with the correction than that without the correction.