An aerosol model optimized for northeast Asia is updated with the inversion data from the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-northeast (NE) Asia campaign which was conducted during spring from March to May 2012. This updated aerosol model was then applied to a single visible channel algorithm to retrieve aerosol optical depth (AOD) from a Meteorological Imager (MI) on-board the geostationary meteorological satellite, Communication, Ocean, and Meteorological Satellite (COMS). This model plays an important role in retrieving accurate AOD from a single visible channel measurement. For the single-channel retrieval, sensitivity tests showed that perturbations by 4 % (0.926 ± 0.04) in the assumed single scattering albedo (SSA) can result in the retrieval error in AOD by over 20 %. Since the measured reflectance at the top of the atmosphere depends on both AOD and SSA, the overestimation of assumed SSA in the aerosol model leads to an underestimation of AOD. Based on the AErosol RObotic NETwork (AERONET) inversion data sets obtained over East Asia before 2011, seasonally analyzed aerosol optical properties (AOPs) were categorized by SSAs at 675 nm of 0.92 ± 0.035 for spring (March, April, and May). After the DRAGON-NE Asia campaign in 2012, the SSA during spring showed a slight increase to 0.93 ± 0.035. In terms of the volume size distribution, the mode radius of coarse particles was increased from 2.08 ± 0.40 to 2.14 ± 0.40. While the original aerosol model consists of volume size distribution and refractive indices obtained before 2011, the new model is constructed by using a total data set after the DRAGON-NE Asia campaign. The large volume of data in high spatial resolution from this intensive campaign can be used to improve the representative aerosol model for East Asia. Accordingly, the new AOD data sets retrieved from a single-channel algorithm, which uses a precalculated look-up table (LUT) with the new aerosol model, show an improved correlation with the measured AOD during the DRAGON-NE Asia campaign. The correlation between the new AOD and AERONET value shows a regression slope of 1.00, while the comparison of the original AOD data retrieved using the original aerosol model shows a slope of 1.08. The change of y-offset is not significant, and the correlation coefficients for the comparisons of the original and new AOD are 0.87 and 0.85, respectively. The tendency of the original aerosol model to overestimate the retrieved AOD is significantly improved by using the SSA values in addition to size distribution and refractive index obtained using the new model.

Ambient measurements of elemental species concentrations were made using an online elemental monitor at an air pollution monitoring station in Gwangju, Korea to evaluate the performance of the monitor for near–real time PM2.5 elemental monitoring and identify possible sources of the observed elements. This study also demonstrates the utility of integrating hourly elemental data with the meteorological data to better understand the sources of elements. Good agreement between the online and filter–based measurements was obtained for the elements studied, with an R2 of 0.73–0.97 and regression slopes of 0.84–2.37, suggesting the potential use of the online monitor to observe temporal variations in anthropogenic aerosol particles. Atmospheric element concentration levels studied were 2–20 times greater than their background levels when pollution plumes coming from industrial areas had impacted the site. Examination of the elements data revealed several short spikes of elements that are associated with local industrial emissions and road dusts. For the haze episodes observed over the study period, the element K was significantly influenced by biomass burning emissions with some impacts from soil dusts and industrial activities. Based on the wind direction and wind speed data, As/Se, Se/SO42−, and correlations among Se, As, Pb, SO2, and SO42−, it is suggested that the observed As and Se were significantly impacted by local anthropogenic sources and long–range transport of aerosols, rather than local coal combustion or coke emissions. Conditional probability functions were applied to identify likely local emission source locations of the elements observed at the site, indicating that the elements contributions were from the southwest and northeast directions, where two industrial areas and an express highway are located. Results from principal component analysis indicate that the observed concentrations of the element species were likely attributed to road dust/local industrial emissions, oil combustion, and metal processing.

A new dust detection algorithm is developed by combining the results of multiple dust detection methods using IR channels onboard the MODerate resolution Imaging Spectroradiometer (MODIS). Brightness Temperature Difference (BTD) between two wavelength channels has been used widely in previous dust detection methods. However, BTD methods have limitations in identifying the offset values of the BTD to discriminate clear-sky areas. The current algorithm overcomes the disadvantages of previous dust detection methods by considering the Brightness Temperature Ratio (BTR) values of the dual wavelength channels with 30-day composite, the optical properties of the dust particles, the variability of surface properties, and the cloud contamination. Therefore, the current algorithm shows improvements in detecting the dust loaded region over land during daytime. Finally, the confidence index of the current dust algorithm is shown in 10×10pixels of the MODIS observations. From January to June, 2006, the results of the current algorithm are within 64 to 81% of those found using the fine mode fraction (FMF) and aerosol index (AI) from the MODIS and Ozone Monitoring Instrument (OMI). The agreement between the results of the current algorithm and the OMI AI over the non-polluted land also ranges from 60 to 67% to avoid errors due to the anthropogenic aerosol. In addition, the developed algorithm shows statistically significant results at four AErosol RObotic NETwork (AERONET) sites in East Asia.

Surface erythemal UV radiation is mainly affected by total column ozone, aerosols, clouds, and solar zenith angle. The effect of ozone on the surface UV radiation has been explored many times in the previous studies due to the decrease of ozone layer. In this study, we calculated the effect of aerosols on the surface UV radiation as well as that of ozone using data acquired from Ozone Monitoring Instrument (OMI). First, ozone, aerosol optical depth (AOD), and surface erythemal UVB radiation measured from satellite are compared with those from ground measurements. The results showed that the comparison for ozone was good with r 2 of 0.92. For aerosol, there was difference between satellite measurements and surface measurements due to the insufficient information on aerosol in the retrieval algorithm. The r 2 for surface erythemal UV radiation was high (∼0.94) but satellite measurements showed about 30% larger values than surface measurements on average by not considering the effect of absorbing aerosols in the retrieval process from satellite measurements. Radiative amplification factor (RAF) is used to access the effect of ozone and aerosol quantitatively. RAF for ozone was 0.97∼1.49 with solar zenith angle. To evaluate the effect of aerosol on the surface UV radiation, only clear-sky pixel data were used and solar zenith angle and total column amount of ozone were fixed. Also, RAF for aerosol was assessed according to the single scattering albedo (SSA) of aerosols. The results showed that RAF for aerosol with smaller SSA (< 0.90) was larger than that for with larger SSA (> 0.90). The RAF for aerosol was 0.09∼0.22 for the given conditions which was relatively small compared to that for ozone. However, considering the fact that aerosol optical depth can change largely in time and space while the total column amount of ozone does not change very much, it needs to include the effect of aerosol to predict the variations of surface UV radiation more correctly.

Mercury is one of the most hazardous air pollutants. Recently, mercury has been a concern in domestic and overseas because it has lethal toxicity, long distance transport, persistence and bioaccumulation in the environment. Stationary combustion sources such as coal-fired power plants, waste incinerators, and cement kilns are the major sources of mercury emissions. The objectives of this study were to measure the concentration for mercury from coal-fired power plants and to calculate emission factor to estimate its emission. The results showed that the mercury concentrations in the flue gas were 1.63 similar to 3.03 mg/Sm-3 in anthracite-fired power plants (average 2.32 mg/Sm3) and 1.95 similar to 3.33 mg/Sm3 in bituminous-fired power plants (average 2.6 mg/Sm3). Mercury emission factor was estimated as 25.74 mg/ton for anthracite-fired power plants and 12.48 mg/ton for bituminous-fired power plants. Because actual measurements are limited in quantity, it is desirable to refine our estimates by extending the actual measurements.

The unequivocal risk of climate change, the weakness of energy security, and the problem of air quality will be possibly accelerated by the same reason, the enhanced fossil fuel dependancy in the future. It is obvious that greenhouse gases and air pollutants are mainly emitted from same sources. Moreover, greenhouse gases and air pollutants have their adversed impacts on same socio-economical, and environmental sectors. With these regards, several but limited studies have emphasized on the importance of the integrated management of climate change and air quality problem. In this study, we address the current trend of energy consumption and the change of air quality condition. Also the related policies are checked out in order to reduce emissions of greenhouse gases and air pollutants in Korea. By surveying previous studies, it is shown that the cost of climate change actions can be reduced by air quality co-benefits and vis-a-versa. Also the integrated strategy for climate change and air quality is introduced in term of cost-effectiveness and co-benefit.

The effect of ozone and surface temperature on the ozone band at 9.7 pm has been investigated from radiative transfer theory together with observations in order to derive empirical methods for remotely sensing ground-ozone concentration. Simultaneous observations of satellite (MODIS Aqua; ECT 13:30) and ground-ozone at 79 stations have been used over the Seoul Metropolitan Area (SMA; 125.7-127.2 E, 37.2-37.7 N) during four ozone-warning days in the year 2003. Cloud effect on the band in the methods was filtered out based on synoptic observations. Upwelling radiance values at 9.6 mu m which have been estimated at the given ozone concentration of 327-391 DU depend on surface temperature (Ts) showing 5.52-5.78 Wm(-2)sr(-1) at Ts = 290 K, and 9.00-9.57 Wm(-2)Sr(-1) at Ts = 325 K. Thus, the partitioned contributions of ozone and temperature to intensity of ozone absorption band are 0.26 Wm(-2)sr(-1)/64 DU and 0.31 Wm(-2)sr(-1)/35 K, respectively. Here the intensity which has been used to remotely detect ground-ozone concentration from infrared satellite measurement is defined as the difference in brightness temperature between 11 pm and 9.7 mu m (i.e., T-11.97). The methods in this study have been applied to estimate ground-ozone from MODIS data in cases that there are significant correlations between the band intensity and ground-ozone. The values of estimated ozone significantly correlate (0.49-0.63) with ground observations at a significance level of 1%. For the improved methods, farther study may be required to use tropospheric ozone rather than ground-ozone, considering the variation stratospheric ozone.

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter > or = 10 microm, and ozone (O3) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km x 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of approximately 0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.

This study was carried out to understand long-range transport of using aircraft measurements for the identification of it's horizontal and vertical concentration and distribution pattern. Thirteen missions of aircraft measurements have been done around 3700'/12430' from October 1997 to November 2001. Concentrations of was 1.5~2.0 ppb in the below mixing layer, 0.6~1.1 ppb in the above mixing layer. was found to be relatively higher than marine background level, 0.08~0.2ppb, indicating the western coast being influenced by long-range transport except for the summer season. The vertical distribution of was classified into 3 groups using its vertical sounding and meteorology pattern; the first is linear decay pattern, the second is exponential decay pattern, and the last is gaussian distribution pattern in the below mixing layer, 2 patterns of linear decay and gaussian distribution patterns in the upper layer. It is founded that vertical distribution pattern is strongly dependent on meteorological condition, for example atmospheric stability and predominant air flow.