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Concentrations of ambient particulate matter (such as PM2.5 and PM10) have come to represent a serious environmental problem worldwide, causing many deaths and economic losses. Because of the detrimental effects of PM2.5 on human health, many countries and international organizations have developed and operated regional and global short-term PM2.5 prediction systems. The short-term predictability of PM2.5 (and PM10) is determined by two main factors: the performance of the air quality model and the accuracy of the initial states. While specifically focusing on the latter factor, this study attempts to demonstrate how information from ‘classical’ ground observation networks, a ‘state-of-the-art’ geostationary (GEO) satellite sensor, and an advanced air quality modeling system can be synergistically combined to improve short-term PM2.5 predictability over South Korea. Such a synergistic combination of information can effectively overcome the major obstacle of scarcity of information, which frequently occurs in PM2.5 prediction systems using low Earth orbit (LEO) satellite-borne observations. This study first presents that the scarcity of information is mainly associated with cloud masking, sun-glint effect, and ill-location of satellite-borne data, and it then demonstrates that an advanced air quality modeling system equipped with synergistically-combined information can achieve substantially improved performances, producing enhancements of approximately 10%, 17%, 49%, and 19% in the predictability of PM2.5 over South Korea in terms of IOA (index of agreement), R (correlation coefficient), MB (mean biases), and HR (hit rate), respectively, compared to PM2.5 prediction systems using only LEO satellite-derived observations.

With the increasing importance of monitoring and verifying urban CO2 concentrations to mitigate carbon emissions from cities, a high-resolution ground networks of low-cost CO2 sensors are emerging that have a price advantage over existing high-cost sensors. This study develops a low-cost CO2 instrument called the Seoul National University CO2 Measurement (SNUCO2M) to monitor and analyze intra-city CO2 concentrations over Seoul, Korea. The first step of establishing this low-cost CO2 sensor network involved installing the SNUCO2M at the Yongsan Building (YSB; 113 m MASL) and Namsan Seoul Tower-High (NSTH; 385 m MASL) on October 18, 2018 and July 8, 2019, respectively. For comparison with the SNUCO2M, we utilized CO2 concentrations measured by the Picarro instrument (high-cost CO2 sensor) at Gwanak Mountain (GWA) background measurement site and the lower part of the NST (NSTL). The initial CO2 measurements from the SNUCO2M, show that 1) the SNUCO2M has a 0.71% maximum error range and is sufficient to measure urban atmospheric CO2 concentrations; and 2) the SNUCO2M captures 26.92 and 20.30 ppm of Seoul’s summer and winter time CO2 enhancement compared to the GWA background site. Our results suggest that the low-cost sensors such as SNUCO2M successfully detect urban CO2 characteristics over the megacity and has great potential to replace high-cost sensors with cost and management limitations.

Efforts to reduce greenhouse gas emissions are ongoing in many East Asian countries; however, their influences on future drought remain unknown. We analyzed future changes in drought intensity over East Asia using the Representative Concentration Pathway (RCP) 8.5 and the new two limiting local greenhouse gas emission scenarios in East Asia: National Institute of Environmental Research (NIER)-H scenario for high emission and NIER-L scenario for low emission. The two scenarios were made by a fully coupled global climate model with prescribed gas boundaries of high and low greenhouse gas emissions from an atmospheric chemistry model reflecting the up-to-date environmental policies of South Korea, China, and Japan. The application of a clustering analysis to the calculated drought index time series identified four zonally distributed drought regions in the present-day period (1951 - 2016). Among these regions, higher latitude regions showed a more rapidly increasing trend in drought intensity than other regions for the present-day period. All future scenarios projected the continuation of this meridional intensification trend of drought until 2100; however, the intensification rates in the NIER-L were much smaller than those in the RCP8.5 and NIER-H scenarios. Our results suggest that reducing greenhouse gas emissions is critical for East Asian countries to alleviate the potential damages of future droughts.

The emission of pollution from Chinese point sources, and its migration to Korea, downwind of China, is an important issue in terms of Korean air quality management. Therefore, this study intended to improve the Asian Emission Inventory, NIER/KU-CREATE, by improving information about the point source emissions, their location, and discharge conditions, in China. By using the Global dataset, we can establish point source location information for Coal Power Plants and Non-Coal Power Plants in the Chinese power sector, and calculate and allocate emissions in the inventory. In addition, the emission inventory of NH3, as a by-product of NOx abatement processing, was regarded as being insufficiently characterized in the previous emission inventory, and has been re-estimated. As a result, 3798 LPSs in China were identified, and NH3 emissions from those power plants have increased significantly. In addition, the vertical distribution of emissions through the allocation stack height parameters showed atmospheric injection heights of between 250 m and 1000 m. Using this information, HY-SPLIT trajectory modeling found that during periods of active westerly from China to Korea, emissions from the higher injection height were more prone to move towards Korea, than those from the lower height.

Understanding how ozone (O3) and fine particulate matter (PM) formation respond to the precursor concentrations in the presence of biogenic emissions (BEs) and thereby changes in health effects can be a key step to design effective air quality management plans. This is particularly true in the Seoul Metropolitan Area (SMA), where future significant controls of anthropogenic sources of O3 and PM2.5 precursors are expected. In this paper, we investigate the effects of BEs on O3 and fine PM (PM2.5) concentrations during a strong photochemical air pollution season in the SMA in Korea. O3 and PM2.5 levels are modeled with and without BEs in June 2008. Further, we perform the health impact assessments (HIA) of O3 and PM2.5 concentration changes due to BEs to seek useful implications for air quality management by utilizing the adjusted exposure concentration fields for O3 and PM2.5 with an observation fusing (OBF) method. With BEs, daily maximum 8-h average O3 (maximum 8-h O3) and secondary organic aerosol (SOA) concentrations in the SMA increase by 17 and 474%, respectively. These increments are associated with significant consumption of photochemical oxidants (Ox), such as a ~ 60% reduction in OH∙ radicals. The reduction in Ox, conversely, lowers the production of secondary inorganic aerosols (SIOAs) by 2.7%. Adjusted O3 and PM2.5 exposure metrics and the subsequent HIA reveal that large mean increments of O3, about 8.43 ppb, due to BEs are responsible for approximately 62 all-cause premature mortalities in the SMA in June. However, mean increment of PM2.5 due to BEs is approximately 0.3 μg m−3 and results in negligible impacts on the all-cause mortality. Significant correlations of O3 and mortality rates (MR) with the VOC/NOx ratios across the SMA suggest that controlling volatile organic compounds (VOCs) from anthropogenic sources can be a priority to reduce O3 levels and population health risks in the SMA. Specifically, linear relationships of log [O3] and log [MR] to log [VOC/NOx] ensure that a 10% decrease in the VOC/NOx ratios through the VOC abatements would lead to a 1.5% decrease in the O3 levels and a 4.3% decrease in the MR on average across the SMA.

Climate change is an important issue, with many researches examining not only future climatic conditions, but also the interaction of climate and air quality. In this study, a new version of the emissions processing software tool - Python-based PRocessing Operator for Climate and Emission Scenarios (PROCES) - was developed to support climate and atmospheric chemistry modeling studies. PROCES was designed to cover global and regional scale modeling domains, which correspond to GEOS-Chem and CMAQ/CAMx models, respectively. This tool comprises of one main system and two units of external software. One of the external software units for this processing system was developed using the GIS commercial program, which was used to create spatial allocation profiles as an auxiliary database. The SMOKE-Asia emissions modeling system was linked to the main system as an external software, to create model-ready emissions for regional scale air quality modeling. The main system was coded in Python version 2.7, which includes several functions allowing general emissions processing steps, such as emissions interpolation, spatial allocation and chemical speciation, to create model-ready emissions and auxiliary inputs of SMOKE-Asia, as well as user-friendly functions related to emissions analysis, such as verification and visualization. Due to its flexible software architecture, PROCES can be applied to any pre-gridded emission data, as well as regional inventories. The application results of our new tool for global and regional (East Asia) scale modeling domain under RCP scenario for the years 1995-2006, 2015-2025, and 2040-2055 was quantitatively in good agreement with the reference data of RCPs.

Spatial and temporal variations of mercury, including dry and wet deposition fluxes, were assessed over Northeast Asia, targeting the Yellow Sea, using meteorology and chemistry models. Four modeling periods, each representative of one of the four seasons, were selected. Modeling results captured general patterns and behaviors, and fell within similar ranges with respect to observations. However, temporal variations of mercury were not closely matched, possibly owing to the effects of localized emissions. Modeling results indicated that dry deposition is correlated with wind speed, while wet deposition is correlated with precipitation amount. Overall, the wet deposition flux of 66 ng/m2-day was about twice as large as the dry deposition flux of 32 ng/m2-day, when averaged over the four modeling periods. Dry deposition occurred predominantly in the form of reactive gaseous mercury (RGM). In contrast, RGM accounted for only about two-thirds of wet deposition, while particulate mercury accounted for the remainder.

To address the limitations of titanium dioxide (TiO2) and expand the applicability of the photocatalytic activity of TiO2,WSe2 and silica, an eco-friendly, self-assembled method for combining a silica precursor with a WSe2-graphene-TiO2 composite with cetyltrimethylammonium bromide (CTAB) as surface active agents is proposed. Firstly, for the main target, the photocatalytic degradation of organic dye solutions with different initial pH levels and catalyst dosages under visible light irradiation was surveyed. The as-synthesized sample exhibited highly efficient photocatalytic effects for the treatment of the SO dye solution in the optimal conditions of this study, which included a solution with a pH level of 11 and 0.05-gram dosage of the catalyst. Secondly, previous photocatalytic hydrogen production studies reported markedly better outcomes with SiO2/WSe2-graphene-TiO2 than with the binary WSe2-graphene and ternary WSe2-graphene-TiO2 composites under ambient conditions with and without 20% methanol sacrificing reagents. The SiO2/WSe2-graphene-TiO2 composite is promising to become a potential candidate for photocatalytic performance that performs excellently as well as offer an efficient heterosystem for hydrogen production.

We examine the meteorological responses due to the probable eruption of Mt. Baekdu using an off-line Climate-Chemistry model that is composed of the National Center for Atmospheric Research (NCAR) Climate Atmosphere Model version 3 (CAM3) and a global chemistry transport model (GEOS-Chem). Using the aerosol dataset from the GEOS-Chem driven by GEOS-5 meteorology, experiment and control simulations of the climate model are performed and their meteorological differences between the two simulations are analyzed. The magnitudes of volcanic eruption and column injection height were presumably set to 1/200 of the Mt. Pinatubo eruption and 9 km, respectively. Significant temperature drop in the lower troposphere (850 hPa), which is mainly due to a direct effect of prescribed volcanic aerosols from Mt. Baekdu, has been simulated up to about −4 K. The upper atmosphere (150 hPa) right above the volcano, however, shows significant warming due to the absorption of the infrared radiation by volcanic aerosols. As a result of the volcanic eruption in the climate model, wave-like patterns are shown in both the geopotential height and horizontal wind. The changes in the lower atmospheric temperature are well associated with the modification of the atmospheric circulation through the hydrostatic balance. In spite of limitations in our current simulations due to several underlying assumptions, our results could give a clue to understanding the meteorological impacts from Mt. Baekdu eruptions that are currently attracting considerable public attention.

Emissions in East Asia for 1993 by administrative units and source types are estimated to support regional emission assessments and transport modeling studies. Total emission of SOx, NOx, soil NOx, N2O, and NH3 are 24 150, 12 610, 1963, 908, and 8263 kton yr-1, respectively.China's emission contribution is the highest for every species.The area sources are the most significant source type for SOx and NOx, but the fraction due to mobile source is highest for NOx. Major LPSs are located from the middle to the east part of China, south and middle-west part of South Korea, and the east part of Japan. The area sources of SOx show a pattern similar to population density, whereas NH3 shows a strong landuse dependency. Detail emissions analysis reveals higher SOx emission `cores' within each province. The estimated emissions are used to estimate sulfur deposition in the regions. The seasonal average sulfur distribution amounts are estimated from the ATMOS2 chemical transport model. The results showed anti-correlation with temperature for sulfur (SO2 + SO4-2) concentrations and a positive correlation with rainfall for deposition.