• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.

• Microbiology and Biotechnology Letters
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• v.27 no.4
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• pp.311-319
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• 1999

Leaves of Aloe vera Linne and bloods of domestic animal were composted in a soild state fermentation reactor (SSFR) by using microbial additive including a bulking and moisture controlling agent. From solid-culture of microbial additive, 10 species of bacteria and 10 species of fungi were isolated and, their enzyme activities including amylase, carboxy methyl cellulase CMCase, lipase and protease were detected. Optimum fermentation conditions of Aloe leaves and domestic animal bloods in SSFR were obtained from the studies of response surface analysis employing microbial additive content, initial moisture content, and fermentation temperature as the independent variables. The optimum conditions for SSFR using Aloe leaves were obtained at 9.45$\pm$73%(w/w) of microbial additives, 62.73$\pm$4.54%(w/w) of initial moisture content and 55.32$\pm$3.14$^{\circ}C$ of fermentation temperature while those for SSFR using domestic animal bloods were obtained at 10.25$\pm$2.04%, 58.68$\pm$4.97% and 57.85$\pm$5.$65^{\circ}C$, respectively. Composting process in SSFR was initially proceeded through fermentation and solid materials were decomposed within 24 hours by maintaining higher moisture level, and maturing and drying steps are followed later. After the fermentation step, the concentrations of solid phase inorganic components were increased while that of organic components were decreased. Also, concentrations of total organic carbon(TOC), peptides, amino acids, polysaccharides, and low fatty acids in water extracts were increased. As fermentation in composting process depends on initial C/N ratios in water extracts of two samples were increased because of increased water-soluble TOC. From these results, it was revealed that solid state fermentation reactor using microbial additives can be used in composting process of organic wastes with broad C/N ratio.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.2
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• pp.95-112
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• 2002

A precision analysis was conducted for the quantification of trace metal levels in airborne particulates using ICP-MS. According to our study the quantitative analysis using Whatman grade 41 filters produces more precise and representative values of metal concentrations than that using EPM 2000 filters. The mean concentration of PM 10 analyzed during 1998 ~ 2000 was 82 $\mu$g/m$^3$. The concentrations of human carcinogens such as As and Cr were 8.65 and 25.87 ng/m$^3$, respectively, while those of probable human carcinogens such as Cd and Pb were 3.13 and 219.46 ng/m$^3$, respectively. Time-weighted mean concentration, calculated using surface wind speed and direction, indicated that there were differences between metals of crustal origin and metals of anthropogenic origin. The rectorial concentrations of anthropogenic metals and PM 10 were higher for north -west sector with calm or low wind speed conditions than for any other sector with high wind speed conditions. On the contrary, the rectorial concentrations of crustal metals were high with high wind speed. In addition, the sectorial concentrations of crustal metals were more affected by south-west wind directions, which were compared with those of anthropogenic metals. The enrichment factor (EF) values of many anthropogenic metals were higher than 50, while those of crustal metals were lower than 3, respectively. The concentrations of Cr and Ni in Daejeon industrial complex area were 11 times higher than those in the background site of Kuopio in Finland, while that of Pb in the complex area was 22 times higher, respectively.

• Atmosphere
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• v.30 no.4
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• pp.439-454
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• 2020

This study investigates the change in the fine particulate matter (PM2.5) concentration and World Health Organization (WHO) air quality index (AQI) in East Asia (EA) under Shared Socioeconomic Pathways (SSPs). AQI is an indicator of increasing levels about health concern, divided into six categories based on PM2.5 annual concentrations. Here, we utilized the ensemble results of UKESM1, the climate model operated in Met Office, UK, for the analysis of long-term variation during the historical (1950~2014) and future (2015~2100) period. The results show that the spatial distributions of simulated PM2.5 concentrations in present-day (1995~2014) are comparable to observations. It is found that most regions in EA exceeded the WHO air quality guideline except for Japan, Mongolia regions, and the far seas during the historical period. In future scenarios containing strong air quality (SSP1-2.6, SSP5-8.5) and medium air quality (SSP2-4.5) controls, PM2.5 concentrations are substantially reduced, resulting in significant improvement in AQI until the mid-21st century. On the other hand, the mild air pollution controls in SSP3-7.0 tend to lead poor AQI in China and Korea. This study also examines impact of increased in PM2.5 concentrations on downward shortwave energy at the surface. As a result, strong air pollution controls can improve air quality through reduced PM2.5 concentrations, but lead to an additional warming in both the near and mid-term future climate over EA.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.2
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• pp.294-305
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• 2018

Quantitative assessment on the impact from North Korean emissions to surface particulate matter(PM) concentration in the Seoul Metropolitan Area (SMA), South Korea is conducted using a 3-dimensional chemistry transport model. Transboundary transport of air pollutants and their precursors are important to understand regional air quality in East Asian countries. As North Korea locates in the middle of main transport pathways of Chinese pollutants, quantifiable estimation of its impact is essential for policy making in South Korean air quality management. In this study, the Community Multiscale Air Quality Modeling System is utilized to simulate regional air quality and its sensitivity, using the Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment 2015 and the Clean Air Policy Support System 2013 emissions inventories for North and South Korea, respectively. Contributions were estimated by a brute force method, perturbing 50% of North and South Korean emissions. Simulations demonstrate that North Korean emissions contribute $3.89{\mu}g/m^3$ of annual surface PM concentrations in the SMA, which accounts 14.7% of the region's average. Impacts are dominant in nitrate and organic carbon (OC) concentrations, attributing almost 40% of SMA OC concentration during January and February. Clear seasonal variations are also found in North Korean emissions contribution to South Korea (and vice versa) due to seasonal characteristics of synoptic weather, especially by the change of seasonal flow patterns.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.2
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• pp.133-140
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• 2009

In order to examine the effects of micrometeorological and climatological influences on urban scale particulate air pollutants observed in Busan, power spectrum analysis was applied to the observed particulate matter with aerodynamic diameter ${\le}10{\mu}m$ ($PM_{10}$) for the period from 1991 to 2006. Power spectrum analysis has been employed to the daily mean $PM_{10}$ concentrations obtained at 13 sites to identify different scales of periodicities of $PM_{10}$ concentrations. The results show that, aside from the typical and well-known periodicities such as diurnal and annual variations caused by anthropogenic emission influences, another two significant peaks of power spectrum density were identified: 21 day and $3{\sim}4$ year of periodicities. Cospectrum analysis indicates that the intraseasonal 21 day periodicity are found to be negatively correlated with wind speed and surface pressure but shows consistently positive with relative humidity and temperature. This result implied that 21 day periodicity is presumably relevant to the secondary aerosol formation processes through the photochemical reaction that can be subsequently resulted from hygroscopic characteristics of aerosol formation. However, the interannual $3{\sim}4$ year of periodicity is found to have positive correlation with pressure, and negative with temperature and relative humidity, which is rather consistent with both characteristics of air mass during the Asian dust event and the occurrence frequency of Asian dust whose periodicities have been recorded inter-annually over the Korean peninsula.

• Atmosphere
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• v.33 no.3
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• pp.319-330
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• 2023

As the need for PM type observation increases, Surface Particulate Matter Network (SPARTAN), PM samplers analyzes aerosol samples for PM mass concentration and chemical composition, were recently installed at two sites: Yonsei University at Seoul and Ulsan Institute of Science and Technology (UNIST) at Ulsan. These SPARTAN filter samplers and nephelometers provide the PM_2.5 mass concentration and chemical speciation data with aerosol type information. We introduced the overall information and installation of SPARTAN at the field site in this study. After installation and observation, both Seoul and Ulsan sites showed a similar time series pattern with the daily PM_2.5 mass concentration of SPARTAN and the data of Airkorea. In particular, in the case of high concentrations of fine particles, daily average value of PM_2.5 was relatively well-matched. During the Yonsei University observation period, high concentrations were displayed in the order of sulfate, black carbon (BC), ammonium, and calcium ions on most measurement days. The case in which the concentration of nitrate ions showed significant value was confirmed as the period during which the fine dust alert was issued. From the data analysis, SPARTAN data can be analyzed in conjunction with the existing urban monitoring network, and it is expected to have a synergetic effect in the research field. Additionally, the possibility of being analyzed with optical data such as AERONET is presented. In addition, the method of installing and operating SPARTAN has been described in detail, which is expected to help set the stage for the observation system in the future.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.2
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• pp.159-173
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• 2017

The Weather Research and Forecast (WRF) - Community Multiscale Air Quality (CMAQ) system was applied to investigate the influence of major point sources located in Chungcheongnam-do (CN) on surface $PM_{2.5}$ (Particulate Matter of which diameter is $2.5{\mu}m$ or less) concentrations in its surrounding areas. Uncertainties associated with contribution estimations were examined through cross-comparison of modeling results using various combinations of model inputs and setups; two meteorological datasets developed with WRF for 2010 and 2014, and two domestic emission inventories for 2010 and 2013 were used to estimate contributions of major point sources in CN. The results show that contributions of major point sources in CN to annual $PM_{2.5}$ concentrations over Seoul, Incheon, Gyeonggi, and CN ranged $0.51{\sim}1.63{\mu}g/m^3$, $0.71{\sim}1.62{\mu}g/m^3$, $0.63{\sim}1.66{\mu}g/m^3$, and $1.04{\sim}1.86{\mu}g/m^3$, respectively, depending on meteorology and emission inventory choice. It indicates that the contributions over the surrounding areas can be affected by model inputs significantly. Nitrate was the most dominant $PM_{2.5}$ component that was increased by major point sources in CN followed by sulfate, ammonium, and others. Based on the model simulations, it was estimated that primary $PM_{2.5}$ $(PPM)-to-PM_{2.5}$ conversion rates were 41.3~50.7 ($10^{-6}{\mu}g/m^3/TPY$) for CN, and 12.4~18.3 ($10^{-6}{\mu}g/m^3/TPY$) for Seoul, Incheon, and Gyeonggi, respectively. In addition, spatial gradients of PPM contributions show very steep trends. $NO_X$-to-nitrate conversion rates were 7.61~12.3 ($10^{-6}{\mu}g/m^3/TPY$) for CN, and 3.94~11.3 ($10^{-6}{\mu}g/m^3/TPY$) for the sub-regions in the SMA. $SO_2$-to-sulfate conversion rates were 4.04~5.28 ($10^{-6}{\mu}g/m^3/TPY$) for CN, and 3.73~4.43 ($10^{-6}{\mu}g/m^3/TPY$) for the SMA, respectively.

• Atmosphere
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• v.22 no.2
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• pp.245-257
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• 2012

The Asian dust (Hwangsa) forecasting model, Asian Dust Aerosol Model (ADAM) has been modified by using satelliate monitoring of surface vegetation, which enables to simulate dusts occuring not only in springtime but also for all-year-round period. Coupled with the Unified Model (UM), the operational weather forecasting model at KMA, UM-ADAM2 was implemented for operational dust forecasting since 2010, with an aid of development of Meteorology-Chemistry Interface Processor (MCIP) for usage UM. The performance analysis of the ADAM2 forecast was conducted with $PM_{10}$ concentrations observed at monitoring sites in the source regions in China and the downstream regions of Korea from March to December in 2010. It was found that the UM-ADAM2 model was able to simulate quite well Hwangsa events observed in spring and wintertime over Korea. In the downstream region of Korea, the starting and ending times of dust events were well-simulated, although the surface $PM_{10}$ concentration was slightly underestimated for some dust events. The general negative bias less than $35{\mu}g\;m^{3}$ in $PM_{10}$ is found and it is likely to be due to other fine aerosol species which is not considered in ADAM2. It is found that the correlation between observed and forecasted $PM_{10}$ concentration increases as forecasting time approaches, showing stably high correlation about 0.7 within 36 hr in forecasting time. This suggests the possibility that there is potential for the UM-ADAM2 model to be used as an operational Asian dust forecast model.

• Korean Chemical Engineering Research
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• v.57 no.1
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• pp.90-104
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• 2019

In this study, CALPUFF modeling was performed, using a real surface and upper air meterological data to predict trustworthy modeling-results. Pollutant-releases from windscreen chambers of enclosed poultry farms, P1 and P2, and from a open poultry farm, P3, and their diffusing behavior were modeled by CALPUFF modeling with volume sources as well as by finally-adjusted CALPUFF modeling where a linear velocity of upward-exit gas averaged with the weight of each directional-emitting area was applied as a model-linear velocity ($u^M_y$) at a stack, with point sources. In addition, based upon the scenario of poultry farm-releasing odor and particulate matter (PM) removal efficiencies of 0, 20, 50 and 80% or their corresponding emission rates of 100, 80, 50 and 20%, respectively, CALPUFF modeling was performed and concentrations of odor and PM were predicted at the region as a discrete receptor where civil complaints had been frequently filed. The predicted concentrations of ammonia, hydrogen sulfide, $PM_{2.5}$ and $PM_{10}$ were compared with those required to meet according to the offensive odor control law or the atmospheric environmental law. Subsequently their required removal efficiencies at poultry farms of P1, P2 and P3 were estimated. As a result, a priori assumption that pollutant concentrations at their discrete receptors are reduced by the same fraction as pollutant concentrations at P1, P2 and P3 as volume source or point source, were controlled and reduced, was proven applicable in this study. In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of P1 compared with those of point source-adopted CALPUFF modeling, were predicted similar each other. However, In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of both ammonia and $PM_{10}$ at not only P2 but also P3 were predicted higher than those of point source-adopted CALPUFF modeling. Nonetheless, the volume source-adopted CALPUFF modeling was preferred as a safe approach to resolve civil complaints. Accordingly, the required degrees of pollution prevention against ammonia, hydrogen sulfide, $PM_{2.5}$ and $PM_{10}$ at P1 and P2, were estimated in a proper manner.