• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.275-290
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• 2021

Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.

• Korean Journal of Environmental Agriculture
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• v.37 no.4
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• pp.268-276
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• 2018

BACKGROUND: In the month of January 2018, fine dust alerts and warnings were issued 36 times for $PM_{10}$ and 81 times for PM2.5. Air quality is becoming a serious issue nation-wide. Although interest in air-purifying plants is growing due to the controversy over the risk of chemical substances of regular air-purifying solutions, industrial spread of the plants has been limited due to their efficiency in air-conditioning perspective. METHODS AND RESULTS: This study aims to propose a vegetation-based bio-filter system that can assure total indoor air volume for the efficient application of air-purifying plants. In order to evaluate the quantitative performance of the system, time-series analysis was conducted on air-conditioning performance, indoor air quality, and comfort index improvement effects in a lecture room-style laboratory with 16 persons present in the room. The system provided 4.24 ACH ventilation rate and reduced indoor temperature by $1.6^{\circ}C$ and black bulb temperature by $1.0^{\circ}C$. Relative humidity increased by 24.4% and deteriorated comfort index. However, this seemed to be offset by turbulent flow created from the operation of air blowers. While $PM_{10}$ was reduced by 39.5% to $22.11{\mu}g/m^3$, $CO_2$ increased up to 1,329ppm. It is interpreted that released $CO_2$ could not be processed because light compensation point was not reached. As for the indoor comfort index, PMV was reduced by 83.6 % and PPD was reduced by 47.0% on average, indicating that indoor space in a comfort range could be created by operating vegetation-based bio-filters. CONCLUSION: The study confirmed that the vegetation-based bio-filter system is effective in lowering indoor temperature and $PM_{10}$ and has positive effects on creating comfortable indoor space in terms of PMV and PPD.

• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.112-117
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• 2011

This study was conducted for searching the functional feeding groups, and community stability of the macroinvertebrate on forest fire area of Uljin-gun. The samples were collected from 2 sites of control area and 2 sites of experimental area during 2007 to 2009. The identified species were 89 belonged to 47 families, 16 order, 6 class, and 4 phylum in control area. And 84 belonged to 43 families, 16 order, 6 class, and 4 phylum were identified in experimental area. As a result of changes in species and individuals of E.P.T. taxa investigated in experimental area by year, Ephemeroptera was 21 species, $2,434.6inds./m^2$, Plecoptera was 3 species, $199.8inds./m^2$, and Trichoptera 14 species, $540.2inds./m^2$ in 2007. And in 2009, Ephemeroptera was 9 species, $296inds./m^2$, Trichoptera was 4 species, $44.4inds./m^2$, and Plecoptera was none, showing that species and individuals belonging to E.P.T. taxa decrease rapidly every year. Community analysis by year, in 2008 when the water system started to be influenced by the fire directly, it showed a trend that H' and RI decreased in the experimental area. Functional feeding group by year, it showed a trend that species and individuals of GC type which is a functional group picking up and eating FPOM (fine particulate organic matter) from deposits in the bottom of water or benthic areas and performs an important function of material circulation in ecosystem decrease every year. Community stability by year, an environment of water system in forest fire area started to be somewhat destroyed, from 2008, it is shown that both species in I area which have great ability of resistance and recovery and species in III area which live in relatively stable water system decreased a little.

• Korean Journal of Environmental Biology
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• v.39 no.1
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• pp.100-107
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• 2021

Along with an increase in the frequency of high-concentration fine particulate matter in Korea, interest and research on ammonia (NH₃) are actively increasing. It is obvious that agriculture has contributed significantly to NH₃ emissions. However, studies on the long-term effect of fertilizer use on the ambient NH₃ concentration of agricultural land are insufficient. Therefore, in this study, NH₃ concentration in the atmosphere of agricultural land was monitored for 11 months using a passive sampler. The average ambient NH₃ concentration during the total study period was 2.02 ㎍ m^-3 and it was found that the effect of fertilizer application on the ambient NH₃ concentration was greatest in the month immediately following fertilizer application (highest ambient NH₃ concentration as 11.36㎍ m^-3). After that, it was expected that the NH₃ volatilization was promoted by increases in summer temperature and the concentration in the atmosphere was expected to increase. However, high NH₃ concentrations in the atmosphere were not observed due to strong rainfall that lasted for a long period. After that, the ambient NH₃ concentration gradually decreased through autumn and winter. In summary, when studying the contribution of fertilizer to the rate of domestic NH₃ emissions, it is necessary to look intensively for at least one month immediately after fertilizer application, and weather information such as precipitation and no-rain days should be considered in the field study.

• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.281-302
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• 2023

Carbon is not only an essential element for life but also a key player in climate change. The radiocarbon (¹⁴C) analysis using accelerator mass spectrometry (AMS) is a powerful tool not only to understand the carbon cycle but also to track pollutants derived from fossil carbon, which have a distinct radiocarbon isotope ratio (Δ¹⁴C). Many studies have reported Δ¹⁴C of carbon compounds in streams, rivers, rain, snow, throughfall, fine particulate matter (PM_2.5), and wastewater treatment plant effluents in South Korea, which are reviewed in this manuscript. In summary, (1) stream and river carbon in South Korea are largely derived from the chemical weathering of soils and rocks, and organic compounds in plants and soils, strongly influenced by precipitation, wastewater treatment effluents, agricultural land use, soil water, and groundwater. (2) Unprecedentedly high Δ¹⁴C of precipitation during winter has been reported, which can directly and indirectly influence stream and river carbon. Although we cannot exclude the possibility of local contamination sources of high Δ¹⁴C, the results suggest that stream dissolved organic carbon could be older than previously thought, warranting future studies. (3) The ¹⁴C analysis has also been applied to quantify the sources of forest throughfall and PM_2.5, providing new insights. The ¹⁴C data on a variety of ecosystems will be valuable not only to track the pollutants derived from fossil carbon but also to improve our understanding of climate change and provide solutions.