• 한국물환경학회지
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• 제27권1호
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• pp.120-128
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• 2011

Korea Groundwater Quality Monitoring Network is a database of annual groundwater quality survey results to prevent groundwater pollution. We estimated contamination index (CI) values for each type of land use, and analyzed temporal trends of pollutant concentration data in the Groundwater Quality Monitoring Network from 2001 to 2009. Among the pollutants considered in the database, the concentrations of nitrate and chloride were higher than their standards. In the case of nitrate, recreation parks, golf courses and general waste dumping regions showed increasing trends according to linear regression analysis, whereas industrial complexes and residential regions of urgan and recreation parks showed increasing trends in the chloride concentration data. According to multiple variable linear regression analysis, EC, pH and topography were major factors influencing CI values. These results suggest that groundwater with a high CI value and increasing trend is vulnerable for potential contamination, which requires more careful groundwater pollution control.

• Journal of Korea Artificial Intelligence Association
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• 제1권2호
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• pp.15-20
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• 2023

This study aims to enhance the accuracy of fine dust predictions by analyzing various factors within the local environment, in addition to atmospheric conditions. In the atmospheric environment, meteorological and air pollution data were utilized, and additional factors contributing to fine dust generation within the region, such as traffic volume and electricity transaction data, were sequentially incorporated for analysis. XGBoost, Random Forest, and ANN (Artificial Neural Network) were employed for the analysis. As variables were added, all algorithms demonstrated improved performance. Particularly noteworthy was the Artificial Neural Network, which, when using atmospheric conditions as a variable, resulted in an MAE of 6.25. Upon the addition of traffic volume, the MAE decreased to 5.49, and further inclusion of power transaction data led to a notable improvement, resulting in an MAE of 4.61. This research provides valuable insights for proactive measures against air pollution by predicting future fine dust levels.

• Journal of Korean Society for Atmospheric Environment
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• 제11권E호
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• pp.45-54
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• 1995

Indoor air quality models are useful to predict indoor air pollutant concentrations as a function of several indoor factors. Indoor air quality model was developed to evaluate the pollutant removal efficiency of variable-air-volume/bypass filtration system (VAV/BPFS) compared with the conventional variable-air-volume (VAV) system. This model provides relative pollutant removal effectiveness of VAV/BPFS by concentration ratio between the conventional VAV system and VAV/BPFS. The predictions agree closely, from 5 to 10 percent, with the measured values for each energy load. As a results, we recommend the VAV/BPFS is a promising alternative to conventional VAV system because it is capable of reducing indoor air pollutant concentration and maintaining good indoor air quality.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2010년도 춘계학술대회 논문집
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• pp.646-648
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• 2010

• 전력전자학회:학술대회논문집
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• 전력전자학회 1999년도 전력전자학술대회 논문집
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• pp.659-662
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• 1999

As utility pollution take a growing interest, ac/dc converter optimizing utility condition has been vigorously studied in decades. In this paper three phase DCM converter is analyzed and equations for average input currents are presented. Also relationships of voltage gain & duty according to angular velocity are presented and variable frequency controller is implemented using reset integrator which is designed in detail. In result power factor and THD characteristics of 3-stage and 4-stage operation ae compared respectively.

• 대한환경공학회지
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• 제33권8호
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• pp.572-577
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• 2011

비점오염부하량 산정을 위해 사용되는 원단위는 쉽게 이용 가능하지만, 지역의 토지이용 특성과 강우강도의 시간적인 변이를 고려하지 못하는 단점이 있다. 본 연구에서는 간편하면서도 강우량에 따른 부하량 변화를 고려한 보다 정확한 비점부하량 산정방법을 개발 및 적용하였다. 경기도 경안천 유역에 위치한 두 개의 비점오염저감시설을 대상으로 2010년 6월부터 11월까지 모니터링을 수행하여 강우강도, 유출 특성, 오염부하 등에 관한 분석을 진행하였다. 비점오염원 유출수의 특성을 나타내는 유량가중평균농도(Event Mean Concentration; EMC)의 경우에는 도시 지역인 경기도 광주시 경안동이 산과 밭으로 이루어진 용인시 모현면에 비해 높거나 비슷한 값을 보였으나, TP (Total Phosphorus)의 경우 유역 내 농경지에 사용된 퇴비나 비료에 포함된 인의 영향으로 모현면이 경안동보다 더 높게 나타났다. 강우량과 오염물질 배출부하량과의 관계는 3차원 다항식에 의해 가장 잘 설명되었으며, 0.33~0.81 범위의 결정계수를 나타내고 있다. 산정된 유출율 및 부하량 함수의 기울기가 EMC 결과와 반대되는 경향을 보이는 것으로부터, 비점오염원은 토지이용 이외에도 지형, 토성, 수리 수문현상 등에 따라 배출특성이 달라짐을 알 수 있다. 따라서 비점오염물질의 유출 특성을 정확히 파악하기 위해서는 장기모니터링을 통한자료의 수집을 바탕으로 강우량에 따른 부하량 변화를 고려한 비점부하량 산정함수를 구하는 것이 필요하다.

• Journal of the Korean Data and Information Science Society
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• 제26권6호
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• pp.1409-1416
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• 2015

기온의 변화는 인간의 건강뿐 아니라 동식물의 성장, 경제, 사회, 산업, 문화 등의 전 분야에 영향을 준다. 본 연구에서는 수원시 2003년-2012년 기온을 기상자료, 온실가스자료, 대기자료를 이용하여 자기회귀오차 (autoregressive error)모형으로 월별로 분석하였다. 기온을 위한 기상자료로는, 풍속, 강수량, 일사량, 운량, 습도를 사용했고, 온실가스자료는 이산화탄소 ($CO_2$), 메탄 ($CH_4$), 아산화질소 ($N_2O$), 염화불화탄소 ($CFC_{11}$), 대기자료는 미세먼지 ($PM_{10}$), 이산화황 ($SO_2$), 이산화질 소 ($NO_2$), 오존 ($O_3$), 일산화탄소 (CO)을 사용하였다. 기온을 월별 분석한 결과 기상변수로는 일사량, 운량, 풍속이 영향을 많이 주는 것으로 분석되었다. 특히 일사량은 봄, 여름, 가을에 영향을 많이 주고 풍속은 겨울에 영향을 많이 주는 것으로 나타났다. 온실가스변수로는 염화불화탄소와 메탄이 기온에 영향을 많이 주고 대기변수로는 오존이 영향을 많이 주는 것으로 타났다. 자기회귀오차모형으로 월별 기온을 43%~69% 정도 설명할 수 있다.

• 한국기후변화학회지
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• 제3권2호
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• pp.153-159
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• 2012

자동차 에어컨 냉매로 사용되어온 CFC-12는 1991년부터 1994년에 걸쳐 HFC 계열의 냉매인 R134a로 대체되었으며, R-134a는 현재자동차 에어컨 냉매로 널리 사용되고 있다. 그러나 R-134a는 지구온난화 지수(GWP)가 1,300으로 매우 높으며, 교토의정서에서 정한 6대 온실가스 중에 하나로 포함되어 누출량 관리 및 대체 냉매 개발이 필요한 실정이다. 본 연구에서는 자동차에서 배출되는 $non-CO_2$ 온실가스 배출량 산출을 위한 기초연구로 실차 상태에서의 에어컨 냉매 누출량을 분석하기 위하여 가변온도밀폐실(VT shed)과 Running loss test shed를 이용하여 R-134a의 농도변화를 측정하였다. 대상차종에 대한 주차상태에서 R-134a 누출량을 분석한 결과, 연간 누출량이 6.46~13.28 g/yr 수준으로 기존의 에어컨 시스템을 이용한 누출량 분석결과와 유사한 수준으로 분석되었다. 동일 모델 차량에 단일증발기를 적용한 차량과 이중증발기를 적용한 차량에 대해 냉매 누출량을 비교한 결과, 단일증발기로 구성된 에어컨이 적용된 차량에 비하여 이중증발기가 적용된 에어컨이 장착된 차량에서 누출량이 높게 나타났다. 이는 이중증발기 적용에 따라 에어컨 시스템 구성시 연결부위(호스, 접합부 등)가 추가되면서 해당 부위에서의 누출이 증가된 것으로 보인다. 또한, 차속별 R-134a 농도변화를 분석한 결과, 고속주행시(100 km/hr) 냉매 누출이 증가하였으며, 송풍량 증가에 따른 누출량 변화는 나타나지 않았다.

• 가정과삶의질연구
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• 제22권1호
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• pp.55-64
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• 2004

The major purpose of this study was to investigate purchasing behavior of environmental products by Korean consumers, which will ultimately help foster sustainable consumption. Environmental consciousness, environmental behaviors, level of awareness of environmental products, and purchasing of environmental products were examined. Mean differences between purchasers and non-purchasers of environmental products were compared in terms of environmental consciousness and behaviors, and the level of awareness of environmental products. A survey was conducted on 310 consumers in the greater Seoul metropolitan area. The data were analyzed by frequencies, percentages, logistic regression, and t-tests using a variable for interval scale and a variable for nominal scale. There were significant mean differences between purchasers and non-purchasers of environmental products on three variables of environmental consciousness and behaviors. Those who were educated on environmental issues showed a higher preference in purchasing environmental products. Among socio-demographic variables, the income level was the only variable that showed a significant mean difference between the two groups. Also, there was a remarkable difference in purchasing behavior between the two groups. For the purchasers of environmental products, the purchasing decisions took into account environment-friendliness of products. Non-purchasers of environmental products put more emphasis on price or quality of products. The results of the logistic regression analysis indicated that those who had higher education, who viewed environmental pollution as a serious problem, and who are more cognizant of the environmental labeling tend to purchase more environmental products.

• 자원환경지질
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• 제55권6호
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• pp.617-632
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• 2022

In recent years, environmental pollution and determining the main factors causing this pollution have become an important issue. This study investigates the relationship between the agricultural sector and environmental pollution in Azerbaijan for 1992-2018. The dependent variable in the study is the agricultural greenhouse gas emissions (CO₂ equivalent). Eight variables were selected as explanatory variables: four agricultural inputs and four agricultural macro indicators. Unit root tests, ARDL boundary test, FMOLS, DOLS and CCR long-term estimators, Granger causality analysis, and variance decomposition analyses were used to investigate the effect of these variables on agricultural emissions. The results show that chemical fertilizer consumption, livestock number, and pesticide use positively and statistically significantly affect agricultural emissions from agricultural input variables. In contrast, agricultural energy consumption has a negative and significant effect. From agricultural macro indicator variables, it was found that the crop and animal production index had a positive and significant effect on agricultural emissions. According to the Granger causality test results, it was concluded that there are a causality relationship from chemical fertilizer consumption, livestock number, crop and livestock production index variables towards agricultural emissions. Considering all the results obtained, it is seen that the variables that have the most effect on the increase in agricultural emissions in Azerbaijan are the number of livestock, the consumption of chemical fertilizers, and the use of pesticides, respectively. The results from the research will contribute to the information on agricultural greenhouse gas emissions and will play an enlightening role for policymakers and the general public.