• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.424-425
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• 2016

본 연구는 우리나라의 지역별 미세먼지 발생 데이터에 대한 수집과 그에 대한 분석, 처리 방법에 대한 연구로 수집된 미세먼지 데이터에 대한 클러스터링 메소드를 설계하고 구현하는 것을 목표로한다. 본 연구에서는 기상청 산하의 30여개의 관측소에서 측정된 미세먼지 데이터를 기반으로 클러스터링 작업에 대한 전처리를 실시한다. 이러한 전 처리에는 각 관측소의 미세먼지 데이터의 시계열 그래프의 유사도를 비교하기 위하여 Dynamic Time Warping알고리즘을 활용하였으며 이를 통해 산출되는 DTW값을 통하여 유사도가 높은 미세먼지 측정 지역별 클러스터링을 수행해 클러스터링 군별 미세먼지 발생 원인에 대한 분석과 대비, 피해저감 방안등의 대책 마련을 위한 자료로서 활용됨을 목적으로 한다.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.218-236
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• 2023

This study attempted to analyze the environmental equity of fine dust(PM₁₀) in Daegu using MGWR(Multi-scale Geographically Weighted Regression) and KT(Korea Telecom Corporation) sensor data. Existing national monitoring network data for measuring fine dust are collected at a small number of ground-based stations that are sparsely distributed in a large area. To complement these drawbacks, KT sensor data with a large number of IoT(Internet of Things) stations densely distributed were used in this study. The MGWR model was used to deal with spatial heterogeneity and multi-scale contextual effects in the spatial relationships between fine dust concentration and socioeconomic variables. Results indicate that there existed an environmental inequity by land value and foreigner ratio in the spatial distribution of fine dust in Daegu metropolitan city. Also, the MGWR model showed better the explanatory power than Ordinary Least Square(OLS) and Geographically Weighted Regression(GWR) models in explaining the spatial relationships between the concentration of fine dust and socioeconomic variables. This study demonstrated the potential of KT sensor data as a supplement to the existing national monitoring network data for measuring fine dust.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.417-425
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• 2020

This study investigated predictors of the behavior related to particulate matter in nursing students. The participants in this descriptive study were 186 nursing students at K university in G city from May 1 to 14 in 2018. Collected data were analyzed by t-test, one-way ANOVA, Pearson's correlation coefficient, and multiple linear regression using SPSS WIN 18.0 program. The level of knowledge(10.6/15), attitude(59.94/75) and behavior(42.56/60) were relatively high. The significant predictors of the behavior were attitude(β=.591, p<.001), smoking(β=-.134, p=.049) and respiratory disease(β=.133, p=.025), and explained 40.1% of it. Educational programs to enhance nursing students' health promoting behaviors against particulate matter must be focused on attitude change.

• The Journal of Bigdata
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• v.4 no.2
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• pp.105-114
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• 2019

Missing value replacement is one of the big issues in data analysis. If you ignore the occurrence of the missing value and proceed with the analysis, a bias can occur and give incorrect results for the estimate. In this paper, we need to find and apply an appropriate alternative to missing data from weather data. Through this, we attempted to clarify and compare the simulations for various situations using existing methods such as MICE and MissForest based on R and time series-based models. When comparing these results with each variable, it was determined that the kalman filter of the auto arima model using the ImputeTS package and the MissForest model gave good results in the weather data.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.11a
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• pp.134-135
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• 2000

현실적이고 장기적인 대기환경관련 정책을 수립하기 위해서는 대기질 개선에 필요한 비용과 그에 따른 이익이 같이 예측되고 평가되어야 하는데, 대기질의 오염정도를 중장기적으로 예측하기 위해서 대기질 모델링이 사용되며 이의 주요한 입력자료는 배출량 자료이다. 한편, 현재 우리나라 수도권에서 관찰되는 대기오염의 형태가 과거와는 달리 주요 오염물질이 아황산가스 등 1차 오염물질에서 미세먼지와 오존 등으로 바뀌고 있다는 점은 주목할 만하다. 또한 미세먼지의 인체에 미치는 영향에 대한 연구들이 여러 나라에서 진행되고 있다. (중략)

• Journal of Climate Change Research
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• v.9 no.4
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• pp.423-433
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• 2018

Particulate matter air pollution is a serious problem affecting human health and visibility. The variations in $PM_{10}$ concentrations are influenced by not only local emission sources, but also atmospheric circulation conditions. In this study, we investigate the temporal features of $PM_{10}$ concentrations in South Korea and the atmospheric circulation patterns associated with high concentration episodes of $PM_{10}$ during winter (December-January-February) 2001-2016. Based on those analyses, a Korea Particulate matter Index (KPI) is developed to represent the large-scale atmospheric pattern associated with high concentration episodes of $PM_{10}$. The atmospheric patterns are characterized by persistent high-pressure anomalies, weakened lower-level north-westerly anomalies, and northward shift of the upper-level meridional wind anomalies near the Korean Peninsula. To evaluate the change in occurrence of high concentration episodes of $PM_{10}$ under a possible future warmer climate, we apply KPI analysis to CMIP5 climate simulations. Here, historical and two representative concentration pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) are used. It is found that the occurrence of atmospheric conditions favorable for high $PM_{10}$ concentration episodes tends to increase over South Korea in response to climate change. This suggests that large-scale atmospheric circulation changes under future warmer climate can contribute to increasing high $PM_{10}$ concentration episodes in South Korea.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.109-114
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• 2015

This paper presents a computational model on the transfer of airborne fine particles to analyze the similarities and influences among the 25 districts in Seoul by quantifying a time series data collected from each district. The properties of each district are driven with the model of a time series of the fine particle concentrations, and the calculation of edge-based weights are carried out with the transfer entropies between all pairs of the districts. We applied a modularity-based graph clustering technique to detect the communities among the 25 districts. The result indicates the discovered clusters correspond to a high transfer-entropy group among the communities with geographical adjacency or high in-between traffic volumes. We believe that this approach can be further extended to the discovery of significant flows of other indicators causing environmental pollution.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.127-133
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• 2020

The international cancer research institute under the WHO designated fine dust as a first-class carcinogen. Particular matter refers to dust that is small enough to be invisible and floating in the air. Particular matter is mainly emitted from the combustion process of fossil fuels such as coal and oil, and is a risk factor that can cause lung disease, pneumonia, and heart disease. The Ministry of Environment recently analyzed the output data of 10 fine dust measuring stations and, as a result, announced that about 60% had an error that the existing atmospheric measurement concentration was higher. In order to accurately predict fine dust, the wind direction and measurement position must be corrected. In this paper, in order to solve these problems, fuzzy rules are used to solve these problems. In addition, in order to calculate the fine particulate sensation index actually felt by pedestrians on the street, a computer simulation experiment was conducted to calculate the fine particulate sensation index in consideration of weather conditions, temperature conditions, humidity conditions, and wind conditions.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2003.05b
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• pp.247-248
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• 2003

우리 나라의 도시ㆍ산업단지 지역의 대기오염은 심각한 수준으로, 특히 미세먼지로 인한 대기오염은 스모그 등 심미적인 문제뿐만 아니라 호흡성 분진으로 인한 건강 위해성 측면에서 철저한 오염원 관리가 필요하다. 현재 우리 나라의 먼지 배출량을 보면 비산먼지의 배출량이 연소과정에서 발생되는 미세먼지보다도 큰 것으로 추정되며, 특히 이 중에서 자동차의 도로주행시 발생되는 먼지가 비산먼지 발생량 중 90 %이상을 차지하고 있는 것으로 추정된다(국립환경연구원, 2002). 차량운행으로 인하여 포장도로에서 발생하는 비산먼지 배출량은 도로 표면의 단위면적 당 silt(75$\mu\textrm{m}$이하의 입자)량, 즉 silt loading에 의해 좌우되는데 silt loading은 도시ㆍ산업단지의 체계적인 개발계획 및 대기질 관리정책을 수립에 없어서는 안 될 중요한 자료이다. (중략)

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.237-245
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• 2022

Peach is a typical summer fruit which can be used for various food, processed food, and fragrance ingredients in Korea. Peach is also known as one of serious allergens which make difficulty for farm workers during peach sorting operations. After peach harvesting, it moves to the sorting operations for removing cover material, removing fuzz on peach surface, sorting by size, and packing. The air-samplers and optical particle counters were used to analyze the characteristics of fine dust generation by location and operation characteristics in the experimental peach farms. During removing peach fuzz, the dust concentrations were increased by 6.89 times on total suspended particulate (TSP), 2.13 times on PM-10 (particulate matter), and 1.30 times on PM-2.5 compared to non-working periods, respectively. During removing peach covering materials, the dust concentrations were increased by 3.14 times on TSP, 1.91 times on PM-10, and 1.43 times on PM-2.5 compared to non-working periods, respectively. This represents peach fuzz can be affected to farm workers during peach sorting operations.