• Journal of IKEEE
• /
• v.24 no.4
• /
• pp.1136-1140
• /
• 2020

As air pollution caused by fine dust becomes serious, interest in the spread of fine dust and prediction of air quality is increasing. The causes of fine dust are very diverse, and some fine dust naturally occurs through forest fires and yellow dust, but most of them are known to be caused by air pollutants from burning fossil fuels such as petroleum and coal or from automobile exhaust gas. In this paper, the CALPUFF model recommended by the US EPA is used, and CALPUFF diffusion modeling is performed by generating a wind field through the CALMET model as a meteorological preprocessing program that generates a three-dimensional wind field, which is a meteorological element required by CALPUFF. Through this, we propose a fine dust diffusion modeling and air quality prediction system that reflects complex topography.

• Journal of Energy Engineering
• /
• v.29 no.2
• /
• pp.23-29
• /
• 2020

In this study, the last 10 years of news data on fine dust was collected and 80 topics are selected through LDA analysis. As a result, weather-related information made up the main words for the topic, and we can see that fine dust becomes a big issue below 10 degrees Celsius. The frequency of exposure to the media and the maximum concentration of fine dust are correlated with positive. Topics related to fine dust reduction measures and the government's comprehensive measures over the past decade, topics related to products such as air purifiers related to fine dust, topics related to policies protecting vulnerable people from fine dust, and topics on fine dust reduction through R&D were found to be major topics. Measures against fine dust as a social issue can be seen to be closely related to the government's policy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.540-542
• /
• 2019

With many announcements on air pollution and human effects from particulate matters, particulate matter forecasts are attracting a lot of public attention. As a result, various efforts have been made to increase the accuracy of particulate matter forecasting by using statistical modeling and machine learning technique. In this paper, the particulate matter AQI index prediction is performed using the multilayer perceptron neural network for particulate matter prediction. For this purpose, a prediction model is designed by using the meteorological factors and particulate matter concentration values commonly used in a number of studies, and the accuracy of the particulate matter AQI prediction is compared.

• The Journal of the Korea Contents Association
• /
• v.22 no.6
• /
• pp.1-14
• /
• 2022

This study aims to identify topics in newspaper articles related to fine particle matter and to investigate the characteristics and time series trend of each topic. Related national newspaper articles during 1990 and 2021 were collected from Bigkinds. A total of 18 topics have been discovered using LDA, and 11 clusters deduced from clustering. Hot topics include related products/residence, overseas cause(China), power plant as a domestic cause, nationwide emergency reduction measures, international cooperation, political issues, current situation & countermeasure in other countries, and consumption patterns. Cold topics include the concentration standard and indoor air quality improvement. These findings would be useful in inferring the political direction and strategies. In particular, the consumer protection policy should be expanded as the related market is growing. It will also be necessary to pursue policies that will promote public safety and health, and that will enhance public consensus and international cooperation.

• Korean Journal of Environment and Ecology
• /
• v.34 no.5
• /
• pp.466-482
• /
• 2020

This study used 3D computational fluid dynamics (CFD) in the ENVI-met program to investigate how particulate matters (PM) generated on roads disperse through adjacent urban neighborhoods according to the urban development pattern. An urban area centered on a six-lane road in the vicinity of Miryang City Hall in Gyeongnam Province was selected to simulate the effect of the green space and building height on the PM concentration. The ENVI-met model considered the presence of green space and different building heights (high/low) on both sides of the road to examine the dispersion of PM. The result showed that the area of high-rise buildings and green space had the lowest PM concentration dispersed to the adjacent area, followed by the area of high-rise buildings and no green space. In contrast, the PM concentration remained relatively high for low-rise buildings, regardless of the green space. The reason for the low PM concentration in the area with high-rise buildings was a strong building wind, which caused PM to disperse to the outside, lowering the PM concentration quickly. These results indicate that the PM can disperse faster, and the PM concentration remains low in the urban neighborhood. On the other hand, green space had no significant effect on reducing PM in the urban neighborhood. In particular, when there are low-rise buildings on both sides of the road, the green space has no effect on the PM concentration in the urban neighborhood. Since this study considered only the case of PM emitted from the road, future studies should investigate other factors to figure out the dispersion model of PM and conduct on-site experiments.

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

• Applied Chemistry for Engineering
• /
• v.25 no.2
• /
• pp.222-226
• /
• 2014

In this study, the purposes are investigating and analyzing car emission factors for estimating road emissions and the legal framework for the control of particulate matters. At the result, when input emission data are not realistic, the modeling output concentration distributions can lead to a serious distortion of the results. So, the spatial analysis of the dust emission vehicles have to be based on the actual traffic volumes. Because dust emission factors used in the car by National Institute of Environmental Research Method (2010) are mainly targeted for 2003-2007 cars these could not reflect the effect of DPF and the dust emission of gasoline passenger car. So, the real dust emission factors of diesel and gasoline cars need to be developed.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.23 no.7
• /
• pp.40-48
• /
• 2019

New concept of fine dust measurement method is suggested based on ultrasonic scattering. These days, fine dust has been social problem in Korea, and many researches has been conducted including the area structural maintenance. Conventional measurement system such as optical scattering and semiconductor has a limit from environmental factors like relative humidity. However, ultrasound is based on mechanical waves, which perturb mechanical properties of medium such as density and elastic constants. Using the advantage, the algorithm for fine dust measurement is derived and evaluated using 2-D finite difference method. The numerical analysis simulates ultrasonic wave propagation inside multiple scattering medium like fine dust in air. Signal processing scheme is also suggested and the results show that the error of the algorithm is around minimum of 0.7 and maximum of 24.9 in the number density unit. It is shown that cross-section of fine dust is a key parameter to improve the accuracy of algorithm.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.873-885
• /
• 2022

The particulate matter (PM) has emerged as a hot topic around the world as it has been reported that PM is related to an increase in mortality and prevalence rates. In South Korea, the importance of PM has been recognized since the late 1990s, and various studies on PM have been conducted. This study investigated the PM research topics and trends for papers (D=2,764) published in Research Information Sharing Service (RISS) using topic modeling based on Latent Dirichlet Allocation (LDA). As a result, a total of 10 topics were identified in the whole papers, and the PM research topics were classified as 'PM reduction (Topic 1)', 'Government policy and management (Topic 2)', 'Characteristics of PM (Topic 3)', 'PM model (Topic 4)', 'Environmental education (Topic 5)', 'Bio (Topic 6)', 'Traffic (Topic 7)', 'Asian dust (Topic 8)', 'Indoor PM (Topic 9)', 'Human risk (Topic 10)'. In particular, the proportion of papers on topics 'Government policy and management (Topic 2)', 'PM model (Topic 4)', 'Environmental education (Topic 5)', and 'Bio (Topic 6)' to the toal number of papers increased over time (linear slope > 0). The results of this study provide the new literature review methodology related to particulate matter and the history and insight.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.11
• /
• pp.427-434
• /
• 2018

Recently, the Seoul government implemented 'Free Public Transportation' policy and 'Citizen Participatory Alternative-Day-No-Driving' system as 'Emergency Fine Dust Reduction Measures'. In this paper, after identifying the effectiveness of the two traffic policies, suggestions for direction of future fine dust policy were made. The effect of traffic on the fine dust was analyzed by regression analysis and the responses to the two traffic policies and petitions were analyzed using text mining. Our experimental results show that the responses to the policy were mostly negative, and the influence of the domestic factors was considerable unlike expectation of citizens. Moreover, the result made us possible to know people's specific needs on fine dust reduction policy. Finally, based on the result, the suggestions for fine dust reduction policy direction were provided.