• 제목/요약/키워드: Air Pollution Modeling

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Receptor Modeling

  • 이학성
    • 한국대기환경학회:학술대회논문집
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    • 한국대기환경학회 1994년도 제19회 추계 대기보전학술대회 요지집
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    • pp.109-109
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    • 1994

연안도시지역에서 대기오염의 3차원 수치예측모델링 -(I) 침적현상이 대기질에 미치는 영향예측 (3-D Numerical Prediction Modeling of Air Pollution in Coastal Urban Region -(I) An Effect Prediction for Deposition Phenomenon affecting on Air Quality)

  • 원경미;이화운
    • 한국대기환경학회지
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    • 제15권5호
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    • pp.625-638
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    • 1999
  • Air quality modeling for coastal urban region has been composed of a complex system including meteorological, chemical and physical processes and emission characteristics in complex terrain. In this study, we studied about an effect prediction for deposition phenomenon affecting on air quality in Pusan metopolitan metropolitan city. In air quality modeling including ship sources, a situation considered deposition process habe better result than not considered when compared with observed value. Air pollutants emitted into urban air during the daytime nearly removed through urban atmosphere polluted. Also these phenomena correlated concentration variation connent with sea/land breezes and terrain effect. Therefore we conclude that the concentration was low at daytime when deposition flux is high, and deposition effect on industrial complex and Dongrae region is considerable in particular.

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Box Model Approach for Indoor Air Quality (IAQ) Management in a Subway Station Environment

  • Song, Jihan;Pokhrel, Rajib;Lee, Heekwan;Kim, Shin-Do
    • Asian Journal of Atmospheric Environment
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    • 제8권4호
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    • pp.184-191
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    • 2014
  • Air quality in a subway tunnel has been crucial in most of the subway environments where IAQ could be affected by many factors such as the number of passengers, the amount and types of ventilation, train operation factors and other facilities. A modeling approach has been introduced to manage the general IAQ in a subway station. Field surveys and $CO_2$ measurements were initially conducted to analyze and understand the relationship between indoor and outdoor air quality while considering internal pollution sources, such as passengers and subway trains, etc. The measurement data were then employed for the model development with other statistical information. For the model development, the algorithm of simple continuity was set up and applied to model the subway IAQ concerned, while considering the major air transport through staircases and tunnels. Monitored $CO_2$ concentration on the concourse and platform were correlated with modeling results where the correlation values for the concourse and platform were $R^2=0.96$ and $R^2=0.75$, respectively. It implies that the box modeling approach introduced in this study would be beneficial to predict and control the indoor air quality in subway environments.

Using Different Method for petroleum Consumption Forecasting, Case Study: Tehran

  • Varahrami, Vida
    • 동아시아경상학회지
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    • 제1권1호
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    • pp.17-21
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    • 2013
  • Purpose: Forecasting of petroleum consumption is useful in planning and management of petroleum production and control of air pollution. Research Design, Data and Methodology: ARMA models, sometimes called Box-Jenkins models after the iterative Box-Jenkins methodology usually used to estimate them, are typically applied to auto correlated time series data. Results: Petroleum consumption modeling plays a role key in big urban air pollution planning and management. In this study three models as, MLFF, MLFF with GARCH (1,1) and ARMA(1,1), have been investigated to model the petroleum consumption forecasts. Certain standard statistical parameters were used to evaluate the performance of the models developed in this study. Based upon the results obtained in this study and the consequent comparative analysis, it has been found that the MLFF with GARCH (1,1) have better forecasting results.. Conclusions: Survey of data reveals that deposit of government policies in recent yeas, petroleum consumption rises in Tehran and unfortunately more petroleum use causes to air pollution and bad environmental problems.

PMF모델을 이용한 대기 중 PM-10 오염원의 정량적 기여도 추정 (Estimation of Quantitative Source Contribution of Ambient PM-10 Using the PMF Model)

  • 황인조;김동술
    • 한국대기환경학회지
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    • 제19권6호
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    • pp.719-731
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    • 2003
  • In order to maintain and manage ambient air quality, it is necessary to identify sources and to apportion its sources for ambient particulate matters. The receptor methods were one of the statistical methods to achieve reasonable air pollution strategies. Also, receptor methods, a field of chemometrics, is based on manifold applied statistics and is a statistical methodology that analyzes the physicochemical properties of gaseous and particulate pollutant on various atmospheric receptors, identifies the sources of air pollutants, and quantifies the apportionment of the sources to the receptors. The objective of this study was 1) after obtaining results from the PMF modeling, the existing sources of air at the study area were qualitatively identified and the contributions of each source were quantitatively estimated as well. 2) finally efficient air pollution management and control strategies of each source were suggested. The PMF model was intensively applied to estimate the quantitative contribution of air pollution sources based on the chemical information (128 samples and 25 chemical species). Through a case study of the PMF modeling for the PM-10 aerosols, the total of 11 factors were determined. The multiple linear regression analysis between the observed PM-10 mass concentration and the estimated G matrix had been performed following the FPEAK test. Finally the regression analysis provided quantitative source contributions (scaled G matrix) and source profiles (scaled F matrix). The results of the PMF modeling showed that the sources were apportioned by secondary aerosol related source 28.8 %, soil related source 16.8%, waste incineration source 11.5%, field burning source 11.0%, fossil fuel combustion source 10%, industry related source 8.3%, motor vehicle source 7.9%, oil/coal combustion source 4.4%, non-ferrous metal source 0.3%. and aged sea- salt source 0.2%, respectively.