• Title/Summary/Keyword: Air Quality Model

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Receptor Model(CMB) and Source Apportionments of VOCs in Seoul Metropolitan Area (수용모델(CMB)을 이용한 수도권 VOCs의 배출원별 기여율 추정)

  • Han, Jin-Seok;Hong, Y.D.;Shin, S.A.;Lee, S.U.;Lee, S.J.
    • Journal of Environmental Impact Assessment
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    • v.14 no.4
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    • pp.227-235
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    • 2005
  • Source contribution for VOCs collected in Seoul metropolitan area was conducted using PAMs (Photochemical assessment monitoring system) data and CMB(Chemical Mass Balance) model8.0, in order to estimate spatial and temporal variations of VOCs source contribution in that area, and also to compare with corresponding emission inventory. VOCs data used in model calculation were collected at 6 different sites of PAMs(Seokmori, Guwoldong, Simgokdong, Bulgwangdong, Jeongdong and Yangpyeong) and 22 out of 56 VOCs species were analyzed from June 2002 to march 2003 and used for CMB model estimation. The result showed that vehicle exhaust, coating and energy combustion were important sources of VOCs in Seoul metropolitan area, averaging 32.6%, 25.5% and 25.1%, respectively. In this study as well as other references, it was revealed that vehicle exhaust is the main contributor of urban area VOCs, but there is remarkable contrast between emission inventory and model estimation. Vehicle exhaust portion is seriously underestimated while coating is usually overestimated in emission estimates, compared to CMB results. Therefore, it is considered to assert and confirm the uncertainty of emission estimates and clarify the distinction between two other source apportionment methods.

A study on Estimation of NO2 concentration by Statistical model (통계모형을 이용한 NO2 농도 예측에 관한 연구)

  • Jang Nan-Sim
    • Journal of Environmental Science International
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    • v.14 no.11
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    • pp.1049-1056
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    • 2005
  • [ $NO_2$ ] concentration characteristics of Busan metropolitan city was analysed by statistical method using hourly $NO_2$ concentration data$(1998\~2000)$ collected from air quality monitoring sites of the metropolitan city. 4 representative regions were selected among air quality monitoring sites of Ministry of environment. Concentration data of $NO_2$, 5 air pollutants, and data collected at AWS was used. Both Stepwise Multiple Regression model and ARIMA model for prediction of $NO_2$ concentrations were adopted, and then their results were compared with observed concentration. While ARIMA model was useful for the prediction of daily variation of the concentration, it was not satisfactory for the prediction of both rapid variation and seasonal variation of the concentration. Multiple Regression model was better estimated than ARIMA model for prediction of $NO_2$ concentration.

Artificial Intelligence-Based Descriptive, Predictive, and Prescriptive Coating Weight Control Model for Continuous Galvanizing Line

  • Devraj Ranjan;G. R. Dineshkumar;Rajesh Pais;Mrityunjay Kumar Singh;Mohseen Kadarbhai;Biswajit Ghosh;Chaitanya Bhanu
    • Corrosion Science and Technology
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    • v.23 no.3
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    • pp.228-234
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    • 2024
  • Zinc wiping is a phenomenon used to control zinc-coating thickness on steel substrate during hot dip galvanizing by equipment called air knife. Uniformity of zinc coating weight in length and width profile along with surface quality are most critical quality parameters of galvanized steel. Deviation from tolerance level of coating thickness causes issues like overcoating (excess consumption of costly zinc) or undercoating leading to rejections due to non-compliance of customer requirement. Main contributor of deviation from target coating weight is dynamic change in air knives equipment setup when thickness, width, and type of substrate changes. Additionally, cold coating measurement gauge measure coating weight after solidification but are installed down the line from air knife resulting in delayed feedback. This study presents a coating weight control model (Galvantage) predicting critical air knife parameters air pressure, knife distance from strip and line speed for coating control. A reverse engineering approach is adopted to design a predictive, prescriptive, and descriptive model recommending air knife setups that estimate air knife distance and expected coating weight in real time. Implementation of this model eliminates feedback lag experienced due to location of coating gauge and achieving setup without trial-error by operator.

Estimation of Air Pollutant Emission Factors for Motorcycle (이륜자동차의 대기오염물질 배출계수 산정을 위한 연구)

  • Lim, Jae-Hyun;Kim, Hyun-Min;Lee, Sang-Moon;Kang, Hee-Jun;Lim, Yoon-Sung;Seo, Choong-Yeol;Kim, Jong-Choon
    • Journal of Korean Society for Atmospheric Environment
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    • v.26 no.1
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    • pp.69-76
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    • 2010
  • While increased use of motor cycles in the recent years for various demands could worsen air quality, only few studies have been conducted on estimation of emission factors and characterization of emissions from motorcycle. In this study, emissions from selected six models of motorcycle based on largest market share and production rate were investigated. To investigate gaseous and carbonaceous air pollutants, such as carbon monoxide (CO), total hydrocarbon (THC), nitrogen oxide ($NO_x$), elemental carbon (EC) and organic carbon (OC), total 124 motorcycles between 2003 and 2007 model year were tested with regulatory driving conditions, such as CVS-40 and CVS-47 mode. These motorcycles were further sub-categorized based on their displacement (< 50 cc, 50~150 cc, and $\geq$ 150 cc), type of stroke (2- and 4 strokes) and model year (2003~2005 and 2006~2007). Tested motorcycles with recent model year (2006~2007) exhibited less emissions of regulatory gaseous and carbonaceous air pollutants compared to old model year (2003~2005). Chemical analysis showed that CO present in highest concentration followed by THC and $NO_x$ for all tested motorcycles. Interestingly, two strokes motorcycle produced higher THC emission but less CO and $NO_x$ than those of four strokes. For all types of displacement and stroke, emission factors (gram per kilometer) of THC and CO except $NO_x$ with recent model year (2006~2007) showed decreased trend compared to old model year (2003~2005). In addition to this, due to mixed combustion between gasoline fuel and lubricant, two strokes motorcycle showed OC > EC emission trend.

A Numerical Investigation of Indoor Air Quality with CFD

  • Sin V. K;Sun H. I
    • 한국전산유체공학회:학술대회논문집
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    • 2003.10a
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    • pp.207-208
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    • 2003
  • Increasing interest in indoor air quality (IAQ) control has been found because of its serious effect on human health. To evaluate IAQ, thermal comfort in terms of temperature and velocity distributions of indoor air has to be analyzed in detail. Choice of location for installation of air-conditioner in a building will affect the performance of cooling effect and thermal comfort on the occupants, which in turn will affect the indoor air quality (IAQ) of the building. In this paper, we present a discussion on the proper location of the air-conditioner in order to obtain good thermal comfort for occupant of a typical bedroom in Macao. A set of carefully designed numerical experiments is run with the Computational Fluid Dynamics (CFD) software FLOVENT 3.2 [1]. Reynolds averaged Navier-Stokes equations are solved with finite volume technique and turbulence effects upon the mean flow characteristics is modeled with the k - & model. Assumption of steady state environment is made and only convective and conductive heat transfer from the occupant and air-conditioner are being concerned.

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Evaluation of Temperature and Precipitation on Integrated Climate and Air Quality Modeling System (ICAMS) for Air Quality Prediction (대기질 예측을 위한 기후·대기환경 통합모델링시스템 (ICAMS)의 기온 및 강수량 예측 능력 평가)

  • Choi, Jin-Young;Kim, Seung-Yeon;Hong, Sung-Chul;Lee, Jae-Bum;Song, Chang-Keun;Lee, Hyun-Ju;Lee, Suk-Jo
    • Journal of Korean Society for Atmospheric Environment
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    • v.28 no.6
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    • pp.615-631
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    • 2012
  • This study provides an evaluation for capability of Integrated Climate and Air quality Modeling System (ICAMS) on future regional scale climate projection. Temperature and precipitation are compared between ground-level observation data and results of regional models (MM5) for the past 30 years over the Korean peninsula. The ICAMS successfully simulates the local-scale spatial/seasonal variation of the temperature and precipitation. The probability distribution of simulated daily mean and minimum temperature agree well with the observed patterns and trends, although mean temperature shows a little cold bias about $1^{\circ}C$ compared to observations. It seems that a systematic cold bias is mostly due to an underestimation of maximum temperature. In the case of precipitation, the rainfall in winter and light rainfall are remarkably simulated well, but summer precipitation is underestimated in the heavy rainfall phenomena of exceeding 20 mm/day. The ICAMS shows a tendency to overestimate the number of washout days about 7%. Those results of this study indicate that the performance of ICAMS is reasonable regarding to air quality predication over the Korean peninsula.

Development of an Integrated Multizone Model for Indoor Air Environment Prediction (실내공기환경 예측을 위한 통합 다구획 모델의 개발)

  • Cho, Seok-Ho
    • Journal of Environmental Science International
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    • v.17 no.9
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    • pp.993-1003
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    • 2008
  • Interior space in most buildings is divided into several zones. The most important factors relating to the indoor air environment are temperature, airflow, humidity, and contaminant concentration. An integrated multizone model to predict these environmental factors simultaneously was developed. Also, a computer program for this model was written by the language of VISUAL BASIC. The proposed model was applied to a apartment with five rooms that had been tested by Chung. Comparison of predicted results by this study with measured results by Chung showed that their variations were within 14% for airflow rates, 1% for temperatures, 12% for humidities, and 5% for concentrations. It was seen that the opening operation schedule of building has a significant effect on the air moisture md contaminant removal. Thus, this model may be available for predicting the indoor air environment and may be contributed to design the ventilation plan for controling of indoor air quality.

Analysis of Seasonal Characteristics about Long-Range Transport and Deposition of Sulfur (황(S)의 장거리 이동 및 침적량에 대한 계절별 특성 분석)

  • Hong, Sung-Chul;Lee, Jae-Bum;Moon, Kyung-Jung;Song, Chang-Keun;Bang, Cheol-Han;Choi, Jin-Young;Kim, Jeong-Soo;Hong, You-Deog
    • Journal of Korean Society for Atmospheric Environment
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    • v.26 no.1
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    • pp.34-47
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    • 2010
  • Long-range transport of air pollutants was simulated using Comprehensive Acid Deposition Model (CADM) and Yonsei University-Sulfuric Acid Deposition Model (YU-SADM). For the simulation, weather patterns that represent the four seasons were derived through a clustering analysis with 5-years of meteorological data. The simulation result showed that in spring, influenced by strong low pressure from China, air pollutants of moved to the Korean Peninsula. In summer, humid air moved into the Korean Peninsula across the Yellow Sea while the north pacific high pressure extended, making the concentration of air pollutants lower than that in the other seasons. In autumn, air pollutants were transported by the northwest wind caused by the movement of high pressure over the Yellow Sea, while in winter air pollutants were influenced by northwest winds from continental highs. The amount of air pollutants in each season showed that high amount of pollutants were transported in winter due to the strong northwest wind. The in-flows were 3 to 8 times higher than those of the other seasons, and out-flows were about as twice as high. The amount of wet deposition in summer and autumn increased significantly compared to the amount in the other seasons due to the increase of rainfall. Source-receptor relationship analysis for sulfur showed that 70 to 91 precent of the total deposition came from the self-contribution by the Korean Peninsula. In winter, contribution from China was about 25 percent of the total deposition which was higher amount than any other season.

Analysis of Supply Airflow Control by a Stratified Thermal Model in a VAV System

  • Kim, Seo-Young;Moon, Jeong-Woo;Cho, Hyung-Hee
    • International Journal of Air-Conditioning and Refrigeration
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    • v.9 no.3
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    • pp.46-56
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    • 2001
  • The present study concerns the numerical simulation of a supply airflow control in a variable air volume (VAY) system. A stratified thermal model (multi-zone model) is suggested to predict a local thermal response of an air-conditioned space. The effects of various thermal parameters such as the cooling system capacity, the thermal mass of an air-conditioned space, the time delay of thermal effect, and the building envelope heat transmission are investigated. Further, the influence of control parameters such as the supply air temperature, the PI control factor and the thermostat location on a VAV system is quantitatively delineated. The results obtained show that the previous homogeneous lumped thermal model (single zone model) may overestimate the time taken to the set point temperature. It is also found that there exist the appropriate ranges of the control parameters for the optimal airflow control of the VAV system.

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A Study on Particulate Matter Forecasting Improvement by using Asian Dust Emissions in East Asia (황사배출량을 적용한 동아시아 미세먼지 예보 개선 연구)

  • Choi, Daeryun;Yun, Huiyoung;Chang, Limseok;Lee, Jaebum;Lee, Younghee;Myoung, Jisu;Kim, Taehee;Koo, Younseo
    • Journal of the Korean Society of Urban Environment
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    • v.18 no.4
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    • pp.531-546
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    • 2018
  • Air quality forecasting system with Asian dust emissions was developed in East Asia, and $PM_{10}$ forecasting performance of chemical transport model with Asian dust emissions was validated and evaluated. The chemical transport model (CTM) with Asian dust emission was found to supplement $PM_{10}$ concentrations that had been under-estimated in China regions and improved statistics for performance of CTM, although the model were overestimated during some periods in China. In Korea, the prediction model adequately simulated inflow of Asian dust events on February 22~24 and March 16~17, but the model is found to be overestimated during no Asian dust event periods on April. However, the model supplemented $PM_{10}$ concentrations, which was underestimated in most regions in Korea and the statistics for performance of the models were improved. The $PM_{10}$ forecasting performance of air quality forecasting model with Asian dust emissions tends to improve POD (Probability of Detection) compared to basic model without Asian dust emissions, but A (Accuracy) has shown similar or decreased, and FAR (False Alarms) have increased during 2017.Therefore, the developed air quality forecasting model with Asian dust emission was not proposed as a representative $PM_{10}$ forecast model in South Korea.