• Journal of Korean Society for Atmospheric Environment
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• v.24 no.4
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• pp.423-438
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• 2008

BEIS2 (Biogenic Emissions Inventory System version 2) and BEIS3.12 (BEIS version 3.12) were used to estimate hourly biogenic emissions over South Korea using a set of vegetation and meteorological data simulated with the MM5 (Mesoscale Model version 5). Two biogenic emission models utilized different emission factors and showed different responses to solar radiations, resulting in about $10{\sim}20%$ difference in the nationwide isoprene emission estimates. Among the 11-vegetation classes, it was found that mixed forest and deciduous forest are the most important vegetation classes producing isoprene emissions over South Korea comprising ${\sim}90%$ of the total. The simulated isoprene concentrations over Seoul metropolitan area show that diurnal and daily variations match relatively well with the PAMS (Photochemical Air Monitoring Station) measurements during the period of June 3${\sim}$June 10, 2004. Compared to BEIS2, BEIS3.12 yielded ${\sim}35%$ higher isoprene concentrations during daytime and presented better matches to the high peaks observed over the Seoul area. This study showed that the importance of vegetation data and emission factors to estimate biogenic emissions. Thus, it is expected to improve domestic vegetation categories and emission factors in order to better represent biogenic emissions over South Korea.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.2
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• pp.67-83
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• 2002

The coupled model (SMART) of dynamic meteorology model and particle dispersion model was developed. The numerical experiment on the relationship between change of land use and diffusion behavior in complex terrain was carried out using this model. It tried to investigate the change of particle diffusion behavior and local weather under the condition in which land-land breeze and sea breeze and mountain breeze intermingled. The numerical experiment results are as follows; 1) The more complicated local circulation field of the interaction of sea breeze, mountain breeze and Land -land breeze is formed. Then, the region circulation in which the urbanization is specific by location of the region is strengthened and is weakened. 2) Though in the region with dominant sea breeze, Land-land breeze does not appear directly, the progress of the sea wind to the inland is affected. 3) In the prediction of the air diffusion, emission high quality and accurate information of the emission site are important. That is to say, the dispersion predicting result which emission high quality and small error of the site perfectly vary for Land - land breeze in the effect may be brought about.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.21 no.4
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• pp.185-192
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• 2011

To predict contaminant concentrations within a multi-zone work environment, an air quality model in the work environment was developed. To do this, airflow equations on the basis of orifice equation were solved by using the Conte and De Boor scheme, and then equations for the conservation of mass on contaminant were solved by using the fourth-order Runge-Kutta algorithm. To validate the accuracy of simulated results, this model was applied to the controlled environment chamber that had been tested in 1998 by Chung KC. The comparison of predicted concentrations by this study with measured concentrations by the Chung KC indicated that the average deviations were 2.66, 3.35, and 3.15% for zone 1, zone 2, and zone 3, respectively. Also, this model was applied to a working plant with four zones. Thus, the results of contaminant concentration versus time were predicted according to the schedule of the openings operation, and case studies were done for four cases of the openings operation to investigate the interaction of airflow and contaminant concentration. The results indicated that opening operation schedules had a significant effect on contaminant removal efficiency. Therefore, this model might be able to apply for the design of ventilation schedules to control contaminants optimally.

• KIEAE Journal
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• v.17 no.5
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• pp.33-41
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• 2017

Purpose: Indoor air quality in residential buildings needs to be evaluated over the long term. In previous research, there has been an attempt to perform the health risk assessment of pollutants by using numerical models as a method of long-term evaluation. However, the numerical model of this precedent study has limitations that do not reflect the actual concentration distribution. Therefore, this study introduces the CRPS index, constructs a numerical model that can reflect the concentration distribution, and then presents a more accurate health risk assessment method using it. At this time, the pollutants are toluene, which is a typical material released from building materials. Method: CRPS index was applied to existing numerical model to reflect concentration distribution. This was used to calculate concentrations at adult breathing area and to use them for exposure assessment in a health risk assessment. After that, we entered adult data and conducted a health risk assessment of toluene. Results: The non-carcinogenic risk of toluene was calculated to be 0.0060. This is 5% smaller than the existing numerical model, meaning that it is more accurate to predict the pollutant risks. This value is also lower than the US EPA reference value of 1. Therefore, under the conditions of this study, long-term exposure of adults to toluene has no impact on health.

• Asian Journal of Atmospheric Environment
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• v.12 no.2
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• pp.139-152
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• 2018

The urban model inter-comparison study (UMICS) was conducted in order to improve the performance of air quality models (AQMs) for simulating fine particulate matter ($PM_{2.5}$) in the Greater Tokyo Area of Japan. UMICS consists of three phases: the first phase focusing on elemental carbon (UMICS1), the second phase focusing on sulfate, nitrate and ammonium (UMICS2), and the third phase focusing on organic aerosol (OA) (UMICS 3). In UMICS2/3, all the participating AQMs were the Community Multiscale Air Quality modeling system (CMAQ) with different configurations, and they similarly overestimated $PM_{2.5}$ nitrate concentration and underestimated $PM_{2.5}$ OA concentration. Various sensitivity analyses on CMAQ configurations, emissions and boundary concentrations, and meteorological fields were conducted in order to seek pathways for improvement of $PM_{2.5}$ simulation. The sensitivity analyses revealed that $PM_{2.5}$ nitrate concentration was highly sensitive to emissions of ammonia ($NH_3$) and dry deposition of nitric acid ($HNO_3$) and $NH_3$, and $PM_{2.5}$ OA concentration was highly sensitive to emissions of condensable organic compounds (COC). It was found that $PM_{2.5}$ simulation was substantially improved by using modified monthly profile of $NH_3$ emissions, larger dry deposition velocities of $HNO_3$ and $NH_3$, and additionally estimated COC emissions. Moreover, variability in $PM_{2.5}$ simulation was estimated from the results of all the sensitivity analyses. The variabilities on CMAQ configurations, chemical inputs (emissions and boundary concentrations), and meteorological fields were 6.1-6.5, 9.7-10.9, and 10.3-12.3%, respectively.

• Atmosphere
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• v.30 no.3
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• pp.257-276
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• 2020

Faithful evaluation of the meteorological input is a prerequisite for a better understanding of air quality model performance. Despite the importance, the preliminary meteorological assessment has rarely been concerned. In this study, we aim to evaluate the performance of the Weather Research and Forecasting (WRF) model conducting a year-long high-resolution meteorological simulation in 2016 over the Seoul metropolitan area. The WRF model was configured based on a series of sensitivity simulations of initial/boundary meteorological conditions, land use mapping data, reanalysis grid nudging method, domain nesting method, and urban canopy model. The simulated results of winds, air temperature, and specific humidity in the atmospheric boundary layer (ABL) were evaluated following statistical evaluation guidance using the surface and upper meteorological measurements. The statistical evaluation results are presented. The model performance was interpreted acceptable for air quality modeling within the statistical criteria of complex conditions, showing consistent overestimation in wind speeds. Further statistical analysis showed that the meteorological model biases were highly systematic with systematic bias fractions (f_SB) of 20~50%. This study suggests that both the momentum exchange process of the surface layer and the ABL entrainment process should be investigated for further improvement of the model performance.

• Asian Journal of Atmospheric Environment
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• v.7 no.1
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• pp.25-37
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• 2013

Open biomass burning (excluding biofuels) is an important contributor to air pollution in the Asian region. Estimation of emissions from fires, however, has been problematic, primarily because of uncertainty in the size and location of sources and in their temporal and spatial variability. Hence, more comprehensive tools to estimate wildfire emissions and that can characterize their temporal and spatial variability are needed. Furthermore, an emission processing system that can generate speciated, gridded, and temporally allocated emissions is needed to support air-quality modeling studies over Asia. For these reasons, a biomass-burning emissions modeling system based on satellite imagery was developed to better account for the spatial and temporal distributions of emissions. The BlueSky Framework, which was developed by the USDA Forest Service and US EPA, was used to develop the Asian biomass-burning emissions modeling system. The sub-models used for this study were the Fuel Characteristic Classification System (FCCS), CONSUME, and the Emissions Production Model (EPM). Our domain covers not only Asia but also Siberia and part of central Asia to assess the large boreal fires in the region. The MODIS fire products and vegetation map were used in this study. Using the developed modeling system, biomass-burning emissions were estimated during April and July 2008, and the results were compared with previous studies. Our results show good to fair agreement with those of GFEDv3 for most regions, ranging from 9.7 % in East Asia to 52% in Siberia. The SMOKE modeling system was combined with this system to generate three-dimensional model-ready emissions employing the fire-plume rise algorithm. This study suggests a practicable and maintainable methodology for supporting Asian air-quality modeling studies and to help understand the impact of air-pollutant emissions on Asian air quality.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.3
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• pp.249-261
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• 2003

A three-dimensional mesoscale atmospheric dispersion modeling system consisting of the Lagrangian particle dispersion model (LPDM) and the meteorological mesoscale model (MM5) was employed to simulate the transport and dispersion of non-reactive pollutant during the nuclear spill event occurred from Sep. 31 to Oct. 3, 1999 in Tokaimura city, Japan. For the comparative analysis of numerical experiment, two more sets of foreign mesoscale modeling system; NCEP (National Centers for Environmental Prediction) and DWD (Deutscher Wetter Dienst) were also applied to address the applicability of air pollution dispersion predictions. We noticed that the simulated results of horizontal wind direction and wind velocity from three meteorological modeling showed remarkably different spatial variations, mainly due to the different horizontal resolutions. How-ever, the dispersion process by LPDM was well characterized by meteorological wind fields, and the time-dependent dilution factors ($\chi$/Q) were found to be qualitatively simulated in accordance with each mesocale meteorogical wind field, suggesting that LPDM has the potential for the use of the real time control at optimization of the urban air pollution provided detailed meteorological wind fields. This paper mainly pertains to the mesoscale modeling approaches, but the results imply that the resolution of meteorological model and the implementation of the relevant scale of air quality model lead to better prediction capabilities in local or urban scale air pollution modeling.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.2
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• pp.294-305
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• 2018

Quantitative assessment on the impact from North Korean emissions to surface particulate matter(PM) concentration in the Seoul Metropolitan Area (SMA), South Korea is conducted using a 3-dimensional chemistry transport model. Transboundary transport of air pollutants and their precursors are important to understand regional air quality in East Asian countries. As North Korea locates in the middle of main transport pathways of Chinese pollutants, quantifiable estimation of its impact is essential for policy making in South Korean air quality management. In this study, the Community Multiscale Air Quality Modeling System is utilized to simulate regional air quality and its sensitivity, using the Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment 2015 and the Clean Air Policy Support System 2013 emissions inventories for North and South Korea, respectively. Contributions were estimated by a brute force method, perturbing 50% of North and South Korean emissions. Simulations demonstrate that North Korean emissions contribute $3.89{\mu}g/m^3$ of annual surface PM concentrations in the SMA, which accounts 14.7% of the region's average. Impacts are dominant in nitrate and organic carbon (OC) concentrations, attributing almost 40% of SMA OC concentration during January and February. Clear seasonal variations are also found in North Korean emissions contribution to South Korea (and vice versa) due to seasonal characteristics of synoptic weather, especially by the change of seasonal flow patterns.

• Asian Journal of Atmospheric Environment
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• v.11 no.1
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• pp.33-36
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• 2017

China is suffering from severe air pollution especially fine $PM_{2.5}$ pollution. In 2015, the annual average $PM_{2.5}$ concentration of the 338 municipal cities was $50{\mu}g/m^3$, 78% cities at or above the prefectural level failed to comply with the $PM_{2.5}$ concentration standards. The $13^{th}$ Five-Year Plan for National Economic and Social Development set the goal that the annual average concentration of $PM_{2.5}$ in the municipal cities which failed to attain the ambient air quality standards shall be decreased by 18% by 2020 (CCCPC, 2016). In this study, an air pollution control scenario during the $13^{th}$ Five-Year Plan period was proposed and the $SO_2$, $NO_x$ and PM emission reductions in response to different measures in 31 provincial-level regions mainland China by 2020 were estimated. The air quality in the target year (2020) was simulated using the WRF-CMAQ model. The results showed that by 2020, the emissions of $SO_2$, $NO_x$ and primary PM in mainland China will be reduced by 4.19 million tons, 3.94 million tons and 4.41 million tons, a drop of 23%, 21% and 25% respectively compared with that in 2015, and the annual average concentration of $PM_{2.5}$ will decrease by 19%. Coal-fired power plant contributes the most pollutant emission reduction.