• Journal of the Korean earth science society
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• v.32 no.3
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• pp.276-293
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• 2011

In this study a modeling system consisting of Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emissions (SMOKE), the Community Multiscale Air Quality (CMAQ) model, and the CMAQ-Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) model has been applied to estimate enhancements of $PM_{10}$ during Asian dust events in Korea. In particular, 5 experimental formulas were applied to the WRF-SMOKE-CMAQ (MADRID) model to estimate Asian dust emissions from source locations for major Asian dust events in China and Mongolia: the US Environmental Protection Agency (EPA) model, the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model, and the Dust Entrainment and Deposition (DEAD) model, as well as formulas by Park and In (2003), and Wang et al. (2000). According to the weather map, backward trajectory and satellite image analyses, Asian dust is generated by a strong downwind associated with the upper trough from a stagnation wave due to development of the upper jet stream, and transport of Asian dust to Korea shows up behind a surface front related to the cut-off low (known as comma type cloud) in satellite images. In the WRF-SMOKE-CMAQ modeling to estimate the PM10 concentration, Wang et al.'s experimental formula was depicted well in the temporal and spatial distribution of Asian dusts, and the GOCART model was low in mean bias errors and root mean square errors. Also, in the vertical profile analysis of Asian dusts using Wang et al's experimental formula, strong Asian dust with a concentration of more than $800\;{\mu}g/m^3$ for the period of March 31 to April 1, 2007 was transported under the boundary layer (about 1 km high), and weak Asian dust with a concentration of less than $400\;{\mu}g/m^3$ for the period of 16-17 March 2009 was transported above the boundary layer (about 1-3 km high). Furthermore, the difference between the CMAQ model and the CMAQ-MADRID model for the period of March 31 to April 1, 2007, in terms of PM10 concentration, was seen to be large in the East Asia area: the CMAQ-MADRID model showed the concentration to be about $25\;{\mu}g/m^3$ higher than the CMAQ model. In addition, the $PM_{10}$ concentration removed by the cloud liquid phase mechanism within the CMAQ-MADRID model was shown in the maximum $15\;{\mu}g/m^3$ in the Eastern Asia area.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.5
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• pp.435-444
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• 2017

In this study, we investigated the effect of aerosol feedback on $PM_{10}$ simulation using a two-way coupled air quality model (WRF-CMAQ). $PM_{10}$ concentration over Korea in January 2014 was simulated, and the aerosol feedback effect on the simulated solar radiation was intensively examined. Two $PM_{10}$ simulations were conducted using the WRF-CMAQ model with (FB) and without(NFB) the aerosol feedback option. We find that the simulated solar radiation in the west part of Korea decreased by up to $-80MJ/m^2$ due to the aerosol feedback effect. The feedback effect was significant in the west part of Korea, showing high $PM_{10}$ estimates due to dense emissions and its long-range transport from China. The aerosol feedback effect contributed to the decreased rRMSE(relative Root Mean Square Error) for solar radiation (47.58% to 30.75%). Aerosol feedback effect on the simulated solar radiation was mainly affected by concentration of $PM_{10}$. Moreover, FB better matched the observed solar radiation and $PM_{10}$ concentration than NFB, implying that taking into account the aerosol direct effects resulted in the improved modeling performance. These results indicate that aerosol feedback effects can play an important role in the simulation of solar radiation over Korean Peninsula.

• Journal of the Korean earth science society
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• v.34 no.3
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• pp.209-223
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• 2013

The purpose of this study was to estimate the contributed concentration of each emission source to $CH_4$ by verifying the simulated concentration of $CH_4$ in the Korean peninsula, and then to compare the $CH_4$ emission used to the $CH_4$ simulation with that of a box model. We simulated the Weather Research Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model to estimate the mean concentration of $CH_4$ during the period of April 1 to 22 August 2010 in the Korean peninsula. The $CH_4$ emissions within the model were adopted by the anthropogenic emission inventory of both the EDGAR of the global emissions and the GHG-CAPSS of the green house gases in Korea, and by the global biogenic emission inventory of the MEGAN. These $CH_4$ emission data were validated by comparing the $CH_4$ modeling data with the concentration data measured at two different location, Ulnungdo and Anmyeondo in Korea. The contributed concentration of $CH_4$ estimated from the domestic emission sources in verification of the $CH_4$ modeling at Ulnungdo was represented in about 20%, which originated from $CH_4$ sources such as stock farm products (8%), energy contribution and industrial processes (6%), wastes (5%), and biogenesis and landuse (1%) in the Korean peninsula. In addition, one that transported from China was about 9%, and the background concentration of $CH_4$ was shown in about 70%. Furthermore, the $CH_4$ emission estimated from a box model was similar to that of the WRF-CMAQ model.

• Journal of Environmental Impact Assessment
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• v.27 no.5
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• pp.509-520
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• 2018

The impact of meteorological condition on surface $PM_{10}$ concentrations in South Korea was quantitatively simulated from 2010 to 2014 using WRF (ver.3.8.1) and CMAQ (5.0.2) model. The result showed that seasonal standard deviations of PM10 induced by change of weather conditions were $4.8{\mu}g/m^3$, $1.7{\mu}g/m^3$, $1.7{\mu}g/m^3$, $4.2{\mu}g/m^3$ for spring, summer, autumn and winter compared to 2010, respectively, with the annual mean standard deviation of about $2.6{\mu}g/m^3$. The results of 18 regions in South Korea showed standard deviation of more than $1{\mu}g/m^3$ in all regions and more than $2{\mu}g/m^3$ in Seoul, Northern Gyeonggi, Southern Southern Gyeonggi, Western Gangwon and Northern Chungcheong in South Korea.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2016.10a
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• pp.70-70
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• 2016

• Journal of the Korean earth science society
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• v.34 no.7
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• pp.669-680
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• 2013

Ozone sensitivity analysis with respect to $NO_x$ is conducted around the south-eastern area of the Korean Peninsula. WRF-CMAQ modeling system is used to simulate a local circulation and high ozone episode day. To analyze the sensitivity, the adjoint model for CMAQ is adopted in this study. The purpose of current study is to investigate the location that affects a day time ozone concentration of these receptors on the high ozone episode day. Adjoint sensitivity analysis for Daegu shows two areas of influence. One is the range from the neighboring location to Pohang and it affects mainly on the same day as receptor time. The other is the remote south-eastern area from Daegu. This remote influence area suggests that $NO_x$ emitted on the previous day can change the ozone concentration at receptor time. The influence area for Busan, on the other hand, is originated only from the emission on the previous day because the sea-breeze occurred on the episode day makes low influence of surrounding emission. The cross sectional analysis reveals that $NO_x$ advection is important not only near the surface of land but also around the height of boundary layer.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.1
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• pp.11-18
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• 2017

The performance of a modeling system consisting of WRF model v3.3 and CMAQ model v4.7.1 for forecasting $PM_{2.5}$ concentrations were evaluated during the period May 2012 through December 2014. Twenty-four hour averages of $PM_{2.5}$ and its major components obtained through filter sampling at the Bulgwang intensive measurement station were used for comparison. The mean predicted $PM_{2.5}$ concentration over the entire period was 68% of the mean measured value. Predicted concentrations for major components were underestimated except for $NO_3{^-}$. The model performance for $PM_{2.5}$ generally tended to degrade with increasing the concentration level. However, the mean fractional bias (MFB) for high concentration above the $80^{th}$ percentile fell within the criteria, the level of accuracy acceptable for standard model applications. Among three bias correction methods, the ratio adjustment was generally most effective in improving the performance. Albeit for limited test conditions, this analysis demonstrated that the effects of bias correction were larger when using the data with a larger bias of predicted values from measurement values.

• Atmosphere
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• v.32 no.4
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• pp.341-351
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• 2022

Recently, interest in the possibility of a washout effect using artificial rain enhancement technology to reduce high-concentration fine dust is growing. Therefore, in this study, the reduction rate of PM₁₀ concentration according to the amount of artificial rain enhancement was calculated during Asian Dust event which occurred over the Korean Peninsula on March 29, 2021 using air quality model [i.e., Community Multiscale Air Quality (CMAQ)] combined with the mesoscale model for artificial rain enhancement (i.e., WRF-MMS). According to WRF-MMS, the washout effect lasted 5 hours, and the maximum precipitation rate was calculated to be 1.5 mm hr^-1. According the CMAQ results, the PM₁₀ reduction rate was up to 22%, and the affected area was calculated to be 6.4 times greater than that of the artificial rain enhancement area. Even if the maximum amount of precipitation per hour is lowered to 0.8 mm hr^-1 (about 50% level), the PM₁₀ reduction rate appears to be up to 16%. In other words, it is believed that this technique can be used as a direct method for reducing high-concentration fine dust even when the artificial rain enhancement effect is weak.

• Journal of Environmental Impact Assessment
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• v.24 no.5
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• pp.456-471
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• 2015

Emission source term is one of the strong controlling factors for the air quality simulation capability, particularly over the urban area. Ulsan is an industrial area and frequently required to simulate for environmental assessment. In this study, two CAPSS (Clean Air Policy Support System) emission data; CAPSS-2003 and CAPSS-2010 in Ulsan, were employed as an input data for WRF-CMAQ air quality model for emission assessment. The simulated results were compared with observations for the local emission dominant synoptic conditions which had negative vorticities and lower geostrophic wind speed at 850hPa weather maps. The measurements of CO, $NO_2$, $SO_2$ and $PM_{10}$ concentrations were compared with simulations and the 'scaling factors' of emissions for CO, $NO_2$, $SO_2$, and $PM_{10}$ were suggested in in aggregative and quantitative manner. The results showed that CAPSS-2003 showed no critical discrepancies of CO and $NO_2$ observations with simulations, while $SO_2$ was overestimated by a factor of more than 12, while $PM_{10}$ was underestimated by a factor of more than 20 times. However, CAPSS-2010 case showed that $SO_2$ and $PM_{10}$ emission were much more improved than CAPSS-2003. However, $SO_2$ was still overestimated by a factor of more than 2, and $PM_{10}$ underestimated by a factor of 5, while there was no significant improvement for CO and $NO_2$ emission. The estimated factors identified in this study can be used as'scaling factors'for optimizing the emissions of air pollutants, particularly $SO_2$ and $PM_{10}$ for the realistic air quality simulation in Ulsan.

• Journal of Environmental Impact Assessment
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• v.28 no.3
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• pp.183-200
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• 2019

In this study, the characteristics of seasonal $PM_{2.5}$ behavior in South Korea and other Northeast Asian regions were analyzed by using the $PM_{2.5}$ ground measurement data, weather data, WRF and CMAQ models. Analysis of seasonal $PM_{2.5}$ behavior in Northeast Asia showed that $PM_{2.5}$ concentration at 6 IMS sites in South Korea was increased by long-distance transport and atmospheric congestion, or decreased by clean air inflow due to seasonal weather characteristics. As a result of analysis by applying BFM to air quality model, the contribution from foreign countries dominantly influenced the $PM_{2.5}$ concentrations of Baengnyeongdo due to the low self-emission and geographical location. In the case of urban areas with high self-emissions such as Seoul and Ulsan, the $PM_{2.5}$ contribution from overseas was relatively low compared to other regions, but the standard deviation of the season was relatively high. This study is expected to improve the understanding of the air pollutant phenomenon by analyzing the characteristics of $PM_{2.5}$ behavior in Northeast Asia according to the seasonal weather condition change. At the same time, this study can be used to establish the air quality policy in the future, knowing that the contribution of $PM_{2.5}$ concentration to the domestic and overseas can be different depending on the regional emission characteristics.