• 대기
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• 제29권1호
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• pp.1-12
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• 2019

For the allergy patient who needs to know the situation about the extent of pollen risk, the National Institute of Meteorological Sciences developed a pollen forecasting system based on the Community Multiscale Air Quality Modeling (CMAQ). In the old system, pollen emission from the oak was estimated just based on the airborne concentration and meteorology factors, resulted in high uncertainty. For improving the quality of current pollen forecasting system, therefore the estimation of pollen emission is now corrected based on the observation of pollen emission at the oak forest to better reflect the real emission pattern. In this study, the performance of the previous (NIMS2014) and current (NIMS2016) model system was compared using observed oak pollen concentration. Daily pollen concentrations and emissions were simulated in pollen season 2016 and accuracy of onset and end of pollen season were evaluated. In the NIMS2014 model, pollen season was longer than actual pollen season; The simulated pollen season started 6 days earlier and finished 13.25 days later than the actual pollen season. The NIMS2016 model, however, the simulated pollen season started only 1.83 days later, and finished 0.25 days later than the actual pollen season, showing the improvement to predict the temporal range of pollen events. Also, the NIMS2016 model shows better performance for the prediction of pollen concentration, while there is a still large uncertainty to capture the maximum pollen concentration at the target site. Continuous efforts to correct these problems will be required in the future.

• 한국지구과학회지
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• 제34권3호
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• pp.209-223
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• 2013

이 연구의 목적은 한반도에서 $CH_4$ 농도의 수치모의 검증을 통하여 $CH_4$ 배출원의 기여 농도를 추정하는 것이고, 이 수치모의에 사용된 $CH_4$ 배출량을 상자모델로부터 추정된 $CH_4$ 배출량과 비교하는 것이다. 한반도에서 2010년 4월 1일부터 8월 22일까지 $CH_4$의 평균 농도를 추정하기 위해 WRF-CMAQ 모델이 사용되었다. 모델에서 $CH_4$ 배출량은 전지구 배출량인 EDGAR와 한국에서의 온실기체 배출량인 GHG-CAPSS로부터 인위적 배출 인벤토리와 전지구 자연적 인벤토리인 MEGAN이 적용되었다. 이들 $CH_4$ 배출량은 안면도 및 울릉도에서 측정된 $CH_4$ 농도와 모델링 농도 자료를 비교함으로써 검증되었다. 울릉도에서 국내 배출원으로부터 추정된 $CH_4$의 기여 농도는 약 20%로 나타났고, 이것은 한반도 내 농장(8%), 에너지 기여 및 산업공정(6%), 일반폐기물(5%), 생체 및 토지이용(1%) 등 $CH_4$ 배출원으로부터 기원하였다. 그리고 중국으로부터 수송된 $CH_4$의 기여 농도는 약 9%였고, 나머지 배경농도는 약 70%로 나타났다. 박스모델로 추정된 $CH_4$ 배출량은 WRF-CMAQ 모델에서 사용한 $CH_4$ 배출량과 유의미한 결과를 얻었다.

• 한국환경과학회지
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• 제25권1호
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• pp.85-97
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• 2016

A comparison of ozone simulations in the seoul metropolitan region (SMR) using the community multiscale air quality (CMAQ) model with SAPRC99 and CB05 chemical mechanisms (i.e. EXP-SP99 and EXP-CB05) has been conducted during four seasons of 2012. The model results showed that the differences in average ozone concentrations between the EXP-SP99 and EXP-CB05 were found to be large in summer, but very small in the other seasons. This can be attributed that the SAPRC99 tends to produce more ozone than the CB05 in urban area like the SMR with low VOC/NOx ratio under high ozone conditions. Through quantitative comparison between two mechanisms for the summer, it was found that the average ozone concentrations from the EXP-SP99 were about 3 ppb higher than those from the EXP-CB05 and agreed well with the observations. Horizontal differences in ozone concentrations between SAPRC99 and CB05 showed that significant differences were found in southern part of the SMR and over the sea near the coast in summer.

• 한국지구과학회지
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• 제42권2호
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• pp.149-163
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• 2021

본 연구에서는 광화학 대기질 모델인 CMAQ을 활용해 화력발전소 배출량 제거에 따른 O3 농도의 변화 특성을 분석하였다. 하동 화력발전소를 대상으로 주변 지역의 O3 농도 변화에 대한 발전소 배출량의 영향을 조사하기 위해 하동 화력발전소의 배출량 제거 전과 후의 CMAQ 수치 모의를 수행하였다. 수치 모의 결과 O3의 주요 전구 물질인 NOx (-18.87%)와 VOCs (-11.27%)의 농도가 감소한 반면에 O3 (25.24%)의 농도는 증가한 것으로 나타났다. 화력발전소 배출량 제거로 인한 NO와 O3 농도의 상대적인 변화를 비교해 본 결과 높은 음의 상관관계(R= -0.72)를 나타내는 것이 확인되었다. 이러한 결과는 O3의 농도 증가가 NO 농도 감소로 인한 O3의 적정 효과 완화로 설명 될 수 있음을 의미한다. 해당 지역의 O3의 농도 증가가 NO의 농도 감소에 주로 영향을 받은 이유는 해당 지역이 VOC-limited (i.e., NOx-saturated) 지역이기 때문으로 분석되었다. 이러한 결과는 특정 지역의 O3의 농도가 단순히 배출량의 증감에 따라 비례하게 나타나지 않을 수 있다는 것을 암시한다. 따라서 화력발전소 배출량 저감 조치로 인한 대기 중 O3 농도 개선 효과를 정확히 예측 및 평가하기 위해서는 지역 별 O3의 생성 및 소멸 기작에 대한 심도 있는 이해가 필요하다.

• 한국지구과학회지
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• 제34권7호
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• pp.669-680
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• 2013

한반도 동남 지역에서 고농도 오존이 발생한 사례에 대해 $NO_x$에 대한 오존의 수반민감도를 살펴보았다. 사례일에 지배적이었던 국지 순환과 고농도 오존을 모의하기 위해 WRF-CMAQ 모델을 사용하였다. 수반민감도 분석을 위해 CMAQ의 수반 모델을 적용하였다. 본 연구의 목적은 고농도 오존에 주변지역이 미친 영향을 살펴본 수용지 중심의 민감도 분석이다. 또한, 행정 구역별 기여도를 정량적으로 산정하였는데, 대구를 수용지로 하는 민감도 분석 결과 영향지역은 대구에 인접하여 포항으로 이어지는 영역과 남동쪽으로 떨어진 넓은 지역으로 나타났다. 첫 번째 영역은 고농도 사례일 당일에 배출된 $NO_x$의 민감도가 주로 나타났고 두 번째 영역은 전 날 배출에 의한 영향이었다. 반면, 부산을 수용지로 한 경우 사례일 당일 주간의 해풍의 영향으로 같은 날의 $NO_x$ 배출 효과 보다는 전 날 배출되었던 농도에 대한 민감도가 더 중요하였다. 민감도 영향지역에 대한 단면도 분석 결과 지표부근의 $NO_x$ 수송과 함께 상층에서 이류되는 영향도 중요하였다.

• 한국환경과학회지
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• 제26권10호
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• pp.1167-1180
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• 2017

Numerical Weather Prediction (NWP) models such as the Weather Research and Forecasting (WRF) model are essential for forecasting one-day-ahead solar irradiance. In order to evaluate the performance of the WRF in forecasting solar irradiance over the Korean Peninsula, we compared WRF prediction data from 2008 to 2010 corresponding to weather observation data (OBS) from the Korean Meteorological Administration (KMA). The WRF model showed poor performance at polluted regions such as Seoul and Suwon where the relative Root Mean Square Error (rRMSE) is over 30%. Predictions by the WRF model alone had a large amount of potential error because of the lack of actual aerosol radiative feedbacks. For the purpose of reducing this error induced by atmospheric particles, i.e., aerosols, the WRF model was coupled with the Community Multiscale Air Quality (CMAQ) model. The coupled system makes it possible to estimate the radiative feedbacks of aerosols on the solar irradiance. As a result, the solar irradiance estimated by the coupled system showed a strong dependence on both the aerosol spatial distributions and the associated optical properties. In the NF (No Feedback) case, which refers to the WRF-only stimulated system without aerosol feedbacks, the GHI was overestimated by $50-200W\;m^{-2}$ compared with OBS derived values at each site. In the YF (Yes Feedback) case, in contrast, which refers to the WRF-CMAQ two-way coupled system, the rRMSE was significantly improved by 3.1-3.7% at Suwon and Seoul where the Particulate Matter (PM) concentrations, specifically, those related to the $PM_{10}$ size fraction, were over $100{\mu}g\;m^{-3}$. Thus, the coupled system showed promise for acquiring more accurate solar irradiance forecasts.

• Asian Journal of Atmospheric Environment
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• 제3권1호
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• pp.1-8
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• 2009

Enhancement of aerosol optical thickness (AOT) and surface aerosol mass concentration in Korea for an active forest fire episode in Northeast Asia were estimated by Community Multi-scale Air Quality (CMAQ) model. MODIS/TERRA remote detects of fires in Northeast Asia for May 2003 gave a constraint for estimation of wildfire emissions with an NDVI distribution for recent five years. The simulated wildfire plumes and enhancement of AOT were evaluated and well resolved by comparing multiple satellite observations such as MODIS, TOMS, and others. Scatter plots of observed daily mean aerosol extinction coefficient versus $PM_{10}$ concentration in ground level in Korea showed distinctively different trends based on the ambient relative humidity.

• Asian Journal of Atmospheric Environment
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• 제12권2호
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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.

• 한국환경과학회지
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• 제32권8호
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• pp.595-611
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• 2023

The purpose of this study is to improve the daily prediction results of PM2.5 from the air quality diagnosis and evaluation system operated by the Busan Institute of Health and Environment in real time. The air quality diagnosis and evaluation system is based on the photochemical numerical model, CMAQ (Community multiscale air quality modeling system), and includes a 3-day forecast at the end of the model's calculation. The photochemical numerical model basically has limitations because of the uncertainty of input data and simplification of physical and chemical processes. To overcome these limitations, this study applied DNN (Deep Neural Network), a deep learning technique, to the results of the numerical model. As a result of applying DNN, the r of the model was significantly improved. The r value for GFS (Global forecast system) and UM (Unified model) increased from 0.77 to 0.87 and 0.70 to 0.83, respectively. The RMSE (Root mean square error), which indicates the model's error rate, was also significantly improved (GFS: 5.01 to 6.52 ug/m³ , UM: 5.76 to 7.44 ug/m³ ). The prediction results for each concentration grade performed in the field also improved significantly (GFS: 74.4 to 80.1%, UM: 70.0 to 77.9%). In particular, it was confirmed that the improvement effect at the high concentration grade was excellent.

• 한국대기환경학회지
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• 제33권1호
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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.