• 한국대기환경학회지
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• 제29권6호
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• pp.838-848
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• 2013

The Community Multiscale Air Quality (CMAQ) model is capable of providing high quality atmospheric chemistry profiles through the utilization of high-resolution meteorology and emissions data. However, it cannot simulate air quality accurately if input data are not appropriate and reliable. One of the most important inputs required by CMAQ is the air pollutants emissions, which determines air pollutants concentrations during the simulation. For the CMAQ simulation of Korean peninsula, we, in general, use the Korean National Emission Inventory data which are estimated by Clean Air Policy Support System (CAPSS). However, since they are not provided by model-ready emission data, we should convert CAPSS emissions into model-ready data. The SMOKE is the emission model we used in this study to generate CMAQ-ready emissions. Because processing the emissions data is very monotonous and tedious work, we have developed CAPSS2SMOKE program to convert CAPSS emissions into SMOKE-ready data with ease and effective. CAPSS2SMOKE program consists of many codes and routines such as source classification code, $PM_{10}$ to $PM_{2.5}$ ratio code, map projection conversion routine, spatial allocation routine, and so on. To verify the CAPSS2SMOKE program, we have run SMOKE using the CAPSS 2009 emissions and found that the SMOKE results inherits CAPSS emissions quite well.

• 한국환경보건학회지
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• 제49권4호
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• pp.190-200
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• 2023

Background: Gunsan has been constantly affected by pollutants generated by the Saemangeum development and the construction industry since the completion of the Saemangeum seawall on April 27, 2010. However, there are limitations to its study, such as taking into consideration weather conditions, geographical factors, and foreign inflows. Objectives: In this study, we compared the Existing-CAPSS emissions of Gunsan with Recalculated-CAPSS emissions data to analyze the differences in emissions characteristics by year (2016~2019). Methods: Using Existing data on CAPSS emissions (2016~2019) and Recalculated-CAPSS emissions (2016~2019) for Gunsan, which were Recalculated following the improvement of emissions calculations for 2020, we organized CO, NO_X, SO_X, PM₁₀, VOC_S, and NH₃ emissions by substance and investigated the differences and characteristics of the Recalculated emissions by year. Results: For Re-CO and Re-PM₁₀, the emission characteristics of CO were examined as energy industry combustion and PM₁₀ emission characteristics were examined as ship cargo from non-road transportation sources, as ship leisure sources were excluded from non-road transportation source emissions. Conclusions: Comparing the emissions of Existing-CAPSS and Recalculated-CAPSS in Gunsan, the emissions of Recalculated-CAPSS by substance decreased by 39.76% for CO, 9.98% for PM₁₀, 5.53% for VOC_S, and 9.24% for NH₃, while Re-NO_X increased by 2.86% and Re-SO_X increased by 1.97%. On the other hand, when comparing the emissions characteristics of Existing-CAPSS and Recalculated-CAPSS in Gunsan, Jeonju, and Iksan, the emission characteristics of Re-NO_X, Re-SO_X, Re-VOC_S and Re-NH₃ were similar to those of Ex-NO_X, Ex-SO_X, Ex-VOC_S, and Ex-NH₃. As such, Gunsan, Iksan, and Jeonju, showed differences in the comparison of different emission characteristics due to the geographical characteristics of the region (population, area, topography, weather factors) and the characteristics of the industrial complex (metal, petrochemical).

• 한국대기환경학회지
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• 제25권5호
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• pp.410-419
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• 2009

Generally, air pollutant emission at workplace is estimated by two methods: indirect methods using emission factors and direct methods based on CEMS (Continuous Emission Monitoring System). CAPSS (Clean Air Policy Support System) is a representative indirect method and the national air pollutant database of Korea. However, characteristics of some workplaces may create a gap between CAPSS and CEMS data. For improving of emission data accuracy, emission data of CEMS (named CleanSYS) equipped at 138 target workplaces were compared with those of CAPSS. As a result, $SO_x$ and $PM_{10}$ emission levels obtained by CAPSS were lower than those of CleanSYS. $SO_x$ and $PM_{10}$emission ratios were 61.5% and 71.2% lower respectively, showing the biggest gaps. On the other hand, $NO_x$ emission of CAPSS was higher by 10.4%. $SO_x$ showed the biggest difference in 'Energy industry combustion' and $NO_x$ did in 'Production Process' within the SCC category. $PM_{10}$ presented a large gap in 'Manufacturing industry combustion.' The differences in $SO_x$ between the two systems occurred because some large-size facilities lack pollution controllers or efficient pollution controllers. Based on this study, CAPSS emission database of Korea will improve accuracy through adopting CEMS emission system, which enables more efficient national atmospheric policies and workplace management.

• 한국대기환경학회지
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• 제30권1호
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• pp.26-36
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• 2014

The uncertainty assessment is important to improve the reliability of emission inventory data. The DARS (Data Attribute Rating System) have recommended as the uncertainty assessment technic of emission inventory by U.S. EPA (Environmental Protection Agency) EIIP (Emission Inventory Improvement Program). The DARS score is based on the perceived quality of the emission factor and activity data. Scores are assigned to four attributes; measurement/method, source specificity, spatial congruity and temporal congruity. The resulting emission factor and activity rate scores are combined to arrive at an overall confidence rating for the inventory. So DARS is believed to be a useful tool and may provide more information about inventories than the usual qualitative grading procedures (e.g. A through E). In this study, the uncertainty assessment for 2009 CAPSS (Clean Air Policy Support System) emission inventory is conducted by DARS. According to the result of this uncertainty assessment, the uncertainty for fugitive dust emission data is higher than other sources, the uncertainty of emission factor for surface coating is the highest value, and the uncertainty of activity data for motor cycle is the highest value. Also it is analysed that the improvement of uncertainty for activity data is as much important as the improvement for emission factor to upgrade the reliability of CAPSS emission inventory.

• 환경영향평가
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• 제24권5호
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• pp.456-471
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• 2015

배출량 자료는 대기질 수치모의에 있어서 큰 영향을 주는 요소로서 정확한 대기질 수치모의를 위해서 배출량 자료의 정확성과 신뢰도 향상은 대기질 모델 연구에 있어 필수적이다. 본 연구에서는 울산지역을 대상으로 2003년과 2010년 CAPSS 배출량 자료인 CAPSS-2003과 CAPSS-2010를 입력자료로 하여 WRF-CMAQ 모델을 수행하여 울산지역 배출량 지료의 타당성을 검토하였다. 우선 오염물질의 장거리 수송 영향을 배제하기 위하여 울산지역 자체 내의 배출량 영향이 우세한 종관 기상조건을 가진 사례일을 선정하고 선정된 사례일에 대해서 WRF-CMAQ모델을 수행한 후 그 결과인 CO, $NO_2$, $SO_2$, $PM_{10}$ 농도와 관측 값을 비교하여, 과소 혹은 과대 모의되는 정도를 분석하여 모의결과를 보정 할 수 있는 'scaling factor'를 제시하였다. 그 결과 CAPSS-2003을 이용한 모의결과는 CO와 $NO_2$에 대해서는 관측과 유사한 수준으로 모의하였으나 $SO_2$는 약 12배 과대모의, $PM_{10}$은 약 27배나 과소모의하는 결과를 얻었다. 반면 CAPSS-2010을 이용한 모의결과에서는 CO와 $NO_2$의 모의결과는 유사하였으며, $SO_2$는 약 2배 과대모의, $PM_{10}$은 약 5배 과소모의 하여 $SO_2$와 $PM_{10}$ 배출량이 상당히 개선됨을 확인하였다. $SO_2$와 $PM_{10}$ 역시 이전 보다는 관측에 가깝게 모의되었으나 현실적 모델링 결과를 도출하기 위해서 배출량은 향후 개선되어야 할 부분으로 판단되었다. 따라서 보다 현실적인 모델링 결과를 도출하기 위해서는 본 연구에서 제시한 울산지역 배출량의 'scaling factor'를 이용하면 보다 안정된 모델링 결과가 도출 될 것으로 판단된다.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2009년도 추계학술대회 논문집
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• pp.280-282
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• 2009

• 한국기후변화학회지
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• 제2권2호
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• pp.69-77
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• 2011

최근 화석 연료와 에너지 사용의 증가에 따라 기후변화가 심화되고 대기질이 악화되고 있으나, 국내에서는 지역별 배출 부문별 온실가스 배출량을 산정하고, 배출 특성에 관한 분석 연구가 활발히 수행되고 있지 않은 실정이다. 이에 본 연구에서는 국가 및 지자체의 온실가스 감축 정책 수립 및 추진을 지원하기 위하여 온실가스 인벤토리에 관한 국제지침(IPCC Guideline)에 따라 온실가스 및 대기오염물질 통합관리시스템(GHG-CAPSS)을 구축하고, 국내 기초자치단체 단위(시 군 구)의 부문별(산업, 수송, 상업 공공, 가정, 폐기물, 농업, 기타) 온실가스 배출량을 상향식 접근론(bottom-up approach)을 적용하여 산정하였다. 2006년도를 기준으로 국내 총 온실가스 배출량($CO_2$ eq.)은 588,011천톤/년으로 산정되었으며, 이중 산업 부문이 50.1%(294,467천톤/년)로 가장 높은 배출기여율을 나타냈고, 수송 부문 17.6%(103,255천톤/년), 상업 공공 부문 12.6%(74,309천톤/년), 가정 부문 12.6%(74,209천톤/년), 폐기물 부문 2.6%(15,358천톤/년), 농업 부문 2.5%(14,516천톤/년) 순으로 나타났다. 지역별 배출량 산정 결과, 경기도 지역의 배출량이 전체의 14.9%(87,342천톤/년)를 차지하였고, 전남 12.4%(73,067천톤/년), 경북 11%(64,814천톤/년) 순으로 나타났다.

• 한국기후변화학회지
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• 제2권3호
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• pp.203-219
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• 2011

최근 인벤토리 구축이 활발해짐에 따라 인벤토리의 정확도 및 신뢰도 평가에 대한 수요 역시 크게 증가하고 있다. 따라서 본 연구에서는 GHG-CAPSS의 신뢰도를 향상시키는데 지표로 활용될 GHG-CAPSS의 신뢰도를 평가하기 위한 방법론을 개발하는데 그 목적을 두고 있다. 본 논문에서는 GHG-CAPSS 신뢰도 평가 방법을 정성적 정량적으로 구분하였으며, 정성적 정량적 평가 결과를 종합하여 신뢰도를 결정할 수 있는 방법을 고안하여 액체 화석 연료 연소에 의한 $CO_2$ 배출량과 매립에 의한 $CH_4$ 배출량에 시범 적용하였다. 시범 적용 결과, 액체 화석 연료연소의 신뢰도 정성적 및 정량적 점수는 각각 25점(/50점), 50점(/50점)으로 최종적으로 75점으로 나타났으며, 매립에 의한 $CH_4$ 배출량의 신뢰도 정성적 및 정량적 점수는 각각 22점(/25점), 20점(/50점)으로 최종적으로 42점으로 평가되었다. 따라서 GHG-CAPSS의 액체화석연료 연소 부문과 매립 부문 배출량의 신뢰도를 평가한 결과, 두 배출원의 정성적 신뢰도는 비슷하였으나, 정량적 평가에서 큰 차이를 보였다. 이는 각 배출원 간의 불확도가 큰 편차를 보였기 때문으로 액체화석연료 연소에 의한 $CO_2$ 배출량의 경우, 신뢰도 향상을 위해 정성적 신뢰도 부분을 향상시키는 데 주력해야 하며, 매립에 의한 $CH_4$ 배출량의 경우 정량적 신뢰도 향상을 위한 연구가 필요할 것으로 사료된다. 또한, 두 배출원 모두, 신뢰도 정성 평가의 점수를 향상시키기 위해 품질 관리 절차 또는 지침서를 개발하여 품질 관리의 수준을 향상시킬 필요가 있는 것으로 사료된다.

• 한국대기환경학회지
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• 제24권3호
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• pp.284-299
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• 2008

Emission input modules was developed to produce emission input data and change some profiles for Sparse Matrix Operator Kernel Emissions (SMOKE) using Clean Air Policy Support System (CAPSS)'s activities and previous studies. Specially, this study was focused to improve chemical speciation and temporal allocation profiles of SMOKE. At first, SCC cord mapping was done. 579 SCC cords of CAPSS were matched with EPA's one. Temporal allocation profiles were changed using CAPSS monthly activities. And Chemical speciation profiles were substituted using Kang et al. (2000) and Lee et al. (2005) studies and Kim et al. (2005) study. Simulation in Seoul Metropolitan Area (Seoul, Incheon, Gyeonggi) using MM5, SMOKE and CMAQ modeling system was done for effect analysis of changed input modules of SMOKE. Emission model results adjusted with new input modules were slightly changed as compared to using EPA's default modules. SMOKE outputs shows that aldehyde emissions were decreased 4.78% after changing chemical profiles, increased 0.85% after implementing new temporal profiles. Toluene emissions were decreased 18.56% by changing chemical speciation profiles, increased 0.67% by replacing temporal profiles as well. Simulated results of air quality were also slightly elevated by using new input modules. Continuous accumulation of domestic data and studies to develop input system for air quality modeling would produce more improved results of air quality prediction.

• 한국대기환경학회지
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• 제28권6호
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• pp.656-665
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• 2012

Recently, yearly production of SRF (Solid Recovered Fuel) as an alternative fuel has been rapidly increasing because of the limited waste disposal, rise in oil prices and reduction of greenhouse gas emission. However, SRF using facilities are excluded from the National Air Pollutant Emission Estimation because SRF using facilities are not yet included among the SCC (Source Classification Code). The purpose of this research was to estimate the emission and emission factor of SRF using facilities' PM and $NO_x$, in order to investigate whether or not they are included in the National Air Pollutant Emission Estimation. The emission factors of SRF using facilities' PM and $NO_x$ are calculated as 0.216 kg/ton, and 3.970 kg/ton, and the emission was estimated based on the yearly total SRF usage of 2011. The results above was 18.7% for PM and 12.8% for $NO_x$ emissions from combustion facility (SCC2) in manufacturing industry combustion (SCC1) of CAPSS. If CAPSS estimate the emission by adding SCC on unlisted SRF in case of Boiler (SCC3) fuel, both PM and $NO_x$'s emissions would increase by 15.8% and 11.3% compare to the emissions for the existing combustion facility. As a result, emissions caused by SRF should be considered when calculating the National Air Pollutant Emission Estimation. In addition, further researches to develop emission factor and improve subdivided SCC should be done in the future, for the accurate and reliable estimation of National Emission.