• 한국대기환경학회지
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• 제33권4호
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• pp.377-392
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• 2017

A set of BFM (Brute Force Method) simulations with the CMAQ (Community Multiscale Air Quality) model were conducted in order to estimate self-contributions and conversion rates of PPM (Primary $PM_{2.5}$), $NO_x$, $SO_2$, $NH_3$, and VOC emissions to $PM_{2.5}$ concentrations over the SMA (Seoul Metropolitan Area). CAPSS (Clean Air Policy Support System) 2013 EI (emissions inventory) from the NIER (National Institute of Environmental Research) was used for the base and sensitivity simulations. SCCs (Source Classification Codes) in the EI were utilized to group the emissions into area, mobile, and point source categories. PPM and $PM_{2.5}$ precursor emissions from each source category were reduced by 50%. In turn, air quality was simulated with CMAQ during January, April, July, and October in 2014 for the BFM runs. In this study, seasonal variations of SMA $PM_{2.5}$ self-sensitivities to PPM, $SO_2$, and $NH_3$ emissions can be observed even when the seasonal emission rates are almost identical. For example, when the mobile PPM emissions from the SMA were 634 TPM (Tons Per Month) and 603 TPM in January and July, self-contributions of the emissions to monthly mean $PM_{2.5}$ were $2.7{\mu}g/m^3$ and $1.3{\mu}g/m^3$ for the months, respectively. Similarly, while $NH_3$ emissions from area sources were 4,169 TPM and 3,951 TPM in January and July, the self-contributions to monthly mean $PM_{2.5}$ for the months were $2.0{\mu}g/m^3$ and $4.4{\mu}g/m^3$, respectively. Meanwhile, emission-to-$PM_{2.5}$ conversion rates of precursors vary among source categories. For instance, the annual mean conversion rates of the SMA mobile, area, and point sources were 19.3, 10.8, and $6.6{\mu}g/m^3/10^6TPY$ for $SO_2$ emissions while those rates for PPM emissions were 268.6, 207.7, and 181.5 (${\mu}g/m^3/10^6TPY$), respectively, over the region. The results demonstrate that SMA $PM_{2.5}$ responses to the same amount of reduction in precursor emissions differ for source categories and in time (e.g. seasons), which is important when the cost-benefit analysis is conducted during air quality improvement planning. On the other hand, annual mean $PM_{2.5}$ sensitivities to the SMA $NO_x$ emissions remains still negative even after a 50% reduction in emission category which implies that more aggressive $NO_x$ reductions are required for the SMA to overcome '$NO_x$ disbenefit' under the base condition.

• 한국대기환경학회지
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• 제26권1호
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• pp.48-56
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• 2010

Recently it has reported that the motorcycle is a major source of air pollution in urban area by many studies. But the air pollution emission from motorcycle has been high uncertainty due investigation of a lack of activity data and emission factors in Korea. So in this study, the population of moped and VKT (Vehicle kilometers travelled) of motorcycle are investigated for calculation of the emission from this source categories. As the results, the population of moped is estimated as about 400, 000 and corresponded as 23% of registrated motorcycle which is larger than 50 cc in engine displacement. And it is found that the VKT of moped and motorcycle are investigated as 19.1 km/day and 32.3 km/day. Annual air pollution emission from motorcycle and moped are estimated by investigated VKT and updated emission factors. The nationwide emissions of PM_{10}, CO, $NO_x$, VOC are calculated as 910 ton/yr, 208, 198 ton/yr, 3, 032 ton/yr and 25, 575 ton/yr in 2008. The contribution ratio of CO, VOC emission from these sources are estimated as 29%, 24% in on-road transport sector and it is confirmed that motorcycle and moped are major air pollution sources in urban area.

• 한국정밀공학회지
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• 제28권12호
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• pp.1372-1378
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• 2011

The smart air condition system is superior to conventional air condition system in the aspect of control accuracy, environmental preservation and it is foundation for intelligent vehicle such as electric vehicle, fuel cell vehicle. In this paper, failure analyses of smart air condition system will be performed and then sensor fusion technique will be proposed for fail safety of smart air condition system. A sensor fusion logic of air condition system by using CO sensor, $CO_2$ sensor and VOC, $NO_x$ sensor will be developed and simulated by fault injection simulation. The fusion technology of smart air condition system is generated in an experiment and a performance analysis is conducted with fusion algorithms. The proposed algorithm adds the error characteristic of each sensor as a conditional probability value, and ensures greater accuracy by performing the track fusion with the sensors with the most reliable performance.

• 한국대기환경학회지
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• 제34권4호
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• pp.517-533
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• 2018

We utilize the CAMx (Comprehensive Air Quality Model with eXtensions) system and the PSAT (Particulate Source Apportionment Technology) diagnostic tool to determine the $PM_{2.5}$ concentration and to perform its source apportionment in the southeastern region of South Korea. For a year-long simulation, eight local authorities in the region such as Pohang, Daegu, Gyeongju, Ulsan, Busan-Gimhae, Gosung-Changwon, Hadong, and all remaining areas in Gyeongsangnam-do, are selected as source areas based on the emission rates of $NO_x$, $SO_x$, VOC, and primary PM in CAPSS (Clean Air Policy Support System) 2013 emissions inventory. The CAMx-PSAT simulation shows that Pohang has the highest $PM_{2.5}$ self-contribution rate (25%), followed by Hadong (15%) and Busan-Gimhae (14%). With the exception of Pohang, which has intense fugitive dust emissions, other authorities are strongly affected by emissions from their neighboring areas. This may be measured as much as 1 to 2 times higher than that of the self-contribution rate. Based on these estimations, we conclude that the efficiency of emission reduction measures to mitigate $PM_{2.5}$ concentrations in the southeastern region of South Korea can be maximized when the efforts of local or regional emission controls are combined with those from neighboring regions. A comprehensive control policy planning based on the collaboration between neighboring jurisdictional boundaries is required.

• 한국응용과학기술학회지
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• 제34권4호
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• pp.799-806
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• 2017

점토를 이용하여 세 종류의 새로운 형태의 변형된 유기물점토를 제조하였다. Cetylpyridinium chloride (CPC)를 점토에 층간 삽입시켜 OC-CPC를 합성하였고, Aluminium 축을 갖는 Al-PILC 만든 후, cetylpyridinium chloride를 Al-PILC에 삽입시켜 IOC-CPC 화합물을 합성하였다. IR과 TGA를 이용하여 이들 구조를 분석한 결과 층간 삽입반응이 성공적으로 이루어졌음을 확인할 수 있었다. X-ray 회절을 이용하여 층간 거리를 조사하였는데 OC-CPC가 제일 큰 값을 보여 주었다. 층간 구조를 갖는 화합물들은 삽입반응을 이용하여 구조를 변형시킬 수 있으며 이를 통해 층간거리, 표면적, 공간 크기, 화학적 친화성 같은 여러 물리적 성질들을 바꿀 수 있으므로, 본 논문에서는 자연점토를 이용하여 층간 반응을 통해 휘발성 유기화합물의 흡착에 쓰일 수 있는 유용한 유기점토 화합물을 합성하고 이들의 구조를 확인코자 하였다. 벤젠과 톨루엔의 흡착은 IOC-CPC나 Al-PILC에서 보다 OC-CPC에서 더 잘 이루어졌으며, 자연점토에서는 거의 흡착이 일어나지 않았다. OC-CPC 화합물에서는 친 소수성 성질이 크고 층간 거리도 증가했기 때문에 흡착이 잘 일어났다고 볼 수 있으며, 반면에 친수성이 큰 Al-PILC에서는 벤젠과 톨루엔 같은 휘발성 유기물에 대한 흡착이 상대적으로 적게 일어났다.

• 한국대기환경학회지
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• 제30권6호
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• pp.555-568
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• 2014

The construction equipment is one of the major sources for hazardous air pollutants in Korea, and the its management has been of great concern recently. The objective of this study was to estimate each contribution of emission of construction equipments according to their production year, electric power consumption and type. To achieve this goal, we developed pollutant emission factors for the machineries manufactured after 2009, which are excluded from the present framework of Korean air pollutants inventory, CAPSS. More than 800 data obtained from emission investigations were utilized for the estimation. Compared with the previous estimation, the scheme used this study was modified to incorporate new emission factors as well as to include the corresponding activity data. Such improvement allow us to gain more detailed emission informations which are better characterized by specifications of construction equipments. The total amount of pollutants emitted from construction equipments in 2011 were estimated as 126.8, 7.0, 58.3, and 17.0 kton for $NO_x$, PM, CO, and VOC, respectively. The estimation results indicate that the increase in the emission of equipments is significantly related to their age and power consumption. The emissions of the older ones manufactured from 1992~1996 were estimated to be the contribution ranged from 23.7% to 26.8%, whereas the newer ones (2009~2011) showed the attributions of 11.3~21.5%. In addition, the results show that the emission of each equipment was increased with the increase in the electric power consumption of engine, probably due to their average output power. Among the nine types of machinery compared, excavators and forklifts were investigated to contribute relatively higher emissions in the level of 39.8~44.0% and 32.0~34.2%, respectively.