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A Stochastic Analysis of VOC Emissions from the Distribution Process of the Gasoline
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  • A Stochastic Analysis of VOC Emissions from the Distribution Process of the Gasoline
  • A Stochastic Analysis of VOC Emissions from the Distribution Process of the Gasoline
저자명
Han. Wha-Jin,Song. Yanghoon,Cho. Yongsung
간행물명
Journal of Korean society for atmospheric environment
권/호정보
2001년|17권 |pp.163-168 (6 pages)
발행정보
한국대기환경학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Estimating the emission rate of VOCs from a gasoline industry at national level can be a challenging take even though the estimation is mean-based. However, using the procedures in the US EPA AP-42 guidelines, it is possible to approximate the mean industry emission rate once enough data are available. However, this estimate can be misled in the sense that there exist many stochastic factors in the EPA\`s estimation procedures and also throughout the marketing channels of gasoline industry. Addressing the stochasticity problem in EPA\`s procedure is hard to tackle because the detailed data needed to execute the estimation are not usually available even from refiners. Instead, this research tries to stay focused on the second type of stochasticity issue, raised from the mean0based metrological and marketing practice data collected from the 4 major refiners. To do so emission raters from each marketing channels (8 marketing points by 3 transportation types and by storage facilities of 4 refiners) are estimated monthly, following AP-42 procedures and using Tank 4.0. Once these estimates are acquired, the distribution of VOC emission rate for each marketing channel of all 4 refiners is estimated through simulation method using @Risk. The mean-based emission rates are weighted by company quantities to estimate the emission rate from the whole gasoline industry. Simple economic implication is provided, based on the result. This study found that, on the mean-bases, about 0.66% of gasoline marketed are evaporated into air. Considering the stochasticity in the estimation, about 90% of simulation results fell into the range of 0.65 to 0.68%. For 90% chance, the estimated economic loss is $54.65 million to $57.17 million, not counting the cost caused by air quality degradation and associated health impact.