Decision analysis of multi-pollutant control strategy for coal-fired power plant in Malaysia

The promulgation of Environmental Quality (Clean Air) Regulations 2014 on emissions from coal-fired power plants in Malaysia has prompted power plant operators to adopt emission control strategy that complies with the new emission limits. Currently, various emission control strategies are available...

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Main Authors: Mokhtar, M. M., Taib, M. R., Hassim, M. H.
Format: Article
Published: Springer Verlag 2016
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Online Access:http://eprints.utm.my/id/eprint/72438/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957640726&doi=10.1007%2fs10098-016-1114-2&partnerID=40&md5=ccf14e7ea1092e75f83bd23c53cb32bb
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Institution: Universiti Teknologi Malaysia
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spelling my.utm.724382017-11-22T12:07:38Z http://eprints.utm.my/id/eprint/72438/ Decision analysis of multi-pollutant control strategy for coal-fired power plant in Malaysia Mokhtar, M. M. Taib, M. R. Hassim, M. H. TP Chemical technology The promulgation of Environmental Quality (Clean Air) Regulations 2014 on emissions from coal-fired power plants in Malaysia has prompted power plant operators to adopt emission control strategy that complies with the new emission limits. Currently, various emission control strategies are available to achieve the desired emission level. Each strategy offers unique advantages and disadvantages, depending on the objective of emissions control, process nature, and constraints on the resources incurred. To address this challenge, a proper decision-making analysis needs to be performed. In this paper, a systematic decision analysis methodology is proposed to select the most effective multi-pollutant control strategy that is compatible for coal-fired power plants in Malaysia. The methodology includes: (1) identification of pollutant emission from the plant under study and comparison with the stipulated emission limits, (2) establishment of emission factors, (3) selection of multi-pollutant control strategy, (4) identification of emission reduction factor for the pollutants and control technologies of interest, (5) determination of emission level from the selected multi-pollutant control strategy, and (6) prediction of ground-level concentration of pollutants. The decision analysis methodology is applied to a real case study of coal-fired power plant in Malaysia, which also currently faces a dilemma to comply with the additional and more stringent emission limits stipulated in the Environmental Quality (Clean Air) Regulations 2014. The proposed method is applicable for both the process concept under the design phase as well as the existing process plant. Springer Verlag 2016 Article PeerReviewed Mokhtar, M. M. and Taib, M. R. and Hassim, M. H. (2016) Decision analysis of multi-pollutant control strategy for coal-fired power plant in Malaysia. Clean Technologies and Environmental Policy, 18 (5). pp. 1361-1367. ISSN 1618-954X https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957640726&doi=10.1007%2fs10098-016-1114-2&partnerID=40&md5=ccf14e7ea1092e75f83bd23c53cb32bb
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TP Chemical technology
spellingShingle TP Chemical technology
Mokhtar, M. M.
Taib, M. R.
Hassim, M. H.
Decision analysis of multi-pollutant control strategy for coal-fired power plant in Malaysia
description The promulgation of Environmental Quality (Clean Air) Regulations 2014 on emissions from coal-fired power plants in Malaysia has prompted power plant operators to adopt emission control strategy that complies with the new emission limits. Currently, various emission control strategies are available to achieve the desired emission level. Each strategy offers unique advantages and disadvantages, depending on the objective of emissions control, process nature, and constraints on the resources incurred. To address this challenge, a proper decision-making analysis needs to be performed. In this paper, a systematic decision analysis methodology is proposed to select the most effective multi-pollutant control strategy that is compatible for coal-fired power plants in Malaysia. The methodology includes: (1) identification of pollutant emission from the plant under study and comparison with the stipulated emission limits, (2) establishment of emission factors, (3) selection of multi-pollutant control strategy, (4) identification of emission reduction factor for the pollutants and control technologies of interest, (5) determination of emission level from the selected multi-pollutant control strategy, and (6) prediction of ground-level concentration of pollutants. The decision analysis methodology is applied to a real case study of coal-fired power plant in Malaysia, which also currently faces a dilemma to comply with the additional and more stringent emission limits stipulated in the Environmental Quality (Clean Air) Regulations 2014. The proposed method is applicable for both the process concept under the design phase as well as the existing process plant.
format Article
author Mokhtar, M. M.
Taib, M. R.
Hassim, M. H.
author_facet Mokhtar, M. M.
Taib, M. R.
Hassim, M. H.
author_sort Mokhtar, M. M.
title Decision analysis of multi-pollutant control strategy for coal-fired power plant in Malaysia
title_short Decision analysis of multi-pollutant control strategy for coal-fired power plant in Malaysia
title_full Decision analysis of multi-pollutant control strategy for coal-fired power plant in Malaysia
title_fullStr Decision analysis of multi-pollutant control strategy for coal-fired power plant in Malaysia
title_full_unstemmed Decision analysis of multi-pollutant control strategy for coal-fired power plant in Malaysia
title_sort decision analysis of multi-pollutant control strategy for coal-fired power plant in malaysia
publisher Springer Verlag
publishDate 2016
url http://eprints.utm.my/id/eprint/72438/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957640726&doi=10.1007%2fs10098-016-1114-2&partnerID=40&md5=ccf14e7ea1092e75f83bd23c53cb32bb
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