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Effect of various blended fuels on syngas quality and performance in catalytic co-gasification: A review

Inayat, M. and Sulaiman, S.A. and Kurnia, J.C. and Shahbaz, M. (2019) Effect of various blended fuels on syngas quality and performance in catalytic co-gasification: A review. Renewable and Sustainable Energy Reviews, 105 . pp. 252-267.

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Abstract

Gasification is a well proven thermal conversion technology that has been used to convert solid fuel into gaseous fuel. There are different types of conventional feedstocks such as coal and biomass that have been gasified in either individual or blended form. The advantage of co-gasification over typical gasification is the ability to obtain the desired product gas composition by varying the blending ratio and feedstock. Furthermore, it is applicable for many feedstocks such as sewage sludge, black liquor, glycerol, and municipal solid waste. These feedstocks have good thermophysical properties, however, gasification of these feedstocks is difficult using a conventional technique, thus highlighting the need for co-gasification. Recently, the effect of feedstock type and their blending for syngas production have attracted interest among researchers especially when feedstocks are non-conventional. Several review articles have been published on gasification of individual coal and biomass. However, no review that exhaustively dealt with the catalytic co-gasification of a different kind of conventional and non-conventional feedstock. The feedstock type and blending ratio of feedstock are the most important parameters that affect the co-gasification process. The objective of the current paper is therefore to review the effect of feedstock type and their blending ratio on syngas quality, co-gasification performance, and tar formation for catalytic co-gasification of both conventional and non-conventional feedstocks. This review highlights the need for research and development in co-gasification and also provides the research gap for further research to develop a state of art technologies. © 2019 Elsevier Ltd

Item Type:Article
Impact Factor:cited By 0
ID Code:22092
Deposited By: Ahmad Suhairi
Deposited On:28 Feb 2019 08:09
Last Modified:28 Feb 2019 08:09

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