Multi-Biomass Refinery Siting: A GIS Geospatial Optimisation Approach

Mohammad Alherbawi, Gordon McKay, Hamish R. Mackey, Tareq Al-Ansari*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Biomass feedstock is a key sustainable alternative to the finite fossil resources to produce fuels and chemicals. Biomass sources vary from energy crops to a wide range of municipal, agricultural, and industrial wastes. Therefore, it is attracting growing attention due to its wide availability in almost every country worldwide. However, due to the irregular generation and the scattered distribution of biomass resources, the design of supply chains and the selection of refinery sites become a challenging task. As such, this study presents a framework for an optimal site selection of a multiple biomass refinery. Qatar is chosen as the case study, whereby, its main sources and locations of biomass are identified. While a mathematical optimisation model is established by utilising the geographic information system (GIS) and analytical hierarchy process (AHP) to spot optimal biorefinery sites that may enhance the supply chain of available biomass. Multiple criteria are considered in the model including the site accessibility to key infrastructural facilities, as well as biomass locations, availability, and calorific values. While several constraints are employed to alleviate social and environmental concerns. The model generates several candidate sites, which are then reduced to a single optimal site (at coordinates: 25.144, 51.351). The selected optimal site is believed to maximise the potential biomass energy supply and enhance the biomass supply chain through minimising biomass transportation cost, which is evaluated at an average of 7 $/tonne.

Original languageEnglish
Pages (from-to)73-78
Number of pages6
JournalChemical Engineering Transactions
Volume92
DOIs
Publication statusPublished - 2022

Keywords

  • AHP
  • Biomass
  • Biorefinery siting
  • GIS
  • MCLP
  • Qatar
  • Supply chain

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