TY - CHAP
T1 - Waste valorisation within the Energy-Water-Food Nexus
T2 - A hybrid techno-geospatial optimisation approach
AU - Alherbawi, Mohammad
AU - Namany, Sarah
AU - Haji, Maryam
AU - McKay, Gordon
AU - Al-Ansari, Tareq
N1 - Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2023/1
Y1 - 2023/1
N2 - Waste of multiple categories such as agricultural, municipal, and industrial waste are the most abundant biomass sources worldwide. The mismanagement of such waste results in severe impacts on the environment, human health, and resources availability for future generations. However, waste can be utilised within energy, water and food sectors. As such, evaluating the optimal processing pathway, in addition to the optimal supply chain is crucial to fulfilling an adequate balance in the Energy-Water-Food (EWF) Nexus considering national priorities. In this study, 10 waste biomass categories were located over 35 locations across the Qatar using the geographic information systems (GIS), while their quantities, calorific values, and possible associated product yields were defined. Meanwhile, three biomass processing plants representing the EWF industries have been considered, including: biorefinery, desalination plant, and livestock feed developer. An optimisation model was then developed to select optimal biomass and minimise the overall transportation costs for all three industries. Three scenarios were introduced to ensure an EWF Nexus balance throughout the biomass allocation process. The scenarios included: a) equal biomass-based production amongst EWF industries, b) equal biomass distribution, and c) equal biomass-based sales. The model was able to allocate biomass resources from almost all sites at different utilisation percentages. Biomass transportation cost was minimised to 1.98 $/t in scenario (b), where 0.48 M t/y of biomass were utilised, 49.8 M t/y of products were generated and sold at 82.5 M $/y. However, scenario (c) achieved higher utilisation rate of biomass at 1.49 M t/y, transported at a minimised cost of 4.33 $/t. The established model provides an insight on advanced decision-making approaches for optimal waste biomass valorisation to meet the growing demand on EWF resources.
AB - Waste of multiple categories such as agricultural, municipal, and industrial waste are the most abundant biomass sources worldwide. The mismanagement of such waste results in severe impacts on the environment, human health, and resources availability for future generations. However, waste can be utilised within energy, water and food sectors. As such, evaluating the optimal processing pathway, in addition to the optimal supply chain is crucial to fulfilling an adequate balance in the Energy-Water-Food (EWF) Nexus considering national priorities. In this study, 10 waste biomass categories were located over 35 locations across the Qatar using the geographic information systems (GIS), while their quantities, calorific values, and possible associated product yields were defined. Meanwhile, three biomass processing plants representing the EWF industries have been considered, including: biorefinery, desalination plant, and livestock feed developer. An optimisation model was then developed to select optimal biomass and minimise the overall transportation costs for all three industries. Three scenarios were introduced to ensure an EWF Nexus balance throughout the biomass allocation process. The scenarios included: a) equal biomass-based production amongst EWF industries, b) equal biomass distribution, and c) equal biomass-based sales. The model was able to allocate biomass resources from almost all sites at different utilisation percentages. Biomass transportation cost was minimised to 1.98 $/t in scenario (b), where 0.48 M t/y of biomass were utilised, 49.8 M t/y of products were generated and sold at 82.5 M $/y. However, scenario (c) achieved higher utilisation rate of biomass at 1.49 M t/y, transported at a minimised cost of 4.33 $/t. The established model provides an insight on advanced decision-making approaches for optimal waste biomass valorisation to meet the growing demand on EWF resources.
KW - Decision-making
KW - EWF nexus
KW - GIS
KW - Optimisation
KW - Qatar
KW - Supply chain
UR - http://www.scopus.com/inward/record.url?scp=85165098428&partnerID=8YFLogxK
U2 - 10.1016/B978-0-443-15274-0.50343-7
DO - 10.1016/B978-0-443-15274-0.50343-7
M3 - Chapter
AN - SCOPUS:85165098428
T3 - Computer Aided Chemical Engineering
SP - 2155
EP - 2160
BT - Computer Aided Chemical Engineering
PB - Elsevier B.V.
ER -