@inbook{2147bab22226460f949da2a692cc1d17,
title = "A network model-based optimisation analysis for the utilisation of CO2 in Qatar's chemical industries",
abstract = "A continuous increase of anthropogenic greenhouse gas (GHG) concentrations in the atmosphere since the industrial revolution has been attributed to global climate change. Mitigation technologies, such as CO2 Capture and Utilisation (CCU) is promising where by it can reduce the global environmental footprint of CO2. In addition, CCU adds value to the producers by enabling the increase of exports of economically valuable products to the global markets. The objective of this study is to assess the integration of CO2 utilisation in the existing processes and technologies to create economic opportunities within the State of Qatar. The study considers CO2 capture and subsequent utilisation as chemical feedstock for several industrial applications. The methodology includes the development of a geospatial (network) optimisation model that comprehensively models the CCU infrastructure, from the CO2 sources to sinks considering pipeline transportation routes in order to maximise the economic benefits of CO2 utilisation. The methodology is primarily based on a techno-economic assessment and single-objective linear programming of the proposed CO2 utilisation network which includes Methanol, Urea and Gas-to-Liquid industries. It considers the economic life cycle of the network at the plant-level and modelling the economic objective in terms of the net present value (NPV) and internal rate of return (IRR), implemented within a multi-period optimisation formulation. The results demonstrate that by applying back-testing using the market prices of value-added products, mainly for the urea, methanol, gasoline, diesel and wax for the period of 2005 - 2018, the optimal solution of the distribution and utilisation of CO2 within the industrial network changes reach to 5.99 Mt/y, whilst considering the revenue functions as the network objectives vary from 1.17 to 3.99 Billion US dollar per year.",
keywords = "CO Utilisation, GTL, IRR, Linear Programming, Methanol, NPV, Urea",
author = "Al-Yaeeshi, {Ali Attiq} and Tareq Al-Ansari and Rajesh Govindan",
note = "Publisher Copyright: {\textcopyright} 2019 Elsevier B.V.",
year = "2019",
doi = "10.1016/B978-0-12-818634-3.50050-3",
language = "English",
series = "Computer Aided Chemical Engineering",
publisher = "Elsevier B.V.",
pages = "295--300",
booktitle = "Computer Aided Chemical Engineering",
address = "Netherlands",
}