An Analysis of the Potential and Cost of the U.S. Refinery Sector Decarbonization.

In 2019, U.S. petroleum refineries emitted 196 million metric tons (MT) of CO2, while the well-to-gate and the full life cycle CO2 emissions were significantly higher, reaching 419 and 2843 million MT of CO2, respectively. This analysis examines decarbonization opportunities for U.S. refineries and the cost to achieve both refinery-level and complete life-cycle CO2 emission reductions. We used 2019 life-cycle CO2 emissions from U.S. refineries as a baseline and identified three categories of decarbonization opportunity: (1) switching refinery energy inputs from fossil to renewable sources (e.g., switch hydrogen source); (2) carbon capture and storage of CO2 from various refining units; and (3) changing the feedstock from petroleum crude to biocrude using various blending levels. While all three options can reduce CO2 emissions from refineries, only the third can reduce emissions throughout the life cycle of refinery products, including the combustion of fuels (e.g., gasoline and diesel) during end use applications. A decarbonization approach that combines strategies 1, 2, and 3 can achieve negative life-cycle CO2 emissions, with an average CO2 avoidance cost of $113-$477/MT CO2, or $54-$227/bbl of processed crude; these costs are driven primarily by the high cost of biocrude feedstock.

Integration of environmental aspects in modelling and optimisation of water supply chains.

Climate change becomes increasingly more relevant in the context of water systems planning. Tools are necessary to provide the most economic investment option considering the reliability of the infrastructure from technical and environmental perspectives. Accordingly, in this work, an optimisation approach, formulated as a spatially-explicit multi-period Mixed Integer Linear Programming (MILP) model, is proposed for the design of water supply chains at regional and national scales. The optimisation framework encompasses decisions such as installation of new purification plants, capacity expansion, and raw water trading schemes. The objective is to minimise the total cost incurring from capital and operating expenditures. Assessment of available resources for withdrawal is performed based on hydrological balances, governmental rules and sustainable limits. In the light of the increasing importance of reliability of water supply, a second objective, seeking to maximise the reliability of the supply chains, is introduced. The epsilon-constraint method is used as a solution procedure for the multi-objective formulation. Nash bargaining approach is applied to investigate the fair trade-offs between the two objectives and find the Pareto optimality. The models' capability is addressed through a case study based on Australia. The impact of variability in key input parameters is tackled through the implementation of a rigorous global sensitivity analysis (GSA). The findings suggest that variations in water demand can be more disruptive for the water supply chain than scenarios in which rainfalls are reduced. The frameworks can facilitate governmental multi-aspect decision making processes for the adequate and strategic investments of regional water supply infrastructure.