Key points are not available for this paper at this time.
The energy transition is driven both by the motivation to decarbonize as well as the decrease in cost of low carbon technology. Net-carbon neutrality over the lifetime of technology use can neither be quantitatively assessed nor realized without accounting for the flows of carbon comprehensively from cradle to grave. Sources of emission are disparate with contributions from resource procurement, process establishment and function, and material refining. The synergies between the constituent value chains are especially apparent in the mobility transition which involves (i) power generation, storage and dispatch, (ii) synthesis of polymeric materials, (iii) manufacturing of vehicles and establishment of infrastructure. Decision-making frameworks that can coordinate these aspects and provide cooperative sustainable solutions are needed. To this end, we present a multiscale modeling and optimization framework for the simultaneous resolution of the material and energy value chains. A case study focusing on the transition of mobility technology towards electric vehicles in Texas is presented. The key contributions of the proposed framework are (i) integrated network design and operational scheduling, (ii) the tracking of disparate emissions, (ii) simultaneous modeling of the material and energy supply chains, (iv) implementation on energiapy, a python package for the multiscale modeling and optimization of energy systems.
Kakodkar et al. (Tue,) studied this question.