Geospatial modelling framework for assessing chemical processes and energy systems: applications in direct air capture and electrolytic hydrogen production

The global transition towards net-zero emissions will require increased adoption of technologies with location-dependent performance. Geospatial analysis can be a rapid and cost-effective tool in screening the performance of technologies and systems with location-dependent performance. It can aid decision-makers in the crucial task of identifying optimal deployment locations. This thesis presents a geospatial modelling framework that integrates detailed process- and system-level modelling with regional data. The framework can account for variations in regional climate, intermittent renewable energy availability and economic factors, providing a holistic understanding of the factors influencing the performance of low-carbon technologies. The utility of the framework is illustrated in three case studies. First, it is used for technology assessment, specifically direct air capture. The study assesses how ambient temperature and relative humidity affect direct air capture process performance and costs. It then analyses multiple years of high-resolution climatic data to identify optimal locations for direct air capture deployment. Building on this, the framework is extended to system-level assessments using a process systems engineering approach. This enables the geospatial assessment of direct air capture systems coupled with different low-carbon energy sources, including intermittent renewables, nuclear power and natural gas. Finally, the framework is used in policy assessment by examining the policy implications of enforcing an hourly time-matching requirement for grid-connected electrolytic hydrogen production from intermittent renewable energy. By analysing two decades of wind and solar data, the study highlights the challenges and economic impacts of hourly aligning hydrogen production with variable renewable energy availability. The findings offer insights into designing policies that balance economic and environmental objectives. Overall, this thesis offers a valuable tool for screening and identifying the optimal deployment of low-carbon technologies by incorporating regional variations and system-level interactions. This can support policymakers and stakeholders in ensuring a cost-effective and sustainable transition to a low-carbon economy.