Global bulk chemical production is responsible for huge amounts of carbon emissions, with

ammonia alone responsible for nearly 2% of global CO2. The transition to renewable

production is a key to meeting net zero goals and also has the potential to allow the storage of

renewably generated energy. By combining technoeconomic, life cycle, and social life cycle

assessment with AI-enhanced probabilistic prediction of future development, the most

complete assessment of renewable production technologies can be undertaken, predicting both

present and future performance. We find hydrogen to be cost competitive by 2030, but that

ammonia production will require substantially more capacity for planned 2050 production.

This thesis is presented in publication format with each chapter self-contained and several

featuring journal articles. Chapter one provides a literature review, assessing prior work to

identify strengths, weaknesses, and opportunities for future research. Chapters two to four

present papers which focus on the renewable production of hydrogen, ammonia, and other bulk

chemicals. These chapters present technoeconomic, life cycle, and social life cycle assessments

of production routes for these chemicals to better define the most sustainable technology both

currently and over time as their development proceeds. These works explore gaps such as the

need for a robust integrated mechanistic and economic model for chemical production, the

future price distribution of hydrogen production, the optimal renewable ammonia production

technology and deployment route.

Chapter five provides two papers that collectively analyse the need for responsible

generative AI use in chemical engineering, covering its impacts in both the private sector and

education. Finally, Chapter six contains the thesis conclusions and outlines directions for future

work.