Heat pumps for high-temperature industrial applications: low-global warming potential (GWP) working fluids and statistical thermodynamic modelling

The industrial sector requires scalable decarbonization strategies to address high-temperature heat demand and reduce reliance on fossil fuels. This study presents a predictive thermodynamic and economic modeling framework to evaluate the integration of high-temperature heat pumps in heavy industry. By coupling the Perturbed-Chain Statistical Associating Fluid Theory equation of state with Arrhenius chemical degradation kinetics, the framework assesses the dynamic performance of heavy refrigerants under continuous thermal stress, moving beyond standard stationary cycle analysis. This methodology is applied to target process sinks up to 160°C, representing critical heating applications within the pulp and paper and petrochemical industries, which currently rely on fossil-fueled steam generation. To address barriers limiting widespread industrial uptake, the analysis translates these thermodynamic boundaries into risk-adjusted economic and environmental metrics. The proposed architectures are evaluated against a natural gas boiler baseline subject to carbon taxes. The performance comparison demonstrates that static models overestimate carbon emission reductions and underestimate long-term operational costs. Accounting for the kinetic degradation of the working fluid at elevated discharge temperatures reveals a compounding financial penalty that degrades the coefficient of performance over the system lifespan. This continuous efficiency loss reduces the projected emission savings and significantly extends the economic payback period. Ultimately, this framework provides industrial stakeholders and policymakers with a reliable computational tool to quantify perceived technical risks, assess life-cycle costs, and evaluate the true emission reduction potential of emerging heat pump architectures.