Bridging Data Gaps for Industrial Heat Pump Deployment: A Sector-Based Approach Using NACE Classification
Heat demand below 200 °C in buildings and industry remains a major contributor to natural gas use and associated greenhouse-gas emissions in Germany. High-temperature heat pumps (HTHPs) offer a technically mature option to decarbonize this demand, but deployment is slowed by limited availability of plant-level information, including load profiles, process temperatures and waste-heat characteristics. This paper presents an outside-in screening method that identifies HTHP opportunities using only public statistics and sector classifications. Industrial activities are referenced through the NACE Rev. 2 classification (the EU’s Statistical Classification of Economic Activities). Sectoral energy balances and process-level energy distributions are taken from JRCIDEES (the Joint Research Centre’s Integrated Database of the European Energy System), which reports harmonized energy-carrier splits for EU industry. The method links Eurostat employment statistics with IDEES energy data to scale sectoral final energy to representative site sizes. Temperature levels, operating hours and typical waste-heat streams are compiled from technical literature. A best-practice database provides source and sink temperatures, temperature lifts and capacities from realized HTHP projects; where no case exists, standard integration schemes are applied and the COP is estimated for the corresponding source and sink temperatures using an empirical correlation. The approach is demonstrated for the pulp and paper sector. The scaled energy intensities per employee, thermal loads and waste-heat characteristics are consistent with values reported by industry associations, sustainability reports and documented HTHP demonstrators. The screening also identifies process-specific waste-heat streams, supporting the early assessment of suitable heat sources and integration points. Overall, the results show that even with limited public data, an outside-in approach can indicate dominant energy-intensive processes, characteristic temperature levels, associated waste-heat potentials and plausible HTHP integration schemes. The workflow provides a transparent and reproducible basis for