This study builds upon the existing work on futurizing the ecoinvent database at the service of the prospective LCA method that requires a temporally matched foreground and background system. It is a first effort in modelling future scenarios of Industrial Process Heat (IPH) generation using projections from the IMAGE Integrated Assessment Model (IAM) following the SSP2-baseline, SSP2-RCP2.6 and SSP2- RCP1.9 scenarios from 2020 to 2050. These scenarios are then implemented in the ecoinvent database (version 3.8, cut-off) and used to quantify the environmental impacts of generating 1MJ of IPH across four markets in twenty-six regions for three different scenarios. The markets under study are chemicals, food and tobacco, pulp and paper, while the rest of the sectors without cement and steel are grouped under the “other industries” category, as per IMAGE classification. We quantify and analyze the climate change impact and cumulative decarbonization potential of the future IPH generation markets across sectors and regions. Furthermore, we quantify their performance across fifteen additional impact categories to check for potential burden shift. On top of IMAGE projections, we also explore whether coupling CHP with CCS impacts our results.

By 2050, even in the best-case scenario (SSP2-RCP1.9), fossil fuels are still expected to be responsible for the generation of 48% of the global IPH demand for food and tobacco, 51.4% for the Other industries category, 64% for chemicals and 88% for pulp and paper. Nevertheless, heat from coal is expected to reduce its share in the global IPH generation market mixes in a range of -56% to -95% across sectors, being one of the main reasons why climate change impact shows a decrease in the range of 31-60% across sectors when compared to the baseline (pulp and paper: -31%, food and tobacco: -57%, Other industries: -60%, chemicals: -34%).

By 2050, in the best-case scenario, the direct combustion of biomass is expected to supply 25% of the global IPH demand for food and tobacco and 20.8% of the global IPH demand for other industries category. Biofuels are expected to provide 1/3 of the IPH demand in the chemicals sector with little impact on climate change but at the cost of contributing with a significant share in other environmental impact categories such as marine eutrophication (63.4%), terrestrial eutrophication (57.8%), non-carcinogenic human toxicity (70.2%), land use (98%), water use (91.8%) and minerals depletion (80.6%). Electrification is expected to take a more prominent role mainly in food and tobacco and other industries sectors offsetting emissions by -9.07% and -13.7% but at the cost of increasing the ionising radiation impact from electricity production.

The results from the other environmental categories highlight a decrease in impacts across most of the environmental impact categories except for land use, ionising radiation, water use and minerals depletion, which emphasized the potential burden shift that the decarbonization efforts may cause.



Our results also show that the most optimal outcomes are received when the decarbonization of the heat supply is combined with the demand reduction. The demand reduction across sectors as well as the respective decarbonization of IPH generation market mixes, results in a cumulative decarbonization potential of 85.78 Gt CO2-eq. (RCP2.6) and 105.29 Gt CO2-eq. (RCP1.9).

Implementing CHP with CCS is beneficial to climate change but may decline the improvement potential for many impact categories compared to when CHP is not coupled with CCS.

By 2050, the highest emitters of CO2-Eq. emissions are the regions that drive the global IPH demand: China (CHN), India (INDIA), Middle East (ME), USA and Western Europe (WEU), responsible for at least 70% of the global carbon footprint across scenarios.

This study is the first trial of this sort, and as a consequence, there is a lot of potential for improvement of future IPH generation scenarios, which requires further research for the following aspects:

• Enriching IMAGE projections with shares of conversion technologies for IPH generation
• Enriching the ecoinvent database with lifecycle inventories of cleaner heat generation technologies
• Enriching IMAGE with projections for renewable heat sources and cleaner fuels for IPH generation
• Enriching IMAGE scenarios with projections on GHG emissions reductions for IPH generation as well as projections on CCS implementation for IPH generation
• Disaggregating the “Other Industries” category
• Improving ecoinvent lifecycle inventories for the manufacturing processes in the most carbon- intensive industries that do not disaggregate fuels used for IPH generation versus feedstocks

Considering the data scarcity, time limitations and unresolved uncertainties, it is essential to treat these results as potential future trends rather than in absolute terms.