Environmentally-extended multi-region input-output (EE-MRIO) models allow calculating environmental impacts of goods and services in a supply-chain perspective. However, current EE-MRIO databases only have limited coverage of toxic pollutant emissions. This limited coverage is caused by the fact that public emission databases currently provide a rather modest pollutant coverage, are restricted to a limited number of countries, and lack differentiation in terms of sectors. This therefore calls for alternative data sources and inventorying techniques. Using the production of heat and electricity as a case study, we investigate the usability of available process-based inventories like the ecoinvent database from the field of Life Cycle Assessment (LCA) to build national emission inventories of pollutants. We thus develop the ecoinvent-based National Energy-related Emission (ENEE) inventory, comprising a total of 231 airborne emissions and 87 waterborne emissions of pollutants from heat and electricity power plants in 140 countries over the period 1995-2014. Using the improved data sets, we demonstrate that extending the coverage of pollutants beyond the few commonly-reported ones, like greenhouse gases, has a significant influence on the quantification of other important environmental impacts such as ionizing radiation and impacts of toxic substances to freshwater ecosystems. The ENEE inventory is an important first step towards building comprehensive inventories of pollutant emissions from power and heat generation, thus enabling more complete assessments of the energy sector. It also exemplifies the gains that can be made when introducing process-based data to complement public national and sectoral data for life cycle assessments and nations environmental footprinting.
Leclerc, A. S. C., Hauschild, M. Z., Wood, R., & Laurent, A. (2020). Building national emission inventories for the energy sector: Implications for life cycle assessment and nations environmental footprinting. Science of the Total Environment, 708, . https://doi.org/10.1016/j.scitotenv.2019.135119