In this master’s thesis project, future scenarios for year 2050 were constructed for Denmark, Finland and Sweden using an environmentally extended input-output analysis (EEIOA). Scenarios were constructed based on national sustainability targets. A case-specific five stage modeling approach was developed. Approach consists of changes in input-output tables for Electricity grid, Fossil primary energy, Industry sectors, Transport and Allocation of fossil fuel replacements. To represent business-as-usual development, EEIO tables for 2009 were used as reference and baseline scenarios. Constructed scenario models resulted in substantial CO2 emission reductions compared to baseline scenario. In scenario results for Denmark, emissions reduced 98.17 %, in Finland 81.41 % and in Sweden 77.90 %. Furthermore, based on Planetary Boundary framework, greenhouse gas emission carrying capacities were estimated in sectoral level for 2050. Carrying capacities for year 2050 for Denmark, Finland and Sweden were 9909.99 kton CO2-eq, 9049.42 kton CO2-eq and 18691.96 kton CO2-eq, respectively. Compared to radically reduced emissions in scenario results, Denmark and Sweden reached emission levels below estimated national carrying capacities. For Finland, carrying capacity level was exceeded by 2437.77 ktons. EEIOA was found to be an efficient tool for constructing and analyzing explorative long-term scenarios. In addition, it is possible to integrate absolute sustainability thresholds to EEIOA. Scenario results indicate that implementation of the existing national sustainability targets would lead to radical emission reductions in Denmark, Finland and Sweden by 2050 compared to business-as-usual development. Based on the scenario results, transport and industry sectors were identified as the emission hotspot sectors in 2050. EEIOA is a noteworthy method for decision-support for assessing sustainability strategies. With EEIOA, it is possible to allocate and study national sustainability targets on a sectoral level, and that way potentially substantially increase the effectiveness and implementation of defined sustainability targets. However, further research on modeling dynamics, data quality and underlined uncertainties are needed before studied approaches can develop into decision-support tools.