Jump to Main Content
The Swedish footprint: A multi-model comparison
- Dawkins, Elena, Moran, Daniel, Palm, Viveka, Wood, Richard, Björk, Ida
- Journal of cleaner production 2019 v.209 pp. 1578-1592
- carbon dioxide, carbon footprint, climate, databases, geographical distribution, greenhouse gas emissions, models, statistics, time series analysis, Sweden
- Sweden has a large per capita carbon footprint, particularly compared to the levels recommended for maintaining a stable climate. Much of that footprint falls outside Sweden's territory; emissions occurring abroad are “embodied” in imported goods consumed in Sweden. In this study we calculate the total amount and geographical hotspots of the Swedish footprint produced by different multi-regional input-output (MRIO) models, and compare these results in order to gain a picture of the present state of knowledge of the Swedish global footprint. We also look for insights for future model development that can be gained from such comparisons. We first compare a time series of the Swedish carbon footprint calculated by the Swedish national statistics agency, Statistics Sweden, using a single-region model, with data from the EXIOBASE, GTAP, OECD, Eora, and WIOD MRIO databases. We then examine the MRIO results to investigate the geographical distribution of four types of Swedish footprint: carbon dioxide, greenhouse gas emissions, water use and materials use. We identify the hotspot countries and regions where environmental pressures linked to Swedish consumption are highest. We also consider why the results may differ between calculation methods and types of environmental pressure. As might be expected, given the complexity and modelling assumptions, the MRIO models and Statistics Sweden data provide different (but similar) results for each footprint. The MRIO models have different strengths that can be used to improve the national calculations. However, constructing and maintaining a new MRIO model would be very demanding for one country. It is also clear that for a single country's calculation, there will be better and more precise data available nationally that would not have priority in the construction of an MRIO model. Thus, combining existing MRIO data with national economic and environmental data seems to be a promising method for integrated footprint analysis. Our findings are relevant not just for Sweden but for other countries seeking to improve national consumption-based accounts. Based on our analysis we offer recommendations to guide future research and policy-making to this end.