The Carbon Footprint of Municipalities

A consumption-based account of greenhouse gas emissions reveals true climate impacts of public services.

Analysis based on the environmental impacts of consumption often  focuses on household consumption. Some consumption, however, is provided  by public authorities and paid for through taxes, not prices.  Education, health care, elderly care, street cleaning and – important  for Norway! – snow plowing are examples for that. What are the  environmental impacts of these activities. In a series of papers, my PhD  student Hogne Nersund Larsen takes up the issue and illustrates the usefulness of a carbon footprint account for municipalities. InIdentifying important characteristics of municipal carbon footprints,  we present a calculation of the carbon footprint of public services  provided by all municipalities in Norway. The figure shows the  per-capita carbon footprint for each municipality in a map produced with  help of Statens Kartverk. The carbon footprint of municipalities varies  substantially, from 0.3 to 3 tons per-capita, with small, rich  municipalities having the highest per-capita carbon footprints. The  optimal size in terms of the lowest CF is somewhere around 50’000  inhabitants. We investigate the contribution of different purchases to  the municipal CF. This paper demonstrates the usefulness of the  underlying model which combines the standard financial accounting system  of public entities in Norway with the input-output table. It allowed  for a rapid calculations of CF for all the municipalities.

The second paper Implementing Carbon-Footprint-Based Calculation Tools in Municipal Greenhouse Gas Inventories investigates  the use of CF calculations by two municipalities in their climate  decision making.Following a detailed analysis of the Carbon footprint of Tromsø,  the paper discusses a case study focusing on primary schools. It  presents the activities that really produce the CF – such as the  conveyance of pupils and purchase of food. It also compares different  schools to each other, identifying a large variation in CF per pupil.  The analysis tool developed by Hogne allows for an easy disaggregation  of results to the unit level. It is here, in discussion with the  responsible unit leaders, that the ultimate usefulness of the  calculations becomes apparent. The tool identifies problem areas. It is  less suited to evaluate improvement options, as the measurement offered  by input-output analysis is too crude to distinguish different options  of delivering the same service. Still, we see in both Tromsø and  Trondheim that the results are utilized in municipal climate action  plans.

The case of Tromsø points to the importants of green purchasing  strategies in reducing the carbon footprint of public services: direct  emissions through fuel combustion by the municipality account for only  10% of the total emissions. We see similar results for other  municiplities. What the Greenhouse Gas Protocollabels  “Scope 3” emissions, those resulting from the purchases of goods and  services other than energy, are clearly the most important. These are  the big issues we need to focus on.