Decoding Carbon Footprints: Empowering Municipalities in Climate Change Mitigation through Individualized Energy and Electricity Consumption Data
Information
Författare: Klara Flygare, Moa TingstedtBeräknat färdigt: 2024-06
Handledare: Katarina Axelsson
Handledares företag/institution: Stockholm Environment Institute
Ämnesgranskare: Max Rosvall
Övrigt: -
Presentationer
Presentation av Klara FlygarePresentationstid: 2024-06-03 08:15
Presentation av Moa Tingstedt
Presentationstid: 2024-06-03 09:15
Opponenter: Fredrik Hermodsson, Erik Ekstrand
Abstract
This study contributes to exploring methodologies and approaches to sustainability reporting in the district heating sector, emphasizing the importance for open-access and decoding of environmental data to help mitigate climate impacts. The study investigates avenues for enhancing the understanding and accuracy of emission calculations with a consumption-based perspective related to district heating in Sweden. The study examines contemporary open data sources related to district heating in Sweden and assesses the challenges and obstacles associated with sustainability reporting, and semi-structured interviews were conducted to evaluate data quality and field challenges. The study also performed computations on emissions from district heating, aiming for high geographical resolution and consumption-based calculations. Based on previous inputs, the thesis constructed its own models to compute emissions.
The study’s results identified data sources available, it was observed that many of them lack the transparency and documentation needed for third party users. Despite covering the same topics, differences in data were identified, likely due to varying methodologies for activity and emission data production. This underscores the challenge in selecting appropriate frameworks and methodologies for sustainability reporting, and its significant impact. Two main challenges were identified because of this, virtual networks and the allocation of emissions, both highly contested concepts. The computations demonstrated that it is possible to increase the granularity of emissions, using emission factors for district heating energy specifically linked to municipal areas. It also showed that using different data sources and methodologies can lead to varied outcomes, although they generally align with national trends. It is important to consider this variability when interpreting results and making decisions based on such data. Modelling to increase higher geographical resolution indicated that downscaling to postcode level is achievable but laborious and time-consuming. However, this approach can enhance understanding of local variations, aiding in the comprehension of emission patterns. Moreover, ensuring data transparency and accessibility can aid local initiatives and inform strategies for reduction, which are crucial for climate change mitigation efforts.