CO2 bottom-up emission inventory based on municipal power generation and heating data in Munich
- 1Environmental Sensing and Modeling, Technical University of Munich, Munich, Germany (patrick.aigner@tum.de)
- 2TNO, Climate Air and Sustainability, Utrecht, Netherlands
- 3Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
- 4Stadtwerke München (SWM), Munich, Germany
Cities’ climate action efforts towards carbon neutrality will be challenged in the next decades by more and more people moving into cities and the correspondingly growing demand for services and infrastructure. By 2050, over 70% of the world's population is projected to be living in densely populated urban areas. This will add another level of difficulty to fulfilling the demand for clean energy and heating considering the available technology and infrastructure. It will be important for city stakeholders to understand current and future demands in detail to make informed decisions, implement effective carbon mitigation measures, and achieve a good return on investment. To kick this off, the ICOS-cities project chose three pilot cities (Paris, Munich, and Zurich) to generate high-resolution spatial and temporal bottom-up inventories for CO2 and co-emitted species.
Existing municipal emission inventories for Munich report annual emissions estimates without spatial information. We present a temporal (1h) and spatial (100m x 100m) explicit high-resolution bottom-up inventory for public power production consisting of electricity and district heating (GNFR A) and other stationary combustion (GNFR-C) in Munich. Both sectors are derived from power and heating plant data of the year 2019 provided by the Stadtwerke München (SWM) and the latest municipal geospatial datasets provided by the City of Munich. Furthermore, we compare state-of-the-art but more generic TNO activity and temporal profiles with temporal profiles derived from data from local CHP plants data and a heat demand function validated with Munich’s reported yearly heat demand. Additionally, we present emission factors calculated from the fuel composition (2019) of inflowing gas and burned waste alongside available state-of-the-art emissions factors from IPCC (2019), EPA (2022), and UBA (2022).
How to cite: Aigner, P., Suhendra, M., Yirtar, B., Kühbacher, D., Super, I., Droste, A., Denier van der Gon, H., Brunner, D., Kohlmeier, H., Althammer, T., and Chen, J.: CO2 bottom-up emission inventory based on municipal power generation and heating data in Munich, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13451, https://doi.org/10.5194/egusphere-egu23-13451, 2023.