Sustainability Carbon Footprint of Research
Research at Heidelberg University significantly contributes to the progress of our society. Many disciplines deal with research questions that directly or indirectly relate to the topic of sustainability. However, research is also energy- and labor-intensive, inevitably leading to a CO₂ footprint. How large is this footprint, and how are its components distributed?
In order to optimize the sustainability of research operations, it is first necessary to establish a baseline – how large are the emissions caused, and what is their origin? This will make it possible to identify specific improvement measures, whose effects can also be quantified. However, a detailed and systematic examination of the emissions generated by research operations themselves has yet to be undertaken. The great diversity of research at Heidelberg University makes it obvious that a generalized view of the university’s emissions will not provide an accurate picture of the situation in individual labs and research groups.
To obtain a data-based overview of the extent and complexity, the position of Carbon Footprint Advisor for research operations has been jointly funded by all four Fields of Focus at the university.
Project Goals
In contrast to a university-wide inventory, the objective of this pilot project is focused on compiling datasets with the highest possible resolution. The pilot project is intended to empower researchers to reduce their greenhouse gas emissions without negatively affecting their research questions. To this end, the following goals are defined:
- Establishing an emissions baseline at the research group level
All relevant emission categories in accordance with the GHG Protocol are to be identified and accounted for. Without establishing a baseline, the prerequisites for a measurable and evaluable emissions reduction strategy are lacking. - High-resolution data aggregation
Collection of datasets across all relevant emission categories at a high level of resolution. The aim is to provide researchers with maximum analytical flexibility to develop meaningful reduction strategies for their own research operations. Based on reliable and comprehensive emissions data, it must be possible to assess which reduction options can be reconciled with the feasibility of achieving the respective research objectives. - Identification of challenges in the data basis
Where do gaps exist in the collection of emissions-relevant data? How can documentation processes and measurement approaches be adapted to close potential gaps and/or improve the resolution of existing datasets? - Comprehensive accounting of multiple pilot projects
Selection of different test cases in order to examine data collection and analysis in the form of case studies and to translate the approach into a standardized process.
It must be explicitly emphasized that greenhouse gas accounting at the level of individual research groups should not be used as a basis for evaluative or comparative assessments between different groups. There is no robust metric that would allow for a substantively sound comparison. The pronounced heterogeneity of research at a comprehensive university results in an extremely diverse spectrum of research questions, addressed through methodologically highly distinct approaches. Against this background, neither a comparison of absolute emissions nor of per capita emissions or emissions-related subcategories (e.g., business travel emissions) can be meaningfully conducted. Any such comparison would implicitly entail an evaluation of the respective research question, its methodology, or its scientific necessities. This touches upon questions in the philosophy of science that lie beyond the scope of the emissions datasets used here and that cannot be represented or legitimately assessed by them.
Methodology
The project adopts the established greenhouse gas reporting standard Greenhouse Gas Protocol. Within this framework, different emission sources are grouped into so-called scopes. All emission sources defined therein—where relevant in the university context—are to be recorded as part of the project.
A people-based approach is chosen as the accounting framework, in contrast to an assessment at the level of entire institutes or buildings. Selecting research groups or individual research projects as the unit of analysis enables a differentiated attribution of emissions to specific organizational entities, thereby creating the foundation for targeted mitigation measures at the group or project level.
At the same time, the complexity of data aggregation increases for those emission sources that have previously been recorded exclusively at the building level. This increased complexity does not represent an inherent methodological deficit of the chosen approach; rather, it reflects a previously insufficiently differentiated data collection and attribution structure. Mitigating the challenges of limited data availability may be attempted through attribution concepts based on floor area distributions and, selectively, through targeted measurements.
The institutional data management of Heidelberg University is not designed – neither at the level of individual research groups nor at the university-wide level – for the systematic collection, aggregation, and provision of emissions-relevant indicators. Instead, it is structurally oriented primarily toward the representation and control of financial flows. Accordingly, no standardized reporting structures exist that would allow for the direct derivation of greenhouse gas-related activity data.
For each identified emission category, it was therefore necessary to develop a specific data aggregation strategy, taking into account the available primary and secondary data sources.
Distribution of CO₂ Emissions Across Different Research Projects
Summary of Results
Based on the data collected for the selected pilot projects, the following conclusions can be drawn regarding the emissions data landscape at Heidelberg University. It is important to note that data quality and resolution must meet the requirements of the project’s objective – namely, to enable researchers to identify emission reduction measures and to evaluate their effectiveness. These requirements of a people-up approach are not yet met for most emission categories, whereas the data situation is in some cases already sufficient for a building-down approach or for university-wide carbon accounting.
The most significant deficiencies exist in the areas of building-related energy consumption and consumables, particularly in natural and life science research fields.
The discrepancy in data requirements becomes evident when considering electricity demand: For building-level or university-wide accounting, data availability is generally adequate. However, the current metering infrastructure does not provide sufficiently granular resolution to supply researchers with robust information for process-level analysis and the identification of concrete savings potentials. There is therefore a structural gap between aggregated reporting capability and operational steering capability.
In the category of consumables, the data situation is inadequate at all levels of analysis. Fundamental and reliable emission factors are lacking for many of the substances and products used. While estimation via monetary emission factors is methodologically feasible, it entails a substantial risk of systematic underestimation of actual emissions – particularly given the highly specialized and often energy-intensive demands of scientific research.
In contrast, emissions from travel activities – aside from purely administrative challenges in data aggregation, which can be mitigated with relatively little effort – can be captured with sufficient robustness, both in terms of absolute magnitude and at a high level of granularity.
Overall, the current data situation is insufficient to enable researchers to implement data-based emission reduction measures. The identification and prioritization of mitigation potentials can presently hardly be grounded in robust emissions data. Neither is the relevance of individual emission sources transparent in the context of total emissions – thus precluding a sound cost-benefit assessment – nor can implemented measures be systematically evaluated and their effectiveness quantitatively assessed.
Contact
The pilot project was carried out by Dr. rer. nat. Florian Freundt. He earned his doctorate at the Institute of Environmental Physics (IUP) in Heidelberg and subsequently led a laboratory there for several years as a postdoctoral researcher. The project was based at the Heidelberg Center for the Environment (HCE).
