Research

The Emission Trading System 2 of the European Union (ETS2) will introduce uniform EU-wide carbon pricing for fossil car fuels, affecting a large share of households across the Union. A recent study on residential heating (Bertelsmann Stiftung 2026), using a synthetic EU population of 188 million households, shows that while roughly half of all households are affected, the majority can absorb the additional costs. However, a significant minority faces substantial financial burdens – particularly in Eastern and Southern Europe. The study further demonstrates that ETS2 revenues are, in principle, sufficient to cushion the most adverse distributional impacts. Beyond residential energy use, fossil car fuel consumption constitutes the second major sector covered by ETS2. Yet this sector has not been analysed with comparable granularity. Closing this gap is essential, not least because a comprehensive assessment is required to evaluate the full redistributive potential of ETS2 revenues. This project therefore aims to provide a detailed analysis of the regional and social impacts of carbon pricing in the transport sector, thereby enabling a more complete and policy-relevant evaluation of ETS2.

The project explores the environmental history of forests in the area of the present-day national park Berchtesgaden, building on the historical sources kept in the local forest archive. It pursues two main thematic foci: The first explores how forest use (management, forest grazing, hunting) evolved in Berchtesgaden since the late 18th century. It further investigates the effects of these management changes on forest C dynamics. Important sources include visitation protocols, forest maps, forest cutting plans and overviews, and descriptions of servitute rights. Using methods such as C accounting and modelling, C stocks and fluxes in forest ecosystems will be reconstructed and analysed over long time periods and in a spatially explicit way. The second research focus inquires how historical interventions (or their cessation) affect present-day biodiversity in the forests of Berchtesgaden. To this end, the data compiled in the first thematic focus will be complemented by further spatially explicit data and recent datasets on biodiversity and spatially analysed. The topics will be further developed in an environmental history dissertation project and specified depending on source availability, and in case of need, additional sources will be consulted beyond those of the Forest Archive in Berchtesgaden.

Levels and structure of energy and resource demands are increasingly recognized as a key critical determinant of feasibility, timing, and costs of climate mitigation actions and their SDG synergies and tradeoffs. The higher the demand, the earlier, the more stringent, and the more costly climate mitigation will have to be. Conversely, lower demands increase the temporal flexibility of climate mitigation and reduce the stringency and costs of mitigation actions, thus also reducing the risks of SDG tradeoffs. Energy and resource demands themselves are intermediary variables, and it is the services and amenities that the use of energy and other resources provides. The efficiency of resource use and the efficiency of alternative service provision models thus moves into center stage of climate mitigation from a demand, or end-use perspective. Because of the high heterogeneity of consumers and the multitude of demand types (food, shelter, mobility, communication, etc.) the theoretical understanding and modeling of “demand” (outside aggregated simplistic formulation) remains limited and fragmented, as are resulting capabilities to propose and to assess demand-side policy interventions from the twin angle of climate mitigation as well as of promoting the SDGs. Overall project objectives 1. to improve the state-of-art of demand modeling in environmental and climate policy analysis, via methods and model intercomparisons and assisting the transfer of conceptual and methodological improvements across disciplines, sectors, and environmental domains. 2. to better inform policy via structured model experiments and simulations that assess potential impacts, barriers, as well as synergies and tradeoffs to other SDG objectives of demand-side policy interventions, particularly in novel fields and service provision models such as digitalization, sharing economy, or the integration of SDG and climate objectives in synergistic policy designs. 3. EDITS focuses on both the human and the technical resources by launching an expert network and a demand-side model comparison exercise.