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In the Paris Accord to the UN Climate Change Conference COP21 in 2015, the international community agreed to "make every effort" to reach a significant reduction in greenhouse gas (GHG) emissions and to limit global average temperature rise to preferably 1.5°C by 2100 (UNFCC 2018). A transition to a climate-friendly energy supply, however, would come largely at the expense of coal - a fossil fuel with large global reserves that are also widely dispersed regionally. Therefore, especially since the turn of the millennium, the question has been raised as to how coal could be used in a climate-friendly way in the future. So far, the only way to do this is to apply CCS technology or CCU. CCS involves the capture of carbon dioxide (CO2) emissions from fossil fuel-fired power plants or industrial sources and its storage underground, such as in deep saline aquifers or in depleted oil and natural gas fields, or their use for enhanced oil or gas recovery (EOR/EGR). When carbon capture and utilisation (CCU) is applied, the CO2 is further used, for example as feedstock for the production of durable plastics. Due to the relatively low potential of CCU compared to CCS (IPCC 2005), only CCS is considered in this thesis.
The majority of studies and roadmaps have discussed CCS as a technology option that could make a significant contribution to achieving the objective of decreasing GHG emissions for many years (IPCC 2014a, 2018). Particularly in the power sector, however, these expectations have not yet been met. As of November 2019, worldwide only two small base-load power plants, capturing a total of 2.4 Mt CO2/year and mainly using it for EOR, are in operation, together with a few pilots in industrial applications and, in particular, natural gas processing (in total 30 Mt CO2/year) (Global CCS Institute 2019).
Early on, it became clear that the predicted high deployment targets and their underlying studies should be critically questioned for various reasons. Particularly due to the lack of a systems-analytical evaluation of this technology (which was relatively new at the time), no reliable answers could be given about the ecological, economic, social and structural effects of its large-scale application. Such analyses are, however, a pre-condition for comprehensively classifying the contribution of a new technology as a promising option for a sustainable energy supply system and assessing it in comparison to other technologies.
To address these challenges, several studies, most of which initiated by the author, were conducted on this topic between 2004 and 2018. The resulting papers became the basis for this thesis.
With increasing world population and an unsettling resource scarcity in the back, sustainble consumption has moved to the foreground of political, economical and social discussions. One major school-of-thought is Circular Economy (CE), an approach summarizing various sustainable consumption activites under one roof. However, quantitative studies on the consumer are rare, yet crucial for a transfer from linear to circular consumption. This dissertation adds to literature by providing pioneer insights into consumer behavior in CE as an overarching concept, instead limiting research on singular subconcepts. Namely, four consumer activities are studied: recycling, upcycling, renting and sharing. In order to identify relevant insights for both academics and practitioners in CE, the research question ("what drives participation in CE?") is broken down into sub-hypotheses, which are addressed by three empirical studies. Using the SOR-Model (adaption Belk 1975) as overarching logic, the three studies deal with (1) the consumer (and their motivation) and situational stimuli (both (2) offline and (3) online). Respectively, three data sets are consulted to assess the sub-hypotheses and to identify overarching insights on how to accelerate consumer participation in CE, The research methodology employed ranges from a structured equation model (SEM), a random allocation field experiment during Fashion Week in Berlin to a discrete-choice model with best-worst scaling. The dissertation succeeds in revealing that (1) different activities in CE can be summarized in one latent variable, proving CE as a wholesome concept in consumer-related activities; that (2) Trust has a leveraging effect on participation in CE activities. Further, Trust can be enhanced offline via face-to-face interaction and online via third-party online attributes.; and that (3) experience in CE activities affects perception of online attributes, implying the need for adapted measures when dealing with CE-unexperienced consumers as compared to consumers with prior experience in CE activities.
Ambition coefficients : aligning baselines for international carbon markets with net zero pathways
(2021)
Climate change is a transformation challenge. It requires the transformation of a patchwork of independent socio-technical systems. These complex systems have their own specific challenges and path dependencies. Lukas Hermwille introduces a perspective on socio-technical complexity to the study of global climate governance and asks what governance arrangements on the international level, in particular the United Nations Framework Convention of Climate Change (UNFCCC) and its Paris Agreement, can offer to facilitate and foster the required transformational change. His work shows the importance of the discursive power of global climate governance, shifting the expectations and visions of the future of key actors and, as a corollary, changing their investment decisions of today towards a more sustainable future.
The COVID-19 pandemic has affected human mobility via lockdowns, social distancing rules, home quarantines, and the full or partial suspension of transportation. Evidence-based policy recommendations are urgently needed to ensure that transport systems have resilience to future pandemic outbreaks, particularly within Global South megacities where demand for public transport is high and reduced access can exacerbate socio-economic inequalities. This study focuses on Metro Manila - a characteristic megacity that experienced one of the most stringent lockdowns worldwide. It analyzes aggregated cell phone and GPS data from Google and Apple that provide a comprehensive representation of mobility behavior before and during the lockdown. While significant decreases are observed for all transport modes, public transport experienced the largest drop (-74.5 %, on average). The study demonstrates that: (i) those most reliant on public transport were disproportionately affected by lockdowns; (ii) public transport was unable to fulfil its role as public service; and, (iii) this drove a paradigm shift towards active mobility. Moving forwards, in the short-term policymakers must promote active mobility and prioritize public transport to reduce unequal access to transport. Longer-term, policymakers must leverage the increased active transport to encourage modal shift via infrastructure investment, and better utilize big data to support decision-making.
In this thesis, the systematic, situation-oriented selection of approaches to sustainability assessment and effects of selection on assessment results are investigated. The central focus lies on the practice-oriented design of a framework to support selection decisions as well as the necessary criteria and scales for the systematic, quantifiable description of assessment approaches and assessment situations within such a framework. Sustainability assessments are important instruments for the derivation of goals, strategies and measures for shaping sustainable development in all domains. They provide decision-makers in science, industry, politics and society with vital answers to sustainability-related questions that arise in the most diverse contexts. Numerous different assessment approaches are available for carrying out sustainability assessments within such assessment situations. Because of the multitude and diversity of assessment situations and approaches, not every approach is fitting for every situation. In current practice, the fit between approaches and assessment situations is not, or only insufficiently, taken into account when selecting sustainability assessment approaches. Furthermore, no systematic studies have yet been conducted on the effects of approach selection on assessment results. The central result of this work is a concept for the situation-oriented selection support of sustainability assessment approaches based on a Multi-Criteria Decision-Making framework. With the framework, "fitness scores" are calculated, which are used to quantify and operationalize the fit between assessment approaches and assessment situations. With the developed concept, different assessment approaches are selected and exemplarily applied within a use case. Hereby, the effects of approach selection on assessment results are examined. On the basis of the knowledge gained with regard to approach selection, framework development and application, the potentials and limits of assessment approaches widely fitting for diverse assessment situations are finally derived.