Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-10473
Authors: Schieberle, Christian
Title: Development of a stochastic optimization approach to determine cost-efficient environmental protection strategies : case study of policies for the future European passenger transport sector with a focus on rail-bound and on-road activities
Issue Date: 2019
Publisher: Stuttgart : Universität Stuttgart, Institut für Energiewirtschaft und Rationelle Energieanwendung
metadata.ubs.publikation.typ: Dissertation
metadata.ubs.publikation.seiten: xxx, 218
Series/Report no.: Forschungsbericht / Institut für Energiewirtschaft und Rationelle Energieanwendung;137
URI: http://elib.uni-stuttgart.de/handle/11682/10490
http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-104903
http://dx.doi.org/10.18419/opus-10473
ISSN: 0938-1228
Abstract: Recurrent violation of air quality standards detected at measuring stations worries city authorities across Europe. Accompanied by the recent disclosure of large-scale irregularities in real driving vehicle emissions air pollution control has nowadays taken on greater significance than ever before. Decision-makers aim to reduce the amount adverse effects of polluted air and climate change simultaneously by implementing proper legislation. However, they face severe uncertainties when estimating both people’s response to policies and the resulting environmental impact. Obviously, this imposes risk on achieving the desired effect. Furthermore, failure to succeed in reducing the adverse impacts lowers acceptance of policies among the general public. Recent studies in this field do not sufficiently account for this risk and ignore a decision-maker’s level of risk-aversion when recommending policies: While some of the studies acknowledge the existence of large uncertainties in impact estimation, they do not adequately incorporate current knowledge in the analysis. Some studies use expected values only during the optimization approach which leads to results that cannot be considered recommendations for risk-averse decision-makers. Other approaches deliberately overestimate costs in the presence of uncertainty and even exclude uncertain aspects of the assessment entirely from the analysis. A stochastic optimization approach to determine cost-efficient environmental protection strategies via cost-benefit analysis (CBA) is developed in this thesis. Furthermore, it is integrated into a novel modelling framework that incorporates uncertainty of environmental impacts as well as uncertainty of people’s response to policy in a consistent manner. Policy intervention is modelled via implementation of both technical and non-technical measures. A case study is conducted, and its results are presented and discussed. It investigates how further improvements can be achieved in the passenger transport sector of the 28 EU member states plus Norway and Switzerland.
Appears in Collections:04 Fakultät Energie-, Verfahrens- und Biotechnik

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