@phdthesis{Krummenauer2022,
  author    = {Krummenauer, Linda},
  title     = {Global heat adaptation among urban populations and its evolution under different climate futures},
  doi       = {10.25932/publishup-55929},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-559294},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 161},
  year      = {2022},
  abstract  = {Heat and increasing ambient temperatures under climate change represent a serious threat to human health in cities. Heat exposure has been studied extensively at a global scale. Studies comparing a defined temperature threshold with the future daytime temperature during a certain period of time, had concluded an increase in threat to human health. Such findings however do not explicitly account for possible changes in future human heat adaptation and might even overestimate heat exposure. Thus, heat adaptation and its development is still unclear. Human heat adaptation refers to the local temperature to which populations are adjusted to. It can be inferred from the lowest point of the U- or V-shaped heat-mortality relationship (HMR), the Minimum Mortality Temperature (MMT). While epidemiological studies inform on the MMT at the city scale for case studies, a general model applicable at the global scale to infer on temporal change in MMTs had not yet been realised. The conventional approach depends on data availability, their robustness, and on the access to daily mortality records at the city scale. Thorough analysis however must account for future changes in the MMT as heat adaptation happens partially passively. Human heat adaptation consists of two aspects: (1) the intensity of the heat hazard that is still tolerated by human populations, meaning the heat burden they can bear and (2) the wealth-induced technological, social and behavioural measures that can be employed to avoid heat exposure. The objective of this thesis is to investigate and quantify human heat adaptation among urban populations at a global scale under the current climate and to project future adaptation under climate change until the end of the century. To date, this has not yet been accomplished. The evaluation of global heat adaptation among urban populations and its evolution under climate change comprises three levels of analysis. First, using the example of Germany, the MMT is calculated at the city level by applying the conventional method. Second, this thesis compiles a data pool of 400 urban MMTs to develop and train a new model capable of estimating MMTs on the basis of physical and socio-economic city characteristics using multivariate non-linear multivariate regression. The MMT is successfully described as a function of the current climate, the topography and the socio-economic standard, independently of daily mortality data for cities around the world. The city-specific MMT estimates represents a measure of human heat adaptation among the urban population. In a final third analysis, the model to derive human heat adaptation was adjusted to be driven by projected climate and socio-economic variables for the future. This allowed for estimation of the MMT and its change for 3 820 cities worldwide for different combinations of climate trajectories and socio-economic pathways until 2100. The knowledge on the evolution of heat adaptation in the future is a novelty as mostly heat exposure and its future development had been researched. In this work, changes in heat adaptation and exposure were analysed jointly. A wide range of possible health-related outcomes up to 2100 was the result, of which two scenarios with the highest socio-economic developments but opposing strong warming levels were highlighted for comparison. Strong economic growth based upon fossil fuel exploitation is associated with a high gain in heat adaptation, but may not be able to compensate for the associated negative health effects due to increased heat exposure in 30\% to 40\% of the cities investigated caused by severe climate change. A slightly less strong, but sustainable growth brings moderate gains in heat adaptation but a lower heat exposure and exposure reductions in 80\% to 84\% of the cities in terms of frequency (number of days exceeding the MMT) and intensity (magnitude of the MMT exceedance) due to a milder global warming. Choosing a 2 ° C compatible development by 2100 would therefore lower the risk of heat-related mortality at the end of the century. In summary, this thesis makes diverse and multidisciplinary contributions to a deeper understanding of human adaptation to heat under the current and the future climate. It is one of the first studies to carry out a systematic and statistical analysis of urban characteristics which are useful as MMT drivers to establish a generalised model of human heat adaptation, applicable at the global level. A broad range of possible heat-related health options for various future scenarios was shown for the first time. This work is of relevance for the assessment of heat-health impacts in regions where mortality data are not accessible or missing. The results are useful for health care planning at the meso- and macro-level and to urban- and climate change adaptation planning. Lastly, beyond having met the posed objective, this thesis advances research towards a global future impact assessment of heat on human health by providing an alternative method of MMT estimation, that is spatially and temporally flexible in its application.},
  language  = {en}
}
@phdthesis{GomezZapata2023,
  author    = {G{\´o}mez Zapata, Juan Camilo},
  title     = {Towards unifying approaches in exposure modelling for scenario-based multi-hazard risk assessments},
  doi       = {10.25932/publishup-58614},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-586140},
  school      = {Universit{\"a}t Potsdam},
  pages     = {iii, xiii, 155},
  year      = {2023},
  abstract  = {This cumulative thesis presents a stepwise investigation of the exposure modelling process for risk assessment due to natural hazards while highlighting its, to date, not much-discussed importance and associated uncertainties. Although "exposure" refers to a very broad concept of everything (and everyone) that is susceptible to damage, in this thesis it is narrowed down to the modelling of large-area residential building stocks. Classical building exposure models for risk applications have been constructed fully relying on unverified expert elicitation over data sources (e.g., outdated census datasets), and hence have been implicitly assumed to be static in time and in space. Moreover, their spatial representation has also typically been simplified by geographically aggregating the inferred composition onto coarse administrative units whose boundaries do not always capture the spatial variability of the hazard intensities required for accurate risk assessments. These two shortcomings and the related epistemic uncertainties embedded within exposure models are tackled in the first three chapters of the thesis. The exposure composition of large-area residential building stocks is studied on the scope of scenario-based earthquake loss models. Then, the proposal of optimal spatial aggregation areas of exposure models for various hazard-related vulnerabilities is presented, focusing on ground-shaking and tsunami risks. Subsequently, once the experience is gained in the study of the composition and spatial aggregation of exposure for various hazards, this thesis moves towards a multi-hazard context while addressing cumulative damage and losses due to consecutive hazard scenarios. This is achieved by proposing a novel method to account for the pre-existing damage descriptions on building portfolios as a key input to account for scenario-based multi-risk assessment. Finally, this thesis shows how the integration of the aforementioned elements can be used in risk communication practices. This is done through a modular architecture based on the exploration of quantitative risk scenarios that are contrasted with social risk perceptions of the directly exposed communities to natural hazards. In Chapter 1, a Bayesian approach is proposed to update the prior assumptions on such composition (i.e., proportions per building typology). This is achieved by integrating high-quality real observations and then capturing the intrinsic probabilistic nature of the exposure model. Such observations are accounted as real evidence from both: field inspections (Chapter 2) and freely available data sources to update existing (but outdated) exposure models (Chapter 3). In these two chapters, earthquake scenarios with parametrised ground motion fields were transversally used to investigate the role of such epistemic uncertainties related to the exposure composition through sensitivity analyses. Parametrised scenarios of seismic ground shaking were the hazard input utilised to study the physical vulnerability of building portfolios. The second issue that was investigated, which refers to the spatial aggregation of building exposure models, was investigated within two decoupled vulnerability contexts: due to seismic ground shaking through the integration of remote sensing techniques (Chapter 3); and within a multi-hazard context by integrating the occurrence of associated tsunamis (Chapter 4). Therein, a careful selection of the spatial aggregation entities while pursuing computational efficiency and accuracy in the risk estimates due to such independent hazard scenarios (i.e., earthquake and tsunami) are discussed. Therefore, in this thesis, the physical vulnerability of large-area building portfolios due to tsunamis is considered through two main frames: considering and disregarding the interaction at the vulnerability level, through consecutive and decoupled hazard scenarios respectively, which were then contrasted. Contrary to Chapter 4, where no cumulative damages are addressed, in Chapter 5, data and approaches, which were already generated in former sections, are integrated with a novel modular method to ultimately study the likely interactions at the vulnerability level on building portfolios. This is tested by evaluating cumulative damages and losses after earthquakes with increasing magnitude followed by their respective tsunamis. Such a novel method is grounded on the possibility of re-using existing fragility models within a probabilistic framework. The same approach is followed in Chapter 6 to forecast the likely cumulative damages to be experienced by a building stock located in a volcanic multi-hazard setting (ash-fall and lahars). In that section, special focus was made on the manner the forecasted loss metrics are communicated to locally exposed communities. Co-existing quantitative scientific approaches (i.e., comprehensive exposure models; explorative risk scenarios involving single and multiple hazards) and semi-qualitative social risk perception (i.e., level of understanding that the exposed communities have about their own risk) were jointly considered. Such an integration ultimately allowed this thesis to also contribute to enhancing preparedness, science divulgation at the local level as well as technology transfer initiatives. Finally, a synthesis of this thesis along with some perspectives for improvement and future work are presented.},
  language  = {en}
}