The research presented in this thesis investigated the environmental impacts of structural design decisions across the life of buildings located in seismic regions. In particular, the impacts of expected earthquake damage were incorporated into a traditional life cycle assessment (LCA) using a probabilistic method, and links between sustainable and resilient design were established for a range of case-study buildings designed for different seismic performance objectives. These links were quantified using a metric herein referred to as the seismic carbon risk, which represents the expected environmental impacts and resource use indicators associated with earthquake damage during buildings’ life. The research was broken into three distinct parts: (1) a city-level evaluation of the environmental impacts of demolitions following the 2010/2011 Canterbury earthquake sequence in New Zealand, (2) the development of a probabilistic framework to incorporate earthquake damage into LCA, and (3) using case-study buildings to establish links between sustainable and resilient design. The first phase of the research focused on the environmental impacts of demolitions in Christchurch, New Zealand following the 2010/2011 Canterbury Earthquake Sequence. This large case study was used to investigate the environmental impact of the demolition of concrete buildings considering the embodied carbon and waste stream distribution. The embodied carbon was considered here as kilograms of CO2 equivalent that occurs on production, construction, and waste management stage. The results clearly demonstrated the significant environmental impacts that can result from moderate and large earthquakes in urban areas, and the importance of including environmental considerations when making post-earthquake demolition decisions. The next phase of the work introduced a framework for incorporating the impacts of expected earthquake damage based on a probabilistic approach into traditional LCA to allow for a comparison of seismic design decisions using a carbon lens. Here, in addition to initial construction impacts, the seismic carbon risk was quantified, including the impacts of seismic repair activities and total loss scenarios assuming reconstruction in case of non-reparability. A process-based LCA was performed to obtain the environmental consequence functions associated with structural and non-structural repair activities for multiple environmental indicators. In the final phase of the work, multiple case-study buildings were used to investigate the seismic consequences of different structural design decisions for buildings in seismic regions. Here, two case-study buildings were designed to multiple performance objectives, and the upfront carbon costs, and well as the seismic carbon risk across the building life were compared. The buildings were evaluated using the framework established in phase 2, and the results demonstrated that the seismic carbon risk can significantly be reduced with only minimal changes to the upfront carbon for buildings designed for a higher base shear or with seismic protective systems. This provided valuable insight into the links between resilient and sustainable design decisions. Finally, the results and observations from the work across the three phases of research described above were used to inform a discussion on important assumptions and topics that need to be considered when quantifying the environmental impacts of earthquake damage on buildings. These include: selection of a non-repairable threshold (e.g. a value beyond which a building would be demolished rather than repaired), the time value of carbon (e.g. when in the building life the carbon is released), the changing carbon intensity of structural materials over time, and the consideration of deterministic vs. probabilistic results. Each of these topics was explored in some detail to provide a clear pathway for future work in this area
Disasters, either man-made or natural, are characterised by a multiplicity of factors including loss of property, life, environmental degradation, and psychosocial malfunction of the affected community. Although much research has been undertaken on proactive disaster management to help reduce the impacts of natural and man-made disasters, many challenges still remain. In particular, the desire to re-house the affected as quickly as possible can affect long-term recovery if a considered approach is not adopted. Promoting recovery activities, coordination, and information sharing at national and international levels are crucial to avoid duplication. Mannakkara and Wilkinson’s (2014) modified “Build Back Better” (BBB) concept aims for better resilience by incorporating key resilience elements in post-disaster restoration. This research conducted an investigation into the effectiveness of BBB in the recovery process after the 2010–2011 earthquakes in greater Christchurch, New Zealand. The BBB’s impact was assessed in terms of its five key components: built environment, natural environment, social environment, economic environment, and implementation process. This research identified how the modified BBB propositions can assist in disaster risk reduction in the future, and used both qualitative and quantitative data from both the Christchurch and Waimakariri recovery processes. Semi-structured interviews were conducted with key officials from the Christchurch Earthquake Recovery Authority, and city councils, and supplemented by reviewing of the relevant literature. Collecting data from both qualitative and quantitative sources enabled triangulation of the data. The interviewees had directly participated in all phases of the recovery, which helped the researcher gain a clear understanding of the recovery process. The findings led to the identification of best practices from the Christchurch and Waimakariri recovery processes and underlined the effectiveness of the BBB approach for all recovery efforts. This study contributed an assessment tool to aid the measurement of resilience achieved through BBB indicators. This tool provides systematic and structured approach to measure the performance of ongoing recovery
Road networks are highly exposed to natural hazard events, which can lead to significant economic and social consequences. In New Zealand, events such as the 2011 Christchurch earthquake, the 2016 Kaikōura earthquake, and the Cyclone Gabrielle in 2023 have demonstrated the severe consequences of road network disruptions. Traditional post event economic assessments often focus solely on clean-up and repair costs, neglecting the broader and more enduring impacts these events can have. Furthermore, business cases for resilience investments usually fail when quantifying the economic benefits of mitigation strategies, due to the underestimation of road disruption consequences. Importantly, not all road link disruptions contribute equally to these consequences, making the identification of critical road links a key step in resilience focused investment prioritization. Furthermore, traditional transportation asset management typically evaluates the life cycle of roads under normal conditions, such as traffic loads and standard environmental factors, while neglecting the influence of natural hazards. However, these events can significantly alter road deterioration and increase maintenance costs, emphasizing the need for integrating risk and resilience into transportation asset management approaches. This thesis presents a methodology to evaluate road criticality by assessing the economic consequences of road disruptions in combination with a hazard model in a prioritization index. Initially, the consequences are quantified through increased travel time, higher vehicle operating costs, and increased gas emissions. Thereafter, a new consequence model is introduced to estimate the increase in maintenance costs on alternative routes that absorb diverted traffic following a disruption. These consequence models are initially applied in a 'full-scan' analysis approach, where each road link is removed in turn to quantify its potential impact and, therefore, its criticality. Subsequently, a hazard model is integrated to develop a road prioritization index that combines the expected impacts of road disruptions, the individual road link criticality, and the probability of occurrence of natural hazard events. This index is designed to help road agencies in prioritizing mitigation strategies. Furthermore, the proposed methodology can also be applied to quantify the indirect economic impacts of natural hazard events. The methodology is demonstrated using New Zealand’s South Island inter-urban network as a case study, incorporating an earthquake-induced landslide model, with Python based simulations, providing road agencies a valuable tool to quantify the economic benefits of resilience investments
