Cities are growing and becoming more complex, and as they continue to do so, their capacity to deal with foreseen and unforeseen challenges derived from climate change has to adapt accordingly. In the last decade, an effort has been made to build city resilience and improve cities’ capacity to respond to, recover from and adapt to climate change. However, certain city stakeholders’ lack of proactive behavior has resulted in less effective city resilience-building strategies. In this sense, the importance of developing stakeholders’ awareness of climate change in order to ensure proactivity is documented in the literature. However, there is a lack of studies that define how, when and what should be done to develop stakeholders’ climate change awareness at a city scale. This paper presents a framework to develop stakeholders climate change awareness as a result of a systematic literature review and a co-creation process with the participation of 47 experts through a focus group and a Delphi study. The framework defines a four-step process and includes nine policies that seek to develop stakeholders’ climate change awareness. The framework concludes determining the responsibilities of each stakeholder by defining the policies they should implement, and the effect one policy might cause on other stakeholders and among policies.

No abstract

Critical Infrastructures (CIs) are resources that are essential for the performance of society, including its economy and its security. Large-scale disasters, whether natural or man-made, can have devastating primary (direct) effects on some CI and significant indirect effects (cascading effects) on other CIs, because CIs are interconnected and depend on each other's services. Recent work by Laugé et al. expressed the dependency values among CIs as dependency matrices for various durations of the primary CI failure. For better preparedness and mitigation of CI failures knowledge of the weak points in CI interdependencies is crucial. To this effect, we have developed a MATLAB code that identifies the forward paths and loops between pairs of CIs based on a simplified version of Laugé's matrices. The code calculates the parallel forward paths and loops dependencies to identify and quantify the amplification of cascading effects of any disruption that might hit one of the CIs included in the research. A main consequence, which has implications for expert assessment of dependencies between CIs, is that the cascading effects are not limited to the direct values expressed in the dependency matrices.

No abstract

No abstract