2016): SHARP: integrating a traditional survey with participatory self-evaluation and learning for climate change resilience assessment, Climate and Development, Climate change, population growth and social conflict have left many farmers and pastoralists in sub-Saharan Africa at near constant crisis conditions. Participatory climate resilience assessments can help farmer and pastoralist communities to identify, measure and prioritize actions to improve the climate resilience of their agricultural systems. Self-evaluation and Holistic Assessment of climate change Resilience of farmers and Pastoralists (SHARP) has been developed as a dualpurpose tool, employing participatory methods to help farmers and pastoralists to discuss and understand threats and opportunities, and to prioritize individual and collective actions aimed at improving overall resilience. Additionally, SHARP provides government and programme management with qualitative and quantitative information on a wide variety of important economic and development factors. The development of SHARP faces many challenges inherent to assessing resilience in terms of the complex nature and wide-reaching impacts of climate change. SHARP presents a unique assessment that combines resilience literature and indicators with a participatory self-assessment from the farmers and pastoralists.

Farm systems are exposed to predictable and unpredictable shocks and stresses. Such events may affect the functioning of farm systems and threaten their capacity to provide food in adequate quantities and sufficient quality. The capacity of farm systems to recover, reorganize, and evolve following external shocks and stresses is analysed within the framework of resilience theory. The SHARP (self-evaluation and holistic assessment of climate resilience of farmers and pastoralists) tool was developed to assess the resilience of farm systems to climate change in a participatory way. The SHARP was originally designed for developing countries. This paper outlines the process and changes made to adapt the tool for use in the Swiss farming context, including the challenges and trade-offs of the adaptation. Its first application in the Canton of Vaud provides insights on the levels of resilience to climate change for farmers in Switzerland. The results showed that of twenty-five farmers, “environment” and “market” are two groups of farm-system components where the farm systems are least resilient. The paper provides preliminary comments on agricultural systems in the west of Switzerland that could be explored further.

Multicriteria decision analysis (MCDA) has been applied to various energy problems to incorporate a variety of qualitative and quantitative criteria, usually spanning environmental, social, engineering, and economic fields. MCDA and associated methods such as life-cycle assessments and cost-benefit analysis can also include risk analysis to address uncertainties in criteria estimates. One technology now being assessed to help mitigate climate change is carbon capture and storage (CCS). CCS is a new process that captures CO2 emissions from fossil-fueled power plants and injects them into geological reservoirs for storage. It presents a unique challenge to decisionmakers (DMs) due to its technical complexity, range of environmental, social, and economic impacts, variety of stakeholders, and long time spans. The authors have developed a risk assessment model using a MCDA approach for CCS decisions such as selecting between CO2 storage locations and choosing among different mitigation actions for reducing risks. The model includes uncertainty measures for several factors, utility curve representations of all variables, Monte Carlo simulation, and sensitivity analysis. This article uses a CCS scenario example to demonstrate the development and application of the model based on data derived from published articles and publicly available sources. The model allows high-level DMs to better understand project risks and the tradeoffs inherent in modern, complex energy decisions.

Summary Climate change is one of the most serious threats facing humankind. Mitigating climate change will require a suite of actions to reduce greenhouse gas emissions. Carbon capture and storage (CCS) is a new technology aimed at mitigating climate change by capturing and storing carbon dioxide, typically in deep geological reservoirs. CCS has risks characteristic of new technologies, as well as risks unique to this technology and its application. Large‐scale CCS decision making is complex, encompassing environmental, social, and economic considerations and requiring the risks to be taken into consideration. CCS projects have been cancelled as a result of inadequate assessments of risks. To date, studies assessing CCS have been limited mostly to environmental, social, and economic fields in isolation from each other, predominantly using life cycle assessments (LCAs), cost benefit analyses (CBAs), or surveys of public perception. LCAs, CBAs, and surveys of public perception all have limitations for assessing difficult multifaceted problems. Incompatibilities across CCS assessment methods have hindered the comparison of the results across these single‐discipline studies and limited the possibility of drawing broader conclusions about CCS development. More standardization across assessment methods, study assumptions, functional units, and assessment criteria for CCS could be beneficial to the integration of multiple study results. We propose a set of criteria, which decision analysts could use to develop CCS‐project–specific criteria lists in order to comprehensively assess a CCS project's viability. This list was created by determining the frequency of use of each criterion in recent studies, with a focus on their use across disciplines.

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