Integrated Modeling of Spatial and Temporal Heterogeneities and Decisions Induced by Catastrophic Events

This paper discusses an integrated model capable of dealing with spatial and temporal heterogeneities induced by extreme events, in particular weather related catastrophes. The model can be used for quite different problems which take explicitly into account the specifics of catastrophic risks: highly mutually dependent losses, inherent capacity of information, the need for long-term perspectives (temporal heterogeneity) and geographically explicit analyses (spatial heterogeneity) with respect to losses and gains of various agents such as individuals, governments, farmers, products, consumers, insurers, investors, and their decisions on coping with risks. We illustrate emerging challenging decision-making problems with a case study of severe floods in a pilot region in the Upper Tisza River. Special attention is given to the evaluation of a flood loss-spreading program taking explicitly into account location specific distributions of agricultural and structural losses. This enables us to evaluate premiums, insurance coverage, and governmental compensation schemes minimizing, in a sense, the risk of locations to overpay actual losses, risks of bankruptcy/insolvency for insurers, and overcompensation of losses by the government. GIS-based catastrophe models and stochastic optimization methods are used to guide policy analysis with respect to location-specific risk exposures. We use special risk functions in order to convexity discontinuous insolvency constrains

Discounting and catastrophic risk management

The risk management of complex coupled human-environmental systems essentially relies on discounting future losses and gains to their present values. These evaluations are used to justify catastrophic risks management decisions which may turn into benefits over long and uncertain time horizons. The misperception of proper discounting rates critically affects evaluations and may be rather misleading. Catastrophes are not properly treated within conventional economic theory. The lack of proper evaluations dramatically contributes to increasing the vulnerability of our society to human-made and natural disasters. Underestimation of rare low probability - high consequences potentially catastrophic scenarios (events) have led to the growth of buildings and industrial land and sizable value accumulation in flood (and other disaster) prone areas without paying proper attention to flood mitigations. A challenge is that an extreme event, say a once-in-300-year flood which occurs on average only once in 300 years, may have never occurred before in a given region. Therefore, purely adaptive policies relying on historical observations provide no awareness of the risk although, a 300-year flood may occur next year. For example, floods in Austria, Germany and the Czech Republic in 2002 were classified as 1000-, 500-, 250-, and 100-year events. Chernobyl nuclear disaster was evaluated as 106-year event. Yet common practice is to ignore these types of events as improbable events during a human lifetime. This paper analyzes the implications of potentially catastrophic events on the choice of discounting for long-term catastrophic risk management. It is shown that arbitrary discounting can be linked to "stopping time" events, which define the discount-related random horizon ("end of the world") of valuations. In other words, any discounting compares potential gains and losses only within a finite random discount-related stopping time horizon. The expected duration of this horizon for standard discount rates obtained from capital markets does not exceed a few decades and, as such, these rates cannot properly evaluate impacts of 1000-, 500-, 250-, 100- year catastrophes. The paper demonstrates that the correct discounting can be induced by the concept of stopping time, i.e. by explicit modelling of arrival time scenarios of potential catastrophes. In general, catastrophic events affect the induced discount rates, which alter the optimal mitigation efforts that, in turn, change events. The paper shows that stopping-time related discounting calls for the use of stochastic optimisation methods. Combined with explicit spatio-temporal catastrophe modelling, this induces the discounting which allows to properly focus risk management solutions on arrival times of potential catastrophic events rather then horizons of capital markets

The development of a resource-efficient photovoltaic system

This paper presents the measures taken in the demonstration of the photovoltaic case study developed within the European project ‘Towards zero waste in industrial networks’ (Zerowin), integrating the D4R (Design for recycling, repair, refurbishment and reuse) criteria at both system and industrial network level. The demonstration is divided into three phases. The first phase concerns the development of a D4R photovoltaic concept, the second phase focused on the development of a specific component of photovoltaic systems and the third phase was the demonstration of the D4R design in two complete photovoltaic systems (grid-connected and stand-alone). This paper includes a description of the installed photovoltaic systems, including a brief summary at component level of the lithium ion battery system and the D4R power conditioning system developed for the pilot installations. Additionally, industrial symbioses within the network associated with the photovoltaic systems and the production model for the network are described

Modelling the drivers of a widespread shift to sustainable diets

A reduction in global meat consumption can significantly reduce the adverse environmental effects of the food system, but it would require widespread dietary changes. Such shifts to sustainable diets depend on several behavioural factors that have not yet been addressed in relation to the food system. This study links a behavioural diet shift model to an integrated assessment model to identify the main drivers of global diet change and its implications for the food system. The results show that the social norm effect (for instance, the extent of vegetarianism in the population that accelerates a further switch to a vegetarian diet) and self-efficacy are the main drivers of widespread dietary changes. These findings stress the importance of value-driven actions motivated either by intrinsic identity or by group dynamics over health and climate risk perceptions in steering diet change dynamics

Fix the broken food system in three steps

Land use and food production are not meeting people’s needs1. Agriculture destroys forests and biodiversity, squanders water and releases one-quarter of global greenhouse-gas emissions. Yet one-third of food is wasted, 800 million people remain undernourished, 2 billion are deficient in micronutrients, and obesity is on the rise. These figures will worsen as the planet warms, soils degrade and the global population grows, urbanizes and consumes more. Threats to agriculture, climate and health are entwined. Yet policies treat each in isolation and are misaligned. National strategies for mitigating climate change pay scant attention to biodiversity and food security. The European Union’s Common Agricultural Policy includes steps to reduce emissions from livestock and fertilizers, for example, but offers no way of improving diets