The flood risk is a function of the flood hazard, the exposed values and their vulnerability. In addition to extreme hydrological events, different anthropogenic activities such as extensive urbanization and land use play an important role in producing catastrophic floods.Considerations of both physical and social dimensions are therefore equally important in flood risk assessment. However, very often the risk assessment studies either focus on physical or social dimensions. In addition, the available studies often focus on economic valuation of only direct tangible costs. In this study, we provide an integrated flood risk assessment approach that go beyond valuation of direct tangible costs, through incorporating physical dimensions in hazard and exposure and social dimensions in vulnerability. The method has been implemented in the Dhaka City, Bangladesh, an area internationally recognized hotspot for flood risk. In this study, flood hazards for different return periods are calculated in spatial environment using a hydrologic model, HEC-RAS. Vulnerability is assessed through aggregation of various social dimensions i.e., coping and adaptive capacities, susceptibility. We assess vulnerability for both baseline and improved scenario. In the baseline scenario, current early warning for study area is considered. In the alternative scenario, the warning system is expected to improve. Aggregating hazard, exposure and vulnerability, risk maps (in terms of both tangible and intangible costs) of several return period floods are produced for both baseline and improved scenario. Compared to traditional assessments, the integrated assessment approach used in this study generates more information about the flood risk. Consequently, the results are useful in evaluating policy alternatives and minimizing property loss in the study area.

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Food fraud is receiving considerable attention with the growing body of literature that recognises its importance. No system exists that collects media reports on food fraud. In this study, we used the infrastructure provided by the European Media Monitor (EMM), in particular it's MedISys portal for this purpose. We developed a food fraud tool (MedISys-FF) that collects, processes and presents food fraud reports published world-wide in the media. MedISys-FF is updated every 10 min 24/7. Food fraud reports were collected with MedISys-FF for 16 months (September 2014 to December 2015) and benchmarked against food fraud reports published in Rapid Alert for Food and feed (RASFF), Economically Motivated Adulteration Database (EMA) and HorizonScan. The results showed that MedISys-FF collects food fraud publications with high relevance > 75% and the top 4 most reported fraudulent commodities in the media were i) meat, ii) seafood, iii) milk and iv) alcohol. These top stories align with those found in RASFF and EMA but differences in frequency are apparent. Analysis of the collected articles can help understanding food fraud issues in the origin countries and can facilitate the development of control measures and to detect food fraud in the food supply chain.

Essential environmental resources are rapidly exploited globally, while socialecological systems at different scales fail to meet sustainable development challenges. Ecosystem services research, which at present predominantly utilizes static modelling approaches, needs better integration with socio-economic dynamics in order to assist a scientific approach to sustainability. This article focuses on Brownfield lands, a unique landscape that is undergoing transformations and provides ecosystem services that remain, at this point in time, mostly unrecognized in public discourse. We discuss the main issues associated with current modelling and valuation approaches and formulate an ecosystem-based integrated redevelopment workflow applied to the assessment of Brownfield redevelopment options.

This article presents a novel methodology to assess flood risk to people by integrating people's vulnerability and ability to cushion hazards through coping and adapting. The proposed approach extends traditional risk assessments beyond material damages; complements quantitative and semi-quantitative data with subjective and local knowledge, improving the use of commonly available information; and produces estimates of model uncertainty by providing probability distributions for all of its outputs. Flood risk to people is modeled using a spatially explicit Bayesian network model calibrated on expert opinion. Risk is assessed in terms of (1) likelihood of non-fatal physical injury, (2) likelihood of post-traumatic stress disorder and (3) likelihood of death. The study area covers the lower part of the Sihl valley (Switzerland) including the city of Zurich. The model is used to estimate the effect of improving an existing early warning system, taking into account the reliability, lead time and scope (i.e., coverage of people reached by the warning). Model results indicate that the potential benefits of an improved early warning in terms of avoided human impacts are particularly relevant in case of a major flood event