Deviant behaviour on various levels of the food supply chain may cause food risks. It entails irregular technological procedures which cause (increased probabilities of) adverse outcomes for buyers and consumers. Besides technological hazards and hitherto unknown health threats, moral hazard and malpractice in food businesses represent an additional source of risk which can be termed 'behavioural food risk'. From a regulatory perspective, adverse outcomes associated with deviance represent negative externalities that are caused by the breaking of rules designed to prevent them. From a rational choice perspective, the probability of malpractice increases with the benefits for its authors. It decreases with the probability of detection and resulting losses. It also decreases with bonds to social norms that protect producers from yielding to economic temptations. The design of mechanisms that reduce behavioural risks and prevent malpractice requires an understanding of why food businesses obey or do not obey the rules. This project aims to contribute to a better understanding of malpractice on the restaurant/retail level through comparative case studies and statistical analyses of food inspection and survey data. Accounting for the complexity of economic behaviour, we will not only look at economic incentives but consider all relevant behavioural determinants, including social context factors.
Farm structures are often characterized by regional heterogeneity, agglomeration effects, sub-optimal farm sizes and income disparities. The main objective of this study is to analyze whether this is a result of path dependent structural change, what the determinants of path dependence are, and how it may be overcome. The focus is on the German dairy sector which has been highly regulated and subsidized in the past and faces severe structural deficits. The future of this sector in the process of an ongoing liberalization will be analyzed by applying theoretical concepts of path dependence and path breaking. In these regards, key issues are the actual situation, technological and market trends as well as agricultural policies. The methodology will be based on a participative use of the agent-based model AgriPoliS and participatory laboratory experiments. On the one hand, AgriPoliS will be tested as a tool for stakeholder oriented analysis of mechanisms, trends and policy effects. This part aims to analyze whether and how path dependence of structural change can be overcome on a sector level. In a second part, AgriPoliS will be extended such that human players (farmers, students) can take over the role of agents in the model. This part aims to compare human agents with computer agents in order to overcome single farm path dependence.
To overcome the limitation in spatial and temporal resolution of methane oceanic measurements, sensors are needed that can autonomously detect CH4-concentrations over longer periods of time. The proposed project is aimed at:- Designing molecular receptors for methane recognition (cryptophane-A and -111) and synthesizing new compounds allowing their introduction in polymeric structure (Task 1; LC, France); - Adapting, calibrating and validating the 2 available optical technologies, one of which serves as the reference sensor, for the in-situ detection and measurements of CH4 in the marine environments (Task 2 and 3; GET, LAAS-OSE, IOW) Boulart et al. (2008) showed that a polymeric filmchanges its bulk refractive index when methane docks on to cryptophane-A supra-molecules that are mixed in to the polymeric film. It is the occurrence of methane in solution, which changes either the refractive index measured with high resolution Surface Plasmon Resonance (SPR; Chinowsky et al., 2003; Boulart et al, 2012b) or the transmitted power measured with differential fiber-optic refractometer (Boulart et al., 2012a; Aouba et al., 2012).- Using the developed sensors for the study of the CH4 cycle in relevant oceanic environment (the GODESS station in the Baltic Sea, Task 4 and 5; IOW, GET); GODESS registers a number of parameters with high temporal and vertical resolution by conducting up to 200 vertical profiles over 3 months deployment with a profiling platform hosting the sensor suite. - Quantifying methane fluxes to the atmosphere (Task 6); clearly, the current project, which aims at developing in-situ aqueous gas sensors, provides the technological tool to achieve the implementation of ocean observatories for CH4. The aim is to bring the fiber-optic methane sensor on the TRL (Technology Readiness Level) from their current Level 3 (Analytical and laboratory studies to validate analytical predictions) - to the Levels 5 and 6 (Component and/or basic sub-system technology validation in relevant sensing environments) and compare it to the SPR methane sensor, taken as the reference sensor (current TRL 5). This would lead to potential patent applications before further tests and commercialization. This will be achieved by the ensemble competences and contributions from the proposed consortium in this project.
Dairy farming across Germany displays diverse production systems. Factor endowment, management, technology adoption as well as competitive dynamics in the local or regional land, agribusiness and dairy processing sectors contribute to this differentiation on farm level. These differences impact on the ability of dairy farms and regional dairy production systems to successfully respond to pressures arising from future market and policy changes. The overall objective of the research activities of which this project is a part of, is to develop a thorough understanding of the processes that govern the spatial dynamics of dairy farm development in different regions in Germany. The central hypothesis of this research project is that management system and technological choices differ systematically across local production and market conditions. The empirical approach will focus on the estimation of farm specific nonparametric cost functions for dairy farms located in across Germany differentiated by time and location. A spatially differentiated data base with information on input use, resource availability, as well as local market conditions for land and output markets will be compiled. The nonparametric approach is specifically suited to disclose a more accurate representation of dairy production system heterogeneity across locations and time compared to parametric concepts as it provides the necessary flexibility to accommodate non-linearities relevant for a wide domain of explanatory variables. The methodology employed goes beyond the state of the art of the literature as it combines kernel density estimation with a Bayesian sampling approach to provide theory consistent parameters for each farm in the data sample.The specific methodological hypothesis is that the nonparametric approach is superior to current parametric techniques and this hypothesis is tested using statistical model evaluation. Regarding the farm management and technological choices, we hypothesize that land suitability for feed production determines the farm intensity of dairy production and thus management and technological choices. With respect to the ability of farms to successfully respond to market pressures we hypothesize that farms at the upper and lower tail of the intensity distribution both can generate positive returns from dairy production. These last two hypotheses will be tested using the estimated spatially differentiated farm specific costs and marginal costs.The expected outcomes are of relevance for the agricultural sector and the food supply chain economy as a whole as fundamental market structure changes in the dairy sector are ongoing due to the abolition of the quota regulation in the years 2014/2015. Thus, exact knowledge about differences and development of dairy cost heterogeneity of farms within and between regions are an important factor for the actors involved in the market as well as the political support of this process.
Objective: Water is one of our most precious and valuable resources. It is important to determine how to fairly use, protect and preserve water. New strategies and new technologies are needed to assess the chemical and ecological status of water bodies and to improve the water quality and quantity. The relatively recent progress in micro-electronics and micro-fabrication technologies has allowed a miniaturization of sensors and devices, opening a series of new exciting possibilities for water monitoring. Moreover, robotics and advanced ICTbased technology can dramatically improve detection and prediction of risk/crisis situations, providing new tools for the global management of the water resources. The HydroNet proposal is aimed at designing, developing and testing a new technological platform for improving the monitoring of water bodies based on a network of autonomous, floating and sensorised mini-robots, embedded in an Ambient Intelligence infrastructure. Chemo- and bio-sensors, embedded in the mobile robots will be developed and used for monitoring in real time physical parameters and pollutants in water bodies. Enhanced mathematical models will be developed for simulating the pollutants transport and processes in rivers, lakes and sea. The unmanaged, self-assembling and self-powered wireless infrastructure, with an ever-decreasing cost per unit, will really support decisional bodies and system integrators in managing water bodies resources. The robots and sensors will be part of an Ambient Intelligence platform, which will integrate not only sensors for water monitoring and robot tasks execution, but also communications backhaul systems, databases technologies, knowledge discovery in databases (KDD) processes for extracting and increasing knowledge on water management. Following the computation on stored data, feedback will be sent back to human actors (supervisors, decision makers, industrial people, etc.) and/or artificial actuators, in order to perform actions.
This research will evaluate climate change mitigation options in China and India and the conditions for a strategic cooperation on RD&D and technology transfer with EU. This project will identify and assess technology options that might significantly reduce greenhouse gases (GHG) emissions in China and India in key sectors (i.e. power generation, transport, agriculture, and heavy industry). It will also define the necessary institutional and organizational architecture that would stimulate technology cooperation. The research will emphasize the strategic dimension of RD&D cooperation, and the key role of creating incentives for the participation of developing countries (DCs) in post-2012 GHG emissions reduction strategies and technological cooperation. Finally it will evaluate how the Clean Development Mechanism (CDM) and international emission trading (IET) might improve the attractiveness of new energy technology options for DCs, and thus contribute to stimulate RD&D cooperation and technology transfers toward China and India. The research will be structured around the use of an ensemble of models that will be coupled together via advanced large scale mathematical programming techniques: (i) a World and regional (i.e. China and India) MARKAL/TIMES bottom-up techno-economic models permitting a global assessment of technology options in different regions of the world; (ii) a CGE multi-country and multi-region of the world economy (GEMINI-E3) that includes a representation of developing countries economies (i.e. China and India) permitting an assessment of welfare, terms of trade and emissions trading effects; (iii) a multi-region integrated model (WITCH) representing the effect on economic growth of technology competition in a global climate change mitigation context; (iv) a game theoretic framework that will be implemented to analyze self-enforcing agreements regarding abatement commitment and technological cooperation.
Objectives: The study links East African and European re-searchers into strategic alliances so as to contribute to resolving conflicts prevailing between the needs of different forest stakeholders and the need to sustain the remaining forest and its biodiversity. The project will develop a scientific basis and directly applicable tools for forest ecosystem restoration and sustainable management. The particular objectives are to: - Establish and validate ecological & socio-economic criteria against which status and pro-cesses of forest and its management can be assessed - Assess indicators that permit inference of the status of a particular criterion and to formulate appropriate verifiers - Design and validate nature-based silvicultural tools to gear operations so as to improve local livelihoods and sustain forest resources - Integrate results into appropriate technology packages and disseminate to target-groups. Activities: Establishment of country-specific tandems of local and European institutions. Identification of locally applicable C&I for sustainable forest management and standardisation of research methods. Together with stakeholders, joint development of a framework in which C&I can be verified locally, based on prevailing information and complementary research. Participating NGOs to facilitate establishment of socio-economic context, research institutions to investigate status and dynamics of forests. In parallel, research will commence on silviculturally relevant ecosystem characteristics. Mid-project evaluation of descriptive-analytical 1st project phase so as to formulate the experimental, predictive 2nd phase of the study. Definition of research approaches to calibrate verifiers for indicators and to test silvicultural tools suited to guide the forest ecosystem into the desired direction or status. Research on the management of invasive species, natural establishment of desirable species and on stand improvement treatments. The continuous input and evaluation through an NGO moderator will help to fine-tune and ensure the client-orientated approach of the silvicultural research. A specific communication module serves to translate scientific findings into technological packages relevant to stakeholders. Expected Outcome: Regional framework to assess sustainability of forest management. Silvicultural tools for forest restoration and sustainable forest management. Research findings translated into formats appropriate to the target group, including extension, policy advice and management guidelines.
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