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Model projections show that production of high-value products from microalgae could be profitable nowadays and commodities will become profitable within 10 years.

<p>High temperature aquifer thermal energy storage (HT-ATES) can play a key role for a sustainable interplay between different energy sources and in the overall reduction of CO<sub>2</sub>emission. In this study, we numerically investigate the thermo-hydraulic processes of an HT-ATES in the Greater Geneva Basin (Switzerland). The main objective is to investigate how to handle the yearly excess of heat produced by a nearby waste-to-energy plant. We consider potential aquifers located in different stratigraphic units and design the model from available geological and geophysical data. Aquifer properties, flow conditions and well strategies are successively tested to evaluate their influence on the HT-ATES economic performance and environmental impact. This was achieved using a new open-access, user-friendly and efficient code that we also introduce here as a possible tool for geothermal applications.</p><p> </p><p>The results highlight the importance of thorough numerical simulations based on more realistic exploitation when designing HT-ATES systems. We show that relations between thermal performance and the shape of the injected thermal volume are generally hard to derive when complex well schedules are imposed because the injected/produced volumes may not be equal. Despite more complex storage strategies to comply with legal regulations, the shallower group of investigated aquifers in this study remains economically more suitable for storage up to 90ºC. In average four well doublets will be required to store the yearly excess of energy. The deeper group of investigated aquifers, however, become interesting for storage at higher temperatures.</p>

ABSTRACT Three graduate-level short courses on ecological agriculture and food systems were held in 1995–1997 in Norway to introduce systems thinking, creative research methods, and innovative learning approaches. In 1999, a three-day evaluation and planning workshop was held to assess course impacts, to determine relative importance of content areas, to compare learning methods with special attention to case studies, and to vision and develop action plans for future education in the region. Students and faculty agreed that soft systems research methods and varied learning processes in the course were more valuable than specific technical content that can be learned in other venues. Nine priority education areas were identified for ecological agriculture: (1) systems thinking, (2) research methods, (3) farmer/stakeholder participation, (4) improving production methods, (5) relating agriculture to food systems, (6) learning about learning, (7) values and ethics, (8) faculty development and institutional ch...

Despite the scientific evidence that more plants and less animal-based food is more sustainable, policy interventions to reduce meat consumption are scarce. However, campaigns for meat free days in school and office canteens have spread globally over the last years. In this paper, we look at the Norwegian Armed Forces’ attempt to introduce the Meatless Monday campaign in their camps, and we evaluate the implementation process as well as the effect of the campaign on soldiers. Qualitative interviews with military staff indicate that lack of conviction about benefits of meat reduction, and the fact that kitchen staff did not feel ownership to the project, partly explain why vegetarian measures were not fully implemented in all the camps. A multivariate regression analysis with survey data from soldiers indicate that those who have experienced meat free days in the military kitchen are more prone to claim that joining the military has given them a more positive view on vegetarian food. Furthermore, the survey gives evidence that stated willingness to eat more vegetarian food is higher among soldiers who believe in the environmental and health benefits of meat reduction.

Abstract An assessment of the human impact on the global water cycle requires estimating the volume of water withdrawn for irrigated agriculture. A key parameter in this calculation is the irrigation efficiency, which corrects for the fraction of water lost between irrigation withdrawals and the crop due to management, distribution or conveyance losses. Here we show that the irrigation efficiency used in global irrigation models is flawed for it overlooks key ambiguities in partial efficiencies, irrigation technologies, the definition of ‘large-scale’ irrigated areas or managerial factors. Once accounted for, these uncertainties can make irrigation withdrawal estimates fluctuate by more than one order of magnitude at the country level. Such variability is larger and leads to more extreme values than that caused by the uncertainties related with climate change. Our results highlight the need to embrace deep uncertainties in irrigation efficiency to prevent the design of shortsighted policies at the river basin-water-agricultural interface.

Crop adaptation to climate change requires accelerated crop variety introduction accompanied by recommendations to help farmers match the best variety with their field contexts. Existing approaches to generate these recommendations lack scalability and predictivity in marginal production environments. We tested if crowdsourced citizen science can address this challenge, producing empirical data across geographic space that, in aggregate, can characterize varietal climatic responses. We present the results of 12,409 farmer-managed experimental plots of common bean ( Phaseolus vulgaris L.) in Nicaragua, durum wheat ( Triticum durum Desf.) in Ethiopia, and bread wheat ( Triticum aestivum L.) in India. Farmers collaborated as citizen scientists, each ranking the performance of three varieties randomly assigned from a larger set. We show that the approach can register known specific effects of climate variation on varietal performance. The prediction of variety performance from seasonal climatic variables was generalizable across growing seasons. We show that these analyses can improve variety recommendations in four aspects: reduction of climate bias, incorporation of seasonal climate forecasts, risk analysis, and geographic extrapolation. Variety recommendations derived from the citizen science trials led to important differences with previous recommendations.