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Integrated Multi-Trophic Aquaculture takes advantage of the mutualism between some detritivorous fish and phytoplankton. The fish recycle nutrients by consuming live (and dead) algae and provide the inorganic carbon to fuel the growth of live algae. In the meanwhile, algae purify the water and generate the oxygen required by fishes. Such mechanism stabilizes the functioning of an artificially recycling ecosystem, as exemplified by combining the euryhaline tilapia Sarotherodon melanotheron heudelotii and the unicellular alga Chlorella sp. Feed addition in this ecosystem results in faster fish growth but also in an increase in phytoplankton biomass, which must be limited. In the prototype described here, the algal population control is exerted by herbivorous zooplankton growing in a separate pond connected in parallel to the fish-algae ecosystem. The zooplankton production is then consumed by tilapia, particularly by the fry and juveniles, when water is returned to the main circuit. Chlorella sp. and Brachionus plicatilis are two planktonic species that have spontaneously colonized the brackish water of the prototype, which was set-up in Senegal along the Atlantic Ocean shoreline. In our system, water was entirely recycled and only evaporation was compensated (1.5% volume/day). Sediment, which accumulated in the zooplankton pond, was the only trophic cul-de-sac. The system was temporarily destabilized following an accidental rotifer invasion in the main circuit. This caused Chlorella disappearance and replacement by opportunist algae, not consumed by Brachionus. Following the entire consumption of the Brachionus population by tilapias, Chlorella predominated again. Our artificial ecosystem combining S. m. heudelotii, Chlorella and B. plicatilis thus appeared to be resilient. This farming system was operated over one year with a fish productivity of 1.85 kg/m2 per year during the cold season (January to April).

At present, the synthesis of ammonia through the Haber-Bosch (HB) process accounts for 1.2% of the global carbon emissions, representing roughly one-fourth of the global fossil consumption from the chemical industry, which creates a pressing need for alternative low-carbon synthesis routes. Analyzing seven essential planetary boundaries (PBs) for the safe operation of our planet, we find that the standard HB process is unsustainable as it vastly transgresses the climate change PB. In order to identify more responsible strategies from this integrated perspective, we assess the absolute sustainability level of 34 alternative routes where hydrogen (H-2) is supplied by steam methane reforming with carbon capture and storage, biomass gasification, or water electrolysis powered by various energy sources. We found that some of these scenarios could substantially reduce the global impact of fossil HB, yet alleviating the impact on climate change could critically exacerbate the impacts on other Earth-system processes. Furthermore, we identify that reducing the cost of electrolytic H-2 is the main avenue toward the economic appeal of the most sustainable routes. Our work highlights the need to embrace global impacts beyond climate change in the assessment of decarbonization routes of fossil chemicals. This approach enabled us to identify more suitable alternatives and associated challenges toward environmental and economically attractive ammonia synthesis. ACS Sustainable Chemistry & Engineering, 9 (29) ISSN:2168-0485

As the effects of global climate change become more apparent, animal species will become increasingly affected by extreme climate and its effect on the environment. There is a pressing need to understand animal physiological and behavioural responses to climatic stressors. We used the reactive scope model as a framework to investigate the influence of drought conditions on vervet monkey ( Chlorocebus pygerythrus ) behaviour, physiological stress and survival across 2.5 years in South Africa. Data were collected on climatic, environmental and behavioural variables and physiological stress via faecal glucocorticoid metabolites (fGCMs). There was a meaningful interaction between water availability and resource abundance: when food availability was high but standing water was unavailable, fGCM concentrations were higher compared to when food was abundant and water was available. Vervet monkeys adapted their behaviour during a drought period by spending a greater proportion of time resting at the expense of feeding, moving and social behaviour. As food availability decreased, vervet mortality increased. Peak mortality occurred when food availability was at its lowest and there was no standing water. A survival analysis revealed that higher fGCM concentrations were associated with an increased probability of mortality. Our results suggest that with continued climate change, the increasing prevalence of drought will negatively affect vervet abundance and distribution in our population. Our study contributes to knowledge of the limits and scope of behavioural and physiological plasticity among vervet monkeys in the face of rapid environmental change.

Post-processing has received much attention during the last couple of years within the hydrological community, and many different methods have been developed and tested, especially in the field of flood forecasting. Apart from the different meanings of the phrase “post-processing” in meteorology and hydrology, in this paper, it is regarded as a method to correct model outputs (predictions) based on meteorological (1) observed input data, (2) deterministic forecasts (single time series) and (3) ensemble forecasts (multiple time series) and to derive predictive uncertainties. So far, the majority of the research has been related to floods, how to remove bias and improve the forecast accuracy and how to minimize dispersion errors. Given that global changes are driving climatic forces, there is an urgent need to improve the quality of low-flow predictions, as well, even in regions that are normally less prone to drought. For several catchments in Switzerland, different post-processing methods were tested with respect to low stream flow and flooding conditions. The complexity of the applied procedures ranged from simple AR processes to more complex methodologies combining wavelet transformations and Quantile Regression Neural Networks (QRNN) and included the derivation of predictive uncertainties. Furthermore, various verification methods were tested in order to quantify the possible improvements that could be gained by applying these post-processing procedures based on different stream flow conditions. Preliminary results indicate that there is no single best method, but with an increase of complexity, a significant improvement of the quality of the predictions can be achieved.

An aerosol reactor was tested for the thermal reduction of ceria as part of a solar thermochemical redox cycle for producing H2 and CO from H2O and CO2. The design is based on the downward aerosol flow of ceria particles, counter to an argon sweep gas, which are rapidly heated and thermally reduced within residence times of less than 1 s. When operating in the temperature range of 1723–1873 K and at oxygen partial pressures between 5 × 10–5 and 1.2 × 10–4 atm, reduction extents of small particles (Dv50 = 12 μm) approached those predicted by thermodynamics. However, heat- and mass-transfer effects were found to limit their conversion when the ceria mass flow rate was increased above 100 mg s–1. This reactor concept inherently results in separation of the reduced ceria and evolved O2(g), operates isothermally throughout the day, and decouples the reduction and oxidation steps in both space and time for potential 24-h syngas generation.

Optimization models can support decision-makers in the synthesis and operation of multi-sector energy systems. To identify the optimal design and operation of a low-carbon system, we need to consider high temporal and spatial variability in the electricity supply, sector coupling, and environmental impacts over the whole life cycle. Incorporating such aspects in optimization models is demanding. To avoid redundant research efforts and enhance transparency, the developed models and used data sets should be shared openly. In this work, we present the SecMOD framework for multi-sector energy system optimization incorporating life-cycle assessment (LCA). The framework allows optimizing multiple sectors jointly, ranging from industrial production and their linked energy supply systems to sector-coupled national energy systems. The framework incorporates LCA to account for environmental impacts. We hence provide the first open-source framework to consistently include a holistic life-cycle perspective in multi-sector optimization by a full integration of LCA. We apply the framework to a case-study of the German sector-coupled energy system. Starting with few base technologies, we demonstrate the modular capabilities of SecMOD by the stepwise addition of technologies, sectors and existing infrastructure. Our modular open-source framework SecMOD aims to accelerate research for sustainable energy systems by combining multi-sector energy system optimization and life-cycle assessment.

This paper discusses the influence of time horizon on dynamic optimization of small-size wastewater treatment plants alternating aerobic and anoxic processes. The optimization problem consists in determining the aeration policy (air-on and air-off periods) that minimizes the energy dissipated by the aeration system subject to both effluent and operating constraints. Optimization over short time horizons is first considered and reductions of the energy consumption up to 30% are obtained with respect to the usual operating mode of the process. But the application of such aeration strategies eventually results in a biomass wash-out when applied over long time periods. Here, it is shown that long time horizon optimized policies guarantee a durable functioning of the treatment plant. The resulting energy consumption savings are however lower (up to 15%), but are still important.