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AbstractBACKGROUND: Inappropriate utilisation of biosolids may adversely impact agrosystem productivity. Here, we address the response of wheat (Triticum durum) to different doses (0, 40, 100, 200 and 300 t ha−1) of either municipal solid waste (MSW) compost or sewage sludge in a greenhouse pot experiment. Plant growth, heavy metal uptake, and antioxidant activity were considered.RESULTS: Biomass production of treated plants was significantly enhanced at 40 t ha−1 and 100 t ha−1 of MSW compost (+48% and +78% relative to the control, respectively). At the same doses of sewage sludge, the increase was only 18%. Higher doses of both biosolids restricted significantly the plant growth, in concomitance with the significant accumulation of heavy metals (Ni2+, Pb2+, Cu2+ and Zn2+), especially in leaves. Leaf activities of antioxidant enzymes (ascorbate peroxidase, glutathione reductase, catalase and superoxide dismutase) were unchanged at 40 t ha−1 MSW compost or sewage sludge, but were significantly stimulated at higher doses (200–300 t ha−1), together with higher leaf concentration of reduced glutathione.CONCLUSION: This preliminary study suggests that a MSW supply at moderate doses (100 t ha−1) could be highly beneficial for wheat productivity. Copyright © 2010 Society of Chemical Industry

Le Meillour & Sinet-Mathiot et al. 2024 Increasing sustainability in palaeoproteomics by optimizing digestion times for large-scale archaeological bone analyses DOI: 10.1016/j.isci.2024.109432 MALDI-ToF MS data (raw data: mzML files, merged spectra: msd files) used for the ZooMS analysis of the bone material from Baishiya Karst Cave (China) and La Draga (Spain), along with the R codes for merging triplicates into one msd file. 

Diesel engine exhausts from a common rail 3.0 L F1C diesel engine were analyzed at two different load conditions of the WLTC testing cycle downstream of both the diesel particulate filter (DPF) and selective catalytic reactor (SCR) to verify their effect on the characteristics of carbon particulate matter. An array of chemical, physical and spectroscopic techniques (gas chromatography coupled with mass spectrometry (GC-MS), mobility analyzer, UV-Visible absorption and fluorescence spectroscopy) was applied for characterizing polycyclic aromatic hydrocarbons (PAH), heavy aromatic compounds and soot, constituting the particulate matter (PM) sampled from the exhaust. The engine was operated in half load (HL) (188 Nm, representing the more common condition for engine in urban traffic) and full load (FL) (452 Nm, representing the best performance of the engine operation) conditions, at the same engine speed (2000 rpm). Soot formation was enhanced in HL condition, with respect to FL, but, just because of the much lower soot amount, the after-treatment systems in this last condition resulted to be less efficient in the soot abatement. Indeed, the abatement through DPF was about 40% lower in the FL condition with respect to HL condition, and any significant further concentration decrease was found after SCR, in both conditions. By contrast, PAH concentration after DPF abatement was found to be higher in the HL with respect to FL condition. A further PAH concentration decrease of about 30% was found after the SCR in the HL condition whereas in FL the reduction was only about 5-6%. Also the heavy aromatic compounds having molecular weight above the GC-MS detection limit (300 u), were mitigated by SCR. Therefore, SCR did not cause a further soot reduction, whereas it was effective in largely reducing PAH and heavy aromatics emissions, especially in the lower temperature condition featuring the half-load condition, when combustion efficiency is worse. Moreover, SCR system reduced the emission of small particles probably due to an enhanced agglomeration of particles, with beneficial effect on the harmfulness to human health.

Capítulos en libros This paper describes a strategic information platform developed for the German electric utility Eon, to provide historical bidding analysis and medium-term forecasting of the Iberian Electricity Market. This platform, PLAMER, has three main modules: Initialization module, consisting of different sub-modules to define the electrical system structure and to organize the input data of the rest of modules, PLAMER-bids, to read, aggregate and visualize market historical bids and also to prepare them for their future forecasted values, and PLAMER-clearing, for market clearing emulation using forecasted bids. PLAMER-clearing models the Iberian market based on a bid clearing mechanism with an inherent market splitting procedure. This market splitting is built with a bi-nodal simplification, one node representing the Spanish System and the other the Portuguese one. Both are simply connected by a unique equivalent interconnection line. The medium term clearing model uses a generation portfolio per generation company in terms of technologies, for supplying monthly demand for different load levels, and labour and non-labour periods. Some technical constraints, such as minimum outputs and pumping energy balance, are also taking into account. The mathematical problem of PLAMER-clearing is a quadratic programming model solved using GAMS language and CPLEX optimizer. Finally, a real Iberian case study is detailed and some market splitting outputs are analyzed. info:eu-repo/semantics/publishedVersion

Climaps.eu is an online atlas providing data, visualizations and commentaries about climate adaptation debate. It contains 33 issue-maps and 5 issue-stories. Each of the maps focuses on one issue in the adaptation debate and provides.The atlas is addressed to climate experts (negotiators, NGOs and companies concerned by global warming, journalists…) and to citizens willing to engage with the issues of climate adaptation.It employs advanced digital methods to deploy the complexity of the issues related to climate adaptation and information design to make this complexity legible.

In ecological risk assessment, exposure is generally modelled assuming static conditions, herewith neglecting the potential role of emission, environmental and biomass dynamics in affecting bioavailable concentrations. In order to investigate the influence of such dynamics on predicted bioavailable concentrations, the spatially-resolved dynamic model "ChimERA fate" was developed, incorporating macrophyte and particulate/dissolved organic carbon (POC/DOC) dynamics into a water-sediment system. An evaluation against three case studies revealed a satisfying model performance. Illustrative simulations then highlighted the potential spatio-temporal variability of bioavailable concentrations after a pulsed emission of four chemicals in a system composed of a pond connected to its inflow and outflow streams. Changes in macrophyte biomass and POC/DOC levels caused exposure variations which were up to a factor of 4.5 in time and even more significant (several orders of magnitude) in space, especially for highly hydrophobic chemicals. ChimERA fate thus revealed to be a useful tool to investigate such variations and to identify those environmental and ecological conditions in which risk is expected to be highest.

Originally developed and validated at the Cabauw (Netherlands) topographically flat onshore location, the alpha-I wind resource extrapolating method was tested at the FINO3 offshore site in the North Sea (Germany). The aim was to prove its validity also when applied over a substantially different environment in terms of surface characteristics and stability conditions. Data from local mast at 30, 80, and 100 m were used, with extrapolations to 80-m and 100-m turbine hub heights accomplished based on 30-m turbulence intensity observations. Trained over a 2-year period (2011-2012), the method was validated on year 2013. Similarly to the onshore application, the method was reliable in extrapolating wind speed to both 80 m and 100 m, with bias within 5%, NRMSE = 0.20 and r = 0.94. Conversely, scores were largely better than at the onshore site in predicting the annual energy yield, biased by 0.41-1.02% at 80 m, and 1.12-1.36% at 100 m. The method proved to be highly sensitive to the stability classification, as not considering this option increased its biases to 4.51-5.93% at 80 m, and 7.46-8.23% at 100 m. Method's reliability might suitably help reduce the number of masts installed throughout a large offshore area.

The present paper exhibits a real time assessment of a robust Energy Management Strategy (EMS) for battery-super capacitor (SC) Hybrid Energy Storage System (HESS). The proposed algorithm, dedicated to an electric vehicular application, is based on a self-gain scheduled controller, which guarantees the H∞ performance for a class of linear parameter varying (LPV) systems. Assuming that the duty cycle of the involved DC-DC converters are considered as the variable parameters, that can be captured in real time, and forwarded to the controller to ensure both; the performance and robustness of the closed-loop system. The subsequent controller is therefore time-varying and it is automatically scheduled according to each parameter variation. This algorithm has been validated through experimental results provided by a tailor-made test bench including both the HESS and the vehicle traction emulation system. The experimental results demonstrate the overall stability of the system, where the proposed LPV supervisor successfully accomplishes a power frequency splitting in an adequate way, respecting the dynamic of the sources. The proposed solution provides significant performances for different speed levels.