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The world, society and education are constantly evolving, and to respond to these changes, the main governmental institutions have been proposing different global strategies to focus efforts in the same direction. Currently, the United Nations and its 17 Sustainable Development Goals (SDG) have presented a series of indicators that could help to minimise the environmental, economic and social instability we are experiencing. In this sense, Education for Sustainable Development (ESD) has been described as a fundamental factor. Specifically, in previous work, we argued that physical education (PE) could be a good tool to contribute to SDGs. Based on this, no research analysing the voices of Physical Education Teachers (PET) on how this contribution could be made has been identified in previous literature. Therefore, the objectives of this research are: (1) to analyse the voices and opinions of active PETs in terms of the knowledge they have about Sustainable Development (SD); (2) to determine their opinions about the contribution that PE could make to SDGs; and finally, (3) to identify the challenges and limitations of pedagogical action of SD in PE. For this purpose, a qualitative analysis through a semi-structured interview with 41 active PETs was carried out. The main findings will be presented and discussed around four themes: (a) agreement on the concept of sustainability; (b) PE can contribute to the achievement of SDGs; (c) ambiguity in applying SDGs to PE lessons; and (d) teachers’ constraints on how to implement SDGs in PE. It seems to indicate that PETs do not have a multidimensional vision of sustainable development. While they recognise the potential of PE to contribute to SDGs through awareness raising and student learning, they point to its pedagogical and formative constraints as the main barriers to being able to contribute. They pointed to a lack of knowledge on how to do so, guidelines on how to integrate ESD, lack of involvement, shortage of time or resources in school physical education.

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.

It is now environmentally desirable and legally mandatory to add renewable fuels such as ethanol or ethyl tert-butyl ether to gasoline. However, biofuels affect, among other properties, the distillation curve of gasoline, which is subject to strict regulations. This work presents a simple mathematical model capable of accurately predicting the influence that the addition of these oxygenates has on the distillation curve. In order to address this issue, it is essential to find a simple mathematical correlation between the boiling temperatures of the hydrocarbons present in gasoline and the properties (boiling temperature and volume or molar concentration of ethanol) of the corresponding azeotropic mixtures formed with ethanol. Power functions have been assumed to model the temperature composition diagrams of the vapour-liquid equilibrium. Experimental data previously published by these and other authors have been used to fit and validate the model. The results provided by the mathematical model can be of great interest to understand the process of fuel evaporation in spark-ignition engines or the adjustment of distillation cuts in refineries, in order to comply with the regulations, in terms of the distillation curve, after adding ethanol or ethyl tert-butyl ether.

Hot water heat stores with stratification are a common technology used in solar energy systems and reuse of waste heat. Adding a PCM module at the top of the water tank would give the system higher storage density, and compensate heat loss in the top layer. The work presented here includes experimental results and numerical simulation of the system using an explicit finite-difference method. Experiments and simulations were carried out using different cylindrical PCM modules. With only 1/16 of the volume of the store being PCM, 3/16 of water at the top of the store was held warm for 50% to 200% longer and the average energy density was increased by 20% to 45%. Furthermore, these 3/16 of water were reheated by the heat from the module after being cooled down in only 20 min.

The aim of this report is to demonstrate and evaluate the potential of tall wheatgrass (Elytrigia elongata) to avoid GHG emissions and obtain lower economic costs in marginal areas of Spain. Our research built scenarios based on experimental plots (2 and 3 years growth) in 3 locations of Spain with completely different climate conditions (provinces of Girona, Soria and Palencia). In our experiences, we achieved an adequate establishment and biomass production, and assumed a rank of biomass yields until the end of the life cycle that is usually accepted to be about 15 years in many other studies in United States, Argentina and Eastern Europe where tall wheatgrass is extensively cultivated in marginal areas for sheep livestock production. Using our experimental plots and statistical information for economic inputs costs, we built 5 different scenarios per region considering a large range of biomass yields of tall wheatgrass. The analysis included a comparison with annual grasses economic costs calculated for a wide range of biomass yields of a previous study. We estimated GHG emissions savings for tall wheatgrasses and used our previous study (which had GHG emissions savings as well). Savings were calculated replacing natural gas electricity with electricity from biomass combustion in real power plants in Spain. In a wide range of yields, the results suggest that marginal areas might present a better performance with tall wheatgrass compared to annual winter grasses (cereals whole plant cuttings), thus producing biomass yields with higher GHG savings and lower economic costs at the farm level. Proceedings of the 20th European Biomass Conference and Exhibition, 18-22 June 2012, Milan, Italy, pp. 217-229

In this study, air concentrations of BaP in two different seasons (winter 2015 and summer 2016) and BaP levels in ground vegetation from Tarragona County were used as control simulations performed with the WRF-CHIMERE air quality modelling system, in order to reproduce the incidence of that hazardous chemical in air and soils. The CTM was validated for the present climatology, showing a good ability to represent air and soil concentrations of BaP over the target domain (petrochemical, chemical, urban and background sites), particularly in the winter. Then, the variation of the BaP concentrations in air and soils were simulated for the time series 1996-2015 and for the climate change scenario RCP8.5 (2031-2050). While an increase is projected for the levels in air, particularly in chemical and remote sites where the variation can go up to 10%, in terms of soil deposition the findings are the opposite, with an evident decrease in soil BaP concentrations, particularly for background sites. Finally, a potential health effect of BaP for the local population (lung cancer) was assessed. Although according to the projections the EU threshold for BaP atmospheric incidence (1 ng m-3) will not be reached by 2050, there will be an increase in the life-time risk of lung cancer, particularly in the most populated areas within the simulation domain.

Abstract The Mediterranean region is one of the most vulnerable regions to climate change. The majority of climate models forecast a rise in temperatures and less rainfall, which have been observed in recent decades. These changes will affect several vegetation properties, especially phenological dynamics and traits, by increasing drought intensity and recurrence. In this climate change context, the present study aims to assess the evolution of vegetation state and its relation with the climate dynamics in the Mediterranean forest region of northeast Tunisia using Land Surface Phenology (LSP) metrics and the vegetation index (NDVI) analysis from 2000 to 2017. To conduct this work, we used precipitation and temperature data from the two closest weather stations and 16-day NDVI composite images from the MODIS satellite source, with 250-m spatial resolution. Three phenological metrics— start of season (SOS), end of season (EOS), and length of season (LOS) — were obtained and compared for different vegetation types. The LSP variation in response to climatic metrics was also analyzed. The results showed that the LSP in our study area changed significantly during the 2000–2017 period, which includes an average 7.8 days delay in the SOS, an average advance in the EOS by 5 days, and LOS shortened by an average 12.8 days. Autumn (Pr_9) and spring (Pr_3 and P3_4) precipitations, as well as maximum temperature (Tx9+10), represent the best climate parameters to explain the changes in LSP. Both the NDVI and SPEI showed a significant high correlation (p

In this study we examine the determination accuracy of both the mean radiant temperature (Tmrt) and the Universal Thermal Climate Index (UTCI) within the scope of numerical weather prediction (NWP), and global (GCM) and regional (RCM) climate model simulations. First, Tmrt is determined and the so-called UTCI-Fiala model is then used for the calculation of UTCI. Taking into account the uncertainties of NWP model (among others the HIgh Resolution Limited Area Model HIRLAM) output (temperature, downwelling short-wave and long-wave radiation) stated in the literature, we simulate and discuss the uncertainties of Tmrt and UTCI at three stations in different climatic regions of Europe. The results show that highest negative (positive) differences to reference cases (under assumed clear-sky conditions) of up to -21°C (9°C) for Tmrt and up to -6°C (3.5°C) for UTCI occur in summer (winter) due to cloudiness. In a second step, the uncertainties of RCM simulations are analyzed: three RCMs, namely ALADIN (Aire Limitée Adaptation dynamique Développement InterNational), RegCM (REGional Climate Model) and REMO (REgional MOdel) are nested into GCMs and used for the prediction of temperature and radiation fluxes in order to estimate Tmrt and UTCI. The inter-comparison of RCM output for the three selected locations shows that biases between 0.0 and ±17.7°C (between 0.0 and ±13.3°C) for Tmrt (UTCI), and RMSE between ±0.5 and ±17.8°C (between ±0.8 and ±13.4°C) for Tmrt (UTCI) may be expected. In general the study shows that uncertainties of UTCI, due to uncertainties arising from calculations of radiation fluxes (based on NWP models) required for the prediction of Tmrt, are well below ±2°C for clear-sky cases. However, significant higher uncertainties in UTCI of up to ±6°C are found, especially when prediction of cloudiness is wrong.