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The development of heat transfer fluids (HTF) and heat storage materials (HSM) is crucial to design concentrating solar plant (CSP). Binary alkaline nitrate mixtures are currently used as sensible thermal energy storage materials. However, multi-component nitrate/nitrite systems were proposed as possible better candidates. In particular, ternaries mixtures containing sodium, potassium, and calcium are extremely promising as thermal fluids, given their reduced toxicity and greater cost-effectiveness. Nevertheless, very few data are present in the scientific literature regarding the correspondent phase diagram, and only the properties of specific compositions are reported. For this reason, a regular solution model was developed and employed in this work, and validated by comparing the simulation results with experimentally obtained phase change values. In particular, given that the common calorimetric techniques are impracticable for detecting the transition temperatures of calcium containing nitrate mixtur...

The development of heat transfer fluids (HTF) and heat storage materials (HSM) is crucial to design concentrating solar plant (CSP). Binary alkaline nitrate mixtures are currently used as sensible thermal energy storage materials. However, multi-component nitrate/nitrite systems were proposed as possible better candidates. In particular, ternaries mixtures containing sodium, potassium, and calcium are extremely promising as thermal fluids, given their reduced toxicity and greater cost-effectiveness. Nevertheless, very few data are present in the scientific literature regarding the correspondent phase diagram, and only the properties of specific compositions are reported. For this reason, a regular solution model was developed and employed in this work, and validated by comparing the simulation results with experimentally obtained phase change values. In particular, given that the common calorimetric techniques are impracticable for detecting the transition temperatures of calcium containing nitrate mixtur...

In order to achieve the Paris Agreement goals of keeping the temperature rise well below 2 °C or even 1.5 °C, all countries would need to make fair and ambitious contributions to reducing emissions. A vast majority of countries have adopted reduction targets by 2030 in their Nationally Determined Contributions (NDCs). There are many alternative ways to analyze the fairness of national mitigation contributions. This article uses a model framework based on six equity principles of effort-sharing, to allocate countries’ reduction targets under global emissions scenarios consistent with meeting the Paris climate goals. It further compares these allocations with the NDCs. The analysis shows that most countries need to adopt more ambitious reduction targets by 2030 to meet 2 °C, and even more for 1.5 °C. In the context of 2 °C, the NDCs of the United States of America and the European Union lack ambition with respect to the approaches that emphasize responsibility; China's NDC projection falls short of satisfying any approach in 2030. In the context of 1.5 °C, only India, by implementing its most ambitious efforts by 2030, could be in line with most equity principles. For most countries, the NDCs would use most of their allowed emissions space for the entire 21 st century by 2030, posing a major challenge to transform to a pathway consistent with their fair contributions in the long-term.

In order to achieve the Paris Agreement goals of keeping the temperature rise well below 2 °C or even 1.5 °C, all countries would need to make fair and ambitious contributions to reducing emissions. A vast majority of countries have adopted reduction targets by 2030 in their Nationally Determined Contributions (NDCs). There are many alternative ways to analyze the fairness of national mitigation contributions. This article uses a model framework based on six equity principles of effort-sharing, to allocate countries’ reduction targets under global emissions scenarios consistent with meeting the Paris climate goals. It further compares these allocations with the NDCs. The analysis shows that most countries need to adopt more ambitious reduction targets by 2030 to meet 2 °C, and even more for 1.5 °C. In the context of 2 °C, the NDCs of the United States of America and the European Union lack ambition with respect to the approaches that emphasize responsibility; China's NDC projection falls short of satisfying any approach in 2030. In the context of 1.5 °C, only India, by implementing its most ambitious efforts by 2030, could be in line with most equity principles. For most countries, the NDCs would use most of their allowed emissions space for the entire 21 st century by 2030, posing a major challenge to transform to a pathway consistent with their fair contributions in the long-term.

Abstract The sustainability of the built environment largely depends on its energy and environmental performances. The overall objective, across the different phases of the building life cycle, is to improve building and system performances in terms of economics, comfort, environmental impact and durability. Several modelling methodologies have been developed in order to evaluate the energy performance of buildings. Generally, every modelling methodology responds effectively to some specific tasks, but there exists a lack of integration in particular with respect to the cross-disciplinary role of data. Given the multi-scale and multi-objective nature of the problem of optimization of the energy and environmental performances of the built environment, an appropriate synthesis and integration process in modelling methodologies has to be identified, addressing realistically the uncertainties inherently present in modelling strategies. Visualization and data analysis techniques are successfully used in a wide variety of applications, both in theoretical and applied domains, but questions remains about their robustness, efficiency and applicability to the problems introduced before. The paper aims to analyze critically these topics by means of case studies, showing a possible path to create a multi-scale methodology able to synthesize all the relevant aspects.

Abstract The sustainability of the built environment largely depends on its energy and environmental performances. The overall objective, across the different phases of the building life cycle, is to improve building and system performances in terms of economics, comfort, environmental impact and durability. Several modelling methodologies have been developed in order to evaluate the energy performance of buildings. Generally, every modelling methodology responds effectively to some specific tasks, but there exists a lack of integration in particular with respect to the cross-disciplinary role of data. Given the multi-scale and multi-objective nature of the problem of optimization of the energy and environmental performances of the built environment, an appropriate synthesis and integration process in modelling methodologies has to be identified, addressing realistically the uncertainties inherently present in modelling strategies. Visualization and data analysis techniques are successfully used in a wide variety of applications, both in theoretical and applied domains, but questions remains about their robustness, efficiency and applicability to the problems introduced before. The paper aims to analyze critically these topics by means of case studies, showing a possible path to create a multi-scale methodology able to synthesize all the relevant aspects.

Toxic elements, lead, and copper are often found in wastewater discharged from industries such as mining. The discharge of untreated effluent poses severe environmental challenges and sorption methods using agricultural waste materials are proposed as an efficient and cost-effective solution. For this research, activated sunflower material (ASM) was prepared from abundantly available agricultural sunflower waste residues and utilised to remove Pb2+ and Cu2+ ions from an aqueous medium. To begin, we examine variables that may have an impact on the adsorption process, such as pH, contact time, adsorbent dose, and initial concentration using Box-Behnken Design (BBD) to find optimal conditions. Maximum removal efficiency was found at a pH of 5, contact time of 180 min, and initial concentration of 50 mg/L for Pb2+ and 150 mg/L for Cu2+. Additionally, adsorbent dose differed by element, for Cu2+ it was 200 mg, whilst for Pb2+ it was 124 mg. Features of activated carbon such as morphology, elemental composition, textural properties, and surface functionalities were characterised using SEM-EDS, BET, FTIR, and XPS. The adsorption equilibrium data were analysed by Langmuir, Freundlich, and Dubinin-Radushkevich isotherm models. It was found that the obtained results for Pb2+ adsorption were better described with the Freundlich isotherm model. Maximum adsorption capacities for Pb2+ and Cu2+ were 91.8 mg/g and 20.5 mg/g, respectively. Furthermore, kinetic studies confirmed that the adsorption process followed a pseudo-first-order kinetic model for Pb2+, but for Cu2+ all applied kinetic models fitted experimental data with the same values of the correlation coefficient (R2 = 0.99). After comprehensive analysis using the methods mentioned above, ASM was tested for the removal of Cu2+ from mining wastewater sample, and the obtained removal efficiency was 98.6% ± 2.0%. The results of desorption experiments conducted, confirm that ASM has good potential to be reused for the purpose of removing Cu2+ from wastewater.

Toxic elements, lead, and copper are often found in wastewater discharged from industries such as mining. The discharge of untreated effluent poses severe environmental challenges and sorption methods using agricultural waste materials are proposed as an efficient and cost-effective solution. For this research, activated sunflower material (ASM) was prepared from abundantly available agricultural sunflower waste residues and utilised to remove Pb2+ and Cu2+ ions from an aqueous medium. To begin, we examine variables that may have an impact on the adsorption process, such as pH, contact time, adsorbent dose, and initial concentration using Box-Behnken Design (BBD) to find optimal conditions. Maximum removal efficiency was found at a pH of 5, contact time of 180 min, and initial concentration of 50 mg/L for Pb2+ and 150 mg/L for Cu2+. Additionally, adsorbent dose differed by element, for Cu2+ it was 200 mg, whilst for Pb2+ it was 124 mg. Features of activated carbon such as morphology, elemental composition, textural properties, and surface functionalities were characterised using SEM-EDS, BET, FTIR, and XPS. The adsorption equilibrium data were analysed by Langmuir, Freundlich, and Dubinin-Radushkevich isotherm models. It was found that the obtained results for Pb2+ adsorption were better described with the Freundlich isotherm model. Maximum adsorption capacities for Pb2+ and Cu2+ were 91.8 mg/g and 20.5 mg/g, respectively. Furthermore, kinetic studies confirmed that the adsorption process followed a pseudo-first-order kinetic model for Pb2+, but for Cu2+ all applied kinetic models fitted experimental data with the same values of the correlation coefficient (R2 = 0.99). After comprehensive analysis using the methods mentioned above, ASM was tested for the removal of Cu2+ from mining wastewater sample, and the obtained removal efficiency was 98.6% ± 2.0%. The results of desorption experiments conducted, confirm that ASM has good potential to be reused for the purpose of removing Cu2+ from wastewater.