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Abstract An alkaline earth boro-aluminosilicate glass (Eagle XG), a soda-lime glass, and a light-weight polyethylene-terephthalate (PET) foil, used as typical substrates for photovoltaics, were treated by an energetic proton beam (3 MeV, dose 106–107 Gy) corresponding to approx. 30 years of operation at low Earth orbit. Properties of the irradiated substrates were characterized by atomic force microscopy, optical absorption, optical diffuse reflectance, Raman spectroscopy, X-ray photoelectron spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, and terahertz (THz) spectroscopy. Minimal changes of optical and morphological properties are detected on the bare Eagle XG glass, whereas the bare PET foil exhibits pronounced increase in optical absorption, generation of photoluminescence, as well as mechanical bending. On the other hand, the identical substrates coated with Indium-tin-oxide (ITO), which is a typical material for transparent electrodes in photovoltaics, exhibit significantly higher resistance to the modifications by protons while ITO structural and electronic properties remain unchanged. The experimental results are discussed considering a potential application of these materials for missions in space.

Alpine grasslands on the Qinghai-Tibetan Plateau are sensitive and vulnerable to climate change and human activities. Climate warming and overgrazing have already caused degradation in a large fraction of alpine grasslands on this plateau. However, it remains unclear how human activities (mainly livestock grazing) regulates vegetation dynamics under climate change. Here, alpine grassland productivity (substituted with the normalized difference vegetation index, NDVI) is hypothesized to vary in a nonlinear trajectory to follow climate fluctuations and human disturbances. With generalized additive mixed modelling (GAMM) and residual-trend (RESTREND) analysis together, both magnitude and direction of climatic (in terms of temperature, precipitation, and radiation) and anthropogenic impacts on NDVI variation were examined across alpine meadows, steppes, and desert-steppes on the Qinghai-Tibetan Plateau. The results revealed that accelerating warming and greening, respectively, took place in 76.2% and 78.8% of alpine grasslands on the Qinghai-Tibetan Plateau. The relative importance of temperature, precipitation, and radiation impacts was comparable, between 20.4% and 24.8%, and combined to explain 66.2% of NDVI variance at the pixel scale. The human influence was strengthening and weakening, respectively, in 15.5% and 14.3% of grassland pixels, being slightly larger than any sole climatic variable across the entire plateau. Anthropogenic and climatic factors can be in opposite ways to affect alpine grasslands, even within the same grassland type, likely regulated by plant community assembly and species functional traits. Therefore, the underlying mechanisms of how plant functional diversity regulates nonlinear ecosystem response to climatic and anthropogenic stresses should be carefully explored in the future.

Among the biofuels produced nowadays in the world, biodiesel became more and more attractive thanks to its advantages compared with petroleum-based diesel: (a) reducing the dependence on petroleum; (b) reduction of most exhaust emissions; (c) biodegradability; (d) higher flash point, leading to safer handling and storage; (e) excellent lubricity. However, the neat vegetable oils used in biodiesel production determine a higher price of biodiesel compared with petroleum diesel price. Waste cooking oils can be alternative raw material for biodiesel production especially because of its low cost, high availability and benefits of environmental protection. The research presented in this paper aimed to establish: (a) simple methods for monitoring the synthesis of biodiesel by transesterification of two different waste cooking sunflower oils with methanol using NaOH as catalyst, in comparison with neat sunflower oil and (b) the characteristics of oils and biodiesel obtained, comparative with characteristics described for biodiesel by the standards ASTM D6751 and EN 14214. The results obtained showed that during biodiesel synthesis, the saponification value decreased both for sunflower oil and waste cooking oils due to transesterification reaction of lipids from oils and formation of methyl esters. The values of physical and chemical characteristics of biodiesel were much smaller than those for neat and waste sunflower oils, especially viscosity, saponification value and acid value. The characteristics values of biodiesel obtained from waste cooking oils were better than characteristics of the petroleum diesel (standard EN 590), and they fit within ASTM D6751 and EN 14214 standards, which indicate that the obtained biodiesel samples could be used in engines without other modifications.

In this paper, the performances of two iron-based syngas-fueled chemical looping (SCL) systems for hydrogen (H2) and electricity production, with carbon dioxide (CO2) capture, using different reactor configurations were evaluated and compared. The first investigated system was based on a moving bed reactor configuration (SCL-MB) while the second used a fluidized bed reactor configuration (SCL-FB). Two modes of operation of the SCL systems were considered, namely, the H2 production mode, when H2 was the desired product from the system, and the combustion mode, when only electricity was produced. The SCL systems were modeled and simulated using Aspen Plus software. The results showed that the SCL system based on a moving bed reactor configuration is more efficient than the looping system with a fluidized bed reactor configuration. The H2 production efficiency of the SCL-MB system was 11 % points higher than that achieved in the SCL-FB system (55.1 % compared to 44.0 %). When configured to produce only electricity, the net electrical efficiency of the SCL-MB system was 1.4 % points higher than that of the SCL-FB system (39.9 % compared to 38.5 %). Further, the results showed that the two chemical looping systems could achieve >99 % carbon capture efficiency and emit ~2 kg CO2/MWh, which is significantly lower than the emission rate of conventional coal gasification-based plants for H2 and/or electricity generation with CO2 capture.

Tourism has become one of the most important sectors in many countries, significantly contributing to their economic growth and development. However, the expansion of tourism has also brought about various environmental and social challenges. The relationship between tourism, economic growth, trade openness, and the environment is diverse and complex. The objective of this paper is to investigate the relationship between the international tourism development index, GDP per capita, CO2 emissions, trade openness index as well as the energy intensity index in EU 27, over the 1995–2019 period. A composite index for international tourism was developed using the Principal Component Analysis (PCA). Panel Autoregressive distributed lag (ARDL) approach is used to reveal the long- and short-run impact of GDP per capita, CO2 emissions, trade openness index as well as the energy intensity index on the tourism development index. Panel ARDL estimates confirm some of our research hypotheses: at the level of EU countries, there is a short-run relationship between tourism and GDP per capita, but only in a few EU countries, trade openness influences tourism development index. Dumitrescu-Hurlin causality test confirms long-run feedback relationship between tourism development index and trade openness, between tourism development index and CO2 emissions, and between tourism development index and GDP and unilateral causality running from tourism development index towards energy efficiency.

Cost-effective CO2 capture and storage (CCS) is critical for the rapid global decarbonization effort recommended by climate science. The increase in levelized cost of electricity (LCOE) of plants with CCS is primarily associated to the large energy penalty involved in CO2 capture. This study therefore evaluates three high-efficiency CCS concepts based on integrated gasification combined cycles (IGCC): (1) gas switching combustion (GSC), (2) GSC with added natural gas firing (GSC-AF) to increase the turbine inlet temperature, and (3) oxygen production pre-combustion (OPPC) that replaces the air separation unit (ASU) with more efficient gas switching oxygen production (GSOP) reactors. Relative to a supercritical pulverized coal benchmark, these options returned CO2 avoidance costs of 37.8, 22.4 and 37.5 €/ton (including CO2 transport and storage), respectively. Thus, despite the higher fuel cost and emissions associated with added natural gas firing, the GSC-AF configuration emerged as the most promising solution. This advantage is maintained even at CO2 prices of 100 €/ton, after which hydrogen firing can be used to avoid further CO2 cost escalations. The GSC-AF case also shows lower sensitivity to uncertain economic parameters such as discount rate and capacity factor, outperforms other clean energy benchmarks, offers flexibility benefits for balancing wind and solar power, and can achieve significant further performance gains from the use of more advanced gas turbine technology. Based on all these insights, the GSC-AF configuration is identified as a promising solution for further development.

(1) Background: The present development of transport networks focusses on the better management of fuels and energy and the preservation of the environment. To fulfill these desiderates, some countries have already reconsidered the deployment plans of new highways. This research studies the feasibility of less polluting, quasi-self-powered, intelligent highway infrastructure functional blocks accommodating functions for the future introduction of smart wireless sensor grids and connected autonomous vehicles. Subject of investigation are the possibilities of energy harvesting, and the intelligent management of resources. (2) Methods: the research investigates the main technologies for energy harvesting and recommends an optimal solution. It also proposes a framework for the intelligent, AI-based management of energy and the use of an optimized backup solution relying on 5G beamforming for energy supply of the local wireless sensing network devices; (3) Results: recommendations are made for the best energy harvesting solution, an architecture of the energy management system, an algorithm for energy management and backup solution based on 5G beamforming; (4) Conclusions: the research emphasizes the advantages and drawbacks for different solutions regarding energy harvesting in an intelligent green highway scenario with a focus on the infrastructure developed to accommodate future connected and autonomous vehicles. The term “intelligent highway” must be understood in the automotive industry to describe a network of roads where cars communicate with the infrastructure and among themselves for the purpose of avoiding congestion and performing the seamless operation of services, and a space where cars and infrastructure cooperatively process information for obtaining better road safety, less pollution, and efficient energy management. With the recent recession of conventional fuel availability and the increase in prices, a solution to improving autonomy of both cars and infrastructure might be welcomed.

Nowadays, in order to optimize resource consumption and reduce costs, companies concern themselves with the adoption of innovative energy efficiency solutions. Substantiating the decision to implement energy efficiency measures is challenging, due to a high number of factors that influence the rentability of the project, such as weather conditions, energy pricing, laws and regulations, available resources and energy demand. Thus, each company faces a unique combination of factors that needs to be properly evaluated prior to the adoption of energy efficiency measures. The paper presents an IoT and Cloud-based energy monitoring and simulation platform that aims to help companies monitor energy production and consumption within various cost-centers, forecast the energy production potential and simulate the economic efficiency for multiple investment scenarios.

This work intended to explore some motivations that influence people’s eating habits towards sustainability. This was an observational, cross-sectional study, carried out by questionnaire survey on a non-probabilistic sample of 10,067 participants from 13 countries (Argentina, Brazil, Croatia, Greece, Hungary, Latvia, Lithuania, Poland, Portugal, Serbia, Slovenia, Romania and United States). Results indicated that people prefer fresh local foods from the season, being important because it allows transportation and storage to be reduced, which in many cases implies refrigeration systems and consequent energy expenditure. Although people avoid food waste at home, the awareness for the waste at restaurants still needs to be improved. Consumers seem to prefer foods that have been produced and packed in sustainable ways but still give importance to the package—understandable for food products. The results also indicated significant differences in the food choice motivations between groups for all sociodemographic variables tested (age, sex, marital status, education, professional area, living environment and country), but the association was high only for variable country. Additionally, a tree classification analysis allowed to identify the relative importance of the influential variables on the sustainable food choices, with country being the most important, followed by age and sex. Additionally, discriminant function analysis allowed establishing a model for the relation between country and six variables accounting for preservation of biodiversity, respect for life, save natural resources, save energy, reduce industrial pollution and minimal packaging. Although with some limitations, this study brings valuable insight into some aspects linked with sustainable food choices on a number of countries and how people shape their food choices according to some sustainability issues.