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Social acceptance has proven to be a significant barrier in the implementation of renewable energy systems (hereinafter “RES”). While a general acceptance of RES is high, low local acceptance has hindered the development of renewable energy projects (hereinafter “REP”). This study assesses the determinants of local and general social acceptance of REP across Europe through a qualitative analysis from 25 case studies of the most significant social drivers and barriers that include all European countries. These case studies contain qualitative and quantitative analyses of the main factors for social acceptance of many representative groups including residents, stakeholders, and experts. Understanding the influences of social acceptance enables us to create strategies that will promote the development of REP by mitigating any public opposition.

Air pollution remains one of the most pressing environmental challenges of our time, particularly in urban and industrial settings, where high population densities and concentrated anthropogenic activities intersect [...]

Yazd province in central Iran is highly prone to dust and sand storms, causing significant environmental, economic, and health impacts. This study investigates the spatiotemporal dynamics of dust storms in Yazd over 2003–2022 using ground-based meteorological station records and satellite-derived aerosol optical depth (AOD) data from MODIS (MYD08_D3 v6.1) at monthly, seasonal, and annual scales. Analysis of ten synoptic stations data revealed an increasing trend of ~0.5 dusty days/year, with the highest frequency in spring and winter, particularly from March to May. MODIS AOD data confirmed these patterns and showed a rising annual aerosol load, peaking in May. Spatial analysis indicated that central and northern regions are most affected, consistent across datasets. The increasing frequency and intensity of dust storms are driven by natural and anthropogenic factors, including regional drought, desertification, drying wetlands, land use changes, and transboundary dust transport (from Iraq, Syria, Saudi Arabia). These findings underscore the value of integrating in situ and remote sensing observations to monitor dust events. To mitigate impacts, policymakers should prioritize long-term environmental monitoring and interventions addressing both natural and human factors influencing dust emissions. This study provides actionable insights for decision-makers to enhance environmental resilience and protect public health in arid regions.

The Southwest Asia Anticyclone (SWAA) plays a pivotal role in governing the regional precipitation regime. This study analyzes the structure and spatiotemporal variability of the SWAA core at the 850, 700, and 500 hPa levels, and its relationship with precipitation across Southwest Asia. Monthly precipitation and geopotential height (HGT) data were obtained from ERA5 reanalysis with a 0.25° spatial resolution over 1940–2023. The results showed that in September the SWAA core migrates from northwestern and western Saudi Arabia, shifting southward during colder periods and retreating landward in warmer periods. At 850 hPa, the core is absent during June–August, while at 700 hPa it is positioned over the southeastern Caspian Sea. The SWAA has intensified in recent decades, and its directional shifts exert a marked influence on precipitation variability: northeastward, eastward, southeastward, and southward displacements enhance rainfall, whereas northward, northwestward, and westward movements suppress it. Overall, the intensity and positioning of the SWAA are strongly linked to precipitation patterns in Southwest Asia. These findings contribute to refining precipitation and climate projections and offer practical implications for water resource management and agricultural planning in the region.

In this study, we present a statistical forecasting framework and assess its efficacy using a range of established machine learning algorithms for predicting Particulate Matter (PM) concentrations in the Arctic, specifically in Pallas (FI), Reykjavik (IS), and Tromso (NO). Our framework leverages historical ground measurements and 24 h predictions from nine models by the Copernicus Atmosphere Monitoring Service (CAMS) to provide PM10 predictions for the following 24 h. Furthermore, we compare the performance of various memory cells based on artificial neural networks (ANN), including recurrent neural networks (RNNs), gated recurrent units (GRUs), long short-term memory networks (LSTMs), echo state networks (ESNs), and windowed multilayer perceptrons (MLPs). Regardless of the type of memory cell chosen, our results consistently show that the proposed framework outperforms the CAMS models in terms of mean squared error (MSE), with average improvements ranging from 25% to 40%. Furthermore, we examine the impact of outliers on the overall performance of the model.

Anaerobic digestion (AD) is an attractive straw resource treatment technology as it can improve the utilization efficiency of straw resource. Raw straw materials contain complex polymers, so some enhancements are needed to achieve better biodegradability. The addition of various additives has become an effective method to improve the AD efficiency, among which the effect of nano zero-valent iron (NZVI) and biochar (BC) on AD has become a research hot spot. In this paper, the powder of NZVI and BC (mixing ratio 1:1) was used as additives to study the effect of different addition amount (3%, 6%, 9%, 12% and 15%) on the AD of corn straw for methane production. The cycle of AD was 28 days, the fermentation temperature was 35 ℃, and the total solid (TS) concentration was 4%. The combined addition of NZVI and BC enhanced the pH stability of the digestion process and the degradation of organic acids. The greatest enhancement of methane production was obtained when the combined addition amount of NZVI and BC was 9%, and the cumulative methane production was 151.06 mL/g VS, which is 20.73% higher than the control group. The combined addition of NZVI and BC could increase the methane content within a certain range, but an inhibitory effect was observed when exceeded 9%. When the addition amount reached 12% and 15%, the cumulative gas production and cumulative methane production of corn straw AD were inhibited to varying degrees. The VS removal efficiency was the highest in the group with the addition amount of 9%, which was 20.41% higher than the control. The modified Gompertz equation fitted well with the maximum methane production rate (Rm) and lag time ( λ ) when the addition amount was 9%, with high correlation coefficients. Considering that NZVI could be recovered by magnetic separation to further reduce the cost of additives, while the cost of biochar was relatively low, it was believed that the crop straw AD technology had certain commercial application value. Graphic abstract

Drying is a critical point for the exploitation of biomass for energy production. High moisture content negatively affects the efficiency of power generation in combustion and gasification systems. Different types of dryers are available however; it is known that rotary dryers have low cost of maintenance and consume 15% and 30% less in terms of specific energy. The study analyzed the drying process of woody residues using a new prototype of mobile rotary dryer cocurrent flow. Woodchip of poplar (Populus spp.), black locust (Robinia pseudoacacia L.), and grapevine (Vitis vinifera L.) pruning were dried in a rotary drier. The drying cycle lasted 8 h for poplar, 6 h for black locust, and 6 h for pruning of grapevine. The initial biomass had a moisture content of around 50% for the poplar and around 30% for grapevine and black locust. The study showed that some characteristics of the biomass (e.g., initial moisture content, particle size distribution, bulk density) influence the technical parameters (i.e., airflow temperature, rate, and speed) of the drying process and, hence, the energy demand. At the end of the drying process, 17% of water was removed for poplar wood chips and 31% for grapevine and black locust wood chips. To achieve this, result the three-biomass required 1.61 (poplar), 0.86 (grapevine), and 1.12 MJ kgdry solids−1 (black locust), with an efficiency of thermal drying (η) respectively of 37%, 12%, and 27%. In the future, the results obtained suggest an increase in the efficiency of the thermal insulation of the mobile dryer, and the application of the mobile dryer in a small farm, for the recovery of exhaust gases from thermal power plants.

The present study focuses on the use of Convolutional Neural Networks (CNN or ConvNet) to classify a multi-seasonal dataset of Sentinel-2 images to discriminate four grassland habitats in the “Murgia Alta” protected site. To this end, we compared two approaches differing only by the first layer machinery, which, in one case, is instantiated as a fully-connected layer and, in the other case, results in a ConvNet equipped with kernels covering the whole input (wide-kernel ConvNet). A patchwise approach, tessellating training reference data in square patches, was adopted. Besides assessing the effectiveness of ConvNets with patched multispectral data, we analyzed how the information needed for classification spreads to patterns over convex sets of pixels. Our results show that: (a) with an F1-score of around 97% (5 × 5 patch size), ConvNets provides an excellent tool for patch-based pattern recognition with multispectral input data without requiring special feature extraction; (b) the information spreads over the limit of a single pixel: the performance of the network increases until 5 × 5 patch sizes are used and then ConvNet performance starts decreasing.

The recycling of plastic waste is undergoing fast growth due to environmental, health and economic issues, and several blends of post-consumer and post-industrial polymeric materials have been characterized in recent years. However, most of these researches have focused on plastic containers and packaging, neglecting hard plastic waste. This study provides the first experimental characterization of different blends of hard plastic waste and virgin polypropylene in terms of melt index, differential scan calorimetry (DSC), thermogravimetric analysis (TGA), mechanical properties (tensile, impact and Shore hardness) and Vicat softening test. Compared to blends based on packaging plastic waste, significant differences were observed in terms of melt flow index (about 10 points higher for hard plastic waste). Mechanical properties, in particular yield strain, were instead quite similar (between 5 and 9%), despite a higher standard deviation being observed, up to 10%, probably due to incomplete homogenization. Results demonstrate that these worse performances could be mainly attributed to the presence of different additives, as well as to the presence of impurities or traces of other polymers, other than incomplete homogenization. On the other hand, acceptable results were obtained for selected blends; the optimal blending ratio was identified as 78% post-consumer waste and 22% post-industrial waste, meeting the requirement for injection molding and thermoforming.

Clean- and high-value recovery and reuse of the residue of biohydrogen production (biohydrogen slurry) is an urgent problem to be solved. In this study, sodium alginate (SA) gel was used to concentrate nutrients quickly in situ from biohydrogen slurry, which was prepared into gel microspheres (GMs), just like “capsule.” The immobilization and release efficiency of conventional and reverse spherification were investigated. Better immobilization and release efficiency were detected under the conventional spherification method. The effect of GM sizes and concentrations of SA and calcium chloride (CaCl 2 ) was further studied in terms of sphericity factor, nutrient release, yield, encapsulation efficiency, and loading capacity. The best immobilization effect was obtained with a 1.6-mm syringe needle, 3.0 wt% SA, and 6 wt% CaCl 2 , in which the sphericity factor, nitrogen release, yield, nitrogen encapsulation efficiency, and nitrogen loading capacity reached to 0.047, 96.20, 77.68, 38.37, and 0.0476%, respectively. This process not only avoids environmental pollution from biohydrogen slurry but also uses them at a high value as a fertilizer to nourish the soil. The feasibility of “slurry capsule” preparation will realize the clean recovery and reuse of biohydrogen slurry, which provides a new idea for ecological protection and carbon neutral goals and has important significance for sustainable development.