In Côte d’Ivoire, the government and its development partners have implemented a national strategy to promote agroforestry and reforestation systems as a means to combat deforestation, primarily driven by agricultural expansion, and to increase national forest cover to 20% by 2045. However, the assessment of these systems through traditional field-based methods remains labor-intensive and time-consuming, particularly for the measurement of dendrometric parameters such as tree height. This study introduces a remote sensing approach combining drone-based Airborne Laser Scanning (ALS) with ground-based measurements to enhance the efficiency and accuracy of tree height estimation in agroforestry and reforestation contexts. The methodology involved two main stages: first, the collection of floristic and dendrometric data, including tree height measured with a laser rangefinder, across eight (8) agroforestry and reforestation plots; second, the acquisition of ALS data using Mavic 3E and Matrice 300 drones equipped with LiDAR sensors to generate digital canopy models for tree height estimation and associated error analysis. Floristic analysis identified 506 individual trees belonging to 27 genera and 18 families. Tree height measurements indicated that reforestation plots hosted the tallest trees (ranging from 8 to 16 m on average), while cocoa-based agroforestry plots featured shorter trees, with average heights between 4 and 7 m. A comparative analysis between ground-based and LiDAR-derived tree heights showed a strong correlation (R² = 0.71; r = 0.84; RMSE = 2.24 m; MAE = 1.67 m; RMSE = 2.2430 m and MAE = 1.6722 m). However, a stratified analysis revealed substantial variation in estimation accuracy, with higher performance observed in agroforestry plots (R² = 0.82; RMSE = 2.21 m and MAE = 1.43 m). These findings underscore the potential of Airborne Laser Scanning as an effective tool for the rapid and reliable estimation of tree height in heterogeneous agroforestry and reforestation systems.

Two-dimensional hexagonal boron nitride nanosheets (h-BNNS) were synthesized on silver (Ag) substrates via a scalable, room-temperature atmospheric pressure plasma (APP) technique, employing borazine as a precursor. This approach overcomes the limitations of conventional chemical vapor deposition (CVD), which requires high temperatures (>800 °C) and low pressures (10⁻² Pa). The h-BNNS were characterized using FT-IR spectroscopy, confirming the presence of BN functional groups (805 cm⁻¹ and 1632 cm⁻¹), while FESEM/EDS revealed uniform nanosheet morphology with reduced particle size (80.66 nm at 20 min plasma exposure) and pore size (28.6 nm). XRD analysis demonstrated high crystallinity, with prominent h-BN (002) and h-BN (100) peaks, and Scherrer calculations indicated a crystallite size of ~15 nm. The coatings exhibited minimal disruption to UV-VIS reflectivity, maintaining Ag’s optical properties. Crucially, Vickers hardness tests showed a 39% improvement (38.3 HV vs. 27.6 HV for pristine Ag) due to plasma-induced cross-linking and interfacial adhesion. This work establishes APP as a cost-effective, eco-friendly alternative for growing h-BNNS on temperature-sensitive substrates, with applications in optical mirrors, corrosion-resistant coatings, energy devices and gas sensing.

Land use changes have been demonstrated to exert a significant influence on urban planning and sustainable development, particularly in regions undergoing rapid urbanization. Tehran Province, as the political and economic capital of Iran, has undergone substantial growth in recent decades. The present study employs sophisticated Geographic Information System (GIS) instruments and the Google Earth Engine (GEE) platform to comprehensively track and analyze land use change over the past two decades. A comprehensive analysis of Landsat images of the Tehran metropolitan area from 2003 to 2023 has yielded significant insights into the patterns of land use change. The methodology encompasses the utilization of GIS, GEE, and TerrSet techniques for image classification, accuracy assessment, and change detection. The Kappa coefficients for the maps obtained for 2016 and 2023 were 0.82 and 0.87 for four classes: built-up, vegetation cover, barren land, and water bodies. The findings suggest that, over the past two decades, Tehran Province has undergone a substantial decline in ecological and vegetative areas, amounting to 2.4% (458.3 km²). Concurrently, the urban area and the barren lands have expanded by 287.5 and 125.5 km², respectively. The increase in water bodies during this period is likely attributable to the reduction of vegetation cover and dam construction in the region. The present study demonstrates that remote sensing and GIS are excellent tools for monitoring environmental and sustainable urban development in areas experiencing rapid urbanization and land use changes.

This study examined the impact of aluminium doping on the structural, electrical, and magnetic properties of Li_(0.5)Co_(0.75)Al_xFe_(2−x)O₄ spinel ferrites (x =0.15 to 0.60). The samples were synthesised using the sol-gel auto-combustion technique, and they were examined using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), dielectric measurements, and vibrating sample magnetometry (VSM). All samples possessed a single-phase cubic spinel structure with Fd-3m space group, according to XRD analyses. SEM images showed the creation of homogeneous particles with an average size of about 21 nm. All samples had spinel ferrite phases, confirmed from FTIR spectra. DC electrical conductivity studies showed that the conductivity increased with increasing aluminium content up to x = 0.45 before dropping at x = 0.60. The maximum saturation magnetization value was found at x = 0.45, according to VSM measurements, which demonstrated that the magnetic characteristics were strongly correlated with the amount of aluminium.

Given the increasing demand for sustainable energy sources and the challenges associated with the limited efficiency of solar cells, this review focuses on the application of gold quantum dots (AuQDs) in enhancing solar cell performance. Gold quantum dots, with their unique properties such as the ability to absorb ultraviolet light and convert it into visible light expand the utilization of the solar spectrum in solar cells. Additionally, these quantum dots, through plasmonic effects and the enhancement of localized electric fields, improve light absorption, charge carrier generation (electrons and holes), and their transfer. This study investigates the integration of quantum dots with gold plasmonic nanoparticles into the structure of solar cells. Experimental results demonstrate that using green quantum dots and gold plasmonic nanoparticles as intermediate layers leads to an increase in power conversion efficiency. This improvement highlights the significant impact of this technology on solar cell performance. Furthermore, the reduction in charge transfer resistance and the increase in short-circuit current are additional advantages of utilizing this technology. The findings of this research emphasize the high potential of gold quantum dots in advancing next-generation solar cell technology.

With modern society and the ever-increasing consumption of polymeric materials, the way we look at products has changed, and one of the main questions we have is about the negative impacts caused to the environment in the most diverse stages of the life cycle of these materials, whether in the acquisition of raw materials, in manufacturing, distribution, use or even in their final disposal. The main methodology currently used to assess the environmental impacts of products from their origin to their final disposal is known as Life Cycle Assessment (LCA). Thus, the objective of this work is to evaluate how much the biodegradable polymer contributes to the environment in relation to the conventional polymer considering the application of LCA in the production mode. This analysis is configured through the Systematic Literature Review (SLR) method. In this review, 28 studies were selected for evaluation, whose approaches encompass knowledge on LCA, green biopolymer (from a renewable but non-biodegradable source), conventional polymer (from a non-renewable source) and, mainly, the benefits of using biodegradable polymers produced from renewable sources, such as: corn, sugarcane, cellulose, chitin and others. Based on the surveys, a comparative analysis of LCA applications was made, whose studies considered evaluating quantitative results in the application of LCA, in biodegradable and conventional polymers. The results, based on comparisons between extraction and production of biodegradable polymers in relation to conventional polymers, indicate greater environmental benefits related to the use of biodegradable polymers.