In the context of environmental monitoring studies, the complex dynamics of environmental systems, constrained by the distribution, intensity and interaction of multiple sources, limits the ability to detect pollution phenomena and to identify their sources. The deployment of multidisciplinary, multilevel and multi-factorial strategies supports the identification of the links between the pollutants’ sources and targets. Our new biomonitoring strategy, based on the integration of remote (satellite) and proximal (drone) sensing monitoring data with field data (bio/chemical analyses) and focused on the use of cyanobacteria as bioindicators of pollution, was implemented and was validated through its application on a test-bed area, i.e., Lake Avernus (Campania Region, Southern Italy). A long-term analysis of multispectral remote sensing observations centred on the Lake Avernus area highlighted the periodicity and seasonality of cyanobacterial bloom events over the time interval 2019-2021. However, a sudden change of characteristics, observable through remotely sensed data, was evidenced during the first and major lockdown related to the COVID-19 pandemics, in year 2020. This sudden change depended on the drastic modification of human habits and a reduction in pollutant emissions, as widely reported by the scientific literature. During the same lockdown period, the opportunity to collect samples in the field allowed to identify an unusual progression of Microcystis' bloom, whose dynamics is triggered by the existing anthropogenic sources and the evolution of environmental parameters, that can stimulate the blooming events. This work shows and demonstrates how pollution attribution can be achieved using remote sensing of cyanobacteria, which are excellent bioindicators due to their sensitivity to multiple stressors and rapid response to habitat changes throughout the event.

CVBEM is a numerical method of solving boundary value problems that satisfy Laplace's Equation in two dimensions. Three key parameters that impact the computational error and functionality of CVBEM are the basis function, the positions of the modeling nodes, and the coefficient determination methodology. To demonstrate the importance of these parameters, a case study of 2D ideal fluid flow into a 90-degree bend and over a semicircular hump was conducted comparing models using original CVBEM, complex log, complex pole, and digamma function variants basis functions, using two different NPAs, NPA1 and NPA2, and using collocation and least squares methods to determine coefficients. Results indicate that the combination of the original CVBEM basis function, NPA2, and least squares results in an approximation with the least computational error. Moreover, least squares appear to enable stability in both NPAs regarding reduction of computational error due to taking advantage of all boundary data and more stable condition number growth. By exploring the interaction of the three main CVBEM parameters, this paper clarifies the unique impact they have on the modelling process and explicitly identifies a fourth parameter, collocation point placement, as being impactful on computational error.

The study aimed to determine the levels of heavy metals in some selected plant samples near the Wadafiea Dumpsite in Khartoum North, Sudan, and compare the variations between dry and rainy seasons. Except for Sudanese sorghum, Conocarpus lancifolius, and Leptadenia arborea, zinc contents in all plant samples during the dry season were higher than WHO/FAO guideline value (5mg/kg). In the rainy season, Cd concentrations were generally lower than in the dry season due to rainfall dilution. According to the findings, an open landfill of solid waste could have a severe impact on the quality of plants in the research area and surrounding farms, perhaps causing future concerns for human health and the environment due to pollution.

The continual pursuit of fuel efficiency, cost-effectiveness, and desirable physical and mechanical properties of materials has steered researchers towards the latest generation of aluminum matrix composites for automotive and aerospace applications. In this context, the present study investigates the microhardness behavior of Al6061/TiC composites produced by friction stir processing. The morphological characteristics of the produced surface composites were analyzed using optical microscopy and Scanning Electron Microscopy (SEM). SEM micrographs confirmed the presence of TiC particles and their uniform distribution within the aluminum matrix. The mechanical properties of the composites were explored using a microhardness tester, revealing a distinctive feature of the Al6061/TiC composites - a 35% increase in microhardness value compared to the base Al6061 alloy. This improvement in microhardness can be attributed to enhanced interfacial bonding, obstructions in dislocation movement, and grain refinement, all contributing to Hall-Petch strengthening.

Using an entropy generation analysis, heat exchangers can be designed with optimal efficiency. This study delves into the irreversibility of forced convection heat transfer and friction flow around a horizontal cylinder, revealing that pressure drops induce entropy generation that varies in accordance with Reynolds numbers. The investigation encompasses four groups of Re_D, covering ranges of 0.4_D<4, 4_D<40, 40_D<4000, and 4000_D<40000. The study aims to elucidate the relationship between the entropy generation number (Ns), Re_D, the irreversibility distribution ratio (∅), the optimal Reynolds number (Re_D,opt), and the Bejan number (Be), particularly where entropy generation has a minimal effect. Additionally, it seeks to determine the relationship between the duty parameter and Re_D,opt across all Re_D ranges. The findings highlight the optimum design point for forced convection around a horizontal cylinder. At this point, the entropy generation number reaches its minimum value when Ns=1 and the ratio Re_D/Re_D,opt=1, marking the optimal point for irreversibility or entropy generation. At this juncture, the irreversibility distribution ratio ∅ equals 0.5, and the optimal Bejan number stands at 0.667.

Passive design solutions play a pivotal role in fostering sustainable practices within traditional architecture, as they empower historical urban designs to harmoniously engage with their surroundings and weather conditions, particularly in hot regions such as the United Arab Emirates. This research followed a qualitative approach to propose modifications for the thermal conditions and comfort in the modern contemporary urban districts based on the positive strategies from old traditional ones in a Hot-Arid Climate - Ajman-United Arab Emirates (UAE) as a case study using ENVI-met software-microscale three-dimensional software model for simulating complex urban environments. Moreover, this study made an evaluation and comparison of the outdoor air temperature and thermal comfort between the traditional and modern urban districts to highlight the passive design solutions that increase the thermal effectiveness in the traditional urban fabrics, as some of these passive design solutions can be used to modify the thermal conditions in the modern ones. Additionally, the research output revealed that the traditional urban design has valuable, sustainable strategies, as there was a decrease in the maximum reading for the air temperature for the traditional Ajman heritage district compared to the modern district on the 21^st of August - as a reference day- and that improved the thermal comfort in the outdoor open spaces too. In conclusion, the study results confirmed that the thermal conditions in the existing modern districts could be improved using passive design solutions such as shading devices and greenery. Finally, this research is expected to be a phase amongst different phases that can benefit urban designers and architects to adopt strategies from traditional and vernacular urban projects and merge them with contemporary modern urban design.

This study explores the performance of the Photovoltaic/Thermal system using nanofluid with a novel collector design. Experiments were carried out on the University of Technology- Iraq campus. An experiment was carried out using two photovoltaic modules, one connected to 120 protrusions arranged eight columns by 15 rows (for comparison) and the other not. Nanofluid was used to cool solar panels with flow rates of 1.5 and 3.5 l/min. The nanofluid contains nano-Al2O3 at 1%, 2%, and 3% concentrations in water. As the flow rate of water used as a cooling fluid increased, the surface temperature of the cell decreased. The cell temperature is reduced by 22.3% when Al2O3/water is added at a volumetric concentration of 3%. An increase in the electrical and thermal efficiency of PV/T systems was also recorded by 12% and 18.4%, respectively, at a concentration of 3%.

The integration of diesel and biodiesel, particularly biodiesel derived from water hyacinth, as a combined fuel source has recently emerged as a promising area of study, with a particular focus on the effects of nanoparticle additives. Notably, the reduction of emissions achieved by introducing iron oxide nanoparticles (Fe₃O₄) to biodiesel has been substantiated. However, the potential impact of blending nanoparticles with the diesel and biodiesel mix on the performance characteristics of a diesel engine has yet to be sufficiently explored. This research undertook performance and emission assessments employing diverse fuel samples in a single-cylinder diesel engine. The thermal brake efficiency metrics for the 50 ppm and 100 ppm iron oxide nanoparticle blends surpassed those of the D80B20 and D60B40 biofuel blends, exhibiting increases of 3.5% and 4.85% for D80B20N50 and D80B20N100, and 6.2% and 7.4% for D80B20N50 and D80B20N100, respectively, in comparison to neat diesel. The carbon monoxide emission levels of the biofuel blends with iron oxide were less than that of neat diesel, with the most significant reduction detected in the D60B40N100 blend. Furthermore, the nitrogen oxide emissions for all nanoparticle blends were lower than those for neat diesel, attributable to a shortened ignition delay and minimized fuel usage during combustion, subsequently leading to a reduction in nitrogen oxide emissions.