Heavy metals originating from industrial runoff, agricultural practices, urbanization, and natural geological processes persist in coastal sediments due to their low degradation rates and high stability. Their cycling is influenced by sediment dynamics, water circulation, and complex interactions with biological and chemical factors. Heavy metal pollution demonstrates serious risks to coastal biota, including fish, shellfish, algae, and marine mammals through mechanisms such as bioaccumulation and biomagnification. These processes lead to biodiversity loss, habitat degradation, and reduced ecosystem functionality. Current mitigation strategies for pollution control regulations and remediation techniques show promise but face challenges in implementation. Emerging technologies such as nanotechnology and bioremediation offer innovative solutions but require further validation. Knowledge gaps persist in understanding the long-term ecological impacts of heavy metal contamination and optimizing management strategies for diverse coastal ecosystems. Coastal ecosystems are vital for supporting biodiversity and providing essential ecosystem services, but they are increasingly threatened by heavy metal pollution—a pervasive environmental challenge that demands urgent attention. This review investigates the sources, characteristics, pathways, ecological impacts, and management strategies associated with heavy metal contamination in coastal environments. The review synthesizes findings from recent literature, employing a systematic approach to analyze natural and anthropogenic sources, contamination pathways, and the biogeochemical processes governing heavy metal cycling. Future research should focus on addressing these gaps through interdisciplinary approaches, integrating advanced modeling techniques, stakeholder engagement, and sustainable management practices. By prioritizing these efforts, we can safeguard coastal ecosystems and their essential services from the escalating threats of heavy metal pollution.

In light of climate change and the ever-increasing population, salt stress has become a critical issue for agriculture and food security. The use of nano-fertilizers in agriculture is a promising application for salt stress management. Therefore, we investigated a hydroponic experiment to evaluate the effect of different nano-fertilizers: macro-nutrient (K₂SO₄) and micro-nutrient (ZnO and SiO₂) on two alfalfa (Medicago sativa L.) genotypes: (Susceptible: Bulldog 505, and tolerant: Mesa-Sirsa) grown with different salt concentrations (6 and10 dS m⁻¹) in split-split design. The results demonstrated that nano-K₂SO₄ enhanced shoot dry weight, plant height, number of flowers, number of tillers, root length, root fresh weight, and root dry weight under both salt levels. Addition of nano-K₂SO₄ enhanced plant relative water contents and electrolyte leakage with both genotypes under different salt levels. Nano-SiO₂ promoted proline and SOD production with high salinity with values of (0.78 and 1.06 µmol g⁻¹ FW) and 191.15 and 143.46 U. g⁻¹ FW under Bulldog and Mesa-Sirsa, respectively. The application of nano-ZnO promoted plant micro-elements under 6 dS m⁻¹ with both genotypes. The incorporation of nano-fertilizers into hydroponic systems provides a promising strategy, especially in regions with low water quality.

Assessing soil quality is considered one the most important indicators to ensure planned and sustainable use of agricultural lands according to their potential. The current study was carried out to develop a spatial model for the assessment of soil quality, based on four main quality indices, Fertility Index (FI), Physical Index (PI), Chemical Index (CI), and Geomorphologic Index (GI), as well as the Geographic Information System (GIS) and remote sensing data (RS). In addition to the GI, the Normalized Difference Vegetation Index (NDVI) parameter were added to assess soil quality in the study area (western part of Matrouh Governorate, Egypt) as accurately as possible. The study area suffers from a lack of awareness of agriculture practices, and it depends on seasonal rain for cultivation. Thus, it is very important to assess soil quality to deliver valuable data to decision makers and regional governments to find the best ways to improve soil quality and overcome the food security problem. We integrated a Digital Elevation Model (DEM) with Sentinel-2 satellite images to extract landform units of the study area. Forty-eight soil profiles were created to represent identified geomorphic units of the investigated area. We used the model builder function and a geostatistical approach based on ordinary kriging interpolation to map the soil quality index of the study area and categorize it into different classes. The soil quality (SQ) of the study area, classified into four classes (i.e., high quality (SQ2), moderate quality (SQ3), low quality (SQ4), and very low quality (SQ5)), occupied 0.90%, 21.87%, 22.22%, and 49.23% of the total study area, respectively. In addition, 5.74% of the study area was classified as uncultivated area as a reference. The developed soil quality model (DSQM) shows substantial agreement (0.67) with the weighted additive model, according to kappa coefficient statics, and significantly correlated with land capability R² (0.71). Hence, the model provides a full overview of SQ in the study area and can easily be implemented in similar environments to identify soil quality challenges and fight the negative factors that influence SQ, in addition to achieving environmental sustainability.

The biosynthesis of iron oxide nanoparticles has received increasing attention in the field of food nanotechnology because of their non-toxicity, high efficiency, high antibacterial power, and decontamination features. Therefore, biosynthesis of iron oxide nanoparticles (nFe) was prepared from the leaves of some vegetables, such as cabbage (C) and turnips (T), as well as moringa leaves (M). Alcoholic extracts of these nanoparticles were also tested on Staphylococcus aureus and Escherichia coli to evaluate their antibacterial activity. The results revealed that the particle sizes of the biosynthesis nanomaterials studied ranged from 12.99 to 22.72 nm, and the particles were spherical, irregular, and surrounded by black color. It also contains many functional groups and minerals. Iron nanoparticles modified with Moringa oleifera extract at a concentration of 200 ppm had the highest phenol content compared to other biosynthesis nanoparticles studied. TnFe and MnFe at 200 ppm had a maximum zone of inhibition of 25 mm and 24 mm against Staphylococcus aureus and Escherichia coli, respectively. While the minimum inhibition zone of 8.0 mm was observed at 25 ppm for nFe against Escherichia coli. Therefore, it is recommended to use these extracts of biosynthesis iron oxide nanoparticles as antibacterial agents for stored foods.