Heavy-metal contamination in river and ocean is a critical environmental issue that endangers marine ecosystems and human health. Therefore, conducting extensive research to devise effective mitigation measures is imperative. Sediment samples were taken randomly throughout the study area. Analysis was done to determine the presence of different metals, including arsenic, cadmium, chromium, nickel, copper, zinc, lead, and manganese. The assessment of different pollution levels was done by using various pollution indicators including “geo-accumulation index (Igeo), contamination factor (CF), enrichment factor (EF)” for accuracy. The Igeo measurement for Cd indicated varying pollution, ranging from moderate to significantly polluted, while Mn revealed no contamination. Elements such as Ni, Cr, Cu, and Zn showed a moderate level of contamination. The contamination factor values exhibited a range of 0.436 (Pb) to 7.637 (Cd), with average values spanning from 0.9176 (Mn) to 4.9714 (Cd), suggesting significant regional variation. EF exhibits a pattern of contamination comparable to that of Igeo. The noncarcinogenic risk associated with exposure to Cd and As exceeded the higher limit (HI > 1) for children and adults. Furthermore, the carcinogenic risk presented by pollutants such as copper (Cu), arsenic (As), nickel (Ni), cadmium (Cd), and chromium (Cr) was found to exceed the limits in children. In adults, only arsenic (As) and copper (Cu) were shown to represent a higher risk of cancer than the limit of 10⁻⁴. The PCA analysis revealed that two (PCs) accounted for more than 65% of the total variance in the River Ravi, as determined by eigenvalues greater than 1. This study underscores the importance of the ongoing monitoring and management of heavy-metal pollution to ensure sustainable marine ecosystem development and public health protection.

High lead (Pb) levels in agricultural soil and wastewater threaten ecosystems and organism health. Microbial remediation is a cost-effective, efficient, and eco-friendly alternative to traditional physical or chemical methods for Pb remediation. Previous research indicates that micro-organisms employ various strategies to combat Pb pollution, including biosorption, bioprecipitation, biomineralization, and bioaccumulation. This study delves into recent advancements in Pb-remediation techniques utilizing bacteria, fungi, and microalgae, elucidating their detoxification pathways and the factors that influence Pb removal through specific case studies. It investigates how bacteria immobilize Pb by generating nanoparticles that convert dissolved lead (Pb-II) into less harmful forms to mitigate its adverse impacts. Furthermore, the current review explores the molecular-level mechanisms and genetic engineering techniques through which microbes develop resistance to Pb. We outline the challenges and potential avenues for research in microbial remediation of Pb-polluted habitats, exploring the interplay between Pb and micro-organisms and their potential in Pb removal.

Global hunger has increased recently, returning to levels observed a decade ago. Climate change is identified as a key factor contributing to these increases and is a significant cause of severe food crises. When combined with population growth and globalization, future climate variability is expected to significantly affect global food security. This study examined the influence of climate variability, globalization, and population growth on food security (FS) in Pakistan from 1995 to 2023. Food security data was sourced from the Food and Agricultural Organization, and globalization data was obtained from the KOF Globalization Index. Datasets on climate variability, population growth, unemployment, and inflation were collected from the World Development Indicators. A two-layer principal component analysis was utilized to develop the food security index. Multivariate Generalized Auto-Regressive Conditional Heteroscedasticity was used to assess the impact of globalization, population growth, and climate variability on food security. All indexed components explained more than 50% of the variance, resulting in a food security eigenvalue of 3.603 with a 0.901 proportion. The findings indicated that population growth and climate variability significantly negatively affect Pakistan’s food security. Furthermore, the study found that globalization notably mitigates the adverse effects of climate variability and population growth on food security. This research may help alleviate the risk of future undernourishment, reverse current trends of escalating food insecurity, and support the sustainable development goal of eliminating global hunger by 2030.