Evaluation of heavy metal pollution in the Zayandeh-Rud River as the only permanent river in the central plateau of Iran

Unveiling the Rising Threat of Cadmium Pollution and Alarming Health Risks Associated with the Consumption of 15 Commercially Important Fish Species in the Middle Stretch of River Ganga, at Patna, India

Among environmental contaminants, the rising level of cadmium in freshwater ecosystems is one of the most significant global concerns. The study addresses the current pollution status of cadmium in the middle stretch of River Ganga and explores the potential hazard associated with the consumption of 15 commercially important fish species by the inhabitants. Together 72 water and sediment samples were analyzed from the four representative sampling sites of River Ganga after the surveillance of major anthropogenic stressors. The concentration of cadmium ranges from 0.003 to 0.011 mg/l and 0.2 to 3.48 mg/kg in water and sediment respectively in 2022. The average concentration of cadmium was recorded to be the highest in Channa punctatus (1.35 mg/kg), followed by Rita rita = Johnius coitor (1.15 mg/kg), and the lowest in Labeo bata (0.2 mg/kg). The finding highlights greater exposure duration and feeding preferences of fish species have played a significant role in the bioaccumulation of the metal in the riverine system. Notably, the domestic effluents, agricultural runoffs, and pollutants brought along by the tributaries of River Ganga are identified as the main anthropogenic stressors for the moderate to considerably polluted status of the River Ganga. The target hazard quotient (THQ) and target carcinogenic risk (TCR) have revealed a higher susceptibility to cadmium contamination in children followed by females, and males. In addition, hierarchical cluster analysis (HCA) has noted intake of Rita rita, Channa punctata, Puntius sophore, and Johnius coitor could be more detrimental to children's health than adults.

Potentially Toxic Elements' Accumulation in Relation to Sediment Physicochemical Attributes and Microplastic Content in Zayandeh-Rood River, Iran

Microplastics (MPs) are an emerging pollutant whose ability to adsorb potentially toxic elements (PTEs) poses a serious threat to aquatic ecosystems, including rivers. In highly developed basins, the abundance of MPs in river sediment is expected to be high, elevating the sedimentary accumulation of PTEs. This hypothesis was tested in the Zayandeh-Rood River, Central Iran, with 21 sediment sampling stations distributed along the entire river stretch. Results of sediment analysis showed significant variations in the abundance and size of MPs, with concentrations ranked as Ba (270.71 mg/kg) > Li (21.29 mg/kg) > Cs (2.50 mg/kg) > Be (1.44 mg/kg) > Sn (1.17 mg/kg) > Mo (1.06 mg/kg) > Ag (0.76 mg/kg), along with sediment physicochemical attributes such as EC, TOC, pH and grain size. MPs were identified in all sediment samples with a mean of 588 items/kg dry weight. Except for Ag, all other PTEs were classified as uncontaminated but exhibited increased enrichment downstream. According to the results of the generalized additive model (maximum R-sq of 0.766), the sedimentary concentration of the majority of PTEs is nonlinearly and positively associated with smaller and more abundant MPs. This study acknowledges that MPs might influence sediment porosity, permeability and structure, thereby directly affecting the settling dynamics of other particles, especially PTEs.

Indexing and segment-level mapping of soil quality in a spatially complex watershed in northern Iran

Soil quality (SQ) modeling and mapping is a leading research field aiming to provide reproducible and cost-effective yet accurate SQ predictions at the landscape level. This endeavor was conducted in a complex watershed in northern Iran. We classified the region into spectrally and topographically homogenous land units (average area of 48 ± 23 ha) using object-based segmentation analysis. Following the physicochemical analysis of soil samples from 98 stations, the Nemoro soil quality index (SQIn) was produced using the minimum dataset procedure and a non-linear sigmoid scoring function. SQIn values averaged 0.21 ± 0.06 and differed statistically between major land uses. To predict and map SQIn for each land unit, the best-performing regression model (F(3, 84) = 45.57, p = 0.00, R2 = 0.62) was built based on the positive contribution of the mean Landsat 8-OLI band 5, and negative influence of land surface temperature retrieved from Landsat 8-OLI band 10 and surface slope (t-test p-values < 0.01). Results showed that dense-canopy woodlands located in low-slope land units exhibit higher SQIn while regions characterized by either low-vegetation or steep-sloped land units had SQ deficits. This study provides insights into SQ prediction and mapping across spatially complex large-scale landscapes.

Biomagnification of potentially toxic elements in animals consuming fodder irrigated with sewage water

Globally, sewage water is considered a cheap and effective alternative source of irrigation and nutrient supplement. For example, in Faisalabad, Pakistan untreated sewage water loaded with potentially toxic elements (PTEs) is being routinely used to grow fodder crops in the peri-urban areas, where PTEs accumulate at different trophic levels and contaminate the food chain. Trophic transfer, bioaccumulation, and biomagnification of hazardous metals in food chains had toxic implications for human health. Currently, the major concern is associated with the consumption of PTEs contaminated fodder by animals and the subsequent translocation into humans via consumption of milk and meat from these animals. This study thus analyzed the concentration of Cd, Cu, Pb and Zn in sewage water, sewage irrigated soil, fodder is grown on such soils and the milk of cows and buffalos to calculate the transfer through water and fodder to animal milk. Overall, concentrations and bioaccumulation factors of Cd and Cu in buffalo milk were higher than the cow milk, whereas it was inverse for the concentration of Zn. Non-significant difference in the bioaccumulation factor for Pb in both buffalo and cow milk was observed. Calculation of the estimated daily intake indicated that there was no health risk associated with the consumption of tested milk samples. However, given the widespread exposure of infants to milk, continuous monitoring of milk quality is recommended to preclude a child's exposure to elevated levels of PTEs.

Controlling factors of groundwater chemistry and statistical analysis of the samples related to ophiolite of Nourabad-Harsin, West of Iran

Recognizing controlling factors of groundwater chemistry in the ophiolite region of the southeastern area of Kermanshah is the aim of this study. The findings reveal that some samples' calcium, magnesium, and sodium absorption risk is higher than the standard range. Besides, statistical relationships of the data were investigated to recognize the key factors controlling water chemistry. Pearson's correlation was used to determine the elements with the same source. Saturation index (SI) and water-rock interaction helped us find the important minerals in reaction with water. Besides, the map of the spatial distribution of heavy elements was applied to prove the elements with a common source. According to these ties, the important factors controlling groundwater chemistry of the region are dissolution of gypsum as the common source of Ca, Sr, and S; dissolution and weathering of Cr-spinel mineral in peridotites as the common source of Si, Mg, and Cr; dissolution of existing Fe-Mg olivine and pyroxene in peridotite silicates as the common source of Mg and Ni, and dissolution of chalcedony, barite, and calcite as three minerals with the highest dissolution in water-rock interaction of groundwater samples.

Linking river sediment arsenic to catchment spatial attributes in agricultural landscapes

Understanding of the sources and processes involved in the heavy metal accumulation in river sediments is important for measuring the risks associated with human exposure. Hence, an integrated modeling approach was designed to study the linkage between landscape-related natural and anthropogenic features and high arsenic levels at the outlet of six catchments on the Ghareh-Ajagh River, central Iran. Sediment arsenic levels were measured in 8 months from October 2018 to November 2019 when the river sediment and water conditions were stable and ranged from 16.3 to 78.5 mg/kg. Monthly catchment-level agricultural areas were extracted from Landsat 8-OLI images. Predictive variables included NDVI values; area and spatial patterns of agriculture measured using four landscape metrics of NP, PD, MPS, and ENN; length and slope of the streams extended from main agricultural areas to the catchment outlet; and four hydrologic soil groups. The best-fitted multiple regression model (r2 = 0.763, p≤ 0.05) with the Akaike information criteria of 105.07 was developed using stream length, soil group C, and area and PD of agricultural areas. Results showed that sediment arsenic levels increase with increasing quantity and density of agricultural activities that were close to the river outlet and increasing proportion of silty loam or loamy soils but are relatively less dependent on agricultural structural patterns. These insights are helpful to inform policy decisions regarding the processes involved in river contamination in central Iran.