The concentrations of selected heavy metals in sediments and waters in Baychebagh copper mine were determined using ICP-OES. Except for Co, the average concentrations of Cd, Cu, Pb, and Zn in sediments from the Ghalechay River in the district exceed the world-average shale and continental upper crust value. Enrichment factors for Pb, Cu, and Cd were significantly enriched in sediments, indicating environmental contamination. Geoaccumulation index calculated for different sampling stations indicates that the sediments are unpolluted with respect to Co and Zn while unpolluted to moderately polluted with Cu and highly polluted with Pb and Cd. The Sediment Quality Guidelines (SQGs) suggest that Cd and Pb may pose the highest risk for the environment. Sequential extraction analyses of sediments revealed that Cu, Co, Pb, and Zn bound to extractable, carbonate, reducible and oxidizable fractions are lower than residual fraction. About 10% of the total Pb was associated with the exchangeable fraction, indicating remobilization, while Cd (89%), Pb (73%) Co (58%), Cu (76%), and Zn (68%) closely associated with the residual and oxidizable fractions, resulting in their environmental immobility. The residual forms are not expected to be released under normal conditions in the river and could be considered an inert phase.

Climate change is one of the biggest problems facing today’s world. Rising temperatures and declining rainfall have had a profound effect on the planet, one of which is the destructive effects of soil salinity. Soil salinity phenomena commonly occur in arid and semi-arid regions. Maharloo Salt Lake, southeast of Shiraz, Iran, with an arid and semi-arid climate, has faced severe droughts in the past and is dealing with the soil salinity problem. One useful way to manage land and soil in such areas is regular monitoring of the soils and lands and keeping abreast of changes to prevent land degradation and erosion. With the advancement of technology, remote sensing techniques to monitor natural factors have become very popular. Landsat sensor images were used in this research, and several environmental indicators were extracted by combining satellite bands. Three machine learning algorithms, RF, GBM, and MLP, were used to evaluate methods for monitoring and mapping saline soils. The models were trained and then tested to compare the accuracy and performance of each model in predicting soil salinity. GBM algorithm showed the best performance with R2 = 0.89 and RMSE = 0.63 for testing the dataset after that RF model with R2 = 0.85 and RMSE = 0.71 and the worst performance was for MLP model with R2 = 0.75 and RMSE = 0.88. The figures mapped from the results of these algorithms for salinity distribution in this region showed that by choosing the appropriate algorithm and suitable in-situ data, it could be possible to estimate soil salinity to an excellent extent by satellite data.

Heavy metal concentrations and magnetic susceptibility of sediment samples were analyzed as indicators of urban and industrial contamination in Anzali wetland in Gilan, Iran. The aim was to investigate the suitability of magnetic properties measurements for indicating heavy metal pollution. The concentration of six heavy metals (Ni, Cr, Cd, Zn, Fe, and Pb) was determined in different depths of four sediment core samples within four different regions of the wetland (Abkenar, Hendekhaleh, Shijan and Siakeshim). Average concentration of heavy metals in the sediment cores was higher than the severe effect level (SEL) for Ni, Cr and Fe (77.26, 113.63 ppm and 5.2%, respectively) and lower than SEL for Cd, Zn and Pb (0.84, 137.7, 29.77 ppm, respectively). It was found that the trend of metal concentrations with the depth is different in each core and is related to the pollution discharges into the rivers entering the wetland. Core magnetic susceptibility measurements also showed different magnetic properties in each core. Cluster analysis was applied using Pearson correlation coefficient between heavy metal concentrations and magnetic properties across each core. Significant relationship was found to exist between magnetic susceptibility and the concentration of Ni in Abkenar and the concentration of Fe in other regions. Whereas Abkenar is almost the isolated and uncontaminated region of the wetland, it revealed a difference in magnetic properties between contaminated and uncontaminated sediments. It was concluded that magnetic properties of samples from contaminated zone were mostly related to Fe content. The result of this study demonstrated that magnetic susceptibility measurements could be applied as a proxy method for heavy metal pollution determination in marine environments in Iran especially as a rapid and cost-effective introductory site assessments.