A combined landfarming-phytoremediation method to enhance remediation of mixed persistent contaminants.

Contamination of soil and water with petroleum hydrocarbons and metals can pose a significant threat to the environment and human health. This study aimed to investigate the establishment and growth of tall fescue and agropyron in two petroleum-contaminated soils (soil S and soil S) with previous landfarming treatments, and to assess the phytoremediation potential for heavy metal removal from these polluted soils. The results showed that the presence of petroleum hydrocarbons significantly (P < 0.

Human exposure to dust and heavy metals in industrial regions and its relationship with the prevalence of multiple sclerosis disease.

In recent decades, multiple sclerosis (MS) diseases have been significantly prevalent in some industrial areas of Iran, such as steel industrial areas in Isfahan province (central Iran). In this study, the environmental impacts of two steel mill factories in Isfahan province and their effects on the spread of MS in the region were investigated. To examine the extent of exposure, seasonal dust samples were collected from 15 sites around the two investigated factories.

Mitigation in availability and toxicity of multi-metal contaminated soil by combining soil washing and organic amendments stabilization.

In order to investigate the decrease in total metal contents and to mitigate the availability and toxicity of metals from farmland near a lead mining area, a combination of two effective soil washing and eco-friendly stabilization technologies was applied in current research. The pre-treatment was performed with three types of agents including Ethylenediaminetetraacetic acid (EDTA), citric acid (CA), and mixture of hydroxylamine hydrochloride and citric acid (HA)) and the post-treatment stabilization was adopted using four rich-carbon organic waste amendments (cow manure compost (CMC), vermicompost (VC), urban sewage sludge (SS), and sludge-derived biochar (BIO)). Furthermore, the fate of residual metals (leachability, plant-availability, bioaccessibility, and chemical distribution), soil quality indicators (phytotoxicity and enzyme activities), and some soil physicochemical properties were examined before and after the two-steps remediation.

Toward a combined Bayesian frameworks to quantify parameter uncertainty in a large mountainous catchment with high spatial variability.

Although hydrological models play an essential role in managing water resources, quantifying different sources of uncertainties is a challenging task. In this study, the application of two parameter uncertainty quantification methods and their performances for predicting runoff was investigated. Sequential Uncertainty Fitting version 2 (SUFI-2) and DiffeRential Evolution Adaptive Metropolis (DREAM-ZS) algorithms were employed to explore the output uncertainty of Soil and Water Assessment Tool (SWAT) at a multisite flow gauging station.