Although Iran’s Ghaen Plain provides saffron to much of the world, no regional groundwater quality (GQ) assessment has yet been undertaken. Given the region’s potential for saltwater intrusion and heavy metal contamination, it is important to assess the GQ and determine its main probable source of pollution (MPSP). Such knowledge would allow for informed mitigation or elimination of the potential adverse health effects of this groundwater through its use as drinking water, or indirectly as a result of the consumption of groundwater-irrigated crops. Total dissolved solids, sodium, and chloride in the water of the majority of 16 wells sampled within the region exceeded World Health Organization and Iranian permissible standards for drinking water. The groundwater proved to only be suitable for irrigating salt tolerant crops under good drainage conditions. Due to the precipitation of calcium carbonate in the water supply facilities, the water from all wells was deemed unsuitable for industrial purposes. Heavy metal pollution and contamination indices showed no groundwater contamination. Analysis of ionic ratios and the application of principal components analysis indicated the MPSP to be saltwater intrusion, with the geology subtending the plain, and to a lesser extent, anthropogenic activities. Reducing groundwater withdrawals, particularly those for agricultural production by using high performance irrigation methods could reduce saltwater intrusion and improve GQ in the Ghaen Plain.

This research aims to assess contamination status of water and sediment in Sabalan dam reservoir (SDR) and evaluate the impact of water withdrawal depths on the carcinogenic and non-carcinogenic risks of metals for exposed people. Results of metal pollution indices revealed some degree of pollution in water and sediment of the reservoir, especially associated with arsenic. Risk assessment of metals in water of the SDR for non-carcinogenic materials through different scenarios of water withdrawal depth revealed that consuming water from the depth of 10 m can be somewhat troublesome to human health. The carcinogenic risk of arsenic from depth of 10 m of the reservoir was about four times greater than that from water surface. Minimum carcinogenic risk of consuming water in the reservoir was found to be 1.69 × 10E-4, which is higher than the maximum limit proposed by the U.S. EPA, indicating the water consumption from the SDR can result in harmful effects on human health.

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.

Air quality prediction is highly important in view of the health impacts caused by exposure to air pollutants in urban air. This work has presented a model based on support vector machine (SVM) technique to predict daily average carbon monoxide (CO) concentrations in the atmosphere of Tehran. Two types of SVM regression models, i.e. -SVM and -SVM techniques, were used to predict average daily CO concentration as a function of 12 input variables. Then, forward selection (FS) technique was applied to reduce the number of input variables. After converting 12 input variables to 7 using the FS, they were fed to SVM models (FS-(-SVM) and FS-(-SVM)). Finally, a comparison among SVM models operation and previously developed techniques, i.e. classical regression model and artificial intelligent methods such as ANN and adaptive neuro-fuzzy inference system (ANFIS) was carried out. Determination of coefficient (R2) and mean absolute error (MAE) for -SVM (-SVM) were 0.87 (0.40) and 0.87 (0.41), respectively, while they were 0.90 (0.39) and 0.91 (0.35) for ANN and ANFIS, respectively. Results of developed SVM models indicated that both FS-(-SVM) and FS-(-SVM) regression techniques were superior. Furthermore, it was founded that the performance of FS-(-SVM) and FS-(-SVM) models were generally a bit better than the best FS-ANFIS and FS-ANN solutions for short term forecasting of CO concentrations.

Risk assessment; safety; FMEA technique; children playground; urban park. This study aimed to identify and assess safety risks in children's playgrounds in urban parks in Arak using the Failure Mode and Effects Analysis (FMEA) technique. The research follows a descriptive-analytical and survey-based approach, with data collected from library resources, safety standards, and field studies, including site visits, observations, and on-site inspections. FMEA was applied for data analysis, and Excel was used for statistical calculations. To examine common playground hazards, an FMEA worksheet was completed for each park, assessing 21 criteria across five categories: lighting equipment, shading structures, protective surfaces, playground equipment, and the playground surroundings. The assessment revealed that 10% of the studied parks contained high-risk (critical) playgrounds, while 80% exhibited moderate-risk (semi-critical) conditions. The absence of shading structures and lack of age-based equipment segregation were identified as major critical hazards, affecting all examined parks. The findings indicate that the safety conditions of children's playgrounds in Arak's urban parks are inadequate. Thus, urban managers should assess and improve playground safety, prioritizing corrective actions for critical-risk parks to prevent accidents and enhance children's safety.