Using Artificial Intelligent to Model Predict the Biological Resilience With an Emphasis on Population of cyanobacteria in Jajrood River in The Eastern Tehran, Iran.

Prediction of bio-resilience in water resources such as rivers is important for better management of land-use systems and water resources. This study has proposed the use of artificial intelligent (AI) models for assessing the relationship among the biological conditions in Jajrood River. For this purpose, the qualitative monthly data of the river related to 2008-2018 were applied.

Estimation of the heavy metals released from cigarette butts to beaches and urban environments.

Cigarette butts (CB) are considered as a commonly littered waste. This hazardous waste contains a variety of pollutants. This study was developed to estimate the release of some heavy metals from CBs to the environment in different climatic conditions in different scenarios.

Non-carcinogenic risk assessment of exposure to heavy metals in underground water resources in Saraven, Iran: Spatial distribution, monte-carlo simulation, sensitive analysis.

Groundwater aquifers are considered the second most abundant water supply for drinking water all over the world. In Iran, ground waters are commonly employed for drinking water, irrigation, and industrial purposes. Heavy metals (HMs) pose human concerns about the groundwater contamination; these pollutants are recognized to be capable of bio-accumulation, long persistence in the natural environment, and toxic effects.