Public concern over environmental issues such as ecosystem degradation is high. However, restoring coupled human-natural systems requires integration across many science …
Contaminants in road dusts can directly pose significant human health risks through oral ingestion, particle inhalation, and dermal contact. Therefore, this study has been designed to …
This study reports a spatiotemporal characterization of toluene, benzene, ethylbenzene, and xylenes concentrations (BTEX) in an urban hot spot in Iran, specifically at an bus terminal …
The main objective of the present study was to predict the associated health endpoint of PM 2.5 using an artificial neural network (ANN). The neural network used in this work contains a …
Dust events in the Middle East are becoming more frequent and intense in recent years with impacts on air quality, climate, and public health. In this study, the relationship between dust …
In this study, we apply six machine-learning algorithms (XGBoost, Cubist, BMARS, ANFIS, Cforest and Elasticnet) to investigate the susceptibility of the Jazmurian Basin in …
This study reports a spatiotemporal characterization of formaldehyde and acetaldehyde in the summer and winter of 2017 in the urban area of Shiraz, Iran. Sampling was fulfilled …
Ahvaz, Iran ranks as the most polluted city of the world in terms of PM 10 concentrations that lead to deleterious effects on its inhabitants. This study examines diurnal, weekly, monthly …
Lake Urmia (LU) once was the second largest hypersaline lake in the world, covering up to 6000 km 2, but has undergone catastrophic desiccation in recent years resulting in loss of …