Nanomaterial-based AOPs for the removal of organic pollutants in aqueous matrices: A systematic review of response surface methodology (RSM) models

Organic pollutants in water mainly originate from human activities and can cause numerous problems for human health and the environment. In order to avoid these problems, organic pollutants must be removed using appropriate and effective methods. Advanced oxidation processes (AOPs), which comprise different technologies, have attracted attention in recent years due to their high efficiency in water and wastewater treatment. This systematic review evaluates the effectiveness of nanomaterial-based AOPs for removing organic pollutants from aqueous solutions. The uniqueness of this study is the investigation of response surface methodology (RSM) models. Specifically, the present study reviewed six subgroups of nanomaterial-based AOPs, including Fe-based, TiO2-based, Zn-based, Cu-based, Mg-based, and a set of disparate processes categorized as others. The effects of process variables (including pH, contact time, initial pollutant concentration, and catalyst dosage) were investigated by considering the classification of different pollutant groups. In total, 71 studies were included in this review. The data were primarily analyzed with R software, and graphs and figures were drawn if necessary. The average pooled percentages of Fe-based, TiO2-based, Zn-based, Cu-based, and Mg-based processes for organic pollutants removal, regardless of pollutant type, were 87.53 %, 82.61 %, 80.16 %, 82.93 %, and 87.93 %, respectively. Based on this systematic review, nano-based AOPs can efficiently remove organic pollutants from aqueous matrices. Notably, however, the efficiency of the process can be changed depending on the conditions applied in the system. [Display omitted] •Nano-based oxidation processes were reviewed for organic pollutants removal.•Nanomaterials are reactive and have high surface area and catalytic properties.•Nano-based hybrid processes can completely remove pollutants in less time.•Aqueous solution properties and experimental variables affect the removal rate.