Hamza Ahmad Isiyaka

TL;DR: In this article, the authors investigated and proposed a reduction in the number of water quality monitoring stations, parameters and developed the best input combination for water quality modelling using artificial neural network and multivariate statistical technique.

TL;DR: This review is devoted to the compilations and analysis of the role of metal-organic frameworks (MOFs) and their composites as potential materials for such applications and the current scenario and challenges that need to be addressed.

TL;DR: In this paper, the authors highlighted the advantage of adsorption technology in the removal of polycyclic aromatic hydrocarbons (PAHs) and phenolic compounds in wastewater, and proposed commercialization, pilot, and industrial-scale applications of the studied adsorbents towards persistent organic pollutants (POPs) removal from wastewater.

TL;DR: In this article, the results from large hydrochemistry data analysed using multivariate statistical techniques such as Cluster Analysis (CA), Discriminant Analysis (DA) and Principal Component Analysis (PCA) with the objectives of determining the spatial variability of groundwater and to identify the sources of pollution that presently affects the groundwater.

TL;DR: In this paper, a review on the adsorption of dyes and pharmaceuticals from water onto UiO (Universitetet i Oslo) metal-organic frameworks (MOFs) is presented.