Water-borne emerging pollutants are among the greatest concern of our modern society. Many of these pollutants are categorized as endocrine disruptors due to their environmental toxicities. They are harmful to humans, aquatic animals, and plants, to the larger extent, destroying the ecosystem. Thus, effective environmental remediations of these pollutants became necessary. Among the various remediation techniques, adsorption and photocatalytic degradation have been single out as the most promising. 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. Emerging organic pollutants, like dyes, herbicides, pesticides, pharmaceutical products, phenols, polycyclic aromatic hydrocarbons, and perfluorinated alkyl substances, have been extensively studied. Important parameters that affect these processes, such as surface area, bandgap, percentage removal, equilibrium time, adsorption capacity, and recyclability, are documented. Finally, we paint the current scenario and challenges that need to be addressed for MOFs and their composites to be exploited for commercial applications.

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This study aims to investigate the spatial variation in the source of air pollution, identify the percentage contribution of each pollutant and apportion the mass contribution of each source category using chemometric techniques. Hierarchical agglomerative cluster analysis (HACA) successfully grouped the five air monitoring sites into three groups (cluster 1, 2 and 3). Principal component analysis (PCA) was used to spot out the sources of air pollution which are attributed to anthropogenic activities. Multiple linear regression (MLR) was used to develop an equation model that explains the contribution of pollutants in each cluster. However, it was observed that particulate matter (PM10) and Ozone (O3) are the most significant pollutants influencing the value of air pollutant index (API). Meanwhile, the source apportionment indicates that cluster 1 is influenced by gas and non-gas pollutants to a degree of 84%, weather condition 15% and 1% by gas and secondary pollutants. Cluster 2 is affected by gas and secondary pollutants to a tune of 87% and 13% by weather condition while cluster 3 is apportioned with 98% secondary gas and non-gas pollutants and 2% weather condition. This study reveals the usefulness of chemometric technique in modeling and reducing the cost and time of monitoring redundant stations and parameters.

Polycyclic aromatic hydrocarbons (PAHs) and phenolic compounds had been widely recognized as priority organic pollutants in wastewater with toxic effects on both plants and animals [...]