A Systematic Review of Heterogeneous Catalysis Applied to the Treatment of Pharmaceutical Wastewater: Operational Conditions and Statistical Analysis

Abstract

The use of heterogeneous photocatalysis has garnered significant attention, mainly due to its remarkable efficacy in degrading recalcitrant compounds. The main objective of this research was to investigate this process applied to pharmaceutical treatment. For that, an analysis of a Final Bibliographic Portfolio (FBP), using the systematic review of the PRISMA and the ProKnow-C method, and a meta-analysis study in a historical series from 2010 to 2020, were performed for scientific works published in indexed journals from the Scopus and Web of Science databases and fully available in English. The works were filtered after a careful reading of the titles, followed by the exclusion of repeated documents and those that were not aligned with the research from 3498 articles, 40 of which were chosen to compose the FBP that addressed the classes of antibiotics, antihypertensives, analgesics, and anti-inflammatory drugs after scientific recognition and exclusion due to not fitting into one of the four FBP structured stages: (1) identification, (2) triage, (3) eligibility, and (4) inclusion. The following gaps were highlighted: (i) a limited number of studies working with interactions of the interfering variables; (ii) a large number of experiments not considering the natural constituents of wastewater; (iii) the use of drug concentrations high above the values found in aquatic matrices; (iv) little applicability of the process at the real scale. In this meta-analysis study, operational parameter optimization was fundamental to guarantee degradation efficiencies above 80% with a variety of pharmaceutical pollutants, the main representatives studied of which were tetracycline, nimesulide, diclofenac, ibuprofen, and atenolol. However, there is still a need to determine the best conditions for this technique when using real effluents, which have the utmost importance for the process on a large scale.