In-line sample preparation for environmental studies in flow-based systems with electroanalytical detection

• Grant number: 18/13157-9
• Support type: Scholarships abroad - Research
• Effective date (Start): November 01, 2019
• Effective date (End): October 29, 2020
• Field of knowledge: Physical Sciences and Mathematics - Chemistry - Analytical Chemistry
• Principal Investigator: Diogo Librandi da Rocha
• Grantee: Diogo Librandi da Rocha
• Host: Maria da Conceicao Branco da Silva
• Home Institution: Centro de Ciências Naturais e Humanas (CCNH). Universidade Federal do ABC (UFABC). Ministério da Educação (Brasil). Santo André , SP, Brazil
• Local de pesquisa : Universidade do Porto (UP), Portugal

Abstract

The development of sensitive methods for complex samples is an actual chanllange in view of the limitations of some established analytical procedures related to selectivity and slowness, also requiring equipment with high costs of acquisition and maintainance. Besides, batch sample preparation can hinder the accuracy of the results. The bioavailability of metallic species in natural waters, such as manganese, varies with its chemical form, making fractionation important. The recovery of wastewaters with pesticides, such as glyphosate, is also important considering the cronical toxicity. Procedures for the degradation of glyphosate, therefore, must be evaluated in view of the waste of solutions that do not hinder the quality of waters. Both themes deserve attention due to the negative impacts on public health and environment. In this project, it will be developed mechanized analytica procedures with in-line photochemical conversions and electroanalytical detection aiming at the fractionation of manganese in natural waters and of the treatment of wastewaters containing glyphosate. Dedicated electroanalytical sensors will be developed with adequate sensitivity and selectivity, and low cost. In-line Mn fractionation will avoid the reconversion of species. In both cases, the results will be compared to literature data where alternative strategies are proposed for solving the anaytical problems.