Since the epidemic of COVID-19 was declared in Wuhan, Hubei Province of China, and other parts of the world, several studies have been carried out over several regions to observe the development of the epidemic, to predict its duration, and to estimate its final size, using complex models such as the SEIR model or the simpler ones such as the SIR model. These studies showed that the SIR model is much more efficient than the SEIR model; therefore, we are applying this model in the Kingdom of Morocco since the appearance of the first case on 2 March 2020, with the objective of predicting the final size of the epidemic.
During the present study, biopolymer lignin was extracted, in particular, from sugar beet pulp (molasses) from the Tadla region (224 km from Marrakech, Morocco). The lignin was characterized by infrared spectroscopy (FTIR) and thermogravimetric TG/DTA analysis and then used as a modifier to enhance the electroanalytical detection of heavy metal ion traces. The performance of the lignin/CPE sensor to detect lead (II) was studied by cyclic voltammetry (CV) and square-wave voltammetry in 0.3 mol L−1 NaCl. With optimized experimental parameters, the lignin/CPE sensor developed has a minimum detection limit of 2.252.10−11 M for Pb (II). The proposed working electrode has been successfully applied for the coanalysis of Pb (II) in tap water with good results.
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