Microalgae separation in MP-PVC contaminated wastewater using plant-based coagulant over different extraction methods in Bauru, Brazil.

This study investigates the effectiveness of coagulation-flocculation and sedimentation (CFS) for separating microalgae, focusing on the use of various Moringa oleifera extracts as natural coagulants. We examined photobioreactor effluent (PBR) both with and without microplastic PVC (MP-PVC) contamination, referred to as PBR R2 and PBR R1, respectively. Utilising response surface methodology, we identified optimal conditions for the removal of microalgae and MP-PVC.

Dynamics of dissolved inorganic carbon (DIC) and stable C isotope ratios (δC) in a tropical watershed with diversified land use in São Paulo State, Brazil.

The fluvial transport of dissolved inorganic carbon (DIC) is an important component of the global carbon cycle. Herein, we assessed the dynamics of DIC and the C stable isotopic composition (δC) in a watershed with diversified land use in São Paulo State (Brazil), more specifically in the Sorocaba River basin (SRB) and considered the temporal and spatial scales. For this purpose, twelve fluvial samples at each sampling point (e.

Assessment of sustainable drainage strategies in urban water systems using urban water metabolism and multi-criteria decision analyses.

The simulation of urban water metabolism (UWM) allows for the tracking of all water, energy, and material flows within urban water systems (UWSs) and the quantification of their performance, including emissions into the air, water, and soil. This study evaluates seven drainage strategies (DSs) within conventional and sustainable urban drainage systems (SUDSs) using UWM and multicriteria decision analysis (MCDA). The DSs were designed to assess their corresponding UWM performances, employing key performance indicators (KPIs) related to sewer system balance, energy consumption, greenhouse gas (GHG) emissions, acidification, eutrophication, contamination, and sludge production.

Machine learning framework for modeling flocculation kinetics using non-intrusive dynamic image analysis.

The implementation of a machine learning (ML) model to improve both the effectiveness and sustainability of the water treatment system is a significant challenge in the water sector, with the optimization of flocculation processes being a major setback. The objective of this study was to develop a ML model for predicting flocs evolution of the flocculation process in water treatment. Furthermore, we have devised a framework for its potential adoption in large-scale water treatment.

Combining ultrafiltration and diffusive gradients in thin films techniques for speciation/fractionation of Cu and Zn in cytosol of liver of Nile tilapia (Oreochromis niloticus).

This work aims to evaluate the size and lability of Cu and Zn bound to proteins in the cytosol of fish liver of Oreochromis niloticus by employing solid-phase extraction (SPE), diffusive gradients in thin films (DGT), and ultrafiltration (UF). SPE was carried out using Chelex-100. DGT containing Chelex-100 as binding agent was employed.