Development of an Innovative Biosensor Based on Graphene/PEDOT/Tyrosinase for the Detection of Phenolic Compounds in River Waters.

Phenolic compounds, originating from industrial, agricultural, and urban sources, can leach into flowing waters, adversely affecting aquatic life, biodiversity, and compromising the quality of drinking water, posing potential health hazards to humans. Thus, monitoring and mitigating the presence of phenolic compounds in flowing waters are essential for preserving ecosystem integrity and safeguarding public health. This study explores the development and performance of an innovative sensor based on screen-printed electrode (SPE) modified with graphene (GPH), poly(3,4-ethylenedioxythiophene) (PEDOT), and tyrosinase (Ty), designed for water analysis, focusing on the manufacturing process and the obtained electroanalytical results.

Electrochemical Detection of Cd, Pb, Cu and Hg with Sensors Based on Carbonaceous Nanomaterials and FeO Nanoparticles.

Two electrochemical sensors were developed in this study, with their preparations using two nanomaterials with remarkable properties, namely, carbon nanofibers (CNF) modified with FeO nanoparticles and multilayer carbon nanotubes (MWCNT) modified with FeO nanoparticles. The modified screen-printed electrodes (SPE) were thus named SPE/FeO-CNF and SPE/FeO-MWCNT and were used for the simultaneous detection of heavy metals (Cd, Pb, Cu and Hg). The sensors have been spectrometrically and electrochemically characterized.

New Approach to Modelling the Impact of Heavy Metals on the European Union's Water Resources.

The present research aims to address the highly topical issue of heavy metal water pollution from an integrated European perspective, i.e., to quantify through modelling a general model of water pollution reduction in the EU.

To a Green Economy across the European Union.

"Is the green economy a real solution to the present economic development?" represents the main question of the present research. The paper deals with assessing the impact of innovation on the green economy and quality of life through policies promoted at the European Union (EU) level. The objectives of the paper are to assess the impact level of the policy implementation across the Member States through the research and development (R&D) process and to identify models for the development of the green economy in Europe.

Multisensory System Used for the Analysis of the Water in the Lower Area of River Danube.

The present paper describes the development of a multisensory system for the analysis of the natural water in the Danube, water collected in the neighboring area of Galati City. The multisensory system consists of a sensor array made up of six screen-printed sensors based on electroactive compounds (Cobalt phthalocyanine, Meldola's Blue, Prussian Blue) and nanomaterials (Multi-Walled Carbon Nanotubes, Multi-Walled Graphene, Gold Nanoparticles). The measurements with the sensors array were performed by using cyclic voltammetry.

Study of physico-chemical characteristics of wastewater in an urban agglomeration in Romania.

This study investigates the level of wastewater pollution by analyzing its chemical characteristics at five wastewater collectors. Samples are collected before they discharge into the Danube during a monitoring campaign of two weeks. Organic and inorganic compounds, heavy metals, and biogenic compounds have been analyzed using potentiometric and spectrophotometric methods.

Estimating annual CO(2) flux for Lutjewad station using three different gap-filling techniques.

Long-term measurements of CO(2) flux can be obtained using the eddy covariance technique, but these datasets are affected by gaps which hinder the estimation of robust long-term means and annual ecosystem exchanges. We compare results obtained using three gap-fill techniques: multiple regression (MR), multiple imputation (MI), and artificial neural networks (ANNs), applied to a one-year dataset of hourly CO(2) flux measurements collected in Lutjewad, over a flat agriculture area near the Wadden Sea dike in the north of the Netherlands. The dataset was separated in two subsets: a learning and a validation set.