Dataset Information

Development of a Heavy Metal Sensing Boat for Automatic Analysis in Natural Waters Utilizing Anodic Stripping Voltammetry.

ABSTRACT: Determination of the levels of heavy metal ions would support assessment of sources and pathways of water pollution. However, traditional spatial assessment by manual sampling and off-site detection in the laboratory is expensive and time-consuming and requires trained personnel. Aiming to fill the gap between on-site automatic approaches and laboratory techniques, we developed an autonomous sensing boat for on-site heavy metal detection using square-wave anodic stripping voltammetry. A fluidic sensing system was developed to integrate into the boat as the critical sensing component and could detect ≤1 μg/L Pb, ≤6 μg/L Cu, and ≤71 μg/L Cd simultaneously in the laboratory. Once its integration was completed, the autonomous sensing boat was tested in the field, demonstrating its ability to distinguish the highest concentration of Pb in an effluent of a galena-enriched mine compared to those at other sites in the stream (Osor Stream, Girona, Spain).

SUBMITTER: Yang Q

PROVIDER: S-EPMC8669633 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The determination of copper (Cu) speciation and its bioavailability in natural waters is an important issue due to its specific role as an essential micronutrient but also a toxic element at elevated concentrations. Here, we report an improved anodic stripping voltammetry (ASV) method for organic Cu speciation, intended to eliminate the important problem of surface-active substances (SAS) interference on the voltammetric signal, hindering measurements in samples with high organic matter concentration. The method relies on the addition of nonionic surfactant Triton-X-100 (T-X-100) at a concentration of 1 mg L-1. T-X-100 competitively inhibits the adsorption of SAS on the Hg electrode, consequently 1) diminishing SAS influence during the deposition step and 2) strongly improving the shape of the stripping Cu peak by eliminating the high background current due to the adsorbed SAS, making the extraction of Cu peak intensities much more convenient. Performed tests revealed that the addition of T-X-100, in the concentration used here, does not have any influence on the determination of Cu complexation parameters and thus is considered "interference-free." The method was tested using fulvic acid as a model of natural organic matter and applied for the determination of Cu speciation in samples collected in the Arno River estuary (Italy) (in spring and summer), characterized by a high dissolved organic carbon (DOC) concentration (up to 5.2 mgC L-1) and anthropogenic Cu input during the tourist season (up to 48 nM of total dissolved Cu). In all the samples, two classes of ligands (denoted as L1 and L2) were determined in concentrations ranging from 3.5 ± 2.9 to 63 ± 4 nM eq Cu for L1 and 17 ± 4 to 104 ± 7 nM eq Cu for L2, with stability constants logK Cu,1 = 9.6 ± 0.2-10.8 ± 0.6 and logK Cu,2 = 8.2 ± 0.3-9.0 ± 0.3. Different linear relationships between DOC and total ligand concentrations between the two seasons suggest a higher abundance of organic ligands in the DOM pool in spring, which is linked to a higher input of terrestrial humic substances into the estuary. This implies that terrestrial humic substances represent a significant pool of Cu-binding ligands in the Arno River estuary.

Dataset Information

Development of a Heavy Metal Sensing Boat for Automatic Analysis in Natural Waters Utilizing Anodic Stripping Voltammetry.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets