Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 414

The DOI matches its Crossref record.

Electrochemical sensors for environmental monitoring: design, development and applications

Hanrahan, Grady, Patil, Deepa G., Wang, Joseph·2004·Journal of Environmental Monitoring

Abstract

The advancement in miniaturization and microfabrication technology has led to the development of sensitive and selective electrochemical devices for field-based and in situ environmental monitoring. Electrochemical sensing devices have a major impact upon the monitoring of priority pollutants by allowing the instrument to be taken to the sample (rather than the traditional way of bringing the sample to the laboratory). Such devices can perform automated chemical analyses in complex matrices and provide rapid, reliable and inexpensive measurements of a variety of inorganic and organic pollutants. Although not exhaustive due to the vast amounts of new and exciting electrochemical research, this review addresses many important advances in electrochemical sensor design and development for environmental monitoring purposes. Critical design factors and development issues including analytical improvements (e.g. detection limits), microfabrication and remote communication are presented. In addition, modern environmental applications will be discussed and future perspectives considered.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1039/b403975k

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 414

Metadata

Authors
Hanrahan, G., Patil, D. G., & Wang, J.
Venue
Journal of Environmental Monitoring
Published
2004
Volume
6
Issue
8
Pages
657
ISSN
  • 1464-0325 (ISSN-L)
  • 1464-0333
OpenAlex
W2021395039
Cited by
414
References
0
FWCI
4.52
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Electrochemical sensors for environmental monitoring: design, development and applications. https://app.cochat.ai/papers/10.1039/b403975k
The paper
Hanrahan, G., Patil, D. G., & Wang, J. (2004). Electrochemical sensors for environmental monitoring: design, development and applications. Journal of Environmental Monitoring. https://doi.org/10.1039/b403975k

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.