Evidence map›Paper›PMID 41262151›Full record

ArticleACS ES&T water2025

Low-Cost Optical Sensing for Nitrate and Phosphate: Advancing Community Freshwater Monitoring.

Riccardo G Cirrone, Amedeo Boldrini, Alessio Polvani, Matteo Arrigucci, Xinyu Liu, Luisa Galgani, Sasha Woods, Steven A Loiselle

Abstract read
In one paragraph

Article in ACS ES&T water, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Riccardo G CirroneDepartment of Biotechnology, Chemistry and Pharmacy, University of Siena, Via Aldo Moro, 2, Siena 53100, Italy.ORCID https://orcid.org/0009-0009-7096-9398
Amedeo BoldriniDepartment of Biotechnology, Chemistry and Pharmacy, University of Siena, Via Aldo Moro, 2, Siena 53100, Italy.ORCID https://orcid.org/0009-0006-8253-7371
Alessio PolvaniDepartment of Biotechnology, Chemistry and Pharmacy, University of Siena, Via Aldo Moro, 2, Siena 53100, Italy.ORCID https://orcid.org/0009-0006-2912-1019
Matteo ArrigucciDepartment of Biotechnology, Chemistry and Pharmacy, University of Siena, Via Aldo Moro, 2, Siena 53100, Italy.
Xinyu LiuDepartment of Biotechnology, Chemistry and Pharmacy, University of Siena, Via Aldo Moro, 2, Siena 53100, Italy.
Luisa GalganiDepartment of Biotechnology, Chemistry and Pharmacy, University of Siena, Via Aldo Moro, 2, Siena 53100, Italy.
Sasha WoodsEarthwatch Europe, 102-104 St Aldate's, Oxford OX1 1BT, United Kingdom.
Steven A LoiselleDepartment of Biotechnology, Chemistry and Pharmacy, University of Siena, Via Aldo Moro, 2, Siena 53100, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-resolution water quality data are fundamental to achieving the objectives of the European Water Framework Directive (WFD) and the United Nations Sustainable Development Goal 6 (SDG). While community-based monitoring projects provide valuable data, concerns remain regarding the accuracy and reliability of those data. This study addresses these challenges by developing an affordable, reliable, and open-source optical sensor for monitoring nitrate and phosphate concentrations in freshwater environments. The sensor was developed to support citizen scientists and community monitoring and consists of a 3D-printed case made of polylactic acid, a light-emitting diode (LED), and a commercial ambient light detector managed by a Raspberry Pi Zero W. Data can be stored offline or transmitted in real time via Wi-Fi. The analytical performance was evaluated in laboratory and operational conditions using standard and natural river samples, performing a comparative analysis with a laboratory-based spectrophotometer. Results showed that the sensor provides accurate and repeatable measurements with a significant improvement over conventional colorimetric methods. The sensor technology follows open science principles as the 3D design, operating software, and user guidelines are freely available online to support further advancements and its application in community-based water quality monitoring.

Indexed as

citizen sciencein-field analysisIoTportable sensorswater quality

Identifiers

PMID41262151
PMCPMC12626233

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.