Evidence map›Paper›PMID 37810808›Full record

ArticleHeliyon2023

Implementation of an electronic nose for real -time identification of odour emission peaks at a wastewater treatment plant.

Stefano Prudenza, Carmen Bax, Laura Capelli

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.5field-weighted citation impact, top 19% of its field
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

0 citing papers in PubMed, 14 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 1 institution in 1 country.

Stefano PrudenzaPolitecnico di Milano, Department of Chemistry Materials and Chemical Engineering "G. Natta", Piazza Leonardo da Vinci 32, 20133, Milano, Italy.
Carmen BaxPolitecnico di Milano, Department of Chemistry Materials and Chemical Engineering "G. Natta", Piazza Leonardo da Vinci 32, 20133, Milano, Italy.
Laura CapelliPolitecnico di Milano, Department of Chemistry Materials and Chemical Engineering "G. Natta", Piazza Leonardo da Vinci 32, 20133, Milano, Italy.
Politecnico di Milano · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper proposes a novel approach for the real-time monitoring of odour emissions from a WasteWater Treatment Plant (WWTP) using an Instrumental Odour Monitoring System (IOMS). The plant is characterized by unpredictable odour peaks at its arrival tank (AT), generating nuisance and complaints in the population living nearby the plant. Odour peaks are most likely due to the conferment of non-identified and malodorous wastewaters coming from various industrial activities. Due to the high variability of sources collecting their wastewaters to the WWTP, a new methodology to train the IOMS, based on the use of a one-class classifier (OCC), has been exploited. The OCC enables to detect deviations from a "Normal Operating Region" (NOR), defined as to include odour concentrations levels unlikely to cause nuisance in the citizenship. Such deviations from the NOR thus should be representative of the odour peaks. The results obtained prove that the IOMS is able to detect real-time alterations of odour emissions from the AT with an accuracy on independent validation data of about 90% (CI

Identifiers

PMID37810808
PMCPMC10551564
OpenAlexW4387107477

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.