A review on chemometrics for detecting emerging pollutants in the environment and assessing their toxicological impact on humans and the environment.

Joseph Sekhar Santhappan, Ahmed Said Ahmed Al-Shahri, Narasimman Kalaiselvan, Nayanjyoti Baishya, Thangavel Mathimani

Abstract readReview

In one paragraph

Review in iScience, 2026. 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

–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

0 citing papers in PubMed.

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

5 authors.

Joseph Sekhar SanthappanDepartment of Engineering and Technology, University of Technology and Applied Sciences, Musandam, Oman.

Ahmed Said Ahmed Al-ShahriDepartment of Engineering and Technology, University of Technology and Applied Sciences, Musandam, Oman.

Narasimman KalaiselvanTechnology Information Forecasting and Assessment Council (TIFAC), Vellore Institute of Technology, Vellore, Tamil Nadu, India.

Nayanjyoti BaishyaDepartment of Mechanical Engineering, Sree Chitra Thirunal College of Engineering, Pappanamcode, Thiruvananthapuram, Kerala 695018, India.

Thangavel MathimaniInstitute of Research and Development, Duy Tan University, Da Nang, Vietnam.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapidly expanding industrial activities, along with rising human living standards, contribute to the emission of emerging pollutants (EPs) that have become one of the foremost threats to human health and the balance of the environment. The increasing significance of health risks and environmental protection has led to an urgent need for intensive research to tackle the challenges associated with developing scalable and advanced technologies for predicting the impacts of EPs and determining their remediation needs. Consequently, this review aims to analyze recent studies on various detection and chemometric techniques employed in the analysis of EPs. Our critical analysis reveals that hybrid analytical techniques and advanced machine learning and deep learning data analysis methods provide scalable and cost-effective solutions for evaluating EPs. Furthermore, understanding their specific effects on human health can serve as a reliable foundation for the selection of appropriate detection and analysis processes.

Indexed as

Environmental monitoringEnvironmental sciencePollution

Identifiers

PMID42382999

DOI10.1016/j.isci.2026.116474

PMCPMC13316213

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

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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.