Evidence map›Paper›PMID 42156400›Full record

ArticleScientific reports2026

Improved ecological risk assessment of phenol in sediments via species sensitivity distribution and equilibrium partitioning method using water toxicity data.

Seonghwan Park, Sang-Jun Lee, Jin-Woo Park, Hee-Jin Jeong, Dong-Hyuk Yeom, Jungmin Kim

Abstract read
In one paragraph

Article in Scientific reports, 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

6 authors.

Seonghwan Park *Center for Environmental Safety Research, Division of Gyeongnam Bio- Environmental Research, Korea Institute of Toxicology, Jinju, 52834, Republic of Korea.
Sang-Jun Lee *Center for Environmental Safety Research, Division of Gyeongnam Bio- Environmental Research, Korea Institute of Toxicology, Jinju, 52834, Republic of Korea.
Jin-Woo ParkCenter for Environmental Safety Research, Division of Gyeongnam Bio- Environmental Research, Korea Institute of Toxicology, Jinju, 52834, Republic of Korea.
Hee-Jin JeongCenter for Environmental Safety Research, Division of Gyeongnam Bio- Environmental Research, Korea Institute of Toxicology, Jinju, 52834, Republic of Korea.
Dong-Hyuk YeomCenter for Environmental Safety Research, Division of Gyeongnam Bio- Environmental Research, Korea Institute of Toxicology, Jinju, 52834, Republic of Korea. dhyeom@kitox.re.kr.
Jungmin KimCenter for Respiratory Safety Research, Division of Jeonbuk Advanced Bio Research , Korea Institute of Toxicology, Jeongeup, 56212, Republic of Korea. jungmin.kim@kitox.re.kr.

Funding

Korea Environmental Industry and Technology Institute RS-2022-KE02211
6 · The paper itself

Abstract

Phenol is a water-soluble contaminant frequently detected in sediments, yet sediment-specific toxicity data are scarce. To address this data gap, we evaluated the use of water-based toxicity data for sediment ecological risk assessment (ERA) by combining the equilibrium partitioning method (EPM) with species sensitivity distributions (SSDs). Acute and chronic toxicity data from laboratory and artificial-stream tests using native aquatic species were compiled and converted to sediment-equivalent values for SSD construction. We quantified how species origin (native vs. foreign), habitat type (benthic vs. non-benthic), taxonomic composition, and sample size affect SSD-derived hazardous concentration for 5% of species (HC

Indexed as

Geologic SedimentsPhenolWater Pollutants, ChemicalAnimalsAquatic OrganismsEcosystemEnvironmental MonitoringRisk AssessmentPhenolWater Pollutants, ChemicalEcological risk assessmentEquilibrium partitioning methodPhenolSedimentSpecies sensitivity distribution

Identifiers

PMID42156400
PMCPMC13186978

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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.