Distribution, Site-Specific Water Quality Criteria, and Ecological Risk Assessment of Heavy Metals in Surface Water in Fen River, China.

Huixian Li, Yue Li, Guanghui Guo, Yang Li, Ruiqing Zhang, Chenglian Feng, Yahui Zhang

Abstract read

In one paragraph

Article in Toxics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it

0cells of the map it votes in

3citing 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

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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

3 citing papers in PubMed.

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

7 authors.

Huixian LiState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.

Yue LiSchool of Ecology and Environment, Inner Mongolia University, Huhhot 010021, China.

Guanghui GuoInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.

Yang LiCollege of Water Resource Science and Engineering, Taiyuan University of Technology, Taiyuan 030030, China.

Ruiqing ZhangSchool of Ecology and Environment, Inner Mongolia University, Huhhot 010021, China.

Chenglian FengState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.ORCID 0000-0001-5493-574X

Yahui ZhangState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.

Funding

the National Key Research Development Program of China 2021YFC3200104; 2022YFC3204103

6 · The paper itself

Abstract

Due to a lack of toxicity reference values that match the regional environmental characteristics, the ecological risk of metals in water bodies cannot be accurately assessed. The Fen River is the second-largest tributary of the Yellow River in China, and the sustainability of this area is threatened by heavy metal pollution caused by intensive industrial and agricultural activities. In this study, site-specific water quality criteria (WQCs) for heavy metals in the Fen River were derived considering toxicity data from native aquatic organisms and regional water quality factors (e.g., water hardness). Short-term WQCs for Mn, Cu, Cd, Zn, Cr, Pb, and Ni were 2026.15, 98.62, 10.02, 63.07, 6.06, 166.74, and 132.73 μg/L, respectively, and long-term WQCs were 166.53, 29.71, 2.18, 19.29, 4.15, 6.38, and 14.76 μg/L, respectively. The distribution characteristics of these metals during the wet season in 2020 were explored, and their average concentrations in the river water did not exceed the environmental quality standards for surface water in China but were higher than the world average levels. Cr was the main pollutant in the sampling sites of Yaodu region, Hongdong Shitan, Xiao River, and Duanchun River, as was Pb in Duanchun River. Based on the site-specific WQCs, using hazardous quotient (HQ) and margin of safety (MOS

Indexed as

ecological risk assessmentecotoxicityFen Riverheavy metalswater quality criteria

Identifiers

PMID37624209

DOI10.3390/toxics11080704

PMCPMC10458924

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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.