Evidence map›Paper›PMID 32344554›Full record

ArticleInternational journal of environmental research and public health2020

Using Principal Components Analysis and IDW Interpolation to Determine Spatial and Temporal Changes of Surface Water Quality of Xin'anjiang River in Huangshan, China.

Wenjie Yang, Yue Zhao, Dong Wang, Huihui Wu, Aijun Lin, Li He

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
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30citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

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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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3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Wenjie YangCollege of Renewable Energy, North China Electric Power University, Beijing 102206, China.
Yue ZhaoChinese Academy for Environmental Planning, Beijing 100012, China.
Dong WangChinese Academy for Environmental Planning, Beijing 100012, China.
Huihui WuBeijing City Environment Pollution Control and Resource Reuse Engineering Research Center, Beijing University of Chemical Technology, Beijing 100029, China.
Aijun LinBeijing City Environment Pollution Control and Resource Reuse Engineering Research Center, Beijing University of Chemical Technology, Beijing 100029, China.
Li HeCollege of Renewable Energy, North China Electric Power University, Beijing 102206, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study was aimed at assessing the spatial and temporal distribution of surface water quality variables of the Xin'anjiang River (Huangshan). For this purpose, 960 water samples were collected monthly along the Xin'anjiang River from 2008 to 2017. Twenty-four water quality indicators, according to the environmental quality standards for surface water (GB 3838-2002), were detected to evaluate the water quality of the Xin'anjiang River over the past 10 years. Principal component analysis (PCA) was used to comprehensively evaluate the water quality across eight monitoring stations and analyze the sources of water pollution. The results showed that all samples could be analyzed by three main components, which accounted for 87.24% of the total variance. PCA technology identified important water quality parameters and revealed that nutrient pollution and organic pollution are major latent factors which influence the water quality of Xin'anjiang River. It also showed that agricultural activities, erosion, domestic, and industrial discharges are fundamental causes of water pollution in the study area. It is of great significance for water quality safety management and pollution control of the Xin'anjiang River. Meanwhile, the inverse distance weighted (IDW) method was used to interpolate the PCA comprehensive score. Based on this, the temporal and spatial structure and changing characteristics of water quality in the Xin'anjiang River were analyzed. We found that the overall water quality of Xin'anjiang River (Huangshan) was stable from 2008 to 2017, but the pollution of the Pukou sampling point was of great concern. The results of IDW helped us to identify key areas requiring control in the Xin'anjiang River, which pointed the way for further delicacy management of the river. This study proved that the combination of PCA and IDW interpolation is an effective tool for determining surface water quality. It was of great significance for the control of water pollution in Xin'anjiang River and the reduction of eutrophication pressure in Thousand Island Lake.

Indexed as

Environmental MonitoringWater Pollutants, ChemicalWater QualityChinaPrincipal Component AnalysisRiversWater Pollutants, Chemicalinverse distance weighted (IDW)principal component analysis (PCA)surface water qualityXin’anjiang River

Identifiers

PMID32344554
PMCPMC7215294

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Registered trials

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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.