Water quality assessment and source identification of the Shuangji River (China) using multivariate statistical methods

Liu, Junzhao; Zhang, Dong; Tang, Qiuju; Xu, Hongbin; Huang, Shanheng; Shang, Dan; Liu, Ruxue

doi:10.1371/journal.pone.0245525

Cited by 36 publications

(20 citation statements)

References 50 publications

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“…The hierarchical cluster analysis (HCA) can be used for grouping data into classes according to characteristics, sources, and features that are similar or dissimilar (Hamid et al 2016;Hajigholizadeh and Melesse 2017). The HCA can be obtained by employing the most widely used data clustering method and application of Ward's method of linkage (Bilgin and Konane 2016;Barzegar et al 2019;Liu et al 2021). Dendrogram is a pictorial representation of the CA result based on either the analyzed parameters or sampling locations.…”

Section: Statistical Analysesmentioning

confidence: 99%

Assessment of heavy metals contamination and associated risks in shallow groundwater sources from three different residential areas within Ibadan metropolis, southwest Nigeria

2021

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This study has been conducted to appraise the concentrations of selected heavy metals and total dissolved solids (TDSs) in the drinking water from shallow wells in parts of Ibadan metropolis, southwest Nigeria. Fifteen (15) water samples were collected from three representative residential locations [traditional core area (TCA), peri-urban area (PUA), and urban area (UA)] for geochemical analysis. Heavy metals and TDS were analyzed with the aid of atomic absorption spectrophotometer and calibrated meter, respectively. The mean concentration (mg/L) of Zn, Pb Mn, Fe, and Cd has been 3.930, 0.658, 0.0304, 1.698, and 0.501, respectively, and as a consequence, the order of abundance of studied metals was Zn > Fe > Pb > Cd > Mn. Concentrations of Zn, Fe, Pb, and Cd were higher than recommended standards in 60%, 86.7%, 100%, and 100% of groundwater samples, respectively. However, at all points tested, the mean concentrations of Mn and TDS in water samples lie within the safe limits set by World Health Organization. The evaluation of geoaccumulation index (Igeo), enrichment factor (EF), and contamination factor suggests that representative water samples were low-to-moderate contamination. The potential ecological risk index advocates low-to-moderate ecological risk in TCA and PUA, while it demonstrated exclusive “moderate” risk in UA. Further, the range of pollution load index (PLI) (0.55–1.32) in both TCA and PUA shows nil-to-moderate pollution status, while PLI values > 1 in UA indicate moderate contaminated state. The degree of contamination in groundwater showed the following trends: UA > TCA > PUA in the study area. Moreover, the results of EF and quantification of contamination of analyzed metals in water samples indicate geogenic and anthropogenic inputs. The contribution of studied metals to the incidence of non-cancer risk via oral intake within the residential sites follows the order: cadmium > lead > zinc > iron > manganese. The hazard index as a result of ingested heavy metals for the three population classes surpasses the acceptable range in the order of infant < child < adult. Cadmium and lead made considerable impact to the estimation of cancer risk in the study area for the three human population categories. Factor analysis extracted only one component that explained 94.64% of the entire variance, while cluster analysis identified three distinct groups based on similar water quality characteristics. Based on the findings of the study, awareness programs toward protecting the shallow groundwater sources should be launched, encouraged, and sustained. Moreover, the study suggests better hygienic practices and pre-treatment of contaminated water before consumption.

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Section: Statistical Analysesmentioning

confidence: 99%

Assessment of heavy metals contamination and associated risks in shallow groundwater sources from three different residential areas within Ibadan metropolis, southwest Nigeria

2021

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“…The combination of a WQI and MSTs may be useful for determining the water quality of rivers. MSTs such as cluster analysis (CA), stepwise discriminant analysis (DA), principal component analysis (PCA), factor analysis (FA), co-occurrence network analysis, and Mann-Kendall trend analysis are widely used for evaluating and interpreting both temporal and spatial variations in large and complex water quality datasets, as well as for source apportionment of pollution [1,3,6,8,9,[24][25][26][27][28]. Mann-Kendall trend analysis has been applied to observe longterm patterns of water quality parameters [29].…”

Section: Introductionmentioning

confidence: 99%

Application of Multivariate Statistical Techniques and Water Quality Index for the Assessment of Water Quality and Apportionment of Pollution Sources in the Yeongsan River, South Korea

Mamun

2021

IJERPH

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This study assessed spatial and temporal variations of water quality to identify and quantify possible pollution sources affecting the Yeongsan River using multivariate statistical techniques (MSTs) and water quality index (WQI) values. A 15 year dataset of 11 water quality variables was used, covering 16 monitoring sites. The nutrient regime, organic matter, suspended solids, ionic contents, algal growth, and total coliform bacteria (TCB) were affected by the summer monsoon and the construction of weirs. Regression analysis showed that the algal growth was more highly regulated by total phosphorus (TP; R2 = 0.37) than total nitrogen (TN, R2 = 0.25) and TN/TP (R2 = 0.01) ratios in the river after weir construction and indicated that the river is a P-limited system. After constructing the weirs, the mean TN/TP ratio in the river was about 40, meaning it is a P-limited system. Cluster analysis was used to classify the sampling sites into highly, moderately, and less polluted sites based on water quality features. Stepwise discriminant analysis showed that pH, dissolved oxygen (DO), TN, biological oxygen demand (BOD), chemical oxygen demand (COD), chlorophyll-a (CHL-a), and TCB are the spatially discriminating parameters, while pH, water temperature, DO, electrical conductivity, total suspended solids, and COD are the most significant for discriminating among the three seasons. The Pearson network analysis showed that nutrients flow with organic matter in the river, while CHL-a showed the highest correlation with COD (r = 0.85), followed by TP (r = 0.49) and TN (r = 0.49). Average WQI values ranged from 55 to 141, indicating poor to unsuitable water quality in the river. The Mann–Kendall test showed increasing trends in COD and CHL-a but decreasing trends for TP, TN, and BOD due to impoundment effects. The principal component analysis combined with factor analysis and positive matrix factorization (PMF) showed that two sewage treatment plants, agricultural activities, and livestock farming adversely impacted river water quality. The PMF model returned greater R2 values for BOD (0.92), COD (0.87), TP (0.93), TN (0.91), CHL-a (0.93), and TCB (0.83), indicating reliable apportionment results. Our results suggest that MSTs and WQI can be effectively used for the simple interpretation of large-scale datasets to determine pollution sources and their spatiotemporal variations. The outcomes of our study may aid policymakers in managing the Yeongsan River.

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“…There are many environmental studies in which multivariate statistical methods were used, for instance, physicochemical analysis of surface waters [34,37,39], waters in retention reservoirs [36], bottom sediments [48,49] and atmospheric air [31,50], as well as the assessment of the microbiological quality of air [3,33,38]. In our current study, the multivariate data analysis with the use of contingency tables showed a statistically significant relationship between the number of molds and yeast-like fungi in the coastal towns in 2014-2017 and 2018.…”

Section: Discussionmentioning

confidence: 99%

“…In our recent research, we searched for hidden relationships and regularities between meteorological factors and the number of mold and yeast-like fungi in the air of five coastal towns of the Gulf of Gda ńsk [33]. For this purpose, the Principal Component Analysis (PCA) model was applied, which is one of the numerous methods of factor analysis that has been used for many years in the analysis of environmental samples [34][35][36][37][38][39]. The PCA analysis showed a significant correlation between meteorological factors and the number of molds and yeast-like fungi in the air of five coastal towns in 2014-2017 and in 2018, which saw an emergency discharge of sewage into the Gulf of Gda ńsk [33].…”

Section: Introductionmentioning

confidence: 99%

Higher Number of Yeast-like Fungi in the Air in 2018 after an Emergency Discharge of Raw Sewage to the Gulf of Gdańsk—Use of Contingency Tables

et al. 2021

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This study aimed to investigate the differences between the number of yeast-like fungi and molds in the coastal air of five coastal towns of the Gulf of Gdańsk in 2014–2017 vs. 2018, which saw an emergency discharge of sewage. In 2014–2017, a total of 62 duplicate samples were collected in the coastal towns of Hel, Puck, Gdynia, Sopot, and Gdańsk-Brzeźno. In 2018, after the emergency disposal of raw sewage, 26 air samples were collected. A Pearson chi-squared test of independence showed that during 2018 in Hel and Sopot, the mean number of molds and yeast-like fungi was higher than in 2014–2017. The result was significantly positive, p ≤ 2.22 × 10−16. The analysis of the General Asymptotic Symmetry Test showed that in Puck and Gdańsk-Brzeźno, the average number of Aspergillus sp. mold fungi was higher in 2018 after an emergency discharge of sewage into the Gulf of Gdańsk compared to the period 2014–2017. The result was not statistically significant. In addition, the average number of Penicillium sp. molds in 2018 in Gdańsk-Brzeźno was higher than in 2014–2017, but statistically insignificant (p = 0.9593). In 2018, the average number of Cladosporium sp. molds in Sopot was higher, but also statistically insignificant (p = 0.2114) compared to 2014–2017. Our results indicate that the study of the number of yeast-like fungi in the air may indicate coastal areas that may be particularly at risk of bacterial or mycological pathogens, e.g., after an emergency discharge of raw sewage.

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Water quality assessment and source identification of the Shuangji River (China) using multivariate statistical methods

Cited by 36 publications

References 50 publications

Assessment of heavy metals contamination and associated risks in shallow groundwater sources from three different residential areas within Ibadan metropolis, southwest Nigeria

Assessment of heavy metals contamination and associated risks in shallow groundwater sources from three different residential areas within Ibadan metropolis, southwest Nigeria

Application of Multivariate Statistical Techniques and Water Quality Index for the Assessment of Water Quality and Apportionment of Pollution Sources in the Yeongsan River, South Korea

Higher Number of Yeast-like Fungi in the Air in 2018 after an Emergency Discharge of Raw Sewage to the Gulf of Gdańsk—Use of Contingency Tables

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