Evaluating Spatial and Temporal Variation
in Tuzaklı Pond Water Using Multivariate
Statistical Analysis

Uncumusaoğlu, Arzu Aydın; Mutlu, Ekrem

doi:10.15244/pjoes/99103

Cited by 27 publications

(17 citation statements)

References 28 publications

(27 reference statements)

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“…Statistical evaluation methods were applied on the complex database from the intense monitoring campaigns, comprising of the principal component analysis (PCA) and cluster analysis (CA), methods that are known to facilitate the evaluation of large number of data, generating useful and reliable information on the state of water quality. PCA provides information on the most significant parameters based on commonalities of spatial and temporal variations that describe the whole data set by excluding the less significant parameters with a minimum loss of original variability [21,22]. Figure 1 represents the loading plot of the first two principal components and it can be seen that most metals are comprised in the first component.…”

Section: Resultsmentioning

confidence: 99%

Assessment of contamination with hazardous substances in surface sediments in the Lower Danube River

Ionescu¹,

Ivanov²,

Deák³

et al. 2019

Technium

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River ecosystems are exposed to various stressors, surface sediments as a constitutive part thereof are an essential feature for the evaluation of aquatic ecosystems status. This paper aims to assess the surface sediment quality in the lower section of the Danube River, in terms of hazardous substances content (As, Cd, Cr, Cu, Pb, Hg, Zn, Ni, PAH and PCB). For this purpose, 10 monitoring sites have been assigned for a period of September 2011-August 2017, where construction works were carried out with the purpose of improving the navigation conditions, which also involved sediment dredging. A total approximately of 1200 surface sediment samples have been collected from the Danube River (km 375-km 175), from the left and right banks, monthly during the construction period (2011-2015) and quarterly in the post-construction period (2015-2017). This study gives a description and more detailed evaluation of the integrated assessment of hazardous substances which was carried out in the surface sediments from the Lower Danube River using statistical analysis. The surface sediment quality evaluation was based on comparison of the obtained values with the chemical quality standards set out in the Romanian legislation (M.O. 161/2006). For a more in-depth assessment of the relationship between hazardous substances and for the identification of potential anthropogenic and natural sources, Principal Component Analysis (PCA) and Cluster Analysis (CA) have been used.

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Section: Resultsmentioning

confidence: 99%

Assessment of contamination with hazardous substances in surface sediments in the Lower Danube River

Ionescu¹,

Ivanov²,

Deák³

et al. 2019

Technium

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“…A KMO value close to unity would generally mean the correlations are compacted and hence the sampling and the samples are highly suitable for FA whereas smaller values would generally mean that the variables in consideration have very little in common [24]. Though KMO greater than 0.5 is considered adequate [27,28], higher values are often recommended. On the other hand, CA was used to group all the monitoring station according to their spatial similarity were Hierarchical Cluster Analysis (HCA) was used to classify the monitoring stations based on the similarity between constituents through Ward's method.…”

Section: Discussionmentioning

confidence: 99%

Spatio-Temporal Evaluation and Quantification of Pollutant Source Contribution in Little Akaki River, Ethiopia: Conjunctive Application of Factor Analysis and Multivariate Receptor Model

Angello¹,

Tränckner²,

Behailu³

2020

Pol. J. Environ. Stud.

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Little Akaki River (LAR) is among the heavily polluted urban rivers in Ethiopia. A bimonthly physico-chemical and heavy metals water quality analysis was conducted aimed at assessing the spatio-temporal characteristics and quantifying sources contributing to the pollution during dry and wet season at 22 montoring stations. Accordingly, laboratory analysis results indicated that most of the constituents deviated from the national and international guideline limits and the river is critically polluted at the middle and downstream segment. Factor Analysis (FA) was used to qualitatively determine the possible sources contributing to the pollution of LAR where three factors are identified that determine the pollution level during wet and dry season explaining 79.26 % and 79.47 % of the total variance respectively. Agricultural and urban runoff (nonpoint pollution sources), industrial and domestic waste are the three dominant factors that contribute to pollution in LAR. On the other hand, pollution sources of heavy metals in LAR are mostly dominated by industrial release whereas urban washouts from garages and automobile oil spills are other possible sources. Cluster Analysis spatially grouped all 22 monitoring stations into four and three clusters during the dry and wet season respectively. USEPA's receptor model, UNMIX, was used to quantify the composition and contribution of LAR constituents. The model predicted quite well with a minimum Signal to Noise ratio (S/N) of 2.71 and 2.16>2 and R 2 of 0.91 and 0.88>0.8 for the dry and wet season respectively. The UNMIX model effectively predicted the water quality source composition with a model predicted to measured ratio (P:M) of 1.04 and 1.16 during the dry season and wet season with an average percentage error of 1.38 % and 17.13 % respectively. LAR water quality management approach incorporating all the three pollution sources could be feasible.

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“…PCA provides information on the most significant parameters [59]. Figure 3a shows which PCA is done to combine measured variables in three components, PC1, PC2, and PC3.…”

Section: Factor Principal Components and Cluster Analysismentioning

confidence: 99%

Evaluation of Sources and Ecological Risk of PAHs in Different Layers of Soil and Groundwater

Ilić¹,

Markić²,

Bjelić³

2020

Preprint

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Research subjects of this study are four representative locations in the industrial complex, in the city of Banja Luka, Republic of Srpska, Bosnia and Herzegovina. 16 polycyclic aromatic hydrocarbons (PAHs) (∑16PAHs), humus and pH were determined. The main objective of the paper is to determine the concentration levels, to assess the probable sources of PAHs contamination in soil and groundwater and to determine the ecological risk. The ∑16PAHs in soil (at depths of 30 cm, 100 cm, 200 cm, 300 cm and 400 cm) ranged from 0.99 to 2.24 mg/kg, from 0.34 to 0.46, from 0.24 to 0.32, from 0.13 to 0.27 and from 0.13 to 0.47, with mean values of 1.70 mg/kg, 0.40 mg/kg, 0.28 mg/kg, 0.20 mg/kg and 0.26 mg/kg, respectively. The ∑16PAHs in groundwater ranged from 0.23 to 4.50 mg/m3, with a mean value of 1.42 mg/m3. Surface soil and groundwater are heavily contaminated. All values of ∑PAHs in soil layers were lower in the depths of the soil. Factor analysis indicates three sources of contamination, i.e. principal component (PC) PC1 (pyrogenic), PC2 (petrogenic) and PC3 (biomass), with 52.39%, 26.14% and 8.46% of the total variance, respectively. ∑PAH and PAHs indicate high ecological risk for most PAHs, which decreases with soil depth.

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Evaluating Spatial and Temporal Variation in Tuzaklı Pond Water Using Multivariate Statistical Analysis

Cited by 27 publications

References 28 publications

Assessment of contamination with hazardous substances in surface sediments in the Lower Danube River

Assessment of contamination with hazardous substances in surface sediments in the Lower Danube River

Spatio-Temporal Evaluation and Quantification of Pollutant Source Contribution in Little Akaki River, Ethiopia: Conjunctive Application of Factor Analysis and Multivariate Receptor Model

Evaluation of Sources and Ecological Risk of PAHs in Different Layers of Soil and Groundwater

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