Water quality assessment and apportionment of pollution sources using APCS-MLR and PMF receptor modeling techniques in three major rivers of South Florida

Gholizadeh, Mohammad Haji; Melesse, Assefa M.; Reddi, Lakshmi N.

doi:10.1016/j.scitotenv.2016.06.046

Cited by 243 publications

(122 citation statements)

References 57 publications

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“…It is not appropriate to apply factor analysis when the correlations among the variables are near zero or very weak, because it is not possible to summarize the information. The KMO value ranges from 0 to 1, with values above 0.6 indicating that the variables and samples evaluated are suitable for factor analysis (Gumbo et al 2016;Gholizadeh et al 2016;Mao et al 2013).…”

Section: Discussionmentioning

confidence: 99%

“…These results indicated the importance of ecosystem services provided by grasslands and urban green spaces in contributing to better water quality (Martinico et al 2014), because the Recanto microbasin has a lower degree of urbanization (21%), compared to the Santa Angélica (47%) and Pylles (81%) areas, leading to a lower specific TDS load. Other studies have also described the influence of urbanization and industrialization on the degradation of water resources in catchments of developed and developing countries including Brazil (Medeiros et al 2013;Daniel et al 2002;Silva et al 2013), Colombia (Sandoval et al 2014), the USA (O 'Neill et al 2013;Gholizadeh et al 2016), South Africa (Gumbo et al 2016), Portugal (Gomes et al 2014), India (Jabeen et al 2014;Jamwal et al 2008), Australia (Hatt et al 2004), Turkey (Bilgin 2015), Sweden (Galfi et al 2016;Berndtsson and Bengtsson 2006) and Finland (Metsäranta et al 2005). …”

Section: Pollutant Loads Transported By Urban Streamsmentioning

confidence: 99%

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Water quality, pollutant loads, and multivariate analysis of the effects of sewage discharges into urban streams of Southeast Brazil

Medeiros

Tresmondi

Queiroz

et al. 2017

Energ. Ecol. Environ.

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Water demand, pollution, and climate change threaten water security in industrialized and urbanized regions worldwide, especially in developing countries. Investments in massive infrastructure have often not met the water needs of the population, requiring water resource managers to adopt new approaches, such as decentralized and regionalized management at the micro-basin scale. However, little is known about the impact of anthropogenic activities on the water quality and vulnerability of streams that cross urban areas and feed into the main rivers and reservoirs supplying cities and industrial regions. The main goals of this research were to evaluate the water quality, pollutant loads, and effect of untreated sewage discharges in streams of the Piracicaba river basin, in the municipality of Americana, Southeast Brazil. The water quality parameters evaluated were as follows: pH, dissolved oxygen, electrical conductivity, biochemical oxygen demand, inorganic phosphorus, total phosphorus, total nitrogen, real colour, turbidity, total dissolved solids, metals (Ba, Cr, Cu, Ni, Pb, Cd, and Zn), total coliforms, and Escherichia coli. Descriptive statistics and multivariate analyses were performed. The results revealed chemical and biological degradation of the water resources, and vulnerability of the urban streams due to the release of untreated sewage into these waterways. The findings indicate the need for an immediate implementation of policies to monitor and control discharges of industrial effluents into the sewage collection systems, as well as discharges of sewage into rainwater drainage systems, together with the maintenance of green spaces.

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Section: Discussionmentioning

confidence: 99%

Section: Pollutant Loads Transported By Urban Streamsmentioning

confidence: 99%

Water quality, pollutant loads, and multivariate analysis of the effects of sewage discharges into urban streams of Southeast Brazil

Medeiros

Tresmondi

Queiroz

et al. 2017

Energ. Ecol. Environ.

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“…Thurston et al (1985) first proposed that, after the normalization of original data, the absolute real score of a factor could be obtained using factor analysis [73], and then combined with a multivariate linear regression model to calculate a common factor contribution rate on water targets. PC S -SMLR can quantitatively depict the main factor's contribution to the receptor of each index, such as the air and water pollution source analysis used in studies [54,74]. This methodology has rarely been used in the soil environment.…”

Section: Receptor Prediction Modelmentioning

confidence: 99%

Bioconcentration, Potential Health Risks, and a Receptor Prediction Model of Metal(loid)s in a Particular Agro-Ecological Area

Cai

Song

2019

Applied Sciences

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To investigate the bioconcentration and potential health risks of metal(loid)s in a particular agro-ecological area, 230 pairs of soil and corresponding crop grain samples were collected from typical corn and wheat plants. The geo-accumulation index (Igeo), bioconcentration factors (BCF), health risk assessment (the target hazard quotient), and Receptor Prediction Model (PCS-SMLR) analysis were adopted to study the spatial distribution, assess the health risks, and predict the relationship between metal(loid)s and soil properties. It was found that the mean concentrations of Cu, Zn, Pb, Hg, and Cd in the study area’s agricultural soils exceeded the background soil concentrations, especially for Cd (0.2 mg/kg), Meanwhile, the corresponding Cd concentration in wheat samples was higher than the food quality limit. The results of the Igeo showed that the samples with a value higher than 0 for Cd and Hg accounted for 47.83% and 33.48%, respectively. The results of BCF of Cu, Zn, Cd, and As were higher in wheat than in corn, except for Ni. The target hazard quotient (TTHQ) of health risk of wheat, corn, and soil were higher for children (2.48) than adults (1.78), showing a potential health risk for individuals who mostly consume wheat. In addition, the PCS-SMLR analysis of the BCF prediction model for Cu, Zn, As, and soil properties showed differences in terms of the influences from wheat and corn. These results provide valuable information that not only can help local residents improve the staple food structure, but also can get provide a reference metal(loid)s concentration level for agricultural soils in the study area and restore a sustainable agro-ecological environment.

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“…However, such monitoring systems generate voluminous databases and their analysis requires robust analytical tools [8]. In recent years, multivariate statistical techniques (such as principal component analysis (PCA), factor analysis (FA) and absolute principal component score-multiple linear regression (APCS-MLR)) have been widely used in the water environment to evaluate both temporal and spatial variations of water quality [8][9][10], to provide qualitative information about potential pollution sources [6,[11][12][13][14][15], and to estimate source distributions for each pollution variable [4,11].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Variation of Groundwater Quality and Source Apportionment Using Multivariate Statistical Techniques for the Hutuo River Alluvial-Pluvial Fan, China

Zhang

Wang

et al. 2020

IJERPH

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Groundwater quality deterioration has become an environmental problem of widespread concern. In this study, we used a water quality index (WQI) and multivariate statistical techniques to assess groundwater quality and to trace pollution sources in the Hutuo River alluvial-pluvial fan, China. Measurement data of 17 variables in 27 monitoring sites from three field surveys were obtained and pretreated. Results showed that there were 53.09% of NO3−, 18.52% of SO42− and 83.95% of total hardness (TH) in samples that exceeded the Grade III standard for groundwater quality in China (GB/T 14848-2017). Based on WQI results, sampling sites were divided into three types: high-polluted sites, medium-polluted sites and low-polluted sites. The spatial variation in groundwater quality revealed that concentrations of total dissolved solids (TDS), Cl−, TH and NO3− were the highest in high-polluted sites, followed by medium-polluted and low-polluted sites. The temporal variation in groundwater quality was controlled by the dilution of rainwater. A principal component analysis (PCA) revealed that the primary pollution sources of groundwater were domestic sewage, industrial sewage and water–rock interactions in the dry season. However, in the rainy and transition seasons, the main pollution sources shifted to domestic sewage and water–rock interactions, nonpoint pollution and industrial sewage. According to the absolute principal component scores-multivariate linear regression (APCS-MLR), most water quality parameters were primarily influenced by domestic sewage. Therefore, in order to prevent the continuous deterioration of groundwater quality, the discharge of domestic sewage in the Hutuo River alluvial-pluvial fan region should be controlled.

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Water quality assessment and apportionment of pollution sources using APCS-MLR and PMF receptor modeling techniques in three major rivers of South Florida

Cited by 243 publications

References 57 publications

Water quality, pollutant loads, and multivariate analysis of the effects of sewage discharges into urban streams of Southeast Brazil

Water quality, pollutant loads, and multivariate analysis of the effects of sewage discharges into urban streams of Southeast Brazil

Bioconcentration, Potential Health Risks, and a Receptor Prediction Model of Metal(loid)s in a Particular Agro-Ecological Area

Spatio-Temporal Variation of Groundwater Quality and Source Apportionment Using Multivariate Statistical Techniques for the Hutuo River Alluvial-Pluvial Fan, China

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