2019
DOI: 10.3390/app9071398
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Analysis of Causal Relationships for Nutrient Removal of Activated Sludge Process Based on Structural Equation Modeling Approaches

Abstract: The removal process of activated sludge in sewage treatment plants is very nonlinear, and removal performance has a complex causal relationship depending on environmental factors, influent load, and operating factors. In this study, how causal relationships are expressed in collected data was identified by structural equation modeling. First, path modeling was attempted as a preliminary step in structural equation model (SEM) construction and, as a result, the nutrient-removal mechanism could not be sufficient… Show more

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Cited by 6 publications
(5 citation statements)
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References 46 publications
(59 reference statements)
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“…In addition, regarding the goodness of fit for this model construct, χ 2 /df = 1.54, GFI = 0.92, AGFI = 0.91, IFI = 0.97, TLI = 0.97, CFI = 0.97, and RMSEA = 0.035 were acquired. The fit scale showed a sufficient fit for this model as these indices were approaching the criterion of a good fit according to some researchers (Bentler and Bonett, 1980;Bollen, 1989;West et al, 2012;Cangur and Ercan, 2015;Kline, 2015;Kim et al, 2019).…”
Section: The Measurement Modelmentioning
confidence: 57%
“…In addition, regarding the goodness of fit for this model construct, χ 2 /df = 1.54, GFI = 0.92, AGFI = 0.91, IFI = 0.97, TLI = 0.97, CFI = 0.97, and RMSEA = 0.035 were acquired. The fit scale showed a sufficient fit for this model as these indices were approaching the criterion of a good fit according to some researchers (Bentler and Bonett, 1980;Bollen, 1989;West et al, 2012;Cangur and Ercan, 2015;Kline, 2015;Kim et al, 2019).…”
Section: The Measurement Modelmentioning
confidence: 57%
“…-The first treatment line, also known as the water line, includes the treatment of water discharges for pollutant removal [13].…”
Section: Wastewater Treatment Plantsmentioning
confidence: 99%
“…There are several goodness-of-fit indices that can be used to assess the fitness of a model. In this study we use the most common indices, such has the root mean square error of approximation (RMSEA) [40][41][42], the goodness-of-fit index (GFI) [43,44], the adjusted goodness of fit index (AGFI) [45,46], the comparative fit index (CFI) [47,48] and the standardized root mean square residual (SRMR) [49,50].…”
Section: Fitness Of Modelsmentioning
confidence: 99%
“…A RMSEA value of less than 0.05 is considered good, while values between 0.05 and 0.08 are acceptable, and values between 0.08 and 0.1 are marginal [40][41][42]. For the GFI, AGFI, and CFI indices, values above 0.8 are considered good, while for the SRMR index, a value less than 0.08 is desirable [43][44][45][46][47][48][49][50].…”
Section: Fitness Of Modelsmentioning
confidence: 99%