Akademik Veri Yönetim Sistemi
Water Resources and Industry, cilt.30, ss.1-26, 2023 (SCI-Expanded)
Struvite
(MAP, magnesium ammonium phosphate hexahydrate, MgNH4PO4.6H2O)
precipitation-aided Fenton’s OXidation (MAPFOX process) was explored in the treatment
of high-strength real sheep slaughterhouse wastewater (RSSW) for the first time
under a comprehensive soft-computing-based modeling study. The experimental results showed
that under the highest-efficiency conditions (chemical
combination of MgCl2.6H2O
+ NaH2PO4.2H2O, a molar ratio of Mg2+:NH4+-N:PO43--P
= 1.2:1:1, a reaction
pH of 9.0 ± 0.10, [NH4+-N]0 = 240 ± 20 mg/L, and a reaction time of 15 min), MAP precipitation could
effectively remove more than 80%, 60%, 55%, and 70% of color, total chemical oxygen demand (TCOD), soluble COD (SCOD), and
ammonium nitrogen (NH4+-N) from the raw RSSW. The results of the Fenton’s oxidation used as the
post-treatment unit of the proposed MAPFOX system indicated that the integrated
advanced oxidation process (AOP) was able to reduce the residual pollutant
levels in the MAP-pretreated RSSW to the relevant discharge standards. Under
the subsequent condition of [Fe2+]0 = 90 mmol/L, [H2O2]0
= 180 mmol/L, reaction pH = 3.25, and total reaction
time = 60 min, more than 97% of color, TCOD, SCOD, and NH4+-N could be removed from the RSSW via
the Fenton’s oxidation after the MAP-based physicochemical treatment. According to SEM micrographs,
surface morphology of dehydrated struvite exhibited irregular-shaped and overlapping
sharp-edged particles of various sizes with an average size of about 50.9 mm. The Fourier Transform Infrared (FTIR) spectroscopy confirmed
the active functional groups and type of bonds for the high-strength RSSW-oriented struvite (heated) within
the spectral range of 4000–450 cm−1. Thermogravimetric Analysis
(TGA), Derivative Thermogravimetry (DTG), Differential Thermal Analysis (DTA),
and Differential Scanning Calorimetry (DSC) of the dehydrated struvite revealed
that the weight loss occurred in three temperature zones, the maximum weight loss
rate of 0.252 mg/min was recorded at around 224 °C and at time of 20.83 min,
and the sample had strong endothermic and medium exothermic peaks at about 241
°C and 679°C, respectively. The predictive successes of the implemented
soft-computing approaches were benchmarked in terms of various statistical
goodness-of-fit parameters. The performance assessment indices corroborated the
superiority of the support vector machines-Pearson VII universal kernel
function (SVM-PUKF)-based model (correlation
coefficient (CC) = 0.9999–1.0000), mean absolute error (MAE) = 0.0222–0.0389%, mean
absolute percentage error (MAPE) = 0.0270–0.0506%, root mean squared error
(RMSE) = 0.0258–0.0415%, coefficient of variation of RMSE (CV(RMSE) =
0.0003–0.0008, Nash–Sutcliffe efficiency (NSE) = 0.9998–1.000, Legates and
McCabe’s index (LMI) = 0.9894–0.9952) over other
data-intelligent models in predicting the pollutant removal efficiencies. The
computational results also indicated that the narrowest uncertainty bands (±1.96Se
= 0.0537–0.1483%) and the lowest amounts of expanded uncertainty (U95
= 3.1224–5.3124%) values for all efficiency sets were achieved for the applied SVM-PUKF-based strategy. This study demonstrated the first-ever and
successful application of the proposed MAPFOX process in treatability of the
RSSW and capability of the implemented soft-computing strategy in modeling a
highly nonlinear treatment system.