Estimating the biodegradability of treated sewage samples using synchronous fluorescence spectra

Fate of Dissolved Nitrogen in a Horizontal Levee: Seasonal Fluctuations in Nitrate Removal Processes

Horizontal levees are a nature-based approach for removing nitrogen from municipal wastewater effluent while simultaneously providing additional benefits, such as flood control. To assess nitrogen removal mechanisms and the efficacy of a horizontal levee, we monitored an experimental system receiving nitrified municipal wastewater effluent for 2 years. Based on mass balances and microbial gene abundance data, we determined that much of the applied nitrogen was most likely removed by heterotrophic denitrifiers that consumed labile organic carbon from decaying plants and added wood chips. Fe(III) and sulfate reduction driven by decay of labile organic carbon also produced Fe(II) sulfide minerals. During winter months, when heterotrophic activity was lower, strong correlations between sulfate release and nitrogen removal suggested that autotrophic denitrifiers oxidized Fe(II) sulfides using nitrate as an electron acceptor. These trends were seasonal, with Fe(II) sulfide minerals formed during summer fueling denitrification during the subsequent winter. Overall, around 30% of gaseous nitrogen losses in the winter were attributable to autotrophic denitrifiers. To predict long-term nitrogen removal, we developed an electron-transfer model that accounted for the production and consumption of electron donors. The model indicated that the labile organic carbon released from wood chips may be capable of supporting nitrogen removal from wastewater effluent for several decades with sulfide minerals, decaying vegetation, and root exudates likely sustaining nitrogen removal over a longer timescale.

Longitudinal Chemical Gradients and the Functional Responses of Nutrients, Organic Matter, and Other Parameters to the Land Use Pattern and Monsoon Intensity

River water quality degradation is one of the hottest environmental issues worldwide. Therefore, monitoring water quality longitudinally and temporally is crucial for effective water management and contamination control. The main aim of this study was to assess the longitudinal variations in water quality in the mainstream of the Han River, Korea, from 2015 to 2019. The trophic state classification (TSC), microbial pollution indicator (MPI), and river pollution index (RPI) were calculated to characterize river water quality and revealed more serious pollution toward the downstream zone (Dz) due to agricultural and urban-dominated areas. The biodegradability index (BI) indicated that non-biodegradable organic pollutants are increasing in the water body from the urban and animal wastewater treatment plants. Nutrients, organic matter contents, total suspended solids, ionic factors, and algal chlorophyll were higher in the Dz than in any other zones and were markedly influenced by the summer monsoon. Empirical analysis showed that nutrients and organic matter had positive linear functional relations with agricultural and urban coverage and negative linear relations with forest coverage. The pollutant-transport function suggested that suspended solids act as TP and TN carriers. Regression analysis indicated that TP (R2 = 0.47) has more positive functional relations with algal growth than TN (R2 = 0.22). Our findings suggest that a combination of empirical models and pollution indices might be utilized to assess river water quality and that the resulting information could aid policymakers in managing the Han River.

Photodegradation-induced biological degradation of treated wastewater effluent organic matter in receiving waters

Effluent organic matter (EfOM) from wastewater treatment plants (WWTP) constitutes an important source of dissolved organic matter in receiving waters. Photodegradation may alter the properties of WWTP EfOM, thereby impacting its biodegradability and microbial respiration. However, whether and how natural sunlight exposure of EfOM affects its biodegradability and microbial oxygen consumption in the receiving waters are unclear. To address these knowledge gaps, incubation experiments of biodegradation, photodegradation, and bio-photodegradation were conducted with the effluent samples from a tertiary WWTP in Heifei, China. The quantity and quality of the EfOM were examined during the incubations to interpret changes in its lability and composition. The results showed that photodegradation facilitated and accelerated the EfOM biodegradation. After natural sunlight exposure, the EfOM degradation rate was significantly enhanced from 0.004 d^-1 to 0.065 d^-1 measured by dissolved organic carbon (DOC). Correspondingly, the DOC concentration of EfOM was reduced by 64.2% (26.6% by photodegradation and 37.5% by bio-photodegradation), while the concentration was only reduced by 5.3% in the direct biodegradation. Sunlight exposure of EfOM resulted in lower molecular weight, less aromatic, lower humified, more bleached photoproducts. These substances could be readily metabolized by the native microbial community in the receiving water, stimulating microbial respiration. Correspondingly, the oxygen consumption rate of EfOM increased from almost 0.11 mg L^-1 d^-1 in the direct biodegradation to 2.17 mg L^-1 d^-1 in the bio-photodegradation. This study highlights that after EfOM is discharged to the receiving water, its post-processing by sunlight can enhance biodegradability. The existence of the coupled photochemical and biological process is suggested to be considered when determining EfOM fate and managing effluent discharge in receiving waters.

Statistical correlation of ecotoxicity and water quality parameters in slaughterhouse wastewater

The major causes of toxicity in slaughterhouse wastewater are identified by analyzing the relationship between representative pollutants and the acute toxicity of Daphnia magna. Experimental results demonstrate that organic matters are strongly associated with the acute toxicity. Among many organic pollutants, proteins and carbohydrates were found to be the main toxicity inducers that cause metabolic transformation of D. magna. Statistical correlation between biodegradable soluble organics and the acute toxicity further explains how principal pollutants play potential toxin roles. Also, this study verifies that the variations of biochemical oxygen demand over total chemical oxygen demand (BOD TCOD^-1) as well as total organic carbon over total carbon (TOC TC^-1) can be indirect indicators explaining the acute toxicity of D. magna because the removal of non-degradable and non-soluble organic matters is connected to the toxicity removal. Overall, these results provide how the acute toxicity of D. magna is attributed to pollutants and what is the potential source of threats to society in slaughterhouse wastewater.

Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer's kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer's kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem.

Effects of ozonation pretreatment on natural organic matter and wastewater derived organic matter - Possible implications on the formation of ozonation by-products

The aim of this study was to investigate possible implications of natural and wastewater derived organic matter in river water that is subsequently used following treatment for drinking purposes. River water was subjected to lab-scale ozonation experiments under different ozone doses (0.1, 0.4, 0.8, 1.0 and 2.0 mgO₃/mgC) and contact times (1, 3, 5, 8 and 10 min). Mixtures of river water with humic acids or wastewaters (sewage wastewater and secondary effluents) at different proportions were also ozonated. Dissolved organic carbon and biodegradable dissolved organic carbon concentrations as well as spectroscopic characteristics (UV absorbance and fluorescence intensities) of different types of dissolved organic matter and possible changes due to the ozonation treatment are presented. River water, humic substances and wastewater exhibited distinct spectroscopic characteristics that could serve for pollution source tracing. Wastewater impacted surface water results in higher formation of carbonyl compounds. However, the formation yield (μg/mgC) of wastewaters was lower than that of surface water possibly due to different composition of wastewater derived organic matter and the presence of scavengers, which may limit the oxidative efficiency of ozone.

A Comparative Study of the Application of Fluorescence Excitation-Emission Matrices Combined with Parallel Factor Analysis and Nonnegative Matrix Factorization in the Analysis of Zn Complexation by Humic Acids

The main aim of this study was the application of excitation-emission fluorescence matrices (EEMs) combined with two decomposition methods: parallel factor analysis (PARAFAC) and nonnegative matrix factorization (NMF) to study the interaction mechanisms between humic acids (HAs) and Zn(II) over a wide concentration range (0–50 mg·dm⁻³). The influence of HA properties on Zn(II) complexation was also investigated. Stability constants, quenching degree and complexation capacity were estimated for binding sites found in raw EEM, EEM-PARAFAC and EEM-NMF data using mathematical models. A combination of EEM fluorescence analysis with one of the proposed decomposition methods enabled separation of overlapping binding sites and yielded more accurate calculations of the binding parameters. PARAFAC and NMF processing allowed finding binding sites invisible in a few raw EEM datasets as well as finding totally new maxima attributed to structures of the lowest humification. Decomposed data showed an increase in Zn complexation with an increase in humification, aromaticity and molecular weight of HAs. EEM-PARAFAC analysis also revealed that the most stable compounds were formed by structures containing the highest amounts of nitrogen. The content of oxygen-functional groups did not influence the binding parameters, mainly due to fact of higher competition of metal cation with protons. EEM spectra coupled with NMF and especially PARAFAC processing gave more adequate assessments of interactions as compared to raw EEM data and should be especially recommended for modeling of complexation processes where the fluorescence intensities (FI) changes are weak or where the processes are interfered with by the presence of other fluorophores.

Assessing trihalomethanes (THMs) and N-nitrosodimethylamine (NDMA) formation potentials in drinking water treatment plants using fluorescence spectroscopy and parallel factor analysis

The formation of disinfection byproducts (DBPs) is a major challenge in drinking water treatments. This study explored the applicability of fluorescence excitation-emission matrices and parallel factor analysis (EEM-PARAFAC) for assessing the formation potentials (FPs) of trihalomethanes (THMs) and N-nitrosodimethylamine (NDMA), and the treatability of THM and NDMA precursors in nine drinking water treatment plants. Two humic-like and one tryptophan-like components were identified for the samples using PARAFAC. The total THM FP (TTHM FP) correlated strongly with humic-like component C2 (r=0.874), while NDMA FP showed a moderate and significant correlation with the tryptophan-like component C3 (r=0.628). The reduction by conventional treatment was more effective for C2 than C3, and for TTHM FP than NDMA FP. The treatability of DOM and TTHM FP correlated negatively with the absorption spectral slope (S275-295) and biological index (BIX) of the raw water, but it correlated positively with humification index (HIX). Our results demonstrated that PARAFAC components were valuable for assessing DBPs FP in drinking water treatments, and also that the raw water quality could affect the treatment efficiency.

Methods for assessing biochemical oxygen demand (BOD): a review

The Biochemical Oxygen Demand (BOD) is one of the most widely used criteria for water quality assessment. It provides information about the ready biodegradable fraction of the organic load in water. However, this analytical method is time-consuming (generally 5 days, BOD5), and the results may vary according to the laboratory (20%), primarily due to fluctuations in the microbial diversity of the inoculum used. Work performed during the two last decades has resulted in several technologies that are less time-consuming and more reliable. This review is devoted to the analysis of the technical features of the principal methods described in the literature in order to compare their performances (measuring window, reliability, robustness) and to identify the pros and the cons of each method.

Estimating the concentration and biodegradability of organic matter in 22 wastewater treatment plants using fluorescence excitation emission matrices and parallel factor analysis

This study aimed at monitoring the changes of fluorescent components in wastewater samples from 22 Korean biological wastewater treatment plants and exploring their prediction capabilities for total organic carbon (TOC), dissolved organic carbon (DOC), biochemical oxygen demand (BOD), chemical oxygen demand (COD), and the biodegradability of the wastewater using an optical sensing technique based on fluorescence excitation emission matrices and parallel factor analysis (EEM-PARAFAC). Three fluorescent components were identified from the samples by using EEM-PARAFAC, including protein-like (C1), fulvic-like (C2) and humic-like (C3) components. C1 showed the highest removal efficiencies for all the treatment types investigated here (69% ± 26%-81% ± 8%), followed by C2 (37% ± 27%-65% ± 35%), while humic-like component (i.e., C3) tended to be accumulated during the biological treatment processes. The percentage of C1 in total fluorescence (%C1) decreased from 54% ± 8% in the influents to 28% ± 8% in the effluents, while those of C2 and C3 (%C2 and %C3) increased from 43% ± 6% to 62% ± 9% and from 3% ± 7% to 10% ± 8%, respectively. The concentrations of TOC, DOC, BOD, and COD were the most correlated with the fluorescence intensity (Fmax) of C1 (r = 0.790-0.817), as compared with the other two fluorescent components. The prediction capability of C1 for TOC, BOD, and COD were improved by using multiple regression based on Fmax of C1 and suspended solids (SS) (r = 0.856-0.865), both of which can be easily monitored in situ. The biodegradability of organic matter in BOD/COD were significantly correlated with each PARAFAC component and their combinations (r = -0.598-0.613, p < 0.001), with the highest correlation coefficient shown for %C1. The estimation capability was further enhanced by using multiple regressions based on %C1, %C2 and C3/C2 (r = -0.691).