Transformation and utilization of slowly biodegradable organic matters in biological sewage treatment of anaerobic anoxic oxic systems

Zhang, Q.H.; Jin, Pengkang; Ngo, Huu‐Hao; Shi, Xuan; Guo, Wenshan; Yang, Shuming; Wang, X.C.; Wang, X.; Dzakpasu, Mawuli; Yang, Wenjing; Liu, Yang

doi:10.1016/j.biortech.2016.06.068

Cited by 31 publications

(4 citation statements)

References 30 publications

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“…Moreover, the intensities of fulvic-like and humic-like fluorescence was even increased after the bio-treatment [54].…”

Section: Scod Removal Performancementioning

confidence: 97%

“…The aerobic degradation capacity of the SCOD of microbial communities in different biological treatment processes varies with the composition of DOM. Generally, according to EEM spectra analysis, the protein-like fractions were easily degraded during biological treatment, but fulvic-like and humic-like factions were more biologically recalcitrant [52,53,54]. Moreover, the intensities of fulvic-like and humic-like fluorescence was even increased after the bio-treatment [54].…”

Section: Scod Removal Performancementioning

confidence: 99%

“…Generally, according to EEM spectra analysis, the protein-like fractions were easily degraded during biological treatment, but fulvic-like and humic-like factions were more biologically recalcitrant [52,53,54]. Moreover, the intensities of fulvic-like and humic-like fluorescence was even increased after the bio-treatment [54].…”

Section: Scod Removal Performancementioning

confidence: 99%

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Insightful Analysis and Prediction of SCOD Component Variation in Low-Carbon/Nitrogen-Ratio Domestic Wastewater via Machine Learning

Zhang,

Guo,

Luo

et al. 2024

Water

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The rapid identification of the amount and characteristics of chemical oxygen demand (COD) in influent water is critical to the operation of wastewater treatment plants (WWTPs), especially for WWTPs in the face of influent water with a low carbon/nitrogen (C/N) ratio. Given that, this study carried out batch kinetic experiments for soluble chemical oxygen demand (SCOD) and nitrogen degradation for three WWTPs and established machine learning (ML) models for the accurate prediction of the variation in SCOD. The results indicate that four different kinds of components were identified via parallel factor (PARAFAC) analysis. C1 (Ex/Em = 235 nm and 275/348 nm, tryptophan-like substances/soluble microbial by-products) contributes to the majority of internal carbon sources for endogenous denitrification, whereas C4 (230 nm and 275/350 nm, tyrosine-like substances) is crucial for readily biodegradable SCOD composition according to the machine learning (ML) models. Furthermore, the gradient boosting decision tree (GBDT) algorithm achieved higher interpretability and generalizability in describing the relationship between SCOD and carbon source components, with an R2 reaching 0.772. A Shapley additive explanations (SHAP) analysis of GBDT models further validated the above result. Undoubtedly, this study provided novel insights into utilizing ML models to predict SCOD through the measurements of the excitation–emission matrix (EEM) in specific Ex and Em positions. The results could help us to identify the degradation and transformation relationship between different kinds of carbon sources and nitrogen species in the wastewater treatment process, and thus provide a novel guidance for the optimized operation of WWTPs.

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“…Moreover, the intensities of fulvic-like and humic-like fluorescence was even increased after the bio-treatment [54].…”

Section: Scod Removal Performancementioning

confidence: 97%

Section: Scod Removal Performancementioning

confidence: 99%

See 1 more Smart Citation

Insightful Analysis and Prediction of SCOD Component Variation in Low-Carbon/Nitrogen-Ratio Domestic Wastewater via Machine Learning

Zhang,

Guo,

Luo

et al. 2024

Water

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“…The primary clarifier has been generally removed in most Chinese WWTPs in order to direct more particulate organics into the nutrient removal process. However, the actual utilization of the carbon sources has recently been questioned due to its limited hydrolysis rate [15,16] and a series of problems, including equipment wear, reduced working volume, and lower sludge activity [17]. It is in this light remarkable to recover the particulate organics at the up-stage of the biological process.…”

Section: Introductionmentioning

confidence: 99%

Intensification of Short Chain Fatty Acid Production during the Alkaline Pretreatment of Fine-Sieving Fractions

et al. 2020

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Maximizing the internal carbon sources in raw wastewater was found to be an alternative option to alleviate the financial burden in external carbon sources (ECS) addition to the biological nutrient removal (BNR) process. Based on previous studies on particulate recovery via fine-sieving technologies, alkali pretreatment was used to improve the short-chain fatty acid (SCFA) production from the fine-sieving fractions (FSF). Hydrolysis performance and methane production were monitored to evaluate the reasons for the SCFA boost. Besides, the microbial community structure was evaluated by high-throughput sequencing. Furthermore, mass balance and financial benefits were preliminarily estimated. The results showed that alkali pretreatment effectively promoted the generation of SCFAs with 234 mg/g volatile suspended solids (VSS), almost double that of the control test. This was partially attributed to the efficient hydrolysis, with soluble polysaccharides and protein increased by 2.1 and 1.2 times compared to that of the control, respectively. Inhibition of methanogens was also devoted to the accumulation of SCFAs, with no methane production until 150 h at high pH value. Finally, a preliminary evaluation revealed that 44.51 kg/d SCFAs could be supplied as the electron donor for denitrification, significantly reducing the cost in ECS addition for most wastewater treatment plants (WWTPs) with carbon insufficiency.

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Potential of industrial by-products and wastes from the Iberian Peninsula as carbon sources for sulphate-reducing bacteria

Carlier

Alexandre

Luís

et al. 2019

Int. J. Environ. Sci. Technol.

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Industrial by-products and wastes from Portugal and Spain were tested for the first time as carbon sources/electron donors for sulphate reducing bacteria. Cultures in mineral medium supplemented with the tested substrates were monitored and sulphate reduction efficiency is discussed in light of substrates compositions, dosages and corresponding chemical oxygen demand/[SO4 2-] ratios. The use of doses targeting a ratio of 1.5 was a good strategy to optimize sulphate reduction activity. As expected, this activity was faster for substrates that have in their composition simple compounds such as low chain alcohols and organic acids and/or compounds that can be rapidly degraded such as sugars, though it also occurred in a longer-term perspective with substrates composed mainly of slowly degradable compounds such as cellulose and lignin. Among eighteen tested substrates, six supported high sulphate reduction efficiency during incubation periods varying between two and four weeks (sugared water from a factory of candies, beetroot molasses, olive mill wastewaters not decanted and decanted, orange molasses without conservative and municipal wastewater from Mina de São Domingos, Portugal), while eight substrates sustained moderate sulphate reduction efficiency during periods from three to seven weeks (water from washing beetroots, Carbocal®, orange molasses with conservative, liquor extracted from orange peels, orange peel fragments, water from washing industrial equipments used to produce orange juice, pine nut shells and pine cone fragments). Nevertheless, after four months of incubation, total sulphate removal was observed with three of the solid substrates tested (orange peels, pine nut shells and pine nut cones).

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Transformation and utilization of slowly biodegradable organic matters in biological sewage treatment of anaerobic anoxic oxic systems

Cited by 31 publications

References 30 publications

Insightful Analysis and Prediction of SCOD Component Variation in Low-Carbon/Nitrogen-Ratio Domestic Wastewater via Machine Learning

Insightful Analysis and Prediction of SCOD Component Variation in Low-Carbon/Nitrogen-Ratio Domestic Wastewater via Machine Learning

Intensification of Short Chain Fatty Acid Production during the Alkaline Pretreatment of Fine-Sieving Fractions

Potential of industrial by-products and wastes from the Iberian Peninsula as carbon sources for sulphate-reducing bacteria

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