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Author |
Peng, L.; Dai, X.; Liu, Y.; Sun, J.; Song, S.; Ni, B.-J. |
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Title |
Model-based assessment of estrogen removal by nitrifying activated sludge |
Type |
A1 Journal article |
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Year  |
2018 |
Publication |
Chemosphere |
Abbreviated Journal |
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Volume |
197 |
Issue |
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Pages |
430-437 |
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Keywords |
A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL) |
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Abstract |
Complete removal of estrogens such as estrone (E1), estradiol (E2), estriol (E3) and ethinylestradiol (EE2) in wastewater treatment is essential since their release and accumulation in natural water bodies are giving rise to environment and health issues. To improve our understanding towards the estrogen bioremediation process, a mathematical model was proposed for describing estrogen removal by nitrifying activated sludge. Four pathways were involved in the developed model: i) biosorption by activated sludge flocs; ii) cometabolic biodegradation linked to ammonia oxidizing bacteria (AOB) growth; iii) non growth biodegradation by AOB; and iv) biodegradation by heterotrophic bacteria (HB). The degradation kinetics was implemented into activated sludge model (ASM) framework with consideration of interactions between substrate update and microorganism growth as well as endogenous respiration. The model was calibrated and validated by fitting model predictions against two sets of batch experimental data under different conditions. The model could satisfactorily capture all the dynamics of nitrogen, organic matters (COD), and estrogens. Modeling results suggest that for El, E2 and EE2, AOB-linked biodegradation is dominant over biodegradation by HB at all investigated COD dosing levels. However, for E3, the increase of COD dosage triggers a shift of dominant pathway from AOB biodegradation to HB biodegradation. Adsorption becomes the main contributor to estrogen removal at high biomass concentrations. (C) 2018 Elsevier Ltd. All rights reserved. |
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Wos |
000426231900049 |
Publication Date |
2018-01-10 |
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Edition |
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ISSN |
0045-6535; 1879-1298 |
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UA library record; WoS full record; WoS citing articles |
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no |
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Call Number |
UA @ admin @ c:irua:149842 |
Serial |
8259 |
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Author |
Peng, L.; Kassotaki, E.; Liu, Y.; Sun, J.; Dai, X.; Pijuan, M.; Rodriguez-Roda, I.; Buttiglieri, G.; Ni, B.-J. |
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Title |
Modelling cometabolic biotransformation of sulfamethoxazole by an enriched ammonia oxidizing bacteria culture |
Type |
A1 Journal article |
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Year |
2017 |
Publication |
Chemical engineering science |
Abbreviated Journal |
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Volume |
173 |
Issue |
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Pages |
465-473 |
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Keywords |
A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL) |
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Abstract |
Antibiotics such as sulfamethoxazole (SFX) are environmentally hazardous after being released into the aquatic environment and challenges remain in the development of engineered prevention strategies. In this work, a mathematical model was developed to describe and evaluate cometabolic biotransformation of SFX and its transformation products (TPs) in an enriched ammonia oxidizing bacteria (AOB) culture. The growth-linked cometabolic biodegradation by AOB, non-growth transformation by AOB and nongrowth transformation by heterotrophs were considered in the model framework. The production of major TPs comprising 4-Nitro-SFX, Desamino-SFX and N-4-Acetyl-SFX was also specifically modelled. The validity of the model was demonstrated through testing against literature reported data from extensive batch tests, as well as from long-term experiments in a partial nitritation sequencing batch reactor (SBR) and in a combined SBR + membrane aerated biofilm reactor performing nitrification/denitrification. Modelling results revealed that the removal efficiency of SFX increased with the increase of influent ammonium concentration, whereas the influent organic matter, hydraulic retention time and solid retention time exerted a limited effect on SFX biodegradation with the removal efficiencies varying in a narrow range. The variation of influent SFX concentration had no impact on SFX removal efficiency. The established model framework enables interpretation of a range of experimental observations on SFX biodegradation and helps to identify the optimal conditions for efficient removal. (C) 2017 Elsevier Ltd. All rights reserved. |
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Wos |
000411764200039 |
Publication Date |
2017-08-14 |
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ISSN |
0009-2509 |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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no |
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Call Number |
UA @ admin @ c:irua:146629 |
Serial |
8267 |
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Author |
Peng, L.; Liu, Y.; Sun, J.; Wang, D.; Dai, X.; Ni, B.-J. |
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Title |
Enhancing immobilization of arsenic in groundwater: A model-based evaluation |
Type |
A1 Journal article |
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Year |
2017 |
Publication |
Journal of cleaner production |
Abbreviated Journal |
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Volume |
166 |
Issue |
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Pages |
449-457 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL) |
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Abstract |
The mobilization of arsenic (As) in aquatic environment (groundwater) can cause severe environmental and healthy issues. To develop remediation strategies, we proposed a comprehensive mathematical model to describe the As removal in a arsenite (As (III)) oxidizing and ferrous iron (Fe (II)) oxidizing denitrifying granular biofilm system. In the model framework, the growth-linked microbial oxidation of As (III) and Fe (II) was coupled to chemolithotrophic denitrification of one-step reduction of nitrate to nitrogen gas. Meanwhile, the precipitation of ferric iron (Fe (III)) and adsorption of arsenate (As (V)) onto the biogenic Fe (III) (hydr)oxides were also considered. The model was calibrated by comparing the model predictions against experimental data from batch experiments. The validity of the model was further demonstrated through testing against long-term experimental results from five independent bioreactors with different reactor configurations and operational conditions. Modeling results revealed that the granule size would exert a limited impact on arsenic and iron removal. Nevertheless, their removal efficiencies increased rapidly with the increase of hydraulic retention time (HRT) from 1 h to 12 h, but became independent of HRT as it further increased. The established model framework enables interpretation of a range of experimental observations on As and Fe removal and helps to identify the optimal conditions for enhanced arsenic remediation. (C) 2017 Elsevier Ltd. All rights reserved. |
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Wos |
000412607100046 |
Publication Date |
2017-08-09 |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0959-6526 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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no |
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Call Number |
UA @ admin @ c:irua:146635 |
Serial |
7919 |
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Author |
Peng, L.; Sun, J.; Liu, Y.; Dai, X.; Ni, B.-J. |
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Title |
Nitrous oxide production in a granule-based partial nitritation reactor : a model-based evaluation |
Type |
A1 Journal article |
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Year |
2017 |
Publication |
Scientific reports |
Abbreviated Journal |
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Volume |
7 |
Issue |
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Pages |
45609 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL) |
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Abstract |
Sustainable wastewater treatment has been attracting increasing attentions over the past decades. However, the production of nitrous oxide (N2O), a potent GHG, from the energy-efficient granule-based autotrophic nitrogen removal is largely unknown. This study applied a previously established N2O model, which incorporated two N2O production pathways by ammonia-oxidizing bacteria (AOB) (AOB denitrification and the hydroxylamine (NH2OH) oxidation). The two-pathway model was used to describe N2O production from a granule-based partial nitritation (PN) reactor and provide insights into the N2O distribution inside granules. The model was evaluated by comparing simulation results with N2O monitoring profiles as well as isotopic measurement data from the PN reactor. The model demonstrated its good predictive ability against N2O dynamics and provided useful information about the shift of N2O production pathways inside granules for the first time. The simulation results indicated that the increase of oxygen concentration and granule size would significantly enhance N2O production. The results further revealed a linear relationship between N2O production and ammonia oxidation rate (AOR) (R-2 = 0.99) under the conditions of varying oxygen levels and granule diameters, suggesting that bulk oxygen and granule size may exert an indirect effect on N2O production by causing a change in AOR. |
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Wos |
000398238200001 |
Publication Date |
2017-04-03 |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2045-2322 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Times cited |
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Open Access |
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Notes |
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no |
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Call Number |
UA @ admin @ c:irua:142397 |
Serial |
8311 |
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