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Li ZH, Wang RL, Lu M, Wang X, Huang YP, Yang JW, Zhang TY. A novel method for identifying aerobic granular sludge state using sorting, densification and clarification dynamics during the settling process. WATER RESEARCH 2024; 253:121336. [PMID: 38382291 DOI: 10.1016/j.watres.2024.121336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 01/22/2024] [Accepted: 02/17/2024] [Indexed: 02/23/2024]
Abstract
Aerobic granular sludge is one of the most promising biological wastewater treatment technologies, yet maintaining its stability is still a challenge for its application, and predicting the state of the granules is essential in addressing this issue. This study explored the potential of dynamic texture entropy, derived from settling images, as a predictive tool for the state of granular sludge. Three processes, traditional thickening, often overlooked clarification, and innovative particle sorting, were used to capture the complexity and diversity of granules. It was found that rapid sorting during settling indicates stable granules, which helps to identify the state of granules. Furthermore, a relationship between sorting time and granule heterogeneity was identified, helping to adjust selection pressure. Features of the dynamic texture entropy well correlated with the respirogram, i.e., R2 were 0.86 and 0.91 for the specific endogenous respiration rate (SOURe) and the specific quasi-endogenous respiration rate (SOURq), respectively, providing a biologically based approach for monitoring the state of granules. The classification accuracy of models using features of dynamic texture entropy as an input was greater than 0.90, significantly higher than the input of conventional features, demonstrating the significant advantage of this approach. These findings contributed to developing robust monitoring tools that facilitate the maintenance of stable granular sludge operations.
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Affiliation(s)
- Zhi-Hua Li
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.
| | - Ruo-Lan Wang
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Meng Lu
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Xin Wang
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Yong-Peng Huang
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Jia-Wei Yang
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Tian-Yu Zhang
- Department of Mathematical Sciences, Montana State University, Bozeman, MT 59717, USA
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Gao X, Liu Y, Tang C, Lu M, Zou J, Li Z. Evaluating river health through respirogram metrics: Insights from the Weihe River basin, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 919:170805. [PMID: 38342463 DOI: 10.1016/j.scitotenv.2024.170805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/18/2024] [Accepted: 02/06/2024] [Indexed: 02/13/2024]
Abstract
Human activities pose a significant threat to rivers, requiring robust assessment methods for effective river management. This study focuses on the Weihe River Basin in Shaanxi province and introduces the respirogram as an innovative assessment technique. The respirogram allows the simultaneous assessment of river health from two important aspects: pollution levels and microbial status. Specifically, the in-situ respiration ratio (Rs/t) serves as an indicator of pollution, with higher Rs/t values correlating with increased pollution levels. Conversely, the recovery index (RI) measures microbial vitality, with values below 0.15 indicating greater microbial activity and recovery potential. Using predefined thresholds of Rs/t = 0.3 and RI = 0.15, water bodies were categorized into four types. For example, rivers with Rs/t > 0.3 and RI > 0.15 were identified as receiving sewage, characterized by high pollution and low microbial vitality. Similarly, different assessment criteria delineated urban rivers, natural rivers, and wastewater treatment plants. Based on these classifications, targeted engineering measures were proposed to enhance the self-purification capabilities of rivers of different statuses.
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Affiliation(s)
- Xingdong Gao
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Yanxia Liu
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Congcong Tang
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Meng Lu
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Jiageng Zou
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Zhihua Li
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.
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Jiang Y, Li C, Hou Z, Shi X, Zhang X, Gao Y, Deng SH. Pollutants removal and connections among sludge properties, metabolism potential and microbial characteristics in aerobic granular sequencing batch reactor for petrochemical wastewater treatment. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 344:118715. [PMID: 37562254 DOI: 10.1016/j.jenvman.2023.118715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/06/2023] [Accepted: 07/26/2023] [Indexed: 08/12/2023]
Abstract
Petrochemical wastewater contains inhibitory compounds such as aromatics that are toxic to microorganisms during biological treatment. The compact and layered structure and the high amount of extracellular polymeric substances (EPS) in aerobic granular sludge (AGS) can contribute to protecting microorganisms from the harsh environment. This study evaluated the changes in the granule properties, pollutants removal, microbial metabolic potential and molecular microbial characteristics of the AGS process for petrochemical wastewater treatment. Granules treating petrochemical wastewater had a higher SVI30/SVI5 value (0.94) than that treating synthetic wastewater. An increase in bioactivity and EPS secretion with higher bio-polymer composition, specifically the functional groups such as hydroxyl, alkoxy and amino in protein, was observed, which promoted biomass aggregation. The granules also had more than 2-fold higher specific oxygen utilization rate. The AGS-SBR process obtained an average COD removal of 93% during petrochemical wastewater treatment and an effluent bCOD of below 1 mg L-1. No obvious inhibition of nitrification and denitrification activity was observed in the processes attributed to the layered structure of AGS. The average effluent NH4+-N of 5.0 mg L-1 was obtained and TN removal efficiencies of over 80.0% was achieved. Molecular microbial analysis showed that abundant functional genera Stenotrophomonas and Pseudoxanthomonas contributed to the degradation of aromatics and other petroleum organic pollutants. They were enriched with the variation of group behavior while metabolisms of amino acids and carboxylic acids by the relevant functional genera (e.g., Cytophagia) were significantly inhibited. The enrichment of Flavobacterium and Thermomonas promoted nitrification and denitrification, respectively. This research revealed the rapid start-up, enhanced granule structural strength, high inhibition resistance and considerable performance of AGS-SBR for petrochemical wastewater treatment.
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Affiliation(s)
- Yu Jiang
- School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, 430070, China
| | - Chaoyu Li
- School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, 430070, China
| | - Zhaozhi Hou
- School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, 430070, China
| | - Xueqing Shi
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao, 266033, PR China
| | - Xiangling Zhang
- School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, 430070, China
| | - Yaohuan Gao
- School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, 710049, PR China
| | - Shi-Hai Deng
- School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, 710049, PR China.
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Ji Y, Liu J, Wang C, Zhang F, Xu X, Zhu L. Stability improvement of aerobic granular sludge (AGS) based on Gibbs free energy change (∆G) of sludge-water interface: Abstract2. Materials and Methods. WATER RESEARCH 2023; 240:120059. [PMID: 37216787 DOI: 10.1016/j.watres.2023.120059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 10/20/2022] [Accepted: 05/08/2023] [Indexed: 05/24/2023]
Affiliation(s)
- Yatong Ji
- Institution of Environment Pollution Control and Treatment, Department of Environmental Engineering, Zhejiang University, Hangzhou 310058, China
| | - Jieyi Liu
- Institution of Environment Pollution Control and Treatment, Department of Environmental Engineering, Zhejiang University, Hangzhou 310058, China
| | - Chen Wang
- Institution of Environment Pollution Control and Treatment, Department of Environmental Engineering, Zhejiang University, Hangzhou 310058, China
| | - Fan Zhang
- Environmental Protection Bureau of Changxing County, Huzhou 313100, China
| | - Xiangyang Xu
- Institution of Environment Pollution Control and Treatment, Department of Environmental Engineering, Zhejiang University, Hangzhou 310058, China; Zhejiang Province Key Laboratory for Water Pollution Control and Environmental Safety, Hangzhou 310058, China; Zhejiang Provincial Engineering Laboratory of Water Pollution Control, 388 Yuhangtang Road, Hangzhou 310058, China
| | - Liang Zhu
- Institution of Environment Pollution Control and Treatment, Department of Environmental Engineering, Zhejiang University, Hangzhou 310058, China; Zhejiang Province Key Laboratory for Water Pollution Control and Environmental Safety, Hangzhou 310058, China; Zhejiang Provincial Engineering Laboratory of Water Pollution Control, 388 Yuhangtang Road, Hangzhou 310058, China.
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Hang Z, Tong P, Zhao P, He Z, Shao L, Jia Y, Wang XC, Li Z. Hierarchical stringent response behaviors of activated sludge system to stressed conditions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 870:161832. [PMID: 36716870 DOI: 10.1016/j.scitotenv.2023.161832] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 01/18/2023] [Accepted: 01/21/2023] [Indexed: 06/18/2023]
Abstract
The stringent response of activated sludge systems to either stressed or harmful environments is important for the stable operation of activated sludge, which is examined by taking copper ion (Cu2+) as a stress model in this study. When weak stress was employed (Cu2+ ≤ 2.5 mg/L), the N-acyl-homoserine lactones (AHLs) of C6-, C8-, and C10-HSL increased by 30 %, 13 %, and 127 %, respectively, while the redox sensor green (RSG) intensity decreased by 28 %. Encountering the increased stress (2.5 mg/L < Cu2+ ≤ 5 mg/L), bacteria concentration in the supernatant increased by 87 %. However, the respiration rates of autotrophic and heterotrophic bacteria (SOURa and SOURh) and adenosine triphosphate decreased by 52 %, 18 %, and 27 %, respectively, and the flocs disintegrated with a diameter decreasing from 57 to 51 μm. When the stress became more serious (Cu2+ > 5 mg/L), the respiration rates continued to decline, but the quasi-endogenous respiration ratio (Rq/t) increased from 31 % to 47 %. Negligible changes occurred in the endogenous respiration rate (SOURe), adenosine diphosphate, and adenosine monophosphate. Based on these results, a hierarchical stringent response model of the activated sludge system to stressed conditions was proposed, and these responses were evaluated by respirogram. The initial response to weak stress was related to the most sensitive signals of quorum sensing and RSG intensity, well described by the quasi-endogenous respiration rate. The adaptive response to increased stress was the proactive migrations of low- and high-nucleic-acid bacteria to the supernatant, causing the looseness and even disintegration of sludge flocs, well described by SOURa, SOURh, and Rq/t. The lethal response to lethal stress was related to endogenous metabolic processes, well described by SOURe. This work provides new insights into understanding the stringent response of activated sludge systems to some stressed conditions. It helps to regulate the stability of activated sludge systems with respirogram technology.
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Affiliation(s)
- Zhenyu Hang
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Peipei Tong
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Pian Zhao
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Zhangwei He
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Linjun Shao
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Yanru Jia
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Xiaochang C Wang
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Zhihua Li
- Key Laboratory of Northwest Water Resource, Environment, and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology in Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.
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