Monitoring morphological changes from activated sludge to aerobic granular sludge under distinct organic loading rates and increasing minimal imposed sludge settling velocities through quantitative image analysis
| Autor: | Ángeles Val del Río, Sérgio Silva, António L. Amaral, Eugénio C. Ferreira, Daniela P. Mesquita, M. Madalena Alves |
|---|---|
| Přispěvatelé: | Universidade do Minho |
| Rok vydání: | 2021 |
| Předmět: |
Flocculation
Environmental Engineering 010504 meteorology & atmospheric sciences Health Toxicology and Mutagenesis 0207 environmental engineering Principal component analysis 02 engineering and technology 01 natural sciences Waste Disposal Fluid Granulation Bioreactors Settling Image processing Partial least squares Environmental Chemistry Turning point 020701 environmental engineering 0105 earth and related environmental sciences Aerobic granulation process Science & Technology Sewage Chemistry Public Health Environmental and Occupational Health Sludge volume index General Medicine General Chemistry Pulp and paper industry Pollution 6. Clean water Sludge settling Aerobiosis Activated sludge 13. Climate action Aerobic granulation Sequencing batch reactors |
| Zdroj: | Repositório Científico de Acesso Aberto de Portugal Repositório Científico de Acesso Aberto de Portugal (RCAAP) instacron:RCAAP |
| ISSN: | 1879-1298 |
| Popis: | Quantitative image analysis (QIA) was used for monitoring the morphology of activated sludge (AS) during a granulation process and, thus, to define and quantify, unequivocally, structural changes in microbial aggregates correlated with the sludge properties and granulation rates. Two sequencing batch reactors fed with acetate at organic loading rates of 1.1±0.6 kgCOD m3 d1 (R1) and 2.0±0.2 kgCOD m3 d1 (R2) and three minimal imposed sludge settling velocities (0.27mh1, 0.53mh1, and 5.3mh1) induced distinct granulation processes and rates. QIA results evidenced the turning point from flocculation to granulation processes by revealing the differences in the aggregates stratification patterns and quantifying the morphology of aggregates with equivalent diameter (Deq) of 200mDeq650m. Multivariate statistical analysis of the QIA data allowed to distinguish the granulation status in both systems, by clustering the observations according to the sludge aggregation and granules maturation status, and successfully predicting the sludge volume index measured at 5min (SVI5) and 30min (SVI30). These results evidence the possibility of defining unequivocally the granulation rate and anticipating the sludge settling properties at early stages of the process using QIA data. Hence, QIA could be used to predict episodes of granules disruption and hindered settling ability in aerobic granulation sludge processes. The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/ 04469/2020 unit and the project AGeNT PTDC/BTA-BTA/31264/2017 (POCI-01-0145-FEDER-031264). The authors also acknowledge the financial support to S´ergio Alves da Silva through the grant SFRH/BD/ 122623/2016 provided by FCT. A. Val del Rio is supported by Xunta de Galicia (ED418B 2017/075) and program Iacobus (2018/2019). info:eu-repo/semantics/publishedVersion |
| Databáze: | OpenAIRE |
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