Microbial and morphological sludge dynamics during the transition to biological nutrient removal using high-starch industrial wastewater

Transitioning from chemically assisted to fully biological nutrient removal is essential for sustainable treatment of industrial wastewaters, yet the mechanisms underlying microbial and morphological sludge transitions under real feedwater conditions remain poorly understood. This study investigated enhanced biological phosphorus removal (EBPR) in sequencing batch reactors (SBRs) fed with starch-rich potato-processing wastewater (PPW). Three reactors were operated for 180 days with distinct inocula: conventional activated sludge, PAO-enriched sludge, and a non-EBPR reference. Reactor performance, hydrolytic enzyme activity, sludge morphology, and microbial community dynamics were evaluated using batch assays, enzyme profiling, 16S rRNA sequencing, and FISH. Conventional sludge (SBR2) was successfully enriched into PAO-dominated communities within 60–90 days, achieving up to 97% COD, 93% TN, and 97% TP-removal, comparable to the pre-enriched inoculum (SBR3). Hydrolytic capacity proved decisive, with amylase activity in SBR2 increasing by >120%, linking starch degradation to phosphorus cycling. Morphological shifts from loose flocs to dense, partially granulated aggregates improved settleability (SVI₃₀ <150 mL/g) and supported stratified microenvironments. Community analyses revealed a trade-off, while PAO enrichment reduced diversity; it enhanced robustness, sustaining nutrient removal even under carbon-limiting conditions. These findings demonstrate that starch-rich industrial wastewaters can be treated biologically without chemical additives when operational selection, rather than inoculum origin, drives enrichment. More importantly, this study provides mechanistic insight into how microbial assembly, sludge morphology, and functional activity co-evolve during the transition from chemically conditioned to fully biological nutrient removal, establishing a framework for scaling EBPR to full-scale PPW treatment and advancing resource recovery in complex wastewater systems. • Operational selection enriched PAOs from conventional sludge in 60–90 days • Amylase activity (>120% increase) linked starch hydrolysis to P cycling • Flocs densified into stable, partially granulated sludge with good settling • EBPR reduced microbial diversity but increased functional robustness

Authors

Institutions

Publication Details

Journal
Environmental Technology & Innovation
Published
2025-11-01
DOI
https://doi.org/10.1016/j.eti.2025.104616
Primary Topic
Phosphorus and nutrient management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Microbial and morphological sludge dynamics during the transition to biological nutrient removal using high-starch industrial wastewater

Dorothee Göttert, Jan Dries, Zehao Li, Johanna Geesey et al.
Environmental Technology & Innovation
Phosphorus and nutrient management
article

Microbial and morphological sludge dynamics during the transition to biological nutrient removal using high-starch industrial wastewater

Dorothee Göttert, Jan Dries, Zehao Li, Johanna Geesey, Jana Scheynen
article en

Abstract

Transitioning from chemically assisted to fully biological nutrient removal is essential for sustainable treatment of industrial wastewaters, yet the mechanisms underlying microbial and morphological sludge transitions under real feedwater conditions remain poorly understood. This study investigated enhanced biological phosphorus removal (EBPR) in sequencing batch reactors (SBRs) fed with starch-rich potato-processing wastewater (PPW). Three reactors were operated for 180 days with distinct inocula: conventional activated sludge, PAO-enriched sludge, and a non-EBPR reference. Reactor performance, hydrolytic enzyme activity, sludge morphology, and microbial community dynamics were evaluated using batch assays, enzyme profiling, 16S rRNA sequencing, and FISH. Conventional sludge (SBR2) was successfully enriched into PAO-dominated communities within 60–90 days, achieving up to 97% COD, 93% TN, and 97% TP-removal, comparable to the pre-enriched inoculum (SBR3). Hydrolytic capacity proved decisive, with amylase activity in SBR2 increasing by >120%, linking starch degradation to phosphorus cycling. Morphological shifts from loose flocs to dense, partially granulated aggregates improved settleability (SVI₃₀ <150 mL/g) and supported stratified microenvironments. Community analyses revealed a trade-off, while PAO enrichment reduced diversity; it enhanced robustness, sustaining nutrient removal even under carbon-limiting conditions. These findings demonstrate that starch-rich industrial wastewaters can be treated biologically without chemical additives when operational selection, rather than inoculum origin, drives enrichment. More importantly, this study provides mechanistic insight into how microbial assembly, sludge morphology, and functional activity co-evolve during the transition from chemically conditioned to fully biological nutrient removal, establishing a framework for scaling EBPR to full-scale PPW treatment and advancing resource recovery in complex wastewater systems. • Operational selection enriched PAOs from conventional sludge in 60–90 days • Amylase activity (>120% increase) linked starch hydrolysis to P cycling • Flocs densified into stable, partially granulated sludge with good settling • EBPR reduced microbial diversity but increased functional robustness

Environmental Technology & InnovationVol. 40
University of Antwerp (BE)
Openalex Percentile: Top 57%
Phosphorus and nutrient management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.