Mark C.M. van Loosdrecht
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643 records found
1
Recovery of C, N, and P from waste activated sludge by enzymatic anaerobic fermentation
Stoichiometry and metatranscriptomics analysis
The recovery of C, N, and P elements by sludge biorefinery potentially reduces operation costs and increases the extra benefits. Herein, we analyzed the elemental stoichiometry of C, N, and P and functional microbiome involved in enzymatic anaerobic fermentation. Enzymatic hydrolysis was observed to increase the release of C, N, and P into the sludge supernatants by 21.8 %–26.3 %. Metatranscriptome analysis indicated that enzymatic pretreatment enhanced the metabolism of the organic carbon degradation, ammonium conversion, and P solubilization in subsequent fermentation. Specifically, enzymatic pretreatment enhanced endogenous carbon hydrolase activity by 48.4 %–72.7 % and upregulated intra-C metabolic pathways, such as glycolysis and pyruvate metabolism. Ammonium transport and conversion were significantly increased by 4–6 fold, stimulating the synthesis of glutamine and endogenous amino acids. Additionally, enzymatic hydrolysis promoted phosphatase secretion and enhanced bacterial P uptake. These effects improved the recovery of C, N, and P as dentification carbon source and struvite by 13.7 %–41.8 % and the dry sludge production was reduced by 24.3 %–28.1 %. Life cycle assessment (LCA) indicated the shift of CO2 emissions from net positive to net negative levels as compared to the conventional A2/O process. This study offers valuable insights into the redistribution and metabolism of various elements involved in the enzymatic anaerobic fermentation, and proposes the potential strategy to recovery C, N, and P from sewage via sludge biorefinery.
The current research attempts to elucidate fundamental mechanistic correlation between the complex chemical architecture of wastewater-derived biopolymers – EPS (extracellular polymeric substances) and their inherent thermal properties for fire-safety applications. By integrating thermogravimetric-infrared spectroscopy with two-dimensional correlation spectroscopy, we resolve intricate mass-loss profiles into three pseudo-components (PCs), each characterised by kinetic signatures and functional group transformations. PC1 (150–350 °C, activation energy (AE) = 140–150 kJ/mol), is primarily governed by the degradation of polysaccharides and release of early-stage volatiles (H2O, CO2, CH4, NH3, and HNCO). PC2 (210–450 °C, AE = 160–175 kJ/mol), represent the transition stage dominated by proteinaceous and lipid cross-linking, which produces nitrogenous species essential for promoting condensed-phase char development. PC3 (290–600 °C, AE > 180 kJ/mol) corresponds to the decomposition of humic-like substances and subsequent aromatic condensation of stable residues. Furthermore, comparative analysis reveals that EPS extracted from activated sludge exhibits higher thermal stability and a significantly increased char yield (33.5 %) than aerobic counterpart, attributed to higher AE during the middle decomposition stage. The persistent detection of C-O-C/P–O–C and aromatic C=C vibrations up to 700 °C confirms the formation of a phosphorus-rich aromatic char structure. This multi-dimensional analytical framework moves beyond conventional TG-based pseudo-component fitting, providing high resolution interpretation of the sequential evolution of volatile species and early-stage charring mechanisms of EPS.
Biomethanation of alkaline waste sludge in haloalkaline conditions
Combined proof of concept experiments and technical economic evaluation
A highly pure biomethane stream (≈97% CH4) was produced continuously under halo-alkaline conditions (pH > 9, 0.6 M Na+) from complex alkaline organic waste residue originating from biopolymer extraction from sewage sludge. During the proof-of-concept operation, the substrate was degraded with similar efficiency (40% of the volatile solids, VS) compared to neutral conditions (36% of the VS). Operational data was utilised in a technical evaluation to identify bottlenecks for full-scale implementation at an early stage of process development and for comparison to conventional biogas upgrading using pressure swing and membranes. Initially identified bottlenecks for alkaline fermentation were related to overcautious assumptions, while others could be technically solved. Alkaline fermentation offers an attractive method for supplying increasingly needed high-purity biomethane using various recalcitrant substrates that have undergone alkaline pre-treatment. This is more feasible than the conventional ex-situ biogas upgrading. Next, upscaling steps for alkaline fermentation should be pursued. Strategies for integrated CO2 sequestration and nutrient recovery are outlined, which will offer additional benefits in the future.
Acetoclastic versus hydrogenotrophic methanogenesis
Defining how pH and alkalinity shape acetate metabolism in a haloalkaliphilic methanogenic community for biomethane production
Static and dynamic dissolved oxygen distributions in algal–bacterial granular sludge
Mapping intragranular oxygen profile and penetration under different oxygenation strategies
Algal–bacterial granular sludge (ABGS) exhibits pronounced intragranular dissolved oxygen (DO) heterogeneity. However, the internal DO microenvironments under different oxygenation strategies remain insufficiently understood. In this study, intragranular DO distributions in ABGS were characterized under darkness, illumination, and artificial aeration. Results show that intragranular DO distributions varied with granule size and were differently influenced by artificial aeration and photosynthetic oxygenation. After 60 min of artificial aeration at an air uplift velocity of 2.8 cm s−1, DO at a depth of approximately 0.8 mm in granules with a diameter of around 3 mm remained nearly 0 mg L−1. In contrast, oxygen generated in situ via photosynthesis rapidly elevated intragranular DO levels, exceeding 4 mg L−1 at the same depth after 30-min illumination. This study shows that intragranular DO in ABGS can be dynamically restructured in response to distinct oxygen supply and consumption processes, which also provides an in-depth insight into better ABGS design and operation.
From fixed points to optimum regions
AI–NSGA-II framework for high-recovery, low-energy brackish water RO
Validated against pilot-scale data with R2 > 0.99 and absolute average relative errors below 5 %, the ANN models accurately predict energy consumption (EC) and recovery (Re) under realistic operational conditions. Coupled with NSGA-II, the framework systematically generates Pareto-optimal operating regions that balance low EC (0.6 kWh/m³) with high Re (up to 80 %) while respecting fouling and scaling constraints. This multi-objective approach provides a flexible operating envelope, such as 3–4.5 LPM feed flow and 90–125 psi with higher-permeability membranes, surpassing the limitations of single-point optima. The optimized recovery represents a 3- to 5-fold increase over the typical factory baseline (∼15 %), translating to energy savings of >50 % and CO₂ emission reductions of 0.1–0.2 kg/m³. Sensitivity analysis confirms feed flow rate and pressure as dominant drivers of EC (31.3 % and 28.6 % relative factor) and membrane type and flow rate as primary influencers of Re (32.2 % and 30.2 %).
This optimum region approach surpasses the limitations of traditional single-point design optimization by providing flexible operating envelopes that accommodate seasonal feed variability, equipment aging, and membrane fouling. All models and the optimization framework are shared via an open-source repository to ensure full reproducibility and facilitate industrial adoption.
Overall, this AI-driven multi-objective optimization framework bridges the gap between theoretical performance and field-ready operation, laying the foundation for more adaptive, cost-effective, and climate-smart brackish water desalination. The modular approach is directly adaptable to multi-stage and hybrid systems, offering a scalable and resilient solution to urgent global water scarcity challenges. ...
Validated against pilot-scale data with R2 > 0.99 and absolute average relative errors below 5 %, the ANN models accurately predict energy consumption (EC) and recovery (Re) under realistic operational conditions. Coupled with NSGA-II, the framework systematically generates Pareto-optimal operating regions that balance low EC (0.6 kWh/m³) with high Re (up to 80 %) while respecting fouling and scaling constraints. This multi-objective approach provides a flexible operating envelope, such as 3–4.5 LPM feed flow and 90–125 psi with higher-permeability membranes, surpassing the limitations of single-point optima. The optimized recovery represents a 3- to 5-fold increase over the typical factory baseline (∼15 %), translating to energy savings of >50 % and CO₂ emission reductions of 0.1–0.2 kg/m³. Sensitivity analysis confirms feed flow rate and pressure as dominant drivers of EC (31.3 % and 28.6 % relative factor) and membrane type and flow rate as primary influencers of Re (32.2 % and 30.2 %).
This optimum region approach surpasses the limitations of traditional single-point design optimization by providing flexible operating envelopes that accommodate seasonal feed variability, equipment aging, and membrane fouling. All models and the optimization framework are shared via an open-source repository to ensure full reproducibility and facilitate industrial adoption.
Overall, this AI-driven multi-objective optimization framework bridges the gap between theoretical performance and field-ready operation, laying the foundation for more adaptive, cost-effective, and climate-smart brackish water desalination. The modular approach is directly adaptable to multi-stage and hybrid systems, offering a scalable and resilient solution to urgent global water scarcity challenges.
Valorising co-produced oxygen from green hydrogen systems
Circular economy pathways in wastewater treatment
Population growth, climate change, and urbanisation significantly contribute to environmental stress, particularly through the depletion of finite resources like clean, easily accessible freshwater. In the water industry, the supply chain must become more independent, shifting from the prevailing linear delivery model to a circular economy. This shift can be achieved by adopting advanced treatment methods to ensure high-quality treated water and minimising waste and emissions. A transition to a circular economy can offer an opportunity to address sustainability issues in multiple sectors. For example, the water and energy nexus recognises that these two sectors are inextricably linked. Integrating green hydrogen production and wastewater treatment (WWT) has been identified as a promising strategy as part of the water-energy nexus, which advances the circular economy. When the green hydrogen economy uses treated wastewater as a feedstock, contributing to water reuse, the water industry can further enhance the sustainability of this approach by utilising co-products from hydrogen synthesis, such as high-purity oxygen. This oxygen can then be employed in various stages of WWT, including aeration and producing key reagents such as ozone and hydrogen peroxide, aiming to improve treatment efficiency and reduce emissions. Accordingly, this study examines how such applications can enhance circularity within the water sector. The principal findings were: (i) integrating green hydrogen production with WWT offers promising environmental and economic benefits but requires deeper technical, regulatory, and stakeholder alignment; (ii) optimising co-product oxygen utilisation in aeration and advanced treatment can help enhance WWT performance and economic viability; (iii) future research should prioritise techno-economic assessments, pilot-scale demonstrations, and system-wide integration studies to enable successful implementation of this circular and sustainable approach.
Riverbank filtration is a nature-based water treatment strategy known for its effective removal of organic micropollutants. Yet, the mechanisms governing their biodegradation, especially the role of redox transitions in mediating biotransformation, remain insufficiently understood. Here, we integrate metagenomic profiling with chemical analytics in a 10 m simulated riverbank filtration system to demonstrate how sequential oxidizing–reducing degradation enhances organic micropollutant transformation. Oxygen stratification structured distinct microbial and enzymatic pathways: oxidizing zones (>+200 mV redox potential) facilitated cytochrome P450-mediated oxidation (oxidizing condition, OXD), while subsequent redox shifts to reducing conditions (←400 mV, sequential oxidizing–reducing (SOR) conditions) activated reductive transformations (e.g., via nitronate monooxygenase and aldehyde dehydrogenase) and conjugation pathways. These SOR conditions significantly enhanced the removal of recalcitrant compounds, including irbesartan (+25.3%), benzotriazole (13.4%), and gabapentin (+9.7%). Metagenomic analysis revealed redox-driven microbial specialization, with Pseudomonadota and Nitrospirota dominating in oxidizing zones and reducing microzones enriched in pathways associated with nitrotoluene and ethylbenzene degradation, providing genomic evidence for sequential organic micropollutant breakdown. These findings establish a mechanistic framework for harnessing oxidizing–reducing microbial partnerships to amplify organic micropollutant removal in nature-based water treatment systems, which can be used for riverbank filtration site selection and well field construction and optimization.
Global insights into extracellular polymeric substances from activated sludge
Yield, composition, and microbial communities
Activated sludge (AS) wastewater treatment generates substantial excess sludge which needs to be discarded and thereby increasing operational costs. Extracellular polymeric substances (EPS) within AS present a potential resource for recovery, reducing sludge volume and mass while adding value. Achieving this goal requires a better characterization of EPS, as the relationship between its composition and the microbial communities responsible for its production remains insufficiently understood. Here, we analysed extracted EPS from 16 wastewater treatment plants across 13 countries and 5 continents and found that alkaline extractable EPS yields varied widely (2.81–18.5 wt.% VSS). The microbial community composition of abundant species varied across plants and particularly across continents and did not correlate to the EPS yield. Only sludge retention time had a significant correlation with the EPS yield (p < 0.005). Traditional colorimetric assays failed to detect compositional trends of the EPS, but Fourier Transform Infrared (FTIR) analysis indicated that extracted EPS from biological phosphorus removal systems had higher lipid and polysaccharide content, while chemical phosphorus removal systems had higher relative protein content. Thus, FTIR proved effective for distinguishing extracted EPS composition, demonstrating its potential as a high-throughput characterization tool. These findings highlighted that the wastewater treatment design and operation may shape the functional groups in EPS when using the alkaline method. More investigations are needed to find possible correlations between the composition of extracted EPS and the microbial community structure. Overall, the study presents a baseline for the amount and overall composition of biopolymers that can be extracted from global AS plants for recovery.
The authors regret that an inconsistency was identified between the results presented in Fig. 6 and the inventory data reported in Tables S.11 and S.12 of the Supplementary Information. This discrepancy arose because an additional scenario from a previous version of the manuscript was inadvertently retained in the Supplementary Information, although it was not included in the final published article. As a result, the scenario numbering in the Supplementary Information did not correspond to the scenarios discussed in the main text, leading to apparent inconsistencies for Climate change and Marine ecotoxicity results for Scenario 3. The Supplementary Information has now been corrected by removing the tables related to the excluded scenario and aligning the remaining scenario numbering with the final version of the article. The results presented in the main article remain unchanged. The authors would like to apologise for any inconvenience caused.
Cow-dung stabilised compressed earth blocks
A mechanistic approach to understand its water resistance behaviour
Cow-dung is a widely used stabiliser applied in traditional earthen buildings with one objective to improve water resistance. However, most research has focused on explaining its mechanical strength, with only one study suggesting water resistance mechanism via formation of insoluble compounds at high pH, a phenomenon uncommon in natural cow dung and soil mixtures. This article investigates the water-resistance behaviour of cow-dung stabilised compressed earthen blocks (CD-CEBs) through an extensive experimental programme to understand the influence of cow-dung and soil related factors and to characterise the components of cow-dung responsible for its water resistance. It was found that the small-sized microbial aggregates (SSMA) present in cow-dung, which are negatively charged hydrophobic aggregates of low specific surface area, are responsible for enhanced water resistance of CD-CEBs. The insights gained from experiments are compiled to recommend the following strategies for improved performance of CD-CEBs: (i) The use of wet cow-dung is advised over dry cow-dung as it provided over 80 times better water resistance; (ii) Adopting a higher compaction liquid content (by 3%) improved the water resistance by over 40 times; (iii) The water resistance of CD-CEBs was improved over 30 times by using soils rich in low-swelling clay minerals such as kaolinite. A case study applying these findings demonstrates the successful scaleup from the lab to field showcasing potential of cow-dung and soil in low-carbon construction.
Wastewater metaproteomics
Tracking microbial and human protein biomarkers
Although biofilms are widespread in nature, the ecological roles and compositional diversity of the extracellular polymeric substances (EPS) forming these structures remain poorly understood. Here, we apply a bottom-up genomic approach by investigating the biosynthetic potential for glycan precursors in the genus “Candidatus Accumulibacter”, with a focus on assessing the intra-genus variability. Within a curated set of 61 “Ca. Accumulibacter” MAGs, our analysis revealed a dichotomy in glycan precursors between a conserved core group of 9 nucleotide-sugars and a variable accessory set of 12 nucleotide-sugars, out of 50 nucleotide-sugars tested. The core nucleotide-sugars in “Ca. Accumulibacter” are related to nucleotide-sugars also found to be widely distributed across the tree of life, whereas the accessory set is enriched in rare nucleotide-sugars. The accessory nucleotide-sugars show an irregular distribution across “Ca. Accumulibacter” phylogeny, and divergent evolutionary histories. This highlights the possibility that distinct evolutionary pressures act on different parts of the EPS-formation metabolism, leading to genotypic diversification driven by complex biological phenomena such as horizontal gene transfer that support the observed divergent evolutionary histories.