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Metagenomes and metagenome-assembled genomes from microbial communities in a biological nutrient removal plant operated at Hamptons Road Sanitation District (HRSD) with high and low dissolved oxygen conditions

Aeration is a major cost at biological nutrient removal (BNR) plants. We report on microbial communities in a pilot-scale BNR system before and after a dissolved oxygen transition from 2.5 to 0.2 mg/L implemented over 18 months. Four PacBio metagenomes and 316 metagenome-assembled genomes are announced.

dissolved oxygen

Metagenomes and Metagenome-Assembled Genomes from Microbial Communities in a Biological Nutrient Removal Plant Operated at Hamptons Road Sanitation District (HRSD) with High and Low Dissolved Oxygen Conditions

In this study, we aimed to evaluate Biological Nutrient Removal (BNR) and investigate microbial community changes as the dissolved oxygen is reduced in the aerated portions of wastewater treatment trains. We present a dataset of Metagenome-Assembled Genomes (MAGs) obtained from activated sludge collected from the Hamptons Road Sanitation District (HRSD) BNR plant at the beginning of operation, when the DO was high, and at the end of operation, when the DO was low.

Genomics

Metagenomes and Metagenome-Assembled Genomes from Microbial Communities in a Biological Nutrient Removal Plant Operated at Los Angeles County Sanitation District (LACSD) with High and Low Dissolved Oxygen Conditions

In this study, we aimed to evaluate Biological Nutrient Removal (BNR) and investigate microbial community changes as the dissolved oxygen is reduced in the aerated portions of wastewater treatment trains. We present a dataset of Metagenome-Assembled Genomes (MAGs) obtained from activated sludge collected from the Los Angeles County Sanitation District (LACSD) BNR plant at the beginning of operation, when the DO was high, and at the end of operation, when the DO was low.

Genomics

Transforming Aeration Energy in Water Resource Recovery Facilities (WRRFs) through Suboxic Nitrogen Removal (Final Report)

The objective of this project was to advance two key technological components—aeration control strategies and process design methodologies—to support the development and broader adoption of suboxic biological nitrogen removal (SBNR). The project focused on achieving the following three goals: • Enhance Model Predictive Control (MPC) Technology: Advance the DO/Nmaster MPC platform from its initial 2018 pilot deployment at the Chico Water Resource Recovery Facility in California to full-scale integration. This included partnering with a blower technology commercialization partner and incorporating machine learning (ML) capabilities to enable nationwide deployment. • Bridge Knowledge Gaps in SBNR Process Design: Address fundamental gaps in SBNR process understanding through controlled pilot-scale testing at a dedicated pilot facility. These efforts supported the development of robust kinetic models to inform reliable SBNR control, operational strategies, and design frameworks. • Demonstrate Full-Scale Implementation of Low DO/SBNR with ML: Transition low dissolved oxygen (DO)/SBNR coupled with ML from pilot-scale trials to full-scale demonstration in flow-through biological nutrient removal (BNR) systems, with the goal of enabling scalable, nationwide adoption in activated sludge treatment processes. The project included demonstration of SBNR at the pilot scale as performed by Hampton Roads Sanitation District (HRSD) and at the full-scale as performed by the Los Angeles County Sanitation Districts' (LACSD) Pomona Water Reclamation Plant (POWRP).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Metagenomes and metagenome-assembled genomes from a nutrient removal plant at Los Angeles County Sanitation Districts (LACSD) that transitioned from high to low dissolved oxygen

Operating biological nutrient removal (BNR) wastewater treatment plants with low dissolved oxygen (DO) conditions can reduce energy costs. We report on five metagenomes and 492 metagenome-assembled genomes (MAGs) obtained from samples collected at the Pomona water reclamation plant before and after a DO reduction from 3.5 to 0.7 mg/L.

dissolved oxygen

Integrated Anaerobic Membrane Bioreactor (AnMBR) – electro assisted fermentation platform for total resource recovery from diverse wastewaters

The overall objective of the project was to demonstrate a successful wastewater resource recovery platform comprising an Anaerobic Membrane Bioreactor (AnMBR) to achieve >50% Carbon sequestration efficiency as Volatile Fatty Acids (VFAs) or as methane gas from agricultural (animal feeding operations) wastewater along with the generation of final water exceeding Biological Nutrient Removal (BNR) standards for indirect potable reuse by coupling with constructed wetlands has been successfully accomplished. The AnMBR achieved stable performance over 350 days, removing 80–90% of COD and BOD₅ and recovering methane (0.17±0.07 L CH4/g COD at 66.5±0.03% v/v) at 3-5 LMH flux and 5-9 days HRT with 3-5% w/v total solids. Phosphorus recovery via CaO addition in an 80-L coagulation-flocculation-sedimentation unit ranged from 40.6% to 99.7%, yielding products with 11.4–13.6% P content and citric acid solubility of 32–38.6% P, comparable to rock phosphate mineral. Ammonium adsorption achieved ~94.5% recovery with exchange capacity of 10 – 16 g NH4-N/kg clinoptilolite. The CW polishing step met Kansas discharge standards for BOD5 and TN (<30 and <10 mg /L,) and approached the TP standard (~2.5 – 4 mg P/L). These findings have either already resulted in two peer reviewed publications, two patent applications, and one publication in conference proceedings.

42 ENGINEERING

LACSD BNR Pilot Plant Metagenomes

In this study, we aimed to evaluate Biological Nutrient Removal (BNR) and investigate microbial community changes when the DO is reduced in the aerated portions of wastewater treatment trains. We present a dataset of metagenomes obtained from activated sludge collected from the Los Angeles Sanitary District BNR pilot plant at the beginning of operation, when the DO was high, and at the end of operation, when the DO was low.

metagenome

Data for Identifying the best high-biomass sorghum hybrids based on biomass yield potential and feedstock quality affected by nitrogen fertility management under various environments

Data were collected from agronomy fields in Urbana and Ewing, IL, during the 2022 and 2023 growing seasons. The dataset includes dry biomass yield, nitrogen, phosphorus, and potassium concentrations and removals, and chemical composition elements (cellulose, hemicellulose, lignin, and soluble fractions) for 13 high-biomass sorghum hybrids. data_sharing.xlsx contains 20 columns and 104 rows. Below is the explanation of all variables in the file: Year: 2022; 2023 Location: Urbana, IL; Ewing, IL N rate (kg-N/ha): 0; 112 Hybrid #: H1-H13 Pedigree: Pedigree for 13 hybrids Dry biomass yield (Mg/ha): Aboveground dry biomass yield N (g/kg): Nitrogen concentration in plant tissue P (g/kg): Phosphorus concentration in plant tissue K (g/kg): Potassium concentration in plant tissue N (kg/ha): Nitrogen removal by aboveground biomass P (kg/ha): Phosphorus removal by aboveground biomass K (kg/ha): Potassium removal by aboveground biomass Cellulose (g/kg): Cellulose concentration in plant tissue Hemicellulose (g/kg): Hemicellulose concentration in plant tissue Lignin (g/kg): Lignin concentration in plant tissue Soluble (g/kg): Soluble concentration in plant tissue Cellulose (Mg/ha): Cellulose content in aboveground biomass Hemicellulose (Mg/ha): Hemicellulose content in aboveground biomass Lignin (Mg/ha): Lignin content in aboveground biomass Soluble (Mg/ha): Soluble content in aboveground biomass

environmental adaptability

Addressing genome scale design tradeoffs in Pseudomonas putida for bioconversion of an aromatic carbon source

Genome-scale metabolic models (GSMM) are commonly used to identify gene deletion sets that result in growth coupling and pairing product formation with substrate utilization and can improve strain performance beyond levels typically accessible using traditional strain engineering approaches. However, sustainable feedstocks pose a challenge due to incomplete high-resolution metabolic data for non-canonical carbon sources required to curate GSMM and identify implementable designs. Here we address a four-gene deletion design in the Pseudomonas putida KT2440 strain for the lignin-derived non-sugar carbon source, p-coumarate (p-CA), that proved challenging to implement. We examine the performance of the fully implemented design for p-coumarate to glutamine, a useful biomanufacturing intermediate. In this study glutamine is then converted to indigoidine, an alternative sustainable pigment and a model heterologous product that is commonly used to colorimetrically quantify glutamine concentration. Through proteomics, promoter-variation, and growth characterization of a fully implemented gene deletion design, we provide evidence that aromatic catabolism in the completed design is rate-limited by fumarase hydratase (FUM) enzyme activity in the citrate cycle and requires careful optimization of another fumarate hydratase protein (PP_0897) expression to achieve growth and production. A double sensitivity analysis also confirmed a strict requirement for fumarate hydratase activity in the strain where all genes in the growth coupling design have been implemented. Metabolic cross-feeding experiments were used to examine the impact of complete removal of the fumarase hydratase reaction and revealed an unanticipated nutrient requirement, suggesting additional functions for this enzyme. While a complete implementation of the design was achieved, this study highlights the challenge of completely inactivating metabolic reactions encoded by under-characterized proteins, especially in the context of multi-gene edits.

59 BASIC BIOLOGICAL SCIENCES

Quantitative DNA Stable Isotope Probing Identifies Active Microorganisms Assimilating Volatile Fatty Acids in Full-Scale Enhanced Biological Phosphorus Removal Processes

Enhanced biological phosphorus removal (EBPR) systems often rely on exogenous carbon sources, such as volatile fatty acids (VFAs), to achieve higher P removal. Here, we employed DNA quantitative stable isotope probing (qSIP) using two VFAs, acetate and propionate, in cyclic anaerobic/aerobic incubations to assess their effects on P cycling and microbial activity with biomass from two full-scale EBPR water resource-recovery facilities that utilize VFA addition. We found that anaerobic VFA uptake preferences differed within known groups of PAOs, such as Candidatus Accumulibacter and Tetrasphaera-affiliated members (e.g., Ca. Phosphoribacter), between the two biomasses. The combination of qSIP with metagenomics identified isotopically labeled phages that were linked to active PAOs, highlighting their potential roles in modulating EBPR community composition and activity. The highest levels of anaerobic labeling from acetate were in genomes belonging to Saccharimonadales and Rickettsiales, which are generally host-associated with bacteria and eukaryotes, respectively. Furthermore, this finding highlights the possibility of cross-feeding between PAO hosts and their parasites or predators, as well as the role of so-far uncharacterized organisms participating in carbon cycling under EBPR conditions. Collectively, these results expand our understanding of the ecological interactions involved in communities anaerobically uptaking VFAs and cycling P that are central to EBPR.

Polyphosphate accumulating organisms

Morphotype-resolved characterization of microalgal communities in a nutrient recovery process with ARTiMiS flow imaging microscopy

Microalgae-driven nutrient recovery represents a promising technology for phosphorus removal from wastewater while simultaneously generating biomass that can be valorized to offset treatment costs. As full-scale processes come online, system parameters including biomass composition must be carefully monitored to optimize performance and prevent culture crashes. In this study, flow imaging microscopy (FIM) was leveraged to characterize microalgal community composition in near real-time at a full-scale municipal wastewater treatment plant (WWTP) in Wisconsin, USA, and population and morphotype dynamics were examined to identify relationships between water chemistry, biomass composition, and system performance. Two FIM technologies, FlowCam and ARTiMiS, were evaluated as monitoring tools. ARTiMiS provided a more accurate estimate of total system biomass, and estimates derived from particle area as a proxy for biovolume yielded better approximations than particle counts. Deep learning classification models trained on annotated image libraries demonstrated equivalent performance between FlowCam and ARTiMiS, and convolutional neural network (CNN) classifiers proved significantly more accurate when compared to feature table-based dense neural network (DNN) models. Across a two-year study period, Scenedesmus spp. appeared most important for phosphorus removal, and were negatively impacted by elevated temperatures and increase in nitrite/nitrate concentrations. Chlorella and Monoraphidium also played an important role in phosphorus removal. For both Scenedesmus and Chlorella, smaller morphological types were more often associated with better system performance, whereas larger morphotypes likely associated with stress response(s) correlated with poor phosphorus recovery rates. Furthermore, these results demonstrate the potential of FIM as a critical technology for high-resolution characterization of industrial microalgal processes.

59 BASIC BIOLOGICAL SCIENCES

Surface water nitrogen and sediment potential nitrate reduction rates, nutrient stocks, and stable isotopes from nine wetlands at the Tanglewood Biological Station, Alabama

This dataset supports a broader study investigating wetland hydrologic and biogeochemical responses to inundation disturbances. Bimonthly surface water and sediment sampling events were conducted at nine wetland sites situated within the Tanglewood Biological Station in Alabama from April 2023 to February 2024. The contents included in the data package include surface water nitrogen (nitrogen oxides and ammonium) and sediment potential nitrate reduction rates (measured as potential denitrification and dissimilatory nitrate reduction to ammonium processing), nutrient stocks (total carbon, total nitrogen, and organic matter), and stable isotopes (carbon and nitrogen). Water level data related to each wetland location can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/2530253 (Kirker et al., 2024) and related water geochemistry data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3001967 (Forbes et al., 2025). In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) field metadata and international generic sample numbers (IGSNs); (4) readme; (5) the field protocol; and (6) a subfolder with sample data. The sample data subfolder contains (1) sediment potential denitrification rate, (2) sediment potential dissimilatory nitrate reduction to ammonium (DNRA) rate, (3) sediment total carbon and nitrogen content, (4) sediment stable isotopes (delta nitrogen-15 and delta carbon-13), (5) sediment percent organic matter, (6) surface water nitrous oxides, (7) surface water ammonium, and (8) methods codes. All files are .csv or .pdf.

Ammonium

Response of Subsurface Nitrogen-Cycling Microbial Communities to Environmental Fluctuations (Final Technical Report)

Riparian floodplains are dynamic ecosystems linking terrestrial and riverine systems. These floodplains experience hydrological shifts such as changes in water table height, flooding, and drought and can be ‘hotspots’ of biogeochemical cycling due to shifting sediment moisture (and saturation) and subsurface exchanges of water, nutrients, and other compounds across different sediment layers. Subsurface microbial communities are the primary drivers of biogeochemical processes in floodplains, and thus their structure and function can directly influence both surface and groundwater quality. The microbial nitrogen (N) cycle is particularly important in floodplains as it affects nutrient availability and removal. Two functional guilds of chemoautotrophic (i.e. CO2-fixing) microorganisms are responsible for the first oxidative step of the N cycle, nitrification: ammonia-oxidizing archaea (AOA) and bacteria (AOB) catalyze the oxidation of ammonia to nitrite, while nitrite-oxidizing bacteria (NOB) oxidize nitrite to nitrate. Despite the critical role nitrification plays in N-cycling in both terrestrial and aquatic ecosystems, our understanding of the diversity, ecophysiology, and activity of nitrifying organisms in subsurface floodplain soils/sediments is extremely limited. To help address this critical knowledge gap, the overarching goal of this project was to determine how shifts in key environmental parameters and gradients impact microbial N-cycling communities/processes, with particular emphasis on nitrification, within hydrologically-variable floodplain sediments in the Wind River Basin near Riverton, Wyoming. The three specific objectives of this project were to: (1) to associate in situ environmental drivers of N cycling with distinct functional guilds; (2) determine the guild response to variation in key ecosystem drivers; and (3) develop a dynamic ecosystem model of the microbial N cycle with the Riverton subsurface using community genomic and biogeochemical data collected in the first two objectives. Over the course of this project, we employed both 16S rRNA gene amplicon sequencing and genome-resolved metagenomics to examine the phylogenetic diversity and metabolic potential of subsurface nitrifier communities within 68 samples collected across multiple sites, depths, and time points within the Riverton floodplain, allowing for both spatial and temporal investigations at different scales. This project benefitted tremendously from recent advances in high-throughput sequencing technologies coupled with dramatic improvements in the computational tools and algorithms available for analyzing such large, complex genomic datasets. By pairing these cutting-edge genomic approaches with depth-resolved sampling and detailed geochemical analyses of the Riverton floodplain, we have gained novel insights into the structure and function of subsurface nitrifier communities in relation to both hydrology and biogeochemistry. This project resulted in the most detailed and comprehensive characterization of N-cycling floodplain microbial communities to date and will hopefully inspire and pave the way for future studies using similar approaches in other floodplains. Indeed, such information is critical for understanding subsurface biogeochemical cycling and how elemental stores are altered from perturbations initiated by the water cycle within floodplains. Finally, because of the terrestrial-aquatic nature of the Riverton floodplain, results from this project are also of relevance to disciplines such as soil science, estuarine science, limnology & oceanography, biogeochemistry, geobiology, environmental engineering, as well as genomics and data science.

54 ENVIRONMENTAL SCIENCES

Data for Multisite Field Evaluation of Oil Accumulation and Agronomic Performance in Grain and Sweet Sorghums Engineered for Lipid Hyperaccumulation

Oil sorghum (OS) has been developed by engineering grain (TX430) and sweet (Ramada) genetic backgrounds to accumulate triacylglycerols (TAG) in vegetative tissues as an energy-dense feedstock for sustainable aviation fuel (SAF) and other biofuels. This study evaluated two TX430 OS lines (TxHO-2, TxHO-3) and two Ramada OS lines (RmHO-1, RmHO-2) alongside wild-type (WT) lines in NE and IL over 2 years (2023–2024) to quantify genotype × environment effects on agronomic performance and TAG accumulation. Across four environments, TX430 OS lines showed average TAG concentrations of 15.0 g kg−1 in leaves and 12.8 g kg−1 in stems, approximately 19-fold higher than WT. Ramada OS lines accumulated 26.1 g kg−1 in leaves and 12.3 g kg−1 in stems, approximately 25-fold and 13-fold increases over WT, respectively. OS lines in TX430 exhibited an 18% reduction in biomass (8.4 vs. 9.9 Mg ha−1 for WT), while Ramada OS lines had similar WT biomass (18.3 vs. 19.9 Mg ha−1 for WT). Among TX430 OS lines, TxHO-2 achieved the highest TAG yield (190 kg ha−1), while RmHO-1 led the Ramada lines (335 kg ha−1) due to higher biomass and similar TAG concentration. Enhanced TAG accumulation increased N, P, and K removal in TX430 lines but not in Ramada lines. Structural carbohydrate and ash concentration were unaffected. Overall, results confirm vegetative lipid accumulation as a viable strategy for high-biomass sorghum, supporting its potential as a dual-purpose feedstock for SAF. Future work should focus on minimizing biomass yield penalties and improving nutrient use efficiency in oil sorghum systems.

Agronomy