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Record W4280516529 · doi:10.1002/wer.10727

Full‐scale transition from denitrification to partial denitrification–anammox (PdNA) in deep‐bed filters: Operational strategies for and benefits of PdNA implementation

2022· article· en· W4280516529 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWater Environment Research · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsnot available
FundersHampton Roads Sanitation DistrictHuman Resources and Skills Development CanadaEnvironmental Protection AgencyDistrict of Columbia Water and Sewer AuthorityWater Research Foundation
KeywordsAnammoxDenitrificationEnvironmental engineeringAmmoniumChemistryEffluentAerationPulp and paper industryNitrateEnvironmental chemistryEnvironmental scienceNitrogenEngineering

Abstract

fetched live from OpenAlex

Abstract This study shows for the first time more than 2 years of operation of a mainstream anammox application at full‐scale under temperate climate. This implementation of partial denitrification–anammox (PdNA) in deep bed filters at the HRSD York River treatment plant was demonstrated to achieve the benefits of shortcut nitrogen removal without nitrite oxidizing bacteria (NOB) out‐selection. The transition from denitrification to PdNA filters required bleeding ammonium to the filters using an optimized ammonium versus NOx (AvN) control in the upstream aeration tanks and maintaining a nitrate residual in the filter effluent through feedforward/feedback control. The latter actions led to savings of 85% in methanol, 100% in alkalinity, and 35% in capacity enhancement. Up to 6 mg NH 4 + ‐N/L with an average of 2.2 ± 0.98 mg NH 4 + ‐N/L was removed through the anammox pathway, which accounted for about 15% of the overall plant nitrogen removal. Anammox enrichment was confirmed by activity testing and molecular analysis. The large excess of AnAOB capacity present in the filters (5–10 times more than normal operation) resulted in stable and reliable operation through winter conditions and showed potential for further intensification. Practitioner Points For the first time, long‐term mainstream anammox was established full‐scale through PdNA implementation in deep‐bed filters. PdNA implementation required upstream aeration control optimization to provide a blend of ammonium and nitrate to the filters. Efficient anammox enrichment and retention resulted in reliable PdNA performance under different seasonal and influent conditions. PdNA implementation resulted in significant methanol and alkalinity savings and upstream capacity enhancement as ammonia removal depended less on aerobic nitrification. In the event of NOB out‐selection and presence of nitrite, carbon savings in PdNA polishing filters can be enhanced via partial nitritation–anammox.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.299
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it