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Enregistrement W3197327331 · doi:10.7939/r3-1sgt-6q26

Hydrogen Sulfide Generation and Control in Sewer Systems with Drop Structures and Pump Stations

2021· article· en· W3197327331 sur OpenAlexaboutno aff
Zhi Feng Yang

Notice bibliographique

RevueUniversity of Alberta Library · 2021
Typearticle
Langueen
DomaineEngineering
ThématiqueAdvanced Sensor and Control Systems
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHydrogen sulfideEnvironmental scienceDrop (telecommunication)EngineeringMaterials scienceMetallurgyTelecommunicationsSulfur

Résumé

récupéré en direct d'OpenAlex

The build-up of hydrogen sulfide in sewer systems can lead to odor nuisances and corrosion of concrete sewers. The City of Edmonton, Alberta, Canada, like many other cities worldwide, is facing sewer odor nuisance and pipe corrosion issues. Field studies were carried out in the sanitary sewer trunk with drops and pump station in Steinhauer area and in the sewer trunk with drops in Bonnie Doon area to identify causes of H2S in both areas and the effect of drops on H2S release so as to develop proper odor control strategies. In addition, four bioreactors imitating force mains of pump stations were operated to evaluate sulfide generation rate. Ferric and nitrate were added into two of the four bioreactors to investigate their effects on sulfide control. Sulfide formation rates in the force mains were also evaluated in the field and continuous nitrate dosing was applied in the wet well of the Big Lake pump station to investigate its effectiveness on sulfide control. In Steinhauer area, relatively high concentrations of H2S were detected at the beginning and the end of the trunk with odor complaints. At the beginning of the trunk, sulfide emission was mainly caused by the increased stripping effect of the drop structures. The pump operation at the end of the trunk led to the long hydraulic retention time (HRT) of the sewage and the subsequent sulfide generation in the trunk and wet well. The calibrated sulfide generation models by using field measurements in the trunk were applied to assess the proposed mitigation strategy, pump operation optimization, and this strategy was found to be able to eliminate sulfide generation in the study trunk sewer. In Bonnie Doon area, the liquid sulfide concentration in the upstream trunk was low (less than 1.0 mg/L), and no H2S gas was detected in the head space. However, high H2S gas concentration was detected in the middle reach of the trunk due to the stripping effect of the three drops (2.7 m, 5.2 m, and 2.0 m) along the trunk. The released H2S at drops was transported to downstream trunk and tributaries in the sewer system and caused odor concerns at these locations. These drops played an important role on H2S release, and the overall H2S mass transfer coefficient at drops was much higher than that in normal gravity sewers. The overall oxygen and H2S mass transfer coefficient were estimated to be around 200 h-1 and 300 h-1 at first two drops, respectively. Sulfide controlled by ferric in the lab-scale bioreactor was only via chemical oxidation and precipitation and total sulfate reducing bacteria (SRB) population did not change. The heterotrophic nitrate reducing bacteria (hNRB), Thauera, outcompeted SRB for organic matter as electron donor as the dominant bacteria when nitrate was added at the beginning of the pump cycle. The sulfide generation was controlled by hNRB activities. A cost-effective nitrate dosing strategy is proposed to add the nitrate at the end of the pump cycle instead of at the beginning of the pump cycle which can save up to 75% nitrate dosage. The co-existence of sulfide and nitrate stimulated the development of nitrate-reducing, sulfide-oxidizing bacteria (NR-SOB), Sulfurovum, which was responsible for sulfide removal in the presence of nitrate. Both ferric and nitrate did not have long-lasting inhibitory/toxic effect on sulfate reduction. The sulfide production rates at the force mains of four pump stations were estimated to be 0.08~0.15 g/m2h under 20 ℃. The 1/2-order biofilm kinetics of DCOD was used to model the sulfide generation rate in the force main and the modelled rate constant for field trial was around 0.006. In the discharge manhole of the Big Lake pump station, sulfide concentration was measured at around 20 mg/L while the H2S gas concentration reached up to 400~500 ppm. A continuous dosing of 85 mg/L nitrate in the pump wet well could completely suppress the sulfide generation in the force main. An optimized dosing strategy is to add the nitrate at a location close to the point of sulfide control rather than in the wet well and the dosing rate should be proportional to the HRT of the wastewater in the between the point of nitrate addition and the end of the force main.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,019
Score d'incertitude au seuil0,038

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,004
Tête enseignante GPT0,145
Écart entre enseignants0,141 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2021
Routes d'admission1
Résumé présentoui

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