Oxygen Transfer in Trickling Filters

Logan, Bruce E.

doi:10.1061/(asce)0733-9372(1993)119:6(1059)

Cited by 22 publications

(13 citation statements)

References 11 publications

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“…The value of r02, max varies with hydraulic loading, wastewater temperature, media characteristics, and can be calculated using the Logan trickling filter model (Logan, 1993(Logan, , 1995Logan et al, 1987).…”

Section: Rn-rn'maxg-n +A /) E (I)mentioning

confidence: 99%

Of: **Symbolic Regression of Upstream, Stormwater, and Tributary E. Coli Concentrations Using River Flows, Jagupilla, S. C. K.; Vaccari, D. A.; Miskewitz, R.; Su, T.‐L.; Hires, R. I. (2015), 87, 26‐34; correction 87,** 576.

Minervini¹,

Jagupilla²,

Vaccari³

et al. 2016

Water Environment Research

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Colfax, WA, operates an aerated lagoon to achieve compliance with its National Pollutant Discharge Elimination System (NPDES) permit, which currently requires biochemical oxygen demand (BOD) and total suspended solids (TSS) removal. However, ammonia removal may soon be required, and Colfax is considering a nitrifying trickling filter (NTF) that would allow them to also maintain the lagoons. To obtain data from which to ultimately design a full-scale system, a four-year NTF pilot study was performed. Results demonstrated that an NTF would be an effective, reliable NH3 removal method and could produce effluent NH3 concentrations < 1 .0 mg/L. NTF performance was characterized by zero-and first-order kinetics; zero-order rates correlated with influent NH3 concentrations and mass load. Utilizing

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Section: Rn-rn'maxg-n +A /) E (I)mentioning

confidence: 99%

Of: **Symbolic Regression of Upstream, Stormwater, and Tributary E. Coli Concentrations Using River Flows, Jagupilla, S. C. K.; Vaccari, D. A.; Miskewitz, R.; Su, T.‐L.; Hires, R. I. (2015), 87, 26‐34; correction 87,** 576.

Minervini¹,

Jagupilla²,

Vaccari³

et al. 2016

Water Environment Research

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“…Other parameters of importance in establishing the oxygen transfer rate of the media are application rate and temperature (Parker et al,1989, Logan, 1993. Nitrification in Moving Bed Biofilm Reactors (MBBRs) is similarly limited by oxygen transfer.…”

Section: Technology Limitationsmentioning

confidence: 99%

Improving Nitrification through Bioaugmentation

Parker¹,

Wanner²

2007

proc water environ fed

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The high costs of upgrading treatment plants for either nitrification or nutrient removal has spurred many investigators to examine bioaugmentation as a means to increase nitrification rates and thereby reduce the costs (and space requirements) for nitrification. In the case of biological nutrient removal (BNR) plants, this would allow release of reactor space to accommodate either nitrogen removal or phosphorus removal or both. In this paper, two types of bioaugmentation schemes are reviewed, external and in situ. Both types apply to activated sludge systems, while only in situ schemes apply to fixed film systems. The advantage of external bioaugmentation schemes is that the promotion of nitrification within the mainstream process can be decoupled from its aerobic SRT. The advantage of in situ schemes is that there is less concern about the loss of activity of the seed nitrifiers when transferred to the mainstream process, because their conditions of growth are similar to those prevalent in the mainstream process. The literature is reviewed on all process types, and new information is provided on the Bioaugmentation R (BAR) process which has seen the broadest full-scale applications of any bioaugmentation scheme. The various forms of bioaugmentation are compared and contrasted and the practical limitations in their implementation are reviewed.

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“…The value of r ðO2; maxÞ can be estimated using the Logan trickling filter model (Logan, 1993(Logan, , 1995Logan et al, 1987); Parker et al (1995) presents some r ðO2; maxÞ values for cross-flow plastic media.…”

Section: Introductionmentioning

confidence: 99%

Design Model Parameter Analysis for Nitrifying Trickling Filters

Coats

2016

Water Environment Research

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Nitrifying trickling filters (NTFs) represent an effective technology for water resource recovery facilities (WRRFs) to achieve compliance with ammonia-N permits. However, while the potential benefits of NTFs are many, the design methods and associated parameter databases are underdeveloped. Research herein focused on analysis of pilot-scale NTF data to develop enhanced design guidance. r values ranged from 1.19-3.38 gN m*d, and correlated with influent ammonia-N concentration and loading. The transition concentration from r ranged from 0.9-22.2 mgN/L, and correlated with ammonia-N loading. Zero-order nitrification ranging from 0.24-1.58 gN m*d was observed down-gradient of r. First-order nitrification was not observed, nor was there a strong exponential correlation for decreasing nitrification rate. To translate results to NTF media different from that utilized, a relationship between the NTF media effectiveness parameter, E, and r was established. Collectively, the data presented enhances the engineer's ability to model and design NTFs.

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Oxygen Transfer in Trickling Filters

Cited by 22 publications

References 11 publications

Of: **Symbolic Regression of Upstream, Stormwater, and Tributary E. Coli Concentrations Using River Flows, Jagupilla, S. C. K.; Vaccari, D. A.; Miskewitz, R.; Su, T.‐L.; Hires, R. I. (2015), 87, 26‐34; correction 87,** 576.

Of: **Symbolic Regression of Upstream, Stormwater, and Tributary E. Coli Concentrations Using River Flows, Jagupilla, S. C. K.; Vaccari, D. A.; Miskewitz, R.; Su, T.‐L.; Hires, R. I. (2015), 87, 26‐34; correction 87,** 576.

Improving Nitrification through Bioaugmentation

Design Model Parameter Analysis for Nitrifying Trickling Filters

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Oxygen Transfer in Trickling Filters

Cited by 22 publications

References 11 publications

Of: Symbolic Regression of Upstream, Stormwater, and Tributary E. Coli Concentrations Using River Flows, Jagupilla, S. C. K.; Vaccari, D. A.; Miskewitz, R.; Su, T.‐L.; Hires, R. I. (2015), 87, 26‐34; correction 87, 576.

Of: Symbolic Regression of Upstream, Stormwater, and Tributary E. Coli Concentrations Using River Flows, Jagupilla, S. C. K.; Vaccari, D. A.; Miskewitz, R.; Su, T.‐L.; Hires, R. I. (2015), 87, 26‐34; correction 87, 576.

Improving Nitrification through Bioaugmentation

Design Model Parameter Analysis for Nitrifying Trickling Filters

Contact Info

Product

Resources

About

Of: **Symbolic Regression of Upstream, Stormwater, and Tributary E. Coli Concentrations Using River Flows, Jagupilla, S. C. K.; Vaccari, D. A.; Miskewitz, R.; Su, T.‐L.; Hires, R. I. (2015), 87, 26‐34; correction 87,** 576.

Of: **Symbolic Regression of Upstream, Stormwater, and Tributary E. Coli Concentrations Using River Flows, Jagupilla, S. C. K.; Vaccari, D. A.; Miskewitz, R.; Su, T.‐L.; Hires, R. I. (2015), 87, 26‐34; correction 87,** 576.