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Record W2252917411 · doi:10.2172/1040596

Selenium Speciation and Management in Wet FGD Systems

2012· report· en· W2252917411 on OpenAlexaff
G. Blythe, Dirk Wallschläger, Paul Chu

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicCoal and Its By-products
Canadian institutionsTrent University
FundersU.S. Department of Energy
KeywordsSeleniumScrubberChemistrySelenateWet scrubberEnvironmental chemistryManganeseGenetic algorithmOrganic chemistry

Abstract

fetched live from OpenAlex

This report discusses results from bench- and pilot-scale simulation tests conducted to determine the factors that impact selenium speciation and phase partitioning in wet FGD systems. The selenium chemistry in wet FGD systems is highly complex and not completely understood, thus extrapolation and scale-up of these results may be uncertain. Control of operating parameters and application of scrubber additives have successfully demonstrated the avoidance or decrease of selenite oxidation at the bench and pilot scale. Ongoing efforts to improve sample handling methods for selenium speciation measurements are also discussed. Bench-scale scrubber tests explored the impacts of oxidation air rate, trace metals, scrubber additives, and natural limestone on selenium speciation in synthetic and field-generated full-scale FGD liquors. The presence and concentration of redox-active chemical species as well as the oxidation air rate contribute to the oxidation-reduction potential (ORP) conditions in FGD scrubbers. Selenite oxidation to the undesirable selenate form increases with increasing ORP conditions, and decreases with decreasing ORP conditions. Solid-phase manganese [Mn(IV)] appeared to be the significant metal impacting the oxidation of selenite to selenate. Scrubber additives were tested for their ability to inhibit selenite oxidation. Although dibasic acid and other scrubber additives showed promise in early clear liquor (sodium based and without calcium solids) bench-scale tests, these additives did not show strong inhibition of selenite oxidation in tests with higher manganese concentrations and with slurries from full-scale wet FGD systems. In bench-tests with field liquors, addition of ferric chloride at a 250:1 iron-to-selenium mass ratio sorbed all incoming selenite to the solid phase, although addition of ferric salts had no impact on native selenate that already existed in the field slurry liquor sample. As ORP increases, selenite may oxidize to selenate more rapidly than it sorbs to ferric solids. Though it was not possible to demonstrate a decrease in selenium concentrations to levels below the project'ale testing were evident at the pilot scale. Specifically, reducing oxidation air rate and ORP tends to either retain selenium as selenite in the liquor or shift selenium phase partitioning to the solid phase. Oxidation air flow rate control may be one option for managing selenium behavior in FGD scrubbers. Units that cycle load widely may find it more difficult to impact ORP conditions with oxidation air flow rate control alone. Because decreasing oxidation air rates to the reaction tank showed that all new selenium reported to the solids, the addition of ferric chloride to the pilot scrubber could not show further improvements in selenium behavior. Ferric chloride addition did shift mercury to the slurry solids, specifically to the fine particles. Several competing pathways may govern the reporting of selenium to the slurry solids: co-precipitation with gypsum into the bulk solids and sorption or co-precipitation with iron into the fine particles. Simultaneous measurement of selenium and mercury behavior suggests a holistic management strategy is best to optimize the fate of both of these elements in FGD waters. Work conducted under this project evaluated sample handling and analytical methods for selenium speciation in FGD waters. Three analytical techniques and several preservation methods were employed. Measurements of selenium speciation over time indicated that for accurate selenium speciation, it is best to conduct measurements on unpreserved, filtered samples as soon after sampling as possible. The capital and operating costs for two selenium management strategies were considered: ferric chloride addition and oxidation air flow rate control. For ferric chloride addition, as might be expected the reagent makeup costs dominate the overall costs, and range from 0.22 to 0.29 mills/kWh. For oxidation air flow rate control, a cursory comparison of capital costs and turndown capabilities for multi-stage and single-stage centrifugal blowers and several flow control methods was completed. For greenfield systems, changing the selection of blower type and flow control method may have payback periods of 4 to 5 years or more if based on energy savings alone. However, the benefits to managing redox chemistry in the scrubber could far outweigh the savings in electricity costs under some circumstances.

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.

How this classification was reachedexpand

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: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.756
Threshold uncertainty score1.000

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)0.0010.000

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 head0.048
GPT teacher head0.227
Teacher spread0.179 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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