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Source Profiles of Particulate Matter Emissions from a Pilot-Scale Boiler Burning North American Coal Blends

2001· article· en· W2041448825 on OpenAlex
S. Win Lee

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Air & Waste Management Association · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsParticulatesEnvironmental scienceWaste managementCoalBoiler (water heating)Environmental engineeringEnvironmental chemistryEngineeringChemistry

Abstract

fetched live from OpenAlex

Recent awareness of suspected adverse health effects from ambient particulate matter (PM) emission has prompted publication of new standards for fine PM with aerodynamic diameter less than 2.5 microm (PM2.5). However, scientific data on fine PM emissions from various point sources and their characteristics are very limited. Source apportionment methods are applied to identify contributions of individual regional sources to tropospheric particulate concentrations. The existing industrial database developed using traditional source measurement techniques provides total emission rates only, with no details on chemical nature or size characteristics of particulates. This database is inadequate, in current form, to address source-receptor relationships. A source dilution system was developed for sampling and characterization of total PM, PM2.5, and PM10 (i.e., PM with aerodynamic diameter less than 10 pm) from residual oil and coal combustion. This new system has automatic control capabilities for key parameters, such as relative humidity (RH), temperature, and sample dilution. During optimization of the prototype equipment, three North American coal blends were burned using a 0.7-megawatt thermal (MWt) pulverized coal-fired, pilot-scale boiler. Characteristic emission profiles, including PM2.5 and total PM soluble acids, and elemental and carbon concentrations for three coal blends are presented. Preliminary results indicate that volatile trace elements such as Pb, Zn, Ti, and Se are preferentially enriched in PM2.5. PM2.5 is also more concentrated in soluble sulfates relative to total PM. Coal fly ash collected at the outlet of the electrostatic precipitator (ESP) contains about 85-90% PM10 and 30-50% PM2.5. Particles contain the highest elemental concentrations of Si and Al while Ca, Fe, Na, Ba, and K also exist as major elements. Approximately 4-12% of the materials exists as soluble sulfates in fly ash generated by coal blends containing 0.2-0.8% sulfur by mass. Source profile data for an eastern U.S. coal show good agreement with those reported from a similar study done in the United States. Based on the inadequacies identified in the initial sampling equipment, a new, plume-simulating fine PM measurement system with modular components for field use is being developed for determining coal combustion PM source profiles from utility boiler stacks.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.352

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)0.0000.000

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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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