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Record W1545205841 · doi:10.4271/2000-01-1865

Tailpipe Emissions Comparison Between Propane and Natural Gas Forklifts

2000· article· en· W1545205841 on OpenAlexaffabout
Baljit Dhaliwal, David Checkel

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2000
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPropaneNatural gasEnvironmental scienceWaste managementProcess engineeringComputer scienceChemistryEngineering

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">It is commonly stated that natural gas-fueled forklifts produce less emissions than propane-fueled forklifts. However, there is relatively little proof. This paper reports on a detailed comparative study at one plant in Edmonton, Canada where a fleet of forklift trucks is used for indoor material movement. (For convenience, the acronym NGV, ie. Natural Gas Vehicle is used to designate natural gas-fueled and LPG, ie. Liquified Petroleum Gas, is used to designate propane-fueled forklifts).</div> <div class="htmlview paragraph">Until recently the forklift trucks (of various ages) were LPG carburetted units with two-way catalytic converters. Prompted partially by worker health concerns, the forklifts were converted to fuel injected, closed-loop controlled NGV systems with three-way catalytic converters. The NGV-converted forklifts reduced emissions by 77% (NO<sub>X</sub>) and 76% (CO) when compared to just-tuned LPG forklifts. After a period of operation, LPG forklifts drifted out of tune while the NGV-converted forklifts maintained similarly low emission levels. In this condition, the NGV-converted forklifts produced lower emissions by 97% (CO) and 84% (NO<sub>X</sub>). Forklifts with older LPG fuel systems tended to drift out of tune faster and produced much higher emissions than the newest ones. With conversion to new NGV fuel injection systems, the emissions of both old and new forklifts were reduced to essentially the same low levels. Tests also simulated maintenance failures on the NGV fuel systems. In event of a complete catalyst failure, the NGV systems provided substantially lower emissions than the LPG systems because their engine-out emissions were lower, (57% less CO and 27% less NO<sub>X</sub>). Also, the Three-way catalysts had a much higher effectiveness with the NGV fuel system than when installed on the carbureted propane systems. An exhaust gas oxygen sensor failure put the NGV fuel systems into open-loop mode but their emissions were still lower than normal operation on LPG, (92% less CO and 73% less NO<sub>X</sub>). An engine coolant temperature sensor failure only slightly degraded the emissions of the NGV fuel systems.</div>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.011
GPT teacher head0.247
Teacher spread0.235 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations11
Published2000
Admission routes2
Has abstractyes

Explore more

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