Impact of Relative Humidity on HVAC Filters Loaded with Hygroscopic and Non-Hygroscopic Particles
Bibliographic record
Abstract
The key characteristics of an air filter—flow resistance and filtration efficiency—are strongly affected by captured particles. The impact of exposing loaded heating, ventilating, and air conditioning air filters to a relative humidity (RH) other than that experienced during loading is investigated to develop an understanding of the role of RH throughout filter operation. Flat sheets of commercial filter media were loaded with hygroscopic, non-hygroscopic, or a mixture of particles in a laboratory apparatus. When filters loaded with hygroscopic particles in dry air were exposed to an elevated RH of 40%, the flow resistance reduced by up to 47%, depending on the filter being tested. Investigation of filter efficiency before and after changes in RH in the same samples shows reductions of up to 11 percentage points in the 130-nm size range. Further increasing RH causes additional drops in flow resistance and efficiency whereas reverting back to a lower humidity does not change the filter characteristics. The irreversibility of the particle-loaded filter characteristics implies that the RH increases are associated with an irreversible change in the particle structure. The response to humidity was reduced if an aerosol mixture of hygroscopic and non-hygroscopic particles is used. Exposure of filters loaded with only non-hygroscopic particles does not show the same dependence on RH. Small increases in growth factor for RH changes below deliquescence, causing morphological changes in captured particle aggregates, is a potential explanation for the changes observed. Copyright 2015 American Association for Aerosol Research
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".