A study of the dispersion of vinyl chloride from a renewable energy facility located in Ontario, Canada
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.
Bibliographic record
Abstract
This study compared the results of modelling vinyl chloride emissions from a renewable energy generation plant, located in the City of Kawartha Lakes, Ontario, Canada, using American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) and California Puff (CALPUFF). The plant utilizes landfill gas emissions from the existing Lindsay/Ops landfill to fuel an on-site generator, and thus generate electricity. The modelling was performed for July 20, 2013 and November 17, 2013, from 00h00 local standard time (LST) to 23h00 LST for both days. The results showed that modelling contaminant dispersion using CALPUFF resulted in significantly higher concentrations than when modelling with AERMOD. This may be due to the several limitations of AERMOD, including its assumptions of straight line trajectory, steady-state and a uniform atmosphere, its inaccuracy when determining long-range transport, and its inability to retain the memory of the previous hours' emissions. The CALPUFF modelling results also showed that the contaminant concentration may, in some instances, be higher farther away from the source than closer to it. The results also show that the concentration of vinyl chloride on July 20, 2013, as modelled by CALPUFF, exceeds the applicable regulatory limit. Thus, it is recommended to use CALPUFF instead of AERMOD to assess the dispersion of emissions from a facility more conservatively. Using CALPUFF will also ensure that the dispersion is assessed further away from the emissions sources as well as nearer to them. The appropriate selection of dispersion models is especially important when the results of one of the models may deem the facility's emissions non-compliant with the applicable regulatory limits.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it