Human Energy Budget Modeling in Urban Parks in Toronto and Applications to Emergency Heat Stress Preparedness
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The current study tests applications of the Comfort Formula (COMFA) energy budget model by assessing the moderating effects of urban parks in contrast to streets, and it also looks at the influence of park types (“open” or “treed”). Exploration into energy budget modeling is based on empirical meteorological data collected in Toronto, Ontario, Canada, on fair-weather days plus the effects of a heat wave and climate change, at various metabolic activity levels. Park cooling temperature intensities ranged from 3.9° to 6.0°C, yet human energy budgets were more closely correlated to incoming solar radiation than to air temperature. A strong linear dependence was found, with absorbed radiation (correlation coefficient squared r 2 = 0.858) explaining the largest fraction of energy budget output. Hence, although the four parks that were examined are classified as urban green space, the distinctive treed areas showed a greater budget decrease than did open park areas (−25.5 W m −2 ). The greatest difference in budget decrease was found when modeling the highest metabolic rate, giving −20 W m −2 for “whole park,” −32 W m −2 for treed sections, and −3 W m −2 in open park areas. These results are intuitive within energy budget modeling and indicate that blocking radiant energy is a vital aspect in lowering high budgets under the conditions tested. Strong empirical support was provided through successful prediction of emergency-response calls during a heat wave in Toronto (5–7 July 2010) and surrounding days. Calls were found to be significantly dependent on the energy budget estimations ( r 2 = 0.860). There is great potential for outdoor energy budget modeling as a meaningful guide to heat stress forecasting, future research, and application in bioclimatic urban design for improving thermal comfort.
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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 | 0.000 | 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