Evaluating the impact of urban parks on the thermal comfort during a heat wave episode in a Mediterranean city
Bibliographic record
Abstract
The Mediterranean basin is expected to experience an increase in intensity and frequency of heat wave events. Additionally, heat peaks are exacerbated by the low albedo of urban materials and the heat island effect of urban areas. To reduce heat-related discomfort and health risks, urban planners aim to implement green infrastructures to regulate temperatures thanks to their transpiration cooling effect. For example, the Metropolitan Area of Barcelona (AMB) has created a metropolitan network of “climate shelters”, which are public spaces (both indoor and outdoor) where urban dwellers can find better climatic conditions. Urban parks can be considered “climate shelters” if two requirements are met: the NDVI of the vegetation is higher than 0.4 and the extension of the park is bigger than 0.5 ha. However, given the dense urban edification and space limitation, we wanted to explore the thermal regulation capacity of smaller urban parks which are easier to implement. In this study, we present the results of a micrometeorological measurement campaign to assess the temporal and spatial variations of thermal comfort in parks of different sizes in the AMB during a heatwave episode in July 2022. The goals of this study are to determine the impact on human biometeorology of urban design in the construction of urban parks for facing heatwave episodes and to check the classification requirements for the “climate shelters”.Using a mobile human-biometeorological weather station (MaRTy cart), we registered the microclimatic factors affecting thermal exposure at different points inside and outside the parks. From the microclimatic measurements we derived the Universal Thermal Climate Index (UTCI). Additional characterization of the measurement points consisted in sky-view-factor estimations and 360o vegetation and impervious view factors. Throughout the campaign period and measurement hours (14:00, 15:00 and 20:00 LT), the UTCI varied between 29.5 oC (moderate heat stress) and 41.9 oC (very strong heat stress). During the early afternoon, when air temperatures and heat stress are higher, the UTCI is lower inside of the parks, by a difference that ranges from 1.0 oC to 3.2 oC. The sky-view-factor is responsible for 43 to 58% of the observed variability in the UTCI, pointing out the importance of tree shadowing inside the parks. Air temperature has also a clear influence on thermal comfort, explaining between 17 and 50% of the UTCI variability. Although air temperature reductions in smaller parks are not as significant as in the “climate shelter” park, there are vegetation zones inside the smaller parks with comparable reductions in the UTCI. The results show that small parks can provide thermal comfort in similar capacity as bigger parks classified as “climate shelters”.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".