Hidden Health Opportunities: The Role of Building Standards in Adapting to Air Pollution in a Changing Climate
Bibliographic record
Abstract
Air pollution, the largest global environmental health threat, associated with millions of premature death each year, is getting worse with climate change. To protect their health from air pollution, governments encourage people to stay indoors and avoid high pollution episodes. Moving indoors to reduce exposure to outdoor air is a form of avoidance adaptation. The frequency of this adaptive action can affect the amount of time people spend inside buildings. In Europe and North America, people already spend 90% of their time indoors. Air pollution from outdoors can infiltrate the building envelope, exposing people to pollution of outdoor origin at all times, and reducing the value of avoidance adaptation. To better understand the effect of this infiltration on human health, we examine the impact of building standards on the value of avoidance adaptation. This involves considering the costs of improving building envelopes and ventilation, and associated benefits due to avoided premature death from air pollution exposure. We conduct a historical study in the United States from 1980 to 2010 to examine the spatial and temporal patterns of costs and benefits associated with improving building standards to enhance adaptation to air pollution. This includes investigating past missed opportunities in reducing mortality and laying the foundation for future studies on existing long-term opportunities, all within the context of a changing climate. To achieve this, we establish baseline levels of exposure to the most harmful air pollutant, fine particulate matter, under this historical building stock across the United States. Subsequently, we assess the benefits and costs realized under each building standard improvement scenario (Improved Building Envelope and Improved Ventilation). This study will identify the demographics that can benefit the most from these improvements, quantifying, for example, the potential net gains of improving housing quality for low-income communities. It will address open questions on the value of adaptation in protecting human health under increasing risks from a changing climate.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".