Methods

The calculator tries to answer three critical questions.

• How much wildfire smoke can our community expect to experience in the future, given the current trends?
• How might our expected wildfire smoke exposure impact our risk for serious health problems?
• What measures can we take personally, and what policies are most effective, to protect our health when air quality is worsened by wildfire smoke?

Here are the steps we took to answer these questions:

• We estimated the current and future levels of wildfire smoke exposure for every zip code in the United States. We synthesized peer reviewed scientific studies and government reports (list below) into a single estimate for each location. We focused on PM 2.5, the fine particles in wildfire smoke, and used average smoke levels over a year for each location.
• We estimated the impacts of wildfire smoke exposure on our risk for asthma, heart attack, and stroke. These are the most serious and best measured health harms experienced on smoky days. Our estimates are based on peer reviewed studies and reports of past wildfire events, where real health impacts in affected communities were described for different exposure levels. Most of these studies describe health harms in terms of urgent health care encounters, such as Emergency Departments visits and hospitalizations.
• We estimated the health benefits of different measures to protect ourselves on days when air is smoky. To do this, we calculated how much specific solutions and policies, such as filter use and mask wearing, would decrease exposure to wildfire smoke particles in the air we breathe. We then calculated the corresponding reduction in risk for acute health events related to asthma, heart attack and stroke.

With this information we created a set of tools for people to advocate for policy solutions to elected leaders, based on their specific community. Our tool offers automated estimates of local exposure levels, local health burden, and anticipated benefits of proposed policy solutions.

The calculator estimates the additional health burden attributable to exposure to wildfire smoke fine particulate matter (PM2.5) at a given location, and projects how that burden changes may evolve under future climate warming scenarios.

Peer-reviewed studies supply the core dose–response relationships and the qualitative structure of age-based susceptibility. On top of these, the tool applies distribution rescaling, three-band age multipliers (magnitudes largely author-estimated), a linear indoor/outdoor mitigation model, and fixed-factor temporal scaling to generate projections. The best-anchored parameter is the older-adult non-infectious respiratory (COPD) scalar, which is tied directly to a large Medicare-cohort study; the least-anchored are the multi-decade climate projections and several cardiovascular age ratios. None of the combination, scaling, or extrapolation logic has been independently peer-reviewed, and results should be treated as illustrative rather than definitive.

Baseline relationships between PM2.5 exposure and health outcomes are drawn from published, peer-reviewed epidemiological studies. Each health outcome (asthma, infectious and non-infectious respiratory conditions, stroke, and ischemic heart disease) is tied to effect sizes reported in that literature, most centrally a Poisson-regression model relating emergency-department visits to interquartile-range increases in PM2.5. Age-stratified susceptibility is grounded in a further set of wildfire-specific studies covering mortality, hospitalization, and emergency-department outcomes across children, working-age adults, and older adults.

Because the source studies were conducted in different places, populations, and time periods, and measured somewhat different endpoints (some measure mortality, others hospitalizations or ED visits), the effect sizes have been harmonized into a common per-person framework rather than taken from any single study.

Turning published effect sizes into a location-specific tool requires several steps that go beyond what any individual study directly reports:

• Distribution rescaling. Effect sizes reported "per interquartile-range increase" in one study's setting are re-expressed using the interquartile range of U.S. wildfire smoke PM2.5, because episodic wildfire smoke is distributed very differently from the chronic urban pollution in some source studies.
• Age-band risk multipliers. Susceptibility is grouped into three age bands (0–17, 18–64, 65+) matching the resolution of the best available evidence. The multipliers reflect published direction and structure, but their specific magnitudes are author estimates, since the literature generally does not publish age-band ratios relative to a single reference group.
• Mitigation modeling. The effect of interventions such as air filtration and masks is modeled by splitting exposure into indoor and outdoor fractions (based on standard time-activity data) and applying published indoor/outdoor ratios and mask protection factors. Because the underlying health formulas are treated as linear in PM2.5, a reduction in exposure translates proportionally into reduced estimated impacts.
• Temporal projection. Near-term (5- and 10-year) and longer-term (20-year, roughly corresponding to a +2 °C scenario) figures are produced by scaling available model outputs up or down with fixed factors. These are simple linear interpolations and extrapolations, not dynamical climate–health simulations.

Smoke PM2.5 predictions and wildfire-occurrence projections are matched to locations on a coordinate grid, combined with population data, and joined with baseline health-burden and social-determinants data at the census-tract level. This yields both per-person risk estimates and population-level totals for a selected location.

This tool provides rough, illustrative estimates. It is not medical advice, not a clinical risk assessment, and not a peer-reviewed scientific result.

The projections shown here are produced by combining published epidemiological findings with a number of simplified assumptions, extrapolations, and author-supplied estimates. They are intended to help people build intuition about how wildfire smoke exposure may affect health outcomes, and how mitigations and future climate scenarios might change that picture. They are not validated predictions of what will happen to any specific person or community.

• No formal peer review. This methodology and its parameter choices have not undergone independent scientific or academic peer review. The underlying source studies are peer-reviewed; the way we have combined, scaled, and extrapolated them is not.
• Estimates, not measurements. Several important numbers — particularly the age-based risk multipliers and the multi-decade climate projections — are informed estimates. The published literature supports their direction and general structure but does not, in most cases, publish the exact values used here.
• Individual results will vary. Actual health risk depends on personal medical history, genetics, behavior, indoor air quality, local conditions, and many other factors this tool does not capture.
• Do not use this for medical or emergency decisions. For questions about your own health or air quality safety, consult a physician and follow guidance from official sources such as the EPA (AirNow), CDC, and local public health authorities.

If you are experiencing a medical emergency, call your local emergency number.