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Uncertainty in health impact assessments of smoke from a wildfire event


Johnson, Megan; Garcia-Menendez, Fernando (2021), Uncertainty in health impact assessments of smoke from a wildfire event, Dryad, Dataset,


Manuscript abstract: Wildfires cause elevated air pollution that can be detrimental to human health. However, health impact assessments associated with emissions from wildfire events are subject to uncertainty arising from different sources. Here, we quantify and compare major uncertainties in mortality and morbidity outcomes of exposure to fine particulate matter (PM2.5) pollution estimated for a series of wildfires in the Southeastern U.S. We present an approach to compare uncertainty in estimated health impacts specifically due to two driving factors, wildfire-related smoke PM2.5 fields and variability in concentration-response parameters from epidemiologic studies of ambient and smoke PM2.5. This analysis focused on the 2016 Southeastern United States wildfires suggests that emissions from these wildfires had public health consequences in North Carolina. Using multiple methods based on publicly available monitor data and atmospheric models to represent wildfire-attributable PM2.5, we estimate impacts on several health outcomes and quantify associated uncertainty. Multiple concentration-response parameters derived from studies of ambient and wildfire-specific PM2.5 are used to assess health-related uncertainty. Results show large variability and uncertainty in wildfire impact estimates, with comparable uncertainties due to the smoke pollution fields and health response parameters for some outcomes, but substantially larger health-related uncertainty for several outcomes. Consideration of these uncertainties can support efforts to improve estimates of wildfire impacts and inform fire-related decision-making.

Usage Notes

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Data included in this folder are described below.

Daily PM2.5 observations were obtained from the U.S. EPA's Air Quality System. These .csv files include monitor observations for all monitors in a given Southeastern state in a given year. Naming format: 'STYYYY_PM25.csv,' where 'ST' is the postal abbreviation of the state, and 'YYYY' is the year. States include AL, GA, NC, SC, TN, and VA. Years include 2012-2016. 
-AQS data can be obtained from:

Hourly November 2016 model results from the NOAA HRRR-NCEP-Smoke model (experimental) are in a netCDF format, converted from the archived GRIB2 format by the NOAA degrib program. HRRR-Smoke netCDFs are organized in compressed folders by forecast date and time. Folder naming format: 'YYYYMMDDHH' where 'YYYY' is the year, 'MM' is the month, 'DD' is the day, and 'HH' is the hour of the forecast. Within the folder, files are named with the format: '' where 'HH' is the hour of the forecast. Most days have two forecast times (00 and 12). At the time of analysis, data was unavailable for some dates and/or forecast times.
-More information on the model and archived forecasts can be found at 
-The NOAA degrib program can be downloaded from:

Archived surface smoke products were obtained from the NOAA NCEI Archive Information Request System (AIRS). When decompressed, the files are in a GRIB2 format. File naming format: '9950_NDGD_LXQ_YYYYMMDD.tar,' where 'YYYY' is the year, 'MM' is the month, and 'DD' is the day of the forecast.
-More information on the smoke forecasting system can be found at:
-Current surface smoke forecasts can be found at:
-Archived smoke forecast products can be obtained from:

Example raw output from BenMAP-CE (v1.5.8). These .csv files include health impact estimates for multiple concentration-response functions for a single spatial smoke field. File names begin with the spatial smoke field used to estimate the health impacts. Estimates included here are aggregated within BenMAP-CE at the state level. Each row includes an impact estimate for a state using the identified concentration-response function. Details on the file format can be found in the BenMAP-CE user manual at Selected column headers are detailed below. BenMAP-CE can be downloaded from
-Col: State FIPS code
-Row: County FIPS code (1 if aggregated for entire state)
-Endpoint: Specific health outcome category of health impact estimate
-Author: Study author of concentration-response function used for health impact estimate
-Point Estimate: Health impact estimate
-Delta: Annual 24-hr average PM2.5 concentration used to estimate health impact
-Percentile 2.5 and Percentile 97.5: used to define the 95% confidence interval on the impact estimate