Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
doi:10.5194/acp-2017-26
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
19 Jan 2017
Review status
This discussion paper is under review for the journal Atmospheric Chemistry and Physics (ACP).
Status Update: Is smoke on your mind? Using social media to determine smoke exposure
Bonne Ford1, Moira Burke2, William Lassman1, Gabriele Pfister3, and Jeffrey R. Pierce1 1Department of Atmospheric Science, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523
2Facebook, Menlo Park, CA 94025
3National Center for Atmospheric Research, 3450 Mitchell Lane, Boulder, CO 80301
Abstract. Exposure to wildland-fire smoke is associated with negative effects on human health. However, these effects are poorly quantified. Accurately attributing health endpoints to wildland-fire smoke requires determining the locations, concentrations, and durations of smoke events. Most current methods for determining these smoke-event properties (ground-based measurements, satellite observations, and chemical-transport modeling) are limited temporally, spatially, and/or by their level of accuracy. In this work, we explore using social-media posts regarding smoke, haze, and air quality from Facebook to determine population-level exposure for the summer of 2015 in the western US. We compare this de-identified, aggregated Facebook data to several other datasets that are commonly used for estimating exposure, such as satellite observations (MODIS aerosol optical depth and Hazard Mapping System smoke plumes), surface particulate-matter measurements, and model (WRF-Chem) simulated surface concentrations. After adding population-weighted spatial smoothing to the Facebook data, this dataset is well-correlated (R2 generally above 0.5) with these other methods in smoke-impacted regions. Removing days with considerable cloud coverage further improves correlations of Facebook data to traditional exposure datasets, which implies that the population is less aware of smoke on cloudy days relative to sunny days. The Facebook dataset is better correlated with surface measurements of PM2.5 at a majority of monitoring sites (163 of 293 sites) than the satellite observations and our model simulation are. We also present an example case for Washington state in 2015, where we combine this Facebook dataset with MODIS observations and WRF-Chem simulated PM2.5 in a regression model. We show that the addition of the Facebook data improves the regression model's ability to predict surface concentrations. This high correlation of the Facebook data with surface monitors and our Washington state example suggests that this social-media-based proxy can be used to estimate smoke exposure in locations without direct ground-based particulate-matter measurements.

Citation: Ford, B., Burke, M., Lassman, W., Pfister, G., and Pierce, J. R.: Status Update: Is smoke on your mind? Using social media to determine smoke exposure, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2017-26, in review, 2017.
Bonne Ford et al.
Bonne Ford et al.
Bonne Ford et al.

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We explore using social-media posts mentioning "smoke" or "air quality" from Facebook to determine exposure to wildfire smoke in the western US during summer 2015. We compare this de-identified, aggregated Facebook dataset to satellite observations, surface measurements, and model-simulated concentrations, and we find good agreement in smoke-impacted regions. Our results suggest that aggregate social-media data can be used to supplement traditional datasets to estimate smoke exposure.
We explore using social-media posts mentioning "smoke" or "air quality" from Facebook to...
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