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Hi, I'm Drew. Welcome to my gluten-free, fair trade, boneless website! I am a postdoctoral associate at the Duke University Nicholas School of the Environment and an incoming assistant professor of environmental studies and sciences at Oberlin College; also, to my knowledge, there is no portrait of me that ages in my place. Be aware that this website is very large, and some of it is randomly generated. For the full experience, reload a bunch of times and navigate as follows:
Date: 23 March 2026 at 7pm CET (approximate)
Location: GKN factory
I will discuss the Italian translation of my book at the occupied GKN factory in Florence.
Date: 24 March 2026 at 5pm CET
Location: University of Bologna
I will discuss the Italian translation of my book at the at the interdepartmental seminar "Ecologie Algoritmi Poteri" in Bologna.
Date: 25 March 2026 at 5pm CET
Location: Campus Luigi Einaudi
I will discuss the Italian translation of my book with Dario Padovan in Turin.
Additional events, future and past, are available on my events page.
Pendergrass, D.C., Jacob, D. J., Oak, Y. J., Lee, J., Kim, M., Kim, J., Lee, S., Zhai, S., Irie, H., & Liao, H. (2025). A continuous 2011–2022 record of fine particulate matter (PM2.5) in East Asia at daily 2-km resolution from geostationary satellite observations: Population exposure and long-term trends. Atmospheric Environment, 346, 121068. Link to paper (open access). Link to PDF. Read a general audience explainer.
Figure: GOCI gap-filled aerosol optical depth (AOD), PM2.5 from air quality networks, and GOCI PM2.5 obtained by applying a RF algorithm to the GOCI AOD data. Data are annual means for 2012 (the first year with complete GOCI data), 2017, and 2022. The gap-filled AOD data provide continuous 2×2 km2 coverage of eastern China, S. Korea, and Japan for 2011-2022. The PM2.5 network data are from individual sites and enlarged for visibility. The S. Korea insets in the middle panels provide greater resolution of network data gaps. PM2.5 measurements from the AirKorea network started in 2015, and the S. Korea PM2.5 network data shown for 2012 are from a RF reconstruction.
You can learn more about my research on the projects page, or you can read through all of our scientific papers and presentations on their respective pages.
Abstract. This paper explores the political uses of images generated by Earth System science. It argues that images of possible climate futures, maps of potential worlds of heatwaves and wildfires, are made legible to policymakers by an alliance with a class of climate-economy models that associate scientific estimates of climate impacts with a prescribed international policy and technology mix. While environmental models have successfully mobilized policymakers in the past by providing images of “planetary scenarios” accompanying different emissions pathways, with climate change a political actor outside the administrative state is required to overcome the entrenchment of fossil capital. The paper suggests such actors are empowered not by the rhetoric of scenario modeling but by the emerging practice of “planetary sensing,” where activists and stakeholders directly mobilize the planetary images generated by Earth System science as they work to evacuate prisons, track pollutants, and repair pipelines.
Pendergrass, D. C. (2024). "From planetary scenarios to planetary sensing: Models, observations, and political legibility." The Anthropocene Review. 20530196241270716. doi:10.1177/20530196241270716 | Read it here.
Read more of my writing here.
19 April 2022 | Watch here
My co-author Troy Vettese and I spoke with Emma Vigeland of the Majority Report about our book Half-Earth Socialism.
Additional interviews and media are available on my interviews page.
CHEEREIO is a tool that uses observations of pollutants in the atmosphere, measured from satellites or surface stations, to correct supercomputer models that simulate the Earth. Powerful use cases for CHEEREIO include tracking pollution back to its source, even if there are no local observations on the ground, and monitoring greenhouse gas emissions in near-real-time. Read more on my projects page or the offical CHEEREIO site.