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Disclaimer: this website is composed of symbols and images that do not in themselves carry meaning outside of a total social situation which none of us choose.
Hi, I'm Drew. My GMO-free, artisanally-crafted, fair trade website is lovingly built from whatever I decide to post online. For that reason, it has a lot of stuff on it. Navigate as follows:
If you are interested in HUMAN CONTACT: I can be reached at drew [at] drewpendergrass [dot] com, or at the academic address in my CV. For upcoming events, check out my events page. If you want to follow my work, you can subscribe to my newsletter below (expect emails every six months or so at most):
Pendergrass, D.C., D. J. Jacob, Y. J. Oak, R. Dang, L. H. Yang, E. Beaudry, N. K. Colombi, S. Zhai, H. Kim, J.-s. Choi, J.-s. Park, S. Kim, and H. Liao. Wintertime trends of fine particulate matter (PM2.5) in South Korea, 2012-2022: response of nitrate and organic components to decreasing NOx emissions. Submitted to Geophysical Research Letters. Link to submitted PDF. Link to preprint (open access).
Figure: DJF PM2.5 and trends in South Korea. Panels (a) and (b) show DJF mean PM2.5 at AirKorea surface stations in (a) 2012 and (b) 2022. PM2.5 monitoring at these stations started in 2015, and data for 2012 is from a synthetic PM2.5 network produced using a random forest (RF) algorithm applied to the station data including PM10 (Pendergrass et al., 2025). Panel (c) shows the DJF emission-driven trend in PM2.5 after removing meteorological influence with a multi-linear regression (MLR) fit. Panel (d) shows observed DJF PM2.5 averaged over 25 sites in the city of Seoul, disaggregated into daytime (8-18 LT) and nighttime (22-5 LT) for weekdays and weekends. Panel (e) shows the emission-driven PM2.5 timeseries (residual from the meteorological MLR model) for the Seoul 0.25°×0.3125° grid cell (centered at 37.5°N,127.0°E) and averaging data from 37 sites.
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.
Q. Why does this page keep changing?
A. This page is randomly generated by the server on each load. Most of the page's contents are not displayed on one particular load, so for the full experience reload a bunch of times.
Q. How can I contact you or keep up with your work?
A. You can reach me at drew [at] drewpendergrass [dot] com (or the academic address in my CV); I'm pretty quick with email. However, if your email is unpleasant, you should direct it to grievances@drewpendergrass.com, an inbox I definitely read.
If you want to keep up with new projects, the best way is to subscribe to my newsletter. I send short emails a few times a year with major updates on science and writing. I keep my social media limited these days, but you can follow/DM me on Bluesky. My old Twitter is still up, but I don't use it anymore.
Q. Who are you?
A. Well, to start off, you cannot prove I have sympathies for the former state of Burgundy, I accept the axiom of choice, I appreciate knowledge of the outcome of a given situation, I am not a closed, non-orientable, boundary-free manifold, and I did not orchestrate the Camp David Accords. Besides that, I am a doctoral student in Environmental Engineering at Harvard University, and I freelance on the side for publications including Harper's and The Guardian. I'm also at work on a sci-fi novel and have a book under contract with Verso on economic democracy. In my activism and organizing, we work to make ecological democracy a reality in my home of Massachusetts. I am also a long-time steward in the Harvard Graduate Students Union (UAW local 5117). For more information, you can check out my projects page or my CV.
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.