Thread by @lucas_henneman

Cool collaborative research on #coal air pollution sources from @irenededoussi, @joanacasey, @cchoirat, and others in @JExpSciEnvEpi

"Comparisons of simple and complex methods for quantifying exposure to individual point source air pollution emissions"

rdcu.be/b3bBX

2/ Hundreds of coal power plants emit air pollution, which is bad for our health. Air quality regulations should target the sources that impart largest health burden first.

But it’s difficult to calculate burdens of hundreds of individual sources

3/ A good place to start: Adjoint chemical transport models, which use the sum of our knowledge of atmospheric processes to calculate the influence of emissions from anywhere in the modeling domain on air pollution/health in a specified location.

But: computationally intensive

4/ Reduced complexity models are another option. They sacrifice some of the complexity of full complexity models for scalability. We use:
1) a HYSPLIT-based model (HyADS) that just incorporates wind fields and emissions
2) a simple metric of emissions divided by distance

5/ Takeaways. For annual point source impacts,
>Total emissions and distance from sources get you pretty far downwind and near (w/in ~1500km) sources
>Wind fields start becoming more important upwind and for farther sources

Wind fields are much more important for monthly impacts

6/ A negative of our reduced complexity models was that they didn’t estimate PM2.5 source impacts (important for current environmental regulations). We developed statistical adjustment models using CMAQ-DDM Hybrid source impacts fields from @dr_sun_shine pubs.acs.org/doi/abs/10.102…

7/7 Code and data available here!

github.com/lhenneman/simp…