Data and code for: Combining eddy covariance towers, field measurements, and the MEMS 2 ecosystem model improves confidence in the climate impacts of bioenergy with carbon capture and storage

Carbon dioxide removal technologies such as bioenergy with carbon capture
and storage (BECCS) are required if the effects of climate change are to
be reversed over the next century. However, BECCS demands extensive land
use change that may create positive or negative radiative forcing impacts
upstream of the BECCS facility through changes to in situ greenhouse gas
fluxes and land surface albedo. When quantifying these upstream climate
impacts, even at a single site, different methods can give different
estimates. Here we show how three common methods for estimating the net
ecosystem carbon balance of bioenergy crops established on former
grassland or former cropland can differ in their central estimates and
uncertainty. We place these net ecosystem carbon balance forcings in the
context of associated radiative forcings from changes to soil N2O and CH4
fluxes, land surface albedo, embedded fossil fuel use, and geologically
stored carbon. Results from long term eddy covariance measurements, a soil
and plant carbon inventory, and the MEMS 2 process-based ecosystem model
all agree that establishing perennials such as switchgrass or mixed
prairie on former cropland resulted in net negative radiative forcing
(i.e., global cooling) of -26.5 to -39.6 fW m-2 over 100 years.
Establishing these perennials on former grassland sites had similar
climate mitigation impacts of -19.3 to -42.5 fW m-2. However, the largest
climate mitigation came from establishing corn for BECCS on former
cropland or grassland, with radiative forcings from -38.4 to -50.5 fW m-2,
due to its higher plant productivity and therefore more geologically
stored carbon. Our results highlight the strengths and limitations of each
method for quantifying the field scale climate impacts of BECCS and show
that utilizing multiple methods can increase confidence in the final
radiative forcing estimates.