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
Abstract
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.
Authors
Grant Falvo1,2, Yao Zhang3,4, Michael Abraha2,5, Samantha Mosier1,2, Yahn-Jauh Su2,5, Cheyenne Lei6, Jiquan Chen2,5, M. Francesca Cotrufo3,4, and G. Philip Robertson1,2
Affiliations
1 Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, Michigan, United States.
2 Great Lakes Bioenergy Research Center, East Lansing, Michigan, United States.
3 Department of Soil and Crop Sciences, Colorado State University, Fort Collins, Colorado, United States.
4 Natural Resource Ecology Laboratory, Fort Collins, Colorado, United States.
5 Department of Geography, Environment and Spatial Sciences, Michigan State University, East Lansing, Michigan, United States.
6 School of Environment and Sustainability, University of Michigan, Ann Arbor, Michigan, United States.
Files and their organization
This Dryad.zip file contains the following directories and files
Observations_Directory
- all_non_soil_obs.csv
- merged quality assured field and eddy covariance tower observations
- NA denotes missing or low quality data
- metadata_for_all_non_soil_obs.csv
- accompanying metadata for field and eddy covariance tower observations
- all_soil_obs.csv
- merged quality assured soil observations
- NA denotes missing or low quality data
- metadata_for_all_soil_obs.csv
- accompanying metadata for soil observations
- MEMS_2_model
- Common_Input_Files
- Model input files to the MEMS 2 model that are shared between sites.
- L1 - M4
- Model input and output files for each of the sites, denoted with ‘in_’ and ‘out_’, respectively.
- in_AtmCO2.csv
- Surface air co2 concentration file. Specify the timeseries evolution of surface atmospheric co2 concentrations here.
- in_Basepars.csv
- Parameters of the model that can be easily changed. These include things like soil organic matter decay rates and microbial carbon use efficiency.
- in_Control.csv
- Definitions of model run protocols. Point to the other input files here. And set run start and end years.
- in_Crop.csv
- Parameters of the crop module for each plant type. This includes parameters such as specific leaf area and light use efficiency.
- in_Operations.csv
- Agronomic operation definitions. This includes specifications for things such as fertilization and planting events.
- in_OutputOptions.csv
- Define which outputs to write daily and yearly.
- in_Sch.csv
- Define the scenario plant and agronomic events. Make a timeseries of these management events.
- in_Site.csv
- Site level parameters and initial conditions. This includes parameters like the elevation and initial carbon pool stocks.
- in_Soil.csv
- Initial conditions of soil in each layer. This includes parameters such as the sand, silt, and clay content of the soil.
- in_Tree.csv
- Not active in this model version.
- in_Weather_Spin_Up.csv
- Forcing data for the spin up period. This includes parameters such as solar radiation and precipitation.
- in_Weather.csv
- Forcing data for the model scenario period. This includes parameters such as solar radiation and precipitation.
- log.txt
- Logfile from the last model run. This will contain messages from the Java code such as warnings and errors.
- out_daily_Crop.csv
- Daily output of model fields for plants. This includes things like leaf and root carbon stocks. Units are g C or N per square meter.
- out_daily_Harvest.csv
- Daily output of model fields for agronomic harvests. This includes seeds and residue removals from the field. Units are g C or N per square meter.
- out_daily_NutrientsFlow.csv
- Daily output of model fields for nitrogen flows and heterotrophic respiration. This includes things like nitrate leaching and heterotrophic respiration. Units are g C or N per square meter.
- out_daily_SoilWaterContent.csv
- Daily output of model fields for soil water content by layer. This includes the soil water content of each soil layer. Units are percent volume.
- out_daily_SOM.csv
- Daily output of model fields for soil carbon stocks by layer. This includes things like particulate and mineral-associated organic matter carbon stocks. Units are g C or N per square meter.
- out_daily_SurfOM.csv
- Daily output of model fields for surface litter carbon stocks and nitrogen. This includes surface litter carbon and nitrogn pools. Units are g C or N per square meter.
- out_daily_WaterFlow.csv
- Daily output of model fields for water fluxes. This includes things like runoff and evapotranspiration. Units are mm per day.
- Common_Input_Files
- Rscripts
- Files to run and calibrate the model to the observations. Some directories are hard coded to be local, will need to change these
- RF_Timeseries
- GLBRC_scale_up_ghg_and_albedo_timeseries.csv
- final timeseries of radiative forcing values and R scripts used in this study
- metadata_for_GLBRC_scale_up_ghg_and_albedo_timeseries.csv
- accompanying metadata for radiative forcing timeseries. Some directories are hard coded to be local, will need to change these
- GLBRC_scale_up_ghg_and_albedo_timeseries.csv
- Tables
- Final tables as they appear in the manuscript
- Table S1. Harvest yields, aboveground net primary productivity, and harvest efficiency for each study site over the 13-year study period. The mean and standard error of all years are provided. For the corn sites both seeds and residue are combined when both were harvested in the same year (i.e. 2015-2021). Harvest efficiency is calculated as harvest yield divided by aboveground net primary productivity. Units are Mg biomass per hectare.
- Table S2. Net ecosystem carbon balance (NECB) for each study site and method over the 13-year study period. Central, 2.5 %, and 97.5 % NECB estimates are provided for each method. Positive values indicate C sequestration and negative values indicate C loss from the ecosystem. Units are Mg carbon per hectare.
- Table S3. Net ecosystem carbon balance (NECB) components for the C inventory and MEMS 2 model methods. Positive values indicate C sequestration and negative values indicate C loss from the ecosystem. Units are Mg carbon per hectare.
- Table S4. Average instantaneous radiative forcing for each component and method during the 100-year period following the land use change event. Positive values indicate a warming impact and negative values indicate a cooling impact, relative to their baseline scenario, which is set to zero by definition. Note that only the NECB differs by method. Units are fW per square meter of earth, per square meter of land transformed.
- Table S5. Parameters included in the MEMS 2 model calibration for each plant type. Values are the lower and upper bound of the uniform distribution used in the calibration.
Stats_Output
- Output from the statistical models used in this study
- glbrc_scale_up_bulk_soil_C_lm_output.csv
- Linear regression output for changes in bulk soil carbon stocks at each of the sites over time.
- glbrc_scale_up_MAOM_soil_C_lm_output.csv
- Linear regression output for changes in mineral-associated soil carbon stocks at each of the sites over time.
- glbrc_scale_up_POM_soil_C_lm_output.csv
- Linear regression output for changes in particulate soil carbon stocks at each of the sites over time.
- glbrc_scale_up_delta_toa_sw_out_gam_output.csv
- Generalized additive model output for changes in top of atmosphere outgoing shortwave radiation at each of the study sites.
- glbrc_scale_up_soil_CH4_gam_output.csv
- Generalized additive model output for changes in soil methane fluxes at each of the study sites.
- glbrc_scale_up_soil_N2O_gam_output.csv
- Generalized additive model output for changes in soil nitrous oxide fluxes at each of the study sites.
- MEMS_Uncertainty_Output/L1-M4
- Confidence intervals for carbon stock component changes at each site from the MEMS model uncertainty runs. These intervals characterize the sensitivity of the model output to the posterior distribution of the calibrated parameters.