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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. 

Abstract Radiative forcing (RF) resulting from changes in surface albedo is increasingly recognized as a significant driver of global climate change but has not been adequately estimated, including by Intergovernmental Panel on Climate Change (IPCC) assessment reports, compared with other warming agents. Here, we first present the physical foundation for modeling albedo-induced RF and the consequent global warming impact (GWI_Δα). We then highlight the shortcomings of available current databases and methodologies for calculating GWI_Δαat multiple temporal scales. There is a clear lack of comprehensivein situmeasurements of albedo due to sparse geographic coverage of ground-based stations, whereas estimates from satellites suffer from biases due to the limited frequency of image collection, and estimates from earth system models (ESMs) suffer from very coarse spatial resolution land cover maps and associated albedo values in pre-determined lookup tables. Field measurements of albedo show large differences by ecosystem type and large diurnal and seasonal changes. As indicated from our findings in southwest Michigan, GWI_Δαis substantial, exceeding the RF_Δαvalues of IPCC reports. Inclusion of GWI_Δαto landowners and carbon credit markets for specific management practices are needed in future policies. We further identify four pressing research priorities: developing a comprehensive albedo database, pinpointing accurate reference sites within managed landscapes, refining algorithms for remote sensing of albedo by integrating geostationary and other orbital satellites, and integrating the GWI_Δαcomponent into future ESMs. 

Abstract Surface albedo can affect the energy budget and subsequently cause localized warming or cooling of the climate. When we convert a substantial portion of lands to agriculture, land surface properties are consequently altered, including albedo. Through crop selection and management, one can increase crop albedo to obtain higher levels of localized cooling effects to mitigate global warming. Still, there is little understanding about how distinctive features of a cropping system may be responsible for elevated albedo and consequently for the cooling potential of cultivated lands. To address this pressing issue, we conducted seasonal measurements of surface reflectivity during five growing seasons on annual crops of corn-soybean–winter wheat (Zea mays L.- Glycine max L.Merrill—Triticum aestivum L.; CSW) rotations at three agronomic intensities, a monoculture of perennial switchgrass, and perennial polycultures of early successional and restored prairie grasslands. We found that crop-species, agronomic intensity, seasonality, and plant phenology had significant effects on albedo. The mean ± SD of albedo was highest in perennial crops of switchgrass (Panicum virgatum; 0.179 ± 0.04), intermediate in early successional crops (0.170 ± 0.04), and lowest in a reduced input corn systems with cover crops (0.154 ± 0.02). Thestrongest cooling potentials were found in soybean (−0.450 kg CO₂e m⁻²yr⁻¹) and switchgrass (−0.367 kg CO₂e m⁻²yr⁻¹), with up to −0.265 kg CO₂e m⁻²yr⁻¹of localized climate cooling annually provided by different agroecosystems. We also demonstrated how diverse ecosystems, leaf canopy, and agronomic practices can affect surface reflectivity and provide another potential nature-based solution for reducing global warming at localized scales. 

Abstract Changes in land surface albedo can alter ecosystem energy balance and potentially influence climate. We examined the albedo of six bioenergy cropping systems in southwest Michigan USA: monocultures of energy sorghum (Sorghum bicolor), switchgrass (Panicum virgatumL.), and giant miscanthus (Miscanthus×giganteus), and polycultures of native grasses, early successional vegetation, and restored prairie. Direct field measurements of surface albedo (α_s) from May 2018 through December 2020 at half‐hourly intervals in each system quantified the magnitudes and seasonal differences in albedo (∆_α) and albedo‐induced radiative forcing (RF_∆α). We used a nearby forest as a historical native cover type to estimate reference albedo and RF_∆αchange upon original land use conversion, and a continuous no‐till maize (Zea mays L.) system as a contemporary reference to estimate change upon conversion from annual row crops. Annually,α_sdiffered significantly (p < 0.05) among crops in the order: early successional (0.288 ± 0.012SE) >> miscanthus (0.271 ± 0.009) ≈ energy sorghum (0.270 ± 0.010) ≥ switchgrass (0.265 ± 0.009) ≈ restored prairie (0.264 ± 0.012) > native grasses (0.259 ± 0.010) > maize (0.247 ± 0.010). Reference forest had the lowest annualα_s(0.134 ± 0.003). Albedo differences among crops during the growing season were also statistically significant, with growing seasonα_sin perennial crops and energy sorghum on average ~20% higher (0.206 ± 0.003) than in no‐till maize (0.184 ± 0.002). Average non‐growing season (NGS)α_s(0.370 ± 0.020) was much higher than growing seasonα_s(0.203 ± 0.003) but these NGS differences were not significant. Overall, the original conversion of reference forest and maize landscapes to perennials provided a cooling effect on the local climate (RF_αMAIZE: −3.83 ± 1.00 W m⁻²; RF_αFOREST: −16.75 ± 3.01 W m⁻²). Significant differences among cropping systems suggest an additional management intervention for maximizing the positive climate benefit of bioenergy crops, with cellulosic crops on average ~9.1% more reflective than no‐till maize, which itself was about twice as reflective as the reference forest. 

Abstract Aims Long-term determination of root biomass production upon land-use conversion to biofuel crops is rare. To assess land-use legacy influences on belowground biomass accumulation, we converted 22-year-old Conservation Reserve Program (CRP) grasslands and 50+-year-old agricultural (AGR) lands to corn (C), switchgrass (Sw) and restored prairie (Pr) biofuel crops. We maintained one CRP grassland as a reference (Ref). We hypothesized that land-use history and crop type have significant effects on root density, with perennial crops on CRP grasslands having a higher root biomass productivity, while corn grown on former agricultural lands produce the lowest root biomass. Methods The ingrowth core method was used to determine in situ ingrowth root biomass, alongside measurements of aboveground net primary productivity (ANPP). Ancillary measurements, including air temperature, growing season length and precipitation were used to examine their influences on root biomass production. Important Findings Root biomass productivity was the highest in unconverted CRP grassland (1716 g m−2 yr−1) and lowest in corn fields (526 g m−2 yr−1). All perennial sites converted from CRP and AGR lands had lower root biomass and ANPP in the first year of planting but peaked in 2011 for switchgrass and a year later for restored prairies. Ecosystem stability was higher in restored prairies (AGR-Pr: 4.3 ± 0.11; CRP-Pr: 4.1 ± 0.10), with all monocultures exhibiting a lower stability. Root biomass production was positively related to ANPP (R2 = 0.40). Overall, attention should be given to root biomass accumulation in large-scale biofuel production as it is a major source of carbon sequestration. 

Land surface albedo is a significant regulator of climate. Changes in land use worldwide have greatly reshaped landscapes in the recent decades. Deforestation, agricultural development, and urban expansion alter land surface albedo, each with unique influences on shortwave radiative forcing and global warming impact (GWI). Here, we characterize the changes in landscape albedo-induced GWI (GWIΔα) at multiple temporal scales, with a special focus on the seasonal and monthly GWIΔα over a 19-year period for different land cover types in five ecoregions within a watershed in the upper Midwest USA. The results show that land cover changes from the original forest exhibited a net cooling effect, with contributions of annual GWIΔα varying by cover type and ecoregion. Seasonal and monthly variations of the GWIΔα showed unique trends over the 19-year period and contributed differently to the total GWIΔα. Cropland contributed most to cooling the local climate, with seasonal and monthly offsets of 18% and 83%, respectively, of the annual greenhouse gas emissions of maize fields in the same area. Urban areas exhibited both cooling and warming effects. Cropland and urban areas showed significantly different seasonal GWIΔα at some ecoregions. The landscape composition of the five ecoregions could cause different net landscape GWIΔα.