Biofuels from crop residue can reduce soil carbon and increase CO₂ emissions

Removal of corn residue for biofuels can decrease soil organic carbon1,2 (SOC) and increase CO2 emissions3 because residue C in biofuels is oxidized to CO2 at a faster rate than when added to soil.4,5 Net CO2 emissions from residue removal are not adequately characterized in biofuel life cycle assessment (LCA).6–8 Here we used a model to estimate CO2 emissions from corn residue removal across the US Corn Belt at 580 million geospatial cells. To test the SOC model,9–11 we compared estimated daily CO2 emissions from corn residue and soil with CO2 emissions measured using eddy covariance,12–14 with 12% average error over nine years. The model estimated residue removal of 6 Mg per ha–1 yr–1 over five to ten years could decrease regional net SOC by an average of 0.47–0.66 Mg C ha–1 yr–1. These emissions add an average of 50–70 g CO2 per megajoule of biofuel (range 30–90) and are insensitive to the fraction of residue removed. Unless lost C is replaced,15,16 life cycle emissions will probably exceed the US legislative mandate of 60% reduction in greenhouse gas (GHG) emissions compared with gasoline. Crop residues are abundant feedstocks that are used for biofuel production globally.17, 18 By 2022, the US Energy Independence and Security Act (EISA) mandates production capacity for cellulosic ethanol and advanced biofuels to be 61 billion liters per year (bly) and 19 bly, respectively.17 Corn residue is predominantly used in US cellulosic ethanol biorefineries, with a combined capacity of 0.38 bly in 2014. 19 An additional 0.42 bly of US hydrocarbon biofuels mostly uses wood,19 but could also be derived from crop residue.20 Absolute changes in soil organic carbon (SOC) from corn residue removal have been estimated in LCA,6 but few have estimated net changes in SOC and CO2 emissions compared with no residue removal,7, 8, 21, 22 as required by consequential LCA.23 Recent research suggests soil CO2 emissions from residue removal could produce life cycle GHG emissions for cellulosic ethanol that exceed the mandated emissions reduction.8 Incubation experiments with soil and corn residue showed that SOC is oxidized to CO2 at 0.54–0.80 Mg C ha—1 per season when residues are completely removed.3 Modelled removal of all corn residue in Austria projected an SOC loss of 0.35 Mg C ha—1 yr—1, which represents nearly 50% of life cycle GHG emissions from a biorefinery system.24 Modelled SOC oxidation to CO2 from removal of sweet sorghum residue showed these emissions could eliminate all GHG emissions benefits of the resulting biofuel compared with gasoline.25 Similar net losses of C stocks have also been projected for biofuels from forestry in some cases.26 Changes in SOC occur by two dominant processes: soil erosion by water and wind, and soil respiration where SOC is oxidized to CO2. 5 Soil erosion has significantly depleted SOC across the US Corn Belt, with a recent loss of 1.7 billion tons of soil in the US in 2007.27 Crop residue has conventionally been left on the field after harvest to reduce soil erosion and maintain the SOC stocks and soil fertility of the Corn Belt.1 Although some soil measurements in the Corn Belt have shown that complete residue removal reduces SOC compared with no removal,28, 29 other studies found no significant differences.16 Measuring SOC change accurately is limited owing to the high spatial variability in SOC stocks, the inability to detect a small annual percentage change, short-term studies, and failure to express SOC results in an equivalent mass basis to account for changes in soil bulk density.30, 31 Furthermore, when crop residue is removed, it is essential to determine whether SOC loss is due to erosion or respiration, to accurately estimate the resulting net CO2 emissions. Models are necessary to confidently estimate small percentage annual changes in regional SOC stocks due to respiration,30, 31 as extensive gas exchange measurements are too costly. Although soil moisture and texture are often used in SOC models,4 a robust model can estimate daily changes in SOC due to oxidation to CO2 based on initial SOC (C0), C inputs from agricultural crops (Ci), and average daily temperature (Ta), as shown below.9–11 The SOC model used here is based on exponential oxidation coefficients for SOC (ks, Ss) and cereal crop residues (kr, Sr) from 36 field studies across North America, Europe, Africa, and Asia (see Supplementary Table 1 and Methods).10 An additional term in the equation is added for each year of new C inputs to the soil from residue and roots. Ta – Tr 1 – Ss Ta – Tr 1 – Sr –ks· (ΣQ10 10 · t) –kr· (ΣQ10 10 · t) Ct = C0· e + Ci· e To test the model in the central US, we compared model results with measured CO2 emissions, residue biomass, and SOC from an irrigated no-till continuous corn field experiment in eastern Nebraska (Mead) from 2001 to 2010.12–14 The model estimated that 83% of initial residue C input was oxidized during the first three years, which closely agreed with field measurements that found an average of 20% remained (Supplementary Figure 1).14 Cellulose, hemicellulose, and protein in residue rapidly oxidize, whereas the more recalcitrant lignin fraction (~18% dry matter 6) undergoes a slower oxidation process and contributes to SOC.4 The model estimated 80.9% of initial SOC remained after nine years (56.1 of 69.4 Mg C ha—1) in the 0–30 cm depth, and net C from residue (8.53 Mg C ha—1) contributed to the maintenance of a total of 93.2% of the initial SOC stock (Figure 1). When compared with soil measurements, the Published in Nature Climate Change 4 (May 2014), pp. 398–401; doi: 10.1038/NCLIMATE2187 http://www.nature.com/natureclimatechange Copyright © 2014 Macmillan Publishers Limited. Used by permission. Submitted August 13, 2013; accepted March 5, 2014; published online April 20, 2014. Biofuels from crop residue can reduce soil carbon and increase CO2 emissions Adam J. Liska,1,2 Haishun Yang,2 Maribeth Milner,2 Steve Goddard,3 Humberto Blanco-Canqui,2 Matthew P. Pelton,1 Xiao X. Fang,1 Haitao Zhu,3 and Andrew E. Suyker 4 1. Department of Biological Systems Engineering, University of Nebraska-Lincoln, Nebraska 68583, USA, 2. Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Nebraska 68583, USA, 3. Department of Computer Science and Engineering, University of Nebraska-Lincoln, Nebraska 68588, USA, 4. School of Natural Resources, University of Nebraska-Lincoln, Nebraska 68583, USA. Corresponding author — A. Liska, email [email protected] 398 digitalcommons.unl.edu Biofuels from crop residue can reduce soil carBon and increase co2 emissions 399 model predicted net SOC loss within 17% accuracy during the first four years of the experiment (Supplementary Table 2). Eddy covariance was used to measure net CO2 fluxes to the atmosphere to estimate ecosystem respiration, which was partitioned into emissions from crop respiration and from soil and residue (Methods).32 The model predicted annual measured net CO2 emissions to the atmosphere from soil and residue with an error of 12.4% on average (range 34 to –22%; Supplementary Tables 3 and 4). While using coefficients for SOC oxidation derived from a global span of field measurements, the modeled SOC dynamics agreed well with the field measurements of CO2 emissions, residue remaining, and SOC. The global character of the model assumptions combined with these regional tests indicates the model has enough accuracy to confidently estimate the average direction of change in net CO2 emissions and SOC from residue removal across the Corn Belt. The model was used to estimate geospatial changes in SOC from hypothetical residue removal under continuous corn across the Corn Belt. Input data included measurement-derived estimates of initial SOC stock (C0), C inputs from county crop yields (Ci) (2001–2010), and monthly average temperature (Ta, Methods). Four supercomputer simulations (R1–R4) applied the SOC model at 580 million grid cells of size 30m × 30m (> 52 × 106 ha in total), at monthly intervals from 2001 to 2010: R1 estimated baseline SOC change with no residue removal, and R2, R3, and R4 correspond to 2, 4, and 6 Mg ha—1 yr—1 residue removal, respectively, with the highest being ~50–100% removal. To simulate each dry metric ton of residue harvested, Ci was reduced by 0.4 Mg C ha—1 yr—1, resulting in a modelled decrease in SOC compared with no removal.33 To test the geospatial application of the model, we compared simulated oxidation of SOC based on field measurements of initial SOC, crop yield, and temperature at Mead with the geospatial method for the same site. Modelled removal of 6 Mg residue ha—1 yr—1 based on site measured parameters resulted in an average loss of 0.47 ± 0.29 (s.d.) Mg C ha—1 yr—1 (range 0.25–1.13) over the nine years compared with no removal (Figure 1) and the geospatial application found a similar average loss of 0.50–0.34 Mg C ha—1 yr—1 (Supplementary Figure 2). This comparison suggests geospatial application of the model using independently derived gridded data agrees well with site-specific modelling based on field measurements for the same site. Simulated R4 removal across the entire Corn Belt resulted in an average loss of 0.66 ± 0.08 Mg C ha—1 yr—1 (range 0.17–0.79, Figure 2b) over the first five years and an average of 0.47 ± 0.4 Mg C ha—1 yr—1 (range 0.22–0.56, Figure 2b) for ten years compared with no removal (R1), owing to decreasing C loss over time as SOC reaches a new equilibrium (Figure 2a, 2b, and Supplementary Table 5). Estimated average trends in SOC across the larger region unexpectedly agreed well with the Nebraska site. Importantly, this loss of SOC as respiration corresponds to only 0.3–0.4% per year of initial average SOC stock for the Corn Belt at 73.8 Mg C ha—1 yr—1 (0–30 cm depth) (Supplementary Figure 3 and Table 6). The actual amount of SOC loss to CO2 on average across the region could be greater than or less than estimated here, but these results indicate the likely direction of change and relative magnitudes. The resulting map indicates that Minnesota, Wisconsin, and Iowa have the highest net loss of SOC (Figure 2a). This region has high SOC stocks from low temperatures, which slow oxidation of SOC and residue, and increase the relative change in SOC from residue removal. In LCA, emissions of CO2 from SOC loss in grams per megajoule of biofuel energy (g CO2 MJ—1) can be determined by dividing the average geospatial emissions by the simulated biofuel energy yield.8 Cellulosic ethanol yields per ton of residue were from current and expected future commercial production.34 More energy dense hydrocarbon fuels (for example, FT-diesel) from crop residue have similar energy yields per ton of residue compared to ethanol but they generally have a lower volume yield (Supplementary Table 8).20 Owing to the LCA calculation, when net SOC losses are divided by the energy yields, R1–R4 estimated CO2 emissions average 70 ± 6.4 g CO2 MJ—1 (range 30–90, Figure 2c) and are similar over the first five years for all three residue removal levels (R1–R4, R1– R3, R1–R2). Over ten years, average emissions estimates are lower at 49 ± 4.3 g CO2e MJ—1 (range 33–63) owing to declining C loss over time. Importantly, for the same time interval, the average intensity of CO2 emissions per amount of residue removed is roughly the same for all removal levels; less residue removed causes less decrease in SOC but is associated with a smaller biofuel energy yield. On a relative basis, biofuels from crop residue yield a low amount of energy and oxidize a large C pool, producing high CO2 emissions per unit energy, which is similar to the previously identified phenomenon for indirect land use change from biofuels.23, 35 Adding the five-year average emissions to other net production emissions (for example, biorefinery) of about 30 g CO2-equivalent per megajoule (g CO2e MJ—1) results in net GHG emissions for cellulosic ethanol at 100 g CO2e MJ—1 (Figure 3 and Supplementary Tables 7 and 8). The average value is 7% greater than gasoline (93.7 g CO2e MJ—1),7 and 62 g CO2e MJ—1 above the 60% GHG reduction set by EISA. The range of SOC loss modelled is 30–90 g CO2e MJ—1 (Figure 2c and Supplementary Figure 4), which makes cellulosic ethanol 60–120 g CO2e MJ—1; decreasing the time interval would further increase these values (Figure 1). Whereas previous estimates for single locations do not represent regional variability in CO2 emissions from residue removal,21, 22 these average geospatial estimates for the region can be applied to US Environmental Protection Agency standards for the industry (or see Supplementary Figure 4), irrespective of the amount of crop residue removed, assuming a consistent time interval; these estimates assume that crop residue is removed and no mitigation action is taken, which seems to predominantly occur. To meet the EISA mandate for cellulosic ethanol and advanced biofuel from corn residue (79.5 bly by 2022), 46 million hectares with a yield of 6 Mg ha—1 yr—1 is needed, which is 88% of the Corn Belt area modelled. Emissions of CO2 from SOC in this area would be 81.8–117 Tg CO2 yr—1 (10–5 year average loss rates), equivalent to 1.4–2.0% of net US GHG emissions in 2011. Instead of increasing CO2 emissions and reducing Figure 1. Modelled soil organic carbon decrease due to removal of 6 Mg corn residue per hectare per year over nine years compared with no removal under irrigated continuous corn. Daily modelled oxidation of soil organic carbon (SOC) and residue to CO2 is based on field measurements of initial SOC (0–30 cm soil depth), corn residue input, and temperature at Mead, Nebraska. The average annual net loss of SOC is 0.47 Mg C ha—1 yr—1, but declines exponentially from 1.13 to 0.25 Mg C ha—1 yr—1 over the first eight years. 400 liska et al. in Nature Climate ChaNge 4 (2014) agricultural SOC stocks, an alternative strategy would be to make vehicles more efficient and decrease fuel demand (consistent with the 2012 US CAFE standards), thus potentially making the expanded fuel supply from the RFS2 unnecessary.36 Alternatively, development of other bioenergy systems, such as perennial grasses or forestry resources, may provide feedstocks that could have less negative impacts on SOC, GHG emissions, soil erosion, food security and biodiversity than from removal of corn residue.36–39 Soil CO2 emissions from residue removal, however, can be mitigated by a number of factors and management options. As residue is a source of N2O emissions, residue removal would lower these emissions by ~4.6 g CO2e MJ—1, or ~8% of SOC emissions (Supplementary Table 8). The lignin fraction of residue can also potentially be burned to produce electricity, offsetting coal-generated electricity and saving emissions of up to ~55g CO2 e MJ—1.7 Furthermore, use of improved soil and crop management practices, such as no-till cover crops, foragebased cropping systems, animal manure, compost, biochar and biofuel co-products, could replace the estimated SOC loss after residue removal.15, 16 These management options require more research under different residue removal practices to ensure SOC stocks are maintained where crop residue is removed.