Abstract
Soil organic carbon (SOC) can be increased by cultivating bioenergy crops to produce low-carbon fuels, improving soil quality and agricultural productivity. This study evaluates the incentives for farmers to sequester SOC by adopting a bioenergy crop, carinata. Two agricultural management scenarios – business as usual (BaU) and a climate-smart (no-till) practice – were simulated using an agent-based modeling approach to account for farmers’ carinata adoption rates within their context of traditional crop rotations, the associated profitability, influences of neighboring farmers, as well as their individual attitudes. Using the state of Georgia, US, as a case study, the results show that farmers allocated 1056 × 103 acres (23.8%; 2.47 acres is equivalent to 1 ha) of farmlands by 2050 at a contract price of $6.5 per bushel of carinata seeds and with an incentive of $50 Mg−1 CO2e SOC sequestered under the BaU scenario. In contrast, at the same contract price and SOC incentive rate, farmers allocated 1152 × 103 acres (25.9%) of land under the no-till scenario, while the SOC sequestration was 483.83 × 103 Mg CO2e, which is nearly four times the amount under the BaU scenario. Thus, this study demonstrated combinations of seed prices and SOC incentives that encourage farmers to adopt carinata with climate-smart practices to attain higher SOC sequestration benefits.
| Original language | English |
|---|---|
| Article number | 119418 |
| Journal | Journal of Environmental Management |
| Volume | 348 |
| DOIs | |
| State | Published - Dec 15 2023 |
Funding
There is no historical record of production costs for carinata in the study area. Several estimates have been made available from the experimental plots established under the Southeast Partnership for Advanced Renewables from Carinata (SPARC) (George et al., 2021; Seepaul et al., 2019). SPARC is a Coordinated Agricultural Project supported by the United States Department of Agriculture National Institute of Food and Agriculture. In light of SPARC's suggested cultivation guides, Karami et al. (2022) made a detail estimation of operational cost under the conventional tillage, which is $286.32 acre−1. This operating cost is used for our study assuming there is no variation in till versus no-till cultivation. This assumption is based on the management of till and no-till scenario specified in Field et al. (2022), that generated yield and SOC data for this study, and the possible costs specified in Karami et al. (2022). Field et al. (2022) suggests that the only variation in till versus no-till cultivation of carinata is in the field preparation, where 2 disk passes were applied for conventional tillage and herbicide burndown was applied for no-till cultivation. In the context of Georgia, the cost for land preparation of these two different managements are similar, which can vary from $15-20 acre−1. Besides, there is no additional equipment costs required for carinata as this crop can be cultivated with the equipment used for traditional field crops, e.g., cotton, corn and peanuts. Considering the maximum average yield in Georgia (53.26 bu acre−1 in the BaU scenario) and the estimated operating cost ($286.32 acre−1), the price of carinata should be at least around $5.5 bu−1 to cover variable production costs. However, the variation in estimated yield levels, and likely production costs, across counties in Georgia mean that breakeven prices may vary significantly.Conservation programs were implemented to improve soil, water and air quality associated with practices, such as cover cropping (Park et al., 2022). The USDA environmental quality incentives program (EQIP) and conservation stewardship program (CSP) are two of the largest conservation programs in terms of acreages and spending (Coppess and Gramig, 2018). Both programs give direct financial and technical assistance to farmers for conservation practices on land that remain in farming, therefore, they are considered ‘working land’ programs. CSP supports long term contracts (5 years) for the entire farm that need to meet a certain threshold of conservation over the years, whereas EQIP provides direct financial support for short term contracts (usually less than 3 years) to recover or share the cost of adding, maintaining, or improving conservation practices. EQIP is a target specific program and is more effective than CSP at the county level (Park et al., 2022) but the CSP imposes thresholds on farmers adding new conservation practices over the existing one. Since farmers make short-term (3 years) rotation decisions and there is no additivity other than integrating carinata into the cotton-cotton-peanuts rotation, we use data on EQIP adoption rates in Georgia to estimate the range of potential land allocation to carinata in this study as follows. The average land allocation rate per farming contract under the EQIP program between 2014 and 2022 in Georgia is 74.79 acres, which is around 30% of the average farm size in the state (USDA, 2022). However, to reflect greater flexibility in our simulation results, we use a uniform distribution of 20–50% to model the proportion of land allocated by farmers that choose to adopt carinata. Although lower than the average land enrollment rate for EQIP in Georgia, the lower bound of this range requires farmers to commit a significant portion of their farmland to carinata production after adoption. The upper bound of the range can be considered conservative since farmers may plant 100% of their land to carinata over the winter to increase profits.This work was primarily supported by the Energy Crop-based Carbon Banking Project sponsored by the DOE Bioenergy Technologies Office (BETO), as well as through the ORNL Laboratory Directed Research and Development Project #10681; the Center for Bioenergy Innovation, a US Department of Energy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science (grant# DE-AC05-00OR22725). We thank John Field, the Ecosystem Modeler at ORNL, for supporting DayCent data. We also thank the anonymous reviewers for their useful feedback that enriched our paper. This work was primarily supported by the Energy Crop-based Carbon Banking Project sponsored by the DOE Bioenergy Technologies Office ( BETO ), as well as through the ORNL Laboratory Directed Research and Development Project #10681; the Center for Bioenergy Innovation , a US Department of Energy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science (grant# DE- AC05-00OR22725 ). We thank John Field, the Ecosystem Modeler at ORNL , for supporting DayCent data. We also thank the anonymous reviewers for their useful feedback that enriched our paper.
Keywords
- Agent-based model
- Bioenergy
- Climate-smart agriculture
- Incentives
- Soil organic carbon
- Sustainable aviation fuel