David J. Muth

An integrated model for assessment of sustainable agricultural residue removal limits for bioenergy systems

Agricultural residues have been identified as a significant potential resource for bioenergy production, but serious questions remain about the sustainability of harvesting residues. Agricultural residues play an important role in limiting soil erosion from wind and water and in maintaining soil organic carbon. Because of this, multiple factors must be considered when assessing sustainable residue harvest limits. Validated and accepted modeling tools for assessing these impacts include the Revised Universal Soil Loss Equation Version 2 (RUSLE2), the Wind Erosion Prediction System (WEPS), and the Soil Conditioning Index. Currently, these models do not work together as a single integrated model. Rather, use of these models requires manual interaction and data transfer. As a result, it is currently not feasible to use these computational tools to perform detailed sustainable agricultural residue availability assessments across large spatial domains or to consider a broad range of land management practices. This paper presents an integrated modeling strategy that couples existing datasets with the RUSLE2 water erosion, WEPS wind erosion, and Soil Conditioning Index soil carbon modeling tools to create a single integrated residue removal modeling system. This enables the exploration of the detailed sustainable residue harvest scenarios needed to establish sustainable residue availability. Using this computational tool, an assessment study of residue availability for the state of Iowa was performed. This study included all soil types in the state of Iowa, four representative crop rotation schemes, variable crop yields, three tillage management methods, and five residue removal methods. The key conclusions of this study are that under current management practices and crop yields nearly 26.5 million Mg of agricultural residue are sustainably accessible in the state of Iowa, and that through the adoption of no till practices residue removal could sustainably approach 40 million Mg. However, when considering the economics and logistics of residue harvest, yields below 2.25 Mg ha^-^1 are generally considered to not be viable for a commercial bioenergy system. Applying this constraint, the total agricultural residue resource available in Iowa under current management practices is 19 million Mg. Previously published results have shown residue availability from 22 million Mg to over 50 million Mg in Iowa.

A Conceptual Evaluation of Sustainable Variable-Rate Agricultural Residue Removal

Agricultural residues have near-term potential as a feedstock for bioenergy production, but their removal must be managed carefully to maintain soil health and productivity. Recent studies have shown that subfield scale variability in soil properties (e.g., slope, texture, and organic matter content) that affect grain yield significantly affect the amount of residue that can be sustainably removed from different areas within a single field. This modeling study examines the concept of variable-rate residue removal equipment that would be capable of on-the-fly residue removal rate adjustments ranging from 0 to 80%. Thirteen residue removal rates (0% and 25-80% in 5% increments) were simulated using a subfield scale integrated modeling framework that evaluates residue removal sustainability considering wind erosion, water erosion, and soil carbon constraints. Three Iowa fields with diverse soil, slope, and grain yield characteristics were examined and showed sustainable, variable-rate agricultural residue removal that averaged 2.35, 7.69, and 5.62 Mg ha, respectively. In contrast, the projected sustainable removal rates using rake and bale removal for the entire field averaged 0.0, 6.40, and 5.06 Mg ha, respectively. The modeling procedure also projected that variable-rate residue harvest would result in 100% of the land area in all three fields being managed in a sustainable manner, whereas Field 1 could not be sustainably managed using rake and bale removal, and only 83 and 62% of the land area in Fields 2 and 3 would be managed sustainably using a rake and bale operation for the entire field. In addition, it was found that residue removal adjustments of 40 to 65% are sufficient to collect 90% of the sustainably available agricultural residue.

Optimization of Biomass Transport and Logistics

Global demand for lignocellulosic biomass is growing, driven by a desire to increase the contribution of renewable energy to the world energy mix. A barrier to the expansion of this industry is that biomass is not always geographically where it needs to be, nor does it have the characteristics required for efficient handling, storage, and conversion, due to low energy density compared to fossil fuels. Technologies exist that can create a more standardized feedstock for conversion processes and decrease handling and transport costs; however, the cost associated with those operations often results in a feedstock that is too expensive. The disconnect between quantity of feedstock needed to meet bioenergy production goals, the quality required by the conversion processes, and the cost bioenergy producers are able to pay creates a need for new and improved technologies that potentially remove barriers associated with biomass use.

Targeted subfield switchgrass integration could improve the farm economy, water quality, and bioenergy feedstock production

Progress on reducing nutrient loss from annual croplands has been hampered by perceived conflicts between short‐term profitability and long‐term stewardship, but these may be overcome through strategic integration of perennial crops. Perennial biomass crops like switchgrass can mitigate nitrate‐nitrogen (NO3‐N) leaching, address bioenergy feedstock targets, and – as a lower‐cost management alternative to annual crops (i.e., corn, soybeans) – may also improve farm profitability. We analyzed publicly available environmental, agronomic, and economic data with two integrated models: a subfield agroecosystem management model, Landscape Environmental Assessment Framework (LEAF), and a process‐based biogeochemical model, DeNitrification‐DeComposition (DNDC). We constructed a factorial combination of profitability and NO3‐N leaching thresholds and simulated targeted switchgrass integration into corn/soybean cropland in the agricultural state of Iowa, USA. For each combination, we modeled (i) area converted to switchgrass, (ii) switchgrass biomass production, and (iii) NO3‐N leaching reduction. We spatially analyzed two scenarios: converting to switchgrass corn/soybean cropland losing >US

A Model Integration Framework for Assessing Integrated Landscape Management Strategies

100 ha−1 and leaching >50 kg ha−1 (‘conservative’ scenario) or losing >US

A Web-Based Interface for Complex Design Using a Virtual Engineering Software Framework

0 ha−1 and leaching >20 kg ha−1 (‘nutrient reduction’ scenario). Compared to baseline, the ‘conservative’ scenario resulted in 12% of cropland converted to switchgrass, which produced 11 million Mg of biomass and reduced leached NO3‐N 18% statewide. The ‘nutrient reduction’ scenario converted 37% of cropland to switchgrass, producing 34 million Mg biomass and reducing leached NO3‐N 38% statewide. The opportunity to meet joint goals was greatest within watersheds with undulating topography and lower corn/soybean productivity. Our approach bridges the scales at which NO3‐N loss and profitability are usually considered, and is informed by both mechanistic and empirical understanding. Though approximated, our analysis supports development of farm‐level tools that can identify locations where both farm profitability and water quality improvement can be achieved through the strategic integration of perennial vegetation.

An Integrated Model Approach for Quantifying Carbon Emissions From Residue-Based Biofuel Production

Nitrogen application is a standard practice for maximizing productivity of an agronomic system. The challenge is that many commercial scale agricultural systems are inefficient in utilizing the nitrogen that is applied. Therefore, understanding the impact of land management practices on nitrogen use inefficiencies within the agroecosystem is critical. This paper presents an integrated model that quantifies the impact of various land management practices on specific agroecosystem units. This integrated model is composed of the Wind Erosion Prediction System (WEPS), the Revised Universal Soil Loss Equation, Version 2 (RUSLE2), the Soil Condition Index (SCI), and the daily CENTURY model, DAYCENT. The integrated model was used to determine the impact of land management strategies on greenhouse gas emissions and nitrate leaching in a 60.5 ha field in Webster County, Iowa, USA. It was found that nitrogen use efficiency can vary significantly across a field and that integrated land management strategies can reduce overall nitrogen losses.

Engineering High-Fidelity Residue Separations for Selective Harvest

VE-Suite is a powerful software framework that allows many complex engineering tasks to be designed, analyzed, and optimized within a comprehensive virtual environment. VESuite is designed to enable the collaboration of engineers across distance and platforms, ranging from immersive Virtual Reality systems to common desktop computers. The purpose of this paper is to describe the development of a web-based interface for VE-Suite. Specific areas covered include the program’s facilities for data storage and retrieval, collaboration methods, and integration with the entire VE-Suite framework. The interface development is presented along with a test case shown within the software framework. Disciplines Computer-Aided Engineering and Design Comments This paper is from Proceedings of the 2nd AIAA Multidisciplinary Design Optimization Specialist Conference, Newport, RI, May 2006. Posted with permission. This conference proceeding is available at Iowa State University Digital Repository: http://lib.dr.iastate.edu/me_conf/57

On the effects of representation on evolving grid robots

This paper presents an agricultural residue removal decision framework that couples the environmental process models WEPS, RUSLE2, SCI, and DAYCENT. One of the goals of this integrated model is to quantify the impacts of land management strategies on soil organic carbon and CO2 emissions. Soil, climate, and land management practices are considered in determining sustainable residue removal rates using wind- and water-induced soil erosion and qualitative soil organic carbon constraints and to quantify the long-term impacts of sustainable residue removal on soil organic carbon and greenhouse gas emissions. Using this integrated model sustainable residue removal for four crop rotations, three tillage regimes, and four soil types representing nearly 70% of the arable acres in Boone County, Iowa are examined. Each scenario was performed for a twenty-year period. Soil organic carbon and CO2 emission results are aggregated by soil type using crop rotation and tillage statistics. The soil type results are aggregated using a normalized percentage area to provide a county level estimate of soil organic carbon changes and CO2 emissions. Results show that for the largest sustainable residue removal rate that soil organic carbon increased 3.53–6.63 Mg/ha over the 20 year simulation and that CO2 emissions ranged from 3.50–4.23 Mg/ha across the four soil types resulting in an average increase of soil organic carbon of 4.85 Mg/ha and CO2 emission of 3.77 Mg/ha at the county level.Copyright

REVIEW: Balancing limiting factors & economic drivers for sustainable Midwestern US agricultural residue feedstock supplies

Composition and pretreatment studies of corn stover and wheat stover anatomical fractions clearly show that some corn and wheat stover anatomical fractions are of higher value than others as a biofeedstock. This premise, along with soil sustainability and erosion control concerns, provides the motivation for the selective harvest concept for separating and collecting the higher value residue fractions in a combine during grain harvest. This study recognizes the analysis of anatomical fractions as theoretical feedstock quality targets, but not as practical targets for developing selective harvest technologies. Rather, practical quality targets were established that identified the residue separation requirements of a selective harvest combine. Data are presented that show that a current grain combine is not capable of achieving the fidelity of residue fractionation established by the performance targets. However, using a virtual engineering approach based on an understanding of the fluid dynamics of the air stream separation, the separation fidelity can be significantly improved without significant changes to the harvester design. A virtual engineering model of a grain combine was developed and used to perform simulations of the residue separator performance. The engineered residue separator was then built into a selective harvest test combine, and tests performed to evaluate the separation fidelity. Field tests were run both with and without the residue separator installed in the test combine, and the chaff and straw residue streams were collected during harvest of Challis soft white spring wheat. The separation fidelity accomplished both with and without the residue separator was quantified by laboratory screening analysis. The screening results showed that the engineered baffle separator did a remarkable job of effecting highfidelity separation of the straw and chaff residue streams, improving the chaff stream purity and increasing the straw stream yield.