Haishun Yang

Improvements in Life Cycle Energy Efficiency and Greenhouse Gas Emissions of Corn‐Ethanol

Corn-ethanol production is expanding rapidly with the adoption of improved technologies to increase energy efficiency and profitability in crop production, ethanol conversion, and coproduct use. Life cycle assessment can evaluate the impact of these changes on environmental performance metrics. To this end, we analyzed the life cycles of corn-ethanol systems accounting for the majority of U.S. capacity to estimate greenhouse gas (GHG) emissions and energy efficiencies on the basis of updated values for crop management and yields, biorefinery operation, and coproduct utilization. Direct-effect GHG emissions were estimated to be equivalent to a 48% to 59% reduction compared to gasoline, a twofold to threefold greater reduction than reported in previous studies. Ethanol-to-petroleum output/input ratios ranged from 10:1 to 13:1 but could be increased to 19:1 if farmers adopted high-yield progressive crop and soil management practices. An advanced closed-loop biorefinery with anaerobic digestion reduced GHG emissions by 67% and increased the net energy ratio to 2.2, from 1.5 to 1.8 for the most common systems. Such improved technologies have the potential to move corn-ethanol closer to the hypothetical performance of cellulosic biofuels. Likewise, the larger GHG reductions estimated in this study allow a greater buffer for inclusion of indirect-effect land-use change emissions while still meeting regulatory GHG reduction targets. These results suggest that corn-ethanol systems have substantially greater potential to mitigate GHG emissions and reduce dependence on imported petroleum for transportation fuels than reported previously.

Large-scale on-farm implementation of soil moisture-based irrigation management strategies for increasing maize water productivity

Irrigated maize is produced on about 3.5 Mha in the U.S. Great Plains and western Corn Belt. Most irrigation water comes from groundwater. Persistent drought and increased competition for water resources threaten long-term viability of groundwater resources, which motivated our research to develop strategies to increase water productivity without noticeable reduction in maize yield. Results from previous research at the University of Nebraska-Lincoln (UNL) experiment stations in 2005 and 2006 found that it was possible to substantially reduce irrigation amounts and increase irrigation water use efficiency (IWUE) and crop water use efficiency (CWUE) (or crop water productivity) with little or no reduction in yield using an irrigation regime that applies less water during growth stages that are less sensitive to water stress. Our hypothesis was that a soil moisture-based irrigation management approach in research fields would give similar results in large production-scale, center-pivot irrigated fields in Nebraska. To test this hypothesis, IWUE, CWUE, and grain yields were compared in extensive on-farm research located at eight locations over two years (16 site-years), representing more than 600 ha of irrigated maize area. In each site-year, two contiguous center-pivot irrigated maize fields with similar topography, soil properties, and crop management practices received different irrigation regimes: one was managed by UNL researchers, and the other was managed by the farmer at each site. Irrigation management in farmer-managed fields relied on the farmers’ traditional visual observations and personal expertise, whereas irrigation timing in the UNL-managed fields was based on pre-determined soil water depletion thresholds measured using soil moisture sensors, as well as crop phenology predicted by a crop simulation model using a combination of real-time (in-season) and historical weather data. The soil moisture-based irrigation regime resulted in greater soil water depletion, which decreased irrigation requirements and enabled more timely irrigation management in the UNL-managed fields in both years (34% and 32% less irrigation application compared with farmer-managed fields in 2007 and 2008, respectively). The average actual crop evapotranspiration (ETC) for the UNL- and farmer-managed fields for all sites in 2007 was 487 and 504 mm, respectively. In 2008, the average UNL and average farmer-managed field had seasonal ETC of 511 and 548 mm, respectively. Thus, when the average of all sites is considered, the UNL-managed fields had 3% and 7% less ETC than the farmer-managed fields in 2007 and 2008, respectively, although the percentage was much higher for some of the farmer-managed fields. In both years, differences in grain yield between the UNL and farmer-managed fields were not statistically significant (p = 0.75). On-farm implementation of irrigation management strategies resulted in a 38% and 30% increase in IWUE in the UNL-managed fields in 2007 and 2008, respectively. On average, the CWUE value for the UNL-managed fields was 4% higher than those in the farmer-managed fields in both years. Reduction in irrigation water withdrawal in UNL-managed fields resulted in

Emissions savings in the corn-ethanol life cycle from feeding coproducts to livestock.

32.00 to

Growing sensitivity of maize to water scarcity under climate change.

74.10 ha-1 in 2007 and

Calibration and Validation of the Hybrid-Maize Crop Model for Regional Analysis and Application over the U.S. Corn Belt

44.46 to

Mapping rootable depth and root zone plant-available water holding capacity of the soil of sub-Saharan Africa

66.50 ha-1 in 2008 in energy saving and additional net return to the farm income. The results from this study can have significant positive implications in future irrigation management of irrigated maize systems in regions with similar soil and crop management practices.

Mesoscale Modeling of the Meteorological Impacts of Irrigation during the 2012 Central Plains Drought

Environmental regulations on greenhouse gas (GHG) emissions from corn (Zea mays L.)-ethanol production require accurate assessment methods to determine emissions savings from coproducts that are fed to livestock. We investigated current use of coproducts in livestock diets and estimated the magnitude and variability in the GHG emissions credit for coproducts in the corn-ethanol life cycle. The coproduct GHG emissions credit varied by more than twofold, from 11.5 to 28.3 g CO(2)e per MJ of ethanol produced, depending on the fraction of coproducts used without drying, the proportion of coproduct used to feed beef cattle (Bos taurus) vs. dairy or swine (Sus scrofa), and the location of corn production. Regional variability in the GHG intensity of crop production and future livestock feeding trends will determine the magnitude of the coproduct GHG offset against GHG emissions elsewhere in the corn-ethanol life cycle. Expansion of annual U.S. corn-ethanol production to 57 billion liters by 2015, as mandated in current federal law, will require feeding of coproduct at inclusion levels near the biological limit to the entire U.S. feedlot cattle, dairy, and swine herds. Under this future scenario, the coproduct GHG offset will decrease by 8% from current levels due to expanded use by dairy and swine, which are less efficient in use of coproduct than beef feedlot cattle. Because the coproduct GHG credit represents 19 to 38% of total life cycle GHG emissions, accurate estimation of the coproduct credit is important for determining the net impact of corn-ethanol production on atmospheric warming and whether corn-ethanol producers meet state- and national-level GHG emissions regulations.

An integrated modeling framework for crop and biofuel systems using the DSSAT and GREET models

Climate change can reduce crop yields and thereby threaten food security. The current measures used to adapt to climate change involve avoiding crops yield decrease, however, the limitations of such measures due to water and other resources scarcity have not been well understood. Here, we quantify how the sensitivity of maize to water availability has increased because of the shift toward longer-maturing varieties during last three decades in the Chinese Maize Belt (CMB). We report that modern, longer-maturing varieties have extended the growing period by an average of 8 days and have significantly offset the negative impacts of climate change on yield. However, the sensitivity of maize production to water has increased: maize yield across the CMB was 5% lower with rainfed than with irrigated maize in the 1980s and was 10% lower (and even >20% lower in some areas) in the 2000s because of both warming and the increased requirement for water by the longer-maturing varieties. Of the maize area in China, 40% now fails to receive the precipitation required to attain the full yield potential. Opportunities for water saving in maize systems exist, but water scarcity in China remains a serious problem.

Kenya public weather processed by the Global Yield Gap Atlas project

AbstractDetailed parameter sensitivity, model validation, and regional calibration of the Hybrid-Maize crop model were undertaken for the purpose of regional agroclimatic assessments. The model was run at both field scale and county scale. The county-scale study was based on 30-yr daily weather data and corn yield data from the National Agricultural Statistics Service survey for 24 locations across the Corn Belt of the United States. The field-scale study was based on AmeriFlux sites at Bondville, Illinois, and Mead, Nebraska. By using the one-at-a-time and interaction-explicit factorial design approaches for sensitivity analysis, the study found that the five most sensitive parameters of the model were potential number of kernels per ear, potential kernel filling rate, initial light use efficiency, upper temperature cutoff for growing degree-days’ accumulation, and the grain growth respiration coefficient. Model validation results show that the Hybrid-Maize model performed satisfactorily for field-scale ...

Meeting Cereal Demand While Protecting Natural Resources and Improving Environmental Quality

In rainfed crop production, root zone plant-available water holding capacity (RZ-PAWHC) of the soil has a large influence on crop growth and the yield response to management inputs such as improved seeds and fertilisers. However, data are lacking for this parameter in sub-Saharan Africa (SSA). This study produced the first spatially explicit, coherent and complete maps of the rootable depth and RZ-PAWHC of soil in SSA. We compiled geo-referenced data from 28,000 soil profiles from SSA, which were used as input for digital soil mapping (DSM) techniques to produce soil property maps of SSA. Based on these soil properties, we developed and parameterised (pedotransfer) functions, rules and criteria to evaluate soil water retention at field capacity and wilting point, the soil fine earth fraction from coarse fragments content and, for maize, the soil rootability (relative to threshold values) and rootable depth. Maps of these secondary soil properties were derived using the primary soil property maps as input for the evaluation rules and the results were aggregated over the rootable depth to obtain a map of RZ-PAWHC, with a spatial resolution of 1 km2. The mean RZ-PAWHC for SSA is 74 mm and the associated average root zone depth is 96 cm. Pearson correlation between the two is 0.95. RZ-PAWHC proves most limited by the rootable depth but is also highly sensitive to the definition of field capacity. The total soil volume of SSA potentially rootable by maize is reduced by one third (over 10,500 km3) due to soil conditions restricting root zone depth. Of these, 4800 km3 are due to limited depth of aeration, which is the factor most severely limiting in terms of extent (km2), and 2500 km3 due to sodicity which is most severely limiting in terms of degree (depth in cm). Depth of soil to bedrock reduces the rootable soil volume by 2500 km3, aluminium toxicity by 600 km3, porosity by 120 km3 and alkalinity by 20 km3. The accuracy of the map of rootable depth and thus of RZ-PAWHC could not be validated quantitatively due to absent data on rootability and rootable depth but is limited by the accuracy of the primary soil property maps. The methodological framework is robust and has been operationalised such that the maps can easily be updated as additional data become available.