Trends in Water Use, Energy Consumption, and Carbon Emissions from Irrigation: Role of Shifting Technologies and Energy Sources.

Novel low-pressure irrigation technologies have been widely adopted by farmers, allowing both reduced water and energy use. However, little is known about how the transition from legacy technologies affected water and energy use at the aquifer scale. Here, we examine the widespread adoption of low-energy precision application (LEPA) and related technologies across the Kansas High Plains Aquifer. We combine direct energy consumption and carbon emission estimates with life cycle assessment to calculate the energy and greenhouse gas (GHG) footprints of irrigation. We integrate detailed water use, irrigation type, and pump energy source data with aquifer water level and groundwater chemistry information to produce annual estimates of energy use and carbon emissions from 1994 to 2016. The rapid adoption of LEPA technologies did not slow pumping, but it reduced energy use by 19.2% and GHG emissions by 15.2%. Nevertheless, water level declines have offset energy efficiency gains because of LEPA adoption. Deeper water tables quadrupled the proportion of GHG emissions resulting from direct carbon emissions, offsetting the decarbonization of the regional electrical grid. We show that low-pressure irrigation technology adoption, absent policies that incentivize or mandate reduced water use, ultimately increases the energy and carbon footprints of irrigated agriculture.

Extreme weather-year sequences have nonadditive effects on environmental nitrogen losses.

The frequency and intensity of extreme weather years, characterized by abnormal precipitation and temperature, are increasing. In isolation, these years have disproportionately large effects on environmental N losses. However, the sequence of extreme weather years (e.g., wet-dry vs. dry-wet) may affect cumulative N losses. We calibrated and validated the DAYCENT ecosystem process model with a comprehensive set of biogeophysical measurements from a corn-soybean rotation managed at three N fertilizer inputs with and without a winter cover crop in Iowa, USA. Our objectives were to determine: (i) how 2-year sequences of extreme weather affect 2-year cumulative N losses across the crop rotation, and (ii) if N fertilizer management and the inclusion of a winter cover crop between corn and soybean mitigate the effect of extreme weather on N losses. Using historical weather (1951-2013), we created nine 2-year scenarios with all possible combinations of the driest ("dry"), wettest ("wet"), and average ("normal") weather years. We analyzed the effects of these scenarios following several consecutive years of relatively normal weather. Compared with the normal-normal 2-year weather scenario, 2-year extreme weather scenarios affected 2-year cumulative NO3- leaching (range: -93 to +290%) more than N2 O emissions (range: -49 to +18%). The 2-year weather scenarios had nonadditive effects on N losses: compared with the normal-normal scenario, the dry-wet sequence decreased 2-year cumulative N2 O emissions while the wet-dry sequence increased 2-year cumulative N2 O emissions. Although dry weather decreased NO3- leaching and N2 O emissions in isolation, 2-year cumulative N losses from the wet-dry scenario were greater than the dry-wet scenario. Cover crops reduced the effects of extreme weather on NO3- leaching but had a lesser effect on N2 O emissions. As the frequency of extreme weather is expected to increase, these data suggest that the sequence of interannual weather patterns can be used to develop short-term mitigation strategies that manipulate N fertilizer and crop rotation to maximize crop N uptake while reducing environmental N losses.

A Case Study of Environmental Benefits of Sensor-Based Nitrogen Application in Corn.

Crop canopy reflectance sensors make it possible to estimate crop N demand and apply appropriate N fertilizer rates at different locations in a field, reducing fertilizer input and associated environmental impacts while maintaining crop yield. Environmental benefits, however, have not been quantified previously. The objective of this study was to estimate the environmental impact of sensor-based N fertilization of corn using model-based environmental Life Cycle Assessment. Nitrogen rate and corn grain yield were measured during a sensor-based, variable N-rate experiment in Lincoln County, MO. Spatially explicit soil properties were derived using a predictive modeling technique based on in-field soil sampling. Soil NO emissions, volatilized NH loss, and soil NO leaching were predicted at 60 discrete field locations using the DeNitrification-DeComposition (DNDC) model. Life cycle cumulative energy consumption, global warming potential (GWP), acidification potential, and eutrophication potential were estimated using model predictions, experimental data, and life cycle data. In this experiment, variable-rate N management reduced total N fertilizer use by 11% without decreasing grain yield. Precision application of N is predicted to have reduced soil NO emissions by 10%, volatilized NH loss by 23%, and NO leaching by 16%, which in turn reduced life cycle nonrenewable energy consumption, GWP, acidification potential, and eutrophication potential by 7, 10, 22, and 16%, respectively. Although mean N losses were reduced, the variations in N losses were increased compared with conventional, uniform N application. Crop canopy sensor-based, variable-rate N fertilization was predicted to increase corn grain N use efficiency while simultaneously reducing total life-cycle energy use, GWP, acidification, and eutrophication.

Impacts of variability in cellulosic biomass yields on energy security.

The practice of modeling biomass yields on the basis of deterministic point values aggregated over space and time obscures important risks associated with large-scale biofuel use, particularly risks related to drought-induced yield reductions that may become increasingly frequent under a changing climate. Using switchgrass as a case study, this work quantifies the variability in expected yields over time and space through switchgrass growth modeling under historical and simulated future weather. The predicted switchgrass yields across the United States range from about 12 to 19 Mg/ha, and the 80% confidence intervals range from 20 to 60% of the mean. Average yields are predicted to decrease with increased temperatures and weather variability induced by climate change. Feedstock yield variability needs to be a central part of modeling to ensure that policy makers acknowledge risks to energy supplies and develop strategies or contingency plans that mitigate those risks.

Aqueous ammonia soaking of switchgrass followed by simultaneous saccharification and fermentation.

Simultaneous saccharification and fermentation (SSF) of switchgrass was performed following aqueous ammonia pretreatment. Switchgrass was soaked in aqueous ammonium hydroxide (30%) with different liquid-solid ratios (5 and 10 ml/g) for either 5 or 10 days. The pretreatment was carried out at atmospheric conditions without agitation. A 40-50% delignification (Klason lignin basis) was achieved, whereas cellulose content remained unchanged and hemicellulose content decreased by approximately 50%. The Sacccharomyces cerevisiae (D5A)-mediated SSF of ammonia-treated switchgrass was investigated at two glucan loadings (3 and 6%) and three enzyme loadings (26, 38.5, and 77 FPU/g cellulose), using Spezyme CP. The percentage of maximum theoretical ethanol yield achieved was 72. Liquid-solid ratio and steeping time affected lignin removal slightly, but did not cause a significant change in overall ethanol conversion yields at sufficiently high enzyme loadings. These results suggest that ammonia steeping may be an effective method of pretreatment for lignocellulosic feedstocks.

Streamflow impacts of biofuel policy-driven landscape change.

Likely changes in precipitation (P) and potential evapotranspiration (PET) resulting from policy-driven expansion of bioenergy crops in the United States are shown to create significant changes in streamflow volumes and increase water stress in the High Plains. Regional climate simulations for current and biofuel cropping system scenarios are evaluated using the same atmospheric forcing data over the period 1979-2004 using the Weather Research Forecast (WRF) model coupled to the NOAH land surface model. PET is projected to increase under the biofuel crop production scenario. The magnitude of the mean annual increase in PET is larger than the inter-annual variability of change in PET, indicating that PET increase is a forced response to the biofuel cropping system land use. Across the conterminous U.S., the change in mean streamflow volume under the biofuel scenario is estimated to range from negative 56% to positive 20% relative to a business-as-usual baseline scenario. In Kansas and Oklahoma, annual streamflow volume is reduced by an average of 20%, and this reduction in streamflow volume is due primarily to increased PET. Predicted increase in mean annual P under the biofuel crop production scenario is lower than its inter-annual variability, indicating that additional simulations would be necessary to determine conclusively whether predicted change in P is a response to biofuel crop production. Although estimated changes in streamflow volume include the influence of P change, sensitivity results show that PET change is the significantly dominant factor causing streamflow change. Higher PET and lower streamflow due to biofuel feedstock production are likely to increase water stress in the High Plains. When pursuing sustainable biofuels policy, decision-makers should consider the impacts of feedstock production on water scarcity.

Production, transportation and milling costs of sweet sorghum as a feedstock for centralized bioethanol production in the upper Midwest.

Sweet sorghum has been identified as a possible ethanol feedstock because of its biomass yield and high concentration of readily fermentable sugars. It has found limited use, however, because of poor post-harvest storage characteristics and short harvest window in cooler climates. Previous research (Bennett, A.S., Anex, R.P., 2008. Farm-gate production costs of sweet sorghum as a bioethanol feedstock. Transactions of the ASABE 51(2), 603-613) indicates that fermentable carbohydrates (FC) can be produced at less expense from sweet sorghum than from corn grain. Previous research, however, did not include costs associated with off-farm transportation, storage, or capital costs associated with milling and energy recovery equipment that are required to provide FC suitable for biological conversion. This study includes these additional costs and reevaluates sweet sorghum as a biocommodity feedstock. A total of eight harvest-transport-processing options are modeled, including 4-row self-propelled and 2-row tractor-pulled forage harvesters, two different modes of in-field transport, fresh processing, on-farm ensilage and at-plant ensilage. Monte Carlo simulation and sensitivity analysis are used to account for system variability and compare scenarios. Transportation costs are found to be significant ranging from $33 to $71 Mg (-1) FC, with highest costs associated with at-plant ensilage scenarios. Economies of scale benefit larger milling equipment and boiler systems reducing FC costs by more than 50% when increasing annual plant capacity from 37.9 to 379 million liters. Ensiled storage of high moisture sweet sorghum in bunkers can lead to significant losses of FC (>20%) and result in systems with net FC costs well above those of corn-derived FC. Despite relatively high transport costs, seasonal, fresh processed sweet sorghum is found to produce FC at costs competitive with corn grain derived FC.

Pilot-scale fermentation of aqueous-ammonia-soaked switchgrass.

Aqueous-ammonia-steeped switchgrass was subject to simultaneous saccharification and fermentation (SSF) in two pilot-scale bioreactors (50- and 350-L working volume). Switchgrass was pretreated by soaking in ammonium hydroxide (30%) with solid to liquid ratio of 5 L ammonium hydroxide per kilogram dry switchgrass for 5 days in 75-L steeping vessels without agitation at ambient temperatures (15 to 33 degrees C). SSF of the pretreated biomass was carried out using Saccharomyces cerevisiae (D(5)A) at approximately 2% glucan and 77 filter paper units per gram cellulose enzyme loading (Spezyme CP). The 50-L fermentation was carried out aseptically, whereas the 350-L fermentation was semiaseptic. The percentage of maximum theoretical ethanol yields achieved was 73% in the 50-L reactor and 52-74% in the 350-L reactor due to the difference in asepsis. The 350-L fermentation was contaminated by acid-producing bacteria (lactic and acetic acid concentrations approaching 10 g/L), and this resulted in lower ethanol production. Despite this problem, the pilot-scale SSF of aqueous-ammonia-pretreated switchgrass has shown promising results similar to laboratory-scale experiments. This work demonstrates challenges in pilot-scale fermentations with material handling, aseptic conditions, and bacterial contamination for cellulosic fermentations to biofuels.

Crop residues: the rest of the story.

Sinking agricultural botanical and soil residues to the deep seafloor may not be a viable option for long-term carbon sequestration.

Development of a fluorescence-based method for monitoring glucose catabolism and its potential use in a biomass hydrolysis assay.

BACKGROUND: The availability and low cost of lignocellulosic biomass has caused tremendous interest in the bioconversion of this feedstock into liquid fuels. One measure of the economic viability of the bioconversion process is the ease with which a particular feedstock is hydrolyzed and fermented. Because monitoring the analytes in hydrolysis and fermentation experiments is time consuming, the objective of this study was to develop a rapid fluorescence-based method to monitor sugar production during biomass hydrolysis, and to demonstrate its application in monitoring corn stover hydrolysis. RESULTS: Hydrolytic enzymes were used in conjunction with Escherichia coli strain CA8404 (a hexose and pentose-consuming strain), modified to produce green fluorescent protein (GFP). The combination of hydrolytic enzymes and a sugar-consuming organism minimizes feedback inhibition of the hydrolytic enzymes. We observed that culture growth rate as measured by change in culture turbidity is proportional to GFP fluorescence and total growth and growth rate depends upon how much sugar is present at inoculation. Furthermore, it was possible to monitor the course of enzymatic hydrolysis in near real-time, though there are instrumentation challenges in doing this. CONCLUSION: We found that instantaneous fluorescence is proportional to the bacterial growth rate. As growth rate is limited by the availability of sugar, the integral of fluorescence is proportional to the amount of sugar consumed by the microbe. We demonstrate that corn stover varieties can be differentiated based on sugar yields in enzymatic hydrolysis reactions using post-hydrolysis fluorescence measurements. Also, it may be possible to monitor fluorescence in real-time during hydrolysis to compare different hydrolysis protocols.

Public participation in life cycle assessment and risk assessment: a shared need.

Life cycle assessment (LCA) and risk assessment are operationally different but share the common purpose of supporting decisions about reducing threats to human welfare. Both analysis methods also involve a complex mixture of science and value judgments reflecting epistemological as well as moral and esthetic values. The inability of risk assessment and LCA to be "value free" has been a source of considerable controversy in both communities. Recognition of the contingent and social nature of human interpretation of the risks and environmental impacts created by public and private decisions has led to an increased appreciation of the importance of involving interested and affected parties in risk characterization. Comparison of the value-based nature of LCA and risk assessment demonstrates the need for participation in LCA. Although the need for participation by affected parties in decision-making processes is gaining acceptance, there is little agreement as to how participation should be structured. Risk assessment and LCA have a shared need for research examining the design and analysis of participation processes appropriate to a given decision context. A proposed framework recommends participation strategies designed to enhance the effectiveness of policy-driven analyses such as risk assessment and LCA based on the level of trust that interested and affected parties have for other policy participants.

A Maximum Entropy Approach to Estimating Emissions.

A maximum information entropy method of calculating probabilistic estimates of volatile organic compound (VOC) emissions by the wood furniture and fixture coating industry is presented. The maximum entropy approach is used to produce minimally biased probability distributions for number of firms, coating use, and coating emission factors from existing summary statistics. These distributions are combined to estimate VOC emissions. The maximum entropy emissions estimate provides information to support probabilistic modeling of regional air quality, probabilistic assessment of emission reduction strategies, and risk assessments. Accurate estimation of emission distributions produces more informed regulatory decisionmaking, risk comparisons, and regulatory and scientific priority setting.