A distributed cellulosic biorefinery system in the US Midwest based on corn stover

Globally, bioethanol is the largest volume biofuel used in the transportation sector, with corn-based ethanol production occurring mostly in the US and sugarcane-based ethanol production occurring mostly in Brazil. Advances in technology and the resulting improved productivity in corn and sugarcane farming and ethanol conversion, together with biofuel policies, have contributed to the significant expansion of ethanol production in the past 20 years. These improvements have increased the energy and greenhouse gas (GHG) benefits of using bioethanol as opposed to using petroleum gasoline. This article presents results from our most recently updated simulations of energy use and GHG emissions that result from using bioethanol made from several feedstocks. The results were generated with the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) model. In particular, based on a consistent and systematic model platform, we estimate life-cycle energy consumption and GHG emissions from using ethanol produced from five feedstocks: corn, sugarcane, corn stover, switchgrass and miscanthus. We quantitatively address the impacts of a few critical factors that affect life-cycle GHG emissions from bioethanol. Even when the highly debated land use change GHG emissions are included, changing from corn to sugarcane and then to cellulosic biomass helps to significantly increase the reductions in energy use and GHG emissions from using bioethanol. Relative to petroleum gasoline, ethanol from corn, sugarcane, corn stover, switchgrass and miscanthus can reduce life-cycle GHG emissions by 19–48%, 40–62%, 90–103%, 77–97% and 101–115%, respectively. Similar trends have been found with regard to fossil energy benefits for the five bioethanol pathways.

Converting land to biofuel feedstock production incurs changes in soil organic carbon (SOC) that can influence biofuel life‐cycle greenhouse gas (GHG) emissions. Estimates of these land use change (LUC) and life‐cycle GHG emissions affect biofuels' attractiveness and eligibility under a number of renewable fuel policies in the USA and abroad. Modeling was used to refine the spatial resolution and depth extent of domestic estimates of SOC change for land (cropland, cropland pasture, grassland, and forest) conversion scenarios to biofuel crops (corn, corn stover, switchgrass, Miscanthus, poplar, and willow) at the county level in the USA. Results show that in most regions, conversions from cropland and cropland pasture to biofuel crops led to neutral or small levels of SOC sequestration, while conversion of grassland and forest generally caused net SOC loss. SOC change results were incorporated into the Greenhouse Gases, Regulated Emissions, and Energy use in Transportation (GREET) model to assess their influence on life‐cycle GHG emissions of corn and cellulosic ethanol. Total LUC GHG emissions (g CO2eq MJ−1) were 2.1–9.3 for corn‐, −0.7 for corn stover‐, −3.4 to 12.9 for switchgrass‐, and −20.1 to −6.2 for Miscanthus ethanol; these varied with SOC modeling assumptions applied. Extending the soil depth from 30 to 100 cm affected spatially explicit SOC change and overall LUC GHG emissions; however, the influence on LUC GHG emission estimates was less significant in corn and corn stover than cellulosic feedstocks. Total life‐cycle GHG emissions (g CO2eq MJ−1, 100 cm) were estimated to be 59–66 for corn ethanol, 14 for stover ethanol, 18–26 for switchgrass ethanol, and −7 to −0.6 for Miscanthus ethanol. The LUC GHG emissions associated with poplar‐ and willow‐derived ethanol may be higher than that for switchgrass ethanol due to lower biomass yield.

A life-cycle assessment (LCA) of corn ethanol was conducted to determine the reduction in the life-cycle greenhouse gas (GHG) emissions of corn ethanol compared to gasoline by integrating biomass fuels in a 190 million liter (50 million gallon) per year dry-grind corn ethanol plant to replace fossil fuels (natural gas and grid electricity). The biomass fuels studied are corn stover and ethanol co-products [dried distillers grains with solubles (DDGS), and syrup (solubles portion of DDGS)]. The biomass conversion technologies/systems considered are process heat (PH) only systems, combined heat and power (CHP) systems, and biomass integrated gasification combined cycle (BIGCC) systems. The key inventory components of the LCA are corn production, stover production, ethanol production, fertilizer inputs, truck transport, co-product credits, ethanol transport to blending, biomass fuel conversion systems, and combustion of anhydrous ethanol (E100). The life-cycle GHG emission reduction for corn ethanol compared to gasoline (97.7 g CO2e/MJ gasoline) is 42.5% for PH with natural gas, 61.3% for PH with corn stover, 82.2% for CHP with corn stover, 81.6% for IGCC with natural gas, 127.7% for BIGCC with corn stover, and 119.1% for BIGCC with syrup and stover. These GHG emission estimates do not include indirect land use change effects. GHG emission reductions for CHP, IGCC, and BIGCC include power sent to the grid which replaces electricity from coal. BIGCC results in greater reductions in GHG emissions than IGCC with natural gas because biomass is substituted for fossil fuels. In addition, underground sequestration of CO2 gas from the ethanol plant’s fermentation tank could further reduce the life-cycle GHG emission of corn ethanol by 31.5% compared to gasoline.

Land management practices such as cover crop adoption or manure application that can increase soil organic carbon (SOC) may provide a way to counter SOC loss upon removal of stover from corn fields for use as a biofuel feedstock. This report documents the data, methodology, and assumptions behind the incorporation of land management practices into corn-soybean systems that dominate U.S. grain production using varying levels of stover removal in the GREETTM (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) model and its CCLUB (Carbon Calculator for Land Use change from Biofuels production) module. Tillage (i.e., conventional, reduced and no tillage), corn stover removal (i.e., at 0, 30% and 60% removal rate), and organic matter input techniques (i.e., cover crop and manure application) are included in the analysis as major land management practices. Soil carbon changes associated with land management changes were modeled with a surrogate CENTURY model. The resulting SOC changes were incorporated into CCLUB while GREET was expanded to include energy and material consumption associated with cover crop adoption and manure application. Life-cycle greenhouse gas (GHG) emissions of stover ethanol were estimated using a marginal approach (all burdens and benefits assigned to corn stover ethanol) and an energy allocation approach (burdens and benefits divided between grain and stover ethanol). In the latter case, we considered corn grain and corn stover ethanol to be produced at an integrated facility. Life-cycle GHG emissions of corn stover ethanol are dependent upon the analysis approach selected (marginal versus allocation) and the land management techniques applied. The expansion of CCLUB and GREET to accommodate land management techniques can produce a wide range of results because users can select from multiple scenario options such as choosing tillage levels, stover removal rates, and whether crop yields increase annually or remain constant. In a scenario with conventional tillage and a 30% stover removal rate, life-cycle GHG emissions for a combined gallon of corn grain and stover ethanol without cover crop adoption or manure application are 49 g CO2eq MJ-1, in comparison with 91 g CO2eq MJ-1 for petroleum gasoline. Adopting a cover crop or applying manure reduces the former ethanol life-cycle GHG emissions by 8% and 10%, respectively. We considered two different life cycle analysis approaches to develop estimates of life-cycle GHG emissions for corn stover ethanol, marginal analysis and energy allocation. In the same scenario, this fuel has GHG emissions of 12 – 20 g CO2eq MJ-1 (for manure and cover crop application, respectively) and 45 – 48 g CO2eq MJ-1 with the marginal approach and the energy allocation approach, respectively.

Corn kernel fiber ethanol that can be produced concurrently with corn starch ethanol has recently been approved as cellulosic biofuel in the USA, suggesting that fiber ethanol could be eligible for a higher credit price than conventional starch ethanol due to its anticipated lower greenhouse gas (GHG) emissions. A life‐cycle analysis was conducted to quantify ethanol's GHG emissions. Here we show that fiber ethanol's life‐cycle GHG emissions (36–39 g CO2e MJ−1) are close to meeting the US cellulosic biofuel's legislative mandate of 60% GHG emissions reduction relative to gasoline (~94 g CO2e MJ−1), with slightly lower emissions under the nth plant mature fiber technology than under the state of technology (SOT). The co‐product, distiller's grain with solubles (DGS), can notably affect fiber ethanol's GHG emissions, and this impact may need to be further examined when evidence of DGS market impacts becomes available. © 2018 Society of Chemical Industry and John Wiley & Sons, Ltd

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

Reducing life cycle greenhouse gas emissions of corn ethanol by integrating biomass to produce heat and power at ethanol plants

The goal of this study is to estimate the county-level environmental performance for continuous corn cultivation of corn grain and corn stover grown under the current tillage practices for various corn-growing locations in the US Corn Belt. The environmental performance of corn grain varies with its farming location because of climate, soil properties, cropping management, etc. Corn stover, all of the above ground parts of the corn plant except the grain, would be used as a feedstock for cellulosic ethanol. Two cropping systems are under investigation: corn produced for grain only without collecting corn stover (referred to as CRN) and corn produced for grain and stover harvest (referred to as CSR). The functional unit in this study is defined as dry biomass, and the reference flow is 1 kg of dry biomass. The system boundary includes processes from cradle to farm gate. The default allocation procedure between corn grain and stover in the CSR system is the system expansion approach. County-level soil organic carbon dynamics, nitrate losses due to leaching, and nitrogen oxide and nitrous oxide emissions are simulated by the DAYCENT model. Life cycle environmental impact categories considered in this study are total fossil energy use, climate change (referred to as greenhouse gas emissions), acidification, and eutrophication. Sensitivities on farming practices and allocation are included. Simulations from the DAYCENT model predict that removing corn stover from soil could decrease nitrogen-related emissions from soil (i.e., N2O, NO x , and NO3 − leaching). DAYCENT also predicts a reduction in the annual accumulation rates of soil organic carbon (SOC) with corn stover removal. Corn stover has a better environmental performance than corn grain according to all life cycle environmental impacts considered. This is due to lower consumption of agrochemicals and fuel used in the field operations and lower nitrogen-related emissions from the soil. The primary source of total fossil energy associated with biomass production is nitrogen fertilizer, accounting for over 30% of the total fossil energy. Nitrogen-related emissions from soil (i.e., N2O, NO x , and NO3 − leaching) are the primary contributors to all other life cycle environmental impacts considered in this study. The environmental performance of corn grain and corn stover varies with the farming location due to crop management, soil properties, and climate conditions. Several general trends were identified from this study. Corn stover has a lower impact than corn grain in terms of total fossil energy, greenhouse gas emissions, acidification, and eutrophication. Harvesting corn stover reduces nitrogen-related emissions from the soil (i.e., N2O, NO x , NO3 −). The accumulation rate of soil organic carbon is reduced when corn stover is removed, and in some cases, the soil organic carbon level decreases. Harvesting only the cob portion of the stover would reduce the negative impact of stover removal on soil organic carbon sequestration rate while still bringing the benefit of lower nitrogen-related emissions from the soil. No-tillage practices offer higher accumulation rates of soil organic carbon, lower fuel consumption, and lower nitrogen emissions from the soil than the current or conventional tillage practices. Planting winter cover crops could be a way to reduce nitrogen losses from soil and to increase soil organic carbon levels. County-level modeling is more accurate in estimating the local environmental burdens associated with biomass production than national- or regional-level modeling. When possible, site-specific experimental information on soil carbon and nitrogen dynamics should be obtained to reflect the system more accurately. The allocation approach between corn grain and stover significantly affects the environmental performance of each. The preferred allocation method is the system expansion approach where incremental fuel usage, additional nutrients in the subsequent growing season, and changes in soil carbon and nitrogen dynamics due to removing corn stover are assigned to only the collected corn stover.

Impacts of pre-treatment technologies and co-products on greenhouse gas emissions and energy use of lignocellulosic ethanol production

The agriculture and forestry sector accounts for approximately 24% of total greenhouse gas (GHG) emissions in Australia. Over the years researchers have produced new knowledge about agricultural GHG emissions and energy use patterns and opportunities to decrease them, albeit in small-scale studies or large-scale ones with coarse resolution. Linking the multiple, diverse and rich datasets around agricultural production in Australia into one dataset that allows for an estimate of GHG emissions and energy use related to agriculture at a national scale and high resolution has not been done before. The approach we describe here is based upon a link between operational data sourced from gross margin (GM) handbooks and life cycle assessment (LCA) process data. We have collected and processed these datasets to produce a comprehensive database of typical agricultural operations covering 72 commodities grown in 42 regions across Australia. We have also created a system that estimates the GHG emission and energy use patterns of the aforementioned commodities using the best available LCA process data. To capture GHG emissions of non-domestically produced fertiliser, we queried the United Nations Commodity Trade Statistics Database (COMTRADE) to analyse the fertiliser and pesticide import patterns for Australia between 2000-2010. This analysis determined the average country energy-mix for fertiliser and pesticide manufacturing and allowed linking the associated GHG emissions to Australian agricultural production. Finally we spatialised agricultural operational data, emissions and energy use at the national scale using the latest Australian Land Use Map (2005/06). Our findings suggest that in 2005/06 greenhouse gas emissions related to Australian agricultural production equate to a total of 95.8 Mt CO-e using 75.7 GWh of energy. According to our results 29.4% of these emissions come from sources that were categorised as non-agricultural (e.g. industrial processes or energy use) in the Australian National Greenhouse Gas Inventory (NGGI) 2006. We find that the provision of transparently modeled GHG emissions and having them linked to a spatially explicit component helps identifying new opportunities for emission reduction and facilitates an assessment of their effects. For example, our findings suggest production of ethanol from corn stover and sugarcane bagasse could have avoided 4.37 Mt CO-e emissions (4.56% of total) without affecting food production.

Exploring impacts of process technology development and regional factors on life cycle greenhouse gas emissions of corn stover ethanol

Co‐production of high‐value chemicals with biofuels could improve the economic viability of biorefineries while reducing biofuel life‐cycle greenhouse gas (GHG) emissions and fossil energy consumption (FEC). Polymer‐grade lactic acid (PGLA) is a high‐potential bioproduct currently produced from first‐generation feedstocks. Opportunity exists to enhance its environmental performance using cellulosic feedstocks. Moreover, ethyl lactate can be used as a functional replacement for high‐volume, energy‐intensive, and emissions‐intensive petroleum‐derived chemicals such as N‐methyl‐2‐pyrrolidone and ethyl acetate. Based on material and energy flows from Aspen Plus process models that we incorporated into the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model's bioproducts module, we developed life‐cycle GHG emissions and FEC estimates for ethyl lactate and PGLA produced from corn stover. We compared these results to those for fossil‐fuel‐derived counterparts, identified key LCA drivers, and explored the impact of end‐of‐life assumptions on LCA results. Irrespective of the end‐of‐life assumption, all the bioproducts demonstrated lower life‐cycle FEC (10–72%) and GHG emissions (23–90%) than fossil‐derived compounds for which they could serve as a functional replacement. Additionally, we reviewed the role of LCA in three major bioproduct sustainability certification schemes (the BioPreferred Program, the Roundtable on Sustainable Biomaterials, and International Sustainability and Carbon Certification Plus). None mandate an LCA of the bioproduct to assess whether, across the supply chain, these products offer environmental benefits as compared to conventional chemicals they could displace either directly or functionally. © 2016 Society of Chemical Industry and John Wiley & Sons, Ltd

Crop residues as raw materials for biorefinery systems – A LCA case study

With the mass market penetration of electric vehicles, the Greenhouse Gas (GHG) emissions associated with lithium-ion battery production has become a major concern. In this study, by establishing a life cycle assessment framework, GHG emissions from the production of lithium-ion batteries in China are estimated. The results show that for the three types of most commonly used lithium-ion batteries, the (LFP) battery, the (NMC) battery and the (LMO) battery, the GHG emissions from the production of a 28 kWh battery are 3061 kgCO2-eq, 2912 kgCO2-eq and 2705 kgCO2-eq, respectively. This implies around a 30% increase in GHG emissions from vehicle production compared with conventional vehicles. The productions of cathode materials and wrought aluminum are the dominating contributors of GHG emissions, together accounting for around three quarters of total emissions. From the perspective of process energy use, around 40% of total emissions are associated with electricity use, for which the GHG emissions in China are over two times higher than the level in the United States. According to our analysis, it is recommended that great efforts are needed to reduce the GHG emissions from battery production in China, with improving the production of cathodes as the essential measure.

Health Care and Climate Change: Challenges and Pathways to Sustainable Health Care.