Allocation in Life Cycle Inventory Analysis for Joint Production

Allocation in joint production is still one of the unresolved and often discussed methodological issues in Life Cycle Inventory Analysis. Using the many years of experience of man agement sciences, a new classification scheme is proposed. It is postulated that companies perform allocation in joint production in view of optimising the products’ performance (economic and/ or environmental), which helps them to maximise their profits. Therefrom it is derived that value judgements and negotiations are inevitable. The proposed classification scheme differentiates between the number of decision-makers involved, and the type of markets for joint products. Several decision-makers have to find fair allocation factors for their commonly operated joint production, whereas individual decision-makers may choose allocation factors considering the (economic and/ or environmental) competitiveness of their joint products. Applied on the case of a small-scale gas-fuelled combined heat and power plant, the methodology proposed shows a strong dependency on the disutility function, i.e., private costs, environmental damage costs or a combination of the two. Presentation and Introduction of this set of articles see Int. J. LCA 4 (3) 175–179 (1999)     

Development of Sustainable Corn Stover Harvest Strategies for Cellulosic Ethanol Production

To prepare for a 2014 launch of commercial scale cellulosic ethanol production from corn/maize (Zea mays L.) stover, POET-DSM near Emmetsburg, IA has been working with farmers, researchers, and equipment dealers through “Project Liberty” on harvest, transportation, and storage logistics of corn stover for the past several years. Our objective was to evaluate seven stover harvest strategies within a 50-ha (125 acres) site on very deep, moderately well to poorly drained Mollisols, developed in calcareous glacial till. The treatments included the following: conventional grain harvest (no stover harvest), grain plus a second-pass rake and bale stover harvest, and single-pass grain plus cob-only biomass, grain plus vegetative material other than grain [(MOG) consisting of cobs, husks, and upper plant parts], grain plus all vegetative material from the ear shank upward (high cut), and all vegetative material above a 10 cm stubble height (low cut), with a John Deere 9750 STS combine, and grain plus direct baling of MOG with an AgCo harvesting system. Average grain yields were 11.4, 10.1, 9.7, and 9.5 Mg ha^?1 for 2008, 2009, 2010, and 2011, respectively. Average stover harvest ranged from 0 to 5.6 Mg ha^?1 and increased N, P, and K removal by an average of 11, 1.6, and 15 kg Mg^?1, respectively. Grain yield in 2009 showed a significant positive response to higher 2008 stover removal rates, but grain yield was not increased in 2010 or 2011 due to prior-year stover harvest. High field losses caused the direct-bale treatment to have significantly lower grain yield in 2011 because the AgCo system could not pick up the severely lodged crop. We conclude that decreases in grain yield across the 4 years were due more to seasonal weather patterns, spatial variability, and not rotating crops than to stover harvest.     

Life Cycle Performance of Cellulosic Ethanol and Corn Ethanol from a Retrofitted Dry Mill Corn Ethanol Plant

This study conducts a life cycle assessment of a simulated dry mill corn ethanol facility in California’s Central Valley retrofitted to also produce ethanol from corn stover, a cellulosic feedstock. The assessment examines three facility designs, all producing corn ethanol and wet distiller’s grains and solubles as a co-product: a baseline facility with no cellulosic retrofit, a facility retrofitted with a small capacity for stover feedstock, and a facility retrofitted for a large capacity of stover feedstock. Corn grain is supplied by rail from the Midwest, while stover is sourced from in-state farms and delivered by truck. Two stover feedstock supply scenarios are considered, testing harvest rates at 25 or 40 % of stover mass. Allocation is required to separate impacts attributable to co-products. Additional scenarios are explored to assess the effect of co-product allocation methods on life cycle assessment results for the two fuel products, corn ethanol and stover ethanol. The assessment tracks greenhouse gas (GHG) emissions, energy consumption, criteria air pollutants, and direct water consumption. The GHG intensity of corn ethanol produced from the three facility designs range between 61.3 and 68.9 g CO₂e/MJ, which includes 19.8 g CO₂e/MJ from indirect land use change for Midwestern corn grain. The GHG intensity of cellulosic ethanol varies from 44.1 to 109.2 g CO₂e/MJ, and 14.6 to 32.1 g CO₂e/MJ in the low and high stover capacity cases, respectively. Total energy input ranges between 0.60 and 0.71 MJ/MJ for corn ethanol and 0.13 to 2.29 MJ/MJ for stover ethanol. This variability is the result of the stover supply scenarios (a function of harvest rate) and co-product allocation decisions.     

Evaluation of Life Cycle Assessment Recycling Allocation Methods

Life cycle assessment practitioners struggle to accurately allocate environmental burdens of metals recycling, including the temporal dimension of environmental impacts. We analyze four approaches for calculating aluminum greenhouse gas emissions: the recycled content (RC) or cut‐off approach, which assumes that demand for recycled content displaces primary production; end‐of‐life recycling (EOLR), which assumes that postuse recycling displaces primary production; market‐based (MB) approaches, which estimate changes in supply and demand using price elasticities; and value‐corrected substitution (VCS), which allocates impact based on price differences between primary and recycled material. Our analysis suggests that applications of the VCS approach do not adequately account for the changing scrap to virgin material price ratio over time, whereas MB approaches do not address stock accumulation and depletion. The EOLR and RC approaches were analyzed using two case studies: U.S. aluminum beverage cans and vehicle engine blocks. These approaches produced similar results for beverage cans, which have a closed material loop system and a short product life. With longer product lifetimes, as noted with the engine blocks, the magnitude and timing of the emissions differs greatly between the RC and EOLR approaches. The EOLR approach indicates increased impacts at the time of production, offset by negative impacts in future years, whereas the RC approach assumes benefits to increased recycled content at the time of production. For vehicle engine blocks, emissions using EOLR are 140% higher than with RC. Results are highly sensitive to recycled content and future recycling rates, and the choice of allocation methods can have significant implications for life cycle studies.     

Spatially Explicit Life Cycle Analysis of Cellulosic Ethanol Production Scenarios in Southwestern Michigan

Modeling the life cycle of fuel pathways for cellulosic ethanol (CE) can help identify logistical barriers and anticipated impacts for the emerging commercial CE industry. Such models contain high amounts of variability, primarily due to the varying nature of agricultural production but also because of limitations in the availability of data at the local scale, resulting in the typical practice of using average values. In this study, 12 spatially explicit, cradle-to-refinery gate CE pathways were developed that vary by feedstock (corn stover, switchgrass, and Miscanthus), nitrogen application rate (higher, lower), pretreatment method (ammonia fiber expansion [AFEX], dilute acid), and co-product treatment method (mass allocation, sub-division), in which feedstock production was modeled at the watershed scale over a nine-county area in Southwestern Michigan. When comparing feedstocks, the model showed that corn stover yielded higher global warming potential (GWP), acidification potential (AP), and eutrophication potential (EP) than the perennial feedstocks of switchgrass and Miscanthus, on an average per area basis. Full life cycle results per MJ of produced ethanol demonstrated more mixed results, with corn stover-derived CE scenarios that use sub-division as a co-product treatment method yielding similarly favorable outcomes as switchgrass- and Miscanthus-derived CE scenarios. Variability was found to be greater between feedstocks than watersheds. Additionally, scenarios using dilute acid pretreatment had more favorable results than those using AFEX pretreatment.     

Economic Allocation in Life Cycle Assessment

This article examines methods for analyzing allocation in life cycle assessment (LCA); it focuses on comparisons of economic allocation with other feasible alternatives. The International Organization for Standardization's (ISO) guideline 14044 indicates that economic allocation should only be used as a last resort, when other methods are not suitable. However, the LCA literature reports several examples of the use of economic allocation. This is due partly to its simplicity and partly to its ability to illustrate the properties of complex systems. Sometimes a price summarizes complex attributes of product or service quality that cannot be easily measured by physical criteria. On the other hand, economic allocation does have limitations arising, for example, from the variability of prices and the low correlation between prices and physical flows. This article presents the state of the debate on the topic and some hypothetical examples for illustration. A general conclusion is that it is not possible to determine one “best” allocation method. The allocation procedure has to be selected on a case‐by‐case basis and no single approach is suitable for every situation. Despite its limitations, economic allocation has certain qualities that make it flexible and potentially suitable for different contexts. In some situations, economic allocation should not be the last methodological resort. The option of economic allocation should be considered, for example, whenever the prices of coproducts and coservices differ widely.     

Implications of Uncertainty and Variability in the Life Cycle Assessment of Pig Production Systems(7 pp)

Goal, Scope and Background Calculating LCA outcomes implies the use of parameters, models, choices and scenarios which introduce uncertainty, as they imperfectly account for the variability of both human and environmental systems. The analysis of the uncertainty of LCA results, and its reduction by an improved estimation of key parameters and through the improvement of the models used to convert emissions into regional impacts, such as eutrophication, are major issues for LCA. Methods In a case study of pig production systems, we propose a simple quantification of the uncertainty of LCA results (intra-system variability) and we explore the inter-system variability to produce more robust LCA outcomes. The quantification of the intra-system uncertainty takes into account the variability of the technical performance (crop yield, feed efficiency) and of emission factors (for NH3, N2O and NO3) and the influence of the functional unit (FU) (kg of pig versus hectare used). For farming systems, the inter-system variability is investigated through differentiating the production mode (conventional, quality label, organic (OA)), and the farmer practices (Good Agricultural Practice (GAP) versus Over Fertilised (OF)), while for natural systems, variability due to physical and climatic characteristics of catchments expected to modify nitrate fate is explored. Results and Conclusion For the eutrophication and climate change impact categories, the uncertainty associated with field emissions contributes more to the overall uncertainty than the uncertainty associated with emissions from livestock buildings, with crop yield and with feed efficiency. For acidification, the uncertainty of emissions from livestock buildings is the single most important contributor to the overall uncertainty. The influence of the FU on eutrophication results is very important when comparing systems with different degrees of intensification such as GAP and OA. Concerning the inter-system variability, differences in farmer practices have a larger effect on eutrophication than differences between production modes. Finally, the physical characteristics of the catchment and the climate strongly affect the results for eutrophication. In conclusion, in this case study, the main sources of uncertainty are in the estimation of emission factors, due both to the variability of environmental conditions and to lack of knowledge (emissions of N2O at the field level), but also in the model used for assessing regional impacts such as eutrophication. Recommendation and Perspective Suitable deterministic simulation models integrating the main controlling variables (environmental conditions, farmer practices, technology used) should be used to predict the emissions of a given system as well as their probabilistic distribution allowing the use of stochastic modelling. Finally, our simulations on eutrophication illustrate the necessity of integrating the fate of pollutants in models of impact assessment and highlight the important margin of improvement existing for the eutrophication impact assessment model.     

Evaluation of Simultaneous Saccharification and Ethanol Fermentation of Undetoxified Steam-Exploded Corn Stover by Saccharomyces cerevisiae Y5

Toxin-tolerant yeast strains that produce high ethanol yield are inevitably requited for cost-effective ethanol production from undetoxified steam-exploded corn stover. To verify the ethanol-producing capability of the strain Saccharomyces cerevisiae Y5 developed in our laboratory, simultaneous saccharification and fermentation of undetoxified steam-exploded corn stover with solids loading of 30 % (w/v) was carried out in different-sized flasks and an automatic fermenter. After 96 h, the ethanol concentrations had reached 50, 47.8, and 47.5 g/L in the 100-mL flask, 3,000-mL flask, and 5-L automatic fermenter, respectively. The experiment demonstrates that ethanol production from undetoxified steam-exploded corn stover using S. cerevisiae Y5 simplifies the production process, reduces equipment investment and water consumption, and generates highly concentrated ethanol. S. cerevisiae Y5 is a promising strain that could reduce the cost of producing ethanol from steam-exploded corn stover.     

Life Cycle Energy and Climate Change Implications of Nanotechnologies

The potential environmental and health impacts of nanotechnologies triggered a recent surge of life cycle assessment (LCA) studies on nanotechnologies. Focusing on the energy use and greenhouse gas emissions impacts, we reviewed 22 LCA‐based studies on nanomaterials, coatings, photovoltaic devices, and fabrication technologies that were published until 2011. The reviewed LCA studies indicate that nanomaterials have higher cradle‐to‐gate energy demand per functional unit, and thus higher global warming impact, than their conventional counterparts. Depending on the synthesis method, carbon‐based nanoparticles (i.e., carbon nanofibers, carbon nanotubes, and fullerenes) require 1 to 900 gigajoules per kilogram (GJ/kg) of primary energy to produce, compared with ～200 megajoules per kilogram (MJ/kg) for aluminum. This is mainly attributed to the fact that nanomaterials involve an energy‐intensive synthesis process or an additional mechanical process to reduce particle size. Most reviewed studies ascertain, however, that the cradle‐to‐grave energy demand and global warming impact from nanotechnologies at a device level are lower than from conventional technologies because nanomaterials are typically used in a small amount to improve functionality and the upgraded functionality offers more energy‐efficient operation of the device. Because of the immature status of most nanotechnologies, the studies reviewed here often rely on inventory data estimated from literature values and parametric analyses based on laboratory or prototype production, warranting future analyses to confirm the current findings.     

Generalized Make and Use Framework for Allocation in Life Cycle Assessment

Allocation in life cycle inventory (LCI) analysis is one of the long‐standing methodological issues in life cycle assessment (LCA). Discussion on allocation among LCA researchers has taken place almost in complete isolation from the series of closely related discussions from the 1960s in the field of input?output economics, regarding the supply and use framework. This article aims at developing a coherent mathematical framework for allocation in LCA by connecting the parallel developments of the LCA and the input?output communities. In doing so, the article shows that the partitioning method in LCA is equivalent to the industry‐technology model in input?output economics, and system expansion in LCA is equivalent to the by‐product‐technology model in input?output output economics. Furthermore, we argue that the commodity‐technology model and the by‐product‐technology model, which have been considered as two different models in input?output economics for more than 40 years, are essentially equivalent when it comes to practical applications. It is shown that the matrix‐based approach used for system expansion successfully solves the endless regression problem that has been raised in LCA literature. A numerical example is introduced to demonstrate the use of allocation models. The relationship of these approaches with consequential and attributional LCA models is also discussed.     

Life Cycle of Titanium Dioxide Nanoparticle Production

Life cycle impact of emissions, energy requirements, and exergetic losses are calculated for a novel process for producing titanium dioxide nanoparticles from an ilmenite feedstock. The Altairnano hydrochloride process analyzed is tailored for the production of nanoscale particles, unlike established commercial processes. The life cycle energy requirements for the production of these particles is compared with that of traditional building materials on a per unit mass basis. The environmental impact assessment and energy analysis results both emphasize the use of nonrenewable fossil fuels in the upstream life cycle. Exergy analysis shows fuel losses to be secondary to material losses, particularly in the mining of ilmenite ore. These analyses are based on the same inventory data. The main contributions of this work are to provide life cycle inventory of a nanomanufacturing process and reveal potential insights from exergy analysis that are not available from other methods.     

Hybrid Input‐Output Life Cycle Assessment of First‐ and Second‐Generation Ethanol Production Technologies in Brazil

A hybrid approach combining life cycle assessment and input‐output analysis was used to demonstrate the economic and environmental benefits of current and future improvements in agricultural and industrial technologies for ethanol production in Brazilian biorefineries. In this article, three main scenarios were evaluated: first‐generation ethanol production with the average current technology; the improved current technology; and the integration of improved first‐ and second‐generation ethanol production. For the improved first‐generation scenario, a US$1 million increase in ethanol demand can give rise to US$2.5 million of total economic activity in the Brazilian economy when direct and indirect purchases of inputs are considered. This value is slightly higher than the economic activity (US$1.8 million) for an energy equivalent amount of gasoline. The integration of first‐ and second‐generation technologies significantly reduces the total greenhouse gas emissions of ethanol production: 14.6 versus 86.4 grams of carbon dioxide equivalent per megajoule (g CO₂‐eq/MJ) for gasoline. Moreover, emissions of ethanol can be negative (–10.5 g CO₂‐eq/MJ) when the system boundary is expanded to account for surplus bioelectricity by displacement of natural gas thermal electricity generation considering electricity produced in first‐generation optimized biorefineries.     

Lactic Acid Production from Pretreated Hydrolysates of Corn Stover by a Newly Developed Bacillus coagulans Strain

An inhibitor-tolerance strain, Bacillus coagulans GKN316, was developed through atmospheric and room temperature plasma (ARTP) mutation and evolution experiment in condensed dilute-acid hydrolysate (CDH) of corn stover. The fermentabilities of other hydrolysates with B. coagulans GKN316 and the parental strain B. coagulans NL01 were assessed. When using condensed acid-catalyzed steam-exploded hydrolysate (CASEH), condensed acid-catalyzed liquid hot water hydrolysate (CALH) and condensed acid-catalyzed sulfite hydrolysate (CASH) as substrates, the concentration of lactic acid reached 45.39, 16.83, and 18.71 g/L by B. coagulans GKN316, respectively. But for B. coagulans NL01, only CASEH could be directly fermented to produce 15.47 g/L lactic acid. The individual inhibitory effect of furfural, 5-hydroxymethylfurfural (HMF), vanillin, syringaldehyde and p-hydroxybenzaldehyde (pHBal) on xylose utilization by B. coagulans GKN316 was also studied. The strain B. coagulans GKN316 could effectively convert these toxic inhibitors to the less toxic corresponding alcohols in situ. These results suggested that B. coagulans GKN316 was well suited to production of lactic acid from undetoxified lignocellulosic hydrolysates.     

Characteristics of Corn Stover Pretreated with Liquid Hot Water and Fed-Batch Semi-Simultaneous Saccharification and Fermentation for Bioethanol Production

Corn stover is a promising feedstock for bioethanol production because of its abundant availability in China. To obtain higher ethanol concentration and higher ethanol yield, liquid hot water (LHW) pretreatment and fed-batch semi-simultaneous saccharification and fermentation (S-SSF) were used to enhance the enzymatic digestibility of corn stover and improve bioconversion of cellulose to ethanol. The results show that solid residues from LHW pretreatment of corn stover can be effectively converted into ethanol at severity factors ranging from 3.95 to 4.54, and the highest amount of xylan removed was approximately 89%. The ethanol concentrations of 38.4 g/L and 39.4 g/L as well as ethanol yields of 78.6% and 79.7% at severity factors of 3.95 and 4.54, respectively, were obtained by fed-batch S-SSF in an optimum conditions (initial substrate consistency of 10%, and 6.1% solid residues added into system at the prehydrolysis time of 6 h). The changes in surface morphological structure, specific surface area, pore volume and diameter of corn stover subjected to LHW process were also analyzed for interpreting the possible improvement mechanism.     

Aerobic and Anaerobic Storage of Single-pass,Chopped Corn Stover

Corn stover has great potential as a biomass feedstock due its widespread availability. However, storage characteristics of moist corn stover harvested from single-pass harvesters have not been well quantified. In 2007, whole-plant corn stover at 19.1–40.3% (w.b.) moisture content was stored for 237 days in aerobic piles, one covered and one uncovered, as well an anaerobic silo bag. In 2008, two stover materials—whole plant and cob/husk from 31.7% to 58.1% (w.b.) moisture—were stored for 183 or 204 days in covered and uncovered anaerobic piles, ventilated bags, or anaerobic silo bags. Stover stored in uncovered piles was rehydrated by precipitation, which increased biological activity resulting in dry matter (DM) losses from 8.2% to 39.1% with an average of 21.5%. Stover in covered piles was successfully conserved when the average moisture was less than 25% (w.b.) with DM losses of 3.3%. Stover above 36% (w.b.) moisture and piled under a plastic cover had DM losses from 6.4% to 20.2% with an average of 11.9%. Localized heating occurred in the aerobic piles when moisture was above 45% (w.b.) which lead to temperatures where spontaneous combustion might be a concern (i.e., >70°C). Ambient air blown through a center tube in the ventilated storage bag dried stover near the tube to an average of 24.2% (w.b.), but the remainder of the bag averaged 46.8% (w.b.) at removal. Loss of DM ranged from 7.4% to 22.0% with an average of 11.8% with this storage method. Stover was most successfully conserved in the bags where anaerobic conditions were maintained. Under anaerobic conditions, DM losses ranged from 0.2% to 0.9%. When anaerobic conditions were not maintained in the silo bag, DM losses averaged 6.1% of DM. Anaerobic storage is the best solution for conserving the value of moist corn stover.     

Assessing the Soil Carbon,Biomass Production,and Nitrous Oxide Emission Impact of Corn Stover Management for Bioenergy Feedstock Production Using DAYCENT

Harvesting crop residue needs to be managed to protect agroecosystem health and productivity. DAYCENT, a process-based modeling tool, may be suited to accommodate region-specific factors and provide regional predictions for a broad array of agroecosystem impacts associated with corn stover harvest. Grain yield, soil C, and N₂O emission data collected at Corn Stover Regional Partnership experimental sites were used to test DAYCENT performance modeling the impacts of corn stover removal. DAYCENT estimations of stover yields were correlated and reasonably accurate (adjusted r ²?=?0.53, slope?=?1.18, p?<<?0.001, intercept?=?0.36, p?=?0.11). Measured and simulated average grain yields across sites did not differ as a function of residue removal, but the model tended to underestimate average measured grain yields. Modeled and measured soil organic carbon (SOC) change for all sites were correlated (adjusted r ²?=?0.54, p?<<?0.001), but DAYCENT overestimated SOC loss with conventional tillage. Simulated and measured SOC change did not vary by residue removal rate. DAYCENT simulated annual N₂O flux more accurately at low rates (≤2-kg N₂O-N ha^?1 year^?1) but underestimated when emission rates were >3-kg N₂O-N ha^?1 year^?1. Overall, DAYCENT performed well at simulating stover yields and low N₂O emission rates, reasonably well when simulating the effects of management practices on average grain yields and SOC change, and poorly when estimating high N₂O emissions. These biases should be considered when DAYCENT is used as a decision support tool for recommending sustainable corn stover removal practices to advance bioenergy industry based on corn stover feedstock material.