A review of widely used drought indices and the challenges of drought assessment under climate change.

Under climate change, drought assessment, which can address nonstationarity in drought indicators and anthropogenic implications, is required to mitigate drought impacts. However, the development of drought indices for a reliable drought assessment is a challenging task in the warming climate. Thus, this study discusses factors that should be considered in developing drought indices in changing climate. Inconsistent drought assessment can be obtained, depending on the baseline period defined in developing drought indices. Therefore, the baseline period should represent the contemporary climate but should also correspond to long enough observations for stable parameter estimation. The importance of accurate potential evapotranspiration (PET) for drought indices becomes higher under a warming climate. Although the Penman-Monteith method yields accurate PET values, depending on the climate and vegetation cover, other suitable PET formulas, such as the Hargreaves method, with fewer hydrometeorological data can be used. Since a single drought index is not enough to properly monitor drought evolution, a method that can objectively combine multiple drought indices is required. Besides, quantifying anthropogenic impacts, which can add more uncertainty, on drought assessment is also important to adapt to the changing drought conditions and minimize human-induced drought. Drought is expected to occur more frequently with more severe, longer, and larger areal extent under global warming, since a more arid background, which climate change will provide, intensifies land-atmosphere feedback, leading to the desiccation of land and drying atmosphere. Thus, an accurate drought assessment, based on robust drought indices, is required.

Artificial intelligence-assisted ultrasound-guided focused ultrasound therapy: a feasibility study.

OBJECTIVES: Focused ultrasound (FUS) therapy has emerged as a promising noninvasive solution for tumor ablation. Accurate monitoring and guidance of ultrasound energy is crucial for effective FUS treatment. Although ultrasound (US) imaging is a well-suited modality for FUS monitoring, US-guided FUS (USgFUS) faces challenges in achieving precise monitoring, leading to unpredictable ablation shapes and a lack of quantitative monitoring. The demand for precise FUS monitoring heightens when complete tumor ablation involves controlling multiple sonication procedures. METHODS: To address these challenges, we propose an artificial intelligence (AI)-assisted USgFUS framework, incorporating an AI segmentation model with B-mode ultrasound imaging. This method labels the ablated regions distinguished by the hyperechogenicity effect, potentially bolstering FUS guidance. We evaluated our proposed method using the Swin-Unet AI architecture, conducting experiments with a USgFUS setup on chicken breast tissue. RESULTS: Our results showed a 93% accuracy in identifying ablated areas marked by the hyperechogenicity effect in B-mode imaging. CONCLUSION: Our findings suggest that AI-assisted ultrasound monitoring can significantly improve the precision and control of FUS treatments, suggesting a crucial advancement toward the development of more effective FUS treatment strategies.

Solid-State Reaction Heterogeneity During Calcination of Lithium-Ion Battery Cathode.

During solid-state calcination, with increasing temperature, materials undergo complex phase transitions with heterogeneous solid-state reactions and mass transport. Precise control of the calcination chemistry is therefore crucial for synthesizing state-of-the-art Ni-rich layered oxides (LiNi1-x-y Cox Mny O2 , NRNCM) as cathode materials for lithium-ion batteries. Although the battery performance depends on the chemical heterogeneity during NRNCM calcination, it has not yet been elucidated. Herein, through synchrotron-based X-ray, mass spectrometry microscopy, and structural analyses, it is revealed that the temperature-dependent reaction kinetics, the diffusivity of solid-state lithium sources, and the ambient oxygen control the local chemical compositions of the reaction intermediates within a calcined particle. Additionally, it is found that the variations in the reducing power of the transition metals (i.e., Ni, Co, and Mn) determine the local structures at the nanoscale. The investigation of the reaction mechanism via imaging analysis provides valuable information for tuning the calcination chemistry and developing high-energy/power density lithium-ion batteries.

Homogenizing Silicon Domains in SiOx Anode during Cycling and Enhancing Battery Performance via Magnesium Doping.

SiOx (x ≈ 1) is one of the most promising anode materials for application in secondary lithium-ion batteries because of its high theoretical capacity. Despite this merit, SiOx has a poor initial Coulombic efficiency, which impedes its widespread use. To overcome this limitation, in this work, we successfully demonstrate a novel synthesis of Mg-doped SiOx via a mass-producible physical vapor deposition method. The solid-state reaction between Mg and SiOx produces Si and electrochemically inert magnesium silicate, thus increasing the initial Coulombic efficiency. The Mg doping concentration determines the phase of the magnesium silicate domains, the size of the Si domains, and the heterogeneity of these two domains. Detailed electron microscopy and synchrotron-based analysis revealed that the nanoscale homogeneity of magnesium silicates driven by cycling significantly affected the lifetime. We found that 8 wt % Mg is the most optimized concentration for enhanced cyclability because MgSiO3, which is the dominant magnesium silicate composition, can be homogeneously mixed with silicon clusters, preventing their aggregation during cycling and suppressing void formation.

Nanoscale light element identification using machine learning aided STEM-EDS.

Light element identification is necessary in materials research to obtain detailed insight into various material properties. However, reported techniques, such as scanning transmission electron microscopy (STEM)-energy dispersive X-ray spectroscopy (EDS) have inadequate detection limits, which impairs identification. In this study, we achieved light element identification with nanoscale spatial resolution in a multi-component metal alloy through unsupervised machine learning algorithms of singular value decomposition (SVD) and independent component analysis (ICA). Improvement of the signal-to-noise ratio (SNR) in the STEM-EDS spectrum images was achieved by combining SVD and ICA, leading to the identification of a nanoscale N-depleted region that was not observed in as-measured STEM-EDS. Additionally, the formation of the nanoscale N-depleted region was validated using STEM-electron energy loss spectroscopy and multicomponent diffusional transformation simulation. The enhancement of SNR in STEM-EDS spectrum images by machine learning algorithms can provide an efficient, economical chemical analysis method to identify light elements at the nanoscale.

Trends in contralateral prophylactic mastectomy rate according to clinicopathologic and socioeconomic status.

PURPOSE: There has been an increasing trend in the use of contralateral prophylactic mastectomy (CPM) among women diagnosed with unilateral breast cancer or mutations in BRCA1 or BRCA2 to reduce the occurrence of contralateral breast cancer. This study aimed to examine trends in the CPM rate according to clinicopathologic and socioeconomic status at a single institution in Korea. METHODS: This study included 128 patients with mutations in BRCA1 or BRCA2. Patients were divided into a CPM group (n = 8) and a non-CPM group (n = 120) between May 2013 and March 2016. The main outcome variables, including epidemiology, clinical features, socioeconomic status, and tumor characteristics, were analyzed. RESULTS: A total of 8 CPMs were performed among 128 patients. All CPM patients were married. The proportion of professional working women was higher in the CPM group (P = 0.049). Most patients who underwent CPM graduated college, compared to less than a third of the non-CPM group (P = 0.013). The CPM group had a higher rate of visits to the Hereditary Breast and Ovarian Cancer (HBOC) clinic (P = 0.021). The risk-reducing salpingo-oophorectomy (RRSO) rate was significantly higher in the CPM group (P < 0.01). CONCLUSION: CPM rates were significantly different according to socioeconomic status. The CPM rate tends to increase in highly educated and professional working women. The socioeconomic status of patients is an important factor in the decision to participate in the HBOC clinic and undergo CPM or RRSO.

Current and Future United States Light-Duty Vehicle Pathways: Cradle-to-Grave Lifecycle Greenhouse Gas Emissions and Economic Assessment.

This article presents a cradle-to-grave (C2G) assessment of greenhouse gas (GHG) emissions and costs for current (2015) and future (2025-2030) light-duty vehicles. The analysis addressed both fuel cycle and vehicle manufacturing cycle for the following vehicle types: gasoline and diesel internal combustion engine vehicles (ICEVs), flex fuel vehicles, compressed natural gas (CNG) vehicles, hybrid electric vehicles (HEVs), hydrogen fuel cell electric vehicles (FCEVs), battery electric vehicles (BEVs), and plug-in hybrid electric vehicles (PHEVs). Gasoline ICEVs using current technology have C2G emissions of ∼450 gCO2e/mi (grams of carbon dioxide equivalents per mile), while C2G emissions from HEVs, PHEVs, H2 FCEVs, and BEVs range from 300-350 gCO2e/mi. Future vehicle efficiency gains are expected to reduce emissions to ∼350 gCO2/mi for ICEVs and ∼250 gCO2e/mi for HEVs, PHEVs, FCEVs, and BEVs. Utilizing low-carbon fuel pathways yields GHG reductions more than double those achieved by vehicle efficiency gains alone. Levelized costs of driving (LCDs) are in the range $0.25-$1.00/mi depending on time frame and vehicle-fuel technology. In all cases, vehicle cost represents the major (60-90%) contribution to LCDs. Currently, HEV and PHEV petroleum-fueled vehicles provide the most attractive cost in terms of avoided carbon emissions, although they offer lower potential GHG reductions. The ranges of LCD and cost of avoided carbon are narrower for the future technology pathways, reflecting the expected economic competitiveness of these alternative vehicles and fuels.

Life cycle energy and greenhouse gas emission effects of biodiesel in the United States with induced land use change impacts.

This study conducted the updated simulations to depict a life cycle analysis (LCA) of the biodiesel production from soybeans and other feedstocks in the U.S. It addressed in details the interaction between LCA and induced land use change (ILUC) for biodiesel. Relative to the conventional petroleum diesel, soy biodiesel could achieve 76% reduction in GHG emissions without considering ILUC, or 66-72% reduction in overall GHG emissions when various ILUC cases were considered. Soy biodiesel's fossil fuel consumption rate was also 80% lower than its petroleum counterpart. Furthermore, this study examined the cause and the implication of each key parameter affecting biodiesel LCA results using a sensitivity analysis, which identified the hot spots for fossil fuel consumption and GHG emissions of biodiesel so that future efforts can be made accordingly. Finally, biodiesel produced from other feedstocks (canola oil and tallow) were also investigated to contrast with soy biodiesel and petroleum diesel.

Well-to-wake analysis of ethanol-to-jet and sugar-to-jet pathways.

BACKGROUND: To reduce the environmental impacts of the aviation sector as air traffic grows steadily, the aviation industry has paid increasing attention to bio-based alternative jet fuels (AJFs), which may provide lower life-cycle petroleum consumption and greenhouse gas (GHG) emissions than petroleum jet fuel. This study presents well-to-wake (WTWa) results for four emerging AJFs: ethanol-to-jet (ETJ) from corn and corn stover, and sugar-to-jet (STJ) from corn stover via both biological and catalytic conversion. For the ETJ pathways, two plant designs were examined: integrated (processing corn or corn stover as feedstock) and distributed (processing ethanol as feedstock). Also, three H2 options for STJ via catalytic conversion are investigated: external H2 from natural gas (NG) steam methane reforming (SMR), in situ H2, and H2 from biomass gasification. RESULTS: Results demonstrate that the feedstock is a key factor in the WTWa GHG emissions of ETJ: corn- and corn stover-based ETJ are estimated to produce WTWa GHG emissions that are 16 and 73%, respectively, less than those of petroleum jet. As for the STJ pathways, this study shows that STJ via biological conversion could generate WTWa GHG emissions 59% below those of petroleum jet. STJ via catalytic conversion could reduce the WTWa GHG emissions by 28% with H2 from NG SMR or 71% with H2 from biomass gasification than those of petroleum jet. This study also examines the impacts of co-product handling methods, and shows that the WTWa GHG emissions of corn stover-based ETJ, when estimated with a displacement method, are lower by 11 g CO2e/MJ than those estimated with an energy allocation method. CONCLUSION: Corn- and corn stover-based ETJ as well as corn stover-based STJ show potentials to reduce WTWa GHG emissions compared to petroleum jet. Particularly, WTWa GHG emissions of STJ via catalytic conversion depend highly on the hydrogen source. On the other hand, ETJ offers unique opportunities to exploit extensive existing corn ethanol plants and infrastructure, and to provide a boost to staggering ethanol demand, which is largely being used as gasoline blendstock.

BRCA1 and BRCA2 mutation predictions using the BRCAPRO and Myriad models in Korean ovarian cancer patients.

OBJECTIVE: To evaluate the predictive efficacies including sensitivity and positive predictive value of the genetic risk prediction model BRCAPRO and the Myriad BRCA risk calculator in Korean ovarian cancer patients. METHODS: Individuals undergoing genetic testing for BRCA mutations from November 2010-August 2016 were recruited from the Department of Obstetrics and Gynecology at a single institute in Korea. The observed BRCA1 and BRCA2 mutation statuses were compared with the predicted carrier probabilities using BRCAPRO and the Myriad BRCA risk calculator. RESULTS: Two hundred thirty-two patients were recruited, of whom 99.1% (230/232) were of Korean ethnicity. Of the 232 individuals, 206 and 26 had ovarian and double primary breast/ovarian cancer, respectively. Thirty-six individuals had a family history of breast/ovarian cancer in first-degree relatives. Fifty-seven patients (24.6%) tested positive for BRCA mutation (41 BRCA1, 16 BRCA2). The mean BRCAPRO and Myriad scores for all patients were 6.4% and 7.7%, respectively. The scores were significantly higher for patients with positive BRCA mutation status (29.0% vs. 6.1%, P<0.001, 12.1% vs. 7.7%, P<0.001, respectively). For all patients, the respective areas under the receiver operating characteristics curves were 0.720 and 0.747 for the BRCAPRO and Myriad models to predict the risk of carrying a BRCA mutation. Both models overestimated the mutation probability in patients with a family history of breast/ovarian cancer (1.55-fold and 1.50-fold, respectively) and underestimated the probability in patients without a family history (both, 0.54-fold). CONCLUSION: BRCAPRO and Myriad seem to be acceptable risk assessment tools for determining the risk of carrying BRCA mutations in Korean ovarian cancer patients.

Comparison of Clinical Outcomes of BRCA1/2 Pathologic Mutation, Variants of Unknown Significance, or Wild Type Epithelial Ovarian Cancer Patients.

PURPOSE: The purpose of this study was to investigate the clinical features of epithelial ovarian cancer (EOC) patients according to BRCA1/2 mutation status (mutation, variant of uncertain significance [VUS], or wild type). MATERIALS AND METHODS: We analyzed 116 patients whose BRCA1/2 genetic test results were available for mutation type and clinical features, including progression-free survival (PFS), overall survival (OS), and response rate. These characteristics were compared according to BRCA1/2 mutation status. RESULTS: Thirty-seven (37/116, 31.9%) BRCA1/2mutations were identified (BRCA1, 30; BRCA2, 7). Mutation of c.3627_3628insA (p.Leu1209_Glu1210?fs) in BRCA1 was observed in five patients (5/37, 13.5%). Twenty-five patients had BRCA1/2 VUSs (25/116, 21.6%). Personal histories of breast cancer were observed in 48.6% of patients with BRCA1/2 mutation (18/37), 16.0% of patients with BRCA1/2 VUS (4/25), and 7.4% of patients with BRCA wild type (4/54) (p < 0.001). Patients with BRCA1/2 mutation showed longer OS than those with BRCA1/2 wild type (p=0.005). No significant differences were detected in PFS, OS, or response rates between patients with BRCA1/2 VUS and BRCA1/2 mutation (p=0.772, p=0.459, and p=0.898, respectively). CONCLUSION: Patientswith BRCA1/2 mutation had longer OS than thosewith BRCA1/2wild type. Patients with BRCA1/2 mutation and BRCA1/2 VUS displayed similar prognoses.

Anisotropic Terahertz Emission from Bi2Se3 Thin Films with Inclined Crystal Planes.

We investigate the surface states of topological insulator (TI) Bi2Se3 thin films grown on Si nanocrystals and Al2O3 substrates by using terahertz (THz) emission spectroscopy. Compared to bulk crystalline Bi2Te2Se, film TIs exhibit distinct behaviors in the phase and amplitude of emitted THz radiation. In particular, Bi2Se3 grown on Al2O3 shows an anisotropic response with a strong modulation of the THz signal in its phase. From x-ray diffraction, we find that the crystal plane of the Bi2Se3 films is inclined with respect to the plane of the Al2O3 substrate by about 0.27°. This structural anisotropy affects the dynamics of photocarriers and hence leads to the observed anisotropic response in the THz emission. Such relevance demonstrates that THz emission spectroscopy can be a sensitive tool to investigate the fine details of the surface crystallography and electrostatics of thin film TIs.

Influence of corn oil recovery on life-cycle greenhouse gas emissions of corn ethanol and corn oil biodiesel.

BACKGROUND: Corn oil recovery and conversion to biodiesel has been widely adopted at corn ethanol plants recently. The US EPA has projected 2.6 billion liters of biodiesel will be produced from corn oil in 2022. Corn oil biodiesel may qualify for federal renewable identification number (RIN) credits under the Renewable Fuel Standard, as well as for low greenhouse gas (GHG) emission intensity credits under California's Low Carbon Fuel Standard. Because multiple products [ethanol, biodiesel, and distiller's grain with solubles (DGS)] are produced from one feedstock (corn), however, a careful co-product treatment approach is required to accurately estimate GHG intensities of both ethanol and corn oil biodiesel and to avoid double counting of benefits associated with corn oil biodiesel production. RESULTS: This study develops four co-product treatment methods: (1) displacement, (2) marginal, (3) hybrid allocation, and (4) process-level energy allocation. Life-cycle GHG emissions for corn oil biodiesel were more sensitive to the choice of co-product allocation method because significantly less corn oil biodiesel is produced than corn ethanol at a dry mill. Corn ethanol life-cycle GHG emissions with the displacement, marginal, and hybrid allocation approaches are similar (61, 62, and 59 g CO2e/MJ, respectively). Although corn ethanol and DGS share upstream farming and conversion burdens in both the hybrid and process-level energy allocation methods, DGS bears a higher burden in the latter because it has lower energy content per selling price as compared to corn ethanol. As a result, with the process-level allocation approach, ethanol's life-cycle GHG emissions are lower at 46 g CO2e/MJ. Corn oil biodiesel life-cycle GHG emissions from the marginal, hybrid allocation, and process-level energy allocation methods were 14, 59, and 45 g CO2e/MJ, respectively. Sensitivity analyses were conducted to investigate the influence corn oil yield, soy biodiesel, and defatted DGS displacement credits, and energy consumption for corn oil production and corn oil biodiesel production. CONCLUSIONS: This study's results demonstrate that co-product treatment methodology strongly influences corn oil biodiesel life-cycle GHG emissions and can affect how this fuel is treated under the Renewable Fuel and Low Carbon Fuel Standards.

Well-to-Wheels Greenhouse Gas Emissions of Canadian Oil Sands Products: Implications for U.S. Petroleum Fuels.

Greenhouse gas (GHG) regulations affecting U.S. transportation fuels require holistic examination of the life-cycle emissions of U.S. petroleum feedstocks. With an expanded system boundary that included land disturbance-induced GHG emissions, we estimated well-to-wheels (WTW) GHG emissions of U.S. production of gasoline and diesel sourced from Canadian oil sands. Our analysis was based on detailed characterization of the energy intensities of 27 oil sands projects, representing industrial practices and technological advances since 2008. Four major oil sands production pathways were examined, including bitumen and synthetic crude oil (SCO) from both surface mining and in situ projects. Pathway-average GHG emissions from oil sands extraction, separation, and upgrading ranged from ∼6.1 to ∼27.3 g CO2 equivalents per megajoule (in lower heating value, CO2e/MJ). This range can be compared to ∼4.4 g CO2e/MJ for U.S. conventional crude oil recovery. Depending on the extraction technology and product type output of oil sands projects, the WTW GHG emissions for gasoline and diesel produced from bitumen and SCO in U.S. refineries were in the range of 100-115 and 99-117 g CO2e/MJ, respectively, representing, on average, about 18% and 21% higher emissions than those derived from U.S. conventional crudes. WTW GHG emissions of gasoline and diesel derived from diluted bitumen ranged from 97 to 103 and 96 to 104 g CO2e/MJ, respectively, showing the effect of diluent use on fuel emissions.

Insulin priming effect on estradiol-induced breast cancer metabolism and growth.

Diabetes is a risk factor for breast cancer development and is associated with poor prognosis for breast cancer patients. However, the molecular and biochemical mechanisms underlying the association between diabetes and breast cancer have not been fully elucidated. Here, we investigated estradiol response in MCF-7 breast cancer cells with or without chronic exposure to insulin. We found that insulin priming is necessary and specific for estradiol-induced cancer cell growth, and induces anaplerotic shunting of glucose into macromolecule biosynthesis in the estradiol treated cells. Treatment with ERK or Akt specific inhibitors, U0126 or LY294002, respectively, suppressed estradiol-induced growth. Interestingly, molecular analysis revealed that estradiol treatment markedly increases expression of cyclin A and B, and decreases p21 and p27 in the insulin-primed cells. In addition, estradiol treatment activated metabolic genes in pentose phosphate (PPP) and serine biosynthesis pathways in the insulin-primed cells while insulin priming decreased metabolic gene expression associated with glucose catabolism in the breast cancer cells. Finally, we found that anti-diabetic drug metformin and AMPK ligand AICAR, but not thiazolidinediones (TZDs), specifically suppress the estradiol-induced cellular growth in the insulin-primed cells. These findings suggest that estrogen receptor (ER) activation under chronic hyperinsulinemic condition increases breast cancer growth through the modulation of cell cycle and apoptotic factors and nutrient metabolism, and further provide a mechanistic evidence for the clinical benefit of metformin use for ER-positive breast cancer patients with diabetes.

Life-cycle fossil energy consumption and greenhouse gas emissions of bioderived chemicals and their conventional counterparts.

Biomass-derived chemical products may offer reduced environmental impacts compared to their fossil-derived counterparts and could improve profit margins at biorefineries when coproduced with higher-volume, lower-profit margin biofuels. It is important to assess on a life-cycle basis the energy and environmental impacts of these bioproducts as compared to conventional, fossil-derived products. We undertook a life-cycle analysis of eight bioproducts produced from either algal-derived glycerol or corn stover-derived sugars. Selected on the basis of technology readiness and market potential, the bioproducts are propylene glycol, 1,3-propanediol, 3-hydroxypropionic acid, acrylic acid, polyethylene, succinic acid, isobutanol, and 1,4-butanediol. We developed process simulations to obtain energy and material flows in the production of each bioproduct and examined sensitivity of these flows to process design assumptions. Conversion process data for fossil-derived products were based on the literature. Conversion process data were combined with upstream parameters in the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model to generate life-cycle greenhouse gas (GHG) emissions and fossil energy consumption (FEC) for each bioproduct and its corresponding petroleum-derived product. The bioproducts uniformly offer GHG emissions reductions compared to their fossil counterparts ranging from 39 to 86% on a cradle-to-grave basis. Similarly, FEC was lower for bioproducts than for conventional products.

Energy efficiency and greenhouse gas emission intensity of petroleum products at U.S. refineries.

This paper describes the development of (1) a formula correlating the variation in overall refinery energy efficiency with crude quality, refinery complexity, and product slate; and (2) a methodology for calculating energy and greenhouse gas (GHG) emission intensities and processing fuel shares of major U.S. refinery products. Overall refinery energy efficiency is the ratio of the energy present in all product streams divided by the energy in all input streams. Using linear programming (LP) modeling of the various refinery processing units, we analyzed 43 refineries that process 70% of total crude input to U.S. refineries and cover the largest four Petroleum Administration for Defense District (PADD) regions (I, II, III, V). Based on the allocation of process energy among products at the process unit level, the weighted-average product-specific energy efficiencies (and ranges) are estimated to be 88.6% (86.2%-91.2%) for gasoline, 90.9% (84.8%-94.5%) for diesel, 95.3% (93.0%-97.5%) for jet fuel, 94.5% (91.6%-96.2%) for residual fuel oil (RFO), and 90.8% (88.0%-94.3%) for liquefied petroleum gas (LPG). The corresponding weighted-average, production GHG emission intensities (and ranges) (in grams of carbon dioxide-equivalent (CO2e) per megajoule (MJ)) are estimated to be 7.8 (6.2-9.8) for gasoline, 4.9 (2.7-9.9) for diesel, 2.3 (0.9-4.4) for jet fuel, 3.4 (1.5-6.9) for RFO, and 6.6 (4.3-9.2) for LPG. The findings of this study are key components of the life-cycle assessment of GHG emissions associated with various petroleum fuels; such assessment is the centerpiece of legislation developed and promulgated by government agencies in the United States and abroad to reduce GHG emissions and abate global warming.

U.S. refinery efficiency: impacts analysis and implications for fuel carbon policy implementation.

In the next two decades, the U.S. refining industry will face significant changes resulting from a rapidly evolving domestic petroleum energy landscape. The rapid influx of domestically sourced tight light oil and relative demand shifts for gasoline and diesel will impose challenges on the ability of the U.S. refining industry to satisfy both demand and quality requirements. This study uses results from Linear Programming (LP) modeling data to examine the potential impacts of these changes on refinery, process unit, and product-specific efficiencies, focusing on current baseline efficiency values across 43 existing large U.S. refineries that are operating today. These results suggest that refinery and product-specific efficiency values are sensitive to crude quality, seasonal and regional factors, and refinery configuration and complexity, which are determined by final fuel specification requirements. Additional processing of domestically sourced tight light oil could marginally increase refinery efficiency, but these benefits could be offset by crude rebalancing. The dynamic relationship between efficiency and key parameters such as crude API gravity, sulfur content, heavy products, residual upgrading, and complexity are key to understanding possible future changes in refinery efficiency. Relative to gasoline, the efficiency of diesel production is highly variable, and is influenced by the number and severity of units required to produce diesel. To respond to future demand requirements, refiners will need to reduce the gasoline/diesel (G/D) production ratio, which will likely result in greater volumes of diesel being produced through less efficient pathways resulting in reduced efficiency, particularly on the marginal barrel of diesel. This decline in diesel efficiency could be offset by blending of Gas to Liquids (GTL) diesel, which could allow refiners to uplift intermediate fuel streams into more efficient diesel production pathways, thereby allowing for the efficient production of incremental barrels of diesel without added capital investment for the refiner. Given the current wide range of refinery carbon intensity values of baseline transportation fuels in LCA models, this study has shown that the determination of refinery, unit, and product efficiency values requires careful consideration in the context of specific transportation fuel GHG policy objectives.

Life-cycle energy use and greenhouse gas emissions of production of bioethanol from sorghum in the United States.

BACKGROUND: The availability of feedstock options is a key to meeting the volumetric requirement of 136.3 billion liters of renewable fuels per year beginning in 2022, as required in the US 2007 Energy Independence and Security Act. Life-cycle greenhouse gas (GHG) emissions of sorghum-based ethanol need to be assessed for sorghum to play a role in meeting that requirement. RESULTS: Multiple sorghum-based ethanol production pathways show diverse well-to-wheels (WTW) energy use and GHG emissions due to differences in energy use and fertilizer use intensity associated with sorghum growth and differences in the ethanol conversion processes. All sorghum-based ethanol pathways can achieve significant fossil energy savings. Relative to GHG emissions from conventional gasoline, grain sorghum-based ethanol can reduce WTW GHG emissions by 35% or 23%, respectively, when wet or dried distillers grains with solubles (DGS) is the co-product and fossil natural gas (FNG) is consumed as the process fuel. The reduction increased to 56% or 55%, respectively, for wet or dried DGS co-production when renewable natural gas (RNG) from anaerobic digestion of animal waste is used as the process fuel. These results do not include land-use change (LUC) GHG emissions, which we take as negligible. If LUC GHG emissions for grain sorghum ethanol as estimated by the US Environmental Protection Agency (EPA) are included (26 g CO2e/MJ), these reductions when wet DGS is co-produced decrease to 7% or 29% when FNG or RNG is used as the process fuel. Sweet sorghum-based ethanol can reduce GHG emissions by 71% or 72% without or with use of co-produced vinasse as farm fertilizer, respectively, in ethanol plants using only sugar juice to produce ethanol. If both sugar and cellulosic bagasse were used in the future for ethanol production, an ethanol plant with a combined heat and power (CHP) system that supplies all process energy can achieve a GHG emission reduction of 70% or 72%, respectively, without or with vinasse fertigation. Forage sorghum-based ethanol can achieve a 49% WTW GHG emission reduction when ethanol plants meet process energy demands with CHP. In the case of forage sorghum and an integrated sweet sorghum pathway, the use of a portion of feedstock to fuel CHP systems significantly reduces fossil fuel consumption and GHG emissions. CONCLUSIONS: This study provides new insight into life-cycle energy use and GHG emissions of multiple sorghum-based ethanol production pathways in the US. Our results show that adding sorghum feedstocks to the existing options for ethanol production could help in meeting the requirements for volumes of renewable, advanced and cellulosic bioethanol production in the US required by the EPA's Renewable Fuel Standard program.

Life-cycle analysis of bio-based aviation fuels.

Well-to-wake (WTWa) analysis of bio-based aviation fuels, including hydroprocessed renewable jet (HRJ) from various oil seeds, Fischer-Tropsch jet (FTJ) from corn-stover and co-feeding of coal and corn-stover, and pyrolysis jet from corn stover, is conducted and compared with petroleum jet. WTWa GHG emission reductions relative to petroleum jet can be 41-63% for HRJ, 68-76% for pyrolysis jet and 89% for FTJ from corn stover. The HRJ production stage dominates WTWa GHG emissions from HRJ pathways. The differences in GHG emissions from HRJ production stage among considered feedstocks are much smaller than those from fertilizer use and N2O emissions related to feedstock collection stage. Sensitivity analyses on FTJ production from coal and corn-stover are also conducted, showing the importance of biomass share in the feedstock, carbon capture and sequestration options, and overall efficiency. For both HRJ and FTJ, co-product handling methods have significant impacts on WTWa results.