Life-Cycle Greenhouse Gas Emissions of Sustainable Aviation Fuel through a Net-Zero Carbon Biofuel Plant Design
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This study evaluated multiple commercially available continuous monitoring (CM) point sensor network (PSN) solutions under single-blind controlled release testing conducted at operational upstream and midstream oil and natural gas (O&G) sites. During releases, PSNs reported site-level emission rate estimates of 0 kg/h between 38 and 86% of the time. When non-zero site-level emission rate estimates were provided, no linear correlation between the release rate and the reported emission rate estimate was observed. The average, aggregated across all PSN solutions during releases, shows 5% of the mixing ratio readings at downwind sensors were greater than the site’s baseline plus two standard deviations. Four of seven total PSN solutions tested during this field campaign provided site-level emission rate estimates with the site average relative error ranging from −100% to 24% for solution D, −100% to −43% for solution E, −25% for solution F (solution F was only at one site), and −99% to 430% for solution G, with an overall average of −29% across all sites and solutions. Of all the individual site-level emission rate estimates, only 11% were within ±2.5 kg/h of the study team’s best estimate of site-level emissions at the time of the releases.
Recent Greening the Grid studies for India highlight the benefits of flexible resources for integrating variable renewable energy onto India’s electricity system. India’s ambitious renewable energy targets, which are particularly focused on renewable resource states such as Karnataka, will face fewer challenges when combined with new planning and operational strategies and technologies. This report explores one such strategy - demand response - by which the system operator shifts load throughout a day to minimize system wide production costs. To explore this strategy, we added demand response resources to Karnataka’s electricity system in a production cost model of India, using load shifting potential analyzed by Lawrence Berkeley National Labs. We then investigated the impacts of increasing demand response capacity under several renewable resource scenarios. Our results show the addition of demand response enables fuel shifting from high-marginal-cost and emissions-intensive subcritical coal and diesel generation to zero-marginal-cost and emissions-free renewable generation. Accordingly, the value that demand response provides to the system increases as the renewable penetration increases. In addition to reducing production costs and emissions, demand response reduces the time that thermal generators spend at their minimum output levels, which typically represents a less efficient and costlier operational state. Agricultural load shifting provides greater value to the system than residential, commercial, or industrial loads. Agricultural demand response is more flexible than other sectors because it is not exposed to subdaily operational constraints and it can operate for more hours per day without impacting customer satisfaction. Further, the first increment of demand response that is added to a system provides the greatest value; further additions provide additional benefits but have a decreasing impact. The insights we discuss could be leveraged by system planners and operators in other jurisdictions, particularly those facing significant renewable energy penetrations, to develop their own demand response programs.
Low-dimensional hybrid organic–inorganic metal halides have received increased attention because of their outstanding optical and electronic properties. However, the most studied hybrid compounds contain lead and have long-term stability issues, which must be addressed for their use in practical applications. In this work, we report a new zero-dimensional hybrid organic–inorganic halide, RInBr 4 , featuring photoemissive trimethyl(4-stilbenyl)methylammonium (R + ) cations and nonemissive InBr 4 – tetrahedral anions. The crystal structure of RInBr 4 is composed of alternating layers of inorganic anions and organic cations along the crystallographic a axis. The resultant hybrid demonstrates bright-blue emission with Commission Internationale de l’Eclairage color coordinates of (0.19, 0.20) and a high photoluminescence quantum yield (PLQY) of 16.36% at room temperature, a 2-fold increase compared to the PLQY of 8.15% measured for the precursor organic salt RBr. On the basis of our optical spectroscopy and computational work, the organic component is responsible for the observed blue emission of the hybrid material. In addition to the enhanced light emission efficiency, the novel hybrid indium bromide demonstrates significantly improved environmental stability. These findings may pave the way for the consideration of hybrid organic In(III) halides for light emission applications.
Field measurements have shown that cold-season methane (CH 4 ) and carbon dioxide (CO 2 ) emissions contribute a substantial portion to the annual net carbon emissions in permafrost regions. However, most earth system land models do not accurately reproduce cold-season CH 4 and CO 2 emissions, especially over the shoulder (i.e., thawing and freezing) seasons. Here we use the Energy Exascale Earth System Model (E3SM) land model version 1 (ELMv1-ECA) to tackle this challenge and fill the knowledge gap of how cold-season CH 4 and CO 2 emissions contribute to the annual totals at Alaska Arctic tundra sites. Specifically, we improved the ELMv1-ECA soil water phase-change scheme, environmental controls on microbial activity, and the methane module. Results demonstrate that both soil temperature and the duration of zero-curtain periods (i.e., the fall period when soil temperatures linger around 0°C) simulated by the updated ELMv1-ECA were greatly improved; e.g., the mean absolute error (MAE) in zero-curtain durations at 12 cm depth was reduced by 62 % on average. Furthermore, the MAEs of simulated cold-season carbon emissions at three tundra sites were improved by 72 % and 70 % on average for CH 4 and CO 2 , respectively. Overall, CH 4 emitted during the early cold season (September and October), which often includes most of the zero-curtain period in Arctic tundra, accounted for more than 50 % of the total emissions throughout the entire cold season (September to May) in the model, compared with around 49.4 % (43 %–58 %) in observations. From 1950 to 2017, both CO 2 emissions during the zero-curtain period and during the entire cold season showed increasing trends, for example, of 0.17 and 0.36 gC m -2 yr -1 at Atqasuk. This study highlights the importance of zero-curtain periods in facilitating cold-season CH 4 and CO 2 emissions from tundra ecosystems.
The Global Climate Action Partnership (GCAP; formerly the Low Emission Development Strategies Global Partnership) is a worldwide network that accelerates ambitious climate goals and advances implementation in Africa, Asia, and Latin America and the Caribbean (LAC). Our strategic approach emphasizes country-driven implementation actions to achieve resilient, just, and inclusive low-emission and net-zero economies. As an incubator for scalable knowledge and solutions, GCAP is leading the way to equitable, climate-resilient, low-emission development.
As the concentration of greenhouse gases (GHGs) in the atmosphere increases, the concerns about carbon emissions are growing. Several net-zero initiatives are taking place around the globe to achieve a balance between the GHGs put into the atmosphere and those taken out. While most efforts present a sectorized approach, this paper describes the importance of integrating information across different sectors for effective modeling of carbon emissions and holistic reduction opportunity analysis. Using the Idaho National Laboratory (INL) campus as a test case, this work provides a web-based tool for INL stakeholders to use when engaging in strategic planning to achieve carbon emissions reduction. This net-zero engineering support tool (NEST) uses historical data as foundational information for applying the modeling framework. Prediction of CO 2 emissions throughout project completion integrates various approaches and schedules aimed at energy conservation, fleet decarbonization, and other GHG reduction activities. Using NEST, stakeholders can visualize carbon emissions, electricity consumption, and costs for decision making when planning the pathway for reaching carbon net zero. The INL’s initiative to transition into an EV fleet was used to demonstrate the developed framework and the advantages of using NEST. It was shown that electrifying different fossil-fueled campus vehicles before 2030 with aggressive replacement schedules require high annual capital expenditure (CAPEX), which may not be available. The tool allows decision makers to test different replacement schedules and prioritize those that yield CAPEX below a certain threshold while meeting target milestones. While the demonstration focused on vehicle electrification, the developed framework lays the foundation for further quantitative analysis of other GHG reduction activities.
Highlights: • It is studied emission correlations between particle emission events in black holes. • Particles emitted have highly correlated moments before the BH stops radiating. • Rainbow Gravity allows maintaining the rest of it stored in its remnant. In this work, we study emission correlations in Rainbow Gravity (RG) black holes known to have black hole remnants. Non-thermal corrections are responsible for generating non-zero correlations between particle emission events during the black hole evaporation process. With this in mind, we calculate the temperatures considering back-reaction effects. Then, we obtain the correlations between emission events for a RG metric proposed by Magueijo and Smolin. We also discuss through a numerical analysis the emission correlations behavior in the last stages of evaporation of the black hole.
Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM (Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.
China has large, estimated potential for direct air carbon capture and storage (DACCS) but its deployment locations and impacts at the subnational scale remain unclear. This is largely because higher spatial resolution studies on carbon dioxide removal (CDR) in China have focused mainly on bioenergy with carbon capture and storage. This study uses a spatially detailed integrated energy-economy-climate model to evaluate DACCS for 31 provinces in China as the country pursues its goal of climate neutrality by 2060. We find that DACCS could expand China’s negative emissions capacity, particularly under sustainability-minded limits on bioenergy supply that are informed by bottom-up studies. But providing low-carbon electricity for multiple GtCO 2 yr -1 DACCS may require over 600 GW of additional wind and solar capacity nationwide and comprise up to 30% of electricity demand in China’s northern provinces. Investment requirements for DACCS range from 330 to 530 billion dollars by 2060 but could be repaid manyfold in the form of avoided mitigation costs, which DACCS deployment could reduce by up to $6 trillion over the same period. Enhanced efforts to lower residual CO 2 emissions that must be offset with CDR under a net-zero paradigm reduce but do not eliminate the use of DACCS for mitigation. For decision-makers and the energy-economy models guiding them, our results highlight the value of expanding beyond the current reliance on biomass for negative emissions in China.
Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.
Idaho National Laboratory (INL) announced at COP27 it would reach net zero greenhouse gas (GHG) emissions by 2031. As a Nuclear, Energy and Environment, and National Homeland Security laboratory, the predominant solution to closing the clean energy gap will include nuclear as a safe, clean, reliable and affordable electricity source with the additional benefit of producing heat and hydrogen to fuel INL’s large transportation fleet. INL’s collaboration first vs. competition is essential to the program’s success. The focused actions in INL’s Nuclear Roadmap include: Infrastructure, Licensing/Regulatory, Financial, Time to Market, Fuel Cycle and Public Confidence/Communications. The roadmap also includes nuclear technology innovations and creative partnerships with utility providers, regulators, businesses, community members, and Indigenous Peoples to accelerate deployment of advanced reactors. Through development of the Net-Zero Nuclear Roadmap, INL will offer a model to provide safe and secure energy for the nation and the world by: (1) establishing the necessary infrastructure on its 890-square mile site to support demonstration, (2) showing proven pathways through the licensing and regulation process, (3) partnering with utilities to ensure commercial application, and (4) collaborating with industry to site new technologies.
Expanding biofuel production is expected to accelerate the conversion of unmanaged marginal lands to meet biomass feedstock needs. Greenhouse gas production during conversion jeopardizes ensuing climate benefits, but most research to date has focused only on conversion to annual crops and only following tillage. Here we report the global warming impact of converting USDA Conservation Reserve Program (CRP) grasslands to three types of bioenergy crops using no-till (NT) versus conventional tillage (CT). In three CRP fields planted to continuous corn, switchgrass, or restored prairie we established replicated NT and CT plots. For the two years following an initial soybean year in all fields, we found that, on average, NT conversion reduced nitrous oxide (N2O) emissions by 50% and carbon dioxide (CO2) emissions by 20% compared to CT conversion. Differences were higher in year 1 than in year 2 in the continuous corn field, and in the two perennial systems the differences disappeared after year 1. In all fields net CO2 emissions (as measured by eddy covariance) were positive for the first two years following CT establishment, but following NT establishment net CO2 emissions were close to zero or negative, indicating net C sequestration. Overall, NT improved the global warming impact of biofuel crop establishment following CRP conversion by over 20-fold compared to CT (-6.01 Mg CO2e ha-1 yr-1 for NT vs. -0.25 Mg CO2e ha-1 yr-1 for CT, on average). We also found that IPCC estimates of N2O emissions (as measured by static chambers) greatly underestimated actual emissions for converted fields regardless of tillage. Policies should encourage adoption of NT for converting marginal grasslands to perennial bioenergy crops in order to reduce carbon debt and maximize climate benefits.
Expanding biofuel production is expected to accelerate the conversion of unmanaged marginal lands to meet biomass feedstock needs. Greenhouse gas production during conversion jeopardizes the ensuing climate benefits, but most research to date has focused only on conversion to annual crops and only following tillage. Here we report the global warming impact of converting USDA Conservation Reserve Program (CRP) grasslands to three types of bioenergy crops using no–till (NT) vs. conventional tillage (CT). We established replicated NT and CT plots in three CRP fields planted to continuous corn, switchgrass, or restored prairie. For the 2 yr following an initial soybean year in all fields, we found that, on average, NT conversion reduced nitrous oxide (N 2 O) emissions by 50% and CO 2 emissions by 20% compared with CT conversion. Differences were higher in Year 1 than in Year 2 in the continuous corn field, and in the two perennial systems the differences disappeared after Year 1. In all fields net CO 2 emissions (as measured by eddy covariance) were positive for the first 2 yr following CT establishment, but following NT establishment net CO 2 emissions were close to zero or negative, indicating net C sequestration. Overall, NT improved the global warming impact of biofuel crop establishment following CRP conversion by over 20–fold compared with CT (–6.01 Mg CO 2 e ha –1 yr –1 for NT vs. –0.25 Mg CO 2 e ha –1 yr –1 for CT, on average). We also found that Intergovernmental Panel on Climate Change estimates of N 2 O emissions (as measured by static chambers) greatly underestimated actual emissions for converted fields regardless of tillage. Policies should encourage adoption of NT for converting marginal grasslands to perennial bioenergy crops to reduce C debt and maximize climate benefits.
Real driving emission (RDE) test conducted in sub-zero temperature conditions has been acting as a severe emission regulation over the existing test methods for diesel engines. In order to cope with this tightened regulation, many studies have been conducted to interpret the factors causing the deteriorated diesel engine combustion in cold operation conditions. The deteriorated fuel injection performance has been regarded as one of the key contributing factors but the governing mechanisms are not thoroughly understood so far. This study aims to provide a comprehensive understanding of the effects of fuel temperature including sub-zero conditions on fuel injection performance by measuring the transient needle motion and injection velocity of a diesel injector using synchrotron X-ray imaging techniques. Here, the factors causing the deteriorated injector performance and their contributions are discussed thoroughly based on the results. The results showed that the injection duration was shortened as the fuel temperature decreased as a result of decreased needle opening speed and increased needle closing speed. The increase of fuel viscosity and bulk modulus was discussed as the main factors associated with these results. The total injection mass was reduced by lowering the fuel temperature not only by the shortened injection duration but also by the decreased injection velocity. These factors exerted near equivalent contribution to the reduced injection mass at low fuel temperatures.
Reducing carbon dioxide emissions is one of the critical challenges to mitigate global climate change, which is having detrimental impacts on society and the environment. Fossil fuel combustion in transportation, power generation, and industrial processes is the dominant contributor to carbon emissions. Over the past decades, sustainable solutions and strategies have been investigated and developed to enable decarbonization. Catalysis plays an essential role to address this global challenge by increasing energy efficiency, reducing carbon emissions, capturing carbon dioxide, and utilizing clean energy sources to displace fossil fuels. In this Review, the role of catalysis in reducing energy demand was discussed, enhancing process efficiency, displacing carbon-intensive feedstocks and products, and therefore, reducing carbon emissions. Here, recent advances in catalyst development were summarized, focusing on applications to enhance industrial processes efficiency and enable utilization of clean energy sources. Emerging approaches in catalysis were reviewed, including the manufacture of iron and steel, direct air capture of CO 2 , production of ethylene, ammonia, and sustainable aviation fuels, plastic recycling, and the synthesis of biobased plastics. The Review was concluded with suggested research directions to achieve a carbon net-zero world.
China’s progress in decarbonizing its transportation, particularly vehicle electrification, is notable. However, the economically effective pathways are underexplored. To find out how much cost is necessary for carbon neutrality for the light-duty vehicle (LDV) sector, this study examines twenty decarbonization pathways, combining the New Energy and Oil Consumption Credit model and the China-Fleet model. We find that the 2060 zero-greenhouse gas (GHG) emission goal for LDVs is achievable via electrification if the battery pack cost is under CNY483/kWh by 2050. However, an extra of CNY8.86 trillion internal subsidies is needed under pessimistic battery cost scenarios (CNY759/kWh in 2050) to eliminate 246 million tonnes of CO 2 -eq by 2050 ensuring over 80% market penetration of battery electric vehicles (BEVs) in 2050. Moreover, the promotion of fuel cell electric vehicles is synergy with BEVs to mitigate the carbon abatement difficulties, decreasing up to 34% of the maximum marginal abatement internal investment.
M Gidden conducted this work prior to joining PNNL and no DOE OFFICE OF SCIENCE, OTHER DOE, OTHER FEDERAL, OR PNNL OVERHEAD FUNDING is being used. Stabilizing and then drawing down global temperature requires achieving net-negative CO2 emissions globally. Carbon removal is needed to offset “hard-to-abate” sectors that remain sources of emissions at net-zero and beyond. We argue the use of scarce carbon removal resources should be guided by the principles enshrined in the Paris Agreement.