Fuel Management Research Articles

Mapping Homogeneous Response Areas for Forest Fuel Management Using Geospatial Data, K-Means, and Random Forest Classification

Accurate description of forest fuels is necessary for developing appropriate fire management strategies aimed at reducing fire risk. Although field surveys provide accurate measurements of forest fuel load estimations, they are time consuming, expensive, and may fail to capture the inherent spatial heterogeneity of forest fuels. Previous efforts were carried out to solve this issue by estimating homogeneous response areas (HRAs), representing a promising alternative. However, previous methods suffer from a high degree of subjectivity and are difficult to validate. This paper presents a method, which allows eliminating subjectivity in estimating HRAs spatial distribution, using artificial intelligence machine learning techniques. The proposed method was developed in the natural protected area of “Sierra de Quila,” Jalisco, and was replicated in “Sierra de Álvarez,” San Luis Potosí and “Selva El Ocote,” Chiapas, Mexico, to prove its robustness. Input data encompassed a set of environmental variables including altitude, average annual precipitation, enhanced vegetation index, and forest canopy height. Four, three, and five HRAs with overall accuracy of 97.78%, 98.06%, and 98.92% were identified at “Sierra de Quila,” “Sierra de Álvarez,” and “Selva El Ocote,” respectively. Altitude and average annual precipitation were identified as the most explanatory variables in all locations, achieving a mean decrease in impurity values greater than 52.51% for altitude and up to 36.02% for average annual precipitation. HRAs showed statistically significant differences in all study sites according to the Kruskal–Wallis test (p-value < 0.05). Differences among groups were also significant based on the Wilcoxon–Mann–Whitney (p-value < 0.05) for all variables but EVI in “Selva El Ocote.” These results show the potential of our approach to objectively identify distinct homogeneous areas in terms of their fuel properties. This allows the adequate management of fire and forest fuels in decision-making processes.

Comparing risk-based fuel treatment prioritization with alternative strategies for enhancing protection and resource management objectives

BackgroundAdvances in fire modeling help quantify and map various components and characterizations of wildfire risk and furthermore help evaluate the ability of fuel treatments to mitigate risk. However, a need remains for guidance in designing landscape-scale fuel treatments with protection objectives, resource management objectives, and wildfire response in mind. It is also important to consider how human factors related to risk tolerance may affect opportunities to manage fire. We build on these themes to illustrate an approach for examining whether, and how, fuel management can simultaneously minimize housing exposure while maximizing area suitable for expansion of beneficial wildfire. We generate multiple hypothetical post-treatment conditions according to distinct treatment prioritization schemes (Housing Protection, Federal Transmission, Random) and variable treatment extents and compare performance across strategies for a 8.5 million ha case study landscape in north-central New Mexico, USA.ResultsIn general, we find that treating near housing units can provide the greatest level of protection relative to treating more remote wildlands to reduce transmission potential. Treating on federal lands to reduce federal transmission was highly effective at reducing exposure from federal fires and at expanding opportunities for beneficial fire but contributed comparatively little to reducing housing exposure from all fires. We find that treatment extents as low as 2.5–5% can yield significant benefits with spatially optimized strategies, whereas the random strategy did not perform comparably until reaching a much larger treatment extent. Increasing risk tolerance for housing exposure expanded the area suitable for managed fire, while decreasing risk tolerance for beneficial fire opportunity and flame length probability shrunk the area suitable for managed fire.ConclusionsThis work provides a contribution in terms of explicitly framing risk analysis and fuel treatment design around federal land and resource management objectives and adds to the knowledge base for designing effective landscape fuel treatment strategies that can protect communities and expand beneficial wildfire on a fire-prone landscape. Successful integration of these themes requires embracing all pillars of the National Cohesive Wildland Fire Management Strategy, including coordinated management of fuels on various ownerships, home ignition zone mitigation, and cross-boundary fire response planning that can guide fire operations in reducing transmission and expand response options.

Strategic Partnerships to Leverage Small Wins for Fine Fuels Management

Rangeland wildfire is a wicked problem that cuts across a mosaic of public and private rangelands in the western United States and countless countries worldwide. Fine fuel accumulation in these ecosystems contributes to large-scale wildfires and undermines plant communities’ resistance to invasive annual grasses and resilience to disturbances such as fire. Yet it can be difficult to implement fuels management practices, such as grazing, in socially and politically complex contexts such as federally managed rangelands in the United States. In this Research-Partnership Highlight, we argue that private-public partners in such settings must be strategic in their selection of tasks to generate “small wins” in order to build the trust, competency, and legitimacy needed to advance an approach for landscape-scale fine fuels management. We highlight a fine fuels reduction partnership consisting of public and private entities in southeastern Oregon that established a research and education project and applied dormant season grazing on three pastures within the Vale District Bureau of Land Management. We describe the impetus for the partnership, antecedents, strategic tactics, and ongoing learning and reflection used to revise processes. In this example, implementing dormant season grazing as a research and education project allowed the partners to assess the efficaciousness of the treatment, as well as the operational logistics and administrative competencies necessary to apply the treatment to manage fine fuels at broader scales. Because dormant season grazing may, in some instances, conflict with established practices and norms, small-scale projects such as this allow partners to refine understandings of the social and administrative conditions that make implementation possible. Generating small wins through projects such as this is a critical precursor for partnerships seeking to take on larger, more complex endeavors that involve increasing ecological, economic, and social uncertainty.

Evaluation of dose rate and uncertainty of fuel debris in a canister for safe handling and management of damaged nuclear fuels

The Fukushima accident severely damaged fuels in three nuclear reactors. Even though part of information on their condition has been identified by investigations with advanced methods, the condition of the fuel is still uncertain. We developed a model to simulate the uncertain condition of damaged fuel debris and evaluated its nuclear radiation. Our research is focused on the uncertain geometry of fuel debris in a canister, and the uncertain condition is modeled by random sampling on size and distribution of the fuel debris in a canister. A Monte Carlo based module of SCALE code is used for the calculation of flux and dose rate, and a Python code is made for the random sampling and the evaluation of uncertainty. The uncertainty of dose rate by the uncertain geometry of fuel debris in a canister is evaluated as the coefficient of variation and the percent relative range of the dose rate.

Woodfuel Consumption in Refugee Hosting Areas and Its Impact on the Surrounding Forests—The Case of Uganda

The high dependency of households on woodfuels in Uganda is a renowned driver of forest degradation. Refugee settlements might aggravate the pressure on the environment caused by woodfuel consumption in the absence of impact assessments and measures to improve environmental management and build sustainable livelihoods. In collaboration with the Government of Uganda, UNHCR, and the World Bank, FAO conducted assessments on woodfuel consumption at the household level in displacement settings in Uganda, as well as its impact on the surrounding forests, through field forest inventories, household surveys, and geospatial analysis. The results of these assessments highlight the impact of woodfuel consumption and other drivers on forest degradation, and provide guidance for the development of comprehensive interventions on landscape management and improvement of household cooking fuels and technologies, targeting both refugee and host communities.

Modeling Herbaceous Biomass for Grazing and Fire Risk Management

Both grazing and fine fuels management are dependent on the temporal and spatial distribution of herbaceous biomass production. Rangeland and wildland fire managers can both benefit from knowing when and where there is excessive herbaceous biomass buildup. In this study, we compared modeled herbaceous biomass outputs from the Phytomass Growth Simulator (Phygrow) to observe and predict herbaceous production on desert, juniper, and pine sites on the Coconino National Forest in Arizona. Models were validated with: (a) 2 years of quarterly data, and (b) fire season-only data. The Phygrow model showed strong agreement between observed and predicted values year-round on the desert (r2 = 0.73) and pine sites (r2 = 0.69), and a lower, but positive agreement in the juniper sites (r2 = 0.54). Fire season predictions were strong for all ecosystem types (desert r2 = 0.89; juniper r2 = 0.62; pine r2 = 0.94), suggesting that the Phygrow model is well suited to provide valuable decision support information with which to address both rangeland and fire management objectives.

Simulating burn severity maps at 30 meters in two forested regions in California

Climate change is altering wildfire and vegetation regimes in California’s forested ecosystems. Present day fires are seeing an increase in high burn severity area and high severity patch size. The ability to predict future burn severity patterns could better support policy and land management decisions. Here we demonstrate a methodology to first, statistically estimate individual burn severity classes at 30 meters and second, cluster and smooth high severity patches onto a known landscape. Our goal here was not to exactly replicate observed burn severity maps, but rather to utilize observed maps as one realization of a random process dependent on climate, topography, fire weather, and fuels, to inform creation of additional realizations through our simulation technique. We developed two sets of empirical models with two different vegetation datasets to test if coarse vegetation could accurately model for burn severity. While visual acuity can be used to assess the performance of our simulation process, we also employ the Ripley’s K function to compare spatial point processes at different scales to test if the simulation is capturing an appropriate amount of clustering. We utilize FRAGSTATS to obtain high severity patch metrics to test the contiguity of our high severity simulation. Ripley’s K function helped identify the number of clustering iterations and FRAGSTATS showed how different focal window sizes affected our ability to cluster high severity patches. Improving our ability to simulate burn severity may help advance our understanding of the potential influence of land and fuels management on ecosystem-level response variables that are important for decision-makers. Simulated burn severity maps could support managing habitat and estimating risks of habitat loss, protecting infrastructure and homes, improving future wildfire emissions projections, and better mapping and planning for fuels treatment scenarios.

Significant legal developments concerning “independent” regulatory agencies in the United States and what it could mean for the Nuclear Regulatory Commission

Multiple sources of international nuclear law, including binding instruments such as the Convention on Nuclear Safety (CNS)1 and the Joint Convention on the Safety of Spent Fuel Management and on the Safety of Radioactive Waste Management (Joint Convention),2 stress the importance of the independence of the regulator, as well as the effective separation of that regulatory body from others tasked with the promotion or utilisation of nuclear energy. Since its creation in 1974, the United States (US) Nuclear Regulatory Commission (NRC) has been characterised as an “independent agency” within the US government. One of the hallmarks of this independence is that, by law, members of the Commission cannot be removed at will by the President over policy disagreements. However, recent decisions by the US Supreme Court have declared that restrictions on the President’s ability to remove the heads of certain agencies are incompatible with the nation’s constitutional structure and are therefore invalid and unenforceable. As of this writing, these decisions have been limited to independent regulatory agencies headed by a single administrator, not multi-member boards or commissions such as the NRC. However, the Court’s legal reasoning sweeps broadly, and if the holding of these decisions were to be applied to multi-member regulatory bodies (as legal scholars predict), it would shake the organisational bedrock upon which the Commission has rested since its creation. It may also risk transforming the Agency’s public image into that of a political or promotional actor, whose activities are closely overseen by the President who is also responsible for setting energy-related national priorities and goals.

Using Dynamic, Fuels-Based Fire Probability Maps to Reduce Large Wildfires in the Great Basin

Spatial and temporal dynamics of rangeland fuels is a primary factor driving large wildfires. Yet detailed information capturing variation in fine fuels has largely been missing from rangeland fire planning and fuels management. New fuels-based maps of Great Basin rangeland fire probability help bridge this gap by coupling dynamic vegetation cover and production data from the Rangeland Analysis Platform with weather and climate data to provide annual forecasts of the relative probability of large wildfire. In this paper, we review these new fuels-based maps and discuss implications for prefire planning, preparedness, and strategic fuels management. Examining patterns of fire probability through time reveals high spatial and temporal variation in risk of large wildfires across the Great Basin. Certain areas are chronically impacted with high fire probability most years, while others have more sporadic or low probability of large fire annually. Maps confirm previous research that the recent increase in large fire risk in the region is highly associated with invasive annual grasses, but total aboveground herbaceous production (including perennials) continues to be a primary predictor of fire probability. Fuels-based fire probability maps can be used alongside existing data sources and prioritization frameworks by fire and fuels managers to inform questions of 1) what kind of fire year might this be, 2) where large fires are most likely to occur given an ignition, and 3) where resources should be focused. We provide examples of how maps can be used to improve prefire preparedness and planning to enhance suppression, facilitate annual targeting of fine fuels reductions, and support land use planning for implementation of landscape-scale fuels management. Proactively incorporating this new information into rangeland fire and fuels management can help address altered fire regimes threatening the region's wildlife and working lands.

Trends in wildfire-related bills in California, 2001–2020

California has recently experienced severe and destructive wildfire seasons, prompting new policy proposals from the California State Legislature. Here, we examine proposed state wildfire-related legislation from the ten two-year legislative sessions between 2001–2002 and 2019–2020 to track trends and factors influencing wildfire-related legislative priorities. We first use Latent Dirichlet allocation topic modeling to identify 29 wildfire topics from the text of 294 bills. We next determine the degree to which legislators’ backgrounds, legislative procedures, and bill intent are correlated with bill topic. We find individual correlations but no overarching correlations between legislators’ personal and political backgrounds (e.g. political party, legislative experience, home district, bipartisanship), legislative procedures (i.e. committee review, state mandates, urgency measures), and bill intent (i.e. wildfire stage, commemorative bill, focus on specific geographic area or vulnerable group) with bill topics. However, we find that successful bills are correlated with review by Appropriations Committees, review by multiple committees, and a focus on specific geographic location. In the 2019–2020 legislative session, bill passage was correlated with Democratic sponsorship. Legislators tend to propose bills related to the dominant challenge or crisis of that legislative session (such as loss of homeowners’ insurance coverage or need for more fuels management), indicating the reactiveness of the legislature to statewide issues with new proposed legislation. These findings provide important insights into how legislative priorities change over time and the policy enablers and barriers for urgent climate change adaptation. Our results indicate a potentially fundamental policy shift in response to recent wildfires in California.

Modelling of the LTDE-SD radionuclide diffusion experiment in crystalline rock at the Äspö Hard Rock Laboratory (Sweden)

This study shows a comparison and analysis of results from a modelling exercise concerning a field experiment involving the transport and retention of different radionuclide tracers in crystalline rock. This exercise was performed within the Swedish Nuclear Fuel and Waste Management Company (SKB) Task Force on Modelling of Groundwater Flow and Transport of Solutes (Task Force GWFTS).Task 9B of the Task Force GWFTS was the second subtask within Task 9 and focused on the modelling of experimental results from the Long Term Sorption Diffusion Experiment in situ tracer test. The test had been performed at a depth of about 410m in the Äspö Hard Rock Laboratory. Synthetic groundwater containing a cocktail of radionuclide tracers was circulated for 198 days on the natural surface of a fracture and in a narrow slim hole drilled in unaltered rock matrix. Overcoring of the rock after the end of the test allowed for the measurement of tracer distribution profiles in the rock from the fracture surface (A cores) and also from the slim hole (D cores). The measured tracer activities in the rock samples showed long profiles (several cm) for non- or weakly-sorbing tracers (Cl-36, Na-22), but also for many of the more strongly-sorbing radionuclides. The understanding of this unexpected feature was one of the main motivations for this modelling exercise. However, re-evaluation and revision of the data during the course of Task 9B provided evidence that the anomalous long tails at low activities for strongly sorbing tracers were artefacts due to cross-contamination during rock sample preparation. A few data points remained for Cs-137, Ba-133, Ni-63 and Cd-109, but most measurements at long distances from the tracer source (>10mm) were now below the reported detection limits.Ten different modelling teams provided results for this exercise, using different concepts and codes. The tracers that were finally considered were Na-22, Cl-36, Co-57, Ni-63, Ba-133, Cs-137, Cd-109, Ra-226 and Np-237. Three main types of models were used: i) analytical solutions to the transport-retention equations, ii) continuum-porous-medium numerical models, and iii) microstructure-based models accounting for small-scale heterogeneity (i.e. mineral grains, porosities and/or microfracture distributions) and potential centimetre-scale fractures. The modelling by the different teams led to some important conclusions, concerning for instance the presence of a disturbed zone (a few mm in thickness) next to the fracture surface and to the wall of the slim hole and the role of micro-fractures and cm-scale fractures in the transport of weakly sorbing tracers. These conclusions could be reached after the re-evaluation and revision of the experimental data (tracer profiles in the rock) and the analysis of the different sets of model results provided by the different teams.

LA-ICP-MS analysis of trace and rare-earth element distribution in calcite fracture fillings from Forsmark, Simpevarp and Laxemar (Sweden)

Concentrations and spatial distribution of trace elements in secondary minerals provide valuable information about mobility controlling processes in natural fractures. Important examples include rare-earth element contents that act as analogues for the retention of trivalent actinides such as Am/Cm or Pu(III). The secondary phases (carbonates) investigated in this study originate from exploration drilling bore cores of the Swedish Nuclear Fuel and Waste Management Company SKB (Forsmark, Simpevarp and Laxemar, Sweden).Here, high-resolution element analysis (Micro-X-ray Fluorescence-Spectrometry (µXRF) and Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS)) is applied to scan for Na and the trace elements Mn, Fe, Sr, Pb, Th and U as well as the rare-earth elements Y, La, Ce and Yb associated with carbonate fracture fillings. High resolution element maps highlight growth zones and microstructures within the samples, which are not detected by the usual point and line measurements. Evidence of phase-dependent partitioning is observed.The partition coefficients, D, determined from formation water and carbonate data were compared to experimentally generated coefficients and values derived from a 17-year precipitation experiment carried out at the Äspö Hard Rock Laboratory (HRL).Distribution coefficients of the light rare-earth elements La and Ce have been found to be relatively high in the studied samples, whereas the coefficients of distribution of Sr and U are remarkably low.Overall, the results of this work show that the secondary calcite formed in deep granitic fractures coprecipitated periodically with significant amounts of radionuclide analogues (i.e., rare-earth elements).

On the Feasibility and Efficiency of Self-Powered Green Intelligent Highways

(1) Background: The present development of transport networks focusses on the better management of fuels and energy and the preservation of the environment. To fulfill these desiderates, some countries have already reconsidered the deployment plans of new highways. This research studies the feasibility of less polluting, quasi-self-powered, intelligent highway infrastructure functional blocks accommodating functions for the future introduction of smart wireless sensor grids and connected autonomous vehicles. Subject of investigation are the possibilities of energy harvesting, and the intelligent management of resources. (2) Methods: the research investigates the main technologies for energy harvesting and recommends an optimal solution. It also proposes a framework for the intelligent, AI-based management of energy and the use of an optimized backup solution relying on 5G beamforming for energy supply of the local wireless sensing network devices; (3) Results: recommendations are made for the best energy harvesting solution, an architecture of the energy management system, an algorithm for energy management and backup solution based on 5G beamforming; (4) Conclusions: the research emphasizes the advantages and drawbacks for different solutions regarding energy harvesting in an intelligent green highway scenario with a focus on the infrastructure developed to accommodate future connected and autonomous vehicles. The term “intelligent highway” must be understood in the automotive industry to describe a network of roads where cars communicate with the infrastructure and among themselves for the purpose of avoiding congestion and performing the seamless operation of services, and a space where cars and infrastructure cooperatively process information for obtaining better road safety, less pollution, and efficient energy management. With the recent recession of conventional fuel availability and the increase in prices, a solution to improving autonomy of both cars and infrastructure might be welcomed.

Prairie wetlands as sources or sinks of nitrous oxide: Effects of land use and hydrology

National and global greenhouse gas (GHG) budgets are continually being refined as data become available. Primary sources of the potent GHG nitrous oxide (N2O) include agricultural soil management and burning of fossil fuels, but comprehensive N2O budgets also incorporate less prominent factors such as wetlands. Freshwater wetland GHG flux estimates, however, have high uncertainty, and wetlands have been identified as both sources and sinks. Here, we analyzed a regional database of >26,000 N2O chamber flux measurements sampled across >150 wetlands from the Prairie Pothole Region (PPR) in the Great Plains of North America. Our goal was to identify important land use and hydrologic drivers of N2O flux to help reduce uncertainty in N2O models, and to incorporate these drivers into an upscaled estimate of wetland N2O emissions from the U.S. portion of the PPR. Within individual wetlands, exposed soils with no standing water, such as along wetland edges, were hotspots that accounted for greater than 90% of wetland N2O emissions. In contrast wet (i.e., ponded) areas had minimal or negative N2O flux. N2O flux from wetlands nested within croplands (16.3–17.3 μg N2O m−2 hr−1) was, in some instances, nearly double that from wetlands within grasslands (9.2–14.4 μg N2O m−2 h−1). We estimated that seasonal N2O flux from PPR wetlands equated to roughly 0.2% (1.04 Tg CO2 equivalents) of the U.S. N2O budget (c. 2019). Overall, even though PPR wetlands are a small net source of N2O to the atmosphere, their emissions are negligible relative to agricultural soil management. Policy and management to restore wetland hydrology and surrounding uplands from cropland to grasslands can reduce landscape N2O fluxes. Future activities focused on wetland N2O flux would benefit from inclusion of adjacent land use and hydrologic factors, as well as from incorporation of temporally dynamic ponded wetland areas.

Legal Triggers for Digitalization of Radioactive Waste and Spent Fuel Management within the European Union

The article examines the impact of digitalization on radioactive waste and spent fuel management in the EU. The purpose of the research is the legal mechanisms that launch new digital technologies to improve radioactive waste accounting and control over its management. To set the goals of the research, such methods of scientific knowledge as logical, system-structural and comparative legal analysis were used. New EU legal documents (EC Digital Strategy 2018 and Shaping Digital Future of Europe 2020) have triggered process digitalization in the EU. According to analysis the EU legal acts, the authors came to the conclusion that the EU Commission principles of digitalization are security, confidentiality, openness, transparency and simultaneity. EURATOM successfully applies digital 3D technology and simulation for dismantling planning of nuclear facilities. In turn, the European Commission uses digitalization applies to data collection and radioactive waste and spent fuel management in the EU Member States. In conclusion, it is determined that the EU has not yet adopted artificial intelligence act for radioactive waste and spent fuel management. However, the EU already has some experience. In the future the EU can adopt a new legal act that will summarize all the practice of the EC, EURATOM and EU Member States to regulate of digitalization in the EU radioactive waste management.

Comparing Remote Sensing and Field-Based Approaches to Estimate Ladder Fuels and Predict Wildfire Burn Severity

While fire is an important ecological process, wildfire size and severity have increased as a result of climate change, historical fire suppression, and lack of adequate fuels management. Ladder fuels, which bridge the gap between the surface and canopy leading to more severe canopy fires, can inform management to reduce wildfire risk. Here, we compared remote sensing and field-based approaches to estimate ladder fuel density. We also determined if densities from different approaches could predict wildfire burn severity (Landsat-based Relativized delta Normalized Burn Ratio; RdNBR). Ladder fuel densities at 1-m strata and 4-m bins (1–4 m and 1–8 m) were collected remotely using a terrestrial laser scanner (TLS), a handheld-mobile laser scanner (HMLS), an unoccupied aerial system (UAS) with a multispectral camera and Structure from Motion (SfM) processing (UAS-SfM), and an airborne laser scanner (ALS) in 35 plots in oak woodlands in Sonoma County, California, United States prior to natural wildfires. Ladder fuels were also measured in the same plots using a photo banner. Linear relationships among ladder fuel densities estimated at broad strata (1–4 m, 1–8 m) were evaluated using Pearson’s correlation (r). From 1 to 4 m, most densities were significantly correlated across approaches. From 1 to 8 m, TLS densities were significantly correlated with HMLS, UAS-SfM and ALS densities and UAS-SfM and HMLS densities were moderately correlated with ALS densities. Including field-measured plot-level canopy base height (CBH) improved most correlations at medium and high CBH, especially those including UAS-SfM data. The most significant generalized linear model to predict RdNBR included interactions between CBH and ladder fuel densities at specific 1-m stratum collected using TLS, ALS, and HMLS approaches (R2 = 0.67, 0.66, and 0.44, respectively). Results imply that remote sensing approaches for ladder fuel density can be used interchangeably in oak woodlands, except UAS-SfM combined with the photo banner. Additionally, TLS, HMLS and ALS approaches can be used with CBH from 1 to 8 m to predict RdNBR. Future work should investigate how ladder fuel densities using our techniques can be validated with destructive sampling and incorporated into predictive models of wildfire severity and fire behavior at varying spatial scales.

Advanced Fuel Property Data Platform: Overview and Potential Applications

This report outlines the establishment of distributed databases for management and integration of current and future aviation fuels. Aviation fuel property and performance data has been gathered for many years in public and company specific fuel surveys. These surveys are suitable for use as overall quality control information and for monitoring changes and trends in the fuels in used for flight. In recent years, significant data has been generated for alternative fuels as part of the due diligence of their approval for use through ASTM D4054, including those outside of the specification. Recently, this data, along with fundamental chemistry data has led to the creation of the Fast Track route for fuels approval when the fuel is constrained to a necessarily narrowly defined composition. The data behind these developments are often stored in a disparate, unindexed way, resulting in their underutilisation for a range of research, engineering design, specification, and in service quality control applications. To make the best use of this data, we present a scalable, Json based format for the storing of fuels data. This concept has been proposed by the Horizon 2020 Jet Fuel SCREENing and Optimization (JETSCREEN) project in conjunction with the Center of Excellence for Alternative Jet Fuels and Environment (ASCENT) programme. We have worked collaboratively to develop a joint database which currently contains data from around 30,000 conventional and 400 alternative fuels/fuel blends from a range of European and United States of America (U.S.) lead research programmes and data sources. This database can be used for a variety of purposes, both in conjunction with, or in isolation of commercially sensitive data with a greater degree of restriction. We present a number of test cases for how we see this model for data storage could be used for the benefit of all. We invite further suggestions as to how this approach could be used and welcome opportunities to work with the wider fuels community to develop this idea further.

On development of in-core fuel system for PWR reactors: Part I generation of macroscopic cross sections using SCALE 6.0 for use in nodal calculation

This work presents the description of the first part of a methodology applied to perform In-Core Fuel Management (ICFM) in Pressurized Water Reactor (PWR). The ICFM of a PWR reactor consists on defining the best charging or recharging pattern of fuel assemblies inside a reactor for an operational cycle. This means, finding a suitable arrangement of fuel assemblies that optimizes the performance of the reactor, which complies with all safety criteria. Genetic algorithms (GAs) are used to select the arrangements that interact with the reactor physics simulation code, holding the neutron characteristics of each fuel assembly. Therefore, a reliable and fast code was developed accordingly. The consolidated technique of coarse mesh node code that numerically solves the multigroup diffusion equation for two groups of energy, fast and thermal neutrons, in two dimensions was selected. In this type of code, it is essential that each fuel assembly is homogenized and characterized by its macroscopic cross sections, for each reactor’s burnup condition. The cross sections are generated with the support of SCALE 6.0, computational platform developed by the Reactor and Nuclear Systems Division (RNSD), from the Oak Ridge National Laboratory (ORNL). The completeness of the qualification and validation of the results obtained from the homogenization of the fuel assembly by the SCALE was performed comparing the results with actual data of a benchmark reactor. The fully documented Almaraz Nuclear Power Plant provided by the International Atomic Energy Agency (IAEA)-TECDOC-815, has been used as benchmark with successful results.

Liaw-UNIFAC flash point model for alcohols-kerosene/diesel fuel blends using average fuel structure

Alcohol has already been widely used as an alternative fuel to blend with petroleum-based fuels. Accurate knowledge of flash points and their reliable prediction methods is essential in hazard identification, fire hazard reduction, process inherently safer design, and the risk management of alcohol-based fuels. This work presents a model to predict the flash point for alcohol + petroleum-based fuel blends based on the Liaw model incorporated with the original UNIFAC model. The flash point prediction model was modified by two steps: 1. applying a single vapor-temperature relationship for the petroleum-based fuel; 2. obtaining the activity coefficients by UNIFAC model using an average fuel structure for the petroleum-based fuel. The proposed model was verified experimentally for five fuel blends of alcohol + kerosene (alcohol being n-butanol, n-hexanol, and n-octanol) and alcohol + diesel (alcohol being n-butanol and n-hexanol). The flash point prediction procedure for alcohol + petroleum-based fuel blends was reduced to that of a binary mixture. The deviations between the predicted values and experimental data were mostly within 2 °C for the five fuel blends.

Population decline in California spotted owls near their southern range boundary

AbstractSpecies worldwide have begun to shift their range boundaries in response to climate change and other anthropogenic causes, with population declines at the trailing edge of a species' range often foreshadowing future changes in core parts of the range. Therefore, we analyzed a 30‐year (1991–2019) data set for the California spotted owl (Strix occidentalis occidentalis) near its southern range boundary in southern California, USA, that included the largest regional population (San Bernardino Mountains) to estimate trends in territory occupancy and reproduction. We then assessed how these demographic rates were affected by habitat, wildfire, fuel treatments, and climate. Mean occupancy declined from 0.82 to 0.39 during our study, whereas reproductive output showed no temporal trends ( young/occupied territory). Territory extinction (extirpation) rates were relatively low in territories with more large trees (≥50 cm dbh), and colonization increased strongly with large tree density for low‐elevation territories within the shrub‐woodland ecotype but not for higher‐elevation territories within mixed‐conifer forest. High‐severity wildfire had an adverse effect on occupancy: territory extinction rates steadily increased with the amount of high‐severity fire within an owl territory during the previous 10 years, while colonization declined to nearly zero when ≥40% of a territory burned at high‐severity during the previous 10 years. The effects of high‐severity fire were unlikely to be confounded with post‐fire fuel treatments, which primarily consisted of the removal, burning, or scattering of brush and small trees and snags (<40.6 cm dbh) and affected much smaller areas than high‐severity fire. Of the 40 territories that received fuel treatments within 10 years of a fire, only 3 of them had post‐fire fuel treatments that affected >5% of the territory, whereas average area burned at high severity for all 40 territories was 17%. Fuel treatments intended to modify fire behavior and reduce the likelihood of large, high‐severity fires led to increases in territory extinction and colonization such that their net effect on occupancy was minimal. Our simulations of occupancy dynamics indicated that high‐severity fire accounted for 9.6% of the observed decline in occupancy, whereas fuel treatments effectively accounted for none of the decline. Spotted owl reproductive output was lower at territories where fuel treatments occurred, but low‐ to moderate‐severity fire resulted in much larger, population‐level reductions in reproductive output (141 fewer young) from 2006–2019 than treatments (19 fewer young). Thus, the benefits of fuel treatments that reduce fire occurrence and severity appear to outweigh potential short‐term costs to spotted owls and their habitat. Because high‐severity fire only explained a modest amount of the long‐term occupancy decline and much of the decline occurred in the 1990s before large fires occurred, additional factors are likely adversely affecting the owl population and merit further study. Nevertheless, the large observed population decline, limited evidence of owl dispersal among mountain ranges in the southern California metapopulation, and negative effects of increasingly large and severe fire suggest that California spotted owls at their southern range boundary are vulnerable to extirpation. In an era of climate change, owls in the core part of the range will likely become increasingly susceptible to warmer temperatures and increased severe fire activity in the future. Thus, the restoration of historical, low‐severity fire regimes through fuels management while maintaining large trees is important to improving owl persistence.