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At least 1,531 records · Page 85

San Joaquin Valley Health & Air Quality II: Assessing Urban Heat Island Distribution and its Intersections with Air Quality to Understand Converging Vulnerabilities

The city of Stockton, California, located within the San Joaquin Valley (SJV), is a major hub for agricultural production and has endured the continuous threat to community health from nitrogen dioxide (NO 2 ) and increasing temperatures. The convergence of these issues occurs within historically segregated communities that are disproportionately facing health risks related to heat and air quality. Little Manila Rising (LMR), a social and environmental justice (EJ) advocacy non-profit, partnered with NASA DEVELOP for a second term project to evaluate county wide urban heat islands, sociodemographic vulnerability, landcover classification, and the convergence of these variables. We utilized Landsat 8 Thermal Infrared Sensor (TIRS) and Operational Land Imager (OLI) data to produce a land surface temperature (LST) and Normalized Difference Vegetation Index map. They added Centers for Disease Control (CDC) socioeconomic data from 2020 to identify which communities in Stockton were more susceptible to these environmental factors. Additionally, we used NAIP imagery to create a landcover map differentiating developed infrastructure from tree canopy cover. We discovered that south Stockton, where LMR resides, had the worst convergence of heat, air pollution, low canopy coverage and sociodemographic vulnerability compared to northern and rural parts of the city. This was further substantiated by statistical analysis showing a strong positive relationship between areas of high LST and low vegetation. The results provided LMR with compelling evidence to use in their EJ advocacy, and in their efforts to inform state officials of the discriminatory issues they face.

Urban Heat Islands↗

High Efficacy Validation of Hydride Mega Tanks at ARIES Lab (HEVHY METAL)

The High Efficacy Validation of Hydride Mega Tanks at ARIES Lab (HEVHY METAL) project will advance materials-based hydrogen storage technologies by large-scale demonstration and identification of deployment pathways. This includes demonstrating how two metal hydride HY2MEGA subsystems are installed with megawatt-scale green hydrogen infrastructure; validating its performance via rates, capacities, and efficiencies; and investigating supply and demand side techno-economics.

ARIES↗

How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits

In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits and proof-of-principle error-correction on a single logical qubit. Nevertheless, despite significant progress and excitement, the path toward a full-stack scalable technology is largely unknown. There are significant outstanding quantum hardware, fabrication, software architecture, and algorithmic challenges that are either unresolved or overlooked. These issues could seriously undermine the arrival of utility-scale quantum computers for the foreseeable future. Here, we provide a comprehensive review of these scaling challenges. We show how the road to scaling could be paved by adopting existing semiconductor technology to build much higher-quality qubits, employing system engineering approaches, and performing distributed quantum computation within heterogeneous high-performance computing infrastructures. These opportunities for research and development could unlock certain promising applications, in particular, efficient quantum simulation/learning of quantum data generated by natural or engineered quantum systems. To estimate the true cost of such promises, we provide a detailed resource and sensitivity analysis for classically hard quantum chemistry calculations on surface-code error-corrected quantum computers given current, target, and desired hardware specifications based on superconducting qubits, accounting for a realistic distribution of errors. Furthermore, we argue that, to tackle industry-scale classical optimization and machine learning problems in a cost-effective manner, heterogeneous quantum-probabilistic computing with custom-designed accelerators should be considered as a complementary path toward scalability.

Mohseni, Masoud↗

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

The engineering development of the new Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these spacecraft systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex system engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in specialized Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model based algorithms and their development lifecycle from inception through Flight Software certification are an important focus of this development effort to further insure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. NASA formed a dedicated M&FM team for addressing fault management early in the development lifecycle for the SLS initiative. As part of the development of the M&FM capabilities, this team has developed a dedicated testbed that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. Additionally, the team has developed processes for implementing and validating these algorithms for concept validation and risk reduction for the SLS program. The flexibility of the Vehicle Management End-to-end Testbed (VMET) enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS. The intent of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software development infrastructure and its related testing entities. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test cases into flight software compounded with potential human errors throughout the development lifecycle. Risk reduction is addressed by the M&FM analysis group working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses that can be tested in VMET to ensure that failures can be detected, and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes.

Trevino, Luis↗

Evaluating hydrogen permeation through medium-density and high-density polyethylene pipes to enable a hydrogen-compatible infrastructure

As the United States and the global community pursue energy abundance and resilience, hydrogen is becoming a critical energy carrier. The future of hydrogen transport depends on one thing: verifying that today’s pipelines are hydrogen ready. This study investigates the permeation behavior of medium-density polyethylene (MDPE) and high-density polyethylene (HDPE) pipelines under pure hydrogen gas environment at various pressures and temperatures. Using thermal desorption analysis (TDA) and direct pipe permeability measurements, hydrogen loss rates are quantified, revealing minimal permeation losses (< 10.5 g/km/day) under realistic operating conditions. Effects of temperature and pressure with Standard Dimension Ratios (SDR), were evaluated to determine their influence on permeation rates of MDPE and HDPE pipelines. In addition, ex-situ density and degree of crystallinity (DOC) of MDPE and HDPEs after hydrogen exposure were also investigated to understand pressure-dependency of polymer properties. The findings provide essential data for assessing polymer-based pipeline materials for safe and reliable hydrogen transport.

08 HYDROGEN↗

Next generation experimental data access at NSLS-II

The NSLS-II network and computing infrastructure has been significantly updated recently. The re-IP process in 2020-2021 enabled the NSLS-II network to be routable to the rest of the BNL campus. Then, standardization of the operating systems and deployment procedures helped to deliver a consistent environment to workstations and servers used by all NSLS-II beamlines. In particular, the RedHat Enterprise Linux 8 was deployed to 700+ machines using the RedHat Satellite infrastructure management product, and all critical services (IOCs, databases, etc.) were migrated to the new OS. NFS users’ home directories are consistent across all of the machines, which eliminates the need for the individual configuration of the user environment on each host. The standard suite of software packages is available to the beamline staff and users, which includes the system packages (deployed via RPM) as well as the conda environments for data acquisition and analysis. Security measures were implemented to comply with the industry standards, which include multi-factor authentication (using Duo), secure screen lock for the beamline machines, and advanced access control to the experimental data that is stored in shared central storage available on all hosts. These major enhancements facilitated sharing the experimental data (currently for a number of selected beamlines, with a plan to extend it to the whole facility in the nearest future) with the users via an externally facing JupyterHub instance. The beamlines keep using the Bluesky data acquisition framework to orchestrate their experiments, and the new infrastructure enabled them to use a next-generation data access library called tiled.

36 MATERIALS SCIENCE↗

Combustion and Emissions Analysis of Alternatives

NASA’s Aeronautics Research Mission Directorate requested an analysis of alternatives (AoA) study on the following three competencies in 2020: subsonic transport acoustics, combustion and emissions, and aircraft icing. This presentation will address details specific to the combustion and emissions analysis of alternatives study. The basic process used for during the AoA study in shown in Figure 1. Figure 1. Flow chart of the Analysis of Alternative process used in this study. The combustion study team was multidisciplinary, including a wide range perspectives and areas of expertise. Inputs were collected from within NASA and a wide range of external stakeholders, including aircraft engine companies, aircraft airframe companies and other government agencies. Eight future realities for aviation were developed in preparation for the applying the AoA process, such as future realities with increased or decrease airline traffic, greater emissions stringency, or a revolution in energy infrastructure (such as hydrogen usage). Based on the inputs collected, over seventy technical elements applicable to combustion and emissions research were developed. To rank the importance of these technical elements for each future reality, a set of evaluation criterion were developed that can be generally characterized as environmental impacts, technologies enabling reduced fuel burn, and elements requiring significant NASA involvement or having significant industry pull. Using in-house codes to apply the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methodology, as well performing consistency checks and other analysis by the study team, a ranked set of technical elements was generated. Several research needs were identified and analyzed to determine the highest priorities for potential research by NASA in the combustion and emissions area. Results from the study will be presented.

combustion↗

SimCCS: An open-source tool for optimizing CO 2 capture, transport, and storage infrastructure

Commercial-scale carbon capture and storage (CCS) technology will involve deploying infrastructure on a massive and costly scale. This effort will require careful and comprehensive planning to ensure that capture locations, storage sites, and the dedicated CO 2 distribution pipelines are selected in a robust and cost-effective manner. Presented in 2009, SimCCS is an optimization model for integrated system design that enables researchers, stakeholders, and policy makers to design CCS infrastructure networks. SimCCS 2.0 is a complete, ground-up redesign that is now a portable software package, useable and shareable by the CCS research, industrial, policy, and public communities. SimCCS 2.0 integrates multiple new capabilities including a refined optimization model, novel candidate network generation techniques, and optional integration with high-performance computing platforms. Accessing user-provided CO 2 source, sink, and transportation data, SimCCS 2.0 creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design. This optimization problem is further solved either through a high-performance computing interface, or through third-party software on a local desktop computing platform. Finally, SimCCS 2.0 employs an open-access geographic information system framework to enable analysis and visualization capabilities. SimCCS 2.0 is written in Java and is publicly available via GitHub to encourage collaboration, modification, and community development.

42 ENGINEERING↗

An Open Source Modeling Framework for Interdependent Energy-Transportation-Communication Infrastructure in Smart and Connected Communities

Infrastructure in future smart and connected communities is envisioned as an aggregate of public services, including energy, transportation, and communication systems, all intertwined with each other. The intrinsic interdependency among these systems may exert the underlying influence on both design and operation of the heterogeneous infrastructures. Yet, few prior studies have tapped into the interdependency among these systems in order to quantify their potential impacts during standard operation. In response to this, this paper proposes an open-source, flexible, integrated modeling framework suitable for designing coupled energy, transportation, and communication systems and for assessing the impact of their interdependencies. First, a novel multi-level, multi-layer, multi-agent approach is proposed to enable flexible modeling of the interconnected systems. Then, for the framework's proof of concept, preliminary component and system-level models for different systems are designed and implemented using Modelica, an equation-based object-oriented modeling language. Finally, three case studies of gradually increasing complexity are presented (energy, energy + transportation, and energy + transportation + communication) to evaluate the interdependencies among the three systems. Quantitative analyses show that the deviation of the average velocity on the road can be 10.5% and the deviation of the power drawn from the grid can be 7% with or without considering the transportation and communication system at the peak commute time, indicating the presence of notable interdependencies. The proposed modeling framework also has the potential to be further extended for various modeling purposes and use cases, such as dynamic modeling and optimization, resilience analysis, and integrated decision making in future connected communities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation system and web infrastructure for the second cryo-EM model challenge

An evaluation system and a web infrastructure were developed for the second cryo-EM model challenge. The evaluation system includes tools to validate stereo-chemical plausibility of submitted models, check their fit to the corresponding density maps, estimate their overall and per-residue accuracy, and assess their similarity to reference cryo-EM or X-ray structures as well as other models submitted in this challenge. The web infrastructure provides a convenient interface for analyzing models at different levels of detail. As a result, it includes interactively sortable tables of evaluation scores for different subsets of models and different sublevels of structure organization, and a suite of visualization tools facilitating model analysis.

59 BASIC BIOLOGICAL SCIENCES↗

Development of an Uncertainty Quantification Predictive Chemical Reaction Model for Syngas Combustion

An automated data-centric infrastructure, Process Informatics Model (PrIMe), was applied to validation and optimization of a syngas combustion model. The Bound-to-Bound Data Collaboration (B2BDC) module of PrIMe was employed to discover the limits of parameter modifications based on uncertainty quantification (UQ) and consistency analysis of the model–data system and experimental data, including shock-tube ignition delay times and laminar flame speeds. Existing syngas reaction models are reviewed, and the selected kinetic data are described in detail. Empirical rules were developed and applied to evaluate the uncertainty bounds of the literature experimental data. Here, the initial H 2 /CO reaction model, assembled from 73 reactions and 17 species, was subjected to a B2BDC analysis. For this purpose, a dataset was constructed that included a total of 167 experimental targets and 55 active model parameters. Consistency analysis of the composed dataset revealed disagreement between models and data. Further analysis suggested that removing 45 experimental targets, 8 of which were self-inconsistent, would lead to a consistent dataset. This dataset was subjected to a correlation analysis, which highlights possible directions for parameter modification and model improvement. Additionally, several methods of parameter optimization were applied, some of them unique to the B2BDC framework. The optimized models demonstrated improved agreement with experiments compared to the initially assembled model, and their predictions for experiments not included in the initial dataset (i.e., a blind prediction) were investigated. The results demonstrate benefits of applying the B2BDC methodology for developing predictive kinetic models.

01 COAL, LIGNITE, AND PEAT↗

Cross-geography scientific data transferring trends and behavior

Wide area data transfers play an important role in many science applications but rely on expensive infrastructure that often delivers disappointing performance in practice. In response, we present a systematic examination of a large set of data transfer log data to characterize transfer characteristics, including the nature of the datasets transferred, achieved throughput, user behavior, and resource usage. This analysis yields new insights that can help design better data transfer tools, optimize networking and edge resources used for transfers, and improve the performance and experience for end users. Our analysis shows that (i) most of the datasets as well as individual files transferred are very small; (ii) data corruption is not negligible for large data transfers; and (iii) the data transfer nodes utilization is low. Insights gained from our analysis suggest directions for further analysis.

Liu, Zhengchun↗

A model for live mission data systems using the OAIS reference model

Space sciences are confronted with overwhelming volume of data. The data rates are increasing, the granularity of registered observations is continuously refining, and computer technology allows producing terabytes of images and catalogs. The inexpensive emerging storage technologies, combined with the availability of high-speed communications will offer the infrastructure for extremely large data repositories to be accessible on-line. Mission data will be quickly accessible almost immediately after it has been collected from space observations. On-line science will demand for new tools and technologies for data access, data analysis, and data discovery. These trends will enhance the archival operational concepts mainly related to the long-term information preservation, placing an equally important emphasis on rapid data production, and dissemination to consumers.

mission data systems srchive system OAIS data mana↗

Evaluating the Impact of Chemical Complexity and Horizontal Resolution on Tropospheric Ozone Over the Conterminous US With a Global Variable Resolution Chemistry Model

A new configuration of the Community Earth System Model (CESM)/Community Atmosphere Model with full chemistry (CAM-chem) supporting the capability of horizontal mesh refinement through the use of the spectral element (SE) dynamical core is developed and called CESM/CAM-chem-SE. Horizontal mesh refinement in CESM/CAM-chem-SE is unique and novel in that pollutants such as ozone are accurately represented at human exposure relevant scales while also directly including global feedbacks. CESM/CAM-chem-SE with mesh refinement down to ∼14 km over the conterminous US (CONUS) is the beginning of the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICAv0). Here MUSICAv0 is evaluated and used to better understand how horizontal resolution and chemical complexity impact ozone and ozone precursors over CONUS as compared to measurements from five aircraft campaigns, which occurred in 2013. This field campaign analysis demonstrates the importance of using finer horizontal resolution to accurately simulate ozone precursors such as nitrogen oxides and carbon monoxide. In general, the impact of using more complex chemistry on ozone and other oxidation products is more pronounced when using finer horizontal resolution where a larger number of chemical regimes are resolved. Large model biases for ozone near the surface remain in the Southeast US as compared to the aircraft observations even with updated chemistry and finer horizontal resolution. This suggests a need for adding the capability of replacing sections of global emission inventories with regional inventories, increasing the vertical resolution in the planetary boundary layer, and reducing model biases in meteorological variables such as temperature and clouds.

MUSICA↗

Gateway Program Development Progress

This paper provides an overview and status of Gateway, humanity’s first space station to orbit the Moon providing vital support for a sustained, long-term human return to the lunar surface and a steppingstone to Mars as part of the Artemis missions. As a lunar outpost, Gateway is a destination for deep space crew expeditions and science investigations, a port for deep space transportation, including landers transiting to the lunar surface or spacecraft embarking to deep space destinations beyond the Earth-Moon system. The National Aeronautics and Space Administration (NASA) leads the Program and is the integrator of the spaceflight capabilities and contributions of U.S. commercial partners and international partners to develop Gateway. This paper will provide an overview of Gateway’s major components in various stages of development. The entire Gateway spacecraft is at preliminary design level of maturity, with some components at or near critical design review. Gateway’s major components are the Power and Propulsion Element; the Habitation and Logistics Outpost; Deep Space Logistics; the International Habitation module; Gateway External Robotics System; European System Providing Refueling, Infrastructure and Telecommunications; and an Airlock. This paper will also provide an update on the status of the integration activities necessary to fly and operate this complex, next-generation integrated spacecraft for a minimum 15 year design life, including systems engineering integrated analysis cycles, the autonomous Vehicle System Manager software, verification and validation labs, and common vehicle equipment. Expanding on the successful partnership that has provided over 20 years of continuous crew operations in low-Earth orbit on the International Space Station, Gateway is an evolution of this extraordinary partnership leveraging the capabilities of each contributor to expand humankind’s sustained exploration deeper into the cosmos. Highlighting the international program with participation from multiple space agencies, this paper will also provide a status of Gateway multilateral governance structure and international agreements.

Sean M Fuller↗

Gateway Program Development Progress

This paper provides an overview and status of Gateway, humanity’s first space station to orbit the Moon providing vital support for a sustained, long-term human return to the lunar surface and a steppingstone to Mars as part of the Artemis missions. As a lunar outpost, Gateway is a destination for deep space crew expeditions and science investigations, a port for deep space transportation, including landers transiting to the lunar surface or spacecraft embarking to deep space destinations beyond the Earth-Moon system. The National Aeronautics and Space Administration (NASA) leads the Program and is the integrator of the spaceflight capabilities and contributions of U.S. commercial partners and international partners to develop Gateway. This paper will provide an overview of Gateway’s major components in various stages of development. The entire Gateway spacecraft is at preliminary design level of maturity, with some components at or near critical design review. Gateway’s major components are the Power and Propulsion Element; the Habitation and Logistics Outpost; Deep Space Logistics; the International Habitation module; Gateway External Robotics System; European System Providing Refueling, Infrastructure and Telecommunications; and an Airlock. This paper will also provide an update on the status of the integration activities necessary to fly and operate this complex, next-generation integrated spacecraft for a minimum 15-year design life, including systems engineering integrated analysis cycles, the autonomous Vehicle System Manager software, verification and validation labs, and common vehicle equipment. Expanding on the successful partnership that has provided over 20 years of continuous crew operations in low-Earth orbit on the International Space Station, Gateway is an evolution of this extraordinary partnership leveraging the capabilities of each contributor to expand humankind’s sustained exploration deeper into the cosmos. Highlighting the international program with participation from multiple space agencies, this paper will also provide a status of Gateway multilateral governance structure and international agreements.

Gateway↗

Modernization Enhancements in SCALE 6.2

SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, industry, and research institutions around the world have used SCALE for nuclear safety analysis and design. However, the underlying architecture of SCALE is based on a 40-year old design with dozens of independent functional modules and control programs, primarily implemented in the Fortran programming language, with extensive use of customized intermediate files to control the logical flow of the analysis. Data are passed between individual computational codes using custom binary files that are read from and written to the hard disk. The SCALE modernization plan provides a progression towards SCALE 7, which will provide an object-oriented parallel-enabled software infrastructure with state-of-the-art methods implemented as reusable components. This paper provides a brief overview of the goals of SCALE modernization and details some modernized features available with SCALE 6.2.

modern↗

Comprehensive Analysis of Thirty Years of Land Change in Georgia: Forest Degradation, Land-Use Patterns, and Drivers

In this talk, we present results from a study, funded by the NASA Land-Cover and Land-Use Change program, of thirty years of environmental change in the country of Georgia. The country, a former Soviet Union Republic, has experienced more political, economic and social change in the last 30 years than most countries. But the environmental implications of these extreme events remain largely unknown – the region is understudied, no national forest inventory has been completed in 20 years, and previous research in the area conducted by the authors were not successful. The latter statement is because of forest degradation. After the collapse of the Soviet Union, much of the forestry infrastructure broke down and people resorted to chopping down individual trees. The result was in many parts of the country a reduction in forest biomass but not to the point of a change in land cover. This type of forest degradation, which was either gradual over decades or abrupt, could not be readily identified using the methods and data at our disposal at the time. In the recent study, we had full access to the Landsat archive in combination with computing power. By using monitoring methods that are based on time series analysis, we were able to capture and identify the gradual processes driven by small scale activities that are so characteristic of the post-Soviet Georgian landscape. We developed an approach (“CCDC-SMA”) that combines time series analysis and spectral mixture analysis running on Google Earth Engine for monitoring abrupt and gradual forest degradation. By using this approach, we found that forest degradation was significantly larger than the area estimate of deforestation; 3,541 ± 556 km2 (11% of the forest area in 1987) compared to 158 ± 98 km2 from 1987 to 2020. The prevailing narrative is that legal and illegal cutting of trees for fuelwood is primarily responsible for this process. Yet, since independence from the Soviet Union in 1991, the country has undergone rapid socioeconomic and institutional changes which have not been explored as drivers of forest change. To further our understanding of the underlying causes, we combined forest disturbance estimates, Georgian statistical data, and historical institutional change data to examine socioeconomic drivers of forest degradation. We found that higher winter temperature and drought were associated with higher degradation at the regional scale, while major institutional changes and drought were associated with higher forest degradation at the national level. Access to natural gas, the major energy alternative to fuelwood, had no significant association with degradation. Our results challenge the narrative that poverty and a lack of alternative energy infrastructure drive forest degradation and suggest that government policies banning household fuelwood cutting, including the new Forest Code of 2020, may not reduce forest degradation. Given these results, improved data on wood harvesting and more research on the commercial drivers of degradation and their links to economic and political reforms is needed to better inform forest policy in the region, especially given ongoing risks from climate change.

Pontus Olofsson↗