Search NASA⌕ Search

SEARCH · Search NASA

Results for “Fusion Engine”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Static characterization of a highly optimized streak tube design incorporating a steering slot anode and an aberration-corrected Einzel lens

The BHx streak tube, under development at the Laboratory for Laser Energetics, incorporates a series of novel electron-optics elements to enable high fidelity measurements for high-energy-density physics experiments. The system is engineered to support a 25-mm active photocathode region compatible with sub-picosecond temporal resolution and with 70% internal photoelectron throughput. It exhibits negligible geometric distortion on a flat output screen, making it well suited for variety of measurements, such as ultrafast x-ray spectroscopy. Here, this paper presents characterization data from a prototype unit tested with an ultraviolet laser in a static deflection (non-swept) mode and shows good agreement with the predictions from numerical modeling, including focusing performance and geometric distortion measurements. Key design elements have been demonstrated and de-risked, laying the foundation for dynamic deflection testing. The anticipated improvements in data fidelity are expected to impact the fields as diverse as inertial confinement fusion, laboratory astrophysics, and materials science.

High energy density physics↗
DOE OSTI2025

TRANSP Workshop Summary - September 27-28, 2024, Princeton Plasma Physics Laboratory, NJ

The TRANSP Code Workshop provided a platform for in-depth discussions on advancing the capabilities of the TRANSP code, focusing on key areas such as predictive capabilities, interpretive frameworks, core-edge coupling, and integration with engineering components. More than 25 scientists from PPPL and around the world contributed to the workshop by making presentations and participating in discussions. The workshop covered a range of topics including: (1) Current Status of TRANSP; (2) Code Infrastructure, Core-Edge Coupling, and Engineering Integration; (3) Enhancing Interpretive Capabilities, and (4) Predictive Capabilities for Discharge Optimization

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

First indirectly driven liquid-DT filled double shell implosions at the National Ignition Facility

Double shell implosions aim to explore material mixing under fusion conditions in a volume burn geometry using high-Z metal pushers. High-Z pushers are more compressible than low-Z pushers enabling high stagnation pressure which reduces the required implosion speed while maintaining a low pusher adiabat despite strong shock heating. Additionally, the use of a small fuel mass reduces the fuel internal energy required for ignition, thus achieving stable platforms with reasonable fusion output to conduct controlled experiments. These factors make volume burn in a double shell implosion highly promising. Recently, a series of liquid-DT filled, indirectly driven, double shell implosions were conducted at the National Ignition Facility with laser drives reaching up to 1.5 MJ. These experiments achieved a maximum DT neutron yield of 1.67 × 10 14 (yield—479 J), DT ion temperature of 2.6 keV, fuel areal density (ρR) of 0.15 g/cm 2 , and stagnation pressure of 79 Gbar. Over the course of these shots, the DT neutron yield has increased by an order of magnitude largely from improved mitigation of outer shell assembly joint driven instability growth using thicker gold plating at the assembly joint. Further performance improvements are expected by enhancing outer-to-inner shell kinetic energy transfer and refined mitigation of degradations from engineering features such as the outer shell joint, fill tube, and surface roughness.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Establishing model credibility for process-microstructure-property relationships in additive manufacturing using exascale computing

Additive Manufacturing (AM) of alloys holds significant promise as a disruptive technology in various industries, yet its adoption is often hindered by challenges in achieving consistent part quality. These issues are primarily due to the complex process-microstructure-property (PSP) relationships inherent to AM. Computational models can greatly aid in understanding these relationships, but their widespread impact and adoption has been limited by a lack of validated, open-source, and computationally efficient PSP modeling frameworks and hardware limitations. Here, this study leverages the ExaAM software suite and data from the AMBench-2018 series of laser powder bed fusion (LPBF) benchmark experiments to perform a comprehensive model assessment, including verification, validation, sensitivity analysis, and uncertainty quantification. The RADICAL-EnTK workflow manager was used to perform an ensemble of heat transport, solidification, and mechanical response simulations on the exascale computer Frontier, considering uncertainties in critical model inputs such as laser spot size and nucleation parameters, and consisting of 125 explicit grain structure simulations and 7875 crystal plasticity simulations. For a selected location within the Inconel 625 AMBench-2018 test artifact, sensitivity analysis and uncertainty quantification were performed using the predicted distributions of grain structure and mechanical properties. Qualitative agreement was found between the predicted grain size and texture and the observed AMBench-2018 microstructure, the mean predicted yield stress was within 5% of the experimental measurement mean, and the mean predicted engineering stress at 5% strain was within 10% of the experimental measurement mean. The insights gained from development and validation of the ExaAM PSP modeling framework will help guide future directions for enhancing the credibility and reliability of PSP models in AM, thereby accelerating the adoption of AM technologies in various industries.

Additive manufacturing↗
DOE OSTI2026

In-situ sensor monitoring of multi-class gas porosity formation in laser powder bed fusion using convolutional neural network

In-situ monitoring of defect formation remains a significant challenge in the laser powder bed fusion (LPBF) process. Recent advances have enabled real-time defect detection with machine learning and in-situ sensing technologies; however, most studies focus on binary classification of keyhole pores, limiting nuanced multi-class pore differentiation and formation mechanisms. This work introduces a multi-class pore detection framework (no pore, small pores < 15 µm, and large pores > 15 µm) by leveraging photodiode sensor data alongside high-fidelity synchrotron X-ray imaging. The 15 µm threshold is selected to distinguish between two fundamentally different defect mechanisms, following the physical size-mechanism boundary established by prior high-resolution synchrotron X-ray characterization of Al6061 LPBF. Distinguishing these classes is critical because large keyhole pores are structurally detrimental, whereas small gas pores are often benign, requiring different process control strategies. Thermal emission monitoring data collected simultaneously with high-speed X-ray imaging at the Stanford Synchrotron Radiation Lightsource (SSRL), are correlated with subsurface melt pool dynamics to establish ground truth. Continuous Wavelet Transform (CWT) with optimized parameters converts the photodiode time-series signals into time–frequency images, facilitating feature extraction. Convolutional Neural Networks (CNN) are then applied for real-time multi-class pore classification in an average inference time of 1 ms per signal window. It achieves 79% accuracy and an Area Under the Receiver Operating Characteristic curve (AUC ROC) score of 0.89 with five-fold cross-validation. The results demonstrate that coupling CWT-based feature engineering with CNN architecture enables reliable multi-class pore detection in Al6061 builds using affordable in-situ sensors. This approach advances scalable and affordable quality assurance in additive manufacturing by moving beyond binary defect detection toward more nuanced classification of porosity mechanisms with in-situ sensors and machine learning.

Laser powder bed fusion, Multi-class pores, In-sit↗
NASA NTRSDate not supplied

Advancing GRCop-based Bimetallic Additive Manufacturing to Optimize Component Design and Applications for Liquid Rocket Engines

Additive manufacturing (AM) is advancing many applications of component design for liquid rocket engines. The ability to rapidly design and manufacture components has provided significant opportunities for development and flight programs across the propulsion industry. AM has demonstrated significant advantages that include cost and schedule savings in addition to performance improvements through new design opportunities. While these performance advantages can be in the characteristics of complex design features, they can also be in the form of new materials. AM has been demonstrated in these various component applications using a variety of metal alloys, many of which are traditional alloys for extreme environments. Additional developments were completed using AM to provide new alloys and maturing these material uses for high performance applications. Almost all of the prior developments across component applications have focused on single-alloys in these AM processes. NASA and industry partners have focused in recent years to advance processing to create bimetallic and multicomponent AM processes and materials. The role of multi-alloy AM offers advantages since it can further optimize weight, optimize reliability and performance by increasing the strength to weight ratio of a component, and can optimize materials for various engineering requirements. This is particularly important in liquid rocket engine combustion devices that must reject heat in high heat flux environments yet maintain adequate structural margins under high operational pressure. NASA has been exploring several AM processes, materials, and applications for combustion devices, specifically combustion chambers, injectors, nozzles, and ignition systems. These components require fine geometric features for internal flow or cooling functionality. They experience high thermal gradients across thin-walls and must survive high pressures and temperatures from propellants and the combustion process. A copper-based alloy is normally used to provide high thermal conductivity, but at the detriment of increased weight if used as a single alloy in an AM chamber. Various AM processes were demonstrated on these components using a copper-based alloy/superalloy bimetallic solution. The AM processes being explored individually and in combination for bimetallic applications include Laser Powder Bed Fusion (L-PBF), Laser Powder Directed Energy Deposition (LP-DED), and cold spray. The combination of bimetallic material combinations explored in this research include copper-based material primarily and superalloys, Inconel 625 or NASA HR-1. The various aspects of the additive manufacturing processes and challenges, materials characterization, and the testing of bimetallic components in a relevant environment will be discussed.

Additive Manufacturing↗
NASA NTRSDate not supplied

Advancing GRCop-based Bimetallic Additive Manufacturing to Optimize Component Design and Applications for Liquid Rocket Engines

Additive manufacturing (AM) is advancing many applications of component design for liquid rocket engines. The ability to rapidly design and manufacture components has provided significant opportunities for development and flight programs across the propulsion industry. AM has demonstrated significant advantages that include cost and schedule savings in addition to performance improvements through new design opportunities. While these performance advantages can be in the characteristics of complex design features, they can also be in the form of new materials. AM has been demonstrated in these various component applications using a variety of metal alloys, many of which are traditional alloys for extreme environments. Additional developments were completed using AM to provide new alloys and maturing these material uses for high performance applications. Almost all of the prior developments across component applications have focused on single-alloys in these AM processes. NASA and industry partners have focused in recent years to advance processing to create bimetallic and multicomponent AM processes and materials. The role of multi-alloy AM offers advantages since it can further optimize weight, optimize reliability and performance by increasing the strength to weight ratio of a component, and can optimize materials for various engineering requirements. This is particularly important in liquid rocket engine combustion devices that must reject heat in high heat flux environments yet maintain adequate structural margins under high operational pressure. NASA has been exploring several AM processes, materials, and applications for combustion devices, specifically combustion chambers, injectors, nozzles, and ignition systems. These components require fine geometric features for internal flow or cooling functionality. They experience high thermal gradients across thin-walls and must survive high pressures and temperatures from propellants and the combustion process. A copper-based alloy is normally used to provide high thermal conductivity, but at the detriment of increased weight if used as a single alloy in an AM chamber. Various AM processes were demonstrated on these components using a copper-based alloy/superalloy bimetallic solution. The AM processes being explored individually and in combination for bimetallic applications include Laser Powder Bed Fusion (L-PBF), Laser Powder Directed Energy Deposition (LP-DED), and cold spray. The combination of bimetallic material combinations explored in this research include copper-based material primarily and superalloys, Inconel 625 or NASA HR-1. The various aspects of the additive manufacturing processes and challenges, materials characterization, and the testing of bimetallic components in a relevant environment will be discussed.

Additive Manufacturing↗
DOE OSTI2024

Direct numerical simulations of three-component Rayleigh–Taylor mixing and an improved model for multicomponent reacting mixtures

We present direct numerical simulations of a three-layer Rayleigh–Taylor instability (RTI) problem with a configuration based on the experiments of Suchandra & Ranjan ( J. Fluid Mech. , vol. 974, 2023, A35) and Jacobs & Dalziel ( J. Fluid Mech. , vol. 542, 2005, pp. 251–279). The problem consists of a layer of light fluid between two layers of heavy fluid with an Atwood number of 0.3. These simulations are first validated through comparison with available experimental data. The validated simulations are then utilized to analyse statistics in this three-component flow. First, length scales are examined utilizing spectra and two-point spatial correlations of velocity and species concentration fluctuations. Next, joint probability density functions (p.d.f.s) of species concentration are compared against several model p.d.f.s representing generalizations of the bivariate beta distribution. Notably, the joint p.d.f.s do not appear to be accurately described by a Dirichlet distribution, indicating the marginal distributions do not conform to a beta distribution. Finally, similarity of the present configuration to three-component mixing found in inertial confinement fusion (ICF) applications is exploited to develop and validate an improved model for the impact of multicomponent mixing on thermonuclear (TN) reaction rates. A single time instant from the present simulations is chosen for a TN burn calculation under the hypothetical assumption of ICF materials and temperatures. Total TN output from this second calculation is then compared against the prediction of the improved model. The new model is found to accurately predict TN reaction rates in both premixed and non-premixed configurations.

42 ENGINEERING↗
DOE OSTI2025

Portable and Adaptable Neutron Diagnostics for Advancing Fusion Energy Science Addendum

Activation detectors developed at LLNL for measuring real-time neutron fluence from fusion sources are used in the broader fusion community. The recommended fluence operating range of this diagnostic is 5x10 2 – 1x10 6 n/cm2. The upper limit on this fluence range is set by the dead time caused by data transfer between the detector and data acquisition computer. Delaying the start of counting is a possible strategy to operate these detectors in higher fluences.

42 ENGINEERING↗
DOE OSTI2026

Counter-propagating toroidal Alfvén eigenmodes in tokamaks

Mechanisms of destabilization of toroidal Alfvén eigenmodes (TAEs) in tokamaks are analyzed with the aim to reveal those leading to modes propagating in the direction opposite to plasma current, i.e. counter-propagating modes (ctr-TAE). Plasmas with fast-ions sources [such as neutral beam injection (NBI), ion cyclotron resonance heating, fusion reactions] and without them (Ohmic discharges) are considered. A particular NSTX-U experiment with NBI, where co- and counter-propagating TAEs were observed simultaneously (Podestà et al 2018 Nucl. Fusion 58 082023), is considered. It is concluded that both types of TAEs occurred because their destabilization was caused by the velocity anisotropy of beam ions, which overrode effects of spatial inhomogeneity of these ions.

Alfvénic instabilities↗
DOE OSTI2025

Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints

This project focuses on developing a thermo-metallurgical-mechanical modeling method to accurately predict the microstructural evolution and residual stress in laser welding between dissimilar metals, such as HSLA steel and high carbon equivalent (CE) gear steel. The method leverages a comprehensive material database to model the temperature and rate dependent phase transformations, along with their associated effects on material properties, such as thermal expansion and flow stress, throughout the welding process. A key innovation is the incorporation of phase transformation and phase-specific properties, which enhances the accuracy of residual stress predictions. The mixture material in the fusion zone due to the dissimilar metals will also be addressed in the numerical model. This is especially critical in scenarios involving phase transformations in the fusion zone and heat-affected zone (HAZ), where the phase changes can induce substantial residual stress variations. The material database has been generated using JMatPro. The modeling approach is implemented through a custom User Material (UMAT) subroutine, executed with the commercial finite element software Abaqus.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Transmission electron microscopy with in-situ ion irradiation: Facilities and community

Whilst there is a clear scientific and technological need for the technical capabilities of transmission electron microscopes with in-situ ion irradiation, it also requires a collaborative community of international researchers to support such facilities in successfully meeting this demand. Instruments of this type serve to provide fundamental understanding of the mechanisms which drive changes in materials important to nuclear fission and fusion energy, the semiconductor industry, quantum information systems, space travel, astronomy, geology and many more applications. As these areas continue to evolve and the instrumentation possibilities expand, the capacity of in-situ ion irradiation facilities must also develop hand-in-hand with the user community to deliver an ever-greater diversity of high-fidelity extreme-environment experimentation. Future directions for the field, such as miniaturization from MEMS/microfluidic devices and advanced controls with ML-based analysis, continuously emerge to advance both the hardware and software which support the coupling of TEMs with ion beams. This review sets out to provide up-to-date insights into the community and advancement of current, and development of future, facilities which have the potential to further unlock access to the nanoscale exploration of coupled extreme environments crucial to many of the important science and engineering challenges we face today.

In-situ irradiation↗
NASA NTRS2019

Channel Wall Nozzle Manufacturing Technology Advancements for Liquid Rocket Engines

A regeneratively-cooled nozzle is a critical component for expansion of the hot gases to enable high temperature and performance liquid rocket engines systems. Channel wall nozzles are a design solution used across the propulsion industry as a simplified method to fabricate the nozzle structure with internal coolant passages. The scale and complexity of the channel wall nozzle (CWN) design is challenging to fabricate leading to extended lead times and higher costs. Some of these challenges include: 1) unique and high temperature materials, 2) Tight tolerances during manufacturing and assembly to contain high pressure propellants, 3) thin-walled features to maintain adequate wall temperatures, and 4) Unique manufacturing process operations and tooling. The United States (U.S.) National Aeronautics and Space Administration (NASA) along with U.S. specialty manufacturing vendors are maturing modern fabrication techniques to reduce complexity and decrease costs associated with channel wall nozzle manufacturing technology. Additive Manufacturing (AM) is one of the key technology advancements being evaluated for channel wall nozzles. Much of additive manufacturing for propulsion components has focused on powder bed fusion, but the scale is not yet feasible for application to large scale nozzles. NASA is evolving directed energy deposition (DED) techniques for nozzles including arc-based deposition, blown powder deposition, and Laser Wire Direct Closeout (LWDC). There are different approaches being considered for fabrication of the nozzle and each of these DED processes offer unique process steps for rapid fabrication. The arc-based and blown powder deposition techniques are being used for the forming of the CWN liner. A variety of materials are being demonstrated including Inconel 625, Haynes 230, JBK-75, and NASA HR-1. The blown powder DED process is also being demonstrated for forming an integral channel nozzle in a single operation in similar materials. The LWDC process is a method for closing out the channels within the liner and forming the structural jacket using a localized laser wire deposition technique. Identical materials mentioned above have been used for this process in addition to bimetallic closeout (C-18150–SS347, and C-18150–Inconel 625). NASA has completed process development, material characterization, and hot-fire testing on a variety of these channel wall nozzle fabrication techniques. This paper will present an overview of the various processes and materials being evaluated and the results from the hot-fire testing. Future development and technology focus areas will also be discussed relative to channel wall nozzle manufacturing.

Gradl, Paul R.↗
DOE OSTI2024

Analysis of Waste Material Feedstocks Using Laser-Induced Breakdown Spectroscopy and Machine Learning

Predicting properties such as heating value, ash fusion temperature, and mineral ash composition from Laser-Induced Breakdown Spectroscopy (LIBS) data can make gasifiers more flexible to different feedstocks. Understanding these feedstock properties in-situ improves feedstock conversion modelling methods that allow for consistent operation, higher carbon conversion, and reduced fouling and erosion rates. The purpose of this study is to demonstrate methods for model creation that take LIBS data as predictor features and estimate higher order material properties as a function of feedstock material properties. Six samples were chosen to represent a mixture of abundant and carbon rich waste materials. LIBS measurements were performed on these samples for elemental wavelengths and intensity values. Laboratory analytical results were obtained for each sample’s heating value, proximate and ultimate analysis, mineral ash composition, ash fusion temperatures, and viscosity temperatures. Thermal conductivity was measured using a HotDisk TPS 2500S. LIBS measurements were processed and used as predictor features for machine learning (ML) models to predict the sample’s material properties. Predictor feature selection algorithms, particularly minimum redundancy maximum relevance (mRMR), reduced the dimensionality of ML models. Many modelling methods such as Gaussian process regression (GPR), regression tree, neural networks (NN), and support vector machines (SVM) were demonstrated to be effective at predicting higher order properties; however, mRMR with GPR stood out as a clear winning combination.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2020

ATD-2 Benefits Mechanism

NASA has been developing and demonstrating a suite of decision support capabilities for integrated arrival, departure, and surface (IADS) operations in a metroplex environment. The effort is being made in three phases, under NASA’s Airspace Technology Demonstration 2 (ATD-2) sub-project, through a close partnership with the Federal Aviation Administration (FAA), air carriers, airport, and general aviation community. The Phase 1 Baseline IADS capabilities provide enhanced operational efficiency and predictability of flight operations through data exchange and integration, tactical surface metering, and automated coordination of release time of controlled flights for overhead stream insertion. The Phase 2 Fused IADS capabilities include the fusion of strategic and tactical surface metering, Atlanta Center airspace tactical scheduling, Electronic Flight Data (EFD) integration, Terminal Flight Data Manager (TFDM) Terminal Publication (TTP) prototype, and Mobile App for General Aviation (GA) community. In the Phase 2 field evaluation, strategic surface metering provides advance notice of metering and additional stability to the assigned gate holds. The users of the IADS system in Phases 1 and 2 include the personnel at Charlotte Douglas International Airport (CLT) air traffic control tower, American Airlines ramp tower, CLT terminal radar approach control (TRACON), and Washington and Atlanta Center. This document describes the ATD-2 benefits mechanism used to assess the Phases 1 and 2 IADS capabilities and field evaluation conducted at CLT since September 2017. The ATD-2 benefits mechanism mainly consists of surface metering and overhead stream insertion. This document provides detailed calculation methods of major benefit metrics, such as fuel savings, gas emissions savings, and engine runtime reduction, which can be obtained through surface metering, gate hold of Approval Request (APREQ) flights prior to pushback, and the renegotiation of release time while taxiing. As of March 31, 2020, it is estimated that 5,075,981 pounds of fuel savings and 15,634,022 pounds of CO2 emission reduction have been achieved so far, with a reduction of 3,832 hours in total engine runtime. The amount of CO2 savings is estimated to be equivalent to planting 116,254 urban trees. The pre- and post-metering comparison results using FAA’s Aviation System Performance Metrics (ASPM) data have also shown that the surface metering had no negative impact on the on-time arrival performance of both outbound and inbound flights at CLT.

ATD-2↗
NASA NTRS2020

ATD-2 Benefits Mechanism

NASA has been developing and demonstrating a suite of decision support capabilities for integrated arrival, departure, and surface (IADS) operations in a metroplex environment. The effort is being made in three phases, under NASA’s Airspace Technology Demonstration 2 (ATD-2) sub-project, through a close partnership with the Federal Aviation Administration (FAA), air carriers, airport, and general aviation community. The Phase 1 Baseline IADS capabilities provide enhanced operational efficiency and predictability of flight operations through data exchange and integration, tactical surface metering, and automated coordination of release time of controlled flights for overhead stream insertion. The Phase 2 Fused IADS capabilities include the fusion of strategic and tactical surface metering, Atlanta Center airspace tactical scheduling, Electronic Flight Data (EFD) integration, Terminal Flight Data Manager (TFDM) Terminal Publication (TTP) prototype, and Mobile App for General Aviation (GA) community. In the Phase 2 field evaluation, strategic surface metering provides advance notice of metering and additional stability to the assigned gate holds. The users of the IADS system in Phases 1 and 2 include the personnel at Charlotte Douglas International Airport (CLT) air traffic control tower, American Airlines ramp tower, CLT terminal radar approach control (TRACON), and Washington and Atlanta Center. This document describes the ATD-2 benefits mechanism used to assess the Phases 1 and 2 IADS capabilities and field evaluation conducted at CLT since September 2017. The ATD-2 benefits mechanism mainly consists of surface metering and overhead stream insertion. This document provides detailed calculation methods of major benefit metrics, such as fuel savings, gas emissions savings, and engine runtime reduction, which can be obtained through surface metering, gate hold of Approval Request (APREQ) flights prior to pushback, and the renegotiation of release time while taxiing. As of April 30, 2020, it is estimated that 5,097,173 pounds of fuel savings and 15,699,292 pounds of CO2 emission reduction have been achieved so far, with a reduction of 3,831 hours in total engine runtime. The amount of CO2 savings is estimated to be equivalent to planting 116,739 urban trees. The pre- and post-metering comparison results using FAA’s Aviation System Performance Metrics (ASPM) data have also shown that the surface metering had no negative impact on the on-time arrival performance of both outbound and inbound flights at CLT.

ATD-2↗
NASA NTRSDate not supplied

Towards A Flexible Data Fusion Tool Incorporating Model, Satellite, Regulatory Monitor and Low-Cost Sensor Data for Air Quality Estimation and Forecasting

Air quality managers, researchers, and concerned community scientists around the world have a variety of sources for air quality information, ranging from traditional regulatory monitoring networks and atmospheric chemistry models to remote sensing data products and low-cost sensor networks. However, the ability to incorporate data from these disparate sources and synthesize a comprehensive overview of the local air quality situation remains a considerable barrier for many end-users. This presentation will outline a tool, currently in development, which will address this need using a flexible data fusion approach. The tool will make use of air quality forecast model outputs (primarily from the NASA GEOS-CF composition forecast modeling system), satellite remote sensing data (from instruments including MODIS, VIIRS, TROPOMI, plus TEMPO for the US when available), and in-situ data from official regulatory and/or low-cost networks where these are available. The ability to incorporate data from low-cost sensor networks will be a key feature of the tool; it will make use of other available data sources to calibrate the low-cost sensor data on a regional scale, then use these calibrated low-cost sensor data for localized updating to resolve finer-scale air quality patterns. Development of this tool is taking place with the help of national and international partners and end-user groups, coordinated through the US EPA and the United Nations Environment Programme (UNEP). The tool is being developed on the Google Earth Engine cloud computing platform to facilitate integration of diverse data sources and free access by a broad community of end-users. Stewardship of the tool will be passed to US EPA and UNEP to support future activities with end-users in the US and around the world, and the tool itself will remain freely accessible. We hope that this tool will lower the barrier to entry for various user groups worldwide, including community scientists, who struggle to integrate disparate data sources to gain insight into their local air quality situations. This presentation will cover the early stages of the development of the tool, including the underlying methods and some pilot case studies in integrating low-cost sensor data.

global models↗