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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Common practices for quantifying methane emissions from plumes detected by remote sensing

This document provides a set of community-accepted practices for quantifying methane emissions based on plumes detected via spectroscopic remote sensing. Its primary goal is to promote consistency in the generation, validation, reporting, and quality assessment of methane emission estimates derived from remote sensing radiances. Developed by subject matter experts with deep experience across all stages of the measurement process, this guidance reflects a critical evaluation of current methodologies and highlights key practices needed to produce reliable, interoperable, and traceable products. The focus is specifically on methane emissions quantified from distinct plumes originating from localized sources, rather than diffuse emissions spread over large regions, which are beyond the scope of this work. This document is intended to serve both data producers and users. For producers, it offers a framework for aligning with field-recognized standards to ensure their outputs meet rigorous quality and transparency criteria. For users, it provides a reference to assess dataset fitness-for-purpose by highlighting essential metadata, assumptions, and methodological choices that underpin emission estimates. By fostering a shared understanding of best practices, this work aims to enhance comparability, confidence, and utility of remotely sensed methane emission products.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Concept for Inclusion of Analytical and Computational Capability in Optical Plume Anomaly Detection (OPAD) for Measurement of Neutron Flux

Researchers are working on many konts to make possible high speed, automated classification and quantification of constituent materials in numerous environments. NASA's Marshall Space Flight Center has implemented a system for rocket engine flow fields/plumes; the Optical Plume Anomaly Detection (OPAD) system was designed to utilize emission and absorption spectroscopy for monitoring molecular and atomic particulates in gas plasma. An accompanying suite of tools and analytical package designed to utilize information collected by OPAD is known as the Engine Diagnostic Filtering System (EDIFIS). The current combination of these systems identifies atomic and molecular species and quantifies mass loss rates in H2/O2 rocket plumes. Additionally, efforts are being advanced to hardware encode components of the EDIFIS in order to address real-time operational requirements for health monitoring and management. This paper addresses the OPAD with its tool suite, and discusses what is considered a natural progression: a concept for migrating OPAD towards detection of high energy particles, including neutrons and gamma rays. The integration of these tools and capabilities will provide NASA with a systematic approach to monitor space vehicle internal and external environment.

Patrick, M. Clinton↗
NASA NTRS1973

Dynamics of suspended sediment in Lake Ontario

The author has identified the following significant results. The suspended sediment plumes generated by the Welland Canal and the Genesee River are identifiable in most band 5 frames received from ERTS-1. In descending order of value for plume detection in Lake Ontario are bands 4, 6, and 7. Little or no information content relative to plume detection is available in band 7. The Oswego River plume was not visible during low flow periods; however, it was identifiable immediately following storms. Increased suspended sediment loading emanating from storm runoff increases turbidity levels to the point where the plume becomes visible in the ERTS-1 imagery. Despite the fact that it is detectable from high altitude (60,000 feet) photography, the Niagara River plume was not visible in any of the ERTS-1 frames. Numerous examples of shoreline erosion were evident in the December 7, 1972, imagery of western Lake Ontario. Near shore lake circulation patterns are usually apparent whenever turbidity plumes are sensed by the satellite.

Pluhowski, E. J.↗
NASA NTRS1996

Development of a Computer Architecture to Support the Optical Plume Anomaly Detection (OPAD) System

The NASA OPAD spectrometer system relies heavily on extensive software which repetitively extracts spectral information from the engine plume and reports the amounts of metals which are present in the plume. The development of this software is at a sufficiently advanced stage where it can be used in actual engine tests to provide valuable data on engine operation and health. This activity will continue and, in addition, the OPAD system is planned to be used in flight aboard space vehicles. The two implementations, test-stand and in-flight, may have some differing requirements. For example, the data stored during a test-stand experiment are much more extensive than in the in-flight case. In both cases though, the majority of the requirements are similar. New data from the spectrograph is generated at a rate of once every 0.5 sec or faster. All processing must be completed within this period of time to maintain real-time performance. Every 0.5 sec, the OPAD system must report the amounts of specific metals within the engine plume, given the spectral data. At present, the software in the OPAD system performs this function by solving the inverse problem. It uses powerful physics-based computational models (the SPECTRA code), which receive amounts of metals as inputs to produce the spectral data that would have been observed, had the same metal amounts been present in the engine plume. During the experiment, for every spectrum that is observed, an initial approximation is performed using neural networks to establish an initial metal composition which approximates as accurately as possible the real one. Then, using optimization techniques, the SPECTRA code is repetitively used to produce a fit to the data, by adjusting the metal input amounts until the produced spectrum matches the observed one to within a given level of tolerance. This iterative solution to the original problem of determining the metal composition in the plume requires a relatively long period of time to execute the software in a modern single-processor workstation, and therefore real-time operation is currently not possible. A different number of iterations may be required to perform spectral data fitting per spectral sample. Yet, the OPAD system must be designed to maintain real-time performance in all cases. Although faster single-processor workstations are available for execution of the fitting and SPECTRA software, this option is unattractive due to the excessive cost associated with very fast workstations and also due to the fact that such hardware is not easily expandable to accommodate future versions of the software which may require more processing power. Initial research has already demonstrated that the OPAD software can take advantage of a parallel computer architecture to achieve the necessary speedup. Current work has improved the software by converting it into a form which is easily parallelizable. Timing experiments have been performed to establish the computational complexity and execution speed of major components of the software. This work provides the foundation of future work which will create a fully parallel version of the software executing in a shared-memory multiprocessor system.

Katsinis, Constantine↗
NASA NTRS1995

Investigation of the collision line broadening problem as applicable to the NASA Optical Plume Anomaly Detection (OPAD) system, phase 1

As a final report for phase 1 of the project, the researchers are submitting to the Tennessee Tech Office of Research the following two papers (reprinted in this report): 'Collision Line Broadening Effects on Spectrometric Data from the Optical Plume Anomaly System (OPAD),' presented at the 30th AIAA/ASME/SAE/ASEE Joint Propulsion Conference, 27-29 June 1994, and 'Calculation of Collision Cross Sections for Atomic Line Broadening in the Plume of the Space Shuttle Main Engine (SSME),' presented at the IEEE Southeastcon '95, 26-29 March 1995. These papers fully state the problem and the progress made up to the end of NASA Fiscal Year 1994. The NASA OPAD system was devised to predict concentrations of anomalous species in the plume of the Space Shuttle Main Engine (SSME) through analysis of spectrometric data. The self absorption of the radiation of these plume anomalies is highly dependent on the line shape of the atomic transition of interest. The Collision Line Broadening paper discusses the methods used to predict line shapes of atomic transitions in the environment of a rocket plume. The Voigt profile is used as the line shape factor since both Doppler and collisional line broadening are significant. Methods used to determine the collisional cross sections are discussed and the results are given and compared with experimental data. These collisional cross sections are then incorporated into the current self absorbing radiative model and the predicted spectrum is compared to actual spectral data collected from the Stennis Space Center Diagnostic Test Facility rocket engine. The second paper included in this report investigates an analytical method for determining the cross sections for collision line broadening by molecular perturbers, using effective central force interaction potentials. These cross sections are determined for several atomic species with H2, one of the principal constituents of the SSME plume environment, and compared with experimental data.

Dean, Timothy C.↗
NASA NTRS2004

Concept for Inclusion of Analytical and Computational Capability in Optical Plume Anomaly Detection (OPAD) for Measurement of Neutron Flux

Researchers are working on many fronts to make possible high-speed, automated classification and quantification of constituent materials in numerous environments. NASA's Marshall Space Flight Center has implemented a system for rocket engine flowfields/plumes. The Optical Plume Anomaly Detector (OPAD) system was designed to utilize emission and absorption spectroscopy for monitoring molecular and atomic particulates in gas plasma. An accompanying suite of tools and analytical package designed to utilize information collected by OPAD is known as the Engine Diagnostic Filtering System (EDiFiS). The current combination of these systems identifies atomic and molecular species and quantifies mass loss rates in H2/O2 rocket plumes. Capabilities for real-time processing are being advanced on several fronts, including an effort to hardware encode components of the EDiFiS for health monitoring and management. This paper addresses the OPAD with its tool suites, and discusses what is considered a natural progression: a concept for taking OPAD to the next logical level of high energy physics, incorporating fermion and boson particle analyses in measurement of neutron flux.

Patrick, Marshall Clint↗
NASA NTRS2008

Algorithms for Spectral Decomposition with Applications to Optical Plume Anomaly Detection

The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main approaches that can be taken to extract relevant features from these high-dimensional data streams. The first set of approaches relies on extracting features using a physics-based paradigm where the underlying physical mechanism that generates the spectra is used to infer the most important features in the data stream. We focus on a complementary methodology that uses a data-driven technique that is informed by the underlying physics but also has the ability to adapt to unmodeled system attributes and dynamics. We discuss the following four algorithms: Spectral Decomposition Algorithm (SDA), Non-Negative Matrix Factorization (NMF), Independent Component Analysis (ICA) and Principal Components Analysis (PCA) and compare their performance on a spectral emulator which we use to generate artificial data with known statistical properties. This spectral emulator mimics the real-world phenomena arising from the plume of the space shuttle main engine and can be used to validate the results that arise from various spectral decomposition algorithms and is very useful for situations where real-world systems have very low probabilities of fault or failure. Our results indicate that methods like SDA and NMF provide a straightforward way of incorporating prior physical knowledge while NMF with a tuning mechanism can give superior performance on some tests. We demonstrate these algorithms to detect potential system-health issues on data from a spectral emulator with tunable health parameters.

Srivastava, Askok N.↗
NASA NTRS2017

Aerial Vehicles to Detect Maximum Volume of Plume Material Associated with Habitable Areas in Extreme Environments

Current technologies of exploring habitable areas of icy moons are limited to flybys of space probes. This research project addresses long-term navigation of icy moons by developing a MATLAB adjustable trajectory based on the volume of plume material observed. Plumes expose materials from the sub-surface without accessing the subsurface. Aerial vehicles capable of scouting vapor plumes and detecting maximum plume material volumes, which are considered potentially habitable in inhospitable environments, would enable future deep-space missions to search for extraterrestrial organisms on the surface of icy moons. Although this platform is still a prototype, it demonstrates the potential aerial vehicles can have in improving the capabilities of long-term space navigation and enabling technology for detecting life in extreme environments. Additionally, this work is developing the capabilities that could be utilized as a platform for space biology research. For example, aerial vehicles that are sent to map extreme environments of icy moons or the planet Mars, could also carry small payloads with automated cell-biology experiments, designed to probe the biological response of low-gravity and high-radiation planetary environments, serving as a pathfinder for future human missions.

Vehicles Extreme Environment↗
NASA NTRS2018

Robotic External Leak Locator (RELL) Leak Plume Field Detection on the International Space Station (ISS)

The Robotic External Leak Locator (RELL) was deployed to the International Space Station (ISS) with the objective of demonstrating the ability to detect and locate small leaks. On-orbit operations began in late November 2016 and following scanning activities to characterize the natural and induced environment of the ISS, RELL focused on the United States External Active Thermal Control System (EATCS). RELL successfully detected ammonia related to a known small ammonia leak in the port-side EATCS, with the highest pressure values around the inboard Radiator Beam Valve Module 1 (RBVM 1). An additional day of scanning was subsequently performed in December 2017 to focus on RBVM 1. RELL was approved for additional external operations in February 2017 with the goal of fine tuning the location of the leak. Using grid scanning patterns, RELL detected ammonia around RBVM 1 and located the approximate source of the leak. The potential leak site was inspected by a crew member during an Extravehicular Activity (EVA) in March 2017, and the suspected radiator-side lines were isolated from the port-side EATCS coolant loop in April 2017. Subsequent monitoring of the system pressures showed that the leak has stopped, indicating RELL accurately located the source of the EATCS leak. These activities verify that RELL enhances the ISS Program's ability to not only locate small leaks, but isolate the source with minimal impact to the entire ISS system.

External Active Thermal Control System↗
DOE OSTI2025

Sensor Placement Optimization Study for the Built Environment: Operational Use Cases

Systems of fixed-position radiation sensors can provide information that assists emergency responders following nuclear and radiological incidents. State, local, tribal, and territorial (SLTT) government agencies that implement systems of fixed-position sensors are faced with numerous decisions regarding sensor selection, quantity, and placement. To develop guidance on implementation of radiation detection systems, we simulated the release of radioactive material in an urban environment using a combination of three models: the Weather Research Forecasting (WRF), Quick Urban and Industrial Complex (QUIC), and Monte Carlo N-Particle (MCNP) models. We then evaluated the performance of several hypothetical sensor systems. The small number of simulations we conducted are not sufficient to generate definitive design guidance for radiation sensor systems, but we did identify trends that would be of interest to emergency planners. For a scenario that releases 1000 curies of Cs-137, radiation detectors were needed at 500-meter intervals to have a high likelihood of event detection and to estimate source location and plume detection. We also noted that optimal detector altitude varied with distance to the source. We recommend additional research in this area be conducted to support developing sensor placement guidelines that expand on a range of locations, isotopes, activity levels, and different weather conditions. Original simulation strategies included a range of environments, additional radioisotopes (Am241 and AmBe), and a larger selection of sensor types. These types of expansions would support SLTT guidance on sensor system recommendations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1979

Volcanic eruption plumes on Io

Preliminary analyses of the eight volcanic eruption plumes detected on Io by Voyager 1 are presented. Plumes were observed on the bright and dark limbs of the satellite corresponding to half of the surface and range from 10,000 to 75 km in width and 280 to 70 km in height. Most plumes were observed to be umbrella-shaped, however one consists of a very diffuse cloud lacking columnar fountain characteristics. Plume sources are characterized by a dark central area, surrounded by a bright ring, which in turn is surrounded by a broad, diffuse region; the presence of similar markings in regions not observed at the limb indicates additional volcanic activity on Io. No changes were detected in the sizes or intensities of the eruptions over the 6.5-day viewing period, however a change in the appearance of a region near one plume suggests a short-lived eruption between observations. Seven of the eight plumes are located within 30 deg of the equator, implying that equatorial surfaces are generally younger than those in the polar regions.

Strom, R. G.↗
DOE OSTI2025

Improved Gas Plume Identification Using Nearest Neighbor Methods for Background Estimation

Longwave infrared (LWIR) hyperspectral imaging (HSI) can be used for many tasks in remote sensing, including detecting and identifying effluent gases by LWIR sensors on airborne platforms. Identification is used after detection to increase confidence in weakly detected plumes, reduce false positives from detection, and distinguish between similar and confounding material signatures. Background estimation is an important step used to reveal the unique spectral characteristics of the detected gas, allowing the identification model to determine what the gas is specifically. The importance of proper background estimation increases when dealing with weak signals, large libraries of gases of interest, and uncommon or heterogeneous backgrounds. In this article, we propose two methods for background estimation: a novel k-nearest segments (KNS) algorithm and the standard k-nearest neighbors (KNN) algorithm. We test our methods and three existing background estimation methods for comparison against global background estimation to determine which performs best at estimating the true background radiance under a plume and for increasing identification confidence using a neural network classification model. We compare the different methods using 640 simulated weak plumes in an urban environment. For identification, our KNS algorithm improves median neural network identification confidence by 53.2%. For background radiance estimation, the KNN algorithm provides a median of 49 times less RMSE than global background estimation. Furthermore, KNN is the easiest method to tune for different plumes, making it an excellent “out of the box” background estimator.

47 OTHER INSTRUMENTATION↗