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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Defining Detection Limits for Continuous Monitoring Systems for Methane Emissions at Oil and Gas Facilities

Networks of fixed-point continuous monitoring systems are becoming widely used in the detection and quantification of methane emissions from oil and gas facilities in the United States. Regulatory agencies and operators are developing performance metrics for these systems, such as minimum detection limits. Performance characteristics, such as minimum detection limits, would ideally be expressed in emission rate units; however, performance parameters such as detection limits for a continuous monitoring system (CMS) will depend on meteorological conditions, the characteristics of emissions at the site where the CMS is deployed, the positioning of CMS devices in relation to the emission sources, and the amount of time allowed for the CMS to detect an emission source. This means that certifying the performance of a CMS will require test protocols with well-defined emission rates and durations; initial protocols are now being used in field tests. Field testing results will vary, however, depending on meteorological conditions and the time allowed for detection. This work demonstrates methods for evaluating CMS performance characteristics using dispersion modeling and defines an approach for normalizing test results to standard meteorological conditions using dispersion modeling.

Chen, Qining (ORCID:0000000316908091)↗
DOE OSTI2024

Mid-IR UAV-based sensing platform with deep learning to Identify and Quantify Gaseous Emission in Gas Flares

This report details the development and evaluation of a Mid-Infrared (Mid-IR) Unmanned Aerial Vehicle (UAV)-based sensing platform integrated with deep learning algorithms for the identification and quantification of gaseous emissions in gas flares. The project, spearheaded by Omega Optics, Inc., aimed to address environmental monitoring challenges by leveraging advanced photonic technologies and autonomous UAV operations. The research focused on designing, optimizing, and fabricating photonic crystal waveguides and grating couplers to enhance the sensitivity and accuracy of gas detection. A comprehensive drone-based system was developed, featuring a miniaturized sensor, GPS module, and microcontroller communication network for real-time gas concentration monitoring. The system's adaptive sampling algorithm, implemented using the Robot Operating System (ROS), enables autonomous detection and localization of gas emission sources. Preliminary results demonstrate the platform's capability to detect and monitor gas emissions with high precision, cost-effectiveness, and scalability. Future work will expand upon this foundation by introducing 3D wind model-based learning for dynamic environmental conditions and further enhancing the user interface and data processing algorithms to support broader environmental monitoring applications. Overall, this project represents a significant step forward in UAV-based environmental sensing technologies, offering robust solutions for detecting and mitigating the impacts of gaseous emissions on public health and safety.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Cell wall O-acetyl and methyl esterification patterns of leaves reflected in atmospheric emission signatures of acetic acid and methanol

Plants emit high rates of methanol (meOH), generally assumed to derive from pectin demethylation, and this increases during abiotic stress. In contrast, less is known about the emission and source of acetic acid (AA). In this study, Populus trichocarpa (California poplar) leaves in different developmental stages were desiccated and quantified for total meOH and AA emissions together with bulk cell wall acetylation and methylation content. While young leaves showed high emissions of meOH (140 μmol m -2 ) and AA (42 μmol m -2 ), emissions were reduced in mature (meOH: 69%, AA: 60%) and old (meOH: 83%, AA: 76%) leaves. In contrast, the ratio of AA/meOH emissions increased with leaf development (young: 35%, mature: 43%, old: 82%), mimicking the pattern of O -acetyl/methyl ester ratios of leaf bulk cell walls (young: 35%, mature: 38%, old: 51%), which is driven by an increase in O -acetyl and decrease in methyl ester content with age. The results are consistent with meOH and AA emission sources from cell wall de-esterification, with young expanding tissues producing highly methylated pectin that is progressively demethyl-esterified. We highlight the quantification of AA/meOH emission ratios as a potential tool for rapid phenotype screening of structural carbohydrate esterification patterns.

Dewhirst, Rebecca↗
DOE OSTI2020

A Remote Sensing Technique to Upscale Methane Emission Flux in a Subtropical Peatland

Abstract Quantification of methane (CH 4 ) gas emission from peat is critical to understand CH 4 budget from natural wetlands under a climate warming scenario. Previous studies have focused on prediction and mapping of CH 4 emission flux using process‐based models, while application of statistical‐empirical models for upscaling spatially sparse in situ measurements is scarce. In this study, we developed an empirical remote sensing upscaling approach to estimate CH 4 emission flux in the Everglades using limited in situ point‐based CH 4 emission flux measurements and Landsat data during 2013–2018. We spatially and temporally linked in situ data with Landsat surface reflectance based on temporally composite data sets and developed an object‐based machine learning framework to model and map CH 4 emission flux. An ensemble analysis of two machine learning models, k ‐Nearest Neighbor ( k ‐NN) and Support Vector Machine (SVM), shows that the upscaling approach is promising for predicting CH 4 emission flux with a R 2 of 0.65 and 0.87 based on a fivefold cross‐validation for a dry season and wet season estimation, respectively. We generated emission flux map products that successfully revealed the spatial and temporal heterogeneity of CH 4 emission within the dominant freshwater marsh ecosystem in the Everglades. We conclude that Landsat is promising for upscaling and monitoring CH 4 emission flux and reducing the uncertainty in emission estimates from wetlands.

Zhang, Caiyun↗
DOE OSTI2024

Wind-driven emissions of coarse-mode particles in an urban environment

Abstract. Quantifying surface–atmosphere exchange rates of particles is important for understanding the role of suspended particulate matter in radiative transfer, clouds, precipitation, and climate change. Emissions of coarse-mode particles with a diameter greater than 0.5 µm provide giant cloud condensation nuclei and ice nuclei. These emissions are critical for understanding the evolution of cloud microphysical properties yet remain poorly understood. Here we introduce a new method that uses lidar retrievals of the elastic backscatter and Doppler velocity to obtain surface number emissions of particles with a diameter greater than 0.53 µm. The technique is applied to study particle number fluxes over a 2-month period from 1 June to 10 August 2022 during the TRACER campaign at an urban site near Houston, TX, USA. We found that all the observed fluxes were positive (upwards), indicating particle emission from the surface. The fluxes followed a diurnal pattern and peaked near noon local time. Flux intensity varied through the 2 months with multi-day periods of strong fluxes and multi-day periods of weak fluxes. Emission particle number fluxes peaked near ∼ 100 cm−2 s−1. The daily averaged emission fluxes correlated with friction velocity and were anticorrelated with surface relative humidity. The emission flux can be parameterized as F= 3000 u*4, where u* is the friction velocity in m s−1 and the emission flux F is in cm−2 s−1. The u* dependence is consistent with emission from wind-driven erosion. Estimated values for the mass flux are in the lower range of literature values from non-urban sites. These results demonstrate that urban environments may play an important role in supplying coarse-mode particles to the boundary layer. We anticipate that quantification of these emissions will help constrain aerosol–cloud interaction models that use prognostic aerosol schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Quantitative Determination of Total Cesium in Savannah River Site (SRS) Tank Waste by Inductively Coupled Plasma Emission Spectroscropy

Utilization of the significant and unique wavelength dynamic range (165 to 1100 nm) available on the Leeman Prodigy Inductively Coupled Plasma Emission Spectroscopy (ICP-ES) allows for quantification of cesium using the emission line 894.347 nm without the potential of Barium interference in nuclear waste samples. Samples are added to a Sodium Peroxide Fusion and Lithium Carbonate buffer in 2% nitric acid solution to increase sensitivity of the easily ionizable (<6 eV) cesium for quantitation to 5 pbb. Through direct comparison of analytical data results, the method is proven to be complementary to the Inductively Coupled Plasma Mass Spectrometry (ICP-MS) analysis (LOQ 100 ppt) in support of the Department of Energy’s (DOE) Nuclear Waste Mission.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Design, Build, and Initial Testing of a Portable Methane Measurement Platform

The quantification of methane concentrations in air is essential for the quantification of methane emissions, which in turn is necessary to determine absolute emissions and the efficacy of emission mitigation strategies. These are essential if countries are to meet climate goals. Large-scale deployment of methane analyzers across millions of emission sites is prohibitively expensive, and lower-cost instrumentation has been recently developed as an alternative. Currently, it is unclear how cheaper instrumentation will affect measurement resolution or accuracy. To test this, the Wireless Autonomous Transportable Methane Emission Reporting System (WATCH 4 ERS) has been developed, comprising four commercially available sensing technologies: metal oxide (MOx,), Non-dispersion Infrared (NDIR), integrated infrared (INIR), and tunable diode laser absorption spectrometer (TDLAS). WATCHERS is the accumulated knowledge of several long-term methane measurement projects at Colorado State University’s Methane Emission Technology Evaluation Center (METEC), and this study describes the integration of these sensors into a single unit and reports initial instrument response to calibration procedures and controlled release experiments. Specifically, this paper aims to describe the development of the WATCH 4 ERS unit, report initial sensor responses, and describe future research goals. Meanwhile, future work will use data gathered by multiple WATCH 4 ERS units to 1. better understand the cost–benefit balance of methane sensors, and 2. identify how decreasing instrumentation costs could increase deployment coverage and therefore inform large-scale methane monitoring strategies. Both calibration and response experiments indicate the INIR has little practical use for measuring methane concentrations less than 500 ppm. The MOx sensor is shown to have a logarithmic response to methane concentration change between background and 600 ppm but it is strongly suggested that passively sampling MOx sensors cannot respond fast enough to report concentrations that change in a sub-minute time frame. The NDIR sensor reported a linear change to methane concentration between background and 600 ppm, although there was a noticeable lag in reporting changing concentration, especially at higher values, and individual peaks could be observed throughout the experiment even when the plumes were released 5 s apart. The TDLAS sensor reported all changes in concentration but remains prohibitively expensive. Our findings suggest that each sensor technology could be optimized by either operational design or deployment location to quantify methane emissions. The WATCH4ERS units will be deployed in real-world environments to investigate the utility of each in the future.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Evaluating the feasibility of using downwind methods to quantify point source oil and gas emissions using continuously monitoring fence-line sensors

The dependable reporting of methane (CH 4 ) emissions from point sources, such as fugitive leaks from oil and gas infrastructure, is important for profit maximization (retaining more hydrocarbons), evaluating climate impacts, assessing CH 4 fees for regulatory programs, and validating CH 4 intensity in differentiated gas programs. Currently, there are disagreements between emissions reported by different quantification techniques for the same sources. It has been suggested that downwind CH 4 quantification methods using CH 4 measurements on the fence line of production facilities could be used to generate emission estimates from oil and gas operations at the site level, but it is currently unclear how accurate the quantified emissions are. To investigate the accuracy of downwind methods, this study uses fence-line simulated data collected during controlled-release experiments as input for a non-standard closed-path eddy covariance (EC), the Gaussian plume inverse model (GPIM), and the backward Lagrangian stochastic (bLs) model in a range of atmospheric conditions. This study's EC attempt was unsuccessful due to data collection and instrumentation issues, resulting in invalid results characterized by underestimated emissions, large negative fluxes, and cospectra/ogives that deviated from their ideal shapes. Consequently, the EC results could not be compared with the GPIM and bLS model. The bLs model demonstrated the highest accuracy for single-release single-point emissions, though it exhibited greater uncertainty than GPIM under multi-release conditions. Across the GPIM and bLs model, the most reliable quantification was achieved with 15 min averaging and a narrow 5° wind sector range. Although EC was limited in this context, future studies should consider employing a standard EC system and further optimizing GPIM and bLs approaches – particularly for complex multi-source scenarios – to enhance quantification accuracy and reduce uncertainty.

03 NATURAL GAS↗
DOE OSTI2025

Orphaned oil and gas well methane emission rates quantified using Gaussian plume inversions of ambient observations

Abstract. Annually, ∼ 3.6 million abandoned oil and gas wells in the US emit a combined ∼ 2.6 Tg methane (CH4), adversely affecting climate and regional air quality. However, these estimates depend on emission factors derived from measuring subpopulations of wells that vary by orders of magnitude due to very limited field sampling and poorly characterized distributions. Currently, US protocols to remediate orphaned wells lacks standardized quantification methods needed to both prioritize plugging and account for emission reductions. Therefore, sensitive, reliable, affordable, and scalable CH4 flux quantification methods are needed. We report the use of a simple Gaussian plume method where the dispersion parameters are constrained by in situ ground measurements of CH4 concentration at four locations 7.5–49 m downwind of the orphan well as well as local winds to estimate the leak rate from an orphan well. We derive a flux of 10.53 ± 1.16 kg CH4 h−1 during a venting procedure in April 2023 that agrees with the directly measured volumetric flow rate of 9.00 ± 0.25 kg CH4 h−1. This is 71 % greater than the 5.3 kg CH4 h−1 flux measured 7 months prior. Additionally, we discovered a secondary leak through the surface casing inferred as 0.43–0.67 kg CH4 h−1 both by our ground Gaussian analysis and by transecting the plume with an uncrewed aerial system (UAS). We show that in situ determination of the dispersion parameters used in our Gaussian inversions allows us to measure methane emissions to 15 % accuracy, significantly reducing errors when compared to the standard practice of assuming stability class. Our results help develop simpler methods and protocols for robust orphan well emission quantification that can be used for reporting.

Follansbee, Emily↗
DOE OSTI2024

Positron emission tomography harmonization in the Alzheimer's Disease Neuroimaging Initiative: A scalable and rigorous approach to multisite amyloid and tau quantification

Abstract INTRODUCTION A key goal of the Alzheimer's Disease NeuroImaging Initiative (ADNI) positron emission tomography (PET) Core is to harmonize quantification of β‐amyloid (Aβ) and tau PET image data across multiple scanners and tracers. METHODS We developed an analysis pipeline (Berkeley PET Imaging Pipeline, B‐PIP) for ADNI Aβ and tau PET images and applied it to PET data from other multisite studies. Steps include image pre‐processing, refacing, magnetic resonance imaging (MRI)/PET co‐registration, visual quality control (QC), quantification of tracer uptake, and standardization of Aβ and tau standardized uptake value ratios (SUVrs) across tracers. RESULTS Measurements from 10,105 cross‐sectional and longitudinal Aβ and tau PET scans acquired in several studies between 2010 and 2024 can be processed, harmonized, and directly merged across tracers and cohorts. DISCUSSION The B‐PIP developed in ADNI is a scalable image harmonization approach used in several observational studies and clinical trials that facilitates rigorous Aβ and tau PET quantification and data sharing. Highlights Quantitative results from ADNI Aβ and tau PET data are generated using a rigorous, scalable image processing pipeline This pipeline has been applied to PET data from several other large, multisite studies and trials Quantitative outcomes are harmonizable across studies and are shared with the scientific community

Neurosciences & Neurology↗
DOE OSTI2020

Impacts of the morphology of new neighborhoods on microclimate and building energy

In anticipation of emerging global urbanization and consequent increases in energy use and carbon dioxide emissions, better understanding and quantification of climate effects on energy use in cities are needed, requiring coordinated research into large-scale, regional, and microclimate impacts to and from the city structure. The methodology described here addresses this need by (1) demonstrating a process for creating and testing example morphologies for new neighborhoods for their impact on local and regional meteorology within a two-way-coupled four-domain nested mesoscale weather model (6 km horizontal resolution outer domain, 90 m horizontal innermost domain) and (2) allocating resulting building-level meteorological profiles to each building in a neighborhood for parallel computation of building-by-building energy use. Our Chicago Loop test case shows that the morphology of even a small new added development to a neighborhood affects not only its own microclimate, but also the microclimate of the original neighborhood to which the development was added, and that these changes in microclimate affect both neighborhoods’ building energy use. Furthermore, this method represents an important step toward quantifying and analyzing the relationships among climatic conditions, urban morphology, and energy use and using these relationships to inform energy-efficient urban development and planning.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Fossil Energy in the Hydrogen Economy – A Carbon-Water-Energy Nexus Adaptive Evaluation Platform

This project develops tools to evaluate fossil energy within the hydrogen economy. In particular, the project seeks to explore the Carbon-Water-Energy Nexus and develop adaptive evaluation tools. The primary goal of this project was to evaluate fossil-based hydrogen production methods with an emphasis on their sustainability, particularly with respect to carbon emissions and water use. The overall technical objectives that guided this evaluation consisted of 1) technology assessment, which sought to establish a comprehensive baseline of existing and emerging technologies for the generation, transportation, storage, and end use of hydrogen derived from fossil fuels, 2) carbon footprint analysis through quantification and analysis of carbon emissions associated with these hydrogen technologies, and identification of novel strategies and technologies that can effectively mitigate the carbon footprint, 3) water intensity assessment by evaluating the water needs (water-energy nexus) associated with different fossil fuel-based hydrogen technologies and proposing strategies to reduce water use, thus ensuring sustainable resource management, and 4) review of regulatory, policy and economic trends were examined to provide an overview of the factors influencing the adoption and integration of fossil fuel-derived hydrogen technologies into current energy markets. Beyond the technical outcomes, this project contributed to 5) education and workforce development through targeted training and educational opportunities for engineering students, preparing the next generation of professionals with technical, economic, and regulatory expertise in the hydrogen economy. Ultimately, this effort was intended to train the future workforce to provide useful insights to policymakers, industry stakeholders, and the broader energy community to facilitate informed decisions and responsible development within the hydrogen economy.

08 HYDROGEN↗
DOE OSTI2025

Computational Fluid Dynamics-Based Modeling of Methane Flows Around Oil and Gas Equipment

Recent studies estimate that emissions from oil and gas production facilities contribute between 20 and 50% of the total methane ( CH 4 ) emitted in the US; therefore, quantifying and reducing these emissions are crucial for achieving climate goals. Methane quantification depends on both measuring methane concentrations and converting them to emissions through a modeling framework. Currently, simple atmospheric dispersion models are primarily used to quantify emissions and concentrations, but these estimates are highly uncertain when quantifying emissions from complex aerodynamic sources, such as oil and gas facilities. This investigation used a CFD modeling approach, which can account for aerodynamic complexity but has hitherto not been used to model methane concentrations downwind of a methane release of a known rate, and compared it against in situ measurements. High-time-resolution (1 Hz) methane concentration and meteorological data were measured during experiments conducted at the METEC on 21 March and 11 July 2024. The METEC site configuration, measured wind data, and controlled emission rates were used as input for the CONVERGE CFD model to model downwind CH 4 concentration. The modeling was carried out between 20 and 70 m, from two different points of release in two separate controlled-release experiments, one from a separator and another from a wellhead. In these experiments, we found that the CFD model could predict the CH 4 concentrations downwind of the release to a good degree. The model was evaluated on multiple metrics to assess its performance in estimating methane concentrations at typical fence line distances (∼30 m). These results help us to understand external flows and the ability of CFD models to predict downwind concentrations in aerodynamically complex environments.

03 NATURAL GAS↗
DOE OSTI2024

Filamentary Dust Polarization and the Morphology of Neutral Hydrogen Structures

Filamentary structures in neutral hydrogen (H$\tiny{I}$) emission are well aligned with the interstellar magnetic field, so H$\tiny{I}$ emission morphology can be used to construct templates that strongly correlate with measurements of polarized thermal dust emission. We explore how the quantification of filament morphology affects this correlation. We introduce a new implementation of the Rolling Hough Transform (RHT) using spherical harmonic convolutions, which enables efficient quantification of filamentary structure on the sphere. We use this Spherical RHT algorithm along with a Hessian-based method to construct H$\tiny{I}$-based polarization templates. We discuss improvements to each algorithm relative to similar implementations in the literature and compare their outputs. By exploring the parameter space of filament morphologies with the Spherical RHT, we find that the most informative H$\tiny{I}$ structures for modeling the magnetic field structure are the thinnest resolved filaments. For this reason, we find a ~10% enhancement in the B-mode correlation with polarized dust emission with higher-resolution H$\tiny{I}$ observations. We demonstrate that certain interstellar morphologies can produce parity-violating signatures, i.e., nonzero TB and EB, even under the assumption that filaments are locally aligned with the magnetic field. Finally, we demonstrate that B modes from interstellar dust filaments are mostly affected by the topology of the filaments with respect to one another and their relative polarized intensities, whereas E modes are mostly sensitive to the shapes of individual filaments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Rare Earth Element Detection and Quantification in Coal and Rock Mineral Matrices

As global demand for rare earth elements (REEs) increases, maintaining the production and supply chain is critical. Technologies capable of being used in the field and in situ in the subsurface for rapid REE detection and quantification facilitates the efficient mining of known resources and exploration of new and unconventional resources. Laser-induced breakdown spectroscopy (LIBS) is a promising technique for rapid elemental analysis both in the laboratory and in the field. Multiple articles have been published evaluating LIBS for detection and quantification of REEs; however, REEs in their natural deposits have not been adequately studied. In this work, detection and quantification of two REEs, La and Nd, have been studied in both synthetic and natural mineral matrices at concentrations relevant to REE extraction. Measurements were performed on REE-containing rock and coal samples (natural and synthetic) utilizing different LIBS instruments and techniques, specifically a commercial benchtop instrument, a custom benchtop instrument (single- and double-pulse modes), and a custom LIBS probe currently being developed for in situ, subsurface, borehole wall detection and quantification of REEs. Plasma expansion, emission intensity, detection limits, and double-pulse signal enhancement were studied. The limits of detection (LOD) were found to be 10/14 ppm for La and 15/25 ppm for Nd in simulated coal/rock matrices in single-pulse mode. Signal enhancement of 3.5 to 6-fold was obtained with double-pulse mode as compared to single-pulse operation.

La detection↗
DOE OSTI2024

Integrated Methane Monitoring Platform Design (Final Report)

As the urgency for understanding methane emissions and the number of methane monitoring technologies being deployed have increased in the last two decades, there is an opportunity and a need to integrate the numerous disparate data sources to enable the detection, quantification, contextualization, and reporting of methane emissions along the oil and gas supply chain. Such an integration would enable emissions reductions through early detection of super emitters, data-driven mitigation strategies, and improved greenhouse gas inventories. The GTI Energy (“GTI”) project team (“the team”) worked with a multitude of industry experts, stakeholders, and subject matter experts (SMEs) to collect guidance, insights, and information to inform the requirements and subsequent engineering, design, deployment, and operations of an integrated methane monitoring platform (IMMP). This final report describes the results of the team’s effort to execute the Integrated Methane Monitoring Platform Design project, ultimately providing an engineering, design, deployment, and operating plan (EDDOP) for the IMMP. This final report summarizes and integrates the project tasks' results and outputs.

03 NATURAL GAS↗
DOE OSTI2024

Supporting Information for the Integrated Methane Monitoring Platform Design (Final Report)

As the urgency for understanding methane emissions and the number of methane monitoring technologies being deployed have increased in the last two decades, there is an opportunity and a need to integrate the numerous disparate data sources to enable the detection, quantification, contextualization, and reporting of methane emissions along the oil and gas supply chain. Such an integration would enable emissions reductions through early detection of super emitters, data-driven mitigation strategies, and improvedgreenhouse gas inventories. The GTI Energy (“GTI”)project team (“the team”) worked with a multitude of industry experts, stakeholders, and subject matter experts (SMEs) to collect guidance, insights, and information to inform the requirements and subsequent engineering, design, deployment, and operations of an integrated methane monitoring platform (IMMP). This final report describes the results of the team’s effort to execute the Integrated Methane Monitoring Platform Design project, ultimately providing an engineering, design, deployment, and operating plan (EDDOP) for the IMMP. This document provides additional information supporting the findings in the final report.

03 NATURAL GAS↗