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NASA NTRS2022

Global Fine Scale Changes in Ambient NO2 During COVID-19 Lockdowns

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health(1–9) . A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-19(10–20). Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates.

Ground level NO2↗

DOE OSTI2012

Subnanometer and nanometer catalysts, method for preparing size-selected catalysts

Highly uniform cluster based nanocatalysts supported on technologically relevant supports were synthesized for reactions of top industrial relevance. The Pt-cluster based catalysts outperformed the very best reported ODHP catalyst in both activity (by up to two orders of magnitude higher turn-over frequencies) and in selectivity. The results clearly demonstrate that highly dispersed ultra-small Pt clusters precisely localized on high-surface area supports can lead to affordable new catalysts for highly efficient and economic propene production, including considerably simplified separation of the final product. The combined GISAXS-mass spectrometry provides an excellent tool to monitor the evolution of size and shape of nanocatalyst at action under realistic conditions. Also provided are sub-nanometer gold and sub-nanometer to few nm size-selected silver catalysts which possess size dependent tunable catalytic properties in the epoxidation of alkenes. Invented size-selected cluster deposition provides a unique tool to tune material properties by atom-by-atom fashion, which can be stabilized by protective overcoats.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2012

Subnanometer and nanometer catalysts, method for preparing size-selected catalysts

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2015

Systematic assessment of wellbore integrity for geologic carbon storage projects using regulatory and industry information

Under this three year project, the condition of legacy oil and gas wells in the Midwest United States was evaluated through analysis of well records, well plugging information, CBL evaluation, sustained casing pressure (SCP) field testing, and analysis of hypothetical CO 2 test areas to provide a realistic description of wellbore integrity factors. The research included a state-wide review of oil and gas well records for Ohio and Michigan, along with more detailed testing of wells in Ohio. Results concluded that oil and gas wells are clustered along fields in areas. Well records vary in quality, and there may be wells that have not been identified in records, but there are options for surveying unknown wells. Many of the deep saline formations being considered for CO 2 storage have few wells that penetrate the storage zone or confining layers. Research suggests that a variety of well construction and plugging approaches have been used over time in the region. The project concluded that wellbore integrity is an important issue for CO 2 storage applications in the Midwest United States. Realistic CO 2 storage projects may cover an area in the subsurface with several hundred legacy oil and gas wells. However, closer inspection may often establish that most of the wells do not penetrate the confining layers or storage zone. Therefore, addressing well integrity may be manageable. Field monitoring of SCP also indicated that tested wells provided zonal isolation of the reservoirs they were designed to isolate. Most of these wells appeared to exhibit gas pressure originating from intermediate zones. Based on these results, more flexibility in terms of cementing wells to surface, allowing well testing, and monitoring wells may aid operators in completing CO 2 storage project. Several useful products were developed under this project for examining wellbore integrity for CO 2 storage applications including, a database of over 4 million items on well integrity parameters in the study areas, a systematic CBL evaluation tool for rating cement in boreholes, SCP field testing procedures and analysis methodology, a process for summarizing well integrity at CO 2 storage fields, a statistical analysis of well integrity indicators, and an assessment of practical methods and costs necessary to repair/remediate typical wells in the region based on assessment of six test study areas. Project results may benefit both CO 2 storage and improved oil recovery applications. This study of wellbore integrity is a useful precursor to support development of geologic storage in the Midwest United States because it sheds more light on the actual well conditions (rather than the perceived condition) of historic oil and gas wells in the region.

42 ENGINEERING↗

NASA NTRS2019

Comprehensive Severe Weather Impact Assessment and Monitoring using Synthetic Aperture Radar and Auxiliary Data

Remote sensing datasets, particularly acquired by Synthetic Aperture Radar (SAR) sensors, have become increasingly important in severe weather disaster impact studies given their ability to observe the Earth largely irrespective of weather and sunlight conditions. The reliability of existing SAR change detection products applied on a pair of SAR images is constrained by the limitation of current methods to differentiate and classify disaster specific changes from anthropogenic surface alterations. Moreover, the inherent properties of the sensors, variations in SAR backscatter due to changes in surface conditions, and other factors exacerbate these limitations. We proposed a novel procedure expanding on earlier SAR-based change detection methods to exclude anthropogenic alterations and other sources of ambiguity that might lead to inaccurate mapping of the impacts of severe weather disasters. We applied the proposed procedure that is based on long term interferometric and amplitude-based change detection analyses of Sentinel- 1 SAR imagery to two study sites recently impacted by severe weather disasters (Flooding post severe weather events in urban centers; Hailstorm damage on crops). For the first case study, Sentinel-1 SLC scenes from two flood events in the Houston area (April 2016 flooding event and Hurricane Harvey of August-September 2017) were used to construct a flood map depicting areas repeatedly affected by the flood. Pixels with consistent coherence values in the pre-disaster coherence stack were retained for comparison with the pre- and post-disaster coherence stack and pixels with significant decline (greater than 60%) in coherence values were retained in the final flood map. The findings of the applied technique were calibrated and validated through datasets from NOAA/NWS Service storm reports, aerial imaging (NOAA and Civil Air Patrol), Federal Emergency Management Agency (FEMA) reporting, and targeted collections of NASA’s L-band UAVSAR data. Findings and products derived from the adopted methodology can be useful in disaster response and mitigation activities.

Gebremichael, Esayas↗

DOE OSTI2010

Independent technical review of the building 100 plume, former doe pinellas site (young - rainey star center), largo, florida

Contaminated groundwater associated with Building 100 at the Young-Rainey Science, Technology, and Research Center, formerly the DOE Pinellas plant, is the primary remedial challenge that remains to be addressed at the site. Currently, Building 100 is an active industrial facility that is now owned and operated by the Pinellas county government. Groundwater samples collected from monitoring wells recently installed near the southern boundary of the site suggest that contaminated groundwater has migrated off the plant site. In response to the challenges presented by the Building 100 plume, the Office of Legacy Management (LM) requested assistance from the DOE Office of Groundwater and Soil Remediation (EM-32) to provide a review team to make technical recommendations so that they can efficiently and effectively address characterization and remediation of the plume. The review team was unanimous in the conclusion that a dynamic strategy that combines a phased implementation of direct push samplers, sensors, and tools can be used to better delineate the extent of contamination, control plume migration, and rapidly remediate the contaminated groundwater at the site. The initial efforts of the team focused on reviewing the site history and data, organizing the information into a conceptual model, identifying appropriate technologies, and recommending an integrated strategy. The current groundwater data from the site indicate a two-lobed plume extending to the east and south. To the east vinyl chloride is the primary contaminant of concern, to the south, vinyl chloride and cis1, 2-DCE are the primary contaminants. The limited data that are available suggest that reductive dechlorination of the TCE is already occurring but is not sufficient to prevent offsite migration of low concentrations of TCE daughter products. The team recommends that DOE pursue a strategy that builds on the natural cleansing capacity of the subsurface with reductive methods including biostimulation and/or bioaugmentation to provide a sustainable remediation system within the flow path of the plume. Additional data will be required to implement this approach and will include: (1) Better delineation of the nature and extent of contamination; (2) Demonstration the plume is currently stable or shrinking; and (3) Demonstration the full reductive dechlorination is occurring. The technical team recommends that DOE use a phased approach to identify residual contamination and to provide rapid installation of remedies. Matrices of characterization and remediation sensors, technologies, and tools were developed by the team in order to match the specific conditions and requirements of the site. The team provides a specific example of remedy that includes the incorporation of a dynamic characterization strategy moving from minimally invasive to more aggressive field techniques, the consideration of multiple complementary remediation approaches based on a spatiotemporally phased approach keyed to the different demands of different parts of the plume, and the integration and sequencing of the characterization and remediation activities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Annual Status Report (FY 2020): Performance Assessment for the Environmental Restoration Disposal Facility

DOE O 435.1 and DOE M 435.1-1 require that a determination of continued adequacy of the performance assessment (PA) (CP-60089), composite analysis, and disposal authorization statement (DAS) be made annually, and these guidelines must be used to consider the results of data collection and analysis from research, field studies, and monitoring as well as provide the need to update any radioactive waste management basis documents. Beginning in 1996, the Environmental Restoration Disposal Facility (ERDF) started accepting low-level radioactive, hazardous, and mixed wastes generated during cleanup activities at the Hanford Site. ERDF is composed of a series of cells or disposal areas and can accommodate future design expansions as needed. Currently, there are 10 cells. During this reporting period (fiscal year 2020, which extended from October 1, 2019, through September 30, 2020), approximately 3.39E+04 U.S. tons (3.07E+04 metric tons) of waste was disposed at ERDF. From ERDF inception through September 30, 2020, approximately 18.5 million U.S. tons of waste has been disposed at ERDF, which equates to the consumption of approximately 88% of the disposal volume. As a condition of the DAS, disposal operations within ERDF must be in accordance with the waste acceptance criteria (ERDF-00011) that provide specific radionuclide disposal limits, waste form restrictions, and descriptions of acceptable waste packages in compliance with DOE M 435.1-1 requirements. The ERDF waste acceptance criteria stipulate that waste destined for disposal at ERDF be controlled based on source, physical form, and contaminant concentration and activity levels. There have been no changes to the physical configuration of ERDF or to the waste forms (source, physical form, etc.). No new Unreviewed Disposal Question Screenings or Evaluations have been generated during this reporting period. Therefore, there are no noted impacts to the PA, composite analysis, DAS, or radioactive waste management basis documents resulting from the evaluations and screenings. Sum of fraction analysis shows that the disposed inventory meets both the concentration and inventory threshold requirements. A sum of fractions value is computed for ERDF sensitive radionuclides contributing to the all pathways and air pathway inventory limits. Computed values were 8.85E-02 and 1.78E-01, respectively. The disposed waste inventory remained well under the PA imposed limits. Required monitoring was satisfactorily completed during the fiscal year reporting period (fiscal year 2020). Compliance with performance objectives were met as each of the reported values were well below the established limit. Overall, there are no substantive changes to primary PA assumptions nor changes to the PA analysis conclusion; therefore, compliance with DOE O 435.1 and the DAS is maintained.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Development of transparent microwell arrays for optical monitoring and dissection of microbial communities

Microbial communities are incredibly complex systems that dramatically and ubiquitously influence our lives. They help to shape our climate and environment, impact agriculture, drive business, and have a tremendous bearing on healthcare and physical security. Spatial confinement, as well as local variations in physical and chemical properties, affects development and interactions within microbial communities that occupy critical niches in the environment. Recent work has demonstrated the use of silicon based microwell arrays, combined with parylene lift-off techniques, to perform both deterministic and stochastic assembly of microbial communities en masse, enabling the high-throughput screening of microbial communities for their response to growth in confined environments under different conditions. The implementation of a transparent microwell array platform can expand and improve the imaging modalities that can be used to characterize these assembled communities. In this paper, the fabrication and characterization of a next generation transparent microwell array is described. The transparent arrays, comprised of SU-8 patterned on a glass coverslip, retain the ability to use parylene lift-off by integrating a low temperature atomic layer deposition of silicon dioxide into the fabrication process. This silicon dioxide layer prevents adhesion of the parylene material to the patterned SU-8, facilitating dry lift-off, and maintaining the ability to easily assemble microbial communities within the microwells. These transparent microwell arrays can screen numerous community compositions using continuous, high resolution, imaging. Finally, the utility of the design was successfully demonstrated through the stochastic seeding and imaging of green fluorescent protein expressing Escherichia coli using both fluorescence and brightfield microscopies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Hardware-Based Demonstration of Temperature Control Functions for Reactor Systems

Establishing autonomy in reactor control systems has become essential for the expansion of nuclear technologies. Thermal regulation in particular remains crucial for maintaining stable operation and ensuring the integrity of fuel. To alleviate public skepticism of the safety of nuclear reactors, demonstrating control over this key factor is pivotal. Utilizing electric heat pads to simulate the heat released in a reactor core, thermocouples for temperature monitoring, and an Arduino micro programmable logic controller (PLC) for control, a hardware-based demonstration of a reactor heating system validates the efficacy of reactor control over this key parameter. To improve precision, a proportional-integral-derivative (PID) algorithm was implemented in the heating control loop to ensure meticulous control of reactor functions. In addition, the integration of this physical system with a digital simulator tool such as RELAP5-3D establishes a foundation for a comprehensive testing environment. This allows for a refinement of temperature control under various simulated reactor conditions, bringing another layer of reliability to the operation of the system. By facilitating a physical demonstration of reactor thermal management and control strategies, this project provides a foundation for expanded testing and educational outreach. Ultimately, this system advances the broader goal of demonstrating the safety and viability of autonomous reactor operations, contributing to public trust and future reactor deployment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1985

Impurities in silicon solar cells

Metallic impurities, both singly and in combinations, affect the performance of silicon solar cells. Czochralski silicon web crystals were grown with controlled additions of secondary impurities. The primary electrical dopants were boron and phosphorus. The silicon test ingots were grown under controlled and carefully monitored conditions from high-purity charge and dopant material to minimize unintentional contamination. Following growth, each crystal was characterized by chemical, microstructural, electrical, and solar cell tests to provide a detailed and internally consistent description of the relationships between silicon impurity concentration and solar cell performance. Deep-level spectroscopy measurements were used to measure impurity concentrations at levels below the detectability of other techniques and to study thermally-induced changes in impurity activity. For the majority of contaminants, impurity-induced performance loss is due to a reduction of the base diffusion length. From these observations, a semi-empirical model which predicts cell performance as a function of metal impurity concentration was formulated. The model was then used successfully to predict the behavior of solar cells bearing as many as 11 different impurities.

Hopkins, R. H.↗

NASA NTRS1991

Model-based diagnostics for the SSME

This paper presents models to diagnose the condition of the Space Shuttle Main Engine (SSME). A qualitative physics based model derived from the thermodynamic processes and the flow characteristics underlying the SSME operation was developed to detect and isolate engine failures to the component level. This qualitative model was augmented with empirical models derived from the SSME test-stand data to rapidly detect faults which manifest themselves in engine parameter measurements as deviations from the nominal values. The empirical models integrated with the qualitative model offer the potential for building a complex modeling framework for performing comprehensive engine health monitoring.

Tulpule, S.↗

NASA NTRS2000

A User's Guide for the Spacecraft Fire Safety Facility

The Spacecraft Fire Safety Facility (SFSF) is a test facility that can be flown on NASA's reduced gravity aircraft to perform various types of combustion experiments under a variety of experimental conditions. To date, this facility has flown numerous times on the aircraft and has been used to perform experiments ranging from an examination of the effects transient depressurization on combustion, to ignition and flame spread. A list of pubfications/presentations based on experiments performed in the SFSF is included in the reference section. This facility consists of five main subsystems: combustion chamber, sample holders, gas flow system, imaging system, and the data acquisition/control system. Each of these subsystems will be reviewed in more detail. These subsystems provide the experiment operator with the ability to monitor and/or control numerous experimental parameters.

Goldmeer, Jeffrey S.↗

NASA NTRS2012

Modeling Climate Responses to Spectral Solar Forcing on Centennial and Decadal Time Scales

We report a series of experiments to explore clima~ responses to two types of solar spectral forcing on decadal and centennial time scales - one based on prior reconstructions, and another implied by recent observations from the SORCE (Solar Radiation and Climate Experiment) SIM (Spectral 1rradiance Monitor). We apply these forcings to the Goddard Institute for Space Studies (GISS) Global/Middle Atmosphere Model (GCMAM). that couples atmosphere with ocean, and has a model top near the mesopause, allowing us to examine the full response to the two solar forcing scenarios. We show different climate responses to the two solar forCing scenarios on decadal time scales and also trends on centennial time scales. Differences between solar maximum and solar minimum conditions are highlighted, including impacts of the time lagged reSponse of the lower atmosphere and ocean. This contrasts with studies that assume separate equilibrium conditions at solar maximum and minimum. We discuss model feedback mechanisms involved in the solar forced climate variations.

Wen, G.↗

NASA NTRS2015

Investigation of Asymmetric Thrust Detection with Demonstration in a Real-Time Simulation Testbed

The purpose of this effort is to develop, demonstrate, and evaluate three asymmetric thrust detection approaches to aid in the reduction of asymmetric thrust-induced aviation accidents. This paper presents the results from that effort and their evaluation in simulation studies, including those from a real-time flight simulation testbed. Asymmetric thrust is recognized as a contributing factor in several Propulsion System Malfunction plus Inappropriate Crew Response (PSM+ICR) aviation accidents. As an improvement over the state-of-the-art, providing annunciation of asymmetric thrust to alert the crew may hold safety benefits. For this, the reliable detection and confirmation of asymmetric thrust conditions is required. For this work, three asymmetric thrust detection methods are presented along with their results obtained through simulation studies. Representative asymmetric thrust conditions are modeled in simulation based on failure scenarios similar to those reported in aviation incident and accident descriptions. These simulated asymmetric thrust scenarios, combined with actual aircraft operational flight data, are then used to conduct a sensitivity study regarding the detection capabilities of the three methods. Additional evaluation results are presented based on pilot-in-the-loop simulation studies conducted in the NASA Glenn Research Center (GRC) flight simulation testbed. Data obtained from this flight simulation facility are used to further evaluate the effectiveness and accuracy of the asymmetric thrust detection approaches. Generally, the asymmetric thrust conditions are correctly detected and confirmed.

gas turbine engines↗

NASA NTRS2018

Harmonized Landsat/Sentinel-2 Products for Land Monitoring

The Harmonized Landsat-8 and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a seamless, harmonized surface reflectance record from the Operational Land Imager (OLI) and Multi-Spectral Instrument (MSI) aboard Landsat-8 and Sentinel-2 remote sensing satellites, respectively. The HLS products are based on a set of algorithms to obtain seamless products from both sensors (OLI and MSI): atmospheric correction, cloud and cloud-shadow masking, geographic co-registration and common gridding, bidirectional reflectance distribution function normalization and bandpass adjustment. As of version 1.3, the HLS v1.3 data set covers 9.12 million km2 and spans from first Landsat-8 data (2013) to present. HLS products provide near-daily surface reflectance information with a common geometric framework, and are suitable for a variety of agricultural and vegetation monitoring tasks, including analysis of crop type, condition, and phenology.

Masek, Jeffrey↗

NASA NTRS2022

Diagnostic classification of flash drought events reveals distinct classes of forcings and impacts

Recent years have seen growing appreciation that rapidly intensifying flash droughts are significant climate hazards with major economic and ecological impacts. This has motivated efforts to inventory, monitor, and forecast flash drought events. Here we consider the question of whether the term “flash drought” comprises multiple distinct classes of event, which would imply that understanding and forecasting flash droughts might require more than one framework. To do this, we first extend and evaluate a soil moisture volatility–based flash drought definition that we introduced in previous work and use it to inventory the onset dates and severity of flash droughts across the contiguous United States (CONUS) for the period 1979–2018. Using this inventory, we examine meteorological and land surface conditions associated with flash drought onset and recovery. These same meteorological and land surface conditions are then used to classify the flash droughts based on precursor conditions that may represent predictable drivers of the event. We find that distinct classes of flash drought can be diagnosed in the event inventory. Specifically, we describe three classes of flash drought: “dry and demanding” events for which antecedent evaporative demand is high and soil moisture is low, “evaporative” events with more modest antecedent evaporative demand and soil moisture anomalies, but positive antecedent evaporative anomalies, and “stealth” flash droughts, which are different from the other two classes in that precursor meteorological anomalies are modest relative to the other classes. The three classes exhibit somewhat different geographic and seasonal distributions. We conclude that soil moisture flash droughts are indeed a composite of distinct types of rapidly intensifying droughts, and that flash drought analyses and forecasts would benefit from approaches that recognize the existence of multiple phenomenological pathways.

Mahmoud Osman↗

DOE OSTI2026

Stochastic Thermo-Hydro Modeling and Neural Network Surrogate Development for Thermal Resource Assessment of the Galleries-to-Calories Geobattery

The Galleries-to-Calories Geobattery concept explores the use of abandoned coal mine workings for large-scale thermal energy transport and storage. The system involves injecting waste heat from a supercomputing facility into flooded mine galleries, where groundwater flow can store and transport thermal energy for potential recovery in downgradient district heating and cooling applications. To evaluate the feasibility and performance of the Geobattery under geological and operational uncertainty, we developed a suite of stochastic thermo-hydrological (TH) simulations using Monte Carlo sampling of key uncertain parameters (e.g., permeability, porosity, thermal conductivity, specific heat capacity) and operating conditions (e.g., injection rate, injection temperature). Results identified injection rate and temperature as the most influential parameters governing thermal front propagation, while the geometry of the room-and-pillar structure played a critical role in directing the extent and orientation of thermal advancement. Optimal combinations of material properties for maximizing heat recovery were also determined. To address the high computational cost of coupled-process stochastic modeling, we trained a neural network surrogate model on 24,000 physics-based realizations, achieving an R² > 0.99 and MAE < 0.1 for temperature predictions at monitoring locations. This surrogate enabled an additional 100,000 realizations for global sensitivity analysis and probabilistic thermal resource assessment. The integrated stochastic physics–surrogate modeling framework offers a computationally efficient tool for quantifying uncertainty, identifying key drivers, and informing early-stage design decisions for Geobattery systems.

15 - GEOTHERMAL ENERGY↗

DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine

03 NATURAL GAS↗