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Regional Oil and gas Aerial Methane Synthesis model (ROAMS) v2.0

The Regional Oil and gas Aerial Methane Synthesis model is a tool to convert the results of wide-area, source-resolved aerial methane remote sensing surveys of oil and natural gas infrastructure in a given region into methane emissions inventories (estimates of the magnitude and breakdown of methane emissions from the surveyed infrastructure). The tool leverages databases of source-resolved methane emissions detected in aerial surveys, aerial survey coverage information (which areas were measured and when), data summarizing surveyed oil and natural gas infrastructure and production (derived from third-party databases), as well as state-of-the-art mechanistic emissions simulation tools to characterize emissions too small for the aerial system to see. The regional methane emissions estimates produced by this tool are much more granular in both space and asset type than common satellite- or flux tower-based regional estimates. Unlike other tools for converting site-level measurements into regional emissions estimates, our unique geostatistical approach integrates aerially measured emissions with limited need for statistical extrapolation, which can be highly sensitive to modeler assumptions. As a result, ROAMS-based estimates of regional methane emissions from oil and gas activity are widely viewed as highly credible, as evidenced by the success of Dr. Sherwin's recent paper in Nature.

Sherwin, Evan [Lawrence Berkeley National Laborato↗

Regional Oil and gas Aerial Methane Synthesis model (Analytica) (ROAMS Analytica) v1.5.2

The Regional Oil and gas Aerial Methane Synthesis model (Analytica) is a tool to convert the results of wide-area, source-resolved aerial methane remote sensing surveys of oil and natural gas infrastructure in a given region into methane emissions inventories (estimates of the magnitude and breakdown of methane emissions from the surveyed infrastructure). This version is written in the Analytica programming language, and this version accompanies a correction in preparation for submission to Sherwin et al. 2024 (Nature). The tool leverages databases of source-resolved methane emissions detected in aerial surveys, aerial survey coverage information (which areas were measured and when), data summarizing surveyed oil and natural gas infrastructure and production (derived from third-party databases), as well as state-of-the-art mechanistic emissions simulation tools to characterize emissions too small for the aerial system to see. The regional methane emissions estimates produced by this tool are much more granular in both space and asset type than common satellite- or flux tower-based regional estimates. Unlike other tools for converting site-level measurements into regional emissions estimates, our unique geostatistical approach integrates aerially measured emissions with limited need for statistical extrapolation, which can be highly sensitive to modeler assumptions. As a result, ROAMS-based estimates of regional methane emissions from oil and gas activity are widely viewed as highly credible, as evidenced by the success of Dr. Sherwin's recent paper in Nature.

Sherwin, Evan [Lawrence Berkeley National Laborato↗

Mucilage produced by aerial roots hosts diazotrophs that provide nitrogen in Sorghum bicolor

Sorghum ( Sorghum bicolor ) is an important food, feed, and fodder crop worldwide and is gaining popularity as an energy crop due to its high potential for biomass production. Some sorghum accessions develop many aerial roots and produce an abundant carbohydrate-rich mucilage after rain. This aerial root mucilage is similar to that observed in landraces of maize ( Zea mays ) from southern Mexico, which have been previously shown to host diazotrophs. In this study, we characterized the aerial root development of several sorghum accessions and the impact of humidity on this trait. We conducted a microbiome study of the aerial root mucilage of maize and sorghum and isolated numerous diazotrophs from field sorghum mucilage. We observed that the prevailing phyla in the mucilage were Pseudomonadota, Bacteroidota, and Bacillota. However, bacterial abundances varied based on the genotype and the location. Using acetylene reduction, 15 N 2 gas feeding, and 15 N isotope dilution assays, we confirmed that these sorghum accessions can acquire about 40% of their nitrogen from the atmosphere through these associations on aerial roots. Nitrogen fixation in sorghum aerial root mucilage offers a promising avenue to reduce reliance on synthetic fertilizers and promote sustainable agricultural practices for food, feed, fodder, and bioenergy production.

Venado, Rafael E.↗

The use of color infrared aerial photography in determining salt marsh vegetation and delimiting man-made structures of Lynnhaven Bay, Virginia

Color infrared aerial photography was found to be superior to color aerial photography in an ecological study of Lynnhaven Bay, Virginia. The research was divided into three phases: (1) Determination of the feasibility of correlating color infrared aerial photography with saline wetland species composition and zonation patterns, (2) determination of the accuracy of the aerial interpretation and problems related to the aerial method used; and (3) comparison of developed with undeveloped areas along Lynnhaven Bay's shoreline. Wetland species composition and plant community zonation bands were compared with aerial infrared photography and resulted in a high degree of correlation. Problems existed with changing physical conditions; time of day, aircraft angle and sun angle, making it necessary to use several different characteristics in wetland species identification. The main characteristics used were known zonation patterns, textural signatures and color tones. Lynnhaven Bay's shoreline was 61.5 percent developed.

Holman, R. E., III↗

Measurements from an Aerial Vehicle: A New Tool for Planetary Exploration

Aerial vehicles fill a unique planetary science measurement gap, that of regional-scale, near-surface observation, while providing a fresh perspective for potential discovery. Aerial vehicles used in planetary exploration bridge the scale and resolution measurement gaps between orbiters (global perspective with limited spatial resolution) and landers (local perspective with high spatial resolution) thus complementing and extending orbital and landed measurements. Planetary aerial vehicles can also survey scientifically interesting terrain that is inaccessible or hazardous to landed missions. The use of aerial assets for performing observations on Mars, Titan, or Venus will enable direct measurements and direct follow-ons to recent discoveries. Aerial vehicles can be used for remote sensing of the interior, surface and atmosphere of Mars, Venus and Titan. Types of aerial vehicles considered are airplane "heavier than air" and airships and balloons "lighter than air". Interdependencies between the science measurements, science goals and objectives, and platform implementation illustrate how the proper balance of science, engineering, and cost, can be achieved to allow for a successful mission. Classification of measurement types along with how those measurements resolve science questions and how these instruments are accommodated within the mission context are discussed.

Wright, Henry S.↗

Aerial Explorers

This paper presents recent results from a mission architecture study of planetary aerial explorers. In this study, several mission scenarios were developed in simulation and evaluated on success in meeting mission goals. This aerial explorer mission architecture study is unique in comparison with previous Mars airplane research activities. The study examines how aerial vehicles can find and gain access to otherwise inaccessible terrain features of interest. The aerial explorer also engages in a high-level of (indirect) surface interaction, despite not typically being able to takeoff and land or to engage in multiple flights/sorties. To achieve this goal, a new mission paradigm is proposed: aerial explorers should be considered as an additional element in the overall Entry, Descent, Landing System (EDLS) process. Further, aerial vehicles should be considered primarily as carrier/utility platforms whose purpose is to deliver air-deployed sensors and robotic devices, or symbiotes, to those high-value terrain features of interest.

Young, Larry A.↗

Venus Aerial Platforms and Engineering and Scientific Modeling Needs

NASA’s Planetary Science Division is performing an assessment of the state of technology in aerial platforms for exploration of Venus. A key factor in the design of aerial platforms is knowledge of the Venus environment. Modeling the Venus environment, which is the subject of this workshop, is needed for the design of robust aerial platforms that can carry out their missions successfully. The purpose of this paper is to enumerate the kinds of models that are important for both engineering and scientific aspects of the design of an aerial platform mission. The first meeting of the NASA Aerial Platforms study team took place from May 30 to June 2, 2017 and defined the science that can be performed by aerial platforms. A second study meeting is planned for late November 2017. This paper focuses on the current status.

Thompson, T. W.↗

Aerial Vehicle Routing and Scheduling for UAS Traffic Management: A Monte Carlo Tree Search Approach

Numerous unmanned aircraft systems operating at low altitudes to deliver goods and services may one day become ubiquitous in our cities. In the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) framework, such a concept is envisioned, where aerial vehicles operate beyond visual line of sight (BVLOS) within specifically reserved and time stamped “corridors” in the airspace. For example, these corridors or operational intent volumes can connect an aerial vehicle’s origin site to its destination site for package delivery operations. There may also be more than one corridor available for an aerial vehicle to choose from and often different corridors may intersect with one another. Thus, it is imperative to ensure flight trajectories belonging to different aerial vehicles are not in conflict. Per the UTM CONOPs, we assume that a vehicle almost always stays inside its corridor or operational volume. This work provides a framework for strategic deconfliction of UTM or package delivery drones, where we schedule the departure time of all vehicles subject to various temporal constraints (including the corridor deconfliction at the intersections). We present the “multi-route weighted package delivery problem” which serves as an exemplifying model for strategic deconfliction in UTM. In the multi-route weighted package delivery problem, a graph network is given which consists of a set of depots (source) and drop-off (destination) nodes, with multiple routes (defined as a sequence of waypoints) connecting the depots to drop-off nodes. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is for a known set of aerial vehicles to depart from the depots, choose a route and take off time, while avoiding conflicts with other aerial vehicles, and minimizing both risk and distance traveled. We provide a mixed integer linear programming (MILP) formulation of the problem, as well as a heuristic solution based on Monte Carlo Tree Search (MCTS) – a method used in game theory and artificial intelligence – to overcome limitations inherent to optimal solvers. Computational results show the advantages of using MCTS over the MILP formulation; the former can provide a sub-optimal solution quickly, and may sometimes even reach an optimal solution, whereas the latter may not even produce a solution in reasonable time. Furthermore, results from both the MILP formulation and MCTS methods were validated using a preliminary agent-based simulator implementing the UTM concept of operations. Thus, the MCTS method can be seen as a scalable solution to the complex multi-route weighted package delivery problem and may possibly be extended to similar complex optimization problems.

Kenny Chour↗

Spatial Feature Evaluation for Aerial Scene Analysis

High-resolution aerial images are becoming more readily available, which drives the demand for robust, intelligent and efficient systems to process increasingly large amounts of image data. However, automated image interpretation still remains a challenging problem. Robust techniques to extract and represent features to uniquely characterize various aerial scene categories is key for automated image analysis. In this paper we examined the role of spatial features to uniquely characterize various aerial scene categories. We studied low-level features such as colors, edge orientations, and textures, and examined their local spatial arrangements. We computed correlograms representing the spatial correlation of features at various distances, then measured the distance between correlograms to identify similar scenes. We evaluated the proposed technique on several aerial image databases containing challenging aerial scene categories. We report detailed evaluation of various low-level features by quantitatively measuring accuracy and parameter sensitivity. To demonstrate the feature performance, we present a simple query-based aerial scene retrieval system.

Swearingen, Thomas S↗

International-Aerial Measuring System (I-AMS) Training Program

Since the Fukushima reactor accident in 2011, there has been an increased interest worldwide in developing national capabilities to rapidly map and assess ground contamination resulting from nuclear reactor accidents. The capability to rapidly measure the size of the contaminated area, determine the activity level, and identify the radionuclides can aid emergency managers and decision makers in providing timely protective action recommendations to the public and first responders. The development of an aerial detection capability requires interagency coordination to assemble the radiation experts, detection system operators, and aviation aircrews to conduct the aerial measurements, analyze and interpret the data, and provide technical assessments. The Office of International Emergency Management and Cooperation (IEMC) at the U.S. Department of Energy, National Nuclear Security Administration (DOE/NNSA) sponsors an International - Aerial Measuring System (I-AMS) training program for partner nations to develop and enhance their response to radiological emergencies. An initial series of courses can be conducted in the host country to assist in developing an aerial detection capability. As the capability develops and expands, additional experience can be gained through advanced courses with the opportunity to conduct aerial missions over a broad range of radiation environments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Strikingly high amount of tricin-lignin observed from vanilla (Vanilla planifolia) aerial roots

Lignin has attracted tremendous interest as a renewable resource for biofuels, biomaterials, and chemicals especially in the era of bio-based refineries. The structural studies of lignin play an essential role in both understanding the nature and biosynthesis of these polymers and optimizing their valorization values. In this study, we have investigated the structures of lignin from different tissues—aerial roots, nodes, internodes, and seeds, from vanilla (Vanilla planifolia) by using gel permeation chromatography (GPC), heteronuclear single-quantum coherence (HSQC) nuclear magnetic resonance (NMR), and 31P NMR. An unusual tricin-lignin was observed in the aerial roots of vanilla with an strikingly high level of tricin unit, whereas the lignin from the nodes and internodes displayed traditional S/G type lignin with only 4–10% tricin abundance. The aerial roots lignin is primarily composed of β-O-4' alkyl-aryl ether substructures (96% of linkages) in comparison to 65 and 73% in the nodes and internodes lignin, respectively. Additionally, thioacidolysis quantification results showed that lignin from aerial roots has 29.1 mg g -1 tricin, about 3- to 5-fold higher than the lignins isolated from nodes (10.1 mg g -1 ) and internodes (6.9 mg g -1 ). This communication of a particularly high level of tricin-lignin in vanilla plant has important impacts including: (1) the presence of the high amount of tricin as part of lignin from aerial roots could play a vital role for the valorization of lignin, even tricin itself, as a feedstock for value-added chemicals and commodities; and (2) it could open new ways to scientists to design and engineer the structure of tricin-lignin, or lignin in general, to confer plants with new or improved properties due to the plasticity of lignification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large reductions in Permian Basin methane intensity shown in multi-year comparison of aerially-visible methane emissions

Spanning the US states of Texas and New Mexico, the Permian Basin has been a hotspot of methane emissions from oil and natural gas activity 1–4, although studies disagree over the magnitude of these emissions. The most comprehensive measurement campaigns published were conducted in 2019 1–5 .There have been large changes in the energy industry since then, including in the prices of oil and gas, both state and federal regulatory environments, investor and activist pressure over methane emissions, and the adoption of new technologies and policies by energy operators. Understanding how any or all of these might influence methane emissions is important for policy makers, oil and gas operators, and other stakeholders. We characterize the time evolution of Permian Basin methane emissions using a series of comprehensive aerial surveys conducted every year from 2020-2023 and compare them to the 2019 results cited above. To maintain comparability, all the data sets are from surveys using Insight M point source methane sensing technology. The scope of these surveys expanded over time: from 33-46% of wells, oil production, and gas production in 2020 to 60-65% in 2021, to 84% of wells and over 90% of both oil and gas production in 2023. These surveys by Insight M also include hundreds of gas processing plants and compressor stations as well as 1000s of km of gathering and transmission pipelines. Considering only the aerially detected portion of emissions (typically the majority of the total in such surveys 4), we find reductions of more than 70% in methane emissions intensity compared to the 2019 New Mexico-only Insight M survey, with variation depending on the year 3,4. Notably, although sources below 100 kg/hr contributed less than 10% of aerially measured emissions the 2019 New Mexico survey 3, these smaller sources constitute a larger proportion of total aerially measured emissions (although not the majority) in 2020-2023. Production facilities and gathering pipelines are responsible for the larges shares of total emissions, followed by compressor stations and gas processing plants. Permian methane emissions were also measured in a comprehensive 2019 Permian-wide survey by the Carbon Mapper team 2. That analysis led to a lower total emissions estimate at the time 4. These new Insight M-based emission rates are still roughly 30-70% lower than the aerially measured portion of the 2019 Carbon Mapper-based estimates 4. Further work is needed to harmonize these surveys in space and time to create the most intercomparable numbers possible 5. Additional analysis is needed to compare our findings to the more spatially constrained 2020, 2021, and 2023 Carbon Mapper surveys in the Permian 4,6. The evidence is strong from these two survey teams that emissions intensity has declined significantly since 2019. Reasons for this trend are currently unclear but point to possible success of emissions control programs. Future work investigating frequency, source, and operator-specific intensities could provide insights into the causes of this promising trend.

methane, oil and gas, data science, remote sensing↗

Aerial Neutron Detection: Neutron Signatures for Nonproliferation and Emergency Response Applications

From 2007 to the present, the Remote Sensing Laboratory has been conducting a series of studies designed to expand our fundamental understanding of aerial neutron detection with the goal of designing an enhanced sensitivity detection system for long range neutron detection. Over 35 hours of aerial measurements in a helicopter were conducted for a variety of neutron emitters such as neutron point sources, a commercial nuclear power reactor, nuclear reactor spent fuel in dry cask storage, depleted uranium hexafluoride and depleted uranium metal. The goals of the project were to increase the detection sensitivity of our instruments such that a 5.4 × 104 neutron/second source could be detected at 100 feet above ground level at a speed of 70 knots and to enhance the long-range detection sensitivity for larger neutron sources, i.e., detection ranges above 1000 feet. In order to increase the sensitivity of aerial neutron detection instruments, it is important to understand the dynamics of the neutron background as a function of altitude. For aerial neutron detection, studies have shown that the neutron background primarily originates from above the aircraft, being produced in the upper atmosphere by galactic cosmic-ray interactions with air molecules. These interactions produce energetic neutrons and charged particles that cascade to the earth’s surface, producing additional neutrons in secondary collisions. Hence, the neutron background increases as a function of altitude which is an impediment to long-range neutron detection. In order to increase the sensitivity for long range detection, it is necessary to maintain a low neutron background as a function of altitude. Initial investigations show the variation in the neutron background can be decreased with the application of a cosmic-ray shield. The results of the studies along with a representative data set are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Autonomous Aerial Power Plant Inspection in GPS-denied Environments

Inspection of coal-fired power plants is frequently dangerous, includes difficult places to reach, and can turn expensive due to the downtimes and cost of inspection crew. Robotic systems have shown capabilities to address some of these issues, but most of the current robotic inspection technology in power plants is designed for specific components. Conversely, recent advances in machine vision have empowered aerial platforms for long-range, remotely-controlled, GPS-based inspections of industrial plants. This capability has led to wide spread utilization of aerial robots (commonly termed Drones, UVS or UAS) platforms for inspection in less challenging environments where both collision avoidance, and GPS reception are not significant issues. The challenge in adapting airborne technology for power plant inspection lies in internal structures and the complex network of piping, and distribution systems, which impose significant risks for collision and can hinder the reception and transmission of GPS signals. The current state of the art in aerial inspection technology within the energy sector is controlled via radio control, and utilizes GPS-based navigation, for inspection of large-scale plants such as offshore platforms and wind turbine parks. Nevertheless, close-range and autonomous inspection in the GPS-denied environments of power plants has not yet been achieved, as it requires precise guidance and navigation with real-time situational awareness and obstacle avoidance capabilities. This endeavor introduced the use of rotary wing flying robots, due to their station keeping and vertical take-off capabilities for power plant components inspection. To enable close quarter inspection two methods were used. One method uses the 3D CAD (Three-dimensional Computer-Aided Design) model of the asset to inspect to generate the UAV’s inspection path. To acquire, analyze and process the 3D model, first, the STL file is produced to obtain surface points and vectors normal to the surface. Later, by introducing other variables such as wall offset and a controlled trajectory between each outline and each subsequent layer, the flight path is generated. The proposed framework will generate a path that will pass as close as desired from the surface and navigate in intricate environments. A second method, use advanced manufacturing techniques such as CNC (Computer Numerical Control) and additive manufacturing. Once the inspection flight path is obtained, vision-based navigation systems are employed to have the UAV autonomously tracking the provided trajectory. Finally, Artificial Intelligence-enabled developments are in charge of detecting cracks and corrosion in structural components of power plants. The proposed methods are validated in simulations, laboratory and industrial setups, where it is shown that the developed systems acting together enable close-quarter autonomous aerial inspection and mapping in power plant assets. The system can be further improved by adding more sensors to navigate in different GPS-denied environments, with non-homogeneous lighting conditions, dust and in general situations where vision-based systems may fail.

01 COAL, LIGNITE, AND PEAT↗

Urban Aerial Mobility Networks using Amphibious Vertical Takeoff and Landing Vehicles

This study considers novel urban aerial mobility (UAM) networks that address some of the key operator and community acceptance challenges inherent in proposed UAM operations. This paper seeks to examine three possible approaches to improve operator and community acceptance – specifically targeting cost, safety, and noise. First, the conceptual design space will be examined for VTOL amphibious vehicle technologies, including the implications of onwater versus in-flight time/speed. Second, the implications of minimizing community overflights by flying over-water will be examined. Third, the implications of the partial use of onwater, or near-shore/littoral, vertiports on UAM network performance will be examined. This study considers an alternate design trade space for urban aerial mobility systems. A large number of cities in the United States are located near or surround large bodies of water. Many of these same cities are considered to be candidates for metropolitan aerial transportation systems so as to moderate the impact of urban ground-transportation congestion. This paper will expand discussion and study of notional amphibious VTOL vehicles. There is nothing particularly new with regards to helicopters with amphibious takeoff and landing capability. For example, light rotorcraft have been outfitted with pontoons since the 1950s. Larger utility helicopters – used for carrying offshore oil-rig crew – have been designed, with varying degrees of success, to emergency land in rough waters in case of onboard mechanical system failures. The unique difference for the proposed amphibious UAM vehicles, as compared to these earlier amphibious rotorcraft, is that water operation is the norm rather than the exception and that, further, the water-born operation (and design) of such vehicles can be optimized to yield significant economic and operational benefits over solely UAM land-based stations and operations. Various different amphibious UAM networks will be discussed. A first-order set of analyses – employing novel mission metrics – is presented in this paper that will examine the operational performance of these amphibious networks. In particular, amphibious operations might address critical safety and community acceptance issues. An examination of the aerodynamic and hydrodynamic characteristics of amphibious VTOL UAM vehicles will be presented in this paper. One possible conceptual design for an amphibious UAM vehicle is a hybrid synchropter/hydroplane vehicle. As interest in urban aerial mobility grows, it is worthwhile to consider whether or not amphibious vertical takeoff and landing vehicles can play an important role in providing such mobility.

Urban Aerial Mobility↗

The Future of Rotorcraft and other Aerial Vehicles for Mars Exploration

The Ingenuity Mars Helicopter is a technology demonstrator. The hope is that Ingenuity will one day lead to future generations of ever-more capable rotorcraft and other aerial vehicles for Mars exploration and other planetary science missions. This paper builds upon nearly twenty-four years of Mars rotorcraft and planetary aerial vehicle work at NASA Ames Research Center. It is posited that a spectrum of different Mars aerial vehicle mission concepts and capabilities could be developed over the next couple of decades – all of which are now potentially enabled by Ingenuity. A series of technology challenges or problems are also detailed in this paper. These problems are presented as an aid in helping establish a nascent planetary rotorcraft or planetary aerial vehicle research community as well as, maybe, helping realize some of the vehicle/mission concepts discussed in the paper.

Rotorcraft↗

Aerial and Processed Model Data Representing As-built Conditions in Coastal Port Arthur, Texas in May 2025

This dataset was collected by the Co-Design Team of the Southeast Texas Urban Integrated Field Lab, a research initiative led by the University of Texas at Austin and funded by the U.S. Department of Energy. The broader project focuses on developing climate-resilient design solutions for the Beaumont–Port Arthur region, with more information available at www.setx-uifl.org. Our team conducted aerial surveys of the Port Arthur coastal neighborhood in May 2025, before the start of construction scheduled for Summer 2026. These pre-construction datasets are designed to facilitate comparative analyses, including pre- and post-construction assessments and simulated inundation scenario evaluations. Aerial images were captured using DroneDeploy autonomous flight systems, with imagery processed through the DroneDeploy engine. All original aerial photographs are provided in JPG format and organized in zipped folders by area. The processed data package includes: 3D surface models Orthomosaics Geospatial and topographic mappings Point clouds For guidance on file contents, structure, and recommended usage, please refer to the included README file.

2D mapping↗

Author Correction: US oil and gas system emissions from nearly one million aerial site measurements

Correction to: Naturehttps://doi.org/10.1038/s41586-024-07117-5 Published online 13 March 2024 In the version of the article initially published, several errors were present and have been corrected in the HTML and PDF versions of the article and Supplementary Information. The main results, conclusions, and our interpretations of the data remain unchanged. See the new Supplementary Information Section S15 for a more detailed description of the errors corrected and the resulting effects on the analysis. Data processing and methods corrections Overflight count correction: We previously used pre-computed source coverage data for some Carbon Mapper campaigns that was computed differently than was required for our analysis. We have re-computed Carbon Mapper source coverage based on flightline polygons and source coordinates. Transition point computation, well sites: The updated version now correctly compares the cumulative emissions distribution of simulated well site emissions with that of aerially detected sources (rather than plumes) when computing the transition point. Transition point computation, midstream: Additionally, the transition point calculation has been corrected to exclude aerially detected midstream emissions below the transition point, which was previously leading to double counting of these emissions. This error was not present for upstream (well site) emissions. Calculation errors Unit error: We corrected a specific unit conversion error affecting well site emissions in the Kairos Fort Worth dataset. Across all datasets, we also correct the conversion factor for converting from standard volume to mass for midstream emissions. Sorting error: We correct code that was applying incorrect sorting when computing correction factors to account for partial detection at well sites. Small typographical corrections were made in Fig. 1b and SI Section S4.1. Data processing and methods corrections Overflight count correction: We previously used pre-computed source coverage data for some Carbon Mapper campaigns that was computed differently than was required for our analysis. We have re-computed Carbon Mapper source coverage based on flightline polygons and source coordinates. Transition point computation, well sites: The updated version now correctly compares the cumulative emissions distribution of simulated well site emissions with that of aerially detected sources (rather than plumes) when computing the transition point. Transition point computation, midstream: Additionally, the transition point calculation has been corrected to exclude aerially detected midstream emissions below the transition point, which was previously leading to double counting of these emissions. This error was not present for upstream (well site) emissions. Calculation errors Unit error: We corrected a specific unit conversion error affecting well site emissions in the Kairos Fort Worth dataset. Across all datasets, we also correct the conversion factor for converting from standard volume to mass for midstream emissions. Sorting error: We correct code that was applying incorrect sorting when computing correction factors to account for partial detection at well sites. Small typographical corrections were made in Fig. 1b and SI Section S4.1. The following practices may help researchers conducting similar analyses avoid making similar errors: 1, Clear, accessible documentation explaining the interpretation of all columns in data input tables and all internal variables within the model, 2, Simple cross-check calculations computed before and after unit conversions.

Sherwin, Evan D↗