Publications

Assessing the Potential Impact of Fugitive Methane Emissions on Offshore Platform Safety

One of the biggest risks to safety on offshore platform safety is the ignition of high pressure natural gas streams. Currently, the size and number of fugitive emissions on offshore platforms is unknown and methods used to detect fugitives have significant shortcomings. To investigate the frequency, size and potential impact of fugitives, a data collection exercise was conducted using incidents reported, leak survey data and independent measurements. The size and number of fugitives on offshore facilities were simulated to investigate likely areas of safety concern. Incident reports indicate in 2021 there were 113 reports of gas leaks on 1119 offshore facilities suggesting 0.02 fugitives per Type 1 facility (older, shallow water platforms) and 0.31 fugitives per Type 2 facility (larger deeper-water facilities). Leak survey data report 12 fugitives per Type 1 facility (average emission 0.6 kg CH4 h-1 leak-1) and 15 fugitives per Type 2 facility (average emission 1.5 kg CH4 h-1 leak-1). Reconciliation of direct measurements with a bottom-up model suggests that the number of fugitive emissions generated from the leak report data is an underestimate for Type 1 platforms (44 fugitives facility-1; average emission 0.6 kg CH4 h-1 leak-1) and in general agreement for the Type 2 platforms (15 fugitives facility-1; average emission 1.5 kg CH4 h-1 leak-1). Analysis of the fugitive emission rates on an offshore platform suggests that gas will not collect to explosive concentration if any air movement is present (> 0.36 mph), however, large volumes of air (~600 m3) near representative leaks on the working deck could become explosive in hour-long zero-wind conditions. We suggest that wearable technology could be employed to indicate gas build up, safety regulations amended to consider low-wind conditions and real-world experiments are conducted to test assumptions of air mixing on the working deck.

Point Sensor Networks Struggle to Detect and Quantify Short Controlled Releases at Oil and Gas Sites

This study evaluated multiple commercially available continuous monitoring (CM) point sensor network (PSN) solutions under single-blind controlled release testing conducted at operational upstream and midstream oil and natural gas (O&G) sites. During releases, PSNs reported site-level emission rate estimates of 0 kg/h between 38 and 86% of the time. When non-zero site-level emission rate estimates were provided, no linear correlation between the release rate and the reported emission rate estimate was observed. The average, aggregated across all PSN solutions during releases, shows 5% of the mixing ratio readings at downwind sensors were greater than the site’s baseline plus two standard deviations. Four of seven total PSN solutions tested during this field campaign provided site-level emission rate estimates with the site average relative error ranging from −100% to 24% for solution D, −100% to −43% for solution E, −25% for solution F (solution F was only at one site), and −99% to 430% for solution G, with an overall average of −29% across all sites and solutions. Of all the individual site-level emission rate estimates, only 11% were within ±2.5 kg/h of the study team’s best estimate of site-level emissions at the time of the releases.

Clearing the Air: Toward a Definition of Leak Detection and Quantification Methods

Supplementary material to "Measurements of methane emissions from natural gas gathering facilities and processing plants: measurement methods"

Electric Energy Management in the Smart Home: Perspectives on Enabling Technologies and Consumer Behavior

Smart homes hold the potential for increasing energy efficiency, decreasing costs of energy use, decreasing the carbon footprint by including renewable resources, and transforming the role of the occupant. At the crux of the smart home is an efficient electric energy management system that is enabled by emerging technologies in the electricity grid and consumer electronics. This paper presents a discussion of the state of the art in electricity management in smart homes, the various enabling technologies that will accelerate this concept, and topics around consumer behavior with respect to energy usage.

Overcoming barriers to direct current power: Lessons learned from four commercial building case studies

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 (WATCH4ERS) 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 WATCH4ERS unit, report initial sensor responses, and describe future research goals. Meanwhile, future work will use data gathered by multiple WATCH4ERS 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.

Characterizing Tracer Flux Ratio Methods for Methane Emission Quantification Using Small Unmanned Aerial System

Accurate methane emission estimates are essential for climate policy, yet current field methods often struggle with spatial constraints and source complexity. Ground-based mobile approaches frequently miss key plume features, introducing bias and uncertainty in emission rate estimates. This study addresses these limitations by using small unmanned aerial systems equipped with precision gas sensors to measure methane alongside co-released tracers. We tested whether arc-shaped flight paths and alternative ratio estimation methods could improve the accuracy of tracer-based emission quantification under real-world constraints. Controlled releases using ethane and nitrous oxide tracers showed that (1) arc flights provided stronger plume capture and higher correlation between methane and tracer concentrations than traditional flight paths; (2) the cumulative sum method yielded the lowest relative error (as low as 3.3%) under ideal mixing conditions; and (3) the arc flight pattern yielded the lowest relative error and uncertainty across all experimental configurations, demonstrating its robustness for quantifying methane emissions from downwind plume measurements. These findings demonstrate a practical and scalable approach to reducing uncertainty in methane quantification. The method is well-suited for challenging environments and lays the groundwork for future applications at the facility scale.

Flow and Transport of Methane from Leaking Underground Pipelines: Effects of Soil Surface Conditions and Implications for Natural Gas Leak Classification

Reducing methane (CH4) emissions from natural gas (NG) pipeline leaks is crucial to minimize global warming while also providing key safety benefits to communities. What is not well understood about pipeline leak scenarios is the impact of different soil surface conditions on the belowground leak transport behavior and subsequently the NG leak classification. In this study, we conducted a series of controlled leak experiments, varying based on the surface conditions including snow, moist soil layers, asphalt, and grass. Data indicated that temporary rain and snow surface cover conditions result in CH4 concentrations extending 3 times further than the equivalent leak scenario under dry soil conditions, resulting in levels that pose heightened environmental and safety risks. Furthermore, after leak termination, CH4 trapped under snow, moist soil, and asphalt surface conditions persisted for up to ∼12 days, with 5–15% CH4 (v/v) conditions persisting underground for 7.5 days. Even after leak termination, NG continued to migrate laterally away from the leak source, extending the plume boundary by 2–4%. While efforts to study a wider range of environmental conditions are underway, the findings of this study provide crucial insight into identifying and prioritizing leaks from the perspectives of both safety and the environment.

Performance Characterization of a Wind Turbine Simulator for Grid Connected and Islanded Wind Turbine Operation

To better understand the effect of significant wind power production on distributed electrical networks, a Wind Turbine Simulator (WTS) was incorporated into the Grid Simulation Laboratory (GSL) at Colorado State University. This paper discusses the development of the engine controls, gain tuning and response matching to field measurements of wind turbines. Response was characterized while connected to the transmission grid, similar to the field information, using a series of transient events gleaned from field information. Transients caused by breaker events, which emulate connecting or disconnecting the individual wind turbines, were also considered. While overall correlation between commanded and actual power output was strong, several limitations were identified and are described.

Mitigating Communication Delays in Remotely Connected Hardware-in-the-Loop Experiments

This paper introduces a potential approach for mitigating the effects of communication delays between multiple, closed-loop hardware-in-the-loop experiments which are virtually connected, yet physically separated. The approach consists of an analytical procedure for the compensation of communication delays, along with the supporting computational and communication infrastructure. The control design leverages tools for the design of observers for the compensation of measurement errors in systems with time-varying delays. The proposed methodology is validated through computer simulation and hardware experimentation connecting hardware-in-the-loop experiments conducted between laboratories separated by a distance of over 100 km.

The effect of communication architecture on the availability, reliability, and economics of plug-in hybrid electric vehicle-to-grid ancillary services

Performance of continuous emission monitoring solutions under single-blind controlled testing protocol.

Continuous emission monitoring (CM) solutions promise to detect large fugitive methane emissions in natural gas infrastructure sooner than traditional leak surveys, and quantification by CM solutions has been proposed as the foundation of measurement-based inventories. This study performed single-blind testing at a controlled release facility (release from 0.4 to 6400 g CH4/h) replicating conditions that were challenging but less complex than typical field conditions. Eleven solutions were tested, including point sensor networks and scanning/imaging solutions. Results indicated 90% probability of detection (POD) of 3-30 kg CH4/h; 6 of 11 solutions achieved POD >50%. False positive rates ranged from 0 to 79%. Six solutions estimated emission rates. For release rate of 0.1-1 kg/h, the solutions' mean relative errors ranged from -44% to +586% with single estimates between -97% and +2077%, with 4 solutions' upper uncertainty exceeding +900%. Above 1 kg/h, mean relative error was -40% to +93%, with two solutions within 20%, and single-estimate relative errors from -82% to +448%. The large variability in performance between CM solutions, coupled with highly uncertain detection, detection limit, and quantification results, indicate that the performance of individual CM solutions should be well understood before relying on results for internal emissions mitigation programs or regulatory reporting.

Methane Emissions from Abandoned Oil and Gas Wells in Colorado

Recent studies indicate emission factors used to generate bottom-up methane inventories may have considerable regional variability. The US’s Environmental Protection Agency’s emission factors for plugged and unplugged abandoned oil and gas wells are largely based on measurement of historic wells and estimated at 0.4 g and 31 g CH4 well-1 h-1, respectively. To investigate if these are representative of wells more recently abandoned, methane emissions were measured from 128 plugged and 206 unplugged abandoned wells in Colorado, finding the first super-emitting abandoned well (76 kg CH4 well-1 h-1) and average emissions of 0 and 586 g CH4 well-1 h-1, respectively. Combining these with other states’ measurements, we update the US emission factors to 1 and 198 g CH4 well-1 h-1, respectively. Correspondingly, annual methane emissions from the 3.4 million abandoned wells in the US are estimated at between 2.6 Tg, following current methodology, and 1.1 Tg, where emissions are disaggregated for well-type. In conclusion, this study identifies a new abandoned well-type, recently-producing orphaned, that contributes 74% to the total abandoned wells methane emissions. Including this new well-type in the bottom-up inventory suggests abandoned well emissions equates to between 22 and 49% of total emissions from US active oil and gas production operations.

State-of-the-Art Leak Detection Methods for Underground Natural Gas Pipelines Introduction

Endpoint Use Efficiency Comparison for AC and DC Power Distribution in Commercial Buildings

Advances in power electronics and their use in Miscellaneous Electric Loads (MELs) in buildings have resulted in increased interest in using low-voltage direct current (DC) power distribution as a replacement for the standard alternating current (AC) power distribution in buildings. Both systems require an endpoint converter to convert the distribution system voltage to the MELs voltage requirements. This study focused on the efficiency of these endpoint converters by testing pairs of AC/DC and DC/DC power converters powering the same load profile. In contrast to prior studies, which estimated losses based on data sheet efficiency and rated loads, in this study, we used part load data derived from real-world time-series load measurements of MELs and experimentally characterized efficiency curves for all converters. The measurements performed for this study showed no systematic efficiency advantage for commercially available DC/DC endpoint converters relative to comparable, commercially available AC/DC endpoint converters. For the eight appliances analyzed with the pair of converters tested, in 50%, the weighted energy efficiency of the DC/DC converter was higher, while, for the other 50%, the AC/DC converter was. Additionally, the measurements indicated that the common assumption of using either data sheet efficiency values or efficiency at full load may result in substantial mis-estimates of the system efficiency.

Uncertainty Quantification of Methods Used to Measure Methane Emissions of 1 g CH4 h−1

The recent interest in measuring methane (CH4) emissions from abandoned oil and gas wells has resulted in five methods being typically used. In line with the US Federal Orphaned Wells Program’s (FOWP) guidelines and the American Carbon Registry’s (ACR) protocols, quantification methods must be able to measure minimum emissions of 1 g of CH4 h−1 to within ±20%. To investigate if the methods meet the required standard, dynamic chambers, a Hi-Flow (HF) sampler, and a Gaussian plume (GP)-based approach were all used to quantify a controlled emission (Qav; g h−1) of 1 g of CH4 h−1. After triplicate experiments, the average accuracy (Ar; %) and the upper (Uu; %) and lower (Ul; %) uncertainty bounds of all methods were calculated. Two dynamic chambers were used, one following the ACR guidelines, and a second “mobile” chamber made from lightweight materials that could be constructed around a source of emission on a well head. The average emission calculated from the measurements made using the dynamic chamber (Qav = 1.01 g CH4 h−1, Ar = +0.9%), the mobile chamber (Qav = 0.99 g CH4 h−1, Ar = −1.4%), the GP approach (Qav = 0.97 g CH4 h−1, Ar = −2.6%), and the HF sampler (Qav = 1.02 g CH4 h−1, Ar = +2.2%) were all within ±3% of 1 g of CH4 h−1 and met the requirements of the FOWP and ACR protocols. The results also suggest that the individual measurements made using the dynamic chamber can quantify emissions of 1 g of CH4 h−1 to within ±6% irrespective of the design (material, number of parts, geometrical shape, and hose length), and changes to the construction or material specifications as defined via ACR make no discernible difference to the quantification uncertainty. Our tests show that a collapsible chamber can be easily constructed around the emission source on an abandoned well and be used to quantify emissions from abandoned wells in remote areas. To our knowledge, this is the first time that methods for measuring the CH4 emissions of 1 g of CH4 h−1 have been quantitively assessed against a known reference source and against each other.

Deployment-invariant probability of detection characterization for aerial LiDAR methane detection

Accurate detection sensitivity characterization of remote methane monitoring technologies is critical for designing, implementing, and auditing effective emissions monitoring and mitigation programs. Several research groups have developed test methods based on single/double-blind controlled release protocols and regression-based data analysis techniques to create probability of detection (PoD) models for characterizing remote sensor detection sensitivities. The previously created methods and models account for some of the important factors that affect detection sensitivity, such as wind speed, and in the case of Conrad et al. flight altitude. However, these models do not account for other important factors, such as terrain albedo, variation in individual sensor performance, or spatial density of the remote sensing measurements. In this paper, we build on the work of Conrad et al. by introducing a gas concentration noise (GCN) model for Gas Mapping LiDAR aerial methane detection technology that, when combined with wind speed at the emission location, accounts for all significant sensor and environmental parameters that affect detection sensitivity for scenarios involving an isolated emission source resulting in a single methane plume. We incorporate the GCN model into Conrad et al.’s PoD model and apply it to several sets of controlled release data acquired across widely varying deployment and environmental conditions to develop PoD models for Bridger Photonics Inc.’s first- and second-generation (GML 2.0) Gas Mapping LiDAR sensors. Finally, we compare controlled release data acquired by GML 2.0 in different geographic regions and terrain cover types, in different wind conditions, deployed on different aircraft types, and with different flight parameters. Results show that the GML 2.0 PoD model remains valid regardless of the location or conditions under which the sensors are deployed, and the aircraft and flight parameters used for deployment. Based on PoD measurements in 12 production basins across North America, the average 90% PoD emission rate for sites measured by GML 2.0 in 2023 was 1.27 kg/h.