Daniel Zimmerle

Measurements of Methane Emissions from Natural Gas Gathering Facilities and Processing Plants: Measurement Results

Facility-level methane emissions were measured at 114 gathering facilities and 16 processing plants in the United States natural gas system. At gathering facilities, the measured methane emission rates ranged from 0.7 to 700 kg per hour (kg/h) (0.6 to 600 standard cubic feet per minute (scfm)). Normalized emissions (as a % of total methane throughput) were less than 1% for 85 gathering facilities and 19 had normalized emissions less than 0.1%. The range of methane emissions rates for processing plants was 3 to 600 kg/h (3 to 524 scfm), corresponding to normalized methane emissions rates <1% in all cases. The distributions of methane emissions, particularly for gathering facilities, are skewed. For example, 30% of gathering facilities contribute 80% of the total emissions. Normalized emissions rates are negatively correlated with facility throughput. The variation in methane emissions also appears driven by differences between inlet and outlet pressure, as well as venting and leaking equipment. Substantial venting from liquids storage tanks was observed at 20% of gathering facilities. Emissions rates at these facilities were, on average, around four times the rates observed at similar facilities without substantial venting.

Constructing a Spatially Resolved Methane Emission Inventory for the Barnett Shale Region

Methane emissions from the oil and gas industry (O&G) and other sources in the Barnett Shale region were estimated by constructing a spatially resolved emission inventory. Eighteen source categories were estimated using multiple data sets, including new empirical measurements at regional O&G sites and a national study of gathering and processing facilities. Spatially referenced activity data were compiled from federal and state databases and combined with O&G facility emission factors calculated using Monte Carlo simulations that account for high emission sites representing the very upper portion, or fat-tail, in the observed emissions distributions. Total methane emissions in the 25-county Barnett Shale region in October 2013 were estimated to be 72,300 (63,400-82,400) kg CH4 h(-1). O&G emissions were estimated to be 46,200 (40,000-54,100) kg CH4 h(-1) with 19% of emissions from fat-tail sites representing less than 2% of sites. Our estimate of O&G emissions in the Barnett Shale region was higher than alternative inventories based on the United States Environmental Protection Agency (EPA) Greenhouse Gas Inventory, EPA Greenhouse Gas Reporting Program, and Emissions Database for Global Atmospheric Research by factors of 1.5, 2.7, and 4.3, respectively. Gathering compressor stations, which accounted for 40% of O&G emissions in our inventory, had the largest difference from emission estimates based on EPA data sources. Our inventorys higher O&G emission estimate was due primarily to its more comprehensive activity factors and inclusion of emissions from fat-tail sites.

Methane Emissions from Natural Gas Compressor Stations in the Transmission and Storage Sector: Measurements and Comparisons with the EPA Greenhouse Gas Reporting Program Protocol

Equipment- and site-level methane emissions from 45 compressor stations in the transmission and storage (T&S) sector of the US natural gas system were measured, including 25 sites required to report under the EPA greenhouse gas reporting program (GHGRP). Direct measurements of fugitive and vented sources were combined with AP-42-based exhaust emission factors (for operating reciprocating engines and turbines) to produce a study onsite estimate. Site-level methane emissions were also concurrently measured with downwind-tracer-flux techniques. At most sites, these two independent estimates agreed within experimental uncertainty. Site-level methane emissions varied from 2-880 SCFM. Compressor vents, leaky isolation valves, reciprocating engine exhaust, and equipment leaks were major sources, and substantial emissions were observed at both operating and standby compressor stations. The site-level methane emission rates were highly skewed; the highest emitting 10% of sites (including two superemitters) contributed 50% of the aggregate methane emissions, while the lowest emitting 50% of sites contributed less than 10% of the aggregate emissions. Excluding the two superemitters, study-average methane emissions from compressor housings and noncompressor sources are comparable to or lower than the corresponding effective emission factors used in the EPA greenhouse gas inventory. If the two superemitters are included in the analysis, then the average emission factors based on this study could exceed the EPA greenhouse gas inventory emission factors, which highlights the potentially important contribution of superemitters to national emissions. However, quantification of their influence requires knowledge of the magnitude and frequency of superemitters across the entire T&S sector. Only 38% of the methane emissions measured by the comprehensive onsite measurements were reportable under the new EPA GHGRP because of a combination of inaccurate emission factors for leakers and exhaust methane, and various exclusions. The bias is even larger if one accounts for the superemitters, which were not captured by the onsite measurements. The magnitude of the bias varied from site to site by site type and operating state. Therefore, while the GHGRP is a valuable new source of emissions information, care must be taken when incorporating these data into emission inventories. The value of the GHGRP can be increased by requiring more direct measurements of emissions (as opposed to using counts and emission factors), eliminating exclusions such as rod-packing vents on pressurized reciprocating compressors in standby mode under Subpart-W, and using more appropriate emission factors for exhaust methane from reciprocating engines under Subpart-C.

An Evaluation of State-of-Charge Limitations and Actuation Signal Energy Content on Plug-in Hybrid Electric Vehicle, Vehicle-to-Grid Reliability, and Economics

Researchers have proposed that plug-in hybrid electric vehicles (PHEVs) performing vehicle-to-grid (V2G) ancillary services can accrue significant economic benefits without degrading vehicle performance. However, analyses to date have not evaluated the effect that automatic generator control signal energy content and call rate has on V2G ancillary service reliability and value. This research incorporates a new level of detail into the modeling of V2G ancillary services by incorporating probabilistic vehicle travel models, time-series automatic generation control signals, and time series ancillary services pricing into a non-linear dynamic simulation of the driving and charging behavior of PHEVs. Stochastic results are generated using Monte-Carlo methods. Results show that in order to integrate a V2G system into the existing market and power grid the V2G system will require: 1) an aggregative architecture to meet current industry standard reliability requirements; 2) the construction of low energy automatic generation control signals; 3) a lower percent call for V2G even if the pool of contracted ancillary service resources gets smaller; 4) a consideration of vehicle performance degradation due to the potential loss of electrically driven miles; and 5) a high-power home charging capability.

Reconciling divergent estimates of oil and gas methane emissions

Significance Past studies reporting divergent estimates of methane emissions from the natural gas supply chain have generated conflicting claims about the full greenhouse gas footprint of natural gas. Top-down estimates based on large-scale atmospheric sampling often exceed bottom-up estimates based on source-based emission inventories. In this work, we reconcile top-down and bottom-up methane emissions estimates in one of the country’s major natural gas production basins using easily replicable measurement and data integration techniques. These convergent emissions estimates provide greater confidence that we can accurately characterize the sources of emissions, including the large impact that a small proportion of high-emitters have on total emissions and determine the implications for mitigation. Published estimates of methane emissions from atmospheric data (top-down approaches) exceed those from source-based inventories (bottom-up approaches), leading to conflicting claims about the climate implications of fuel switching from coal or petroleum to natural gas. Based on data from a coordinated campaign in the Barnett Shale oil and gas-producing region of Texas, we find that top-down and bottom-up estimates of both total and fossil methane emissions agree within statistical confidence intervals (relative differences are 10% for fossil methane and 0.1% for total methane). We reduced uncertainty in top-down estimates by using repeated mass balance measurements, as well as ethane as a fingerprint for source attribution. Similarly, our bottom-up estimate incorporates a more complete count of facilities than past inventories, which omitted a significant number of major sources, and more effectively accounts for the influence of large emission sources using a statistical estimator that integrates observations from multiple ground-based measurement datasets. Two percent of oil and gas facilities in the Barnett accounts for half of methane emissions at any given time, and high-emitting facilities appear to be spatiotemporally variable. Measured oil and gas methane emissions are 90% larger than estimates based on the US Environmental Protection Agency’s Greenhouse Gas Inventory and correspond to 1.5% of natural gas production. This rate of methane loss increases the 20-y climate impacts of natural gas consumed in the region by roughly 50%.

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.

Methane Emissions from United States Natural Gas Gathering and Processing

New facility-level methane (CH4) emissions measurements obtained from 114 natural gas gathering facilities and 16 processing plants in 13 U.S. states were combined with facility counts obtained from state and national databases in a Monte Carlo simulation to estimate CH4 emissions from U.S. natural gas gathering and processing operations. Total annual CH4 emissions of 2421 (+245/-237) Gg were estimated for all U.S. gathering and processing operations, which represents a CH4 loss rate of 0.47% (±0.05%) when normalized by 2012 CH4 production. Over 90% of those emissions were attributed to normal operation of gathering facilities (1697 +189/-185 Gg) and processing plants (506 +55/-52 Gg), with the balance attributed to gathering pipelines and processing plant routine maintenance and upsets. The median CH4 emissions estimate for processing plants is a factor of 1.7 lower than the 2012 EPA Greenhouse Gas Inventory (GHGI) estimate, with the difference due largely to fewer reciprocating compressors, and a factor of 3.0 higher than that reported under the EPA Greenhouse Gas Reporting Program. Since gathering operations are currently embedded within the production segment of the EPA GHGI, direct comparison to our results is complicated. However, the study results suggest that CH4 emissions from gathering are substantially higher than the current EPA GHGI estimate and are equivalent to 30% of the total net CH4 emissions in the natural gas systems GHGI. Because CH4 emissions from most gathering facilities are not reported under the current rule and not all source categories are reported for processing plants, the total CH4 emissions from gathering and processing reported under the EPA GHGRP (180 Gg) represents only 14% of that tabulated in the EPA GHGI and 7% of that predicted from this study.

Robust Control for Microgrid Frequency Deviation Reduction With Attached Storage System

In this paper, we propose a robust control strategy for reducing system frequency deviation, caused by load fluctuation and renewable sources, in a smart microgrid system with attached storage. Frequency deviations are associated with renewable energy sources because of their inherent variability. In this work, we consider a microgrid where fossil fuel generators and renewable energy sources are combined with a reasonably sized, fast acting battery-based storage system. We develop robust control strategies for frequency deviation reduction, despite the presence of significant (model) uncertainties. The advantages of our approach are illustrated by comparing system frequency deviation between the proposed system (designed via μ synthesis) and the reference system which uses governors and conventional PID control to cope with load and renewable energy source transients. All the simulations are conducted in the Matlab™ and Simulink™ environment.

Super-emitters in natural gas infrastructure are caused by abnormal process conditions

Effectively mitigating methane emissions from the natural gas supply chain requires addressing the disproportionate influence of high-emitting sources. Here we use a Monte Carlo simulation to aggregate methane emissions from all components on natural gas production sites in the Barnett Shale production region (Texas). Our total emission estimates are two-thirds of those derived from independent site-based measurements. Although some high-emitting operations occur by design (condensate flashing and liquid unloadings), they occur more than an order of magnitude less frequently than required to explain the reported frequency at which high site-based emissions are observed. We conclude that the occurrence of abnormal process conditions (for example, malfunctions upstream of the point of emissions; equipment issues) cause additional emissions that explain the gap between component-based and site-based emissions. Such abnormal conditions can cause a substantial proportion of a sites gas production to be emitted to the atmosphere and are the defining attribute of super-emitting sites.

Improved Mechanistic Understanding of Natural Gas Methane Emissions from Spatially Resolved Aircraft Measurements

Divergence in recent oil and gas related methane emission estimates between aircraft studies (basin total for a midday window) and emissions inventories (annualized regional and national statistics) indicate the need for better understanding the experimental design, including temporal and spatial alignment and interpretation of results. Our aircraft-based methane emission estimates in a major U.S. shale gas basin resolved from west to east show (i) similar spatial distributions for 2 days, (ii) strong spatial correlations with reported NG production (R2 = 0.75) and active gas well pad count (R2 = 0.81), and (iii) 2× higher emissions in the western half (normalized by gas production) despite relatively homogeneous dry gas and well characteristics. Operator reported hourly activity data show that midday episodic emissions from manual liquid unloadings (a routine operation in this basin and elsewhere) could explain ∼1/3 of the total emissions detected midday by the aircraft and ∼2/3 of the west-east difference in emissions. The 22% emission difference between both days further emphasizes that episodic sources can substantially impact midday methane emissions and that aircraft may detect daily peak emissions rather than daily averages that are generally employed in emissions inventories. While the aircraft approach is valid, quantitative, and independent, our study sheds new light on the interpretation of previous basin scale aircraft studies, and provides an improved mechanistic understanding of oil and gas related methane emissions.