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Dive into the research topics where Daniel Zavala-Araiza is active.

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Featured researches published by Daniel Zavala-Araiza.


Environmental Science & Technology | 2015

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

David R. Lyon; Daniel Zavala-Araiza; Robert C. Harriss; Virginia Palacios; Xin Lan; Robert W. Talbot; Tegan N. Lavoie; Paul B. Shepson; Tara I. Yacovitch; Scott C. Herndon; Anthony J. Marchese; Daniel Zimmerle; Allen L. Robinson; Steven P. Hamburg

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.


Environmental Science & Technology | 2015

Methane Emissions from Process Equipment at Natural Gas Production Sites in the United States: Pneumatic Controllers

David T. Allen; Adam P. Pacsi; David W. Sullivan; Daniel Zavala-Araiza; Matthew Harrison; Kindal Keen; Matthew P. Fraser; A. Daniel Hill; Robert F. Sawyer; John H. Seinfeld

Emissions from 377 gas actuated (pneumatic) controllers were measured at natural gas production sites and a small number of oil production sites, throughout the United States. A small subset of the devices (19%), with whole gas emission rates in excess of 6 standard cubic feet per hour (scf/h), accounted for 95% of emissions. More than half of the controllers recorded emissions of 0.001 scf/h or less during 15 min of measurement. Pneumatic controllers in level control applications on separators and in compressor applications had higher emission rates than controllers in other types of applications. Regional differences in emissions were observed, with the lowest emissions measured in the Rocky Mountains and the highest emissions in the Gulf Coast. Average methane emissions per controller reported in this work are 17% higher than the average emissions per controller in the 2012 EPA greenhouse gas national emission inventory (2012 GHG NEI, released in 2014); the average of 2.7 controllers per well observed in this work is higher than the 1.0 controllers per well reported in the 2012 GHG NEI.


Proceedings of the National Academy of Sciences of the United States of America | 2015

Reconciling divergent estimates of oil and gas methane emissions

Daniel Zavala-Araiza; David R. Lyon; Ramón A. Alvarez; Kenneth J. Davis; Robert C. Harriss; Scott C. Herndon; Anna Karion; Eric A. Kort; Brian K. Lamb; Xin Lan; Anthony J. Marchese; Stephen W. Pacala; Allen L. Robinson; Paul B. Shepson; Colm Sweeney; Robert W. Talbot; Amy Townsend-Small; Tara I. Yacovitch; Daniel Zimmerle; Steven P. Hamburg

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%.


Environmental Science & Technology | 2015

Methane Emissions from Process Equipment at Natural Gas Production Sites in the United States: Liquid Unloadings

David T. Allen; David W. Sullivan; Daniel Zavala-Araiza; Adam P. Pacsi; Matthew Harrison; Kindal Keen; Matthew P. Fraser; A. Daniel Hill; Brian K. Lamb; Robert F. Sawyer; John H. Seinfeld

Methane emissions from liquid unloadings were measured at 107 wells in natural gas production regions throughout the United States. Liquid unloadings clear wells of accumulated liquids to increase production, employing a variety of liquid lifting mechanisms. In this work, wells with and without plunger lifts were sampled. Most wells without plunger lifts unload less than 10 times per year with emissions averaging 21,000-35,000 scf methane (0.4-0.7 Mg) per event (95% confidence limits of 10,000-50,000 scf/event). For wells with plunger lifts, emissions averaged 1000-10,000 scf methane (0.02-0.2 Mg) per event (95% confidence limits of 500-12,000 scf/event). Some wells with plunger lifts are automatically triggered and unload thousands of times per year and these wells account for the majority of the emissions from all wells with liquid unloadings. If the data collected in this work are assumed to be representative of national populations, the data suggest that the central estimate of emissions from unloadings (270 Gg/yr, 95% confidence range of 190-400 Gg) are within a few percent of the emissions estimated in the EPA 2012 Greenhouse Gas National Emission Inventory (released in 2014), with emissions dominated by wells with high frequencies of unloadings.


Environmental Science & Technology | 2015

Toward a Functional Definition of Methane Super-Emitters: Application to Natural Gas Production Sites

Daniel Zavala-Araiza; David R. Lyon; Ramón A. Alvarez; Virginia Palacios; Robert C. Harriss; Xin Lan; Robert W. Talbot; Steven P. Hamburg

Emissions from natural gas production sites are characterized by skewed distributions, where a small percentage of sites-commonly labeled super-emitters-account for a majority of emissions. A better characterization of super-emitters is needed to operationalize ways to identify them and reduce emissions. We designed a conceptual framework that functionally defines superemitting sites as those with the highest proportional loss rates (methane emitted relative to methane produced). Using this concept, we estimated total methane emissions from natural gas production sites in the Barnett Shale; functionally superemitting sites accounted for roughly three-fourths of total emissions. We discuss the potential to reduce emissions from these sites, under the assumption that sites with high proportional loss rates have excess emissions resulting from abnormal or otherwise avoidable operating conditions, such as malfunctioning equipment. Because the population of functionally superemitting sites is not expected to be static over time, continuous monitoring will likely be necessary to identify them and improve their operation. This work suggests that achieving and maintaining uniformly low emissions across the entire population of production sites will require mitigation steps at a large fraction of sites.


Environmental Science & Technology | 2013

Regional Air Quality Impacts of Increased Natural Gas Production and Use in Texas

Adam P. Pacsi; Nawaf S. Alhajeri; Daniel Zavala-Araiza; Mort Webster; David T. Allen

Natural gas use in electricity generation in Texas was estimated, for gas prices ranging from


Environmental Science & Technology | 2016

Aerial Surveys of Elevated Hydrocarbon Emissions from Oil and Gas Production Sites

David R. Lyon; Ramón A. Alvarez; Daniel Zavala-Araiza; Adam R. Brandt; Robert B. Jackson; Steven P. Hamburg

1.89 to


Environmental Science & Technology | 2015

Using Multi-Scale Measurements to Improve Methane Emission Estimates from Oil and Gas Operations in the Barnett Shale Region, Texas.

Robert C. Harriss; Ramón A. Alvarez; David R. Lyon; Daniel Zavala-Araiza; Drew Nelson; Steven P. Hamburg

7.74 per MMBTU, using an optimal power flow model. Hourly estimates of electricity generation, for individual electricity generation units, from the model were used to estimate spatially resolved hourly emissions from electricity generation. Emissions from natural gas production activities in the Barnett Shale region were also estimated, with emissions scaled up or down to match demand in electricity generation as natural gas prices changed. As natural gas use increased, emissions decreased from electricity generation and increased from natural gas production. Overall, NOx and SO2 emissions decreased, while VOC emissions increased as natural gas use increased. To assess the effects of these changes in emissions on ozone and particulate matter concentrations, spatially and temporally resolved emissions were used in a month-long photochemical modeling episode. Over the month-long photochemical modeling episode, decreases in natural gas prices typical of those experienced from 2006 to 2012 led to net regional decreases in ozone (0.2-0.7 ppb) and fine particulate matter (PM) (0.1-0.7 μg/m(3)). Changes in PM were predominantly due to changes in regional PM sulfate formation. Changes in regional PM and ozone formation are primarily due to decreases in emissions from electricity generation. Increases in emissions from increased natural gas production were offset by decreasing emissions from electricity generation for all the scenarios considered.


Environmental Science & Technology | 2014

Atmospheric Hydrocarbon Emissions and Concentrations in the Barnett Shale Natural Gas Production Region

Daniel Zavala-Araiza; David W. Sullivan; David T. Allen

Oil and gas (O&G) well pads with high hydrocarbon emission rates may disproportionally contribute to total methane and volatile organic compound (VOC) emissions from the production sector. In turn, these emissions may be missing from most bottom-up emission inventories. We performed helicopter-based infrared camera surveys of more than 8000 O&G well pads in seven U.S. basins to assess the prevalence and distribution of high-emitting hydrocarbon sources (detection threshold ∼ 1-3 g s(-1)). The proportion of sites with such high-emitting sources was 4% nationally but ranged from 1% in the Powder River (Wyoming) to 14% in the Bakken (North Dakota). Emissions were observed three times more frequently at sites in the oil-producing Bakken and oil-producing regions of mixed basins (p < 0.0001, χ(2) test). However, statistical models using basin and well pad characteristics explained 14% or less of the variance in observed emission patterns, indicating that stochastic processes dominate the occurrence of high emissions at individual sites. Over 90% of almost 500 detected sources were from tank vents and hatches. Although tank emissions may be partially attributable to flash gas, observed frequencies in most basins exceed those expected if emissions were effectively captured and controlled, demonstrating that tank emission control systems commonly underperform. Tanks represent a key mitigation opportunity for reducing methane and VOC emissions.


Nature Communications | 2017

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

Daniel Zavala-Araiza; Ramón A. Alvarez; David R. Lyon; David T. Allen; Anthony J. Marchese; Daniel Zimmerle; Steven P. Hamburg

A growing body of work using varying analytical approaches is yielding estimates of methane emissions from the natural gas supply chain. For shorthand, the resulting emission estimates can be broadly described as top-down or bottom-up. Top-down estimates are determined from measured atmospheric methane enhancements at regional or larger scales. Bottom-up estimates rely on emissions measurements made directly from components or at the site level. (We note that bottom-up emission estimates (e.g., refs 4 and 13) may rely on data obtained with emission quantification methods sometimes labeled as top-down (e.g., refs 6, 7, and 9−12).) Both approaches have strengths and weaknesses. Top-down estimates cannot easily distinguish emissions from specific source types, limiting the development of informed mitigation strategies. Bottom-up estimates are resource intensive, and may not provide sufficient statistical characterization of each source type to accurately estimate total emissions. Previously published large-scale top-down studies report higher methane emissions than estimated by bottom-up emission inventories. Recent reviews of this work suggest that differences may result from (i) incorrect attribution of emissions among methane sources (e.g., fossil vs biogenic sources); (ii) obsolete or incomplete emission inventories, possibly based on emission factors developed using small or unrepresentative samples (including potential bias introduced by sampling only at cooperating facilities) and poor infrastructure activity data (e.g., site or event counts); (iii) failure to account for emissions from uncommon but anomalously high emitting sources (sometimes called superemitters); and (iv) the impact of intermittent, short-duration events. This issue contains 10 articles reporting results from a coordinated, twoweek field campaign that examined methane emissions using a diversity of analytical approaches in an effort to address these issues. The Barnett Shale Coordinated Campaign focused on a region of north Texas that includes the Barnett Shale oil and gas fields and the metropolitan area around Dallas and Fort Worth (population ∼7 million). With about 30 000 active wells, the region produced ∼2 trillion cubic feet of natural gas in 2013, or 7% of total U.S. production. As summarized below and in Figure 1, measurements from the campaign, supplemented with two recent national data sets, were used to develop topdown and bottom-up estimates of oil and gas methane emissions in the Barnett Shale region.

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Steven P. Hamburg

Environmental Defense Fund

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David R. Lyon

Environmental Defense Fund

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David T. Allen

University of Texas at Austin

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Ramón A. Alvarez

Environmental Defense Fund

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Allen L. Robinson

Carnegie Mellon University

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Brian K. Lamb

Washington State University

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Daniel Zimmerle

Colorado State University

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