Melanie L. Sattler

An exploratory study of air emissions associated with shale gas development and production in the Barnett Shale

Information regarding air emissions from shale gas extraction and production is critically important given production is occurring in highly urbanized areas across the United States. Objectives of this exploratory study were to collect ambient air samples in residential areas within 61 m (200 feet) of shale gas extraction/production and determine whether a “fingerprint” of chemicals can be associated with shale gas activity. Statistical analyses correlating fingerprint chemicals with methane, equipment, and processes of extraction/production were performed. Ambient air sampling in residential areas of shale gas extraction and production was conducted at six counties in the Dallas/Fort Worth (DFW) Metroplex from 2008 to 2010. The 39 locations tested were identified by clients that requested monitoring. Seven sites were sampled on 2 days (typically months later in another season), and two sites were sampled on 3 days, resulting in 50 sets of monitoring data. Twenty-four-hour passive samples were collected using summa canisters. Gas chromatography/mass spectrometer analysis was used to identify organic compounds present. Methane was present in concentrations above laboratory detection limits in 49 out of 50 sampling data sets. Most of the areas investigated had atmospheric methane concentrations considerably higher than reported urban background concentrations (1.8–2.0 ppmv). Other chemical constituents were found to be correlated with presence of methane. A principal components analysis (PCA) identified multivariate patterns of concentrations that potentially constitute signatures of emissions from different phases of operation at natural gas sites. The first factor identified through the PCA proved most informative. Extreme negative values were strongly and statistically associated with the presence of compressors at sample sites. The seven chemicals strongly associated with this factor (o-xylene, ethylbenzene, 1,2,4-trimethylbenzene, m- and p-xylene, 1,3,5-trimethylbenzene, toluene, and benzene) thus constitute a potential fingerprint of emissions associated with compression. Implications: Information regarding air emissions from shale gas development and production is critically important given production is now occurring in highly urbanized areas across the United States. Methane, the primary shale gas constituent, contributes substantially to climate change; other natural gas constituents are known to have adverse health effects. This study goes beyond previous Barnett Shale field studies by encompassing a wider variety of production equipment (wells, tanks, compressors, and separators) and a wider geographical region. The principal components analysis, unique to this study, provides valuable information regarding the ability to anticipate associated shale gas chemical constituents.

Plasma surface modified TiO2 nanoparticles: improved photocatalytic oxidation of gaseous m-xylene.

Titanium dioxide (TiO(2)) is a preferred catalyst for photocatalytic oxidation of many air pollutants. In an effort to enhance its photocatalytic activity, TiO(2) was modified by pulsed plasma treatment. In this work, TiO(2) nanoparticles, coated on a glass plate, were treated with a plasma discharge of hexafluoropropylene oxide (HFPO) gas. By appropriate adjustment of discharge conditions, it was discovered that the TiO(2) particles can be either directly fluorinated (Ti-F) or coated with thin perfluorocarbon films (C-F). Specifically, under relatively high power input, the plasma deposition process favored direct surface fluorination. The extent of Ti-F formation increased with increasing power input. In contrast, at lower average power inputs, perfluorocarbon films are deposited on the surface of the TiO(2) particles. The plasma surface modified TiO(2) nanoparticles were subsequently employed as catalysts in the photocatalytic oxidation of m-xylene in air, as carried out inside a batch reactor with closed loop constant gas circulation. Both types of modified TiO(2) were significantly more catalytically active than that of the unmodified particles. For example, the rate constant of m-xylene degradation was increased from 0.012 min(-1) with untreated TiO(2) to 0.074 min(-1) with fluorinated TiO(2). Although it is not possible to provide unequivocal reasons for this increased photocatalytic activity, it is noted that the plasma surface treatment converted the TiO(2) from hydrophilic to highly hydrophobic, which would provide more facile catalyst adsorption of the xylene from the flowing air. Also, based on literature reports, the use of fluorinated TiO(2) reduces electron-hole recombination rates, thus increasing the photocatalytic activity.

Mobile measurement of methane and hydrogen sulfide at natural gas production site fence lines in the Texas Barnett Shale

Production of natural gas from shale formations is bringing drilling and production operations to regions of the United States that have seen little or no similar activity in the past, which has generated considerable interest in potential environmental impacts. This study focused on the Barnett Shale Fort Worth Basin in Texas, which saw the number of gas-producing wells grow from 726 in 2001 to 15,870 in 2011. This study aimed to measure fence line concentrations of methane and hydrogen sulfide at natural gas production sites (wells, liquid storage tanks, and associated equipment) in the four core counties of the Barnett Shale (Denton, Johnson, Tarrant, and Wise). A mobile measurement survey was conducted in the vicinity of 4788 wells near 401 lease sites, representing 35% of gas production volume, 31% of wells, and 38% of condensate production volume in the four-county core area. Methane and hydrogen sulfide concentrations were measured using a Picarro G2204 cavity ring-down spectrometer (CRDS). Since the research team did not have access to lease site interiors, measurements were made by driving on roads on the exterior of the lease sites. Over 150 hr of data were collected from March to July 2012. During two sets of drive-by measurements, it was found that 66 sites (16.5%) had methane concentrations >3 parts per million (ppm) just beyond the fence line. Thirty-two lease sites (8.0%) had hydrogen sulfide concentrations >4.7 parts per billion (ppb) (odor recognition threshold) just beyond the fence line. Measured concentrations generally did not correlate well with site characteristics (natural gas production volume, number of wells, or condensate production). t tests showed that for two counties, methane concentrations for dry sites were higher than those for wet sites. Follow-up study is recommended to provide more information at sites identified with high levels of methane and hydrogen sulfide. Implications: Information regarding air emissions from shale gas production is important given the recent increase in number of wells in various regions in the United States. Methane, the primary natural gas constituent, is a greenhouse gas; hydrogen sulfide, which can be present in gas condensate, is an odor-causing compound. This study surveyed wells representing one-third of the natural gas production volume in the Texas Barnett Shale and identified the percent of sites that warrant further study due to their fence line methane and hydrogen sulfide concentrations.

Characterization of spatially homogeneous regions based on temporal patterns of fine particulate matter in the continental United States.

Abstract Statistical analyses of time-series or spatial data have been widely used to investigate the behavior of ambient air pollutants. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both spatial and temporal characteristics. The objective of this study is 2-fold: (1) to identify an efficient way to characterize the spatial variations of fine particulate matter (PM2.5) concentrations based solely upon their temporal patterns, and (2) to analyze the temporal and seasonal patterns of PM2.5 concentrations in spatially homogenous regions. This study used 24-hr average PM2.5 concentrations measured every third day during a period between 2001 and 2005 at 522 monitoring sites in the continental United States. A k-means clustering algorithm using the correlation distance was used to investigate the similarity in patterns between temporal profiles observed at the monitoring sites. A k-means clustering analysis produced six clusters of sites with distinct temporal patterns that were able to identify and characterize spatially homogeneous regions of the United States. The study also presents a rotated principal component analysis (RPCA) that has been used for characterizing spatial patterns of air pollution and discusses the difference between the clustering algorithm and RPCA.

Method for Predicting Photocatalytic Oxidation Rates of Organic Compounds

Abstract In designing a photocatalytic oxidation (PCO) system for a given air pollution source, destruction rates for volatile organic compounds (VOCs) are required. The objective of this research was to develop a systematic method of predicting PCO rate constants by correlating rate constants with physical-chemical characteristics of compounds. Accordingly, reaction rate constants were determined for destruction of volatile organics over a titanium dioxide (TiO2 ) catalyst in a continuous mixed-batch reactor. It was found that PCO rate constants for alkanes and alkenes vary linearly with gas-phase ionization potential (IP) and with gas-phase hydroxyl radical reaction rate constant. The correlations allow rates of destruction of compounds not tested in this research to be predicted based on physical-chemical characteristics.

Comparative study of carbon nanotubes and granular activated carbon: Physicochemical properties and adsorption capacities

The overall goal was to determine an optimum pre-treatment condition for carbon nanotubes (CNTs) to facilitate air pollutant adsorption. Various combinations of heat and chemical pre-treatment were explored, and toluene was tested as an example hazardous air pollutant adsorbate. Specific objectives were (1) to characterize raw and pre-treated single-wall (SW) and multi-wall (MW) CNTs and compare their physical/chemical properties to commercially available granular activated carbon (GAC), (2) to determine the adsorption capacities for toluene onto pre-treated CNTs vs. GAC. CNTs were purified via heat-treatment at 400 °C in steam, followed by nitric acid treatment (3N, 5N, 11N, 16N) for 3-12 h to create openings to facilitate adsorption onto interior CNT sites. For SWNT, Raman spectroscopy showed that acid treatment removed impurities up to a point, but amorphous carbon reformed with 10h-6N acid treatment. Surface area of SWNTs with 3 h-3N acid treatment (1347 m(2)/g) was higher than the raw sample (1136 m(2)/g), and their toluene maximum adsorption capacity was comparable to GAC. When bed effluent reached 10% of inlet concentration (breakthrough indicating time for bed cleaning), SWNTs had adsorbed 240 mg/g of toluene, compared to 150 mg/g for GAC. Physical/chemical analyses showed no substantial difference for pre-treated vs. raw MWNTs.

Estimating methane emissions from landfills based on rainfall, ambient temperature, and waste composition: The CLEEN model

Accurately estimating landfill methane emissions is important for quantifying a landfills greenhouse gas emissions and power generation potential. Current models, including LandGEM and IPCC, often greatly simplify treatment of factors like rainfall and ambient temperature, which can substantially impact gas production. The newly developed Capturing Landfill Emissions for Energy Needs (CLEEN) model aims to improve landfill methane generation estimates, but still require inputs that are fairly easy to obtain: waste composition, annual rainfall, and ambient temperature. To develop the model, methane generation was measured from 27 laboratory scale landfill reactors, with varying waste compositions (ranging from 0% to 100%); average rainfall rates of 2, 6, and 12 mm/day; and temperatures of 20, 30, and 37°C, according to a statistical experimental design. Refuse components considered were the major biodegradable wastes, food, paper, yard/wood, and textile, as well as inert inorganic waste. Based on the data collected, a multiple linear regression equation (R(2)=0.75) was developed to predict first-order methane generation rate constant values k as functions of waste composition, annual rainfall, and temperature. Because, laboratory methane generation rates exceed field rates, a second scale-up regression equation for k was developed using actual gas-recovery data from 11 landfills in high-income countries with conventional operation. The Capturing Landfill Emissions for Energy Needs (CLEEN) model was developed by incorporating both regression equations into the first-order decay based model for estimating methane generation rates from landfills. CLEEN model values were compared to actual field data from 6 US landfills, and to estimates from LandGEM and IPCC. For 4 of the 6 cases, CLEEN model estimates were the closest to actual.

Removal of Carbonyl Sulfide Using Activated Carbon Adsorption

Abstract Wastewater treatment plant odors are caused by compounds such as hydrogen sulfide (H2S), methyl mercaptans, and carbonyl sulfide (COS). One of the most efficient odor control processes is activated carbon adsorption; however, very few studies have been conducted on COS adsorption. COS is not only an odor causing compound but is also listed in the Clean Air Act as a hazardous air pollutant. Objectives of this study were to determine the following: (1) the adsorption capacity of 3 different carbons for COS removal; (2) the impact of relative humidity (RH) on COS adsorption; (3) the extent of competitive adsorption of COS in the presence of H2S; and (4) whether ammonia injection would increase COS adsorption capacity. Vapor phase react (VPR; reactivated), BPL (bituminous coal-based), and Centaur (physically modified to enhance H2S adsorption) carbons manufactured by Calgon Carbon Corp. were tested in three laboratory-scale columns, 6 in. in depth and 1 in. in diameter. Inlet COS concentrations varied from 35 to 49 ppmv (86–120 mg/m3). RHs of 17%, 30%, 50%, and 90% were tested. For competitive adsorption studies, H2S was tested at 60 ppmv, with COS at 30 ppmv. COS, RH, H2S, and ammonia concentrations were measured using an International Sensor Technology Model IQ-350 solid state sensor, Cole-Parmer humidity stick, Interscan Corp. 1000 series portable analyzer, and Drager Accuro ammonia sensor, respectively. It was found that the adsorption capacity of Centaur carbon for COS was higher than the other two carbons, regardless of RH. As humidity increased, the percentage of decrease in adsorption capacity of Centaur carbon, however, was greater than the other two carbons. The carbon adsorption capacity for COS decreased in proportion to the percentage of H2S in the gas stream. More adsorption sites appear to be available to H2S, a smaller molecule. Ammonia, which has been found to increase H2S adsorption capacity, did not increase the capacity for COS.

A Decision-Making Framework for Ozone Pollution Control

In this paper, an intelligent decision-making framework (DMF) is developed to help decision makers identify cost-effective ozone control policies. High concentrations of ozone at the ground level continue to be a serious problem in numerous U.S. cities. Our DMF searches for dynamic and targeted control policies that require a lower total reduction of emissions than current control strategies based on the “trial and error” approach typically employed by state government decision makers. Our DMF utilizes a rigorous stochastic dynamic programming (SDP) formulation and incorporates an atmospheric chemistry module to model how ozone concentrations change over time. Within the atmospheric chemistry module, methods from design and analysis of computer experiments are employed to create SDP state transition equation metamodels, and critical dimensionality reduction is conducted to reduce the state-space dimension in solving our SDP problem. Results are presented from a prototype DMF for the Atlanta metropolitan region.

Correlating emissions with time and temperature to predict worst-case emissions from open liquid area sources.

Abstract The two primary factors influencing ambient air pollutant concentrations are emission rate and dispersion rate. Gaussian dispersion modeling studies for odors, and often other air pollutants, vary dispersion rates using hourly meteorological data. However, emission rates are typically held constant, based on one measured value. Using constant emission rates can be especially inaccurate for open liquid area sources, like wastewater treatment plant units, which have greater emissions during warmer weather, when volatilization and biological activity increase. If emission rates for a wastewater odor study are measured on a cooler day and input directly into a dispersion model as constant values, odor impact will likely be underestimated. Unfortunately, because of project schedules, not all emissions sampling from open liquid area sources can be conducted under worst-case summertime conditions. To address this problem, this paper presents a method of varying emission rates based on temperature and time of the day to predict worst-case emissions. Emissions are varied as a linear function of temperature, according to Henry’s law, and a tenth order polynomial function of time. Equation coefficients are developed for a specific area source using concentration and temperature measurements, captured over a multiday period using a data-logging monitor. As a test case, time/temperature concentration correlation coefficients were estimated from field measurements of hydrogen sulfide (H2S) at the Rowlett Creek Wastewater Treatment Plant in Garland, TX. The correlations were then used to scale a flux chamber emission rate measurement according to hourly readings of time and temperature, to create an hourly emission rate file for input to the dispersion model ISCST3. ISCST3 was then used to predict hourly atmospheric concentrations of H2S. With emission rates varying hourly, ISCST3 predicted 384 acres of odor impact, compared with 103 acres for constant emissions. Because field sampling had been conducted on relatively cool days (85–90 °F), the constant emission rate underestimated odor impact significantly (by 73%).