Characterizing Fugitive Methane Emissions in the Barnett Shale Area Using a Mobile Laboratory

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1 Characterizing Fugitive Methane Emissions in the Barnett Shale Area Using a Mobile Laboratory Robert Talbot & Xin Lan Institute for Climate and Atmospheric Science, Department of Earth & Atmospheric Sciences, University of Houston, Houston, TX, rtalbot@uh.edu, xlan3@uh.edu, CH 4 Connection September 24, 2014

2 ONG Production in the Barnett Shale Area

3 Satellite image of the Barnett Shale Area

4 Recent Data on ONG CH 4 Emissions Natural-gas operations in Denver-Julesburg Basin reported 4-8% CH 4 loss from processing (Pétron et al., 2012). Airborne measurements over a natural gas field in Utah reported CH 4 emission rate of % of total gas production (Karion et al., 2013). The current EPA database underestimate methane emission nationally by a factor of ~1.5 to ~1.7, and CH 4 emissions in the south-central United States are likely ~ 2.7 times greater than in most inventories (Miller et al. 2013). It is estimated total CH 4 emission from ONG source in Denver-Julesburg Basin is about 3 times higher than 2012 EPA Green House Gas Reporting Program (GHGRP) (Pétron et al., 2014). Allen et al. (2013 ) estimated that the total CH 4 emissions was 0.42% of gross natural gas production in U.S.

5 Methane is a Powerful Greenhouse Gas and its Concentration is Increasing in the Global Atmosphere. Why are we Concerned?

6 University of Houston Mobile Laboratory 10/15/ /31/2013 in total, 3,700 km of continuous CH 4 and CO 2 measurements. Two Picarro cavity ring-down instruments were used to measure CH 4 :precision and accuracy was ±1%; time resolution was seconds. 6

7 Gaussian Dispersion Model for Emission Rate Estimates CC xx, yy, zz; HH nn qq = 2ππσσ zzzz σσ yyyy uu eeeeee 1 2 ii=1 yy ii σσ yyyy 2 eeeeee zz HH 2 2 2σσ zzzz QQ = nn qq CC xx, yy, zz; HH : Elevated CH 4 measured at location xx, yy, zz. The background CH 4 level was also subtracted. Q : Total emission rate. qq: Emission rate from one emission source, in the unit of g/s. HH: Emission height of the pollutant plume. uu: Average wind speed. σσ zzzz : Vertical standard deviation. σσ yyyy : Vertical standard deviation. n: Number of emission points assigned to a source. 7

8 AERMOD for Emission Rate Estimates AERMOD: American Meteorological Society (AMS) - Environmental Protection Agency (EPA) Model: A state-of-art air dispersion model. Step 1: use AERMOD to simulate emission scenario using initial emission rate: Q i. Step 2: Compare modeled CH 4 concentration (C m ) with our observations (C o ) at the same location. Calculate emission rate using: QQ = QQ ii CC oo CC mm RR R is a scale ratio for 10 min. versus 60 min. max concentrations. Source: The meteorological inputs use Integrated Surface Data from nearby observation stations and radiosonde data.

9 Mobile Laboratory Tracks 152 facilities (green) were identified with elevated CH 4 levels, comprised of 125 well pads, 13 compressor stations, 2 gas processing plants, and 12 landfills, 45 of which were selected for emission rates estimates. The information of electricity generator, landfill and ONG facilities were from 2012 GHGRP.

10 Influence of PBL

11 Spatial Distribution of Elevated CH 4 Elevated CH 4 map shows the scattered distribution of CH 4 spikes ( >2.2 ppmv ). Maximum CH 4 level observed was 89 ppmv, which was from a compressor station with 6 engines.

12 Emission Rate Estimates for Well Pads Count Gas Production (MCF/day) y = 37.2x+195 R = 0.69 Emission Rate (kg/hr) Emission rates from 34 well pads were estimated using inverse Gaussian dispersion model. Model results show CH 4 emissions rate from to 58 kg/hr (uncertainties range : - 28% to 81%). The histogram shows that well pads emissions has a heavy-tailed distribution. 70% of well pads had emission rates less than 5 kg CH 4 /hr. Well pad emission rates were correlated with gas production for 26 well pads with gas production data Emission Rate (kg/hr)

13 Emission Rate Estimates for Compressor Stations and Gas Processing Plants AERMOD simulation for compressor station #4 with 10 reciprocating engines; the color scale shows the concentration of CH 4 in ug/m 3 unit; the blue lines depict building structures associated with downwash effect; red crosses represent engines; the cyan square mark locates our mobile laboratory during stationary measurements.

14 Uncertainty Estimates Monte Carlo hourly input data for 100 runs: Parameter Statistical Distribution 95% range Wind Speed normal distribution Mean±20% Wind Direction normal distribution Mean±10 Temperature Gradient lognormal distribution Mean±200% Cloud Cover (tenth scale ) normal distribution Mean±20% PBL Height normal distribution Mean±20% We accounted for the natural variability of wind, instead of only accounting for instrument uncertainty. Simple random sampling was conducted for each parameter from their distributions Count Count Emission Rate by AERMOD (kg/hr) Emission Rate by AERMOD (kg/hr) Histogram of 100 Monte Carlo run results show lognormal/ exponential distributions. Overall, the 95% significant intervals are within a factor of 3 of the emission rates estimates.

15 CH 4 Atop Moody Tower on UH Campus (18 story dorm) - Highest Spikes Reach 25 ppmv

16 Shows highest frequency is from the south but highest mixing ratios from NE to E.

17 Thank You! Questions?

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