Long-term variability and source signature of gases emitted from oil & natural gas and cattle feedlot operations in the Colorado front range
Introduction
A sharp increase in the use of hydraulic fracturing and horizontal drilling has provided high production of natural gas in the US in the past decade (U.S. Energy Information Administration, 2017). This explosive growth of natural gas extraction has attracted attention due to its potential atmospheric effects (Howarth et al., 2011). Two important gases released to the atmosphere by oil and natural gas activities (O&NG) are methane (CH4) and ethane (C2H6), which play a key role in tropospheric and stratospheric chemistry and are two of the most critical direct (CH4) and indirect (C2H6) greenhouse gases (Collins et al., 2002; Intergovernmental Panel on Climate Change, 2013; Nisbet et al., 2014). Although the potential magnitude of these emissions is still debated there are recent research indicates that CH4 emissions from shale gas and conventional natural gas have a larger warming potential than coal emissions (Howarth et al., 2011), therefore recent global and regional atmospheric observations and implications need to be understood.
A recent significant increase of C2H6 has been attributed to the development of O&NG in North America (Franco et al., 2016; Helmig et al., 2016). In particular, O&NG related activities have increased tremendously in the Colorado Northern Front Range (CNFR). An extensive set of measurements have been carried out in the past years to investigate the influence of O&NG operations on air quality in the region. Petron et al. (2012) revealed a strong alkane and benzene signature emitted by oil and gas operations over the CNFR using 2007 to 2010 observations at the 300 m level on the Boulder Atmospheric Observatory (BAO) tower in Erie, Colorado. More recent observations have been from intensive but short field deployments, for example, Gilman et al. (2013) pointed out that volatile organic compounds (VOC) emitted from O&NG sources are significant source of ozone (O3) precursors with major importance in winter. Other recent efforts in the CNFR include the large suite of measurements taken during the joint National Science Foundation/National Center for Atmospheric Research (NSF/NCAR) Front Range Air Pollution and Photochemistry Experiment (FRAPPE) and the fourth deployment of the National Aeronautics and Space Administration (NASA) Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field deployments in the summer of 2014 (Pfister et al., 2017; Flocke et al., 2020). During FRAPPE and DISCOVER-AQ a variety of sampling platforms, including airborne, mobile and ground-based, were used with the aim to improve chemical transport models and emission inventories, in addition to understand the main drivers of summertime ozone in the region, which currently is in non-attainment of the 8-hr ozone National Ambient Air Quality Standard (NAAQS). Flocke et al. (2020) provides a description of FRAPPE, a perspective of the air quality in the region, and introduces main findings and references obtained from the extensive contributors involved in these campaigns.
Even though detailed characterization of major sources of pollutants in the region have been carried out, i.e., vehicle emissions, O&NG operations, and agriculture and feedlot operations, they have been limited mainly to short-term periods. Understanding long-term changes in composition is highly desirable for air quality monitoring, assessing emission inventories, and useful for evaluating chemistry transport models and validating gases retrieved with satellites. Furthermore, long-term records are necessary to determine seasonal cycle changes and annual rates of change. Among the different techniques to measure gas phase species, ground-based remote sensing platforms offer significant advantages by measuring several gases quasi-simultaneously, with the potential of being sensitive to wide geographical coverage on scales that are not feasible with in-situ measurements.
In this work, we aim to contribute to this growing area of research by exploring ten years of measurements using passive ground-based Fourier Transform InfraRed (FTIR) spectroscopy. The location of the FTIR, near the Colorado foothills front range, is well suited to examine air masses from different sectors: urban, fires, O&NG, feedlots, and cleaner conditions. The focus of this work is two-fold: (1) Present and study trends of relatively long-term measurements of atmospheric gases related to various sources, specifically O&NG activities (ethane (C2H6)), cattle feedlot operations (ammonia (NH3)), urban emissions (carbon monoxide (CO), acetylene (C2H2)), and volatile organic compounds related to photochemistry and ozone production (formaldehyde (H2CO), formic acid (HCOOH)). Methane (CH4) is also shown, although its sources are numerous. Then use the Community Atmosphere Model with chemistry (CAM-chem) to compare simulations with the FTIR observations, to investigate main sources of these species and to understand limitations in current knowledge above the CNFR. (2) Isolate local enhancements of gases related to nearby O&NG and concentrated animal feeding operations and determine emission ratios (ER) relative to CO of co-emitted species, which then can be used to estimate emission factors (EF). The FTIR observations are complemented with airborne observations during the FRAPPE research study.
Section snippets
Site description
Fig. 1a shows the location of the ground-based FTIR at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado (40.40° N, 105.24° W, 1600 m.a.s.l). Boulder is situated in the front range of the Rocky mountains at about 40 km Northwest of Denver. The air masses in Boulder are influenced from three different sectors: (1) Southeast urban emissions from the Denver metropolitan area with high level of industrial activities; (2) Northeast with high density of O&NG and concentrated
Time series & seasonal variability
Fig. 2 shows the time series of weighted tropospheric mixing ratios of all target gases derived between 2010 and 2019. All FTIR observations are shown with gray dots and monthly mean values are represented by red circles with associated one-sigma standard deviation as vertical red lines. Orange circles, with associated one-sigma standard deviation, are CAM-chem monthly mean values calculated from daily output. Fig. 2, Fig. 3, Fig. 4 show CAM-chem results using CMIP6 and QFED emissions.
Summary & conclusions
In this work, we present ten years of tropospheric gas observations, from 2010 to 2019, using mid-infrared solar absorption spectra measurements taken with a high-resolution FTIR in Boulder at the foothills of the Rocky Mountains, in northern Colorado. This is the first decadal time series of tropospheric gases for the region, obtained using ground-based remote sensing observations, which complement several intensive short-term field campaigns in the region (e.g., Flocke et al. (2020) and
CRediT authorship contribution statement
I. Ortega: Conceptualization, Methodology, Investigation, Analysis, Formal analysis, Investigation, Writing – original draft, Writing – review & editing. J.W. Hannigan: Investigation, Methodology, Supervision, Writing – review & editing. R.R. Buchholz: Software, Investigation, Writing – review & editing. G. Pfister: Conceptualization, Writing – review & editing.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgment
This material is based upon work supported by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the National Science Foundation under Cooperative Agreement No. 1852977. This study has been supported under contract by the National Aeronautics and Space Administration (NASA) award No. NNX17AE38G. We would like to acknowledge high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR's Computational and Information Systems
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