Improving Characterization of Anthropogenic Methane Emissions in the United States (2018) / Chapter Skim
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3 Methane Emission Measurement and Monitoring Methods
3 Methane Emission Measurement and Monitoring Methods
Pages 77-138
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From page 77... ...
, atmospheric methane concentrations can be transformed, using a variety of modeling tools, to estimate methane emissions from broad geographic areas. These emission estimates, which aggregate emissions from multiple sources, are defined by the Committee as top-down assessments.
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Satellite retrievals that cover regional to global scales may provide instantaneous snapshots or be time averaged to provide longer-term measurements. This chapter describes global-, continental-, and regional-scale atmospheric methane measurements, along with the models used to estimate emissions from these topdown measurements.
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temporal trends. by the use of inlet/ • Quantifies rates for • Single enclosures outlet methane soil oxidation of may not capture all concentrations with an atmospheric methane variability in emissions.
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and therefore may • Examples include flux • Measures uptake of over- or underestimate gradient, integrated atmospheric methane emissions. horizontal flux, eddy (i.e., negative emissions)
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• Labor intensive to measure the spatial and temporal variability of emissions over many sources. Inverse • Measurement of • Estimates total methane • Difficult to isolate various dispersion downwind methane emissions from point sources within the modeling concentrations with and area sources.
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. • Labor intensive to measure the spatial and temporal variability of emissions over many sources.
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measurements across sensitivity footprint.a • Time-series multiple sites Methods are not fully • measurements of • Long time series developed. concentrations, Challenging to apply to • analyzed by eddy individual facilities and covariance or by distinguish confounding inverse modeling.
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BOTTOM-UP TECHNIQUES FOR MEASURING METHANE EMISSIONS Bottom-up emission inventories, as discussed in Chapter 2, have historically been developed by multiplying activity data (e.g., numbers of livestock, natural gas operations, landfilled waste) by emission factors (e.g., emissions per head of livestock, emissions per natural gas facility)
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. In other applications for industrial point sources, measurement devices sampling at a known flow rate attempt to capture the entire emission stream -- the methane emission rate is calculated by multiplying the sampling rate by the methane concentration minus the background air concentration.
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. Micrometeorological Techniques If emissions from a source area cannot be enclosed or captured, there are several micrometeorological techniques that can estimate methane emissions using towers with fast-response methane sensors and wind speed/direction sensors, combined with atmospheric transport modeling.
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Inverse Dispersion Modeling Methane emissions from point and area sources can also be determined utilizing inverse dispersion modeling by making downwind measurements of methane alone (without an external tracer) , along with measurements of background methane concentration 87
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. Facility-Scale In Situ Aircraft Measurements Aircraft-based measurements can be used to estimate emissions from individual facilities (e.g., an animal feeding operation, a landfill, or a natural gas processing facility)
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, methane generated from manure storage is the main source of methane emissions. Methane emissions from livestock are microbially driven and therefore can have large spatial and temporal variability, because microbial activity is governed by the substrate available as well as other conditions.
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. Methods for measuring enteric methane from livestock include enclosure chambers, tracer techniques, "sniffer" techniques, and handheld laser methane detectors.1 The "gold standard" for measuring enteric methane emissions from farm animals (ruminants and nonruminants)
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The ratio of the two gases and the SF6 release rate are used to calculate the methane emission rate. The technique is less costly compared with the investment to build and operate respiration chambers, and has been widely used by research groups around the globe.
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. Comparisons with respiration chambers or SF6 have established that when properly used, GF is a reliable technique for measuring enteric methane emissions from ruminant animals (Dorich et al., 2015; Hammond et al., 2015; Hristov et al., 2016)
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Indirect approaches have been proposed and used to measure enteric methane emissions from livestock. One approach uses estimated carbon dioxide emissions and measured carbon dioxide/methane ratio in exhaled air to estimate methane emissions (Madsen et al., 2010)
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For enclosed barns that are mechanically ventilated, emission rates can be determined by mass balance methods. For open housing systems, measurement techniques can include mass balance, external tracer techniques, inverse dispersion modeling, and micrometeorology techniques.
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They can also be employed over longer time periods that capture the temporal variability of emissions, providing better long-term emission estimates. Additional methods can be employed that do not rely on calculating or estimating ventilation rates and can be applicable to open source areas (dry lots, pasture, manure storage areas, etc.)
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Petroleum and Natural Gas Systems Methane emissions from petroleum and natural gas supply chain sources reported in national inventories include sources from the wellhead to the point of use of the fuel, but they do not include emissions associated with end use (e.g., unburned m ethane from electricity power generation)
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For each emission category, there are large numbers of sources to account for and considerable spatial and temporal variability in methane emissions both within and across category and component types. In the United States, there are currently over 600 gas processing plants and over one million pneumatic devices in combined petroleum and natural gas systems.
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From page 98... ...
For example, in the 2011 GHGI (released in 2013) , emissions from natural gas well completions, summed over the duration of the completions, were estimated to total 0.65 Tg from a total of 8,077 well completions, resulting in average methane emissions per well completion of 81 metric tons (or 0.000081 Tg)
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. A common element in many of the recent methane emission studies on natural gas is the presence of high-emitting sources, that is, a small number of sites or equipment that contribute a disproportionately high fraction of the cumulative total emissions recorded (Box 2.2)
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U.S. national Liquid Average emissions 2-3% of wells Allen et al., sample of unloadings equivalent to those reported account for more 2015b natural gas in EPA GHGI.
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Natural Gas Gathering and Processing Operations U.S. national Downwind Emissions averaged 0.20% Some gathering Marchese sample of sampling of of throughput for gathering facilities had et al., 2015; natural gas sites facilities and 0.075% of emissions that Mitchell et al., sites throughput for processing were in excess 2015 facilities.
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Natural Gas Distribution, Metering, and Regulating (M&R) Thirteen urban Direct sampling Emissions of 0.10% to 0.22% Large reductions Lamb et al., distribution of emissions of the methane delivered, in emissions from 2015 systems equivalent to 36% to 70% high-emitting less than the 2011 EPA GHGI; facilities, compared emission factors reported for to measurements multiple types of pipes and made in early for M&R facilities, multiple 1990s (Harrison et pressures.
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From page 103... ...
Also, landfills must presently comply with minimum cover requirements, standards for biogas management, required biogas recovery at larger sites, quarterly surface scans for elevated methane concentrations, and other operational guidelines under both Subtitle D of the Resource Conservation and Recovery Act and Clean Air Act mandates. These requirements vary somewhat among states to conform with regional differences in landfill practices as well as state requirements that may be stricter than federal minimum standards.
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can quantify the spatial and temporal variability of emissions across a given cover type. Moreover, static chambers can also quantify "negative" emissions (e.g., uptake of atmospheric methane)
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Because of variable environmental conditions (temperature, moisture, soil processes) , active microbial communities were highly diverse with distinct spatial and seasonal clustering, including the concurrent presence of atmospheric methane oxidizers.
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The model provides improved site-specific estimates as the sum of cover-specific methane emissions with and without oxidation for 10-min time steps and 2.5-cm depth increments over a typical annual cycle (using embedded U.S. Department of Agriculture models for average 30-year weather data with 0.5° × 0.5° latitude/longitude reliability)
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Figure 3.3 compares whole-landfill methane emissions for an Indiana landfill using an aircraft mass balance technique, tracer correlation, and modeled monthly emissions with and without oxidation (Cambaliza et al., 2017)
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and aircraft mass balance (AMB) methodologies.
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Emission Estimates Active Underground Mines In underground coal mining, activity data such as numbers of mines and quantities of coal produced are well known and emission estimates rely on stack-based sampling of 6 Transformation of plant biomass into peat and coal (Diessel, 1992)
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requires that trained MSHA inspectors perform mine safety inspections at least quarterly by testing methane emission rates at each coal mine. Air bottle samples are collected at the mine's main ventilation fans along with airflow rate measurement.
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. Empirical methods typically require only a few input parameters (e.g., coal production, gas content, and methane emission rate)
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, and annually reports methane emissions. In general, emission estimates from abandoned underground mines are based on the emissions during the active phase of the mine, assuming that emissions experience a hyperbolic decline after abandonment.
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However, underground mining has a much higher contribution to total methane emissions and therefore is a priority for efforts to improve methane emission estimates from coal mining. TOP-DOWN TECHNIQUES FOR MEASURING METHANE EMISSIONS Global Methane Monitoring Observations Top-down emission estimates for methane, for the United States or any other region, rely on atmospheric measurements of methane and a quantitative understanding of the sources and sinks of methane in the atmosphere.
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It was initiated by the Rowland-Blake Group at the University of California (UC) , Irvine, in 1978 and is ongoing, making these observations the longest-running time series of atmospheric methane concentrations.
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. Uncertainties in top-down emission estimates are influenced both by uncertainties in atmospheric methane measurements and by uncertainties in the models used to estimate emissions based on atmospheric measurements (Box 3.1; for more detailed discussion of uncertainties, see Chapter 4)
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Repeat ability is determined by using agreement between sample pairs excluding flagged pairs. Overall, the total error in atmospheric methane measurements has ranged from 2.4 ppb (95 percent confidence)
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, and UC Irvine, monitoring of methane is conducted by many other nations and these measurements are important for understanding factors that influence the flux of atmospheric methane that enters the United States. For example, Environment and Climate Change Canada collects long-term observations at Alert, Nunavut, and other locations throughout Canada.
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Observations of some hydrocarbons such as ethane and propane may also help to quantify emissions from petroleum and natural gas production since they are co-emitted with methane from this source. The ratio of the emissions of these higher hydrocarbons relative to methane varies considerably and is not well characterized at present (Allen et al., 2017; Peischl et al., 2015, 2016)
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Satellite measurements typically use methane absorption features in the shortwave or thermal infrared spectral range to derive methane abundances. Remote sensing in the shortwave infrared is based on absorption spectroscopy using the sun as a light source, which makes it very sensitive to methane in the entire atmospheric column, including near-surface variations (e.g., Buchwitz et al., 2000)
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These higher-resolution instruments may allow for mass balance approaches to be used to estimate emissions with higher spatial resolution than is currently possible. Potential future missions might also be able to map localized plumes from space (Thompson et al., 2016; Thorpe et al., 2016)
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All of the aircraft, surface discrete, and observatory sites measure methane. The tower sites measure discrete methane except for two sites in alifornia, C which have in situ analyzers.
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. Regional Monitoring Observations Regional atmospheric methane observations can be made using networks of tower sites similar to those used in continental networks, but at a smaller scale.
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Methane Emission Measurement and Monitoring Methods FIGURE 3.8 Map of the CARB greenhouse gas monitoring network. SOURCE: California Air Resources Board.
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; mass balance inversions. San Juan Basin Smith et al., 2017 Airborne in situ samples for mass balance inversions.
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Uintah Basin Karion et al., 2013 Aircraft-based measurements upwind and downwind of production regions; methane measured using high-precision, high-time-resolution instruments, spectrometry at precise infrared wavelengths; light alkanes analyzed from discrete air samples. Los Angeles Peischl et al., Aircraft-based measurements of methane, carbon dioxide, 2013 carbon monoxide, and C2–C5 alkanes using high-precision, high-time-resolution instruments.
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By using inverse modeling to evaluate bottomup models of emissions, improvements can be made to the bottom-up models, and the result may be better confidence in coupled climate–carbon cycle predictions. Forward Methods for Estimating Emissions from Top-Down Observations The forward approach involves use of bottom-up estimates of emissions and sinks, along with an atmospheric transport model to simulate atmospheric methane that can be compared with observations.
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Inverse Methods for Estimating Emissions from Top-Down Observations While the forward approach uses models of atmospheric transport to convert emissions to atmospheric abundance, the inverse approach converts atmospheric abundance to emissions. Differences between atmospheric methane simulated using atmospheric transport models, first-guess emissions (i.e., "priors")
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the requirement that point measurements be accurately simulated with typically coarse-resolution transport models. Inverse modeling could provide information about variability and trends in atmospheric methane.
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Improving atmospheric transport models will also lead to more accurate estimates of emissions using inverse models. Patra et al.
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Use of Satellite Retrievals in Inverse Models Observations of column-average methane from satellite platforms may significantly increase the spatial and temporal coverage of observational constraints. Satellite data can be used in atmospheric inversions in the same way as ground-based observations.
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For this reason, some recent studies have used regional models that simulate atmospheric transport at resolutions of 10 km or less. The most common strategy involves use of a Lagrangian particle dispersion model, such as the HYSPLIT (Hybrid Single Particle Integrated Trajectory Model; Draxler and Hess, 1997)
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Inverse modeling has also been used to estimate emissions at urban and petroleum and natural gas basin scales. For example, Lamb et al.
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Methane Emissions Estimated emissions for the contiguous United States show a large spread, about 30-50 Tg methane yr–1 for 2000-2012 (Figure 3.9)
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Total methane emissions are shown because estimates of total emissions are more robust while source attribution is less certain due to sparse observations and inaccurate prior estimates. Inversions using space-based retrievals of column average do not appear to significantly differ from those using only in situ observations, at least for the continental United States.
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On the other hand, space-based observation offers the unique capability to spatially map local gradients of atmospheric methane across the globe, revealing source processes and, potentially, emission rates.
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Top-down approaches may also need to use prior emission estimates to constrain solutions due to sparse data coverage, and these may also have biases and errors that lead to biased top-down emission estimates. Both top-down and bottom-up measurements used to estimate emissions can also be spatially and temporally sparse, leading to biases.
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Several teams of investigators did ground surveys downwind of individual sites, collecting site-specific emission estimates for hundreds of petroleum and natural gas sites, including production sites as well as other, downstream sources. All of this bottom-up and top-down information was synthesized into a portrait of 137
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From page 138... ...
This effort found significant day-to-day variability in bottom-up emission estimates, depending on the nature of the planned natural gas production operations occurring on particular days. Because operations at individual sites varied from day to day, there was significant spatial variability in emissions from day to day.
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