Improving Characterization of Anthropogenic Methane Emissions in the United States (2018) / Chapter Skim
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4 Addressing Uncertainties in Anthropogenic Methane Emissions
4 Addressing Uncertainties in Anthropogenic Methane Emissions
Pages 139-170
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From page 139... ...
Overall, the major drivers for uncertainty in atmospheric methane emission estimation methods are • lack of accurate activity data throughout all the major source categories; • deficiencies in sampling procedures, resulting in unrepresentativeness of the samples and therefore resulting in unrepresentative emission factors; • poor understanding of temporal and spatial variability of emissions, including climate-driven feedbacks; • presence of sources that are not accounted for; • presence of episodic high-emitting sources; • inadequate spatial coverage of observational networks; • difficulty using top-down approaches in attributing emissions to particular sources; • inherent uncertainties associated with methods utilizing atmospheric trans port models; and • incorrect assumptions used in calculations and models of methane emissions and atmospheric concentrations. Additionally, uncertainty arises due to deficiencies in instruments and techniques used to measure methane emissions, which were discussed in Chapter 3.
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From page 140... ...
. Enteric Fermentation and Manure Management The uncertainties associated with methane emissions from enteric fermentation and manure management are generally due to the accuracy of the activity data and the equations used to estimate emissions.
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. For manure management, uncertainties exist in the activity data and emission factors.
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gas systems (−24% to +149%) a Sparse activity data yet abundance of • Supplementing the Greenhouse Gas • emission sources.
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Uncertain national activity data (annual • Improved collection and statistical analysis • (–9% to +9%) a landfilled waste)
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From page 144... ...
Relatively high uncertainties for • Updated and more reliable gas content • Abandoned mines: abandoned underground mines and data need to replace those currently in use 0.26 (0.21-0.31) surface mines where emissions are to improve surface mine estimates.
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From page 145... ...
NOTES: It is difficult to make direct comparisons between various uncertainty estimates because of different methodological approaches and data sources. This table includes national-scale estimates of methane emissions from major sources; regional estimates are discussed in the text that follows this table.
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From page 146... ...
. The uncertainty ranges indicated by vertical lines represent variations of 95 percent confidence intervals as determined by the EPA.
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From page 147... ...
In addition to uncertainties in emission estimates due to high-emitting sources, there is uncertainty related to the activity data estimates used in the GHGI for key emission components (e.g., count of the different types of pneumatic controllers or condensate tanks)
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. In the past several years, there has been a significant effort to understand and quantify the uncertainties of methane emissions from petroleum and natural gas systems, and much has been learned about the top emission sources.
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and low seasonal methane oxidation rates. The highest-emitting sites shown in the figure using CALMIM corresponded primarily to Central Valley and desert sites with deficient soil moisture and daily temperatures exceeding optimal oxidation conditions.
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For CALMIM, the highest-emitting sites are characterized by large areas of thinner intermediate cover soil and lower seasonal oxidation. See also discussion in Chapter 3.
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As long as the equipment is functioning well and the measurements are taken frequently, methane emission estimates are reliable. However, the position of the sensor with respect to the cross section of the entry and how the measurements are taken can be critical.
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Post-mining emission factors currently assume 32.5 percent of in situ gas content (same for surface and underground mines; EPA, 2005) , following a study on British coals (Creedy, 1993)
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Identifying and quantifying unaccounted-for emissions through multiscale measurement campaigns is critical to addressing uncertainties in emission inventories and to improving understanding of methane emissions in general. Overall Source Category Conclusions Based on the source category–specific discussion about uncertainties, the Committee concludes that Each source category has a wide range of uncertainties for methane emission esti ates: sparse activity data and limited emission measurements are the m rimary reason for uncertainties in most source categories.
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From page 154... ...
network is still very sparse. At continental scales, the presence of strong local sources and atmospheric variability requires dense and frequent sampling to produce accurate and precise emission estimates.
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From page 155... ...
simulating the shallow nocturnal boundary layer, and filtering the data for this biases sampling toward particular times of the day. Uncertainties in current top-down methane emission estimates at global and continental scales are increased by sparse surface observation networks that do not capture the full spatial variability in emissions.
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From page 156... ...
Continental methane mole fraction measurements have been used with mass balance approaches to estimate emissions for continental-scale regions. Upwind and downwind observations are required for this approach as is accurate knowledge of winds and atmospheric stability, which are often not well quantified.
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A combination of ground-based background stations to provide accu rate methane measurement in pristine air and satellite data to quantify strong local and regional gradients of methane has the potential to improve spatial and temporal coverage of measurements. Top-down measurements using aircraft have also been used to estimate emissions at the spatial scale of a fossil fuel basin, but these measurements, while having a fine spatial resolution, are limited in temporal coverage.
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From page 158... ...
methane emissions. Different choices of prior emission estimates and their associated uncertainties is a driver for disagreement among inversions.
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At all scales, uncertainties in top-down methane emission estimates arise due to uncertainties in atmospheric transport models.
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It is hoped that the end result will be better understanding of how anthropogenic and natural emissions of methane evolve over time to influence the chemistry and radiative balance of the atmosphere. EMISSION INVENTORY IMPROVEMENT STUDIES: DESIGN AND DATA ANALYSES Improvements in the accuracy and precision of methane emission estimates will be maximized through the use of both top-down and bottom-up measurements.
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In addition, other variables that affect methane emissions need to be collected, including temperature, pH, and wind speed, in order to develop prediction equations that are meaningful across a range of management and climatic conditions.
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From page 162... ...
Although there were large uncertainties associated with these estimates because of small sample sizes, tails were estimated to be heavier than those of other known heavy-tailed phenomena, such as crop losses and income distribution. The presence of high-emitting sources contributes to increased uncertainty in mean methane emission estimates.
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From page 163... ...
When emission data indicate a small number of high-emitting sources, uncertainty about the mean emission rate could be reduced by employing sampling strategies designed to better quantify the contribution from these high-emitting sources. Careful consideration of any assumptions underlying the statistical analysis is warranted and, when in doubt, selection of statistical methods with fewer distributional assumptions is optimal.
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From page 164... ...
Recent top-down and bottom-up studies have highlighted the importance of site access and collaboration with operators to improve emission estimates and provide a mechanistic understanding of emissions (e.g., Bell et al., 2017; Robertson et al., 2017; Schwietzke et al., 2017; Yacovitch et al., 2017)
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Source Attribution Top-down measurements often result in total emission estimates; attributing these emissions to specific sources using the top-down approach can be done using forward and inverse models, as described in the preceding section. Molecular and isotopic tracers can also provide useful constraints on sources.
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From page 166... ...
Ethane has been used as a marker for petroleum and natural gas emissions, typically assuming that all petroleum and gas sources in a region will have a characteristic ethane-to-methane ratio (Franco et al., 2015, 2016; Hausmann et al., 2016; Helmig et al., 2016; Smith et al., 2015)
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From page 167... ...
, as well as historic methane seepages, there may be overlapping and currently unknown seepages that may contribute to observed atmospheric signatures. Although the information provided by isotopes and molecular tracers can be limited by uncertainty related to trace species due to the lack of unique tracers for individual sources, these measurements can still provide significant information on source attribution.
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From page 168... ...
A ircraft-based mass balance approaches for estimating methane emissions are likely to exhibit temporal sampling issues because the timing of the aircraft measurements is not randomized. To study, for example, emissions from petroleum- and natural-gasproducing regions and livestock emissions, measurements are made for specific short time periods and only when conditions are conducive to the methodology (typically midday)
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From page 169... ...
are needed to better account for temporal and spatial variability in emissions. Bottom-up studies would be more rigorous with the assembly of comprehensive up-to-date spatially and temporally resolved emission estimates from all source categories, including emissions currently "unaccounted for" in the GHGI.
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