Methods for Spatial Extrapolation of Methane Measurements in Constructing Regional Estimates from Sample Populations

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Energy Sector Analysis

Background:

• Methane emission estimates for oil and gas facilities often rely on extrapolating data from a limited sample population to larger regions.
• The inherent variability and intermittency of methane emissions make it challenging to ensure sample populations are representative.
• Comparing basin-level emission estimates with basin-level observations is a common but potentially error-prone practice.

Purpose of the Study:

• To develop a framework for more accurate extrapolation of methane emission estimates from oil and gas facilities.
• To introduce and validate a new metric, the capture ratio, for assessing the representativeness of emission sample populations.
• To improve the accuracy of methane emission inventories and their uncertainty bounds.

Main Methods:

• Development of an extrapolation framework using a case study of an operator in the Green River Basin.
• Identification and application of the 'capture ratio' metric, based on the skewness of source-level emissions.
• Analysis of the correlation between the capture ratio and extrapolation error.

Main Results:

• A strong correlation was found between the capture ratio and extrapolation error.
• The developed framework demonstrated a method to mitigate errors in emission inventory development.
• Understanding source-level emission distributions is key to improving extrapolation accuracy.

Conclusions:

• The proposed framework and capture ratio metric can significantly inform the selection and extrapolation of site measurements for methane emission inventories.
• This approach helps in establishing more reliable uncertainty bounds for emission estimates.
• The findings support better assessment of inventory consistency with independent large-scale observations.