addressing uncertainty in oil and natural gas industry greenhouse

when planning the compilation of an emissions inventory and could address as part of emission inventory
assurance processes (API/IPIECA, OGP, 2003).
Adhering to appropriate sampling, measurement, and estimation procedures – with applicable quality
control and quality assurance measures – can help minimize uncertainties. Nonetheless, it is the nature of
the measurement process that makes it impossible to measure a physical quantity without error.
It is this collection of measurement errors and approximations that contribute largely to overall emission
inventory range of uncertainty. Emission inventory development and uncertainty analysis could be
viewed as components of a quality improved management process. Once estimates of uncertainty are
developed, the inventory preparer could review the inventory and target the most significant sources –
those exhibiting the largest range of uncertainty – for more research and refinement. Table 2-1 provides
an overview of selected methods recommended by the U.S. Environmental Protection Agency (EPA) for
qualitative and quantitative estimation of emissions ranges of uncertainty. The uncertainties associated
with natural variability inherent to the emission process and its underlying data can be assessed by
statistical analysis methods. Further discussion and specific procedures for statistical quantification of
uncertainty intervals are provided in Section 4.0.
Table 2-1. Overview of Methods Used to Estimate Emissions Uncertainty a
METHODOLOGY
Qualitative
Discussion
−
−
DESCRIPTION OF METHOD
Sources of uncertainty are listed and discussed.
General direction of bias and relative magnitude of imprecision are given
if known.
LEVEL OF
EFFORT
Low
Subjective Data
Quality Ratings
−
Subjective rankings based on professional judgment are assigned to each
emission factor or parameter.
Low
Data Attribute
Rating System
(DARS)
−
Numerical values representing relative uncertainty are assigned through
objective methods.
Medium
Expert
Estimation
Method
−
−
−
Experts estimate emission distribution parameters (i.e., mean, standard
deviation, and distribution type).
Simple analytical and graphical techniques are then used to estimate
confidence limits from the assumed distributional data.
In the Delphi method, expert judgment is used to estimate uncertainty
directly.
Medium
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