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Researchers have utilized Other Test Method (OTM) 33A to quantify methane emissions from natural gas infrastructure. Historically, errors have been reported based on a population of measurements compared to known controlled releases of methane. These errors have been reported as 2σ errors of ±70%. However, little research has been performed on the minimum attainable uncertainty of any one measurement. We present two methods of uncertainty estimation. The first was the measurement uncertainty of the state-of-the-art equipment, which was determined to be ±3.8% of the estimate. This was determined from bootstrapped measurements compared to controlled releases. The second approach of uncertainty estimation was a modified Hollinger and Richardson (H&R) method which was developed for quantifying the uncertainty of eddy covariance measurements. Using a modified version of this method applied to OTM 33A measurements, it was determined that uncertainty of any given measurement was ±17%. Combining measurement uncertainty with that of stochasticity produced a total minimum uncertainty of 17.4%. Due to the current nature of stationary single-sensor measurements and the stochasticity of atmospheric data, such uncertainties will always be present. This is critical in understanding the transport of methane emissions and indirect measurements obtained from the natural gas industry. 

Other test method (OTM) 33A has been used to quantify emissions from natural gas sites since it was introduced by the Environmental Protection Agency (EPA). The method relies on point source Gaussian (PSG) assumptions to estimate emissions rates from a targeted site or source. However, the method often results in low accuracy (typically ±70%, even under conducive conditions). These accuracies were verified with controlled-release experiments. Typically, controlled releases were performed for short periods (15–20 min) under atmospheric conditions that were ideal for effective plume transport. We examined three methane release rates from three distances over various periods of time ranging from seven hours to seven days. Data were recorded continuously from a stationary tower. Atmospheric conditions were highly variable and not always conducive to conventional OTM 33A calculations. OTM 33A estimates were made for 20-min periods when the mean wind direction corresponded to ±90° of the direction from the controlled release to the tower. Further analyses were performed by varying the frequency of the data, the length of the individual OTM 33A periods and the size of the wind angle used to filter data. The results suggested that different (than conventionally used) period lengths, wind filters, data acquisition frequencies and data quality filters impacted the accuracy of OTM 33A when applied to long term measurements.