Characterizing detection probabilities of advanced mobile leak surveys

Abstract

Advanced leak detection (ALD) to survey local natural gas distribution systems has reached a point in technological maturity where new federal regulations will require its use in compliance surveys. Because most of these deployments are conducted by commercial providers, there has been little publicly available data documenting characteristics of the underlying methane (CH4) plumes that are the core features measured in ALD surveys. Here, we document key features of CH4 plumes measured in ALD surveys of 15 U.S. metropolitan areas where we had deployed high-sensitivity CH4 analyzers on Google Street View cars. Our analysis reveals that CH4 concentration enhancements from CH4 sources exhibit high temporal variability, often differing by more than 10-fold among repeated observations. This variability introduces challenges for estimating source emission rates because the same source can appear to be large on one drive-by and small on the next. Additionally, the frequency distribution of CH4 enhancements from a given source generally has a strong positive skew that can lead to overestimation of leak size. The magnitude of CH4 enhancements from a source measured with a mobile sensor can also change quickly over time, as indicated by decreasing temporal correlation between mobile measurements longer than an approximately hourly time scale. To manage the uncertainty, we demonstrate how additional survey effort can help overcome this variability and instability to allow discrimination among the wide range of leak sizes. We quantify the probability of source detection, finding that it increases with estimated leak size. Combining these results, we develop a simulation that demonstrates the potential for ALD to detect leaks and quantify emissions as a function of sampling (driving) effort. Our results suggest that five to eight drives of each roadway in a target area would detect >90% of leaks and provide adequate emissions quantification for repair/replacement prioritization.

Ground-Based Mobile Measurements to Track Urban Methane Emissions from Natural Gas in 12 Cities across Eight Countries

“…As an additional caveat for the data collected in our 12 cities, some of the high emission rate estimates might be the result of poor sampling statistics for these locations, as a consequence of the strategy of short-term wide-area surveys with infrequent revisits (e.g., Munich, DE, and Birmingham, UK), which can lead to an overall overestimate in the emission rate . We note that cities that have been surveyed more completely and frequently (e.g., Toronto, CA, and London, UK) should be less susceptible to these high biases, because unusually high local methane enhancements that can lead to very high emission rate estimates will average out when combined with data from multiple survey days.…”

“…A disadvantage of this approach is that many streets were surveyed only once or twice. Controlled release experiments , and frequent passages of the same leak location − have shown that emission estimates from a single detected source can vary by more than an order of magnitude between individual passages and that emission rate estimates based on infrequent visits are biased high. A simple explanation for changing local enhancements is changes in wind speed and direction.…”

Intercomparison of detection and quantification methods for methane emissions from the natural gas distribution network in Hamburg, Germany

“…In recent years, mobile measurement methods using vehicles with fast and high-precision laser instrumentation have been established for leak detection and emission quantification in numerous cities (Jackson et al, 2014;von Fischer et al, 2017;Weller et al, 2018;Keyes et al, 2020;Ars et al, 2020;Maazallahi et al, 2020b;Defratyka et al, 2021;Luetschwager et al, 2021;Fernandez et al, 2022). In situ measurements of atmospheric CH 4 from mobile vehicles are used to pinpoint and quantify CH 4 emission sources at street level in urban areas.…”

Environmental Injustices of Leaks from Urban Natural Gas Distribution Systems: Patterns among and within 13 U.S. Metro Areas

“…We explore variations in the frequency of leak indications derived from our previous urban methane surveys, where we used high-sensitivity methane analyzers deployed in Google Street View cars . The technological approach for gathering this leak indication data, now commonly known as advanced leak detection (ALD) , has been identified as a best practice for finding natural gas leaks and estimating their size . Our survey data included atmospheric methane concentrations in 13 U.S. metro areas, covering neighborhoods that are home to 4.5 million people.…”