The 2015 Paris agreement aims to cut greenhouse gas emissions and keep global temperature rise below 2 °C above pre-industrial levels. Reducing CH4 emissions from leaking pipelines presents a relatively achievable objective. While walking and driving surveys are commonly used to detect leaks, the detection probability (DP) is poorly characterized. This study aims to investigate how leak rates, survey distance and speed, and atmospheric conditions affect the DP in controlled belowground conditions with release rates of 0.5-8.5 g min-1. Results show that DP is highly influenced by survey speed, atmospheric stability, and wind speed. The average DP in Pasquill-Gifford stability (PG) class A is 85% at a low survey speed (2-11 mph) and decreases to 68%, 63%, 65%, and 60% in PGSC B/C, D, E/F, and G respectively. It is generally less than 25% at a high survey speed (22-34 mph), regardless of stability conditions and leak rates. Using the measurement data, a validated DP model was further constructed and showed good performance (R2: 0.76). The options of modeled favorable weather conditions (i.e., PG stability class and wind speed) to have a high DP (e.g., >50%) are rapidly decreased with the increase in survey speed. Walking survey is applicable over a wider range of weather conditions, including PG stability class A to E/F and calm to medium winds (0-5 m s-1). A driving survey at a low speed (11 mph) can only be conducted under calm to low wind speed conditions (0-3 m s-1) to have an equivalent DP to a walking survey. Only calm wind conditions in PG A (0-1 m s-1) are appropriate for a high driving speed (34 mph). These findings showed that driving survey providers need to optimize the survey schemes to achieve a DP equivalence to the traditional walking survey.
Keywords: Atmospheric stability; Detection probability; Methane emissions; Mobile survey; Pipeline leakage.
Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.