Assessment of the impact of the introduction of automated systems for detecting and eliminating methane leaks on atmospheric air quality and climate risks in oil and gas producing regions

Abstract

The study assesses the environmental and climate effects of deploying automated systems for methane leak detection and mitigation at oil and gas facilities, showing that shifting from episodic LDAR surveys to continuous monitoring can reduce emissions and associated risks by multiples; the aim is to develop and validate a methodology for quantitatively estimating the multiplicative effect on emissions, air-quality, and climate-benefit indicators in comparable baseline and intervention scenarios. Materials and methods include a synthetically constructed dataset for a large West Siberian region for 2014-2023 integrating production monitoring (LDAR, incident logs), TROPOMI satellite archives, meteorological data, and equipment reliability specifications; Monte Carlo stochastic modeling (leak occurrence and duration profiles), a parametric model of the automated system (detection probability, time to detection and isolation), agent-based simulation of maintenance crew response, and a Gaussian dispersion model were applied to compute ground-level CH4 concentrations, while avoided emissions were converted to CO2-equivalents using GWP20/GWP100. The results indicate a reduction in annual fugitive emissions from 90,35 to 19,30 thousand t CH4 (-78,64%), including -80,46% at booster compressor stations, -77,71% on trunk gas pipelines, and -75,72% at well pads; the key mechanism is shortening the mean leak duration by more than 40x (from 1,128.7 to 25.15 h) alongside lowering average detection time from 1,080.5 h to 0.45 h and raising the probability of detecting leaks >10 kg/h to 0,998. Air-quality modeling shows a mean annual decrease in ground-level methane concentration by 185.7 ppb within the 500-m impact zone, and avoided emissions amount to ~6 Mt CO2-eq/yr (GWP20); economic effects include a monetized climate benefit (SCC) of $115.3 million/yr and additional revenue from retained gas of $28,4 million/yr with a payback period of 3,8 years. The conclusions confirm the high environmental and investment appeal of continuous monitoring and justify prioritizing the integration of sensors, UAVs, and satellite data with predictive analytics to further reduce leaks and climate risks.