| Summary: | Aggressive reductions of oil and gas sector methane, a potent greenhouse gas, have been proposed in Canada. Few large-scale measurement studies have been conducted to confirm a baseline. This study used a vehicle-based gas monitoring system to measure fugitive and vented gas emissions across Lloydminster (heavy oil), Peace River (heavy oil/bitumen), and Medicine Hat (conventional gas) developments in Alberta, Canada. Four gases (CO 2 , CH 4 , H 2 S, C 2 H 6 ), and isotopic δ 13 C CH 4 were recorded in real-time at 1 Hz over a six-week field campaign. A point-source gaussian plume dispersion model was used to quantify emissions rates. We sampled 1,299 well pads, containing 2,670 unique wells and facilities, in triplicate. Geochemical emission signatures of fossil fuel-sourced plumes were identified and attributed to nearby, upwind oil and gas well pads. Emission occurrences and rates were highest in Lloydminster, where 40.8% of sampled well pads were estimated to be emitting methane-rich gas above our minimum detection limits (µ = 9.73 m 3 d -1 ). Of the well pads we found to be emitting in Lloydminster, an estimated 40.2% emitted above the threshold in which emissions mitigation under federal regulations would be required, suggesting government estimates of infrastructure affected by incoming regulations may be low. Comparing emission intensities with available Canadian-based research suggests good general agreement between studies, regardless of the measurement methodology used for detection and quantification. This study also demonstrates the effectiveness in applying a gaussian dispersion model to continuous mobile-sourced emissions data as a first-order leak detection and repair screening methodology for meeting regulatory compliance. Funding provided by: Petroleum Technology Alliance of Canada (Alberta Upstream Petroleum Research Fund) Crossref Funder Registry ID: Award Number: Funding provided by: Atlantic Canada Opportunities Agency (Atlantic Innovation Fund) Crossref Funder Registry ID: Award Number:
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