Abstract

Assessment of bottom-up greenhouse gas emissions estimates through independent methods is needed to demonstrate whether reported values are accurate or if bottom-up methodologies need to be refined. We report atmospheric methane (CH4) mole fractions and δ13CH4 measurements from Imperial College London since early 2018 using a Picarro G2201-i analyser. Measurements from March 2018 to October 2020 were compared to simulations of CH4 mole fractions and δ13CH4 produced using the NAME dispersion model coupled with the UK National Atmospheric Emissions Inventory, UK NAEI, and the global inventory, EDGAR, with model spatial resolutions of ~2 km, ~10 km, and ~25 km. Observed mole fractions were underestimated by 30–35 % in the NAEI simulations. In contrast, a good correspondence between observations and EDGAR simulations was seen. There was no correlation between the measured and simulated δ13CH4 values for either NAEI or EDGAR, however, suggesting the inventories’ sectoral attributions are incorrect. On average, natural gas sources accounted for 20–28 % of the above background CH4 in the NAEI simulations, and only 6–9 % in the EDGAR simulations. In contrast, nearly 84 % of isotopic source values calculated by Keeling plot analysis (using measurement data from the afternoon) of individual pollution events were higher than −45 ‰, suggesting the primary CH4 sources in London are actually natural gas leaks. The simulation-observation comparison of CH4 mole fractions suggests that total emissions in London are much higher than the NAEI estimate (0.04 Tg CH4 yr−1) but close to, or slightly lower than the EDGAR estimate (0.10 Tg CH4 yr−1). However, the simulation-observation comparison of δ13CH4 and the Keeling plot results indicate that emissions due to natural gas leaks in London are being underestimated in both the UK NAEI and EDGAR.

Highlights

  • Urban areas are hotspots of greenhouse gas (GHG) emissions accounting for 70 % of anthropogenic GHG emissions (IPCC, 2014), making them important targets for GHG emissions mitigation (Duren and Miller, 2012; Hopkins et al, 2016)

  • Measurements from March 2018 to October 2020 were compared to simulations of CH4 mole fractions and δ13CH4 produced using the NAME dispersion model coupled with the UK National Atmospheric Emissions Inventory, UK NAEI, and the global inventory, Emissions Database for Global Atmospheric Research (EDGAR), with model spatial resolutions of ~2 km, ~10 km, and ~25 km

  • 280 We considered four combinations of footprints coupled with anthropogenic emissions data: (i) the 25 km footprints combined with the EDGAR emissions (EDGAR-25km); (ii) the 10 km footprints nested in the 25 km footprints combined with the EDGAR emissions (EDGAR-10km); (iii) the 25 km footprints combined with the UK NAEI emissions for the UK and the EDGAR emissions for the rest of the domain (NAEI-25km); and (iv) the 2 km footprints nested in the 10 km and 25 km footprints combined with the UK NAEI emissions for the UK and EDGAR for the rest of the domain (NAEI-2km)

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Summary

Introduction

Urban areas are hotspots of greenhouse gas (GHG) emissions accounting for 70 % of anthropogenic GHG emissions (IPCC, 2014), making them important targets for GHG emissions mitigation (Duren and Miller, 2012; Hopkins et al, 2016). In the 2017 UK NAEI estimates, CH4 from the 35 waste sector is the dominant source in London accounting for 52 % of London’s CH4 emissions, with fossil-fuel sources of methane (e.g. fugitive gas emissions) making up 41 % of London’s CH4 emissions (NAEI, 2017). Some source sectors are composed of multiple sources with different isotopic source signatures, for example the 230 waste sector includes landfill sites and waste water treatment facilities. In this case the weighted average of the different sources, based on the UK emissions reported to the UNFCCC (https://di.unfccc.int/comparison_by_category), were used to calculate the isotopic source signature of that source sector

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