Radiocarbon (14C) is a powerful tracer of fossil emissions because fossil fuels are entirely depleted in 14C, but observations of 14CO2 and especially 14CH4 in urban regions are sparse. We present the first observations of 14C in both methane (CH4) and carbon dioxide (CO2) in an urban area (London) using a recently developed sampling system. We find that the fossil fraction of CH4 and the atmospheric concentration of fossil CO2 are consistently higher than simulated values using the atmospheric dispersion model NAME coupled with emission inventories. Observed net biospheric uptake in June-July is not well correlated with simulations using the SMURF model with NAME. The results show the partitioning of fossil and biospheric CO2 and CH4 in cities can be evaluated and improved with 14C observations when the nuclear power plants influence is negligible.

Atmospheric trace gas measurements can be used to independently assess national greenhouse gas inventories through inverse modelling. Here, atmospheric nitrous oxide (N2O) measurements made in the United Kingdom (U.K.) and Republic of Ireland are used to derive monthly N2O emissions for 2013-2022 using two different inverse methods. We find mean U.K. emissions of 90.5±23.0 (1\(\sigma\)) and 111.7±32.1 (1\(\sigma\)) Gg N2O yr-1 for 2013-2022, and corresponding trends of -0.68±0.48 (1\(\sigma\)) Gg N2O yr-2 and -2.10±0.72 (1\(\sigma\)) Gg N2O yr-2, respectively for the two inverse methods. The U.K. National Atmospheric Emissions Inventory (NAEI) reported mean N2O emissions of 73.9 Gg N2O yr-1 across this period, which is 14-33% smaller than the emissions derived from atmospheric data. We infer a pronounced seasonal cycle in N2O emissions, with a peak occurring in the spring and a second smaller peak in the late summer for certain years. The springtime peak has a long seasonal decline that contrasts with the sharp rise and fall of N2O emissions estimated from the bottom-up U.K. Emissions Model (UKEM). Bayesian inference is used to minimize the seasonal cycle mismatch between the average top-down (atmospheric data-based) and bottom-up (process model and inventory-based) seasonal emissions at a sub-sector level. Increasing agricultural manure management and decreasing synthetic fertilizer N2O emissions reduces some of the discrepancy between the average top-down and bottom-up seasonal cycles. Other possibilities could also explain these discrepancies, such as missing emissions from NH3 deposition, but these require further investigation.

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. Previous studies of measurements of atmospheric methane (CH4) in London revealed that inventories substantially underestimated the amount of natural gas CH4 1,2. We report atmospheric CH4 concentrations and δ13CH4 measurements from Imperial College London since early 2018 using a Picarro G2201-i analyser. Measurements from May 2019-Feb. 2020 were compared to the values simulated using the dispersion model NAME coupled with the UK national atmospheric emissions inventory, NAEI, and the global inventory, EDGAR, for emissions outside the UK. Simulations of CH4 concentration and δ13CH4 values were generated using nested NAME back-trajectories with horizontal spatial resolutions of 2 km, 10 km and 30 km. Observed concentrations were underestimated in the simulations by 12 %, and there was no correlation between the measured and simulated δ13CH4 values. CH4 from waste sources and natural gas comprised of 32.1 % and 27.5 % of the CH4 added by regional emissions. To estimate the isotopic source signatures for individual pollution events, an algorithm was created for automatically analysing measurement data by using the Keeling plot approach. Over 70 % of source signatures had values higher than -50 ‰, suggesting large amounts of natural gas CH4. The analyses based on model-data comparison of δ13CH4 and on Keeling plot source signature emission both indicate that emissions due to natural gas leaks in London are being under-reported in the NAEI. These results suggest that estimates of CH4 emissions in urban areas need to be revised in the CH4 emissions inventories. 1 Helfter, C. et al. (2016), Atmospheric Chemistry and Physics, 16(16), pp. 10543-10557 2 Zazzeri, G. et al. (2017), Scientific Reports, 7(1), pp. 1-13