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Eddy covariance measurements highlight sources of nitrogen oxide emissions missing from inventories for central London

Drysdale, W. S. ORCID:, Vaughan, A. R. ORCID:, Squires, F. A. ORCID:, Cliff, S. J. ORCID:, Metzger, S. ORCID:, Durden, D. ORCID:, Pingintha-Durden, N., Helfter, C. ORCID:, Nemitz, E. ORCID:, Grimmond, C. S. B. ORCID:, Barlow, J., Beevers, S., Stewart, G., Dajnak, D., Purvis, R. M. ORCID: and Lee, J. D. ORCID: (2022) Eddy covariance measurements highlight sources of nitrogen oxide emissions missing from inventories for central London. Atmospheric Chemistry and Physics, 22 (14). pp. 9413-9433. ISSN 1680-7316

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To link to this item DOI: 10.5194/acp-22-9413-2022


During March–June 2017 emissions of nitrogen oxides were measured via eddy covariance at the British Telecom Tower in central London, UK. Through the use of a footprint model the expected emissions were simulated from the spatially resolved National Atmospheric Emissions Inventory for 2017 and compared with the measured emissions. These simulated emissions were shown to underestimate measured emissions during the daytime by a factor of 1.48, but they agreed well overnight. Furthermore, underestimations were spatially mapped, and the areas around the measurement site responsible for differences in measured and simulated emissions were inferred. It was observed that areas of higher traffic, such as major roads near national rail stations, showed the greatest underestimation by the simulated emissions. These discrepancies are partially attributed to a combination of the inventory not fully capturing traffic conditions in central London and both the spatial and temporal resolution of the inventory not fully describing the high heterogeneity of the urban centre. Understanding of this underestimation may be further improved with longer measurement time series to better understand temporal variation and improved temporal scaling factors to better simulate sub-annual emissions.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:107341
Publisher:Copernicus Publications


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