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We report on more than 3 years of measurements of fluxes of methane (CH4), carbon monoxide (CO) and carbon dioxide (CO2) taken by eddy-covariance in central London, UK. Mean annual emissions of CO2 in the period 2012-2014 (39.1 - 2.4 ktons km-2 yr-1) and CO (89 - 16 tons km-2 yr-1) were consistent (within 1 and 5% respectively) with values from the London Atmospheric Emissions Inventory, but measured CH4 emissions (72 - 3 tons km-2 yr-1) were over two-fold larger than the inventory value. Seasonal variability was large for CO with a winter to summer reduction of 69%, and monthly fluxes were strongly anti-correlated with mean air temperature. The winter increment in CO emissions was attributed mainly to vehicle cold starts and reduced fuel combustion efficiency. CO2 fluxes were 33% higher in winter than in summer and anti-correlated with mean air temperature, albeit to a lesser extent than for CO. This was attributed to an increased demand for natural gas for heating during the winter. CH4 fluxes exhibited moderate seasonality (21% larger in winter), and a spatially variable linear anti-correlation with air temperature. Differences in resident population within the flux footprint explained up to 90% of the spatial variability of the annual CO2 fluxes and up to 99% for CH4. Furthermore, we suggest that biogenic sources of CH4, such as wastewater, which is unaccounted for by the atmospheric emissions inventories, make a substantial contribution to the overall budget and that commuting dynamics in and out of central business districts could explain some of the spatial and temporal variability of CO2 and CH4 emissions. To our knowledge, this study is unique given the length of the data sets presented, especially for CO and CH4 fluxes. This study offers an independent assessment of "bottom-up" emissions inventories and demonstrates that the urban sources of CO and CO2 are well characterized in London. This is however not the case for CH4 emissions which are heavily underestimated by the inventory approach. Our results and others point to opportunities in the UK and abroad to identify and quantify the "missing" sources of urban methane, revise the methodologies of the emission inventories and devise emission reduction strategies for this potent greenhouse gas. [ABSTRACT FROM AUTHOR]

We report on more than three years of measurements of fluxes of methane (CH4), carbon monoxide (CO) and carbon dioxide (CO2) taken by eddy-covariance in central London, UK. Inter-annual variability in the period 2012-2014 ranged from 36.3 to 40.7 ktons km-2 y-1 for CO2, and from 69 to 75 tons km-2 y-1 for CH4. Mean annual emissions of CO2 (39.1 ± 2.4 ktons km-2 y-1) and CO (89 ± 16 tons km-2 y-1) were consistent (within 1% and 5% respectively) with values from the London Atmospheric Emissions Inventory, but measured CH4 (72 ± 3 tons km-2 y-1) was over two-fold larger than the inventory value. Seasonal variability was large for CO with a winter to summer reduction of 69%. Monthly fluxes of CO were strongly anti-correlated with mean air temperature, and the winter emissions accounted for 45% of the annual budget. The winter increment in CO emissions was attributed mainly to vehicle cold starts and reduced fuel combustion efficiency. CO2 fluxes were 33% higher in winter and anti-correlated with mean air temperature, albeit to a lesser extent than for CO. This was attributed to an increased demand for natural gas for heating during the winter. Seasonality in CH4 fluxes was moderate (21% larger in winter) and linear correlation with air temperature was only statistically significant for certain wind sectors (N, NE, E and W), which was also the case for CO2. Differences in resident population within the flux footprint explained ca. 90% variability by wind direction in annual CO2 fluxes and 99% for CH4 (wind sectors excluded from linear regressions: S for CO2; S, SE and E for CH4). Seasonality and proportionality of emissions with respect to population in the outlying wind sectors (S, SE and E) might be masked by constant sources of CO2 and CH4, perhaps of industrial or biogenic origin. To our knowledge, this study is unique given the long-term, continuous dataset of urban CH4 fluxes analysed. [ABSTRACT FROM AUTHOR]

We report on more than three years of measurements of fluxes of methane (CH4), carbon monoxide (CO) and carbon dioxide (CO2) taken by eddy-covariance in central London, UK. Inter-annual variability in the period 2012-2014 ranged from 36.3 to 40.7 ktons km-2 y-1 for CO2, and from 69 to 75 tons km-2 y-1 for CH4. Mean annual emissions of CO2 (39.1 ± 2.4 ktons km-2 y-1) and CO (89 ± 16 tons km-2 y-1) were consistent (within 1% and 5% respectively) with values from the London Atmospheric Emissions Inventory, but measured CH4 (72 ± 3 tons km-2 y-1) was over two-fold larger than the inventory value. Seasonal variability was large for CO with a winter to summer reduction of 69%. Monthly fluxes of CO were strongly anti-correlated with mean air temperature, and the winter emissions accounted for 45% of the annual budget. The winter increment in CO emissions was attributed mainly to vehicle cold starts and reduced fuel combustion efficiency. CO2 fluxes were 33% higher in winter and anti-correlated with mean air temperature, albeit to a lesser extent than for CO. This was attributed to an increased demand for natural gas for heating during the winter. Seasonality in CH4 fluxes was moderate (21% larger in winter) and linear correlation with air temperature was only statistically significant for certain wind sectors (N, NE, E and W), which was also the case for CO2. Differences in resident population within the flux footprint explained ca. 90% variability by wind direction in annual CO2 fluxes and 99% for CH4 (wind sectors excluded from linear regressions: S for CO2; S, SE and E for CH4). Seasonality and proportionality of emissions with respect to population in the outlying wind sectors (S, SE and E) might be masked by constant sources of CO2 and CH4, perhaps of industrial or biogenic origin. To our knowledge, this study is unique given the long-term, continuous dataset of urban CH4 fluxes analysed. [ABSTRACT FROM AUTHOR]