Exploiting stagnant conditions to derive robust emission ratio estimates for CO<sub>2</sub>, CO and volatile organic compounds in Paris

Abstract

We propose an approach to estimate urban emission ratios that takes advantage of the enhanced local urban signal in the atmosphere at low wind speed. We apply it to estimate monthly ratios between CO 2 , CO and some VOCs from several atmospheric concentration measurement datasets acquired in the centre of Paris between 2010 and 2014. We find that this approach is not very sensitive to the regional background level definition and that, in the case of Paris, it samples all days (weekdays and weekends) and all hours of the day evenly. A large seasonal variability of the CO / CO 2 ratio in Paris is shown, with a difference of around 60 % between the extreme values and a strong anti-correlation (r 2 = 0.75) with atmospheric temperature. The comparison of the ratios obtained for two short measurement campaigns conducted in two different districts and two different periods (autumn and winter) shows differences ranging from −120 to +63 %. A comparison with a highly resolved regional emission inventory suggests some spatial variations of the ratio within the city.Published by Copernicus Publications on behalf of the European Geosciences Union.

Atmospheric radiocarbon measurements to quantify CO<sub>2</sub> emissions in the UK from 2014 to 2015

“…Wenger et al: Atmospheric radiocarbon measurements to quantify CO 2 emissions merical Atmospheric dispersion Modelling Environment) developed by the UK Met Office (Jones et al, 2007). Hypothetical particles are released into the model atmosphere at a rate of 10 000 per hour at the location of the observation site and transported backward in time for 30 d. It is assumed that when a particle resides in the lowest 0-40 m of the model atmosphere, pollution from ground-based emission sources is added to the air parcel (Arnold et al, 2018;Manning et al, 2011). The particle residence times in this surface layer are integrated over the 30 d simulation to calculate a "footprint" of each measurement that quantifies the sensitivity of the observation to a grid surrounding the measurement site (Manning et al, 2011).…”

“…This 14 CO 2 emissions map was created with the highestfrequency data available from each nuclear site. Monthly atmospheric emission data were provided by the two operators of the 10 UK nuclear power plants; EDF (Électricité de France) and Magnox Ltd. Data for the other 17 UK nuclear sites were taken from the annual Radioactivity in Food and the Environment RIFE, 1995-2016(Environment Agency, Natural Resources Wales, 2017. The emissions from other European nuclear power plants were sourced from annual environmental reports if available (France, Germany); otherwise, parameterized emissions were calculated according to Graven and Gruber (2011).…”

Diurnal, synoptic and seasonal variability of atmospheric CO<sub>2</sub> in the Paris megacity area

“…However, we could not separate the anthropogenic and biospheric CO 2 signals, nor the role of the different emission sectors. This highlights the need for regular carbon isotopic measurements of CO 2 at the regional network stations, together with measurements of anthropogenic co-emitted species such as CO, NO x , black car-bon and volatile organic compounds (e.g., Lopez et al, 2013;Ammoura et al, 2014Ammoura et al, , 2016. Finally, we show that ancillary data such as local meteorological data and parameters defining the structure of the atmosphere such as the ABL height are very important to understand the observed CO 2 variability.…”

“…Large projects developed in Indianapolis (IN-FLUX; http://influx.psu.edu; e.g., Turnbull et al, 2015;Lauvaux et al, 2016), Boston (http://www.bu.edu/today/2013/ the-climate-crisis-measuring-boston-carbon-metabolism/; McKain et al, 2012), Los Angeles (Megacities; http://megacities.jpl.nasa.gov/portal/; e.g., Newman et al, 2013;Verhulst et al, 2017) and, in our case, Paris (CO 2 -MegaParis; http://co2-megaparis.lsce.ipsl.fr; e.g., Xueref-Remy et al, 2012;Lac et al, 2013;Bréon et al, 2015;Ammoura et al, 2016;Staufer et al, 2016). These projects rely on the development of urban atmospheric in situ CO 2 monitoring networks that should ideally include, all along the dominant wind paths, (1) regional stations upwind of the city to characterize the regional background CO 2 dry air mole fraction (i.e., without having the impact of the regional emissions -regional is here defined within a radius of ∼ 100 km around the center of Paris) and (2) regional stations in the city and downwind of it (that will integrate both the background signal and the peri-urban/urban ones).…”

“…Regional background stations (∼ 100 km) seem to be much better suited for urban regional studies in Paris and elsewhere in the European continent. Several methods are available to extract a background signal from a time series (e.g., Ruckstuhl et al, 2012;Ammoura et al, 2016). Quantifying precisely the Paris background signals values as well as the Paris plume and its variability requires a dedicated analysis that is outside the scope of the present paper: it will be specifically addressed within another dedicated study.…”