Abstract

Abstract. Most of the global fossil fuel CO2 emissions arise from urbanized and industrialized areas. Bottom-up inventories quantify them but with large uncertainties. In 2010–2011, the first atmospheric in situ CO2 measurement network for Paris, the capital of France, began operating with the aim of monitoring the regional atmospheric impact of the emissions coming from this megacity. Five stations sampled air along a northeast–southwest axis that corresponds to the direction of the dominant winds. Two stations are classified as rural (Traînou – TRN; Montgé-en-Goële – MON), two are peri-urban (Gonesse – GON; Gif-sur-Yvette – GIF) and one is urban (EIF, located on top of the Eiffel Tower). In this study, we analyze the diurnal, synoptic and seasonal variability of the in situ CO2 measurements over nearly 1 year (8 August 2010–13 July 2011). We compare these datasets with remote CO2 measurements made at Mace Head (MHD) on the Atlantic coast of Ireland and support our analysis with atmospheric boundary layer height (ABLH) observations made in the center of Paris and with both modeled and observed meteorological fields. The average hourly CO2 diurnal cycles observed at the regional stations are mostly driven by the CO2 biospheric cycle, the ABLH cycle and the proximity to urban CO2 emissions. Differences of several µmol mol−1 (ppm) can be observed from one regional site to the other. The more the site is surrounded by urban sources (mostly residential and commercial heating, and traffic), the more the CO2 concentration is elevated, as is the associated variability which reflects the variability of the urban sources. Furthermore, two sites with inlets high above ground level (EIF and TRN) show a phase shift of the CO2 diurnal cycle of a few hours compared to lower sites due to a strong coupling with the boundary layer diurnal cycle. As a consequence, the existence of a CO2 vertical gradient above Paris can be inferred, whose amplitude depends on the time of the day and on the season, ranging from a few tenths of ppm during daytime to several ppm during nighttime. The CO2 seasonal cycle inferred from monthly means at our regional sites is driven by the biospheric and anthropogenic CO2 flux seasonal cycles, the ABLH seasonal cycle and also synoptic variations. Enhancements of several ppm are observed at peri-urban stations compared to rural ones, mostly from the influence of urban emissions that are in the footprint of the peri-urban station. The seasonal cycle observed at the urban station (EIF) is specific and very sensitive to the ABLH cycle. At both the diurnal and the seasonal scales, noticeable differences of several ppm are observed between the measurements made at regional rural stations and the remote measurements made at MHD, that are shown not to define background concentrations appropriately for quantifying the regional (∼ 100 km) atmospheric impact of urban CO2 emissions. For wind speeds less than 3 m s−1, the accumulation of local CO2 emissions in the urban atmosphere forms a dome of several tens of ppm at the peri-urban stations, mostly under the influence of relatively local emissions including those from the Charles de Gaulle (CDG) Airport facility and from aircraft in flight. When wind speed increases, ventilation transforms the CO2 dome into a plume. Higher CO2 background concentrations of several ppm are advected from the remote Benelux–Ruhr and London regions, impacting concentrations at the five stations of the network even at wind speeds higher than 9 m s−1. For wind speeds ranging between 3 and 8 m s−1, the impact of Paris emissions can be detected in the peri-urban stations when they are downwind of the city, while the rural stations often seem disconnected from the city emission plume. As a conclusion, our study highlights a high sensitivity of the stations to wind speed and direction, to their distance from the city, but also to the ABLH cycle depending on their elevation. We learn some lessons regarding the design of an urban CO2 network: (1) careful attention should be paid to properly setting regional (∼ 100 km) background sites that will be representative of the different wind sectors; (2) the downwind stations should be positioned as symmetrically as possible in relation to the city center, at the peri-urban/rural border; (3) the stations should be installed at ventilated sites (away from strong local sources) and the air inlet set up above the building or biospheric canopy layer, whichever is the highest; and (4) high-resolution wind information should be available with the CO2 measurements.

Highlights

  • Urbanized and industrialized areas are estimated to produce more than 70 % of the global CO2 emissions based on the consumption of fossil fuels (IEA, 2008; Seto et al, 2014)

  • The monthly clusters illustrate the high variability of the origin of the air masses, which could pass over high CO2 emission areas such as the megacity of London, the Benelux or Ruhr regions before reaching in the region Île-de-France (IdF)

  • The air masses could be advected from clean areas such as the Atlantic Ocean or from biospheric regions such as in the middle of France. This high atmospheric transport variability implies that the Paris regional CO2 background signal may be highly variable depending on the synoptic conditions and that wind direction and speed are key parameters to take into account in order to understand the CO2 concentrations recorded at the different sites

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Summary

Introduction

Urbanized and industrialized areas are estimated to produce more than 70 % of the global CO2 emissions based on the consumption of fossil fuels (IEA, 2008; Seto et al, 2014). The emission inventory reported by AIRPARIF (Association de surveillance de la qualité de l’air en IDF; http://www.airparif.asso.fr) estimates that IdF emitted a total of 41.9 Mt of CO2 in 2010, i.e., 12 % of French anthropogenic CO2 emissions (source: CITEPA, 2012; https://www.citepa.org/fr/air-et-climat/polluants/ effet-de-serre/dioxyde-de-carbone). It is based on the combination of benchmark emission factors and activity data for about 80 emission sectors and delivered every year (3 years after the year of the emission reporting). The associated uncertainties are estimated to be 20 % of the total CO2 emitted by month, but they are sector dependent and can reach several tens of percent for some sectors, as discussed in Rayner et al (2010)

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