XCO2 in an emission hot-spot region: the COCCON Paris campaign 2015

Abstract : Providing timely information on urban greenhouse gas (GHG) emissions and their trends to stakeholders relies on reliable measurements of atmospheric concentrations and the understanding of how local emissions and atmospheric transport influence these observations. Portable Fourier transform infrared (FTIR) spectrometers were deployed at five stations in the Paris metropolitan area to provide column-averaged concentrations of CO 2 (XCO 2) during a field campaign in spring of 2015, as part of the Col-laborative Carbon Column Observing Network (COCCON). Here, we describe and analyze the variations of XCO 2 observed at different sites and how they changed over time. We find that observations upwind and downwind of the city centre differ significantly in their XCO 2 concentrations, while the overall variability of the daily cycle is similar, i.e. increasing during night-time with a strong decrease (typically 2-3 ppm) during the afternoon. An atmospheric transport model framework (CHIMERE-CAMS) was used to simulate XCO 2 and predict the same behaviour seen in the observations, which supports key findings , e.g. that even in a densely populated region like Paris (over 12 million people), biospheric uptake of CO 2 can be of major influence on daily XCO 2 variations. Despite a general offset between modelled and observed XCO 2 , the model correctly predicts the impact of the meteorological parameters (e.g. wind direction and speed) on the concentration gradients between different stations. When analyzing local gradients of XCO 2 for upwind and downwind station pairs, those local gradients are found to be less sensitive to changes in XCO 2 boundary conditions and biogenic fluxes within the domain and we find the model-data agreement further improves. Our modelling framework indicates that the local XCO 2 gradient between the stations is dominated by the fossil fuel CO 2 signal of the Paris metropolitan area. This further highlights the potential usefulness of XCO 2 observations to help optimize future urban GHG emission estimates.