Development and deployment of a mid-cost CO₂ sensor monitoring network to support atmospheric inverse modeling for quantifying urban CO₂ emissions in Paris

Abstract. To effectively monitor the highly heterogeneous urban CO₂ emissions using atmospheric observations, there is a need to deploy cost-effective CO₂ sensors at multiple locations within the city with sufficient accuracy to capture the concentration gradients in urban environments. Its measurements could be used as input of an atmospheric inversion system for the quantification of emissions at the sub-city scale or separate specific sectors. Such quantification would offer valuable insights into the efficacy of local initiatives and could also identify unknown emission hotspots that require attention. Here we present the development and evaluation of a mid-cost CO₂ instrument designed for continuous monitoring of atmospheric CO₂ concentrations with a target accuracy of 1 ppm on hourly mean measurement. We assess the sensor sensitivity in relation to environmental factors such as humidity, pressure, temperature and CO₂ signal, which leads to the development of an effective calibration algorithm. Since July 2020, eight mid-cost instruments have been installed within the city of Paris and its vicinity to provide continuous CO₂ measurements, complementing the seven high-precision Cavity Ring-Down Spectroscopy (CRDS) stations that have been in operation since 2016. A data processing system, called CO2calqual, has been implemented to automatically handle data quality control, calibration and storage, which enables the management of extensive real-time CO₂ measurements from the monitoring network. Colocation assessments with the high-precision instrument show that the accuracies of the eight mid-cost instruments are within the range of 1.0 to 2.4 ppm for hourly afternoon (12–17 UTC) measurements. The long-term stability issues require manual data checks and instrument maintenance. The analyses show that CO₂ measurements can provide evidence for underestimations of CO₂ emissions in the Paris region and a lack of several emission point sources in the emission inventory. Our study demonstrates promising prospects in integrating mid-cost measurements along with high precision data into the subsequent atmospheric inverse modeling to improve the accuracy of quantifying the fine-scale CO₂ emissions in the Paris metropolitan area.