Characterization of a commercial lower-cost medium-precision non-dispersive infrared sensor for atmospheric CO 2 monitoring in urban areas

International audienceCO 2 emission estimates from urban areas can be obtained with a network of in situ instruments measuring atmospheric CO 2 combined with high-resolution (inverse) transport modelling. Because the distribution of CO 2 emissions is highly heterogeneous in space and variable in time in urban areas, gradients of atmospheric CO 2 (here, dry air mole fractions) need to be measured by numerous instruments placed at multiple locations around and possibly within these urban areas. This calls for the development of lower-cost medium-precision sensors to allow a deployment at required densities. Medium precision is here set to be a random error (uncertainty) on hourly measurements of ±1 ppm or less, a precision requirement based on previous studies of network design in urban areas. Here we present tests of newly developed non-dispersive infrared (NDIR) sensors manufactured by Senseair AB performed in the laboratory and at actual field stations, the latter for CO 2 dry air mole fractions in the Paris area. The lower-cost medium-precision sensors are shown to be sensitive to atmospheric pressure and temperature conditions. The sensors respond linearly to CO 2 when measuring calibration tanks, but the regression slope between measured and assigned CO 2 differs between individual sensors and changes with time. In addition to pressure and temperature variations, humidity impacts the measurement of CO 2 , with all of these factors resulting in systematic errors. In the field, an empirical calibration strategy is proposed based on parallel measurements with the lower-cost medium-precision sensors and a high-precision instrument cavity ring-down instrument for 6 months. The empirical calibration method consists of using a multivari-able regression approach, based on predictors of air temperature , pressure and humidity. This error model shows good performances to explain the observed drifts of the lower-cost medium-precision sensors on timescales of up to 1-2 months when trained against 1-2 weeks of high-precision instrument time series. Residual errors are contained within the ±1 ppm target, showing the feasibility of using networks of HPP3 instruments for urban CO 2 networks. Provided that they could be regularly calibrated against one anchor reference high-precision instrument these sensors could thus collect the CO 2 (dry air) mole fraction data required as for top-down CO 2 flux estimates