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

Autor: Arzoumanian, Emmanuel, Vogel, Felix, Bastos, Ana, Gaynullin, Bakhram, Laurent, Olivier, Ramonet, Michel, Ciais, Philippe
Přispěvatelé: Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-RAMCES (ICOS-RAMCES), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Atmospheric Measurement Techniques
Atmospheric Measurement Techniques, European Geosciences Union, 2019, 12 (5), pp.2665-2677. ⟨10.5194/amt-12-2665-2019⟩
Atmospheric Measurement Techniques, 2019, 12 (5), pp.2665-2677. ⟨10.5194/amt-12-2665-2019⟩
ISSN: 1867-1381
1867-8548
DOI: 10.5194/amt-12-2665-2019⟩
Popis: International audience; CO 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.
Databáze: OpenAIRE
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