Articles | Volume 16, issue 8
https://doi.org/10.5194/amt-16-2209-2023
https://doi.org/10.5194/amt-16-2209-2023
Research article
 | 
25 Apr 2023
Research article |  | 25 Apr 2023

Reconstruction of high-frequency methane atmospheric concentration peaks from measurements using metal oxide low-cost sensors

Rodrigo Andres Rivera Martinez, Diego Santaren, Olivier Laurent, Gregoire Broquet, Ford Cropley, Cécile Mallet, Michel Ramonet, Adil Shah, Leonard Rivier, Caroline Bouchet, Catherine Juery, Olivier Duclaux, and Philippe Ciais

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Cited articles

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Casey, J. G., Collier-Oxandale, A., and Hannigan, M.: Performance of artificial neural networks and linear models to quantify 4 trace gas species in an oil and gas production region with low-cost sensors, Sensor. Actuat. B-Chem., 283, 504–514, https://doi.org/10.1016/j.snb.2018.12.049, 2019. a, b, c, d, e, f
Cescatti, A., Marcolla, B., Goded, I., and Gruening, C.: Optimal use of buffer volumes for the measurement of atmospheric gas concentration in multi-point systems, Atmos. Meas. Tech., 9, 4665–4672, https://doi.org/10.5194/amt-9-4665-2016, 2016. a
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Short summary
A network of low-cost sensors is a good alternative to improve the detection of fugitive CH4 emissions. We present the results of four tests conducted with two types of Figaro sensors that were assembled on four chambers in a laboratory experiment: a comparison of five models to reconstruct the CH4 signal, a strategy to reduce the training set size, a detection of age effects in the sensors and a test of the capability to transfer a model between chambers for the same type of sensor.
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