Abstract
Abstract. More than 300 non-dispersive infrared (NDIR) CO2 low-cost sensors labelled as LP8 were integrated into sensor units and evaluated for the purpose of long-term operation in the Carbosense CO2 sensor network in Switzerland. Prior to deployment, all sensors were calibrated in a pressure and climate chamber and in ambient conditions co-located with a reference instrument. To investigate their long-term performance and to test different data processing strategies, 18 sensors were deployed at five locations equipped with a reference instrument after calibration. Their accuracy during 19 to 25 months deployment was between 8 and 12 ppm. This level of accuracy requires careful sensor calibration prior to deployment, continuous monitoring of the sensors, efficient data filtering, and a procedure to correct drifts and jumps in the sensor signal during operation. High relative humidity (> ∼85 %) impairs the LP8 measurements, and corresponding data filtering results in a significant loss during humid conditions. The LP8 sensors are not suitable for the detection of small regional gradients and long-term trends. However, with careful data processing, the sensors are able to resolve CO2 changes and differences with a magnitude larger than about 30 ppm. Thereby, the sensor can resolve the site-specific CO2 signal at most locations in Switzerland. A low-power network (LPN) using LoRaWAN allowed for reliable data transmission with low energy consumption and proved to be a key element of the Carbosense low-cost sensor network.
Highlights
The number of available low-cost sensor types for ambient trace gas observations has increased in recent years
The mathematical models provided by the manufacturers are often not sufficient to meet the accuracy demands of trace gas measurements in outdoor conditions
Measurements based on the factory calibration are not as accurate as they can be under outdoor conditions when using an extended model such as those described by Eqs. (4) and (5) (Fig. 8c)
Summary
The number of available low-cost sensor types for ambient trace gas observations has increased in recent years. The accuracy level achieved by low-cost trace gas sensors is still significantly below that of high-precision instruments. This may be acceptable in view of their lower costs if the achievable data quality remains suitable for a specific application. Low-cost sensors have to be individually calibrated for achieving their best performance, and data processing is an essential element to obtain accurate measurements This data processing includes filtering to eliminate and report outliers or data of reduced quality and the detection of changes in sensor characteristics which require the adaptation of the model that converts the raw sensor output to the molar fraction. Most of the findings and developments carried out by means of the Carbosense sensor network such as aspects of data transmission and data processing are generic and transferable to other low-cost trace gas sensor networks
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