A Low-cost UAV Coordinated Carbon observation Network (LUCCN): an analysis of environment impact on ground base measurement node

Most anthropogenic carbon dioxide (CO2) emissions originate from urban areas. To improve understandings of urban and regional emissions, we design and construct a low-cost UAV coordinated carbon observation network (LUCCN) which uses mid-accuracy (±1 ppm) CO2 sensors. In this paper, we introduce our multi-variable non-linear regression method for calibrating the non-dispersive infrared (NDIR) CO2 sensors for LUCCN’s ground stations. We tested our calibration method with concentration data collected at the Xinglong Atmospheric Background Observatory. With comparison against data simultaneously collected by a high-accuracy cavity ring-down spectrometer, we found the maximum standard deviation of LUCCN’s sensors to be 0.782 ppm in a controlled laboratory environment with a 1-second window size and 0.53 ppm in an outdoor environment with a 1-hour running average window size. As validation of LUCCN’s ground measurements, we identify and present consistent trends between local CO2 concentration variations and aerosol pollution events captured by the space-based moderate resolution imaging spectrometer (MODIS).