Abstract
Abstract. Accurate monitoring of atmospheric carbon dioxide (CO2) and its distribution is of great significance for studying the carbon cycle and predicting future climate change. Compared to the ground observational sites, the airborne observations cover a wider area and simultaneously observe a variety of surface types, which helps with effectively monitoring the distribution of CO2 sources and sinks. In this work, an airborne experiment was carried out in March 2019 over the Shanhaiguan area, China (39–41∘ N, 119–121∘ E). An integrated path differential absorption (IPDA) light detection and ranging (lidar) system and a commercial instrument, the ultraportable greenhouse gas analyser (UGGA), were installed on an aircraft to observe the CO2 distribution over various surface types. The pulse integration method (PIM) algorithm was used to calculate the differential absorption optical depth (DAOD) from the lidar data. The CO2 column-averaged dry-air mixing ratio (XCO2) was calculated over different types of surfaces including mountain, ocean, and urban areas. The concentrations of the XCO2 calculated from lidar measurements over ocean, mountain, and urban areas were 421.11 ± 1.24, 427.67 ± 0.58, and 432.04 ± 0.74 ppm, respectively. Moreover, through the detailed analysis of the data obtained from the UGGA, the influence of pollution levels on the CO2 concentration was also studied. During the whole flight campaign, 18 March was the most heavily polluted day with an Air Quality Index (AQI) of 175 and PM2.5 of 131 µg m−3. The aerosol optical depth (AOD) reported by a sun photometer installed at the Funing ground station was 1.28. Compared to the other days, the CO2 concentration measured by UGGA at different heights was the largest on 18 March with an average value of 422.59 ± 6.39 ppm, which was about 10 ppm higher than the measurements recorded on 16 March. Moreover, the vertical profiles of Orbiting Carbon Observatory-2 (OCO-2) and CarbonTracker were also compared with the aircraft measurements. All the datasets showed a similar variation with some differences in their CO2 concentrations, which showing a good agreement among them.
Highlights
Atmospheric carbon dioxide (CO2) is the most important greenhouse gas, and it plays a significant role in hydrology, sea ice melting, sea level rise, and atmospheric temperature changes (Mustafa et al, 2020; Santer et al, 2013; Stocker et al, 2013)
The results showed a difference of 0.36 % relative to the CO2 mixing ratio measured by the National Oceanic and Atmospheric Administration (NOAA) flask sampling data (Yu et al, 2017)
CarbonTracker is one model widely used by the CO2 community, and the integrated path differential absorption (IPDA) lidar is an effective tool for high-precision observation of atmospheric CO2
Summary
Atmospheric carbon dioxide (CO2) is the most important greenhouse gas, and it plays a significant role in hydrology, sea ice melting, sea level rise, and atmospheric temperature changes (Mustafa et al, 2020; Santer et al, 2013; Stocker et al, 2013). Accurate measurement of atmospheric CO2 and its spatiotemporal variation is crucial for estimating the distribution and dynamics of carbon sources and sinks at regional and global scales (Araki et al, 2010; Mustafa et al, 2021). There are several ground-based stations such as the Total Carbon Column Observing Network (TCCON) sites and the stations within the Global Atmospheric Watch (GAW) network, which are monitoring atmospheric CO2 with great precision Q. Wang et al.: Atmospheric Carbon Dioxide Measurement from Aircraft
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