In situ measurement of atmospheric CO2 at the four WMO/GAW stations in China
- 1Chinese Academy of Meteorological Sciences (CAMS), China Meteorological Administration (CMA), Beijing, China
- 2Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Boulder, CO, USA
- 3Laboratory for the Science of Climate and the Environment (LSCE), Paris, France
- 4Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Air Pollution/Environmental Technology, Duebendorf, Switzerland
Abstract. Atmospheric carbon dioxide (CO2) mole fractions were continuously measured from January 2009 to December 2011 at four atmospheric observatories in China using cavity ring-down spectroscopy instruments. The stations are Lin'an (LAN), Longfengshan (LFS), Shangdianzi (SDZ), and Waliguan (WLG), which are regional (LAN, LFS, SDZ) or global (WLG) measurement stations of the World Meteorological Organization's Global Atmosphere Watch program (WMO/GAW). LAN is located near the megacity of Shanghai, in China's economically most developed region. LFS is in a forest and rice production area, close to the city of Harbin in northeastern China. SDZ is located 150 km northeast of Beijing. WLG, hosting the longest record of measured CO2 mole fractions in China, is a high-altitude site in northwestern China recording background CO2 concentration. The CO2 growth rates are 3.7 ± 1.2 ppm yr−1 for LAN, 2.7 ± 0.8 ppm yr−1 for LFS, 3.5 ± 1.6 ppm yr−1 for SDZ, and 2.2 ± 0.8 ppm yr−1 (1σ) for WLG during the period of 2009 to 2011. The highest annual mean CO2 mole fraction of 404.2 ± 3.9 ppm was observed at LAN in 2011. A comprehensive analysis of CO2 variations, their diurnal and seasonal cycles as well as the analysis of the influence of local sources on the CO2 mole fractions allows a characterization of the sampling sites and of the key processes driving the CO2 mole fractions. These data form a basis to improve our understanding of atmospheric CO2 variations in China and the underlying fluxes using atmospheric inversion models.