Shumin Wang1, Lingyun Zhu This email address is being protected from spambots. You need JavaScript enabled to view it.1, Shiming Yan1, Ying Li1, Wenya Wang1, Xing’ai Gao1, Zhiqiang Ma2, Peng Liu3, Miao Liang4

1 Shanxi Province Institute of Meteorological Sciences, Taiyuan 030002, China
2 Beijing Shangdianzi Regional Atmosphere Watch Station, Beijing 101500, China
3 Qinghai Meteorological Bureau, China Atmospheric Background Reference Observatory, Xining 810001, China
4 Meteorological Observation Centre (MOC), China Meteorological Administration (CMA), Beijing 100081, China


Received: January 18, 2020
Revised: May 28, 2020
Accepted: May 30, 2020

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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Cite this article:

Wang, S., Zhu, L., Yan, S., Li, Y., Wang, W., Gao, S., Ma, Z., Liu, P. and Liang, M. (2020). Atmospheric CO2 Data Filtering Method and Characteristics of the Mole Fractions at Wutaishan Station in Shanxi of China. Aerosol Air Qual. Res.



  • The first-hand data help the authorities to implement climate policy.
  • The data filtering method combining REBS and MET is used.
  • The results represent the background concentration in Shanxi and the surroundings.


The Wutaishan Station (WTS) in Shanxi Province is built on the Wutai Mountain (2208 m a. s. l.) known as the "North China Roof". There is no obvious industrial source around the station and the surrounding forest vegetation is well covered. This paper uses the online observation data of atmospheric CO2 (Picarro-G2301) from March 2017 to February 2018 at WTS, and uses the combined filtering method of REBS and MET to calculate the CO2 average background concentration of WTS, (410.9 ± 6.4) × 10-6, which can represent the background concentration of atmospheric CO2 in Shanxi and surrounding areas. In addition, based on meteorological data, the following conclusions are drawn. The daily variation of CO2 concentration in WTS among four seasons is from 2.4 × 10-6 to 4.8 × 10-6, which is relatively flat. There is a negative correlation between CO2 concentration and surface wind speed in spring and winter, with R being −0.44 and −0.46, respectively. Using backward trajectory analysis method, it is concluded that the wind from SE-S-SW can effectively increase the native CO2 concentration, whether it is the transmission from high air masses or surface wind.

Keywords: Carbon dioxide; Regional representative; Observation data selection; Backward trajectory

Aerosol Air Qual. Res. 20:-. 

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