In-situ measurement of CO₂ at the Xinglong regional background station over North China

Figures & data

Figure 1. Time series of regional background (black) and non-background (gray) CO₂ concentrations in Xinglong.

Figure 2. Monthly cycles of local sources and regional background CO₂ concentrations over a 12-month period. The upper panel shows the differences between the local sources and regional background CO₂ concentrations over a 12-month period. The lower panel shows the monthly cycles of local sources and regional background CO₂ concentrations over a 12-month period.

Figure 3. Diurnal cycles of regional background concentrations of CO₂ by season.

Table 1. Statistical analysis of cluster trajectories, including trajectory numbers, ratios, average CO₂ concentrations in each cluster, and the regions each cluster runs through.

Season	Cluster	Trajectory number	Ratio	Average CO2 (ppm)	Through-regions
Spring	4	425	16.00%	418.68 ± 10.95	Tangshan and Tianjin in China
	2	714	26.88%	414.68 ± 8.49	Mongolia and Russia, Zhangjiakou in China
	6	436	16.42%	416.69 ± 9.18
	3	318	11.97%	411.18 ± 7.48
	1	506	19.05%	411.07 ± 5.65
	5	257	9.68%	413.26 ± 3.14	Mongolia, north of the station
Summer	1	1133	28.53%	407.30 ± 12.79	Beijing–Tianjin–Hebei and Shandong in China
	5	765	19.26%	409.85 ± 10.99
	4	322	8.11%	404.81 ± 14.05	Mongolia, Zhangjiakou in China
	2	1058	26.64%	401.43 ± 12.16
	3	693	17.45%	397.41 ± 11.03	Inner Mongolia and Chifeng in China
Autumn	1	680	17.33%	418.11 ± 13.20	Beijing–Tianjin–Hebei and Shandong in China
	3	686	17.48%	416.99 ± 12.52	Mongolia, Zhangjiakou and Wulumuqi in China
	4	1110	28.29%	417.05 ± 13.66
	5	844	21.51%	417.94 ± 13.49
	2	604	15.39%	408.38 ± 8.79	Mongolia
Winter	4	171	6.56%	423.84 ± 16.60	Mongolia and Russia, Zhangjiakou in Hebei
	2	516	19.79%	426.49 ± 12.99
	5	485	18.60%	425.26 ± 13.64
	1	526	20.17%	420.39 ± 12.28
	6	394	15.11%	412.54 ± 6.21	Mongolia
	3	516	19.79%	413.17 ± 5.61

Figure 4. Cluster analysis of 72-h backward trajectory and PSCF analysis of CO₂ in Xinglong from May 2016 to December 2017. The numbers indicate the trajectory clustering type and the color depth represents the probability distribution of the emission sources: the deeper the color, the greater the contribution.