Concentration Variation Characteristics of Atmospheric Greenhouse Gases at Waliguan and Shangdianzi in China
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摘要: 研究典型区域大气温室气体的变化有助于有效应对气候变化、减缓全球变暖和减少极端气候事件.选取1997-2018年瓦里关和2009-2015年上甸子温室气体月值数据，应用线性趋势分析法和Mann-Kendall突变检验法分析两站温室气体的时间序列特征、季节变化趋势，构建HYSPLIT后向轨迹模型分析季风运输和大气边界层条件对温室气体的潜在影响.瓦里关和上甸子温室气体均逐年增长，具有明显的季节变化特征.两站CO2均在8月达到最低值，CH4则在8月达到峰值，SF6四季差异不大.瓦里关N2O在12月达到最高，6月降到最低；而上甸子N2O在7月达到峰值，9月降至最低.瓦里关和上甸子大气温室气体均受到局地生物源和非生物源、季风远距离运输、大气边界层条件和光化学过程等多种因素的共同作用.Abstract: Studying the changes of atmospheric greenhouse gases in typical regions will help effectively cope with climate change, slow global warming and reduce extreme climate events. In this paper, monthly data and the linear trend analysis method and Mann-Kendall mutation test method were used to analyze the characteristics of time series and seasonal variations of atmospheric greenhouse gases at Waliguan station during 1997-2018 and Shangdianzi station during 2009-2015. The HYSPLIT backward trajectory model was established to analyze the potential impacts of monsoon transportation and atmospheric boundary layer conditions on greenhouse gases. The greenhouse gases at both Waliguan and Shangdianzi stations significantly increased year by year, with obvious seasonal variations. Atmospheric CO2 at the two stations fell to the lowest in August, atmospheric CH4 reached peaks in August, and SF6 reached its maximum values in August and September, respectively. Atmospheric N2O at Waliguan station reached the highest in December and fell to the lowest in June, while atmospheric N2O at Shangdianzi station reached peaks in July and fell to its lowest in September. Atmospheric greenhouse gases at both Waliguan and Shangdianzi were affected by various factors such as local biological and non-biological sources, long-distance monsoon transportation, atmospheric boundary layer conditions and photochemical processes.
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图 1 中国瓦里关和上甸子本底站的地理位置
Fig. 1. Geographical location of Waliguan and Shangdianzi background stations in China
图 2 1997-2018年瓦里关本底站和2009-2015年上甸子本底站大气温室气体的时间序列
Fig. 2. The time series of atmospheric greenhouse gases for 1997-2018 at Waliguan background station and 2009-2015 at Shangdianzi background station
图 3 瓦里关和上甸子本底站大气温室气体的多年平均月浓度变化
Fig. 3. Multi-year average monthly concentration changes of atmospheric greenhouse gases at Waliguan and Shangdianzi background stations
图 4 1997-2018年瓦里关本底站大气温室气体浓度的季节变化
Fig. 4. Seasonal variations of atmospheric greenhouse gases for 1997-2018 at Waliguan background station
图 5 2009-2015年上甸子本底站大气温室气体浓度的季节变化
Fig. 5. Seasonal variations of atmospheric greenhouse gases for 2009-2015 at Shangdianzi background station
图 6 1997-2018年瓦里关本底站大气温室气体浓度的M-K突变检验曲线
Fig. 6. M-K mutation test curves of atmospheric greenhouse gases for 1997-2018 at Waliguan background station
图 7 2009-2015年上甸子本底站大气温室气体浓度的M-K突变检验曲线
Fig. 7. M-K mutation test curves of atmospheric greenhouse gases for 2009-2015 at Shangdianzi background station
图 8 瓦里关本底站不同月份空气团120 h后向轨迹分析
绿线：100 m AGL；蓝线：500 m AGL；红线：1 000 m AGL
Fig. 8. 120 h backward trajectory analysis of air masses in different months at Waliguan background station
图 9 上甸子本底站不同月份120 h空气团后向轨迹分析
绿线：100 m AGL；蓝线：500 m AGL；红线：1 000 m AGL
Fig. 9. 120 h backward trajectory analysis of air masses in different months at Shangdianzi background station
表 1 中国瓦里关和上甸子本底站大气温室气体浓度的统计特征
Table 1. Statistical characteristics of atmospheric greenhouse gases concentration at Waliguan and Shangdianzi background stations in China
年份 CO2浓度（10‒6） CH4浓度（10‒9） N2O浓度（10‒9） SF6浓度（10‒12） 瓦里关 上甸子 瓦里关 上甸子 瓦里关 上甸子 瓦里关 上甸子 1997 363.95±3.14 ‒ 1 807.35±4.22 ‒ 313.40±0.17 ‒ 4.17±0.04 ‒ 1998 365.77±3.03 ‒ 1 812.10±8.35 ‒ 314.04±0.17 ‒ 4.35±0.07 ‒ 1999 368.29±3.32 ‒ 1 824.35±6.60 ‒ 314.75±0.36 ‒ 4.56±0.08 ‒ 2000 370.38±2.71 ‒ 1 829.99 ±7.98 ‒ 316.16±0.64 ‒ 4.77±0.09 ‒ 2001 371.40±3.69 ‒ 1 827.60±6.41 ‒ 317.08±0.23 ‒ 4.92±0.07 ‒ 2002 372.65±3.53 ‒ 1 820.42±3.62 ‒ 317.57±0.15 ‒ 5.11±0.05 ‒ 2003 376.23±2.26 ‒ 1 834.80±10.10 ‒ 318.28±0.29 ‒ 5.39±0.11 ‒ 2004 378.19±3.05 ‒ 1 841.88±9.56 ‒ 318.89±0.30 ‒ 5.69±0.11 ‒ 2005 380.42±3.59 ‒ 1 839.63±7.31 ‒ 319.71±0.17 ‒ 5.86±0.09 ‒ 2006 382.11±2.80 ‒ 1 832.50±9.60 ‒ 320.37±0.31 ‒ 6.13±0.10 ‒ 2007 384.21±3.09 ‒ 1 841.43±9.93 ‒ 321.27±0.32 ‒ 6.37±0.11 ‒ 2008 386.12±2.98 ‒ 1 846.09±5.76 ‒ 322.02±0.30 ‒ 6.69±0.13 ‒ 2009 387.39±3.27 396.29±11.39 1 852.91±10.48 1 958.42±24.37 322.88±0.26 322.93±0.13 6.97±0.11 7.06±0.01 2010 390.06±2.57 396.59±8.21 1 858.23±8.81 1 949.54±31.83 323.62±0.28 323.83±0.31 7.24±0.11 7.24±0.11 2011 392.26±3.52 397.76±6.67 1 862.64±4.72 1 939.14±47.39 324.69±0.37 324.66±0.20 7.50±0.11 7.50±0.11 2012 394.79±3.87 400.96±9.17 1 877.78±7.80 1 934.36±14.24 325.45±0.25 325.69±0.25 7.85±0.10 7.85±0.10 2013 397.21±3.36 401.86±5.90 1 878.60±9.75 1 938.85±33.39 326.41±0.34 326.42±0.22 8.14±0.10 8.14±0.10 2014 398.74±3.88 405.70±10.33 1 888.62±11.17 1 980.25±39.87 327.76±0.51 327.82±0.40 8.49±0.12 8.49±0.12 2015 400.97±3.31 402.60±8.86 1 897.82±9.44 1 993.68±39.72 328.74±0.31 328.72±0.12 8.83±0.15 8.80±0.17 2016 404.86±3.14 ‒ 1 908.96±8.65 ‒ 329.64±0.26 ‒ 9.17±0.13 ‒ 2017 407.34±3.42 ‒ 1 909.17±3.93 ‒ 330.29±0.24 ‒ 9.47±0.11 ‒ 2018 409.23±2.85 ‒ 1 918.76±8.55 ‒ 331.33±0.50 ‒ 9.80±0.13 ‒ 
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表 2 不同季节瓦里关和上甸子本底站四种大气温室气体浓度的皮尔逊相关性系数
Table 2. Pearson correlation coefficients of four greenhouse gases concentrations at Waliguan and Shangdianzi background stations in different seasons
春季 夏季 秋季 冬季 全年 CO2 CH4 N2O SF6 CO2 CH4 N2O SF6 CO2 CH4 N2O SF6 CO2 CH4 N2O SF6 CO2 CH4 N2O SF6 瓦里关本底站 CO2 1.000 1.000 1.000 1.000 1.000 CH4 0.959** 1.000 0.934** 1.000 0.942** 1.000 0.958** 1.000 0.890** 1.000 N2O 0.996** 0.962** 1.000 0.979** 0.960** 1.000 0.992** 0.960** 1.000 0.994** 0.948** 1.000 0.967** 0.947** 1.000 SF6 0.996** 0.966** 0.997** 1.000 0.981** 0.964** 0.997** 1.000 0.991** 0.965** 0.997** 1.000 0.994** 0.956** 0.997** 1.000 0.961** 0.956** 0.997** 1.000 上甸子本底站 CO2 1.000 1.000 1.000 1.000 1.000 CH4 0.780** 1.000 ‒0.056 1.000 0.022 1.000 0.902** 1.000 ‒0.153 1.000 N2O 0.691** 0.602** 1.000 0.290 0.387 1.000 0.497* 0.108 1.000 0.492* 0.275 1.000 0.311** 0.315** 1.000 SF6 0.706** 0.591** 0.996** 1.000 0.240 0.423 0.987** 1.000 0.429 0.116 0.992** 1.000 0.553* 0.344 0.988** 1.000 0.245* 0.382** 0.986** 1.000 注：*代表0.05水平上相关性显著，**代表0.01水平上相关性显著.
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