Bamberger I, Hörtnagl L, Walser M, Hansel A, Wohlfahrt G
Institute of Ion Physics and Applied Physics, University of Innsbruck, Austria ; now at: Institute of Agricultural Sciences, ETH-Zürich, Switzerland.
Institute of Ecology, University of Innsbruck, Austria.
Biogeosci Discuss. 2013 Nov;10(11). doi: 10.5194/bgd-10-17785-2013.
Up to now the limited knowledge about the exchange of volatile organic compounds (VOCs) between the biosphere and the atmosphere is one of the factors which hinders more accurate climate predictions. Complete long-term flux data sets of several VOCs to quantify the annual exchange and validate recent VOC models are basically not available. In combination with long-term VOC flux measurements the application of gap-filling routines is inevitable in order to replace missing data and make an important step towards a better understanding of the VOC ecosystem-atmosphere exchange on longer time scales. We performed VOC flux measurements above a mountain meadow in Austria during two complete growing seasons (from snowmelt in spring to snow reestablishment in late autumn) and used this data set to test the performance of four different gap-filling routines, mean diurnal variation (MDV), mean gliding window (MGW), look up tables (LUT) and linear interpolation (LIP), in terms of their ability to replace missing flux data in order to obtain reliable VOC sums. According to our findings the MDV routine was outstanding with regard to the minimization of the gap-filling error for both years and all quantified VOCs. The other gap-filling routines, which performed gap-filling on 24 h average values, introduced considerably larger uncertainties. The error which was introduced by the application of the different filling routines increased linearly with the number of data gaps. Although average VOC fluxes measured during the winter period (complete snow coverage) were close to zero, these were highly variable and the filling of the winter period resulted in considerably higher uncertainties compared to the application of gap-filling during the measurement period. The annual patterns of the overall cumulative fluxes for the quantified VOCs showed a completely different behavior in 2009, which was an exceptional year due to the occurrence of a severe hailstorm, compared to 2011. Methanol was the compound which contributed with 381.5 mgCm and 449.9 mgCm most to the cumulative VOC carbon emissions in 2009 and 2011, respectively. In contrast to methanol emissions, however, considerable amounts of monoterpenes (-327.3 mgCm) were deposited to the mountain meadow in consequence to the hailstorm in 2009. Other quantified VOCs had considerably lower influences on the annual patterns.
到目前为止,关于生物圈与大气之间挥发性有机化合物(VOCs)交换的知识有限,这是阻碍更准确气候预测的因素之一。基本上没有完整的几种VOCs长期通量数据集来量化年度交换并验证最近的VOC模型。为了替代缺失数据并朝着在更长时间尺度上更好地理解VOC生态系统 - 大气交换迈出重要一步,结合长期VOC通量测量,应用填补间隙程序是不可避免的。我们在奥地利的一片山地草甸上进行了两个完整生长季节(从春季融雪到秋季末再次降雪)的VOC通量测量,并使用该数据集测试了四种不同填补间隙程序的性能,即日平均变化(MDV)、平均滑动窗口(MGW)、查找表(LUT)和线性插值(LIP),评估它们替换缺失通量数据以获得可靠VOC总量的能力。根据我们的研究结果,MDV程序在最小化两年内所有量化VOCs的填补间隙误差方面表现出色。其他对24小时平均值进行填补间隙的程序引入了大得多的不确定性。应用不同填补程序引入的误差随数据间隙数量线性增加。尽管冬季(完全积雪覆盖)期间测量的平均VOC通量接近零,但这些通量变化很大,与测量期间应用填补间隙相比,填补冬季数据导致的不确定性要高得多。与2011年相比,2009年是异常的一年,因为发生了严重冰雹风暴,量化VOCs的总累积通量的年度模式表现出完全不同的行为。甲醇是分别在2009年和2011年对累积VOC碳排放贡献最大的化合物,分别为381.5 mgC/m²和449.9 mgC/m²。然而,与甲醇排放相反,由于2009年的冰雹风暴,大量单萜烯(-327.3 mgC/m²)沉积到山地草甸。其他量化的VOCs对年度模式的影响要小得多。