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A source-orientated approach for estimating daytime concentrations of biogenic volatile organic compounds in an upper layer of a boreal forest canopy

机译:以来源为导向的方法,估算北方森林冠层上层中生物挥发性有机化合物的日间浓度

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Biologically justified statistical models for daytime atmospheric concentrations of methanol, acetaldehyde, acetone, isoprene and monoterpene were tested using measurements at a boreal forest stand in southern Finland in 2006–2007 and in summer 2008. The canopyscale concentrations of all compounds except monotepene were closely correlated with shoot-scale concentrations indicating a strong link to biological emission source. All the models were based on the exponential relationship between air temperature and atmospheric concentration of biogenic volatile organic compounds (BVOCs). The first model — an exponential function of air temperature (T model) — could explain 27%–64% of the variation in BVOC daytime concentrations in the test data. The second model — a Temperature-State of Development model (T-S model) having two explaining variables (air temperature and seasonal photosynthetic efficiency) — was derived from an empirical adjustment of seasonality. This model slightly increased the fraction of explained variation but it still could not explain the high concentration peaks, which accounted for most of the unexplained variation. To better analyse these peaks we tested the Trigger model including two potential environmental triggers, a PAR index (high photosynthetically active photon flux density (PAR) and high ozone concentration, that could increase the concentrations momentarily. However, the Trigger model described the peak concentrations only somewhat better than the T or T-S model. It seems that it is very difficult to explain more than 32%–67% of variation in BVOC concentrations by a straightforward source-oriented modelling without deep understanding of biological and physical processes. In order to improve the models profound studies on specific stress factors and events inducing BVOC emissions are needed.
机译:在2006-2007年和2008年夏季,在芬兰南部的一个北方森林林地进行了测量,测试了甲醇,乙醛,丙酮,异戊二烯和单萜的白天大气浓度的生物学合理的统计模型。枝条浓度表明与生物排放源密切相关。所有模型均基于空气温度与生物挥发性有机化合物(BVOC)的大气浓度之间的指数关系。第一个模型-气温的指数函数(T模型)-可以解释测试数据中BVOC白天浓度变化的27%–64%。第二个模型是具有两个解释变量(气温和季节性光合作用效率)的温度发展状态模型(T-S模型),该模型是根据季节性的经验调整得出的。该模型稍微增加了所解释的变化的比例,但仍无法解释高浓度峰,这是大多数无法解释的变化的原因。为了更好地分析这些峰,我们测试了包含两个潜在环境触发因素的触发模型,即PAR指数(高光合有效光子通量密度(PAR)和高臭氧浓度,它们可能会瞬时增加浓度)。但是,触发模型描述了峰值浓度似乎很难通过对生物和物理过程没有深入了解的直接面向源的模型来解释BVOC浓度的32%至67%以上的变化,这是非常困难的。改进模型需要对特定压力因素和诱发BVOC排放的事件进行深入研究。

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