摘要
BVOCs对全球碳收支、对流层化学反应及臭氧的形成和气候变化都有很大的影响.选取森林覆盖率高且BVOCs排放尚未有研究报道的中国东北地区作为研究区域,利用美国NCAR中心提供的1°×1°的6hNCEP再分析资料,运行MM5模式,得到模拟结果,从中提取GloBEIS模型所需要的近地面层的温度、湿度、风速和云量的格点气象数据,实现了将MM5模式与GloBEIS相结合对BVOCs进行研究.研究中需要的植被种类及分布数据来自于最新的"植被信息系统"数据库,选取温度较高,太阳辐射较强,植被生长茂盛的2006年7月和2010年7月作为模拟时段,运行GloBEIS模型,对研究区域内的BVOCs的排放情况进行了估算.模拟结果与温度和云量等气象要素的分析结果表明,异戊二烯的排放速率受温度和PAR(光合有效辐射通量)的共同影响,日变化趋势显著,随着温度升高,PAR增强,异戊二烯的排放速率增大,在午后14:00左右达到最大值,之后降低.由于云量与PAR成反比,因此云量越少,异戊二烯的排放量就越高,反之,则越低;与异戊二烯不同,温度是单萜烯和其他VOC的排放的主导因素,受PAR和云量的影响较小,温度越高,排放量越大,反之,则越小.
BVOCs has great impact on the global carbon budget,chemical reactions in troposphere,formation of o- zone, and climate change. The northeast of China is selected as study region, where the forest coverage is high and no research on the emissions of BVOCs has been done yet. The reanalysis data from the National Centers for Envi- ronmental Prediction in U. S run in MM5 are used for simulation, with the spatial and temporal resolution of the re- analysis data being 1 ~ x 1 ~and 6 hours. From the simulation results of MMS, the meteorological data in grid are ex- tracted including the temperature,humidity,wind speed and cloud cover fraction, which are necessary for GloBEIS model. Thus the MM5 is integrated with GloBEIS for research of the BVOCs. The vegetation species and distribution data are derived from the latest ＂Vegetation Information System＂ database. The simulation period are chosen in July of 2006 and July of 2010 ,when the high temperature and strong solar radiation brings the flourish of vegetation in the northeast of China. The GloBEIS is run to estimate the emission of BVOCs. The results show that the isoprene e- mission changes with significant diurnal variation, and is correlated with temperature, PAR and cloud cover fraction. The isoprene emission rises with the increase of temperature and PAR,and reaches maximum value at about 14：00 pm, but it is negatively correlated with cloud cover fraction. While other VOCs are mainly influenced by tempera- ture. This conclusion is consistent with previous studies, so the method of combined MM5 and GloBEIS is feasible and the results are reliable. This research provides effective and reliable means for the forecasting of BVOCs under different scenarios.
出处
《南京信息工程大学学报（自然科学版）》
CAS
2013年第3期236-243,共8页
Journal of Nanjing University of Information Science & Technology（Natural Science Edition）
基金
国家重点基础研究发展计划(2011CB403404)
气科院基本科研业务重点项目(2010Z002)
国家自然科学基金(41205081)
