Statistical characteristics of concentration fluctuations in dispersing plumes in the atmospheric surface layer
Statistical characteristics of concentration fluctuations in dispersing plumes in the atmospheric surface layer
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大气表层弥散羽流浓度波动的统计特征
DOI：
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发表时间：
1993
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通讯作者：
J. Bowers
中科院分区：
文献类型：
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作者：
E. Yee;P. Kosteniuk;G. Chandler;C. Biltoft;J. Bowers
利用最近研制的快速响应光电离探测器，对大气表层一个高架点源产生的弥散羽流的浓度波动进行了测量。该探测器的频率响应（- 6 dB点）约为100 Hz，能够分辨出能量子范围和大部分惯性对流子范围带来的波动方差，由于仪器对羽流中存在的最细尺度进行了平滑处理，波动方差最多减少了4%。对浓度时间序列进行了分析，得到了扩散羽流的振幅和时间结构的统计特征。我们给出了沿风和侧风浓度波动曲线的振幅结构统计数据，如总波动强度和条件波动强度、偏度和峰度，以及时间结构统计数据，如间歇因子、突发频率和平均突发持续时间。经验浓度概率分布与许多模型分布的比较表明，我们的近中性数据最好由对数正态分布在较短范围内表示，其中羽流弯曲和细尺度羽流内混合同样重要（湍流-对流状态），以及伽马分布在较长范围内，其中内部结构或斑点成为主导（湍流-扩散状态）。伽玛分布为稳定分层下测量的所有顺风数据的浓度pdf提供了最佳模型。建立了一个物理模型来解释沿风扩散羽流发展过程中由机制引起的概率方案，该方案导致观测到的浓度概率分布。提取了浓度爆发长度和爆发回复期的概率分布，并证明幂律分布可以很好地模拟。给出了浓度波动的功率谱。这些光谱表现出明显的惯性-对流子范围，谱峰处的频率随着顺风强度的增加而降低。根据实测光谱，确定了惯性-对流子范围的Kolmogorov常数为0.17±0.03。
Measurements have been made of concentration fluctuations in a dispersing plume from an elevated point source in the atmospheric surface layer using a recently developed fast-response photoionization detector. This detector, which has a frequency response (−6 dB point) of about 100 Hz, is shown to be capable of resolving the fluctuation variance contributed by the energetic subrange and most of the inertial-convective subrange, with a reduction in the fluctuation variance due to instrument smoothing of the finest scales present in the plume of at most 4%.Concentration time series have been analyzed to obtain the statistical characteristics of both the amplitude and temporal structure of the dispersing plume. We present alongwind and crosswind concentration fluctuation profiles of statistics of amplitude structure such as total and conditional fluctuation intensity, skewness and kurtosis, and of temporal structure such as intermittency factor, burst frequency, and mean burst persistence time. Comparisons of empirical concentration probability distributions with a number of model distributions show that our near-neutral data are best represented by the lognormal distribution at shorter ranges, where both plume meandering and fine-scale in-plume mixing are equally important (turbulent-convective regime), and by the gamma distribution at longer ranges, where internal structure or spottiness is becoming dominant (turbulent-diffusive regime). The gamma distribution provides the best model of the concentration pdf over all downwind fetches for data measured under stable stratification. A physical model is developed to explain the mechanism-induced probabilistic schemes in the alongwind development of a dispersing plume, that lead to the observed probability distributions of concentration. Probability distributions of concentration burst length and burst return period have been extracted and are shown to be modelled well with a powerlaw distribution. Power spectra of concentration fluctuations are presented. These spectra exhibit a significant inertial-convective subrange, with the frequency at the spectral peak decreasing with increasing downwind fetch. The Kolmogorov constant for the inertial-convective subrange has been determined from the measured spectra to be 0.17±0.03.