A Lagrangian Stochastic Model for Heavy Particle Dispersion in the Atmospheric Marine Boundary Layer

The dispersion of heavy particles and pollutants is often simulated with Lagrangian stochastic (LS) models. Although these models have been employed successfully over land, the free surface at the air-sea interface complicates the implementation of traditional LS models. We present an adaptation of traditional LS models to the atmospheric marine boundary layer (MBL), where the bottom boundary is represented by a realistic wavy surface that moves and deforms. In addition, the correlation function for the turbulent flow following a particle is extended to the anisotropic, unsteady case. Our new model reproduces behaviour for Lagrangian turbulence in a stratified air flow that departs only slightly from the expected behaviour in isotropic turbulence. When solving for the trajectory of a heavy particle in the air flow, the modelled turbulent forcing on the particle also behaves remarkably well. For example, the spectrum of the turbulence at the particle location follows that of a massless particle for time scales approximately larger than the Stokes’ particle response time. We anticipate that this model will prove especially useful in the context of sea-spray dispersion and its associated momentum, sensible and latent heat, and gas fluxes between spray droplets and the atmosphere.     

A Large-Eddy Simulation and Lagrangian Stochastic Study of Heavy Particle Dispersion in the Convective Boundary Layer

Large-eddy simulation and Lagrangian stochastic dispersion models were used to study heavy particle dispersion in the convective boundary layer (CBL). The effects of various geostrophic winds, particle diameters, and subgrid-scale (SGS) turbulence were investigated. Results showed an obvious depression in the vertical dispersion of heavy particles in the CBL and major vertical stratification in the distribution of particle concentrations, relative to the passive dispersion. Stronger geostrophic winds tended to increase the dispersion of heavy particles in the lower CBL. The SGS turbulence, particularly near the surface, markedly influenced the dispersion of heavy particles in the CBL. For reference, simulations using passive particles were also conducted; these simulation results agreed well with results from previous convective tank experiments and numerical simulations.     

Lagrangian statistical simulation of the turbulent motion of heavy particles

A Lagrangian stochastic model for the motion of heavy particles has been developed by coupling a stochastic model for the motion of fluid elements to the Stokes equations of motion of a particle in a turbulent flow. The effects of crossing trajectories and continuity are incorporated by generalising Csanady's (1963) ideas developed for stationary homogeneous turbulence; effects of turbulence inhomogeneity and nonstationarity are embodied in the stochastic model for the fluid motion.The model has been used particularly to examine the effects of turbulence nonstationarity through simulations of the dispersion of heavy particles in the decaying homogeneous turbulence which is obtained by Taylor-transforming grid turbulence. Significant differences from the stationary case occur, mainly as a result of the growth of the turbulent time scale with time.The importance of the source location in influencing both passive scalar and particle dispersion in grid turbulence is highlighted by the model and can be simply accounted for by nondimensionalisation using the r.m.s. turbulence velocity at the source and the mean travel time from the grid to the source as velocity and time scales, respectively. Reconciliation of the three different experiments of Snyder and Lumley (1971), Wells and Stock (1983) and Ferguson (1986) reporting heavy particle flow and dispersion statistics in wind tunnel grid turbulence has been attempted using this nondimensionalisation. A good correspondence between the various data sets was not obtained because the source in the Wells and Stock, and Ferguson experiments was located at the grid where the self-similar development of the turbulence which underlies the scaling is not appropriate.The model matches the data for the heaviest particles used by Snyder and Lumley reasonably well. For very light particles, it correctly reverts to the passive scalar limit, while the experimental data in general do not properly approach this limit.     

Inertial Effects on the Vertical Transport of Suspended Particles in a Turbulent Boundary Layer

In many atmospheric flows, a dispersed phase is actively suspended by turbulence, whose competition with gravitational settling ultimately dictates its vertical distribution. Examples of dispersed phases include snow, sea-spray droplets, dust, or sand, where individual elements of much larger density than the surrounding air are carried by turbulent motions after emission from the surface. In cases where the particle is assumed to deviate from local fluid motions only by its gravitational settling (i.e., they are inertialess), traditional flux balances predict a power-law dependence of particle concentration with height. It is unclear, however, how particle inertia influences this relationship, and this question is the focus of this work. Direct numerical simulations are conducted of turbulent open-channel flow, laden with Lagrangian particles of specified inertia; in this way the study focuses on the turbulent transport which occurs in the lowest few meters of the planetary boundary layer, in regions critical for connecting emission fluxes to the fluxes felt by the full-scale boundary layer. Simulations over a wide range of particle Stokes number, while holding the dimensionless settling velocity constant, are performed to understand the role of particle inertia on vertical dispersion. It is found that particles deviate from their inertialess behaviour in ways that are not easily captured by traditional theory; concentrations are reduced with increasing Stokes number. Furthermore, a similarity-based eddy diffusivity for particle concentration fails as particles experience inertial acceleration, precluding a closed-form solution for particle concentration as in the case of inertialess particles. The primary consequence of this result is that typical flux parametrizations connecting surface emission models (e.g., saltation models or sea-spray generation functions) to elevated boundary conditions may overestimate particle concentrations due to the reduced vertical transport caused by inertia in between; likewise particle emission may be underestimated if inferred from concentration measurements aloft.     

Forward-in-time and Backward-in-time Dispersion in the Convective Boundary Layer: the Concentration Footprint

The turbulence field obtained using a large-eddy simulation model is used to simulate particle dispersion in the convective boundary layer with both forward-in-time and backward-in-time modes. A Lagrangian stochastic model is used to treat subgrid-scale turbulence. Results of forward dispersion match both laboratory experiments and previous numerical studies for different release heights in the convective boundary layer. Results obtained from backward dispersion show obvious asymmetry when directly compared to results from forward dispersion. However, a direct comparison of forward and backward dispersion has no apparent physical meaning and might be misleading. Results of backward dispersion can be interpreted as three-dimensional or generalized concentration footprints, which indicate that sources in the entire boundary layer, not only sources at the surface, may influence a concentration measurement at a point. Footprints at four source heights in the convective boundary layer corresponding to four receptors are derived using forward and backward dispersion methods. The agreement among footprints derived with forward and backward methods illustrates the equivalence between both approaches. The paper shows explicitly that Lagrangian simulations can yield identical footprints using forward and backward methods in horizontally homogeneous turbulence.     

A Velocity–Dissipation Lagrangian Stochastic Model for Turbulent Dispersion in Atmospheric Boundary-Layer and Canopy Flows

An extended Lagrangian stochastic dispersion model that includes time variations of the turbulent kinetic energy dissipation rate is proposed. The instantaneous dissipation rate is described by a log-normal distribution to account for rare and intense bursts of dissipation occurring over short durations. This behaviour of the instantaneous dissipation rate is consistent with field measurements inside a pine forest and with published dissipation rate measurements in the atmospheric surface layer. The extended model is also shown to satisfy the well-mixed condition even for the highly inhomogeneous case of canopy flow. Application of this model to atmospheric boundary-layer and canopy flows reveals two types of motion that cannot be predicted by conventional dispersion models: a strong sweeping motion of particles towards the ground, and strong intermittent ejections of particles from the surface or canopy layer, which allows these particles to escape low-velocity regions to a high-velocity zone in the free air above. This ejective phenomenon increases the probability of marked fluid particles to reach far regions, creating a heavy tail in the mean concentration far from the scalar source.     

A Homogeneous Langevin Equation Model, Part ii: Simulation of Dispersion in the Convective Boundary Layer

We present a Lagrangian stochastic model of vertical dispersion in the convective boundary layer (CBL). This model is based on a generalized Langevin equation that uses the simplifying assumption that the skewed vertical velocity probability distribution is spatially homogeneous. This approach has been shown to account for two key properties of CBL turbulence associated with large-scale coherent turbulent structures: skewed vertical velocity distributions and long velocity correlation time. A 'linear-skewed' form of the generalized Langevin equation is used, which has a linear (in velocity) deterministic acceleration and a skewed random acceleration. 'Reflection' boundary conditions for selecting a new velocity for a particle that encounters a boundary were investigated, including alternatives to the standard assumption that the magnitudes of the particle incident and reflected velocities are positively correlated. Model simulations were tested using cases for which exact, analytic statistical properties of particle velocity and position are known, i.e., well-mixed spatial and velocity distributions. Simulations of laboratory experiments of CBL dispersion show that (1) the homogeneous linear-skewed Langevin equation model (as well as an alternative 'nonlinear-Gaussian' Langevin equation model) can simulate the important aspects of dispersion in the CBL, and (2) a negatively-correlated-speed reflection boundary condition simulates the observed dispersion of material near the surface in the CBL significantly better than alternative reflection boundary conditions. The homogeneous linear-skewed Langevin equation model has the advantage that it is computationally more efficient than the homogeneous nonlinear-Gaussian Langevin equation model, and considerably more efficient than inhomogeneous Langevin equation models.     

Dispersion in the Wake of a Rectangular Building: Validation of Two Reynolds-Averaged Navier–Stokes Modelling Approaches

When modelling the turbulent dispersion of a passive tracer using Reynolds-averaged Navier–Stokes (RANS) simulations, two different approaches can be used. The first consists of solving a transport equation for a scalar, where the governing parameters are the mean velocity field and the turbulent diffusion coefficient, given by the ratio of the turbulent viscosity and the turbulent Schmidt number Sc _t . The second approach uses a Lagrangian particle tracking algorithm, where the governing parameters are the mean velocity and the fluctuating velocity field, which is determined from the turbulence kinetic energy and the Lagrangian time T _L . A comparison between the two approaches and wind-tunnel data for the dispersion in the wake of a rectangular building immersed in a neutral atmospheric boundary layer (ABL) is presented. Particular attention was paid to the influence of turbulence model parameters on the flow and concentration field. In addition, an approach to estimate Sc _t and T _L based on the calculated flow field is proposed. The results show that applying modified turbulence model constants to enable correct modelling of the ABL improves the prediction for the velocity and concentration fields when the modification is restricted to the region for which it was derived. The difference between simulated and measured concentrations is smaller than 25% or the uncertainty of the data on 76% of the points when solving the transport equation for a scalar with the proposed formulation for Sc _t , and on 69% of the points when using the Lagrangian particle tracking with the proposed formulation for T _L .     

Effects of mesoscale sea-surface temperature fronts on the marine atmospheric boundary layer

A numerical modelling study is presented focusing on the effects of mesoscale sea-surface temperature (SST) variability on surface fluxes and the marine atmospheric boundary-layer structure. A basic scenario is examined having two regions of SST anomaly with alternating warm/cold or cold/warm water regions. Conditions upstream from the anomaly region have SST values equal to the ambient atmosphere temperature, creating an upstream neutrally stratified boundary layer. Downstream from the anomaly region the SST is also set to the ambient atmosphere value. When the warm anomaly is upstream from the cold anomaly, the downstream boundary layer exhibits a more complex structure because of convective forcing and mixed layer deepening upstream from the cold anomaly. An internal boundary layer forms over the cold anomaly in this case, generating two distinct layers over the downstream region. When the cold anomaly is upstream from the warm anomaly, mixing over the warm anomaly quickly destroys the shallow cold layer, yielding a more uniform downstream boundary-layer vertical structure compared with the warm-to- cold case. Analysis of the momentum budget indicates that turbulent momentum flux divergence dominates the velocity field tendency, with pressure forcing accounting for only about 20% of the changes in momentum. Parameterization of surface fluxes and boundary-layer structure at these scales would be very difficult because of their dependence on subgrid-scale SST spatial order. Simulations of similar flow over smaller scale fronts (<5 km) suggest that small-scale SST variability might be parameterized in mesoscale models by relating the effective heat flux to the strength of the SST variance.     

北京地区一次PM2.5重污染过程的边界层特征分析

利用北京市环境保护监测中心和美国大使馆的细颗粒物（PM2.5）逐时监测数据,中国科学院大气物理研究所325 m气象梯度塔资料以及实况天气图和探空资料,对2015年11月27日至12月1日北京的PM2.5重污染过程的边界层特征进行了分析。研究发现:这次重污染过程持续时间长、强度大,其中PM2.5浓度超过75 μg/m3的时次共计126 h,超过150 μg/m3共计116 h,小时最高PM2.5浓度为522 μg/m3。在高低空环流场配置的影响下,近地面静风和多层逆温结构抑制了污染物在水平和垂直方向上的输送,加上边界层内的深厚湿层,使得其中气溶胶不断吸湿增长,高PM2.5浓度得以维持。在重污染期间,湍流动能较低,不利于污染物的水平和垂直扩散。垂直方向的湍流动能一直占水平方向的15%~20%左右,水平湍流动能占主要贡献。摩擦速度与湍流动能呈现出相似的变化趋势,不同高度之间的摩擦速度差别不大。超出前后时次一个数量级的湍流强度尖峰的出现是湍流场发生调整的一个信号,是PM2.5浓度发生剧烈转变的前兆,预示着污染状况更加糟糕。重污染过程中感热通量的输送方向为从地面向大气输送,感热通量和潜热通量都大幅减少,并且表现出明显的日变化特征。对湍流功率谱计算和分析表明,在重污染过程期间,时间尺度为5 min至6 h的中尺度过程对从地面到大气方向的动量和热量通量输送做出了重要贡献。     

Lagrangian Stochastic Modeling of Dispersion in the Stable Boundary Layer

Lagrangian stochastic models are well-suited for modeling dispersion in the stable boundary layer, especially in complex terrain. This note briefly describes the formulations and application of a Lagrangian stochastic model to predict dispersion of tracers released within nocturnal drainage flows.     

An Advanced Puff Model Based On A Mixed Eulerian/Lagrangian Approach For Turbulent Dispersion In The Convective Boundary Layer

An advanced model aimed at describing the problem of dispersion in theconvective boundary layer is proposed. The pollutant particles are groupedin clusters and modelled as Gaussian puffs. The expansion of each puff ismodelled according to the concept of relative dispersion and expressed interms of the spectral properties of the energy containing eddies of the turbulent field. The centre of mass of each puff is moved along a stochastic trajectory, obtained using a Lagrangian stochastic model and filtering the velocity with a recursive Kalman filter. At any instant, a filtering procedure, depending both on travel time and on puff size, acts to select spectral components involved in the expansion and in the meandering of the puff. Such an approach requires only a moderate number of puff releases, so that the proposed model is faster to run than a standard Lagrangian model. On the other hand, unlike the traditional puff model, it allows us to simulate both expansion and meandering of the puff. Therefore, it is well suited to simulate dispersion when the turbulent structures are larger thanthe plume dimensions, as for example in convective conditions. Being based onspectral formulations in both Eulerian and Lagrangian parts, the model is consistent in all the turbulent parameterizations utilised. Comparisons with a standard Lagrangian particle model as well as with a classical convective experimental dataset show good performance of the proposed model.     

A Homogeneous Langevin Equation Model, Part i: Simulation of Particle Trajectories in Turbulence with a Skewed Velocity Distribution

A Lagrangian stochastic model for the time evolution of the velocity of a fluid particle is presented. This model is based on a one-dimensional generalized Langevin equation, and assumes the velocity probability distribution of the turbulent fluid is skewed and spatially homogeneous. This has been shown to be an effective approach to simulating vertical dispersion in the convective boundary layer. We use a form of the Langevin equation that has a linear (in velocity) deterministic acceleration and a random acceleration that is a non-Gaussian, skewed process. For the case of homogeneous fluid velocity statistics, this 'linear-skewed' Langevin equation can be integrated explicitly, resulting in an efficient numerical simulation method. Model simulations were tested using cases for which exact, analytic statistical properties of particle velocity are known. Results of these tests show that, for homogeneous turbulence, a linear-skewed Langevin equation model can overcome the difficulties encountered in applying a Langevin equation with a skewed random acceleration. The linear-skewed Langevin equation model results are compared to results of a 'nonlinear-Gaussian' Langevin equation model, and show that the linear-skewed model is significantly more efficient.     

ON THE PDF MODELS FOR ATMOSPHERIC DIFFUSION IN BOUNDARY LAYER

In this paper, taking its turbulent exchange coefficient as a function of the Lagrangian timescale and standard variance of the turbulence in atmosphere, the atmospheric dispersion PDFmodels are obtained on the basis of atmospheric diffusion K-theory. In the model the statistics ofwind speed are directly used as its parameters instead of classic dispersion parameters. The bi-Gaussian PDF is derived in convective boundary layer (CBL), from the statistics of verticalvelocity in both of the downdraft and updraft regions that are investigated theoretically in the otherpart of this paper. Giving the driven parameters of the CBL (including the convective velocity scalew* and the mixing depth h_i) and the time-averaged wind speed at release level, the PDF model isable to simulate the distribution of concentration released at any levels in the CBL. The PDF'ssimulations are fairly consistent with the measurements in CONDORS experiment or the resultsbrought out by some numerical simulations.     

A Wind Tunnel and Numerical Investigation of Turbulent Dispersion in Coastal Atmospheric Boundary Layers

Thermal internal boundary layers in onshore air flows have a significant influence on pollutant diffusion in coastal areas. Although several models for this diffusion problem exist, measurements for model verification are scarce. In this paper, we present a set of wind tunnel observations and examine the performance of a Lagrangian stochastic model. The good agreement between the model simulation and the tunnel measurements confirms the usefulness of the Lagrangian stochastic model for practical purposes. Sensitivity tests of the model to turbulence statistics show that uncertainty in velocity skewness to the extent of observational scatter does not seem to have a significant influence on pollutant dispersion, while uncertainties in turbulence intensity (variance) significantly influence the dispersion pattern.     

On The Dynamical Content Of Lagrangian Stochastic Models In The Well-Mixed Class

It is shown how the correspondence between Lagrangian stochasticmodels and second-moment closures of the scalar-flux equation can be exploited to distinguishbetween Lagrangian stochastic models in the well-mixed class. It is found that physically realisticclosures of the scalar-flux equation correspond to Lagrangian stochastic models that have non-zero`spin' and so produce spiralling tracer-particle trajectories, whilst `zero-spin'models correspond to the isotropic-production model of scalar-fluxes.Lagrangian stochastic models consistent with rapid distortion theory and Speziale's transformation rule for the Reynolds stressequations in the extreme limit of two-dimensional turbulence are also shown to have non-zero spin.The residual non-uniqueness associated with satisfaction of thewell-mixed condition and the specification of mean spin is shown to be related to the helicity oftracer-particle trajectories. Investigations are also made of the influence upon turbulent dispersion oftime-dependent spin and of mean rotations of the fluctuating Lagrangian acceleration vector(i.e., second-order spin).     

广州市近地层大气的湍流微结构和谱特征

本文利用UVW脉动风速仪资料分析了广州市区近地层大气的湍流强度、相关系数、尺度和速度谱,并获得了不同稳定度条件下的速度谱模式.结果表明,城市近地层大气湍流在惯性副区接近局地各向同性、速度谱符合Kolmogorov相似理论;气流方向上下垫面粗糙度的增加,使沿海城市近地层大气湍流能量(特别是铅直方向)比平坦、均匀下垫面上的增加.     

Wind-Tunnel Study Of Atmospheric Stable Boundary Layers Over A Rough Surface

Wind-tunnel simulations of theatmospheric stable boundary layer (SBL) developedover a rough surface were conducted by using athermally stratified wind tunnel at the Research Institutefor Applied Mechanics (RIAM), Kyushu University. Thepresent experiment is a continuation of the workcarried out in a wind tunnel at Colorado StateUniversity (CSU), where the SBL flows were developed over asmooth surface. Stably stratified flows were createdby heating the wind-tunnel airflow to a temperature ofabout 40–50°and by cooling the test-section floor toa temperature of about 10°. To simulate therough surface, a chain roughness was placed over thetest-section floor. We have investigated the buoyancyeffect on the turbulent boundary layer developed overthis rough surface for a wide range of stability,particularly focusing on the turbulence structure andtransport process in the very stable boundary layer.The present experimental results broadly confirm theresults obtained in the CSU experiment with the smoothsurface, and emphasizes the following features: thevertical profiles of turbulence statistics exhibitdifferent behaviour in two distinct stability regimes with weak and strong stability,corresponding to the difference in the verticalprofiles of the local Richardson number. The tworegimes are separated by the critical Richardsonnumber. The magnitudes in turbulence intensities andturbulent fluxes for the weak stability regime aremuch greater than those of the CSU experiments becauseof the greater surface roughness. For the very stableboundary layer, the turbulent fluxes of momentum andheat tend to vanish and wave-like motions due to theKelvin–Helmholtz instability and the rolling up andbreaking of those waves can be observed. Furthermore,the appearance of internal gravity waves is suggestedfrom cross-spectrum analyses.