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综合考虑大气传输过程中存在的平流风扩散、大气湍流扩散、源的释放作用、物化反应及沉降沉积影响的情况下,可以用大气传输方程描述气溶胶粒子的浓度变化[54]。为了能够对沉降扩散过程进行计算、仿真和预测,各种参数化计算方案、程序、模型、软件得以开发运用。
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沉降的仿真体现于相关物理过程的参数化计算,采取基于斯托克斯定律的物理模型或基于试验数据的半经验模型得出沉降速度、沉降通量及其规律。
物理模型着重于平衡重力、浮力和阻力的作用,采用斯托克斯公式计算得到各种气溶胶粒子的重力沉降速度[24,55],王玄玉等[55]利用显微镜分析了几种石墨颗粒粒径及长宽比,发现石墨颗粒具有良好的扩散和悬浮性能,可形成稳定的气溶胶,颗粒平均粒径为5.64 μm,大气环境下的沉降速率为0.00212 m/s。
半经验模型进一步考虑了大气湍流、分子运动以及表面捕获机制,包括布朗扩散、碰撞、截留、反弹、热泳和扩散泳等因素影响,主要适用于特定地表表面和特定粒径段的计算。如Slinn模型[56]采用阻力法,可用于各种植被冠层。Zhang等[57]结合干沉降经验参数对其应用扩展到14种地表类型,包括水面和冰面,得到广泛运用。Zhang等[58]考虑风力间歇性作用,采用拖动分割理论,得出颗粒沉降速度关于空气动力阻力、表面聚集阻力和重力阻力的函数表达式,经风洞测试验证,与气溶胶颗粒在均匀粗糙表面沉积分布相符。Petroff等[59]参数化表征了布朗扩散、拦截和惯性撞击,湍流撞击,定义26种不同地表类型的沉积,并在水、冰和雪表面计算不同粒径气溶胶颗粒沉积时,将观测到的渗流效应速度纳入到漂移速度,显著增加了准确性。
物理模型基于一定的前提假设,半经验模型基于相关试验数据。受湍流边界层的复杂多变以及随机因素影响,模型预测结果与实测数据存在一定偏差。
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扩散数值模拟仿真主要包括四类,分别为高斯模型、拉格朗日模型、欧拉模型以及拉格朗日-欧拉嵌套模型等[60]。高斯模型假设垂直于风速方向上粒子浓度呈高斯分布。拉格朗日模型通过跟随粒子运动轨迹,描述浓度变化。欧拉模型使用控制体流体速度的统计特征来描述浓度扩散。拉格朗日-欧拉嵌套模型采用拉格朗日方法计算近源区的初始输运和扩散,采用欧拉方法计算远距离的输运和扩散,通过取长补短,弥补固有缺陷,优化模拟效果。不同模型具有各自的优缺点,如精度、适用尺度范围和环境条件等(表1)。并有部分学者对模型性能展开了进一步的分析,曹博等[61]基于贝叶斯马尔可夫链蒙特卡洛方法,分析了高斯羽流模型的不确定性,通过计算发现观测误差对置信区间的影响较大。Ul Haq等[62]通过野外示踪试验,对三维拉格朗日粒子扩散模型LAPMOD的中尺度应用进行评估,发现该模型用于复杂地形的短期近场模拟与试验观测数据较为吻合。
表 1 不同气溶胶扩散仿真模型比较
Table 1. Comparison of different simulating models for aerosol diffusion
Simulation mode Data support Computational complexity Scale range Accuracy Environmental conditions Gauss model Wind speed Simple (fast operation, stable result) Short time, distance less than 10 km Low Open and flat terrain; stable atmosphere Lagrange model Real-time detailed meteorological data Complex (solving the particles motion equation) Full scale High Complex terrain; various atmospheric stability conditions Euler model Different scales of meteorological data Complex (solving the concentration equation) Medium and long distances High Complex terrain; various atmospheric stability conditions Lagrange-Euler nested mode Different scales of meteorological data Complex Full scale High Complex terrain; various atmospheric stability conditions 研究气溶胶扩散时应根据具体情况选用相应合理的模拟方法及模型进行修正优化,增强仿真效果。例如,Mészáros等[63]使用全球尺度拉格朗日粒子模型(IMS和RAPTOR)对福岛事故的全球扩散进行数值模拟,结果表明,日本福岛事故可在10天至1个月内显著影响欧洲、北美、亚洲等地区放射性核物质的大气浓度。Luhar[64]通过使用概率密度函数来描述观测到的垂直湍流速度偏差,对高斯烟团模型进行修正,在对微风条件下气溶胶粒子的扩散模拟中发现与拉格朗日粒子模式预测结果较为一致,但由于实际风向分布的非高斯性,模型的有效性还需要验证。孙逊等[65]采用数学形态学算法实时检测烟幕视频边缘数据,实时修正随机游走烟幕仿真模型,在进行的烟幕试验中,实现了复杂大气条件下烟幕沉降扩散的精确化仿真。
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采用计算流体力学(Computational Fluid Dynamics,CFD)方法对气溶胶烟幕扩散进行仿真,通常首先适当设置网格分辨率、边界条件和湍流模型,而后通过求解网格纳维-斯托克斯(Navier-Stokes,N-S)方程,得到复杂的微尺度风场和湍流场。CFD方法适用于扩散源近距离范围的模拟,一般计算成本较高,为提高计算效率,可以结合实际情况进行改进,如Jacob等[66]通过模拟中尺度和城市微尺度大气流中扩散过程,发现基于网格玻耳兹曼方法的大涡模拟方法与基于N-S方程的经典方法相比能显著提高计算效率。CFD一般有三种方程离散方法:有限体积法、有限差分法和有限元法。湍流的计算主要采用直接数值模拟、大涡模拟、雷诺平均等方法[67]。Xu等[68]利用CFD程序PHOENICS研究了集装箱船废气排放的烟羽扩散,定量分析了不同烟囱数量下污染物的质量分数和烟羽高度。肖凯涛等[69]利用Unity 3D软件建立扩散模型,在非结构网格中模拟气溶胶颗粒的湍流运动轨迹。
目前用于气溶胶烟幕扩散研究的CFD软件中,商业软件Fluent和开源软件 OpenFOAM较为通用。例如,何帆等[70]使用Fluent对警用催泪烟幕扩散进行流场数值计算,得到风速对催泪烟幕浓度的影响规律。Wang等[71]采用Fluent数值模拟,研究某均匀推拉式通风系统对油漆喷涂过程中漆雾颗粒扩散的影响,发现漆雾颗粒的扩散程度随着气幕射流速度的增大而增大,而随着送风速度的增大而减小。夏雨婷[72]采用OpenFOAM软件不同湍流模型研究了核电厂大气污染物的浓度分布规律,发现Realizable k-ε湍流模型的计算结果与风洞试验结果最为接近,模拟准确性最高。
不同软件具有各自优缺点,如OpenFOAM具有面向对象、多物理模块添加方便等优点,但存在涉化学反应方程求解、混合输运模型过于简化等不足[73]。进行气溶胶扩散仿真研究,应结合实际情况选用合适的软件,并对其自带的相关模型进行修正。例如,Longest等[74]提出了对Fluent中计算层流气溶胶粒子布朗运动模型进行湍流修正,得到改进的布朗力模型。Chen等[75]通过在Fluent中使用用户定义函数重写布朗扩散系数和粒子积分时间步长来修正布朗力,较好模拟超细气溶胶粒子通过建筑裂缝的扩散。
数值模拟仿真作为一种重要方法,能够为气溶胶沉降扩散过程分析研究提供有力支撑。但真实大气存在各种随机因素难以量化表征,数值模拟仿真模型软件并不完备,得到的结果应进一步通过试验验证。
Research progress on the deposition and diffusion of aerosols (invited)
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摘要: 气溶胶沉降扩散主要研究气溶胶粒子在大气中的运动状态、浓度迁移、表面沉积过程。表征物理量主要包括气溶胶粒子沉降通量、沉降速度、浓度分布、扩散速度等。开展相关研究可以为气溶胶生成方式优化、消光效果评估与预测等提供科学依据。文中概括了三种气溶胶生成方式,分析了气溶胶粒子在大气中沉降扩散过程机理,阐述了气溶胶沉降与扩散特性参量计算、仿真模拟和试验测定方法。结合目前气溶胶沉降扩散研究面临的挑战,对气溶胶沉降扩散理论分析、数值模拟、试验研究与综合运用进行了展望。Abstract: Aerosol deposition and diffusion mainly study the motion state, concentration migration and surface deposition process of aerosol particles in the atmosphere. The physical parameters mainly include the deposition flux, deposition velocity, concentration distribution and diffusion velocity of aerosol particles. Relevant research can provide a scientific basis for the optimization of aerosol generation and the evaluation and prediction of extinction effects. In this paper, three major methods for the generation of aerosols were summarized, the mechanism of aerosol particles settling and diffusing in the atmosphere was analysed, and the calculation, simulation and experimental measurement methods of aerosol settling and diffusing characteristic parameters were expounded. In view of the challenges in the study of aerosol deposition and diffusion, perspectives on future theoretical analyses, numerical simulations, experimental research and comprehensive applications are provided.
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Key words:
- aerosol /
- deposition /
- diffusion /
- simulation model /
- calculation method
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表 1 不同气溶胶扩散仿真模型比较
Table 1. Comparison of different simulating models for aerosol diffusion
Simulation mode Data support Computational complexity Scale range Accuracy Environmental conditions Gauss model Wind speed Simple (fast operation, stable result) Short time, distance less than 10 km Low Open and flat terrain; stable atmosphere Lagrange model Real-time detailed meteorological data Complex (solving the particles motion equation) Full scale High Complex terrain; various atmospheric stability conditions Euler model Different scales of meteorological data Complex (solving the concentration equation) Medium and long distances High Complex terrain; various atmospheric stability conditions Lagrange-Euler nested mode Different scales of meteorological data Complex Full scale High Complex terrain; various atmospheric stability conditions -
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