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A Dynamic Lagrangian, Field-Scale Model of Dust Dispersion from Agriculture Tilling Operations

机译:农业耕作作业中灰尘扩散的动态拉格朗日模型

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摘要

Dust exposure in and near farm fields is of increasing concern for human health and may soon be facing new emissions regulations. Dust plumes of this nature have rarely been documented due to the unpredictable nature of the dust plumes and the difficulties of accurately sampling the plumes. This article presents a dynamic random-walk model that simulates the field-scale PM 10 (particle diameter < 10 � m) dust dispersion from an agriculture disking operation. The major improvements over traditional plume models are that it can simulate moving sources and plume meander. The major inputs are the friction velocity (u*), wind direction in the simulation period, atmospheric stability, and source strength ( � g s -1 ). In each time step of the model simulation, three instantaneous wind velocities (x, y, and z directions) are produced based on friction velocity, mean wind speed, and atmospheric stability. The computational time step is 0.025 times the Lagrangian time scale. The resulting instantaneous wind vectors transport all the individual particles. The particle deposition algorithm calculates if a particle is deposited based on the particle settling speed and vertical wind velocity when it touches the ground surface. The particle mass based concentration in 3-D can be obtained at any instant by counting the particle numbers in a unit volume and then converting to mass based on the particle size and density. Simulations from this model are verified by comparison with dust dispersion and plume concentrations obtained by an elastic backscatter LIDAR. The simulated plume spread parameters ( s y , s z ) at downplume distances up to 160 m were within � 73% of those measured with a remote aerosol LIDAR. Cross-correlations between a modeled plume and LIDAR measurements of the actual plume were as high as 0.78 near the ground and decreased to 0.65 at 9 m above ground, indicating close pattern similarity between the modeled and measured plumes at lower heights but decreasing with elevation above the ground.
机译:农田及其附近地区的粉尘暴露日益引起人们对人体健康的关注,并且可能很快就会面临新的排放法规。由于尘埃羽的不可预测的性质和精确采样羽尘的困难,很少记录这种性质的尘埃羽。本文介绍了一个动态随机游走模型,该模型模拟了来自农业圆盘作业的现场级PM 10(粒径<10μm)尘埃扩散。与传统羽状模型相比,主要改进之处在于它可以模拟运动源和羽状弯曲。主要输入是摩擦速度(u *),模拟期间的风向,大气稳定性和辐射源强度(μg s -1)。在模型仿真的每个时间步中,根据摩擦速度,平均风速和大气稳定性产生三个瞬时风速(x,y和z方向)。计算时间步长是拉格朗日时间尺度的0.025倍。产生的瞬时风矢量传输所有单个粒子。粒子沉积算法根据粒子沉降到地面时的沉降速度和垂直风速来计算是否沉积了粒子。通过在单位体积中计算颗粒数,然后根据颗粒大小和密度转换为质量,可以随时获得3-D中基于颗粒质量的浓度。通过与弹性反向散射激光雷达获得的粉尘散布和羽流浓度进行比较,验证了该模型的仿真结果。下羽距离最大160 m处的模拟羽流扩散参数(s y,s z)在使用远程气溶胶激光雷达测量的参数的73%之内。实际羽流的模型羽和LIDAR测量值之间的互相关在地面附近高达0.78,而在离地面9 m处下降到0.65,表明在较低高度下模拟羽和测量羽之间的模式相似度接近,但随着海拔的升高而降低地面。

著录项

  • 来源
    《Transactions of the ASABE》 |2008年第5期|p.1763-1774|共12页
  • 作者单位

    The authors are Junming Wang, ASABE Member, Research Scientist, Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, New Mexico;

    April L. Hiscox, ASABE Member, Assistant Professor, David R. Miller, ASABE Member, Professor, and Thomas H. Meyer, Associate Professor, Department of Natural Resources Management and Engineering, University of Connecticut, Storrs, Connecticut;

    and Ted W. Sammis, ASABE Member, Professor, Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, New Mexico. Corresponding author: Junming Wang, Department of Plant and Environmental Sciences, New Mexico State University, MSC3Q, Box 30003, Las Cruces, NM 88003;

    phone: 575-646-3239;

    fax: 575-646-6041;

    e-mail: jwang@nmsu.edu.;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Disking, Dust, Field scale, Lagrangian transport, Laser radar, LIDAR, Near-field, Particulate matter, PM 10 , Random walk model;

    机译:磁盘打磨;粉尘;现场规模;拉格朗日运输;激光雷达;激光雷达;近场;颗粒物;PM 10;随机游走模型;

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