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Atmospheric dispersion modelling of particulate and gaseous pollutants affecting the trans-Manche region

机译:影响跨芒什地区的颗粒物和气态污染物的大气弥散模拟

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摘要

This thesis describes the development of a methodology to determine large-scale and meso-scale atmospheric dispersion patterns. The research is only concerned with outdoor exposure to atmospheric pollutants and aims to identify pollution sources using dispersion modelling with the assistance of ground level measurements from British, French and other monitoring stations and remote sensing technology. ududLagrangian Particle Dispersion (LPD) models compute trajectories of a large number of notional particles and can be used to numerically simulate the dispersion of a pollutant (passive tracer) in the planetary boundary layer. Two widely used atmospheric dispersion models were employed: the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model by R. Draxler, and the model FLEXPART by Stohl et al. Both models possess forward tracking and inverse (or receptor-based) modes. Meteorological data output from the PSU/NCAR Mesoscale model (known as MM5), or datasets from the European Centre of Medium-range Weather Forecast (ECMWF) are used to drive the dispersion models. Linkage routines were developed to interpret the LPD codes with the required meteorological information.ududThis study aims to determine whether current approaches and practice for atmospheric dispersion modelling are reliable, consistent and up-to-date. An intercomparison of the models FLEXPART and HYSPLIT is performed for known episodes to determine their accuracy, ease of use, effect of source specification and to investigate their sensitivity to input data and mesh resolution, and in particular the effect of different model formulations and assumptions followed by the models. ududThe possibility of identifying emission sources in the near and far field is investigated, by modelling dispersion backwards in time, in particular the discrimination of multiple sources from receptor data is discussed. The effect of meteorological data resolution on the output of LPD models was evaluated and the most suitable methodology for better source definition was determined for different modelling scales, ranging from the intercontinental transport of airborne pollutants to simulating pollution episodes caused by local sources.
机译:本文描述了确定大规模和中尺度大气弥散模式的方法的发展。该研究仅与室外暴露于大气污染物有关,旨在借助色散模型在英国,法国和其他监测站的地面测量以及遥感技术的帮助下,识别污染源。拉格朗日粒子扩散(LPD)模型可计算大量名义粒子的轨迹,可用于数值模拟行星边界层中污染物(无源示踪剂)的扩散。使用了两种广泛使用的大气弥散模型:R。Draxler的混合单粒子拉格朗日综合轨迹(HYSPLIT)模型和Stohl等人的FLEXPART模型。两种模型都具有前向跟踪和反向(或基于受体)模式。从PSU / NCAR中尺度模型(称为MM5)输出的气象数据,或从欧洲中程天气预报中心(ECMWF)获得的数据集,可用于驱动离散模型。开发了链接例程,以使用所需的气象信息来解释LPD代码。 ud ud本研究旨在确定大气扩散模型的当前方法和实践是否可靠,一致且最新。对已知情节进行模型FLEXPART和HYSPLIT的比较,以确定它们的准确性,易用性,源规范的影响,并调查它们对输入数据和网格分辨率的敏感性,尤其是遵循不同模型公式和假设的影响通过模型。通过在时间上向后建模扩散,研究了在近场和远场识别发射源的可能性,特别是讨论了从接收器数据中识别多个源的问题。评估了气象数据分辨率对LPD模型输出的影响,并针对不同的模型规模,确定了更合适的源定义最合适的方法,范围从航空污染物的洲际运输到模拟本地源引起的污染事件。

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    Plainiotis Stylianos;

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  • 年度 2006
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  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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