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A comparison of plume rise algorithms to stack plume measurements in the Athabasca oil sands

机译:羽流升高算法与堆积羽毛测量的比较

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Plume rise parameterizations calculate the rise of pollutant plumes due to effluent buoyancy and exit momentum. Some form of these parameterizations is used by most air quality models. In this paper, the performance of the commonly used Briggs plume rise algorithm was extensively evaluated, through a comparison of the algorithm's results when driven by meteorological observations with direct observations of plume heights in the Athabasca oil sands region. The observations were carried out as part of the Canada-Alberta Joint Oil Sands Monitoring Plan in August and September of 2013. Wind and temperature data used to drive the algorithm were measured in the region of emissions from various platforms, including two meteorological towers, a radio-acoustic profiler, and a research aircraft. Other meteorological variables used to drive the algorithm include friction velocity, boundary-layer height, and the Obukhov length. Stack emissions and flow parameter information reported by continuous emissions monitoring systems (CEMSs) were used to drive the plume rise algorithm. The calculated plume heights were then compared to interpolated aircraft SO2 measurements, in order to evaluate the algorithm's prediction for plume rise. We demonstrate that the Briggs algorithm, when driven by ambient observations, significantly underestimated plume rise for these sources, with more than 50 % of the predicted plume heights falling below half the observed values from this analysis. With the inclusion of the effects of effluent momentum, the choice of different forms of parameterizations, and the use of different stability classification systems, this essential finding remains unchanged. In all cases, approximately 50 % or more of the predicted plume heights fall below half the observed values. These results are in contrast to numerous plume rise measurement studies published between 1968 and 1993. We note that the observations used to drive the algorithms imply the potential presence of
机译:羽流升高参数化由于流出物浮力和出口动量而计算污染物羽毛的升高。大多数空气质量模型使用这些参数化的某种形式。在本文中,广泛地评估了常用的Briggs流量升高算法的性能,通过对算法的结果进行了广泛评估了气象观察的导向,具有在Athabasca油砂区域的羽流高度的直接观察。该观察结果是在2013年8月和9月的加拿大 - 艾伯塔联合油砂监测计划的一部分进行的。用于驱动算法的风和温度数据在各种平台的排放区域中测量,包括两个气象塔,a无线电声学分析器和一架研究飞机。用于驱动算法的其他气象变量包括摩擦速度,边界层高度和Obukhov长度。连续排放监测系统(CEMS)报告的堆栈排放和流量参数信息用于驱动羽流升高算法。然后将计算出的羽流高度与内插飞机SO2测量进行比较,以便评估算法对羽流升高的预测。我们证明,在环境观测驱动时,Briggs算法显着低估了这些来源的羽流升高,其中超过50%的预测羽流量从该分析中落下了观察到的值的一半。含有流出动量的影响,选择不同形式的参数化,以及使用不同的稳定性分类系统,这种必要的发现保持不变。在所有情况下,预测羽流高度的大约50%或更多的羽流下降到观察到的值的一半。这些结果与1968年至1993年间发布的众多羽流量测量研究相反。我们注意到用于驱动算法的观察意味着潜在的存在意味着

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  • 来源
    《Atmospheric chemistry and physics》 |2018年第2期|共20页
  • 作者单位

    York Univ Earth &

    Space Sci &

    Engn N York ON Canada;

    Environm &

    Climate Change Canada Sci &

    Technol Branch Atmospher Sci &

    Technol Directorate Air Qual Modelling &

    Integrat Sect Air Qual Res D Gatineau PQ Canada;

    Environm &

    Climate Change Canada Sci &

    Technol Branch Atmospher Sci &

    Technol Directorate Air Qual Proc Res Sect Air Qual Res Div Gatineau PQ Canada;

    Environm &

    Climate Change Canada Sci &

    Technol Branch Atmospher Sci &

    Technol Directorate Air Qual Modelling &

    Integrat Sect Air Qual Res D Gatineau PQ Canada;

    Environm &

    Climate Change Canada Sci &

    Technol Branch Atmospher Sci &

    Technol Directorate Air Qual Modelling &

    Integrat Sect Air Qual Res D Gatineau PQ Canada;

    Environm &

    Climate Change Canada Sci &

    Technol Branch Atmospher Sci &

    Technol Directorate Air Qual Modelling &

    Integrat Sect Air Qual Res D Gatineau PQ Canada;

    Environm &

    Climate Change Canada Sci &

    Technol Branch Atmospher Sci &

    Technol Directorate Air Qual Proc Res Sect Air Qual Res Div Gatineau PQ Canada;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 大气科学(气象学);
  • 关键词

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