首页> 外文期刊>Geoscientific Model Development Discussions >The urban dispersion model EPISODE v10.0 – Part 1: An Eulerian and sub-grid-scale air quality model and its application in Nordic winter conditions
【24h】

The urban dispersion model EPISODE v10.0 – Part 1: An Eulerian and sub-grid-scale air quality model and its application in Nordic winter conditions

机译:城市分散模型集V10.0 - 第1部分:欧拉和子网级空气质量模型及其在北欧冬季条件下的应用

获取原文
           

摘要

This paper describes the Eulerian urban dispersion model EPISODE. EPISODE was developed to address a need for an urban air quality model in support of policy, planning, and air quality management in the Nordic, specifically Norwegian, setting. It can be used for the calculation of a variety of airborne pollutant concentrations, but we focus here on the implementation and application of the model for NO2 pollution. EPISODE consists of an Eulerian 3D grid model with embedded sub-grid dispersion models (e.g. a Gaussian plume model) for dispersion of pollution from line (i.e. roads) and point sources (e.g. chimney stacks). It considers the atmospheric processes advection, diffusion, and an NO2 photochemistry represented using the photostationary steady-state approximation for NO2. EPISODE calculates hourly air concentrations representative of the grids and at receptor points. The latter allow EPISODE to estimate concentrations representative of the levels experienced by the population and to estimate their exposure. This methodological framework makes it suitable for simulating NO2 concentrations at fine-scale resolution (100m) in Nordic environments. The model can be run in an offline nested mode using output concentrations from a global or regional chemical transport model and forced by meteorology from an external numerical weather prediction model; it also can be driven by meteorological observations. We give a full description of the overall model function and its individual components. We then present a case study for six Norwegian cities whereby we simulate NO2 pollution for the entire year of 2015. The model is evaluated against in situ observations for the entire year and for specific episodes of enhanced pollution during winter. We evaluate the model performance using the FAIRMODE DELTA Tool that utilises traditional statistical metrics, e.g. root mean square error (RMSE), Pearson correlation R, and bias, along with some specialised tests for air quality model evaluation. We find that EPISODE attains the DELTA Tool model quality objective in all of the stations we evaluate against. Further, the other statistical evaluations show adequate model performance but that the model scores greatly improved correlations during winter and autumn compared to the summer. We attribute this to the use of the photostationary steady-state scheme for NO2, which should perform best in the absence of local ozone photochemical production. Oslo does not comply with the NO2 annual limit set in the 2008/50/EC directive (AQD). NO2 pollution episodes with the highest NO2 concentrations, which lead to the occurrence of exceedances of the AQD hourly limit for NO2, occur primarily in the winter and autumn in Oslo, so this strongly supports the use of EPISODE for application to these wintertime events. Overall, we conclude that the model is suitable for an assessment of annual mean NO2 concentrations and also for the study of hourly NO2 concentrations in the Nordic winter and autumn environment. Further, in this work we conclude that it is suitable for a range of policy applications specific to NO2 that include pollution episode analysis, evaluation of seasonal statistics, policy and planning support, and air quality management. Lastly, we identify a series of model developments specifically designed to address the limitations of the current model assumptions. Part 2 of this two-part paper discusses the CityChem extension to EPISODE, which includes a number of implementations such as a more comprehensive photochemical scheme suitable for describing more chemical species and a more diverse range of photochemical environments, as well as a more advanced treatment of the sub-grid dispersion.
机译:本文介绍了欧拉城市分散模型集。开发的集会是为了满足城市空气质量模型,以支持北欧,特别是挪威的环境,规划和空气质量管理。它可用于计算各种空气污染物浓度,但我们专注于No2污染模型的实施和应用。集发作由eulerian 3D电网模型组成,具有嵌入的子网格分散模型(例如高斯羽毛模型),用于从线路(即道路)和点来源(例如烟囱堆栈)的污染分散。它考虑了使用光触发性稳态近似的Fore2表示的大气流程的平流,扩散和No2光化学。集发作计算了代表网格和受体点的每小时空气浓度。后者允许发作来估计代表人口所经历的水平和估计其暴露的浓度。该方法论框架使其适用于在北欧环境中以微尺度分辨率(100米)的NO2浓度模拟。该模型可以使用来自全球或区域化学传输模型的输出浓度,并由外部数值天气预报模型中的气象强制出来的脱机嵌套模式;它也可以由气象观测驱动。我们完整地描述了整体模型功能及其各个组件。然后,我们为六个挪威城市提供了一个案例研究,我们模拟了2015年整年的NO2污染。该模型是针对整年的原因观察和冬季增强污染的特定事件评估。我们使用使用传统统计指标的FairMode Delta工具评估模型性能,例如,使用传统的统计指标。根均线误差(RMSE),Pearson相关性R和偏置,以及一些用于空气质量模型评估的专业测试。我们发现这一集在我们评估的所有站点中获得了Delta工具模型质量目标。此外,其他统计评估表现出足够的模型性能,但与夏季相比,该模型在冬季和秋季的相关性大大提高了相关性。我们将这一点归因于使用Photostationary稳态方案的NO2,这应该在没有局部臭氧的光化学生产的情况下表现最好。奥斯陆不遵守2008/50 / EC指令(AQD)中的NO2年度限额。 No2污染剧集具有最高的No2浓度,导致No2的AQD每小时限制的超标发生,主要在奥斯陆的冬季和秋季发生,因此这强烈支持使用集中应用于这些冬季事件的剧集。总体而言,我们得出结论,该模型适用于年均平均No2浓度的评估,也适用于北欧冬季和秋季环境中每小时No2浓度的研究。此外,在这项工作中,我们得出结论,它适用于一系列特定于NO2的政策应用,包括污染发作分析,季节性统计,政策和规划支持以及空气质量管理。最后,我们确定了一系列专门设计用于解决当前模型假设的局限性的模型开发。这篇两部分纸的第2部分讨论了Citychem扩展到集中,包括许多实现,例如更全面的光化学方案,适用于描述更多化学品种和更多样化的光化学环境,以及更先进的治疗子网分散。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号