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Adding spatial flexibility to source-receptor relationships for air quality modeling

机译:为空气质量建模增加源-受体关系的空间灵活性

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摘要

To cope with computing power limitations, air quality models that are used in integrated assessment applications are generally approximated by simpler expressions referred to as “source-receptor relationships (SRR)”. In addition to speed, it is desirable for the SRR also to be spatially flexible (application over a wide range of situations) and to require a “light setup” (based on a limited number of full Air Quality Models - AQM simulations). But “speed”, “flexibility” and “light setup” do not naturally come together and a good compromise must be ensured that preserves “accuracy”, i.e. a good comparability between SRR results and AQM.In this work we further develop a SRR methodology to better capture spatial flexibility. The updated methodology is based on a cell-to-cell relationship, in which a bell-shape function links emissions to concentrations. Maintaining a cell-to-cell relationship is shown to be the key element needed to ensure spatial flexibility, while at the same time the proposed approach to link emissions and concentrations guarantees a “light set-up” phase. Validation has been repeated on different areas and domain sizes (countries, regions, province throughout Europe) for precursors reduced independently or contemporarily. All runs showed a bias around 10% between the full AQM and the SRR.This methodology allows assessing the impact on air quality of emission scenarios applied over any given area in Europe (regions, set of regions, countries), provided that a limited number of AQM simulations are performed for training.
机译:为了应对计算能力的局限性,综合评估应用程序中使用的空气质量模型通常通过称为“源-受体关系(SRR)”的简单表达式来近似。除了速度外,还希望SRR在空间上灵活(在各种情况下应用)并要求“灯光设置”(基于有限数量的完整空气质量模型-AQM模拟)。但是“速度”,“灵活性”和“灯光设置”并不能自然地融合在一起,因此必须确保做出良好的折中以保留“准确性”,即SRR结果与AQM之间的良好可比性。在这项工作中,我们进一步开发了SRR方法更好地捕捉空间灵活性。更新的方法基于细胞间关系,其中钟形函数将排放物与浓度联系起来。保持细胞间关系是确保空间灵活性所需的关键要素,与此同时,将排放物和浓度联系起来的拟议方法可确保“光建立”阶段。对于单独或同时减少的前体,已在不同地区和领域大小(国家,地区,全省)上重复进行了验证。所有运行均显示整个AQM与SRR之间存在约10%的偏差。该方法可以评估在欧洲任何给定区域(区域,区域集,国家)应用的排放情景对空气质量的影响对AQM模拟进行训练。

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