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A gaussian-box modeling approach for urban air quality management in a northern Chinese city-I. model development

机译:一种在中国北方城市中进行城市空气质量管理的高斯盒建模方法。模型开发

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摘要

A Gaussian-box modeling approach was presented in this paper to examine the urban air quality due to multiple point- and area-source emissions in the northern Chinese city of Fengnan, which is associated with a deteriorated air quality as a consequence of industrialization and rapid urban growth. A 3-D multi-box (3DMB) air quality model was developed to predict air quality due to area-source emissions. It improved upon the conventional box models by allowing consideration of more details in spatial variations of emission sources and meteorological conditions. The modeling domain was divided into various layers within the mixing height, while each layer was associated with a number of sub-boxes. A multi-source and multi-grid Gaussian modeling approach was then applied to predict the air quality in different sub-boxes that are associated with multiple point-source emissions. Thus the Gaussian-box modeling approach could effectively simulate impacts of both area- and point-source emissions but also reflect more details of the spatial variations in source distributions and meteorological conditions. This modeling approach was employed to predict daily average SO_2, TSP and PM_(10) concentrations for each sub-box during the heating and non-heating seasons, respectively. The analysis of the mean normalized error of the modeling results demonstrates the feasibility and applicability of the developed method, and the presented method could provide more useful and scientific bases for developing effective urban air quality control and management strategies.
机译:本文提出了一种高斯盒建模方法,以研究中国北方城市丰南市由于多点和面源排放导致的城市空气质量,这与工业化和快速发展导致的空气质量下降有关。城市增长。开发了3-D多箱(3DMB)空气质量模型,以预测由于面源排放而产生的空气质量。通过允许考虑排放源和气象条件的空间变化中的更多细节,它对常规盒模型进行了改进。建模域在混合高度内分为不同的层,而每一层都与许多子框相关联。然后,采用多源多网格高斯建模方法来预测与多点源排放相关的不同子框中的空气质量。因此,高斯盒建模方法可以有效地模拟面源和点源排放的影响,而且还可以反映源分布和气象条件的空间变化的更多细节。采用这种建模方法分别预测了供暖季节和非供暖季节每个子箱的每日平均SO_2,TSP和PM_(10)浓度。对建模结果的平均归一化误差进行分析,证明了该方法的可行性和适用性,为开发有效的城市空气质量控制和管理策略提供了更为有用和科学的依据。

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