An operational urban air quality model ENFUSER, based on dispersion modelling and data assimilation

被引：19

作者：

Johansson, Lasse ^{[1
]}

Karppinen, Ari ^{[1
]}

Kurppa, Mona ^{[1
]}

Kousa, Anu ^{[2
]}

Niemi, Jarkko, V ^{[2
]}

Kukkonen, Jaakko ^{[1
,3
]}

机构：

[1] Finnish Meteorol Inst, Atmospher Composit Res, Helsinki, Finland

[2] Helsinki Reg Environm Serv Author HSY, Ilmalantori 1, Helsinki 00240, Finland

[3] Univ Hertfordshire, Ctr Atmospher & Climate Phys Res, Coll Lane, Hatfield AL10 9AB, Hertfordshire, England

来源：

ENVIRONMENTAL MODELLING & SOFTWARE | 2022年 / 156卷

关键词：

Air quality; Dispersion modelling; Data assimilation; ROAD DUST; ATMOSPHERIC COMPOSITION; HIGH-RESOLUTION; STREET CANYON; LAND-USE; EMISSIONS; POLLUTION; SYSTEM; HELSINKI; SCHEMES;

D O I：

10.1016/j.envsoft.2022.105460

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

An operational urban air quality modelling system ENFUSER is presented with an evaluation against measured data. ENFUSER combines several dispersion modelling approaches, uses data assimilation, and continuously extracts information from online, global open-access sources. The modelling area is described with a combination of geographic datasets. These GIS datasets are globally available with open access, and therefore the model can be applied worldwide. Urban scale dispersion is addressed with a combination of Gaussian puff and Gaussian plume modelling, and long-range transport of pollutants is accounted for via a separate regional model. The presented data assimilation method, which supports the use of AQ sensors and incorporates a longer-term learning mechanism, adjusts emission factors and the regional background values on an hourly basis. The model can be used with reasonable accuracy also in urban areas, for which detailed emissions inventories would not be available, due to the data assimilation capabilities.

引用

页数：19

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