Air quality forecasting requires appropriate models and data sources. The Fogees system presented in this paper enables mapping, evaluation and forecasting of the level of PMx pollution in the air, for urban and suburban areas. Input data were downloaded from the Meteoblue service, the GIS database and – in the case of integration with existing measurement systems – also from local air quality monitoring stations. The system uses a diagnostic model to determine the velocity field and a Lagrange model to describe pollution dispersion. The system has an autocalibration model and uses proprietary algorithms to estimate emissions from domestic heating, transport and background pollution levels. Modular design and parallel computation facilitate simultaneous calculation of forecasts for existing emission conditions and calculations for alternative emission conditions. The system permits forecasting for the next hour and for several consecutive hours. The validation results confirm that the system reliable forecasting of PM concentrations.

中文翻译：

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用于预测城市地区颗粒物浓度的 Fogees 系统


空气质量预测需要适当的模型和数据源。本文提出的 Fogees 系统能够对城市和郊区空气中 PMx 污染水平进行绘图、评估和预测。输入数据从 Meteoblue 服务、GIS 数据库下载，在与现有测量系统集成的情况下，还从当地空气质量监测站下载。该系统使用诊断模型来确定速度场，并使用拉格朗日模型来描述污染扩散。该系统具有自动校准模型，并使用专有算法来估算家庭供暖、运输和背景污染水平的排放量。模块化设计和并行计算有助于同时计算现有排放条件的预测和替代排放条件的计算。该系统允许预测下一小时和连续几个小时。验证结果证实该系统对PM浓度的预测可靠。