Data fusion systems are developed to fill the gap between monitoring networks and CTMs. However, they often do not account for temporal dynamics, leading to potential inaccurate air quality assessment and forecasting. We propose a statistical data assimilation strategy for fusing the CTM output with monitoring data in order to improve air quality assessment and forecasting in the Emilia-Romagna region, Italy. We employ dynamic linear modeling to accommodate dependence across time and obtain air pollution assessment and forecasting for the current and next two days. Finally, air pollution forecast maps are provided at high spatial resolution. We apply our strategy to particulate matter (PM10) concentrations during winter 2013.

Paci, L., Bonafè, G., Trivisano, C., Dynamic Data Fusion Approach for Air Quality Assessment, in Steyn, D., Chaumerliac, C. N. (ed.), Air Pollution Modeling and its Applications XXIV, Springer International Publishing, Cham 2016: 629- 633. 10.1007/978-3-319-24478-5_102 [http://hdl.handle.net/10807/98614]

Dynamic Data Fusion Approach for Air Quality Assessment

Paci, Lucia;
2016

Abstract

Data fusion systems are developed to fill the gap between monitoring networks and CTMs. However, they often do not account for temporal dynamics, leading to potential inaccurate air quality assessment and forecasting. We propose a statistical data assimilation strategy for fusing the CTM output with monitoring data in order to improve air quality assessment and forecasting in the Emilia-Romagna region, Italy. We employ dynamic linear modeling to accommodate dependence across time and obtain air pollution assessment and forecasting for the current and next two days. Finally, air pollution forecast maps are provided at high spatial resolution. We apply our strategy to particulate matter (PM10) concentrations during winter 2013.
eng
Air Pollution Modeling and its Applications XXIV
978-3-319-24476-1
Springer International Publishing
Paci, L., Bonafè, G., Trivisano, C., Dynamic Data Fusion Approach for Air Quality Assessment, in Steyn, D., Chaumerliac, C. N. (ed.), Air Pollution Modeling and its Applications XXIV, Springer International Publishing, Cham 2016: 629- 633. 10.1007/978-3-319-24478-5_102 [http://hdl.handle.net/10807/98614]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10807/98614
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