BigAir - BigData driving next generation of Air quality numerical models

 

Academic Track

The idea

The success of air quality forecasting, that is today a legal obligation for public administrations, crucially depends on quality of data representing pollutant emissions, and people exposure to pollution, in space and time.

The goal of BigAir is to develop a new air quality framework driven by “Floating Car Data» as proxy for road traffic at high spatial and temporal resolution, and by «Presence» as proxy for people exposure to pollution.

We aim to demonstrate and quantify how this framework improves current state-of-the-art, taking benefit of an existing large scale infrastructure for regional air quality forecasting developed in Campania (Italy), AriaSana (www.ariasana.org), that adopts state-of-the-art modelling and station-based measurements, and was modified to ingest BigData.

Results assessed by comparing pollutant concentrations at reference stations highlighted that with BigData model error improves in 11 out of 14 stations (78%), while total error across air quality network improves from 103 to 92 mg/m3 (10 %). The result is significant since error includes meteorological model error, that is not controlled by BigData.

Exposure to pollution, that is the result of pollutant presence and people presence, was entirely driven by BigData, providing unprecendented dynamic data coverage with respect current approach based on static population density layers.

Next generation of atmospheric air quality models can potentially be driven by BigData if available in Real Time mode, providing better operational forecasts. Further in the future, models may assimilate a new type of BigData: air quality directly measured by citizens, that become actors feeding a large scale data information system. Technology is being developed to achieve this, such as the AirQuino work at our CNR Lab.

 

Map of road traffic NOx emissions in Naples derived from BigData (Floating Car Data)

 

The Team

IBIMET

Beniamino Gioli, CNR IBIMET (www.ibimet.cnr.it)
Environmental Engeneer (1998) at University of Firenze
PhD in Ecology and Environmental Systems (2003) at University of Udine,
Research Scientist at IBIMET CNR, Firenze, Italy (2004-2009)
Senior Research Scientist at IBIMET CNR (since 2009).
Mobility exchanges with San Diego State University (USA) and UC Berkeley (USA)
His scientific research is focused on: i)measuring and modelling interactions between the biosphere (urban areas and ecosystems) and the atmosphere; ii) developing instruments and measurement technologies especially on mobile platform (ground vehicles, aircraft, UAV).
Participated >10 European funded (EC) research projects.
Author of > 60 peer reviewed publications in international journals, h-index 20 (from Google Scholar), acts as reviewer for international journals and funding agencies. H-index 20 @Google Scholar).

ARIANET (www.aria-net.it)
SME focused on the development and implementation of air quality modelling frameworks. Main goal of ARIANET is to contribute to the comprehension of the atmospheric environment through the numerical simulation of dispersion and transformation of airborne pollutants.

AriaSana (www.ariasana.org)
Regional infrastructure on air quality forecast for Campania region (Italy), made of state of the art modelling frameworks and observational network linked to ARPA-Campania, leaded by CNR ISAFOM-Naples.

 

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