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Sustainability
Volume 16
Issue 15
10.3390/su16156355
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Article

Inland O3 Production Due to Nitrogen Dioxide Transport Downwind a Coastal Urban Area: A Neural Network Assessment

by
Piero Chiacchiaretta
1,2,
Eleonora Aruffo
1,2,*,
Alessandra Mascitelli
1,2,3,
Carlo Colangeli
4,5,
Sergio Palermi
6,
Sebastiano Bianco
6 and
Piero Di Carlo
1,2
1
Department of Advanced Technologies in Medicine & Dentistry, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy
2
Center for Advanced Studies and Technology (CAST), University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy
3
National Research Council-Institute of Atmospheric Sciences and Climate (CNR-ISAC), Via del Fosso del Cavaliere 100, 00133 Rome, Italy
4
Arta Abruzzo Provincial District of Chieti, Via Spezioli 52, 66100 Chieti, Italy
5
Department of Psychological, Health and Territory Science, University of “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy
6
Arta Abruzzo Provincial District of Pescara, Viale Marconi 51, 65126 Pescara, Italy
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(15), 6355; https://doi.org/10.3390/su16156355
Submission received: 21 June 2024 / Revised: 8 July 2024 / Accepted: 22 July 2024 / Published: 25 July 2024
(This article belongs to the Special Issue Air Pollution Management and Environment Research)
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Abstract

The tropospheric production of O3 is complex, depending on nitrogen oxides (NOx = NO + NO2), volatile organic compounds (VOCs), and solar radiation. We present a case study showing that the O3 concentration is higher in a rural area, 14 km downwind from a coastal town in Central Italy, compared with the urban environment. The hypothesis is that the O3 measured inland results from the photochemical processes occuring in air masses originating at the urban site, which is richer in NOx emissions, during their transport inland.To demonstrate this hypothesis, a feed forward neural network (FFNN) is used to model the O3 measured at the rural site, comparing the modeled O3 and the measured O3 in different scenarios, which include both input parameters related to local O3 production by photochemistry and input parameters associated with regional transport of O3 precursors. The simulation results show that the local NOx concentration is not a good input to model the observed O3 (R = 0.17); on the contrary including the wind speed and direction as input of the FFNN model, the modelled O3 is well correlated with that measured O3 (R = 0.82).
Keywords: nitrogen oxides; O3; neural network; regional transport; air pollution; troposphere nitrogen oxides; O3; neural network; regional transport; air pollution; troposphere

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MDPI and ACS Style

Chiacchiaretta, P.; Aruffo, E.; Mascitelli, A.; Colangeli, C.; Palermi, S.; Bianco, S.; Di Carlo, P. Inland O3 Production Due to Nitrogen Dioxide Transport Downwind a Coastal Urban Area: A Neural Network Assessment. Sustainability 2024, 16, 6355. https://doi.org/10.3390/su16156355

AMA Style

Chiacchiaretta P, Aruffo E, Mascitelli A, Colangeli C, Palermi S, Bianco S, Di Carlo P. Inland O3 Production Due to Nitrogen Dioxide Transport Downwind a Coastal Urban Area: A Neural Network Assessment. Sustainability. 2024; 16(15):6355. https://doi.org/10.3390/su16156355

Chicago/Turabian Style

Chiacchiaretta, Piero, Eleonora Aruffo, Alessandra Mascitelli, Carlo Colangeli, Sergio Palermi, Sebastiano Bianco, and Piero Di Carlo. 2024. "Inland O3 Production Due to Nitrogen Dioxide Transport Downwind a Coastal Urban Area: A Neural Network Assessment" Sustainability 16, no. 15: 6355. https://doi.org/10.3390/su16156355

APA Style

Chiacchiaretta, P., Aruffo, E., Mascitelli, A., Colangeli, C., Palermi, S., Bianco, S., & Di Carlo, P. (2024). Inland O3 Production Due to Nitrogen Dioxide Transport Downwind a Coastal Urban Area: A Neural Network Assessment. Sustainability, 16(15), 6355. https://doi.org/10.3390/su16156355

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