Dai, Yuqing, Mazzeo, Andrea, Zhong, Jian ORCID: https://orcid.org/0000-0003-1026-8695, Cai, Xiaoming, Mele, Benedetto, Toscano, Domenico, Murena, Fabio and Rob MacKenzie, A. (2023) Modelling of deep street canyon air pollution chemistry and transport: a wintertime Naples case study. Atmosphere, 14 (9):1385. ISSN 2073-4433 (Online) (doi:10.3390/atmos14091385)

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Abstract

The impact of urban morphology on air quality, particularly within deep canyons with longer residence times for complex chemical processes, remains insufficiently addressed. A flexible multi-box framework was used to simulate air quality at different canyon heights (3 m and 12 m). This approach incorporated essential parameters, including ventilation rates, background concentrations, photochemical schemes, and reaction coefficients. A field campaign within a deep canyon with an aspect ratio of 3.7, in Naples, Italy was conducted and used for the model evaluation. The model performance demonstrated good agreement, especially at the street level, when employing a realistic light intensity profile and incorporating volatile organic compound (VOC) chemistry. Our findings indicate that peroxyl radical production affects NO2 and O3 levels by up to 9.5% in deep canyons and underscore the significance of vertical distribution (approximately 5% variance) in health assessments and urban air quality strategy development. The model response was sensitive to changes in emissions as expected, but also, somewhat more surprisingly, to background conditions, emphasizing that policies to remove pollution hotspots must include local and broader citywide action. This work advances the understanding of air quality dynamics in deep urban canyons and presents a valuable tool for effective air quality management in intricate urban environments.

Item Type:	Article
Additional Information:	This article belongs to the Special Issue Urban Air Quality Modelling.
Uncontrolled Keywords:	aspect ratio, air pollution, chemistry-transport, photochemistry, VOCs, NOx
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	15 Jan 2025 09:15
URI:	http://gala.gre.ac.uk/id/eprint/49362

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