Understanding spatial variability of NO2 in urban areas using spatial modelling and data fusion approaches

Munir, S. orcid.org/0000-0002-7163-2107, Mayfield, M. orcid.org/0000-0002-9174-1773 and Coca, D. orcid.org/0000-0003-2878-2422 (2021) Understanding spatial variability of NO2 in urban areas using spatial modelling and data fusion approaches. Atmosphere, 12 (2). 179.

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2021 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Keywords: nitrogen dioxide; spatial variability; urban air quality; data fusion; dispersion modelling; land use regression; Sheffield
Dates:
  • Accepted: 25 January 2021
  • Published (online): 29 January 2021
  • Published: 29 January 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 09 Mar 2021 08:21
Last Modified: 09 Mar 2021 08:21
Status: Published
Publisher: MDPI AG
Refereed: Yes
Identification Number: https://doi.org/10.3390/atmos12020179

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