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School neighbourhood and compliance with WHO recommended annual NO2 guidelines: a case study of Greater London

School neighbourhood and compliance with WHO recommended annual NO2 guidelines: a case study of Greater London
School neighbourhood and compliance with WHO recommended annual NO2 guidelines: a case study of Greater London
Despite several national and local policies towards cleaner air in England, many schools in London breach the WHO-recommended concentrations of air pollutants such as NO2 and PM2.5. This is while, previous studies highlight significant adverse health effects of air pollutants on children's health. In this paper we adopted a Bayesian spatial hierarchical model to investigate factors that affect the odds of schools exceeding the WHO-recommended concentration of NO2 (i.e., 40 μg/m3 annual mean) in Greater London (UK). We considered a host of variables including schools' characteristics as well as their neighbourhoods' attributes from household, socioeconomic, transport-related, land use, built and natural environment characteristics perspectives. The results indicated that transport-related factors including the number of traffic lights and bus stops in the immediate vicinity of schools, and borough-level bus fuel consumption are determinant factors that increase the likelihood of non-compliance with the WHO guideline. In contrast, distance from roads, river transport, and underground stations, vehicle speed (an indicator of traffic congestion), the proportion of borough-level green space, and the area of green space at schools reduce the likelihood of exceeding the WHO recommended concentration of NO2. We repeated our analysis under a hypothetical scenario in which the recommended concentration of NO2 is 35 μg/m3 – instead of 40 μg/m3. Our results underscore the importance of adopting clean fuel technologies on buses, installing green barriers, and reducing motorised traffic around schools in reducing exposure to NO2 concentrations in proximity to schools. Also, our findings highlight the presence of environmental inequalities in the Greater London area. This study would be useful for local authority decision making with the aim of improving air quality for school-aged children in urban settings.
Air pollution, Bayesian spatial models, Neighbourhood attributes, Nitrogen dioxide, School's exposure
0048-9697
Shoari, Niloofar
9842f393-409c-4553-8835-5ae36be73488
Heydari, Shahram
0d12a583-a4e8-4888-9e51-a50d312be1e9
Blangiardo, Marta
410dbbc0-9c77-43f9-8edf-000bde88d013
Shoari, Niloofar
9842f393-409c-4553-8835-5ae36be73488
Heydari, Shahram
0d12a583-a4e8-4888-9e51-a50d312be1e9
Blangiardo, Marta
410dbbc0-9c77-43f9-8edf-000bde88d013

Shoari, Niloofar, Heydari, Shahram and Blangiardo, Marta (2021) School neighbourhood and compliance with WHO recommended annual NO2 guidelines: a case study of Greater London. Science of the Total Environment, 803, [150038]. (doi:10.1016/j.scitotenv.2021.150038).

Record type: Article

Abstract

Despite several national and local policies towards cleaner air in England, many schools in London breach the WHO-recommended concentrations of air pollutants such as NO2 and PM2.5. This is while, previous studies highlight significant adverse health effects of air pollutants on children's health. In this paper we adopted a Bayesian spatial hierarchical model to investigate factors that affect the odds of schools exceeding the WHO-recommended concentration of NO2 (i.e., 40 μg/m3 annual mean) in Greater London (UK). We considered a host of variables including schools' characteristics as well as their neighbourhoods' attributes from household, socioeconomic, transport-related, land use, built and natural environment characteristics perspectives. The results indicated that transport-related factors including the number of traffic lights and bus stops in the immediate vicinity of schools, and borough-level bus fuel consumption are determinant factors that increase the likelihood of non-compliance with the WHO guideline. In contrast, distance from roads, river transport, and underground stations, vehicle speed (an indicator of traffic congestion), the proportion of borough-level green space, and the area of green space at schools reduce the likelihood of exceeding the WHO recommended concentration of NO2. We repeated our analysis under a hypothetical scenario in which the recommended concentration of NO2 is 35 μg/m3 – instead of 40 μg/m3. Our results underscore the importance of adopting clean fuel technologies on buses, installing green barriers, and reducing motorised traffic around schools in reducing exposure to NO2 concentrations in proximity to schools. Also, our findings highlight the presence of environmental inequalities in the Greater London area. This study would be useful for local authority decision making with the aim of improving air quality for school-aged children in urban settings.

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Accepted/In Press date: 26 August 2021
Published date: 1 September 2021
Keywords: Air pollution, Bayesian spatial models, Neighbourhood attributes, Nitrogen dioxide, School's exposure

Identifiers

Local EPrints ID: 451336
URI: http://eprints.soton.ac.uk/id/eprint/451336
ISSN: 0048-9697
PURE UUID: 344e20bc-438c-4fb0-9502-40281f1b0194

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Date deposited: 21 Sep 2021 16:31
Last modified: 23 Nov 2021 12:31

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Contributors

Author: Niloofar Shoari
Author: Shahram Heydari
Author: Marta Blangiardo

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