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Sci Total Environ. 2018 Apr 1;619-620:480-490. doi: 10.1016/j.scitotenv.2017.11.024. Epub 2017 Nov 29.

Use of a handheld low-cost sensor to explore the effect of urban design features on local-scale spatial and temporal air quality variability.

Author information

1
MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Chemical Sciences, School of Environment, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand. Electronic address: georgia.miskell@auckland.ac.nz.
2
MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Chemical Sciences, School of Environment, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand.

Abstract

Portable low-cost instruments have been validated and used to measure ambient nitrogen dioxide (NO2) at multiple sites over a small urban area with 20min time resolution. We use these results combined with land use regression (LUR) and rank correlation methods to explore the effects of traffic, urban design features, and local meteorology and atmosphere chemistry on small-scale spatio-temporal variations. We measured NO2 at 45 sites around the downtown area of Vancouver, BC, in spring 2016, and constructed four different models: i) a model based on averaging concentrations observed at each site over the whole measurement period, and separate temporal models for ii) morning, iii) midday, and iv) afternoon. Redesign of the temporal models using the average model predictors as constants gave three 'hybrid' models that used both spatial and temporal variables. These accounted for approximately 50% of the total variation with mean absolute error±5ppb. Ranking sites by concentration and by change in concentration across the day showed a shift of high NO2 concentrations across the central city from morning to afternoon. Locations could be identified in which NO2 concentration was determined by the geography of the site, and others as ones in which the concentration changed markedly from morning to afternoon indicating the importance of temporal controls. Rank correlation results complemented LUR in identifying significant urban design variables that impacted NO2 concentration. High variability across a relatively small space was partially described by predictor variables related to traffic (bus stop density, speed limits, traffic counts, distance to traffic lights), atmospheric chemistry (ozone, dew point), and environment (land use, trees). A high-density network recording continuously would be needed fully to capture local variations.

KEYWORDS:

Land use regression; Nitrogen dioxide; Spatio-temporal; Urban network

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