Abstract
This paper reports on the analysis and findings of the data collected during a mobile air quality campaign commissioned by the City of London Corporation (CoL). This was done using an equipped vehicle capable of taking continuous precision measurements of local air quality while travelling within the City. Several comparative analyses on measured Nitrogen Dioxide (NO2) data have been performed between Smogmobile data and those available from CoL precision systems as well as with indicative systems, namely Diffusion Tubes, distributed across the City. Key findings highlight that data collected from the Smogmobile, in terms of average concentration of NO2 across the City (62 µg/m3), are very similar to those obtained by averaging the values from the 48 indicative systems (59.5 µg/m3), with an error of just 4%. Overall, this study demonstrates significant potential and value in using mobile air quality measurements to support assessment of air quality over large areas by Local authorities.
Highlights
The current fixed station monitoring does not provide spatial variations of the pollutant concentrations across a city and tends to underestimate personal exposure, as it does not take into account all locations and activities which contribute to an individual’s exposure [1,2]
A recent study [3] used a smart personal air quality system carried by pedestrians walking on predefined paths or by bus in different locations in India; the analysis revealed non-linear relations between the gaseous pollutant concentrations versus the resistance offered by different sensors; there was not, any data-driven modelling or predictions of the pollutants being measured
The average NO2 concentration measured by the Smogmobile was adopted for the entire road line between two consecutive points
Summary
The current fixed station monitoring does not provide spatial variations of the pollutant concentrations across a city and tends to underestimate personal exposure, as it does not take into account all locations and activities which contribute to an individual’s exposure [1,2]. While outdoor fixed monitoring can provide better information about the air quality, the high level of installation (often around 3 m altitude) does not reflect a true impact of the pollution at the human level. A recent study [3] used a smart personal air quality system carried by pedestrians walking on predefined paths or by bus in different locations in India; the analysis revealed non-linear relations between the gaseous pollutant concentrations versus the resistance offered by different sensors; there was not, any data-driven modelling or predictions of the pollutants being measured. Other studies presented in [5,6] deployed similar mobile sensors near to the breathing level, but there was no data-driven modelling attached to the results, except from visual data representation
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
