Systematic deployment of a mobile laboratory

This discussion paper is/has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP if available. Abstract In urban areas, air quality is the outcome of multiple emission sources, each emitting a different combination of air pollutants. The result is a complex mixture of pollutants with a different spatiotemporal variability for each constituent. Studies exploring average spatial patterns across urban areas typically rely on air quality monitoring networks 5 of a few sites, short multi-site saturation monitoring campaigns measuring a limited number of pollutants and/or air quality models. Each of these options has limitations. This study elucidates the main complexities of urban air quality with respect to small scale spatial differences for multiple pollutants so as to gain a better understanding of the variability in exposure estimates in urban areas. Mobile measurements of 23 air 10 pollutants were taken at high resolution in Montreal, Quebec, Canada, and examined with respect to space, time and their interrelationships. The same route was systematically followed on 34 measurement days spread over different seasons and measurements were compared to adjacent air quality monitoring network stations. This approach allowed linkage of the mobile measurements to the network observations 15 and to generate average maps that provide reliable information on the typical, annual average spatial pattern. Sharp differences in the spatial distribution were found to exist between different pollutants on the suburban scale, i.e. the neighbourhood to street scales, even for pollutants usually associated with the same specific sources. Nearby microenvironments may have a wide range in average pollution levels varying by up to 20 300 %, which may cause large misclassification errors in estimating chronic exposures in epidemiological studies. For example, NO 2 measurements next to a main road mi-croenvironment are shown to be 210–265 % higher than levels measured at a nearby urban background monitoring site, while black carbon is higher by 180–200 % and ul-trafine particles are 300 % higher. 25 For some pollutants (e.g. SO 2 and benzene), there is good correspondence on a large scale due to similar emission sources, but differences on a small scale in proximity to these sources. Moreover. hotspots of different pollutants were identified and 31586 quantified. These results demonstrate the ability of an independent heavily instru-mented mobile laboratory survey to quantify the representativeness of the monitoring sites to unmonitored locations, reveal the complex relationships between pollutants …