Abstract
Abstract. This study evaluates a deployment strategy of a heavily instrumented mobile lab for characterizing multipollutant spatial patterns based upon a limited number of measurement days spread over different seasons. The measurements obtained through this deployment strategy are used to gain insight into average pollutant levels between routine monitoring sites and in relation to emission sources in the region, as well as to assess correlations between pollutant patterns to better understand the nature of urban air pollutant mixtures. A wide range of locations were part of the deployment in order to characterize the distribution of chronic exposures potentially allowing development of exposure models. Comparison of the mobile lab averages to the available adjacent air quality monitoring network stations to evaluate their representativeness showed that they were in reasonable agreement with the annual averages at the monitoring sites, thus providing some evidence that, through the deployment approach, the mobile lab is able to capture the main features of the average spatial patterns. The differences between mobile lab and network averages varied by pollutant with the best agreement for NO2 with a percentage difference of 20%. Sharp differences in the average spatial distribution were found to exist between different pollutants on multiple scales, particularly on the sub-urban scale, i.e., the neighborhood to street scales. For example, NO2 was observed to be 210–265% higher by the main highway in the study region compared to the nearby urban background monitoring site, while black carbon was higher by 180–200% and particle number concentration was 300% higher. The repeated measurements of near-roadway gradients showed that the rate of change differed by pollutant with elevated concentrations detected up to 600–700 m away for some pollutants. These results demonstrate that through systematic deployment mobile laboratory measurements can be used to characterize average or typical concentration patterns, thus providing data to assess monitoring site representativeness, spatial relationships between pollutants, and chronic multipollutant exposure patterns useful for evaluating and developing exposure models for outdoor concentrations in an urban environment.
Highlights
Long-term or chronic exposure to air pollution has been shown in many epidemiological studies of different types, such as cohort studies, case-control studies and cross sectional studies, to be associated with adverse human health outcomes (Ren and Tong, 2008)
We first compare the measurements obtained by CRUISER to routine measurements taken by the air quality (AQ) monitoring network to compare campaign averages to the actual annual average
We examine the spatial variability of several pollutants at the sub-urban scale with respect to their emission sources and quantitatively examine the representativeness of air quality monitoring sites to various microenvironments in their vicinity
Summary
Long-term or chronic exposure to air pollution has been shown in many epidemiological studies of different types, such as cohort studies, case-control studies and cross sectional studies, to be associated with adverse human health outcomes (Ren and Tong, 2008). While most studies have focused on correlations of outcomes (e.g., mortality) with a small number or even a single pollutant (e.g., PM2.5, NO2) (Adar et al, 2013; Jerrett et al, 2009; Pope and Dockery, 2006), it is generally believed that no single pollutant is solely responsible; rather, features of the mix of pollutants in the air, when the myriad of possible adverse health effects is considered, are more likely to be exerting the effects, possibly synergistically (Mauderly and Samet, 2009). Levy et al.: Elucidating multipollutant exposure across a complex metropolitan area
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.
