High-Resolution Mobile Monitoring of Carbon Monoxide and Ultrafine Particle Concentrations in a Near-Road Environment

Abstract

Assessment of near-road air quality is challenging in urban environments that have roadside structures, elevated road sections, or depressed roads that may impact the dispersion of traffic emissions. Vehicles traveling on arterial roadways may also contribute to air pollution spatial variability in urban areas. To characterize the nature of near-road air quality in a complex urban environment, an instrumented all-electric vehicle was deployed to perform high spatial-and temporal-resolution mapping of ultrafine particles (UFPs, particle diameter Ͻ100 nm) and carbon monoxide (CO). Sampling was conducted in areas surrounding a highway in Durham, NC, with multiple repeats of the driving route accomplished within a morning or evening commute time frame. Six different nearroad transects were driven, which included features such as noise barriers, vegetation, frontage roads, and densely built houses. Under downwind conditions, median UFP and CO levels in near-road areas located 20 -150 m from the highway were a factor of 1.8 and 1.2 higher, respectively, than in areas characterized as urban background. Sampling in multiple near-road neighborhoods during downwind conditions revealed significant variability in absolute UFP and CO concentrations as well as in the rate of concentration attenuation with increasing distance from the highway. During low-speed meandering winds, regional UFP and CO concentrations nearly doubled relative to crosswind conditions; however, near-road UFP levels were still higher than urban background levels by a factor of 1.2, whereas near-road CO concentrations were not significantly different than the urban background.

Influence of solid noise barriers on near-road and on-road air quality

“…All air quality instruments used in mobile monitoring measured at 1-s sampling intervals, resulting in a spatial resolution of approximately 10 m at typical side road driving speeds (e.g., 30 km/h) and 25 m at highway driving speeds (e.g., 100 km/h). Hagler et al (2010) describes the vehicle set up, instrumentation, and sampling methods used in the mobile monitoring platform.…”

“…The main source of pollutants that could confound the measurements of impacts from the highway were vehicles operating on the side access roads and traffic on the arterial roads which bordered the study area. In previous studies, to aid in identifying the influence of side road traffic, major short-term spikes in concentrations in the second-by-second mobile monitoring measurements were identified using the procedure described by Hagler et al (2010). This procedure utilized shortterm fluctuations in either CO or ultrafine particles (UFPs) concentrations as exhaust indicators.…”

“…Another exception was the measurements collected along the access roads immediately behind the barriers for both sections. Since pollutants could remain elevated behind the noise barrier for extended time periods, the Hagler et al (2010) method often could not identify the influence of local, access road traffic emissions on the measurements. Thus, these behind-barrier measurements likely reflect some influence of local traffic, and these measurements would have been lower if the access road was not present.…”

Prediction of ultrafine particle number concentrations in urban environments by means of Gaussian process regression based on measurements of oxides of nitrogen

“…NOx and CO (e.g., Janhäll et al, 2004;Sardar et al, 2005;Westerdahl et al, 2005;Hagler et al, 2010), although in varying degrees depending on lower UFP cut-off diameter, distance to traffic, traffic composition and season. Morawska et al (2008) conclude that while in general there is a reasonably good correlation between UFP and traffic emitted gaseous pollutants, the existence and the degree of correlation varies.…”

Mobile monitoring for mapping spatial variation in urban air quality: Development and validation of a methodology based on an extensive dataset

“…Other studies address the potential of using mobile measurements to construct air pollution maps at a high spatial resolution (e.g. Hagler et al, 2010;Choi et al, 2012;Hudda et al, 2014;Peters et al, 2014). Mobile monitoring techniques also receive an increasing attention for participatory sensing and crowd-sourcing methods.…”