Mobile Particle and NOx Emission Characterization at Helsinki Downtown: Comparison of Different Traffic Flow Areas

Abstract

A two weeks measurement campaign by a mobile laboratory van was performed at downtown Helsinki, Finland, in winter 2010. The characteristics of air pollutants such as fine particles in the size ranges of 7-40 nm (N p40 ) and 40-1000 nm (N p1000 ), black carbon (BC), fine particle mass (PM 2.5 ), as well as gaseous compounds NO, NO 2 , NO x , CO and CO 2 were studied. The statistical analysis showed that the air pollution conditions strongly depended on the traffic flow area; therefore, the street sections were classified as high traffic flow areas (HTF1-HTF4), low traffic flow areas (LTF1-LTF5), and urban background areas (BG1-BG3). Large variation of particle emissions was observed, and the momentary peak particle concentrations were 8 × 10 5 cm -3 . At the HTF areas exhaust emissions followed clearly daily average heavy duty vehicle counts rather than the average daily vehicle counts. Higher correlation coefficients were found between CO 2 and NO than between CO 2 and N tot . The dispersion studies indicated that the air pollution conditions strongly improved from high traffic flow areas to low traffic flow areas. Therefore, proper city planning and locating, for example, cycle tracks, schools and hospitals farther from busy city streets might significantly reduce exposure risk for humans.

Chemical and physical characterization of traffic particles in four different highway environments in the Helsinki metropolitan area

“…Vehicle exhaust emissions constitute major sources of ultrafine particles (UFP; below 100 nm in diameter), black carbon (BC), organic carbon (OC), and NO 2 in urban environments (e.g., Pey et al, 2009;Morawska et al, 2008;Johansson et al, 2007;Lähde et al, 2014). Although during the last 15 years particle mass emissions have been significantly reduced, due to the tightened emission regulations and improvements in vehicle technology, the number emissions of the smallest UFP particles (below 50 nm in diameter) have been observed to be significant Kumar et al, 2010).…”

“…During the last decade, pollutant gradients near highways have been extensively examined in the USA Clements et al, 2009;Hagler et al, 2009;Canagaratna et al, 2010;Durant et al, 2010;Padró-Martínez et al, 2012;Massoli et al, 2012), in Canada (Beckerman et al, 2008;Gilbert et al, 2007), in Australia (Gramotnev and Ristovski, 2004), in India (Sharma et al, 2009), and in Finland (Pirjola et al, 2006Lähde et al, 2014). Generally, all of these studies showed that the pollutant concentrations were higher near highway than further from the roadside, sharply decreasing to background levels within 300-500 m downwind.…”

Developing High Spatial Resolution Concentration Maps Using Mobile Air Quality Measurements

“…An increasing number of air quality studies use mobile air pollution monitoring. Mobile measurements have several advantages over conventional stationary measurements, including the opportunity for better data coverage, efficient collection of data in close proximity to sources and logistical efficiency (Hagler et al, 2012;Hu et al, 2012;Birmili et al, 2013;Choi et al, 2013;Peters et al, 2013;Brantley et al, 2014;Lähde et al, 2014). Although mobile measurement data can be highly spatially resolved, they are not always presented as high spatial resolution concentration maps.…”

“…Recently several studies have presented concentration maps of mobile measurement data (Pirjola et al, 2012;Padró-Martínez et al, 2012;Brimili et al, 2013;Brantley et al, 2014;Lähde et al, 2014;Pattinson et al, 2014;Peters et al, 2014). Pirjola et al (2012), Lähde et al (2014) and Padró-Martínez et al (2012) do not state the spatial resolution of their maps, and provide little description of how the maps were developed; Padró-Martínez et al (2012) utilized ArcGIS 9.3.1 to develop concentration maps for individual runs.…”

“…Pirjola et al (2012), Lähde et al (2014) and Padró-Martínez et al (2012) do not state the spatial resolution of their maps, and provide little description of how the maps were developed; Padró-Martínez et al (2012) utilized ArcGIS 9.3.1 to develop concentration maps for individual runs. Brantley et al (2014) and Pattinson et al (2014) used 1 s time resolution data together with ArcGIS (ESRI) to map the median values of sets of runs and produced 50 m spatial resolution maps.…”