Vehicle-induced fugitive particulate matter emissions in a city of arid desert climate
Graphical abstract
Introduction
Road traffic is an indisputable source of particulate matter (PM) pollution in urban areas (Pant and Harrison, 2013). Exposure to vehicular PM can cause acute respiratory and cardiopulmonary conditions, especially to sensitive groups such as children and elders (Brauer, 2002; Fan et al., 2009). Therefore, exhaust particles that come out of a vehicle's tailpipe have been extensively studied and widely regulated in many European and North American countries (Thorpe and Harrison, 2008). Over the years, implementation of emissions control strategies has led to successful reduction in exhaust PM. In contrast, little has been done to address the impact of the non-exhaust (i.e., fugitive) sources (Shirmohammadi et al., 2017).
Vehicle-induced fugitive particulate matter (VfPM) is generated from the abrasion of brake, tire and road components as well as resuspension of dust by the passing vehicles (Kumar et al., 2013). The latter being of greater importance in areas and urban environments with desert arid climate (Tsiouri et al., 2015). Studies in North Carolina, USA suggested that VfPM is the main source of PM10 (≤10 μm in aerodynamic diameter) in urban roads (Abu-Allaban et al., 2003). Measurements collected from two different types of roads in Switzerland found that brake wear and road dust contributed 59% of the total PM10, compared to 41% from exhaust sources (Bukowiecki et al., 2010). Furthermore, abrasion of brake and tire components can produce enormous amounts of sub-micron sized particles (<300 nm in diameter), which pose a higher risk on human health (Kumar et al., 2013). Despite their significance in urban roads, the current knowledge on VfPM and their behavior is far from comprehensive (Pant and Harrison, 2013).
Various techniques have been developed to measure and characterize VfPM. The conventional techniques include quantifying VfPM under real-time conditions through simultaneous measurements at a road-side and a background location (Harrison et al., 2012; Krecl et al., 2018), measuring concentrations at the ends of a road tunnel with known boundary conditions (Lawrence et al., 2016; Riccio et al., 2016) or collecting direct measurements using mobile vehicles (Hussein et al., 2008; Kwak et al., 2014). In reality, estimating individual contributions from non-exhaust (VfPM) traffic sources is difficult because of the interactions between the different sources (e.g., differentiating between the wear directly emitted by the road surface and the pre-deposited material on the road) (Thorpe and Harrison, 2008). Chemical characterization and source apportionment methods are often combined to determine source-specific contributions through the fingerprints of their tracer elements (Amato et al., 2016a). For instance, Bukowiecki et al. (2010) carried out an elemental size-segregated measuring campaign at two different roads in Switzerland, where the USEPA Positive Matrix Factorization (PMF) model was employed to identify source contributions and estimate PM10 emission factors (EFs) for brake wear and resuspension using pre-estimated NOx EFs for Switzerland (INFRAS, 2007). Other studies aimed to examine a particular mechanism under a controlled environment, such as the use of laboratory scale models to simulate road-tire interactions (Grigoratos et al., 2018). Laboratory set ups are advantageous in maximizing the collection of particles, but they tend to underestimate emissions, probably due to the elimination of real world dilution effects (Aatmeeyata et al., 2009; Dahl et al., 2006).
The amount and characteristics of emitted VfPM are highly dependent on meteorology, surface characteristics, and driving conditions. For example, the use of studded tires during the winter season in Nordic countries can dramatically increase the amount of VfPM (Ketzel et al., 2007). In the study of Hussein et al. (2008), mobile measurements were collected from different roads and pavements in Stockholm using a modified version of the TRAKER (Testing Re-entrained Aerosol Kinetic Emissions from Roads) test vehicle (described in Etyemezian et al., 2003). The results showed that studded tires increase road dust emissions between 2.0 and 6.4 times compared to friction tires and 4.4 to 17.0 times compared to summer tires. In contrast, a recent study by Lawrence et al. (2016) estimated non-exhaust PM10 EFs from a busy tunnel in London to be just slightly higher (i.e., 16.7–19.3 mg VKT−1 – vehicle kilometer travelled) compared to exhaust emissions (i.e., 11.1–12.8 mg VKT−1). In a similar way, resuspension of road dust during wet conditions (e.g., rain or snowfall) is low compared to dry periods when evaporation rates increase with temperature (Omstedt et al., 2005).
Surely, there is a large number of specific EFs available in the literature to calculate VfPM emissions based on road type, vehicle class, and driving conditions (some are summarized in Table 1), mostly developed for the typical fleets and climate conditions of Europe and North America. It is obvious, however, that these are so specialized that they might be restricted to specific regions, and hence, non-applicable in areas where fugitive Particulate Matter (fPM) tend to be a bigger challenge like arid or semi-arid desert climates (Hassan et al., 2016). For this reason, the overall aim is to generate EFs for VfPM appropriate for urban environments in arid desert climates.
In this work, EFs and models for such an urban environment (i.e., city of Doha, Qatar) and representative of the wider Middle East area, have been derived by utilizing field measurements taken nearby major roads, source apportionment to estimate source contributions, dispersion modeling and regression analysis. The results presented in this work aim to contribute to a more comprehensive emission inventory for fPM in arid and semi-arid desert areas.
Section snippets
Derivation of the VfPM emissions
Traffic induces PM emissions directly and indirectly. The former, referred to as vehicle exhaust (VEX) emissions, depend mainly on the vehicle numbers, type, technology and the driving conditions factors. The estimation of VEX emissions has been thoroughly studied with well-established literature, EFs and models like the European COPERT (Gkatzoflias et al., 2007) and the US MOVES (USEPA, 2016). The indirect traffic emissions (non-exhaust or VfPM) are the topic of this study. They are more
Measurements
During the campaign period, hourly air temperatures ranged from 17.4 to 45.1 °C, relative humidity from 5.9% to 34.0%, and wind speeds from 0.0 to 8.6 m s−1, as demonstrated in the Supplementary Information (SI); Table S1. Calmer winds were observed between midnight and early mornings (mostly <3 m s−1) while higher averages up to 4.1 m s−1 were reported between 1200 h and 1800 h (local time). Obviously, the measured wind direction is biased by the nearby building, as this is reflected in the
Conclusions
In this study we derived some of the first EFs and emission models to estimate VEX and VfPM in areas with arid desert climates. A combination of field measurements, chemical characterization, and dispersion modelling was used to calculate emission contributions at the measuring site. Following a linear regression analysis (using solely the traffic contributions), the fitted PM10 EF for VEX and VfPM ranged from 620 to 730 mg VKT−1 (adjusted R2 ~ 0.84), and 1080 to 1410 mg VKT−1 (adjusted R2 ~
CRediT authorship contribution statement
Hala Hassan: Conceptualization, Methodology, Software, Formal analysis, Investigation, Writing - original draft, Writing - review & editing. Prashant Kumar: Conceptualization, Resources, Supervision, Funding acquisition, Writing - review & editing. Konstantinos E. Kakosimos: Conceptualization, Validation, Methodology, Resources, Supervision, Funding acquisition, Project administration, Writing - review & editing.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This publication was made possible by a NPRP award [NPRP 7 - 649 - 2 - 241] from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors. The High-Performance Computing resources and services used in this work were provided by the IT Research Computing group in Texas A&M University at Qatar.
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