Vehicle-induced fugitive particulate matter emissions in a city of arid desert climate

https://doi.org/10.1016/j.atmosenv.2020.117450Get rights and content

Abstract

This study investigates and proposes emission factors (EFs) and models for vehicle-induced exhaust (VEX) and fugitive (VfPM) particulate matter emissions representative of areas with arid climates. Particle number (PNC) and mass (PMC) concentrations and their integrated samples were collected for a period of three months for both PM10 and PM2.5 next to a trafficked road in the city of Doha, Qatar. Using Positive Matrix Factorization (PMF) on the elemental data of the samples, six distinct PM sources were identified: traffic exhaust, dust resuspension, fresh and aged sea salt, secondary aerosols, and fuel oil/shipping. Dispersion modelling and regression analysis were combined to derive EFs (linear analysis) and models (non-linear analysis) for the total traffic fleet (heavy and light duty). The estimated EFs were between 620 and 730 mg VKT−1 (VKT; Vehicle Kilometer Travelled) (adj. R2 ~ 0.84) and between 1080 and 1410 mg VKT−1 (adj. R2 ~ 0.70) for VEX and VfPM, respectively. The integration of field measurements, chemical characterization, and dispersion modelling presented herein is one of the first similar studies conducted in the wider region, identifies the importance of fugitive PM (fPM), and marks the need for further studies to improve emissions modelling of VfPM in arid desert climates.

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.

References (65)

  • V. Etyemezian et al.

    Vehicle-based road dust emission measurement: I—methods and calibration

    Atmos. Environ.

    (2003)
  • A. Goel et al.

    Characterisation of nanoparticle emissions and exposure at traffic intersections through fast–response mobile and sequential measurements

    Atmos. Environ.

    (2015)
  • N. Gopalaswami et al.

    Analysis of meteorological parameters for dense gas dispersion using mesoscale models

    J. Loss Prev. Process. Ind.

    (2015)
  • T. Grigoratos et al.

    Experimental investigation of tread wear and particle emission from tyres with different treadwear marking

    Atmos. Environ.

    (2018)
  • H.A. Hassan et al.

    Flux estimation of fugitive particulate matter emissions from loose Calcisols at construction sites

    Atmos. Environ.

    (2016)
  • J. Heo et al.

    Source apportionments of ambient fine particulate matter in Israeli, Jordanian, and Palestinian cities

    Environ. Pollut.

    (2017)
  • p. Holnicki et al.

    An urban scale application and validation of the CALPUFF model

    Atmos. Pollut. Res.

    (2016)
  • T. Hussein et al.

    Factors affecting non-tailpipe aerosol particle emissions from paved roads: on-road measurements in Stockholm, Sweden

    Atmos. Environ.

    (2008)
  • M. Ketzel et al.

    Estimation and validation of PM2.5/PM10 exhaust and non-exhaust emission factors for practical street pollution modelling

    Atmos. Environ.

    (2007)
  • S. Kontos et al.

    Modeling natural dust emissions in the central Middle East: parameterizations and sensitivity

    Atmos. Environ.

    (2018)
  • P. Krecl et al.

    Determination of black carbon, PM2.5, particle number and NOx emission factors from roadside measurements and their implications for emission inventory development

    Atmos. Environ.

    (2018)
  • P. Kumar et al.

    Nanoparticle emissions from 11 non-vehicle exhaust sources – a review

    Atmos. Environ.

    (2013)
  • J. Kwak et al.

    On-road and laboratory investigations on non-exhaust ultrafine particles from the interaction between the tire and road pavement under braking conditions

    Atmos. Environ.

    (2014)
  • S. Lawrence et al.

    Quantification of vehicle fleet PM10 particulate matter emission factors from exhaust and non-exhaust sources using tunnel measurement techniques

    Environ. Pollut.

    (2016)
  • N. Liora et al.

    The natural emissions model (NEMO): description, application and model evaluation

    Atmos. Environ.

    (2015)
  • G. Omstedt et al.

    A model for vehicle-induced non-tailpipe emissions of particles along Swedish roads

    Atmos. Environ.

    (2005)
  • P. Paatero

    Least squares formulation of robust non-negative factor analysis

    Chemometr. Intell. Lab. Syst.

    (1997)
  • P. Paatero et al.

    Understanding and controlling rotations in factor analytic models

    Chemometr. Intell. Lab. Syst.

    (2002)
  • P. Pant et al.

    Estimation of the contribution of road traffic emissions to particulate matter concentrations from field measurements: a review

    Atmos. Environ.

    (2013)
  • N. Pérez et al.

    Impact of harbour emissions on ambient PM10 and PM2.5 in Barcelona (Spain): evidences of secondary aerosol formation within the urban area

    Sci. Total Environ.

    (2016)
  • J. Pey et al.

    Chemical fingerprint and impact of shipping emissions over a western Mediterranean metropolis: primary and aged contributions

    Sci. Total Environ.

    (2013)
  • A. Riccio et al.

    Real-world automotive particulate matter and PAH emission factors and profile concentrations: results from an urban tunnel experiment in Naples

    Italy Atmos. Environ.t

    (2016)
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