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Vertical and Horizontal Profiles of Particulate Matter and Black Carbon Near Elevated Highways Based on Unmanned Aerial Vehicle Monitoring

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  • Rong Cao

    (Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Minhang District, Shanghai 200240, China)

  • Bai Li

    (Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Minhang District, Shanghai 200240, China)

  • Hong-Wei Wang

    (Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Minhang District, Shanghai 200240, China)

  • Shikang Tao

    (State Environmental Protection Key Laboratory of the Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, No. 508 Qinzhou Road, Xuhui District, Shanghai 200233, China)

  • Zhong-Ren Peng

    (International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, Gainesville, FL 32611, USA)

  • Hong-di He

    (Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Minhang District, Shanghai 200240, China)

Abstract

Highways passing through cities cause additional pollution inside the city. However, most of the current studies are using ground-based monitoring technologies, which make it difficult to capture the dispersion patterns of pollutants near elevated highways or transportation interchanges. The purpose of this study is to discover short-term three-dimensional variations in traffic-related pollutants based on unmanned aerial vehicles. The monitoring locations are at suburban elevated highway and transportation interchanges. The monitoring parameters include the particle number concentration (PN), particle mass concentration (PM), and black carbon (BC). The vertical profiles showed that most air pollutants increased significantly with the height of the elevated highways. Compared with the ground level, PNs increased by 54%–248% and BC increased by 201%. The decline rate of particle concentrations decreased with the increase of height and remained stable after 120 m. Furthermore, the R 2 heatmap for regressions between each altitude showed that the linear relationship between 0–120 m was higher than that of other altitudes. In horizontal profiles, PNs spread to 100 m and then began to decline, BC began to decay rapidly after 50 m, but PMs varied less. After crossing another highway, PNs increased by 69–289%, PMs by 7–28%, and BC by 101%. Furthermore, the formation of new particles was observed at both locations as PN 3 increased with distance within 100 m from the highway. This paper fills in the void of three-dimensional in situ monitoring near elevated highways, and can help develop and refine a three-dimensional traffic-related air pollution dispersion model and assess the impacts of transportation facilities on the urban environment.

Suggested Citation

  • Rong Cao & Bai Li & Hong-Wei Wang & Shikang Tao & Zhong-Ren Peng & Hong-di He, 2020. "Vertical and Horizontal Profiles of Particulate Matter and Black Carbon Near Elevated Highways Based on Unmanned Aerial Vehicle Monitoring," Sustainability, MDPI, vol. 12(3), pages 1-16, February.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:1204-:d:317791
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    Cited by:

    1. Blackman, Allen & Bonilla, Jorge A. & Villalobos, Laura, 2023. "Quantifying COVID-19’s silver lining: Avoided deaths from air quality improvements in Bogotá," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).

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