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Comparison of Mobile and Fixed-Site Black Carbon Measurements for High-Resolution Urban Pollution Mapping

  • Sarah E. Chambliss
    Sarah E. Chambliss
    Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, Texas 78712, United States
  • Chelsea V. Preble
    Chelsea V. Preble
    Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California 94720, United States
    Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
  • Julien J. Caubel
    Julien J. Caubel
    Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
    Department of Mechanical Engineering, University of California, Berkeley, Berkeley, California 94720, United States
  • Troy Cados
    Troy Cados
    Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California 94720, United States
    Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
    More by Troy Cados
  • Kyle P. Messier
    Kyle P. Messier
    Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, Texas 78712, United States
    Environmental Defense Fund, Austin, Texas 78701, United States
  • Ramón A. Alvarez
    Ramón A. Alvarez
    Environmental Defense Fund, Austin, Texas 78701, United States
  • Brian LaFranchi
    Brian LaFranchi
    Aclima, Inc., 10 Lombard Street, San Francisco, California 94111, United States
  • Melissa Lunden
    Melissa Lunden
    Aclima, Inc., 10 Lombard Street, San Francisco, California 94111, United States
  • Julian D. Marshall
    Julian D. Marshall
    Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195, United States
  • Adam A. Szpiro
    Adam A. Szpiro
    Department of Biostatistics, University of Washington, Seattle, Washington 98195, United States
  • Thomas W. Kirchstetter
    Thomas W. Kirchstetter
    Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California 94720, United States
    Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
  • , and 
  • Joshua S. Apte*
    Joshua S. Apte
    Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, Texas 78712, United States
    Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California 94720, United States
    School of Public Health, University of California, Berkeley, Berkeley, California 94720, United States
    *Email: [email protected]
Cite this: Environ. Sci. Technol. 2020, 54, 13, 7848–7857
Publication Date (Web):June 11, 2020
https://doi.org/10.1021/acs.est.0c01409
Copyright © 2020 American Chemical Society

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    Supporting Info (1)»

    Abstract

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    Urban concentrations of black carbon (BC) and other primary pollutants vary on small spatial scales (<100m). Mobile air pollution measurements can provide information on fine-scale spatial variation, thereby informing exposure assessment and mitigation efforts. However, the temporal sparsity of these measurements presents a challenge for estimating representative long-term concentrations. We evaluate the capabilities of mobile monitoring in the represention of time-stable spatial patterns by comparing against a large set of continuous fixed-site measurements from a sampling campaign in West Oakland, California. Custom-built, low-cost aerosol black carbon detectors (ABCDs) provided 100 days of continuous measurements at 97 near-road and 3 background fixed sites during summer 2017; two concurrently operated mobile laboratories collected over 300 h of in-motion measurements using a photoacoustic extinctiometer. The spatial coverage from mobile monitoring reveals patterns missed by the fixed-site network. Time-integrated measurements from mobile lab visits to fixed-site monitors reveal modest correlation (spatial R2 = 0.51) with medians of full daytime fixed-site measurements. Aggregation of mobile monitoring data in space and time can mitigate high levels of uncertainty associated with measurements at precise locations or points in time. However, concentrations estimated by mobile monitoring show a loss of spatial fidelity at spatial aggregations greater than 100 m.

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.0c01409.

    • Comparison metrics, calculation of effective LOD, analysis by land use category, instrument and temporal sampling bias ratios, sensitivity to long-range transport events, in-motion co-location vs short-term stationary co-location, figures, tables, and references (PDF)

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    Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

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