Download Hi-Res ImageDownload to MS-PowerPointCite This:Environ. Sci. Technol. 2020, 54, 13, 7848-7857
Comparison of Mobile and Fixed-Site Black Carbon Measurements for High-Resolution Urban Pollution Mapping
- Sarah E. ChamblissSarah E. ChamblissDepartment of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, Texas 78712, United StatesMore by Sarah E. Chambliss
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- Chelsea V. PrebleChelsea V. PrebleDepartment of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California 94720, United StatesEnergy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United StatesMore by Chelsea V. Preble
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- Julien J. CaubelJulien J. CaubelEnergy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United StatesDepartment of Mechanical Engineering, University of California, Berkeley, Berkeley, California 94720, United StatesMore by Julien J. Caubel
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- Troy CadosTroy CadosDepartment of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California 94720, United StatesEnergy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United StatesMore by Troy Cados
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- Kyle P. MessierKyle P. MessierDepartment of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, Texas 78712, United StatesEnvironmental Defense Fund, Austin, Texas 78701, United StatesMore by Kyle P. Messier
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- Ramón A. AlvarezRamón A. AlvarezEnvironmental Defense Fund, Austin, Texas 78701, United StatesMore by Ramón A. Alvarez
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- Brian LaFranchiBrian LaFranchiAclima, Inc., 10 Lombard Street, San Francisco, California 94111, United StatesMore by Brian LaFranchi
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- Melissa LundenMelissa LundenAclima, Inc., 10 Lombard Street, San Francisco, California 94111, United StatesMore by Melissa Lunden
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- Julian D. MarshallJulian D. MarshallDepartment of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195, United StatesMore by Julian D. Marshall
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- Adam A. SzpiroAdam A. SzpiroDepartment of Biostatistics, University of Washington, Seattle, Washington 98195, United StatesMore by Adam A. Szpiro
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- Thomas W. KirchstetterThomas W. KirchstetterDepartment of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California 94720, United StatesEnergy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United StatesMore by Thomas W. Kirchstetter
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- Joshua S. Apte*Joshua S. Apte*Email: [email protected]Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, Texas 78712, United StatesDepartment of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California 94720, United StatesSchool of Public Health, University of California, Berkeley, Berkeley, California 94720, United StatesMore by Joshua S. Apte
Abstract
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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