Atmospheric Environment: X (Apr 2021)

Past, present, and future of ultrafine particle exposures in North America

  • Albert A. Presto,
  • Provat K. Saha,
  • Allen L. Robinson

Journal volume & issue
Vol. 10
p. 100109

Abstract

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There is growing concern that exposure to ultrafine particles (UFP, particles with diameter < 100 nm) may have health effects distinct from exposure to fine particulate matter mass (PM2.5). This investigative review examines spatial and temporal trends in UFP concentrations in North America. We analyze (i) multiyear (2006–2016) datasets from 11 stationary sampling sites and (ii) shorter duration, but highly spatially resolved mobile/stationary sampling data (2017–2019) in three cities (Baltimore, Oakland, and Pittsburgh). UFP concentrations have fallen by an average 30% over the past decade, similar to the reduction of PM2.5 mass concentration (35%). UFP reductions are likely a co-benefit of PM2.5 and other pollutant regulations. UFP have a factor of two to three spatial variation both within and between cities. Traffic is a major factor influencing intra-urban spatial variations. New particle formation (nucleation) is also an important source of UFP in many places. Regulations to reduce SO2 emissions from coal combustion have reduced nucleation events in the Eastern U.S., but some coastal areas with Mediterranean climates still have consistent new particle formation events. Highly spatially resolved UFP exposures in urban areas can be estimated using spatial models such as land use regression (LUR) fit to high spatial resolution data. Data collection for these models often uses mobile monitoring or other short-term sampling strategies because there is not a national-scale monitoring network for UFP. Short-term sampling produces LURs with modest (R2 < 0.5) performance; model performance can be improved with additional sampling. The current ability to estimate exposure at high spatial resolution over larger (e.g., national) scales is limited by a lack of data. We discuss strategies to improve UFP quantification and therefore exposure estimates.

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