Combining Measurements from Mobile Monitoring and a Reference Site To Develop Models of Ambient Ultrafine Particle Number Concentration at Residences.

Environmental Science & Technology
Matthew C SimonJohn L Durant

Abstract

Significant spatial and temporal variation in ultrafine particle (UFP; <100 nm in diameter) concentrations creates challenges in developing predictive models for epidemiological investigations. We compared the performance of land-use regression models built by combining mobile and stationary measurements (hybrid model) with a regression model built using mobile measurements only (mobile model) in Chelsea and Boston, MA (USA). In each study area, particle number concentration (PNC; a proxy for UFP) was measured at a stationary reference site and with a mobile laboratory driven along a fixed route during an ∼1-year monitoring period. In comparing PNC measured at 20 residences and PNC estimates from hybrid and mobile models, the hybrid model showed higher Pearson correlations of natural log-transformed PNC ( r = 0.73 vs 0.51 in Chelsea; r = 0.74 vs 0.47 in Boston) and lower root-mean-square error in Chelsea (0.61 vs 0.72) but no benefit in Boston (0.72 vs 0.71). All models overpredicted log-transformed PNC by 3-6% at residences, yet the hybrid model reduced the standard deviation of the residuals by 15% in Chelsea and 31% in Boston with better tracking of overnight decreases in PNC. Overall, the hybrid model considerably outperfor...Continue Reading

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Citations

May 10, 2019·International Journal of Environmental Research and Public Health·Doug Brugge
Jul 22, 2021·Environmental Science & Technology·Provat K SahaAlbert A Presto
Jun 1, 2019·Environmental Science & Technology·Provat K SahaAlbert A Presto
Jan 30, 2020·Environmental Science & Technology·David J MillerRamón A Alvarez

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