Literature DB >> 23550900

A land use regression model for ultrafine particles in Vancouver, Canada.

Rebecca C Abernethy1, Ryan W Allen, Ian G McKendry, Michael Brauer.   

Abstract

Methods to characterize chronic exposure to ultrafine particles (UFP) can help to clarify potential health effects. Since UFP are not routinely monitored in North America, spatiotemporal models are one potential exposure assessment methodology. Portable condensation particle counters were used to measure particle number concentrations (PNC) to develop a land use regression (LUR) model. PNC, wind speed and direction were measured for sixty minutes at eighty locations during a two-week sampling campaign. We conducted continuous monitoring at four additional locations to assess temporal variation. LUR modeling utilized 135 potential geographic predictors including: road length, vehicle density, restaurant density, population density, land use and others. A novel approach incorporated meteorological data through wind roses as alternates to traditional circular buffers. The range of measured (sixty-minute median) PNC across locations varied seventy-fold (1500-105000 particles/cm(3), mean [SD] = 18200 [15900] particles/cm(3)). Correlations between PNC and concurrently measured two-week average NOX concentrations were 0.6-0.7. A PNC LUR model (R(2) = 0.48, leave-one-out cross validation R(2) = 0.32) including truck route length within 50 m, restaurant density within 200 m, and ln-distance to the port represents the first UFP LUR model in North America. Models incorporating wind roses did not explain more variability in measured PNC.

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Year:  2013        PMID: 23550900     DOI: 10.1021/es304495s

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  21 in total

1.  Outdoor ultrafine particle concentrations in front of fast food restaurants.

Authors:  Cristina Vert; Kees Meliefste; Gerard Hoek
Journal:  J Expo Sci Environ Epidemiol       Date:  2015-11-04       Impact factor: 5.563

2.  Applying land use regression model to estimate spatial variation of PM₂.₅ in Beijing, China.

Authors:  Jiansheng Wu; Jiacheng Li; Jian Peng; Weifeng Li; Guang Xu; Chengcheng Dong
Journal:  Environ Sci Pollut Res Int       Date:  2014-12-10       Impact factor: 4.223

3.  Characterization of Annual Average Traffic-Related Air Pollution Concentrations in the Greater Seattle Area from a Year-Long Mobile Monitoring Campaign.

Authors:  Magali N Blanco; Amanda Gassett; Timothy Gould; Annie Doubleday; David L Slager; Elena Austin; Edmund Seto; Timothy V Larson; Julian D Marshall; Lianne Sheppard
Journal:  Environ Sci Technol       Date:  2022-08-02       Impact factor: 11.357

4.  Insights from Application of a Hierarchical Spatio-Temporal Model to an Intensive Urban Black Carbon Monitoring Dataset.

Authors:  Travis Hee Wai; Joshua S Apte; Maria H Harris; Thomas W Kirchstetter; Christopher J Portier; Chelsea V Preble; Ananya Roy; Adam A Szpiro
Journal:  Atmos Environ (1994)       Date:  2022-03-23       Impact factor: 5.755

5.  An hourly regression model for ultrafine particles in a near-highway urban area.

Authors:  Allison P Patton; Caitlin Collins; Elena N Naumova; Wig Zamore; Doug Brugge; John L Durant
Journal:  Environ Sci Technol       Date:  2014-03-06       Impact factor: 9.028

6.  Comparisons of Traffic-Related Ultrafine Particle Number Concentrations Measured in Two Urban Areas by Central, Residential, and Mobile Monitoring.

Authors:  Matthew C Simon; Neelakshi Hudda; Elena N Naumova; Jonathan I Levy; Doug Brugge; John L Durant
Journal:  Atmos Environ (1994)       Date:  2017-09-04       Impact factor: 4.798

7.  Transferability and generalizability of regression models of ultrafine particles in urban neighborhoods in the Boston area.

Authors:  Allison P Patton; Wig Zamore; Elena N Naumova; Jonathan I Levy; Doug Brugge; John L Durant
Journal:  Environ Sci Technol       Date:  2015-04-30       Impact factor: 9.028

8.  Development of land use regression models for nitrogen dioxide, ultrafine particles, lung deposited surface area, and four other markers of particulate matter pollution in the Swiss SAPALDIA regions.

Authors:  Marloes Eeftens; Reto Meier; Christian Schindler; Inmaculada Aguilera; Harish Phuleria; Alex Ineichen; Mark Davey; Regina Ducret-Stich; Dirk Keidel; Nicole Probst-Hensch; Nino Künzli; Ming-Yi Tsai
Journal:  Environ Health       Date:  2016-04-18       Impact factor: 5.984

9.  Spatial variation in inversion-focused vs 24-h integrated samples of PM2.5 and black carbon across Pittsburgh, PA.

Authors:  Brett J Tunno; Drew R Michanowicz; Jessie L C Shmool; Ellen Kinnee; Leah Cambal; Sheila Tripathy; Sara Gillooly; Courtney Roper; Lauren Chubb; Jane E Clougherty
Journal:  J Expo Sci Environ Epidemiol       Date:  2015-04-29       Impact factor: 5.563

10.  Effects of Urban Landscape Pattern on PM2.5 Pollution--A Beijing Case Study.

Authors:  Jiansheng Wu; Wudan Xie; Weifeng Li; Jiacheng Li
Journal:  PLoS One       Date:  2015-11-13       Impact factor: 3.240

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