An Hourly Regression Model for Ultrafine Particles in a Near-Highway Urban Area
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- 作者：Allison P. Patton ; Caitlin Collins ; Elena N. Naumova ; Wig Zamore ; Doug Brugge ; John L. Durant
- 刊名：Environmental Science & Technology
- 出版年：2014
- 出版时间：March 18, 2014
- 年：2014
- 卷：48
- 期：6
- 页码：3272-3280
- 全文大小：462K
- 年卷期：v.48,no.6(March 18, 2014)
- ISSN：1520-5851
文摘
Estimating ultrafine particle number concentrations (PNC) near highways for exposure assessment in chronic health studies requires models capable of capturing PNC spatial and temporal variations over the course of a full year. The objectives of this work were to describe the relationship between near-highway PNC and potential predictors, and to build and validate hourly log鈥搇inear regression models. PNC was measured near Interstate 93 (I-93) in Somerville, MA using a mobile monitoring platform driven for 234 h on 43 days between August 2009 and September 2010. Compared to urban background, PNC levels were consistently elevated within 100鈥?00 m of I-93, with gradients impacted by meteorological and traffic conditions. Temporal and spatial variables including wind speed and direction, temperature, highway traffic, and distance to I-93 and major roads contributed significantly to the full regression model. Cross-validated model R2 values ranged from 0.38 to 0.47, with higher values achieved (0.43 to 0.53) when short-duration PNC spikes were removed. The model predicts highest PNC near major roads and on cold days with low wind speeds. The model allows estimation of hourly ambient PNC at 20-m resolution in a near-highway neighborhood.