Identifying the impact of large urban airports on local air quality by nonparametric regression

被引:126
作者
Yu, KN
Cheung, YP
Cheung, T
Henry, RC
机构
[1] Univ So Calif, Dept Civil Engn, Environm Engn Program, Los Angeles, CA 90089 USA
[2] City Univ Hong Kong, Dept Phys & Mat Sci, Kowloon, Hong Kong, Peoples R China
关键词
air pollution; airports; Hong Kong; Los Angeles; receptor modeling; statistics; data analysis; nonparametric regression;
D O I
10.1016/j.atmosenv.2004.05.034
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Emissions of air pollutants from aircraft in large urban areas are a health concern to nearby residents. This study examined hourly concentrations of CO, NOx, SO2, and respirable suspended particles (RSP) taken in the vicinity of Hong Kong International Airport (HKIA) and Los Angeles International Airport (LAX). The LAX data cover the period August 1997 through March 1998 and the HKIA all of 2000 and 2001. The average concentration as a function of wind speed and direction was estimated by nonparametric regression. The error variance of the nonparametric regression results was also estimated. The results show that SO2 can be used to identify wind speeds and directions associated with emissions from aircraft. Using this assumption and the nonparametric regression plots for the other pollutants one can identify the impact of aircraft on local air quality. At LAX, CO and NOx are dominated by emissions from ground vehicles going in and out of the airport. However, near HKIA, aircraft are an important contributor to CO and RSP. At both sites, nonparametric regression identified other, smaller sources as well. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:4501 / 4507
页数:7
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