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Short-term measurements of CO, NO, NO"2, organic compounds and PM"1"0 at a motorway location in an Austrian valley [An article from: Atmospheric Environment]

Author J. Beauchamp, A. Wisthaler, W. Grabmer, C. Neuner
Publisher Elsevier
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Book Details
PublisherElsevier
ISBN / ASINB000RR1D7A
ISBN-13978B000RR1D78
AvailabilityAvailable for download now
MarketplaceUnited States 🇺🇸

Description

This digital document is a journal article from Atmospheric Environment, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
In situ measurements of CO, NO"x, PM"1"0 and certain organic compounds took place over an 11 day period encompassing a 12h motorway blockade. Located within the Inn valley (Tirol, Austria), the monitoring site experiences varying meteorological conditions and traffic frequency throughout the day which both strongly influence air pollutant levels. Early morning increases of NO"x, PM"1"0 and aromatic hydrocarbons were clearly correlated with rising traffic. Midday minima and afternoon maxima may be explained by changing wind conditions and varying inversion layer dynamics. Night time lows in concentrations can be explained by minimal traffic activity. Classification of compound sources was made through grouping of data, separated into times when heavy duty vehicles (HDV) were permitted to use the motorway and HDV-ban periods. Increased levels of NO"x and PM"1"0 were observed from data that included periods of high HDV numbers, with levels decreasing significantly during HDV-ban periods. In contrast, the aromatic hydrocarbons and CO displayed only minor variations between these two periods. Furthermore, on typical workdays NO"x levels reached a maximum that corresponded to a peak in HDV numbers, whereas the aromatic compounds peaked later when LDV numbers had reached their maximum. Our findings give strong evidence that increased NO"x and PM"1"0 levels can be predominantly attributed to HDV traffic. Principal components analyses for the separated data further support this conclusion.