On-site assessments on variations of PM2.5, PM10, CO2 and TVOC concentrations in naturally ventilated underground parking garages with traffic volume

Zhijian Liu*, Hang Yin, Shengyuan Ma, Gaungya Jin, Jun Gao, Wenjun Ding

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

There have been an increasing number of automobile vehicles in cities, so that newly developed residential areas are mostly designed with underground parking garages (UPGs). For naturally ventilated UPGs, the ventilation performance may be insufficient to discharge totally vehicle-induced pollutants out of the enclosed underground spaces, which consequently results in threats to residents' health. This study, therefore, aims at examining the patterns of pollutant concentrations in naturally ventilation UPGs as well as their sensitivities to traffic volume. In particular, the naturally ventilated UPGs' weekday particulate matters (PM2.5 and PM10), CO2 and TVOC concentration as well as their relationships between traffic volume were quantitively evaluated based on field measurements in eight residential areas in Baoding, China. Results indicated that daily average PM2.5, PM10, CO2 and TVOC concentrations in studied UPGs were 105.81 μg/m3, 464.17 μg/m3, 571 ppm and 24 ppb, respectively. The PM2.5 concentrations in UPGs were slightly higher than that in ambient environments, while the PM10 concentrations in UPGs were significantly higher. Furthermore, both PM10 and TVOC concentrations in UPGs were in significant relationships with traffic volume at the p < 0.01 level, while the concentration of UPG PM2.5 generally exhibited a significant correlation (p < 0.01) with that of the ambient. Nevertheless, a combination of traffic volume, the ambient and accumulative effect was much better to explain the hourly PM10 concentration in UPGs. These findings will be conducive to instruct engineers with fundamental knowledge of UPG ventilation design.
Original languageEnglish
JournalEnvironmental Pollution
Volume247
Pages (from-to)626-637
ISSN0269-7491
DOIs
Publication statusPublished - 2019

Keywords

  • Correlation analysis
  • Daily variation characteristics
  • Indoor pollutant concentrations
  • Multiple regression model
  • Natural ventilation
  • Underground parking garage

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