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Developing air exchange rate models by evaluating vehicle in-cabin air pollutant exposures in a highway and tunnel setting: case study of Tehran, Iran

Nayeb Yazdi, M ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1007/s11356-018-3611-9
  3. Publisher: Springer Verlag , 2018
  4. Abstract:
  5. The passengers inside vehicles could be exposed to high levels of air pollutants particularly while driving on highly polluted and congested traffic roadways. In order to study such exposure levels and its relation to the cabin ventilation condition, a monitoring campaign was conducted to measure the levels inside the three most common types of vehicles in Tehran, Iran (a highly air polluted megacity). In this regard, carbon monoxide (CO) and particulate matter (PM) were measured for various ventilation settings, window positions, and vehicle speeds while driving on the Resalat Highway and through the Resalat Tunnel. Results showed on average in-cabin exposure to particle number and PM10 for the open windows condition was seven times greater when compared to closed windows and air conditioning on. When the vehicle was passing through the tunnel, in-cabin CO and particle number increased 100 and 30%, respectively, compared to driving on highway. Air exchange rate (AER) is a significant factor when evaluating in-cabin air pollutants level. AER was measured and simulated by a model developed through a Monte Carlo analysis of uncertainty and considering two main affecting variables, vehicle speed and fan speed. The lowest AER was 7 h−1 for the closed window and AC on conditions, whereas the highest AER was measured 70 h−1 for an open window condition and speed of 90 km h−1. The results of our study can assist policy makers in controlling in-cabin pollutant exposure and in planning effective strategies for the protection of public health. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature
  6. Keywords:
  7. Air exchange rate ; Air pollution ; Highway ; In-cabin exposure ; Monte Carlo simulations ; Tehran ; Tunnel
  8. Source: Environmental Science and Pollution Research ; 2018 ; 09441344 (ISSN)
  9. URL: https://link.springer.com/article/10.1007%2Fs11356-018-3611-9