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Vehicular pollution modeling using the operational street pollution model (OSPM) for Chembur, Mumbai (India)

Megacities in India such as Mumbai and Delhi are among the most polluted places in the world. In the present study, the widely used operational street pollution model (OSPM) is applied for assessing pollutant loads in the street canyons of Chembur, a suburban area just outside Mumbai city. Chembur i...

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Bibliographic Details
Published in:Environmental monitoring and assessment 2016-06, Vol.188 (6), p.349-349, Article 349
Main Authors: Kumar, Awkash, Ketzel, Matthias, Patil, Rashmi S., Dikshit, Anil Kumar, Hertel, Ole
Format: Article
Language:English
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Summary:Megacities in India such as Mumbai and Delhi are among the most polluted places in the world. In the present study, the widely used operational street pollution model (OSPM) is applied for assessing pollutant loads in the street canyons of Chembur, a suburban area just outside Mumbai city. Chembur is both industrialized and highly congested with vehicles. There are six major street canyons in this area, for which modeling has been carried out for NO x and particulate matter (PM). The vehicle emission factors for Indian cities have been developed by Automotive Research Association of India (ARAI) for PM, not specifically for PM 10 or PM 2.5 . The model has been applied for 4 days of winter season and for the whole year to see the difference of effect of meteorology. The urban background concentrations have been obtained from an air quality monitoring station. Results have been compared with measured concentrations from the routine monitoring performed in Mumbai. NO x emissions originate mainly from vehicles which are ground-level sources and are emitting close to where people live. Therefore, those emissions are highly relevant. The modeled NO x concentration compared satisfactorily with observed data. However, this was not the case for PM, most likely because the emission inventory did not contain emission terms due to resuspended particulate matter.
ISSN:0167-6369
1573-2959
DOI:10.1007/s10661-016-5337-9