Performance Evaluation of UK ADMS-Urban Model and AERMOD Model to Predict the PM10 Concentration for Different Scenarios at Urban Roads in Chennai, India and Newcastle City, UK

Prince Vijay, S. M. Shiva Nagendra, Sunil Gulia, Mukesh Khare, Margaret Bell, Anil Namdeo

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Abstract

The pollutants and its effects on human health are now a major issue around the world. The impact of traffic and the resulting vehicle emissions has come to the forefront. Particulate matter is one among six criteria pollutants and air pollution related to particulate matter is now becoming a serious problem in developing as well as developed countries. One of the main sources is from the vehicles and the resuspension caused by the vehicular movement. Source apportionment studies of Chennai (Clean Air Asia: Air quality profile 2010 edition) showed that from the residential monitoring stations levels of particulate matter in Chennai lies in the range of 51–70 µg/m3. According to DoT of the total road emissions in UK, about 80% is generated from particulate matter which is due to road traffic even though there are no factors like resuspension in this country. In UK, 103 areas have been declared as local air quality management areas (LAQMA), while in India, 72 cities have been identified as non-attainment area with respect to various air pollutants. Chennai, India and Newcastle City, UK which are the cities under study are the one among them facing severe air pollution problems. The main objective of the paper is application and evaluation of UK ADMS-Urban and AERMOD model for the prediction of particulate matter (PM10) concentrations at urban roadways in Chennai and in Newcastle. The model evaluation has been carried out using traffic data of 2009, meteorological data provided by Laga Systems, Hyderabad for both the cities and the real-time monitored data of the year 2009. The results of the study identified the trends in pollutant patterns and its variation with the different parameters of meteorological data. The statistical descriptors, namely index of agreement (IA), fractional bias (FB), normalized mean square error (NMSE), geometric mean bias (MG) and geometric mean variance (VG) were used to understand the performance of the model. Results indicated that both the models have been able to predict the pollutant concentration with reasonable accuracy. The IA values for ADMS and AERMOD are found to be 0.39 and 0.37, and 0.48 and 0.44, respectively, for Chennai and Newcastle City.
Original languageEnglish
Title of host publicationUrban Air Quality Monitoring, Modelling and Human Exposure Assessment
EditorsS.M. Shiva Nagendra, U. Schlink, A. Müller, M. Khare
Place of PublicationSingapore
PublisherSpringer
Chapter12
Pages169-181
Number of pages13
ISBN (Electronic)9789811555114
ISBN (Print)9789811555107
DOIs
Publication statusPublished - 10 May 2021

Publication series

NameSpringer Transactions in Civil and Environmental Engineering
ISSN (Print)2363-7633
ISSN (Electronic)2363-7641

Keywords

  • UK ADMS-Urban
  • AERMOD
  • Particulate matter
  • Statistical descriptors
  • Meteorological data

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