Literature DB >> 28448843

Prediction of PM2.5 along urban highway corridor under mixed traffic conditions using CALINE4 model.

Rajni Dhyani1, Niraj Sharma2, Animesh Kumar Maity3.   

Abstract

The present study deals with spatial-temporal distribution of PM2.5 along a highly trafficked national highway corridor (NH-2) in Delhi, India. Population residing in areas near roads and highways of high vehicular activities are exposed to high levels of PM2.5 resulting in various health issues. The spatial extent of PM2.5 has been assessed with the help of CALINE4 model. Various input parameters of the model were estimated and used to predict PM2.5 concentration along the selected highway corridor. The results indicated that there are many factors involved which affects the prediction of PM2.5 concentration by CALINE4 model. In fact, these factors either not considered by model or have little influence on model's prediction capabilities. Therefore, in the present study CALINE4 model performance was observed to be unsatisfactory for prediction of PM2.5 concentration.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Keywords:  CALINE4 model; Deposition velocity; Mixed traffic; Molecular mass; PM(2.5); Settling velocity

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Year:  2017        PMID: 28448843     DOI: 10.1016/j.jenvman.2017.04.041

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  1 in total

1.  Design of a Spark Big Data Framework for PM2.5 Air Pollution Forecasting.

Authors:  Dong-Her Shih; Thi Hien To; Ly Sy Phu Nguyen; Ting-Wei Wu; Wen-Ting You
Journal:  Int J Environ Res Public Health       Date:  2021-07-02       Impact factor: 3.390

  1 in total

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