Cargando…
PM(2.5) concentration prediction during COVID-19 lockdown over Kolkata metropolitan city, India using MLR and ANN models
Kolkata is the third densely populated city of India and Kolkata stands in the World's 25 most polluted cities along with 10 worse polluted cities in India. The relevant study claims that due to the imposition of lockdown during COVID-19 pandemic, the atmospheric pollution level has been signif...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040498/ https://www.ncbi.nlm.nih.gov/pubmed/37522150 http://dx.doi.org/10.1016/j.envc.2021.100155 |
_version_ | 1784694350160068608 |
---|---|
author | Bera, Biswajit Bhattacharjee, Sumana Sengupta, Nairita Saha, Soumik |
author_facet | Bera, Biswajit Bhattacharjee, Sumana Sengupta, Nairita Saha, Soumik |
author_sort | Bera, Biswajit |
collection | PubMed |
description | Kolkata is the third densely populated city of India and Kolkata stands in the World's 25 most polluted cities along with 10 worse polluted cities in India. The relevant study claims that due to the imposition of lockdown during COVID-19 pandemic, the atmospheric pollution level has been significantly reduced over the metropolitan city Kolkata like other cities of the world. The main objective of this study is to predict the concentration of PM(2.5) using multiple linear regression (MLR) and artificial neural network (ANN) models and similarly, to compare the accuracy level of two models. The concentration of PM(2.5) data has been obtained from state pollution control board, Govt. of West Bengal and daily meteorological data have been collected from the world weather website. The results show that non-linear artificial neural network model is more rational compared with multiple linear regression model due to its high precision and accuracy level (in respect to RMSE, MAE and R(2)). In this research artificial neural network (ANN) model exhibited higher accuracy during the training and testing phases (root mean square error (RMSE), mean absolute error (MAE) and R(2) indicate 3.74, 1.14 and 0.91 respectively in training phase and 2.55, 4.32 and 0.69 in testing phase respectively). This model (ANN)) can be applied to predict the concentration of PM(2.5) during the execution of urban air quality management plan. |
format | Online Article Text |
id | pubmed-9040498 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Author(s). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90404982022-04-26 PM(2.5) concentration prediction during COVID-19 lockdown over Kolkata metropolitan city, India using MLR and ANN models Bera, Biswajit Bhattacharjee, Sumana Sengupta, Nairita Saha, Soumik Environmental Challenges Article Kolkata is the third densely populated city of India and Kolkata stands in the World's 25 most polluted cities along with 10 worse polluted cities in India. The relevant study claims that due to the imposition of lockdown during COVID-19 pandemic, the atmospheric pollution level has been significantly reduced over the metropolitan city Kolkata like other cities of the world. The main objective of this study is to predict the concentration of PM(2.5) using multiple linear regression (MLR) and artificial neural network (ANN) models and similarly, to compare the accuracy level of two models. The concentration of PM(2.5) data has been obtained from state pollution control board, Govt. of West Bengal and daily meteorological data have been collected from the world weather website. The results show that non-linear artificial neural network model is more rational compared with multiple linear regression model due to its high precision and accuracy level (in respect to RMSE, MAE and R(2)). In this research artificial neural network (ANN) model exhibited higher accuracy during the training and testing phases (root mean square error (RMSE), mean absolute error (MAE) and R(2) indicate 3.74, 1.14 and 0.91 respectively in training phase and 2.55, 4.32 and 0.69 in testing phase respectively). This model (ANN)) can be applied to predict the concentration of PM(2.5) during the execution of urban air quality management plan. The Author(s). Published by Elsevier B.V. 2021-08 2021-05-24 /pmc/articles/PMC9040498/ /pubmed/37522150 http://dx.doi.org/10.1016/j.envc.2021.100155 Text en © 2021 The Author(s). Published by Elsevier B.V. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Bera, Biswajit Bhattacharjee, Sumana Sengupta, Nairita Saha, Soumik PM(2.5) concentration prediction during COVID-19 lockdown over Kolkata metropolitan city, India using MLR and ANN models |
title | PM(2.5) concentration prediction during COVID-19 lockdown over Kolkata metropolitan city, India using MLR and ANN models |
title_full | PM(2.5) concentration prediction during COVID-19 lockdown over Kolkata metropolitan city, India using MLR and ANN models |
title_fullStr | PM(2.5) concentration prediction during COVID-19 lockdown over Kolkata metropolitan city, India using MLR and ANN models |
title_full_unstemmed | PM(2.5) concentration prediction during COVID-19 lockdown over Kolkata metropolitan city, India using MLR and ANN models |
title_short | PM(2.5) concentration prediction during COVID-19 lockdown over Kolkata metropolitan city, India using MLR and ANN models |
title_sort | pm(2.5) concentration prediction during covid-19 lockdown over kolkata metropolitan city, india using mlr and ann models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040498/ https://www.ncbi.nlm.nih.gov/pubmed/37522150 http://dx.doi.org/10.1016/j.envc.2021.100155 |
work_keys_str_mv | AT berabiswajit pm25concentrationpredictionduringcovid19lockdownoverkolkatametropolitancityindiausingmlrandannmodels AT bhattacharjeesumana pm25concentrationpredictionduringcovid19lockdownoverkolkatametropolitancityindiausingmlrandannmodels AT senguptanairita pm25concentrationpredictionduringcovid19lockdownoverkolkatametropolitancityindiausingmlrandannmodels AT sahasoumik pm25concentrationpredictionduringcovid19lockdownoverkolkatametropolitancityindiausingmlrandannmodels |