Analytical equations based prediction approach for PM2.5 using artificial neural network-Reference-Cited by-同舟云学术

Analytical equations based prediction approach for PM2.5 using artificial neural network

Published:2020-08-14 Issue:9 Volume:2 Page:
ISSN:2523-3963
Container-title:SN Applied Sciences
language:en
Short-container-title:SN Appl. Sci.

Author:

Shah Jalpa^ORCID,Mishra Biswajit

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences,General Physics and Astronomy,General Engineering,General Environmental Science,General Materials Science,General Chemical Engineering

Link

https://link.springer.com/content/pdf/10.1007/s42452-020-03294-w.pdf

Reference56 articles.

1. Central Pollution Control Board (2019) National Air Quality Monitoring Programme. http://cpcb.nic.in/about-namp/. Accessed 10 January 2019

2. Central Pollution Control Board (2018) National Air Quality Index.http://www.indiaenvironmentportal.org.in/files/file/Air%20Quality%20Index.pdf. Accessed 25 December 2018

3. Central Pollution Control Board (2018) How is AQI calculated. https://app.cpcbccr.com/ccr_docs/How_AQI_Calculated.pdf. Accessed 24 September 2018

4. World Health Organization (2018) Health effects of particulate matter. http://www.euro.who.int/__data/assets/pdf_file/0006/189051/Health-effects-of-particulate-matter-final-Eng.pdf. Accessed 20 December 2018

5. Hodan WM, Barnard WR (2004) Evaluating the contribution of PM2.5 precursor gases and re-entrained road emissions to mobile source PM2.5 particulate matter emissions. MACTEC Federal Programs, Research Triangle Park, NC

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