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Journals
Atmosphere
Special Issues
Role of Materials in Pollutants Measurement
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Role of Materials in Pollutants Measurement

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Pollution Control".

Deadline for manuscript submissions: closed (7 April 2022) | Viewed by 2683

Special Issue Editors

Dr. Pawan Kumar

E-Mail Website
Guest Editor
Department of Nano science and Materials, Central University of Jammu, India
Interests: sensors; advanced materials; clean energy and environment; pharmaceutical
Dr. Naresh Kumar

E-Mail Website
Guest Editor
Department of Electronics & Communication Engineering, University Institute of Engineering & Technology Panjab University, Chandigarh 160014, India
Interests: oceanography; sensors; artificial intelligence; materials
Dr. Jin Shang

E-Mail Website
Guest Editor
School of Energy and Environment, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, China
Interests: CO2 capture; nature gas/biogas purification; sour gas (SO2, NOx, and H2S) removal; VOCs removal; energy storage; chemical sensing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the last few decades, there has been an increase in the influence of materials science along with the significance of its role in environmental science. Various types of pollutants have been identified in air, water and soil. The adverse effects of these pollutants on the living world are well known. Materials play a significant role preserving the health of living beings. The adsorption, catalysis, separation, sensing, removal and storage features of materials help to create a healthier environment. More precisely, analytical techniques based on materials or sustainable materials offer usable facts for application in the measurement of pollutants. This Special Issue will mainly focus on the application of materials in the field of adsorption, catalysis, separation, sensing, removal and storage of pollutants. In the pursuit for novel materials, this issue will cover the use of materials in the analysis of pollutants, especially particulate matter (PM) in real samples (air, water and soil) as well as recycling and decontamination processes.

Dr. Pawan Kumar
Dr. Naresh Kumar
Dr. Jin Shang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  •  particulate matter
  •  emerging pollutants
  •  advanced materials
  •  adsorption, catalysis, separation, sensing, removal and storage of pollutants
  •  optical and electrochemical sensing techniques
  •  recycling and decontamination processes
  •  real-world sampling and analysis

Published Papers (1 paper)

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Research

21 pages, 2887 KiB  
Article
Assessment of Fine Particulate Matter for Port City of Eastern Peninsular India Using Gradient Boosting Machine Learning Model
by Manoj Sharma, Naresh Kumar, Shallu Sharma, Vikas Jangra, Seema Mehandia, Sumit Kumar and Pawan Kumar
Atmosphere 2022, 13(5), 743; https://doi.org/10.3390/atmos13050743 - 06 May 2022
Cited by 7 | Viewed by 2009
Abstract
An assessment and prediction of PM2.5 for a port city of eastern peninsular India is presented. Fifteen machine learning (ML) regression models were trained, tested and implemented to predict the PM2.5 concentration. The predicting ability of regression models was validated using [...] Read more.
An assessment and prediction of PM2.5 for a port city of eastern peninsular India is presented. Fifteen machine learning (ML) regression models were trained, tested and implemented to predict the PM2.5 concentration. The predicting ability of regression models was validated using air pollutants and meteorological parameters as input variables collected from sites located at Visakhapatnam, a port city on the eastern side of peninsular India, for the assessment period 2018–2019. Highly correlated air pollutants and meteorological parameters with PM2.5 concentration were evaluated and presented during the period under study. It was found that the CatBoost regression model outperformed all other employed regression models in predicting PM2.5 concentration with an R2 score (coefficient of determination) of 0.81, median absolute error (MedAE) of 6.95 µg/m3, mean absolute percentage error (MAPE) of 0.29, root mean square error (RMSE) of 11.42 µg/m3 and mean absolute error (MAE) of 9.07 µg/m3. High PM2.5 concentration prediction results in contrast to Indian standards were also presented. In depth seasonal assessments of PM2.5 concentration were presented, to show variance in PM2.5 concentration during dominant seasons. Full article
(This article belongs to the Special Issue Role of Materials in Pollutants Measurement)
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