Big Data and Artificial Intelligence for Air Quality Assessment and Forecasting

Dear Colleagues,

Clean air is a key issue for guaranteeing human rights such as the right to life, health, and well-being and to a safe, clean, healthy, and sustainable environment. For this reason, the evaluation and prediction of air quality (AQ) are essential for decision-making and the development and regulation of AQ policy. As such, future strategies for AQ assessment and forecasting face challenges such as building a multiscale approach from the global to the sub-urban level and predicting AQ on a  subseasonal basis. Therefore, the monitoring, analysis, and modelling of AQ have become strategic research areas, which are currently facing a major revolution that is driven by the availability of wireless sensor networks (WSN) coupled with the internet of things (IoT) (which provide massive real-time measurements of pollutant concentrations in the air) and the rapid advancement of high-performance computational and analytical capabilities such as supercomputing, cloud-computing, and analytical big data (BD).  

This Special Issue (SI) aims to discuss the role and applicability of top BD technologies in the evaluation and prediction of AQ based on massive air pollution measurement data provided by sensor networks. Scientists and researchers are invited to contribute to this SI by submitting manuscripts (research papers, communications, review articles) describing the fundamentals, underlying models and algorithms, and practical cases of analytical BD and AI technologies for the assessment and forecasting of AQ in real scenarios.

This SI is targeted mainly towards low-cost gas and particulate matter (PM) sensors, data mining (DM), fusion (DF), machine learning (ML), and deep learning (DL) techniques, but other BD- and AI-related technologies may also be considered. Additionally, the SI covers both ambient (outdoor) and indoor air scenarios.

Dr. Esther Hontañón
Prof. Bernardete Ribeiro
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 250 words) can be sent to the Editorial Office for assessment.

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.