Application of machine learning in atmospheric pollution research: A state-of-art review
Abstract Machine learning (ML) is an artificial intelligence technology that has been used in
atmospheric pollution research due to their powerful fitting ability. In this review, 105 articles …
atmospheric pollution research due to their powerful fitting ability. In this review, 105 articles …
Assessing the spatial transferability of calibration models across a low-cost sensors network
Low-cost sensor networks (LCSNs) are expanding worldwide to gather high spatiotemporal
resolution data due to their economic feasibility and compact size. The reliability of LCS …
resolution data due to their economic feasibility and compact size. The reliability of LCS …
A machine learning modelling approach to characterize the background pollution in the Western Macedonia region in northwest Greece
K Rizos, C Meleti, V Evagelopoulos, D Melas - Atmospheric Pollution …, 2023 - Elsevier
The background PM 10 concentration in the Western Macedonia region, a complex terrain
area with combined urban and industrial emission sources is investigated in this study. PM …
area with combined urban and industrial emission sources is investigated in this study. PM …
Aerosols in Northern Morocco (Part 3): the application of three complementary approaches towards a better understanding of PM10 sources
This study investigates the sources and characteristics of PM10 pollution in Tetouan city,
Morocco, by employing a combination of chemical mass closure, source-receptor modelling …
Morocco, by employing a combination of chemical mass closure, source-receptor modelling …
[PDF][PDF] Study of background air pollution using experimental data and mathematical models
K Rizos - 2023 - scholar.archive.org
Nowadays, air pollution has become one of the greatest environmental threats to human
health and ecosystems, alongside climate change and it will continue to be even in future …
health and ecosystems, alongside climate change and it will continue to be even in future …