[HTML][HTML] Air pollution prediction with machine learning: a case study of Indian cities

K Kumar, BP Pande - International Journal of Environmental Science and …, 2023 - Springer
The survival of mankind cannot be imagined without air. Consistent developments in almost
all realms of modern human society affected the health of the air adversely. Daily industrial …

[HTML][HTML] Methods for urban Air Pollution measurement and forecasting: Challenges, opportunities, and solutions

E Mitreska Jovanovska, V Batz, P Lameski… - Atmosphere, 2023 - mdpi.com
In today's urban environments, accurately measuring and forecasting air pollution is crucial
for combating the effects of pollution. Machine learning (ML) is now a go-to method for …

[HTML][HTML] Using machine learning methods to forecast air quality: A case study in Macao

TMT Lei, SWI Siu, J Monjardino, L Mendes, F Ferreira - Atmosphere, 2022 - mdpi.com
Despite the levels of air pollution in Macao continuing to improve over recent years, there
are still days with high-pollution episodes that cause great health concerns to the local …

[HTML][HTML] A radical safety measure for identifying environmental changes using machine learning algorithms

PR Kshirsagar, H Manoharan, S Selvarajan… - Electronics, 2022 - mdpi.com
Due to air pollution, pollutants that harm humans and other species, as well as the
environment and natural resources, can be detected in the atmosphere. In real-world …

[HTML][HTML] A comparison of machine learning methods to forecast tropospheric ozone levels in Delhi

EK Juarez, MR Petersen - Atmosphere, 2021 - mdpi.com
Ground-level ozone is a pollutant that is harmful to urban populations, particularly in
developing countries where it is present in significant quantities. It greatly increases the risk …

A Comparative and Systematic Study of Machine Learning (ML) Approaches for Particulate Matter (PM) Prediction

A Pandya, R Nanavaty, K Pipariya, M Shah - Archives of Computational …, 2024 - Springer
Air quality in metropolitan areas has deteriorated due to growing urbanisation and
industrialisation, leading to severe health and significant economic consequences. This …

[HTML][HTML] Enhancing PM2.5 Prediction Using NARX-Based Combined CNN and LSTM Hybrid Model

ASAEA Moursi, N El-Fishawy, S Djahel, MA Shouman - Sensors, 2022 - mdpi.com
In a world where humanity's interests come first, the environment is flooded with pollutants
produced by humans' urgent need for expansion. Air pollution and climate change are side …

[HTML][HTML] Air Quality Class Prediction Using Machine Learning Methods Based on Monitoring Data and Secondary Modeling

Q Liu, B Cui, Z Liu - Atmosphere, 2024 - mdpi.com
Addressing the constraints inherent in traditional primary Air Quality Index (AQI) forecasting
models and the shortcomings in the exploitation of meteorological data, this research …

Forest fire susceptibility mapping by integrating remote sensing and machine learning algorithms

Shahfahad, S Talukdar, T Das… - Advances in Remote …, 2022 - Wiley Online Library
Forest fires are a very common in India, especially in the hilly regions of the western and
northeastern Himalayas, which puts adverse impacts on the environment and society …

A machine learning approach to investigate the build-up of surface ozone in Mexico-City

M Ahmad, B Rappenglück, OO Osibanjo… - Journal of Cleaner …, 2022 - Elsevier
Ground-level ozone is an important pollutant regarding air quality and climate. Mexico City
frequently experiences severe ozone episodes due to a combination of strong ozone …