Accurate air quality forecasting is critical for systematic pollution control as well as public
health and wellness. Most of the traditional forecasting techniques have shown inconsistent …

Land use regression (LUR) models are widely used in epidemiological and environmental
studies to estimate humans' exposure to air pollution within urban areas. However, the early …

The complexity and dynamics of the environment make it extremely difficult to directly predict
and trace the temporal and spatial changes in pollution. In the past decade, the …

With the recent advances in earth observation technologies, the increasing availability of
data from more and more different satellite sensors as well as progress in semi-automated …

Particulate matter (PM) pollution greatly endanger human physical and mental health, and it
is of great practical significance to predict PM concentrations accurately. This study …

The current study attempts to compare the hybrid artificial intelligence models to forecast the
environmental externalities in Saudi Arabia. We have used the denoising based artificial …

Since air pollution negatively affects human health and causes serious diseases, accurate
air pollution prediction is essential regarding environmental sustainability. Although …

In the past decades, some desert wetlands have become critical regions for dust production
in the arid and semi-arid regions of the world. Accurate prediction of the number of dusty …

Sustainable development is a key challenge for contemporary human societies; failure to
achieve sustainability could threaten human survival. In this review article, we illustrate how …

Particulate matter (PM) or particle pollution include the tiny particles of dust and fly ash
particles are expelled from coal-burning power plants. Coal combustion is an extremely …