Obtaining PM2. 5 data for the entirety of a research region underlies the study of the
relationship between PM2. 5 and human spatiotemporal activity. A professional sampler with …

Long-term air pollution data with high temporal and spatial resolutions are needed to
support the research of physical and chemical processes that affect the air quality, and the …

Over the past few decades, air pollution has caused serious damage to public health.
Therefore, making accurate predictions of PM2. 5 is a crucial task. Due to the transportation …

Various studies are currently underway on PM (Particulate Matter) monitoring in view of the
importance of air quality in public health management. Spatial interpolation has been used …

This study reports a spatiotemporal characterization of formaldehyde and acetaldehyde in
the summer and winter of 2017 in the urban area of Shiraz, Iran. Sampling was fulfilled …

This study aims to determine the impact of land use changes on air quality at the largest
conurbation area in Malaysia, Kuala Lumpur Extended Mega Urban Regions (KLEMUR) …

Air pollution is a complex process and is affected by meteorological conditions and other
chemical components. Numerous studies have demonstrated that data-driven spatio …

Mountains are progressively being invaded by highways for development and defence
purposes. Environmental impact assessment (EIA) of highway projects in mountainous …

This paper presents a semi-parallel architecture for decoding low density parity check
(LDPC) codes. A modified version of min-sum algorithm has been used which the …

Air pollution is a lethal global threat. To mitigate the effects of air pollution, we must first
understand it, find its patterns and correlations, and predict it in advance. Air pollution is …