[HTML][HTML] A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective …

X Ma, B Zou, J Deng, J Gao, I Longley, S **ao… - Environment …, 2024‏ - Elsevier
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 …

Low‐cost air quality monitoring networks for long‐term field campaigns: A review

F Carotenuto, A Bisignano, L Brilli… - Meteorological …, 2023‏ - Wiley Online Library
The application of low‐cost air quality monitoring networks has substantially grown over the
last few years, following the technological advances in the production of cheap and portable …

[HTML][HTML] Calibrating networks of low-cost air quality sensors

P DeSouza, R Kahn, T Stockman… - Atmospheric …, 2022‏ - amt.copernicus.org
Ambient fine particulate matter (PM 2.5) pollution is a major health risk. Networks of low-cost
sensors (LCS) are increasingly being used to understand local-scale air pollution variation …

Flexible, non-contact and multifunctional humidity sensors based on two-dimensional phytic acid doped co-metal organic frameworks nanosheets

Y Huo, M Bu, Z Ma, J Sun, Y Yan, K **u, Z Wang… - Journal of Colloid and …, 2022‏ - Elsevier
The development of high-performance humidity sensors is of great significance to explore
their practical applications in the fields of environment, energy saving and safety monitoring …

[HTML][HTML] Field calibration of low-cost particulate matter sensors using artificial neural networks and affine response correction

S Koziel, A Pietrenko-Dabrowska, M Wojcikowski… - Measurement, 2024‏ - Elsevier
Due to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is
of paramount importance, especially in densely populated urban areas. However, precise …

High-spatiotemporal-resolution PM2. 5 forecasting by hybrid deep learning models with ensembled massive heterogeneous monitoring data

KY Wu, IW Hsia, PY Kow, LC Chang… - Journal of Cleaner …, 2023‏ - Elsevier
High-resolution real-time air quality forecasting can alert decision-makers and residents
about forthcoming air pollution events and refine air quality management. The …

Efficient calibration of cost-efficient particulate matter sensors using machine learning and time-series alignment

S Koziel, A Pietrenko-Dabrowska… - Knowledge-Based …, 2024‏ - Elsevier
Atmospheric particulate matter (PM) poses a significant threat to human health, infiltrating
the lungs and brain and leading to severe issues such as heart and lung diseases, cancer …

Assessment of the applicability of a low-cost sensor–based methane monitoring system for continuous multi-channel sampling

ISP Nagahage, EAAD Nagahage, T Fu**o - Environmental Monitoring and …, 2021‏ - Springer
Abstract Systems that are made of several low-cost gas sensors with automatic gas
sampling may have the potential to serve as reliable fast methane analyzers. However, there …

Performance characterization of low-cost air quality sensors for off-grid deployment in rural Malawi

AS Bittner, ES Cross, DH Hagan… - Atmospheric …, 2021‏ - amt.copernicus.org
Low-cost gas and particulate sensor packages offer a compact, lightweight, and easily
transportable solution to address global gaps in air quality (AQ) observations. However …

Prediction of influencing atmospheric conditions for explosion Avoidance in fireworks manufacturing Industry-A network approach

I Nallathambi, R Ramar, DA Pustokhin… - Environmental …, 2022‏ - Elsevier
This research study uses Artificial Neural Networks (ANNs) to predict occupational accidents
in Sivakasi firework industries. Atmospheric temperature, pressure and humidity are the …