Search Results - "Air quality monitoring"

PM2.5 Concentration Estimation in Single Hazy Images Using Luminance–Spatial Decoupling.

Authors: Wang, Runjie Liu, Yuhang Liu, Xianglei et al.

Source: Remote Sensing. May2026, Vol. 18 Issue 10, p1560. 20p.

Subjects: Air quality monitoring, Deep learning, Atmospheric aerosols, Aerosol analysis, Urban pollution, Image processing, Convolutional neural networks

Geographic Terms: Beijing (China), Shanghai (China)

A Portable Air-Quality Monitoring System and Its Application to Cedar Pollen Dispersion Analysis.

Authors: Noprianto Funabiki, Nobuo Kyaw, Htoo Htoo Sandi et al.

Source: Engineering Letters. Apr2026, Vol. 34 Issue 4, p1224-1240. 17p.

Subjects: Air quality monitoring, Pollen dispersal, Random forest algorithms, Machine learning, Palynology, Air pollutants

Geographic Terms: Japan

A new hybrid model and its application for forecasting of daily PM2.5 concentrations.

Authors: Du, Meng Zhang, Yifan Chen, Cuixin

Source: Environmental Engineering Research. Jun2026, Vol. 31 Issue 3, p1-15. 15p.

Satellite-Based Ground-Level NO 2 Estimation and Population Exposure Assessment Across the Marmara Region Using Tree-Based Machine Learning.

Authors: Yurt, Kemal Gündüz, Halil İbrahim

Source: Applied Sciences (2076-3417); May2026, Vol. 16 Issue 10, p4935, 29p

Real-Time Air Quality Intelligence: Low-Cost Smart Urban Monitoring Using Deep Time-Series Models.

Authors: Alsamrai, Osama Redel, Maria Dolores Dorado, M.P.

Source: Applied Sciences (2076-3417); May2026, Vol. 16 Issue 10, p4890, 22p

Position-Aware Coupling Between Ozone and Welding Fume Peaks Under Local Exhaust Ventilation.

Authors: Xia, Yuxiong Yamane, Satoshi Wang, Weixi et al.

Source: Applied Sciences (2076-3417); May2026, Vol. 16 Issue 10, p4814, 18p

Measurement report: Assessing the ammonia characteristics over a high-altitude mountain site in Shanxi province, China: a comparison with the observations in the North China Plain.

Authors: Pu, Weiwei Xu, Jing Zhu, Lingyun et al.

Source: Atmospheric Chemistry & Physics. 2026, Vol. 26 Issue 9, p6133-6145. 13p.

Prediction of Co, Co2, and Particulate Matter Using Random Forest: Implementation of a Smart Monitoring Prototype in Nuevo Leon, Mexico.

Authors: Reynoso-Guajardo, Luis Alejandro Roberto-Perez, Axel Hernandez-Santos, Carlos et al.

Source: International Journal of Combinatorial Optimization Problems & Informatics. 2026, Vol. 17 Issue 2, p324-340. 17p.

Capability Demonstration of a JEDI‐Based System for TEMPO Assimilation: System Description and Evaluation.

Authors: Abdi‐Oskouei, Maryam Barré, Jérôme Wei, Shih‐Wei et al.

Source: Journal of Advances in Modeling Earth Systems. May2026, Vol. 18 Issue 5, p1-31. 31p.

Ground-based monitoring of nitrogen dioxide in Kumasi, Ghana, and its comparison with satellite observations.

Authors: Mijling, Bas Afotey, Benjamin Eckert, Tim Henrik et al.

Source: Atmospheric Measurement Techniques. 2026, Vol. 19 Issue 9, p3063-3081. 19p.

IoT-Based Air Quality Monitoring with Low-Cost Sensors: Adaptive Filtering and RPA-Based Decision Automation.

Authors: Moldagulova, Aiman Kalpeyeva, Zhuldyz Uskenbayeva, Raissa et al.

Source: Algorithms. May2026, Vol. 19 Issue 5, p395. 25p.

Optimal Monitoring Designs of Indoor Fine Particulate Matter for Assessing Long‐Term Health Effects.

Authors: Park, Young Shin Kim, Younghyun Ji, Seokmin et al.

Source: Indoor Air. 4/18/2026, Vol. 2026, p1-11. 11p.

PAMS-constrained top-down calibration of VOC-speciated CMAQ simulations.

Authors: Chen, Sheng-Po Wang, Chieh-Heng Lee, Yi-Ju et al.

Source: Atmospheric Chemistry & Physics. 2026, Vol. 26 Issue 8, p5497-5516. 20p.

AQ-MultiCal: An Interactive No-Code Machine Learning Platform for Low-Cost Air Quality Sensor Calibration and Comparative Model Analysis.

Authors: Taştan, Mehmet Karsu Asal, Eren Cihan Gökozan, Hayrettin

Source: Sensors (14248220). Apr2026, Vol. 26 Issue 8, p2398. 21p.

A Reproducible QA/QC, Imputation and Robust-Series Workflow for Air-Quality Monitoring Time Series.

Authors: Fernández Palomares, Nuria Álvarez de Prado, Laura Menéndez García, Luis Alfonso et al.

Source: Applied Sciences (2076-3417); Apr2026, Vol. 16 Issue 7, p3396, 31p

Development of a low-cost IoT and machine learning-based air quality monitoring system for dairy barns.

Alternate Title: Süt sığırcılığı ahırları için düşük maliyetli lot ve makine öğrenmesine dayalı bir hava kalitesi izleme sisteminin geliştirilmesi.

Authors: ÇİÇEK, Yasemin Betül MUCAN, Umut KIZIL, Ünal

Source: Journal of Agricultural Faculty of Gaziosmanpasa University / Gazi Osman Pasa Üniversitesi Ziraat Fakültesi Dergisi. Apr2026, Vol. 43 Issue 1, p83-93. 11p.

Debiasing physico-chemical models in air quality monitoring by combining different pollutant concentration measurements.

Authors: Auder, Benjamin Coron, Camille Poggi, Jean-Michel et al.

Source: Communications in Statistics: Case Studies & Data Analysis. 2026, Vol. 12 Issue 1, p18-42. 25p.

Set-Up of an Italian MAX-DOAS Measurement Network for Air-Quality Studies and Satellite Validation.

Authors: Castelli, Elisa Pettinari, Paolo Papandrea, Enzo et al.

Source: Remote Sensing. Mar2026, Vol. 18 Issue 5, p722. 23p.

Subjects: Air quality monitoring, Atmospheric aerosol measurement

Geographic Terms: Po River Valley (Italy), Italy, Southern Europe, Rome

China Aerosol Raman Lidar Network (CARLNET)—Part II: Quality Assessment of Lidar Raw Data.

Authors: Bu, Zhichao Dai, Yaru Mao, Song et al.

Source: Remote Sensing. Feb2026, Vol. 18 Issue 4, p663. 25p.

Subjects: Data quality, Air quality monitoring, Meteorological research

Geographic Terms: China

Machine Learning-Based Estimation of Surface NO 2 Concentrations over China: A Comparative Analysis of Geostationary (GEMS) and Polar-Orbiting (TROPOMI) Satellite Data.

Authors: Ma, Yijin Wang, Yi Wang, Jun et al.

Source: Remote Sensing. Feb2026, Vol. 18 Issue 4, p614. 25p.

Subjects: Geostationary satellites, Air quality monitoring, Nitrogen dioxide, Machine learning, Satellite-based remote sensing

Geographic Terms: China