[HTML][HTML] Large-scale spatiotemporal deep learning predicting urban residential indoor PM2. 5 concentration
Indoor PM 2.5 pollution is one of the leading causes of death and disease worldwide. As
monitoring indoor PM 2.5 concentrations on a large scale is challenging, it is urgent to …
monitoring indoor PM 2.5 concentrations on a large scale is challenging, it is urgent to …
[HTML][HTML] Multi-scenario PM2. 5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk …
C Ou, F Li, J Zhang, P Jiang, W Li, S Kong, J Guo… - Environment …, 2024 - Elsevier
Exposure scenario and receptor behavior significantly affect PM2. 5 exposure quantity of
persons and resident groups, which in turn influenced indoor or outdoor air quality & health …
persons and resident groups, which in turn influenced indoor or outdoor air quality & health …
Predicting indoor particle concentration in mechanically ventilated classrooms using neural networks: Model development and generalization ability analysis
J Ren, J He, A Novoselac - Building and Environment, 2023 - Elsevier
This study presents a comprehensive analysis of the model development (structure,
parameter settings, and prediction accuracy) and generalization ability of neural networks in …
parameter settings, and prediction accuracy) and generalization ability of neural networks in …
Indoor air quality monitoring and source apportionment using low-cost sensors
C Higgins, P Kumar, L Morawska - Environmental Research …, 2024 - iopscience.iop.org
Understanding of the various sources of indoor air pollution requires indoor air quality (IAQ)
data that is usually lacking. Such data can be obtained using unobtrusive, low-cost sensors …
data that is usually lacking. Such data can be obtained using unobtrusive, low-cost sensors …
Rapid prediction of transient particle transport under periodic ventilation using a non-uniform state Markov chain model
X Ding, H Zhang, W Zhang, Y Xuan - Energy and Buildings, 2024 - Elsevier
Predicting transient particle transport is crucial to address the risks posed to human health
by indoor contaminants and to improve the design and control of ventilation systems. The …
by indoor contaminants and to improve the design and control of ventilation systems. The …
Enhancing Wildfire Smoke Exposure Assessment: A Machine Learning Approach to Predict Indoor PM2.5 in British Columbia, Canada
Epidemiological studies typically model wildfire smoke exposure by predicting outdoor fine
particulate matter (PM2. 5) concentrations, overlooking indoor environments where people …
particulate matter (PM2. 5) concentrations, overlooking indoor environments where people …
Theoretical Study to Support Proposed Framework for Spatial Modeling of PM2. 5 Concentration in Pekanbaru City
RT Wahyuni, D Hanafi, MR Tomari… - … and Computer Science …, 2024 - ieeexplore.ieee.org
This paper presents a theoretical study on the spatial modeling of PM2. 5 concentrations by
integrating geostatistical and machine learning methods. The study aims to develop a …
integrating geostatistical and machine learning methods. The study aims to develop a …
Prediction of Particulate Matter (PM) Concentration of Wooden Houses in the Highlands by Two Statistical Modelling Methods.
N Faqih, J Svajlenka - International Journal on Advanced …, 2023 - search.ebscohost.com
Wooden houses can potentially contain high levels of Particulate Matter (PM), which can
cause lung disease in residents. Wooden houses have advantages in terms of maintaining …
cause lung disease in residents. Wooden houses have advantages in terms of maintaining …
Predicting the occurrence of respiratory diseases based on campus indoor air quality
PE Li, YH Ho - ACM Transactions on Intelligent Systems and … - dl.acm.org
Air quality is known to be strongly correlated with respiratory diseases. Indoor air quality
considerably affects human health, especially in spaces such as classrooms, where …
considerably affects human health, especially in spaces such as classrooms, where …