A study on air pollution exposure of “first and last mile” urban commuters under space-behavior dual verification based on big data, land-use regression model and …

X Li, T Yang, Z Zhu, Z Zeng, G Zeng, J Liang… - Journal of Cleaner …, 2023 - Elsevier
Urban traffic-related air pollution (TRAP) exposure is a serious problem during daily
commutes. Previous studies assess the TRAP exposure of commuters mainly based on …

Application of complete ensemble empirical mode decomposition based multi-stream informer (CEEMD-MsI) in PM2. 5 concentration long-term prediction

Q Zheng, X Tian, Z Yu, B Jin, N Jiang, Y Ding… - Expert Systems with …, 2024 - Elsevier
Nowadays, air pollution has become one of the most serious environmental problems facing
humanity and an inescapable obstacle limiting the sustainable development of cities and …

Spatial patterns of the diurnal variations of PM2. 5 and their influencing factors across China

J Liu, S Wang, K Zhu, J Hu, R Li, X Song - Atmospheric Environment, 2024 - Elsevier
Abstract Air pollution, particularly PM 2.5, is a significant public health concern in China and
worldwide. The diurnal fluctuation feature of PM 2.5 is a crucial factor influencing human …

Ensemble of ensembles for fine particulate matter pollution prediction using big data analytics and IoT emission sensors

CN Egwim, H Alaka, Y Pan, H Balogun… - Journal of Engineering …, 2023 - emerald.com
Purpose The study aims to develop a multilayer high-effective ensemble of ensembles
predictive model (stacking ensemble) using several hyperparameter optimized ensemble …

A machine learning-based ensemble model for estimating diurnal variations of nitrogen oxide concentrations in Taiwan

AK Asri, HY Lee, YL Chen, PY Wong, CY Hsu… - Science of the Total …, 2024 - Elsevier
Air pollution is inextricable from human activity patterns. This is especially true for nitrogen
oxide (NO x), a pollutant that exists naturally and also as a result of anthropogenic factors …

Accurate long-term dust concentration prediction in open-pit mines: A novel machine learning approach integrating meteorological conditions and mine production …

Y Yang, W Zhou, Z Wang, IM Jiskani, Y Yang - Journal of Cleaner …, 2024 - Elsevier
Amidst the transition from rapid growth to high-quality development in the surface mining
industry, mine dust remains a severe public health and safety issue. This study introduces a …

Data analysis and preprocessing techniques for air quality prediction: a survey

C Yu, J Tan, Y Cheng, X Mi - Stochastic Environmental Research and Risk …, 2024 - Springer
Air quality prediction technology can provide effective technical means for environmental
governance. In recent years, due to the strong nonlinearity of data, there has been extensive …

What is the spatiotemporal pattern of benzene concentration spread over susceptible area surrounding the Hartman Park community, Houston, Texas?

AK Asri, GD Newman, Z Tao, R Zhu, HL Chen… - Journal of Hazardous …, 2024 - Elsevier
Abstract The Hartman Park community in Houston, Texas-USA, is in a highly polluted area
which poses significant risks to its predominantly Hispanic and lower-income residents …

Explainable geospatial-artificial intelligence models for the estimation of PM2. 5 concentration variation during commuting rush hours in Taiwan

PY Wong, HJ Su, SCC Lung, WY Liu, HT Tseng… - Environmental …, 2024 - Elsevier
PM 2.5 concentrations are higher during rush hours at background stations compared to the
average concentration across these stations. Few studies have investigated PM 2.5 …

Temporal Heterogeneity in the Performance of Machine Learning Models for PM2. 5 Concentration Estimation

P Li, S Huang, C Luo, X Li, Q Zhang, J Wang… - Process Safety and …, 2024 - Elsevier
Machine learning (ML) methods have been applied extensively to simulate air pollutant
concentrations and assess individual exposure in epidemiological studies. However, there …