Explore a deep learning multi-output neural network for regional multi-step-ahead air quality forecasts

Y Zhou, FJ Chang, LC Chang, IF Kao… - Journal of cleaner …, 2019 - Elsevier
Timely regional air quality forecasting in a city is crucial and beneficial for supporting
environmental management decisions as well as averting serious accidents caused by air …

Daily urban air quality index forecasting based on variational mode decomposition, sample entropy and LSTM neural network

Q Wu, H Lin - Sustainable Cities and Society, 2019 - Elsevier
An accurate and effective air quality index (AQI) forecasting is one of the necessary
conditions for the promotion of urban public health, and to help society to be sustainable …

A novel optimal-hybrid model for daily air quality index prediction considering air pollutant factors

Q Wu, H Lin - Science of the Total Environment, 2019 - Elsevier
Accurate and reliable air quality index (AQI) forecasting is extremely crucial for ecological
environment and public health. A novel optimal-hybrid model, which fuses the advantage of …

Deep learning based dynamic behavior modelling and prediction of particulate matter in air

RK Inapakurthi, SS Miriyala, K Mitra - Chemical Engineering Journal, 2021 - Elsevier
Abstract Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks
are utilized to capture the dynamic trends of 15 environmental parameters including …

A decadal synthesis of atmospheric emissions, ambient air quality, and deposition in the oil sands region

EC Horb, GR Wentworth, PA Makar… - Integrated …, 2021 - academic.oup.com
This review is part of a series synthesizing peer‐reviewed literature from the past decade on
environmental monitoring in the oil sands region (OSR) of northeastern Alberta. It focuses on …

A novel hourly PM2. 5 concentration prediction model based on feature selection, training set screening, and mode decomposition-reorganization

W Sun, Z Xu - Sustainable Cities and Society, 2021 - Elsevier
Accurate prediction of PM2. 5 and other air pollutants concentration can provide early
warning information for sustainable urban pollution control, urban construction and travel …

A wavelet PM2. 5 prediction system using optimized kernel extreme learning with Boruta-XGBoost feature selection

AA Heidari, M Akhoondzadeh, H Chen - Mathematics, 2022 - mdpi.com
The fine particulate matter (PM2. 5) concentration has been a vital source of info and an
essential indicator for measuring and studying the concentration of other air pollutants. It is …

Prediction of PM2. 5 concentration based on improved secondary decomposition and CSA-KELM

G Li, L Chen, H Yang - Atmospheric Pollution Research, 2022 - Elsevier
Exposure to high concentration PM2. 5 will increase the risk of human illness and death, so
it is of great significance to establish a high-accuracy PM2. 5 prediction model. Because …

A new classification approach to enhance future VOCs emission policies: Taking solvent-consuming industry as an example

X Zhang, W Zhao, L Nie, X Shao, H Dang… - Environmental …, 2021 - Elsevier
Volatile organic compounds (VOCs) has consistently been linked to ozone (O 3) and
secondary organic aerosol (SOA) formation, and ongoing emission policies are primarily …

[HTML][HTML] Source attribution of European surface using a tagged mechanism

A Lupaşcu, T Butler - Atmospheric Chemistry and Physics, 2019 - acp.copernicus.org
Tropospheric ozone (O 3) is an important air pollutant that affects human health,
ecosystems, and climate. The contributions of O 3 precursor emissions from different …