[HTML][HTML] Air pollution prediction using machine learning techniques–an approach to replace existing monitoring stations with virtual monitoring stations

A Samad, S Garuda, U Vogt, B Yang - Atmospheric Environment, 2023 - Elsevier
Air pollution in the modern world is a matter of grave concern. Due to rapid expansion in
commercial social, and economic aspects, the pollutant concentrations in different parts of …

Predicting of Daily PM2.5 Concentration Employing Wavelet Artificial Neural Networks Based on Meteorological Elements in Shanghai, China

Q Guo, Z He, Z Wang - Toxics, 2023 - mdpi.com
Anthropogenic sources of fine particulate matter (PM2. 5) threaten ecosystem security,
human health and sustainable development. The accuracy prediction of daily PM2. 5 …

Deep learning methods for atmospheric PM2. 5 prediction: A comparative study of transformer and CNN-LSTM-attention

B Cui, M Liu, S Li, Z **, Y Zeng, X Lin - Atmospheric Pollution Research, 2023 - Elsevier
A transformer-based method was firstly developed to predict the hourly PM 2.5 concentration
at 12 monitoring stations in Bei**g. Convolutional neural network-long short-term memory …

[HTML][HTML] Prediction of Monthly PM2.5 Concentration in Liaocheng in China Employing Artificial Neural Network

Z He, Q Guo, Z Wang, X Li - Atmosphere, 2022 - mdpi.com
Fine particulate matter (PM2. 5) affects climate change and human health. Therefore, the
prediction of PM2. 5 level is particularly important for regulatory planning. The main …

Extreme emission reduction requirements for China to achieve world health organization global air quality guidelines

Y Jiang, D Ding, Z Dong, S Liu, X Chang… - Environmental …, 2023 - ACS Publications
A big gap exists between current air quality in China and the World Health Organization
(WHO) global air quality guidelines (AQG) released in 2021. Previous studies on air …

How human activities affect and reduce ecological sensitivity under climate change: Case study of the yangtze river economic belt, china

Y Wei, M An, J Huang, X Fang, M Song, B Wang… - Journal of Cleaner …, 2024 - Elsevier
Ecological sensitivity (ES) shows the adaptability of ecosystem. As anthropogenic activities
and climatic change intensify, they affect ES individually and interactively. Thus, clarifying …

Integrated benefits of synergistically reducing air pollutants and carbon dioxide in China

S Li, S Wang, Q Wu, B Zhao, Y Jiang… - Environmental …, 2024 - ACS Publications
China's advancements in addressing air pollution and reducing CO2 emissions offer
valuable lessons for collaborative strategies to achieve diverse environmental objectives …

Machine learning combined with the PMF model reveal the synergistic effects of sources and meteorological factors on PM2. 5 pollution

Z Zhang, B Xu, W Xu, F Wang, J Gao, Y Li, M Li… - Environmental …, 2022 - Elsevier
PM 2.5 pollution is a complex process mainly affected by emission sources and
meteorological conditions. However, it is hard to accurately assess the effects of emission …

Flexible Bayesian ensemble machine learning framework for predicting local ozone concentrations

X Ren, Z Mi, T Cai, CG Nolte… - … science & technology, 2022 - ACS Publications
3D-grid-based chemical transport models, such as the Community Multiscale Air Quality
(CMAQ) modeling system, have been widely used for predicting concentrations of ambient …

Air quality, health, and equity benefits of carbon neutrality and clean air pathways in China

Y Sun, Y Jiang, J **ng, Y Ou, S Wang… - Environmental …, 2024 - ACS Publications
In the pursuit of carbon neutrality, China's 2060 targets have been largely anchored in
reducing greenhouse gas emissions, with less emphasis on the consequential benefits for …