AIMC Topic: Air Pollution
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An integrated 3D CNN-GRU deep learning method for short-term prediction of PM2.5 concentration in urban environment.
The Science of the total environment
Apr 19, 2022
This study proposes a new model for the spatiotemporal prediction of PM concentration at hourly and daily time intervals. It has been constructed on a combination of three-dimensional convolutional neural network and gated recurrent unit (3D CNN-GRU)...
Pollutant specific optimal deep learning and statistical model building for air quality forecasting.
Environmental pollution (Barking, Essex : 1987)
Feb 17, 2022
Poor air quality is becoming a critical environmental concern in different countries over the last several years. Most of the air pollutants have serious consequences on human health and wellbeing. In this context, efficient forecasting of air pollut...
Real-time image-based air quality estimation by deep learning neural networks.
Journal of environmental management
Jan 24, 2022
Air quality profoundly impacts public health and environmental equity. Efficient and inexpensive air quality monitoring instruments could be greatly beneficial for human health and air pollution control. This study proposes an image-based deep learni...
Assessment of medical waste generation, associated environmental impact, and management issues after the outbreak of COVID-19: A case study of the Hubei Province in China.
PloS one
Jan 24, 2022
COVID-19 greatly challenges the human health sector, and has resulted in a large amount of medical waste that poses various potential threats to the environment. In this study, we compiled relevant data released by official agencies and the media, an...
Deciphering urban traffic impacts on air quality by deep learning and emission inventory.
Journal of environmental sciences (China)
Jan 4, 2022
Air pollution is a major obstacle to future sustainability, and traffic pollution has become a large drag on the sustainable developments of future metropolises. Here, combined with the large volume of real-time monitoring data, we propose a deep lea...
Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting.
Sensors (Basel, Switzerland)
Nov 30, 2021
Data-driven forecasts of air quality have recently achieved more accurate short-term predictions. However, despite their success, most of the current data-driven solutions lack proper quantifications of model uncertainty that communicate how much to ...
A systematic literature review of deep learning neural network for time series air quality forecasting.
Environmental science and pollution research international
Nov 22, 2021
Rapid progress of industrial development, urbanization and traffic has caused air quality reduction that negatively affects human health and environmental sustainability, especially among developed countries. Numerous studies on the development of ai...
Assessing a fossil fuels externality with a new neural networks and image optimisation algorithm: the case of atmospheric pollutants as confounders to COVID-19 lethality.
Epidemiology and infection
Nov 16, 2021
This paper demonstrates how the combustion of fossil fuels for transport purpose might cause health implications. Based on an original case study [i.e. the Hubei province in China, the epicentre of the coronavirus disease-2019 (COVID-19) pandemic], w...
Air quality prediction using CNN+LSTM-based hybrid deep learning architecture.
Environmental science and pollution research international
Sep 23, 2021
Air pollution prediction based on variables in environmental monitoring data gains further importance with increasing concerns about climate change and the sustainability of cities. Modeling of the complex relationships between these variables by sop...
Ambient air pollution and cardiovascular disease rate an ANN modeling: Yazd-Central of Iran.
Scientific reports
Aug 20, 2021
This study was aimed to investigate the air pollutants impact on heart patient's hospital admission rates in Yazd for the first time. Modeling was done by time series, multivariate linear regression, and artificial neural network (ANN). During 5 year...
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