Air Quality Forecasting

Air quality forecasting aims to predict future pollutant levels, enabling proactive measures to mitigate health risks and environmental damage. Current research heavily utilizes machine learning, particularly deep learning architectures like LSTMs, GRUs, and Graph Neural Networks, often integrating diverse data sources such as satellite imagery, meteorological forecasts, and ground-level sensor readings to improve prediction accuracy and spatial resolution. This field is crucial for public health, informing individual decisions and policy interventions, and also advances our understanding of complex atmospheric processes through the development and application of sophisticated spatiotemporal models.

Papers

November 28, 2022

Discretized Linear Regression and Multiclass Support Vector Based Air Pollution Forecasting Technique
Dhanalakshmi M, Radha V
Air Quality Air Quality Forecasting Air Quality Prediction

November 9, 2022

Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Deep Learning-Based Time Series Forecasting
Chen Lin, Safoora Yousefi, Elvis Kahoro, Payam Karisani, Donghai Liang, Jeremy Sarnat, Eugene Agichtein
Search Query Air Quality Air Pollution Air Quality Forecasting Pollution Level Deep Time Series Forecasting

December 10, 2021

Building Autocorrelation-Aware Representations for Fine-Scale Spatiotemporal Prediction
Yijun Lin, Yao-Yi Chiang, Meredith Franklin, Sandrah P. Eckel, José Luis Ambite
Spatiotemporal Representation SpatioTemporal Data Building PCC Spatiotemporal Prediction Air Quality Forecasting Spatiotemporal Learning Representation Matrix Time sEries

December 5, 2021

Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting
Abdulmajid Murad, Frank Alexander Kraemer, Kerstin Bach, Gavin Taylor
Uncertainty Quantification Predictive Uncertainty Model Uncertainty Air Quality Forecasting Probabilistic Deep Learning State of the Art Uncertainty Deep Probabilistic Forecasting

November 28, 2021

AirSPEC: An IoT-empowered Air Quality Monitoring System integrated with a Machine Learning Framework to Detect and Predict defined Air Quality parameters
Nuwan Bandara, Sahan Hettiarachchi, Phabhani Athukorala
Machine Learning Framework Air Quality Air Quality Forecasting Air Quality Index Atmospheric Chemistry

Air Quality Forecasting

Papers

Discretized Linear Regression and Multiclass Support Vector Based Air Pollution Forecasting Technique

Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Deep Learning-Based Time Series Forecasting

Building Autocorrelation-Aware Representations for Fine-Scale Spatiotemporal Prediction

Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting

AirSPEC: An IoT-empowered Air Quality Monitoring System integrated with a Machine Learning Framework to Detect and Predict defined Air Quality parameters