Particulate Matter

Particulate matter (PM) research focuses on understanding its sources, distribution, and health impacts, with a primary objective of developing effective monitoring and mitigation strategies. Current research employs various approaches, including machine learning models like deep convolutional neural networks and recurrent neural networks (RNNs, particularly LSTMs), to analyze satellite imagery, low-cost sensor data, and traffic patterns for PM concentration prediction and estimation of its oxidative potential. These advancements enable more efficient and cost-effective monitoring, improving our ability to assess PM's effects on human health and the environment and inform policy decisions for air quality management.