Deadline for manuscript submissions: 15 April 2020.

Dear Colleagues,

We invite you to contribute to a special issue of Atmosphere, dedicated to statistical approaches to investigate air quality. Encompassing a variety of techniques, these statistical approaches are an important tool for air quality management. For example, they can be used to forecast air pollutant concentrations, identify sources and quantify their contributions to air quality, and, estimate exposure and associated health impacts. As the trend in air quality management continues toward increased use of portable instrumentation, including low-cost sensors, the research community is utilizing sophisticated techniques to analyze large volumes of data, as well as forecast air pollution at fine spatial and temporal scales. Recent advancements in statistical techniques, including data mining and deep learning are currently being utilized and can offer a more robust picture of air quality and support air quality management efforts. At the same time, traditional methods such as receptor models continue to be utilized – especially in regions that have only recently acquired the necessary speciation data. To bring together the research community, we invite researchers in a broad array of fields, including environmental engineering, environmental science and public health to submit original research work this special issue of Atmosphere devoted to statistical approaches to investigate air quality.

Dr. Sivaraman Balachandran
Prof. Piero Di Carlo
Guest Editors