New Tools for Traffic Emissions, Air Quality, and Greenhouse Gases Research

Dear Colleagues,

Emission inventories are one of the most important elements to consider in environmental and climate planning. Road transportation is one of the most important sources of air pollution and greenhouse gas emissions in urban centers. Multiple research efforts have been untaken to improve our understanding of associated sources and process mitigation activities, and many researchers are looking at how we harness new and developing data types as part of that work. For example, several research groups are actively developing real-time emission inventories using live traffic-information internet feeds and data mining methods, while other studies are using live camera feeds, visual computation and artificial intelligence to count and characterize vehicles. Similarly, rapidly evolving monitoring technologies are allowing us to refine our understanding of our vehicle emissions, from low-cost sensors that allow us to measure individual vehicle emissions in increasing numbers to remote measurement options (both on-road and satellite) that allow us to measure our fleet vehicles and environment in increasing detail. In recent years, a number of software platforms and data analysis methods, many of them open source, have been developed to bring these and other complementary datasets together to provide policymakers, vehicle fleet managers, and environmental sector workers with more insightful tools to aid them in their efforts to understand, reduce the negative environmental costs of existing vehicle fleets, and prepare for incoming alternative vehicle technologies.

The aim of this Special Issue is to bring together recent work on these new tools, their development and application, and to highlight the many different ways we can all be collaborating to make the best use of our environmental data.

The areas of interest include but are not limited to:

• Bottom-up and top-down estimates;
• Inverse modeling;
• Air pollution modeling;
• Improvements in the characterization of the volume of traffic;
• Emission factors.

Dr. Sergio Ibarra-Espinosa
Dr. Karl Ropkins
Guest Editors

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• traffic emission
• emission inventory
• remote sensing
• machine learning
• greenhouse gases
• air quality modeling
• climate change
• health effects