Mapping Air Pollution eMissions (MAPM)

The growth of megacities from global urbanization has degraded urban air quality sufficient to impede economic growth and create a public health hazard. Emissions of particulate matter, photochemically reactive gases, and long-lived greenhouse gases, contribute to the urban environmental footprint with concomitant economic and social costs. Mitigation actions rely critically on knowing where these emissions occur. In response to this challenge, our team has developed a new method, MAPM (Mapping Air Pollution eMissions), to generate near real-time surface emissions maps of particulate matter pollution. Surface particulate matter (PM 2.5) emission maps will be derived from atmospheric measurements of particulate matter using an inverse model in conjunction with a state-of-the-art mesoscale atmospheric model.

The MAPM methodology is validated and refined using particulate matter measurements made during a field campaign that took place in Christchurch, New Zealand from June to September 2019. Key questions that MAPM aims to answer include:

• How do uncertainties on the PM 2.5 measurements affect the quality of the emissions maps we extract from our inverse model.
• How do uncertainties in the meteorological data affect the quality of the emissions maps we extract from our inverse model.
• How does the spatial and temporal resolution of the air pollution concentration measurements affect the uncertainties in the retrieved pollution emissions maps?

Here we will not only present the measurements made during the winter field campaign but also present the first derived PM 2.5 emissions maps for the city of Christchurch.