Global Quantification of Particulate Matter (PM2.5) Composition and Sources Using Ground-Based Measurements

In this work, the PI will improve our understanding of aerosol concentrations and composition globally by leveraging ongoing air quality measurements at U.S. Embassies, which use Beta Attenuation Monitor (BAM) filter tapes to measure aerosol concentrations, with a focus on under-sampled regions of the globe (i.e., the Global South, which consists of Africa, Latin America, and developing countries in Asia).

The BAM filter tapes will be collected and analyzed using photographic and laboratory-based measurement techniques. There are four main research questions to be addressed in this work: (1) What is the aerosol composition across the Global South? (2) How does aerosol mass and composition change over time across the Global South? (3) What are the major sources of aerosol in these regions, and do emission profiles differ significantly from those in the Global North? (4) How do models and satellite products compare to these ground-based datasets?

These new datasets will enable better decision-making for affected communities around the globe. In addition, this work will develop a global network of stakeholders, including U.S. citizens working at embassies worldwide and air quality practitioners in multiple countries.

The PI in this project will develop a new high temporal resolution, ground-based global dataset of aerosols from an under-sampled region of the globe utilizing existing datasets. Specific objectives of the work are: (1) Build a global network of embassy partners and local stakeholders, including atmospheric scientists and data users, to enable data analysis and interpretation worldwide; (2) Quantify concentrations and temporal trends of major inorganic ions (sulfate, nitrate, ammonium, chloride), black carbon, and organic aerosol at >15 embassy locations worldwide; (3) Determine aerosol sources at embassy locations and compare source profiles to those determined in the Global North; and (4) Evaluate performance of global models and satellite products using our new dataset.

The methods will be validated using filter samples collected in both the laboratory and ambient air from a Pittsburgh, Pennsylvania air quality surface station. This work also will support and train undergraduate and graduate students in sampling techniques and data analysis.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.