Adam Reff

Receptor Modeling of Ambient Particulate Matter Data Using Positive Matrix Factorization: Review of Existing Methods

Abstract Methods for apportioning sources of ambient particulate matter (PM) using the positive matrix factorization (PMF) algorithm are reviewed. Numerous procedural decisions must be made and algorithmic parameters selected when analyzing PM data with PMF. However, few publications document enough of these details for readers to evaluate, reproduce, or compare results between different studies. For example, few studies document why some species were used and others not used in the modeling, how the number of factors was selected, or how much uncertainty exists in the solutions. More thorough documentation will aid the development of standard protocols for analyzing PM data with PMF and will reveal more clearly where research is needed to help future analysts select from the various possible procedures and parameters available in PMF. For example, research likely is needed to determine optimal approaches for handling data below detection limits, ways to apportion PM mass among sources identified by PMF, and ways to estimate uncertainties in the solution. The review closes with recommendations for documenting the methodological details of future PMF analyses.

Ozone Trends Across the United States over a Period of Decreasing NOx and VOC Emissions

In this work, we evaluate ambient ozone trends at urban, suburban, and rural monitoring sites across the United States over a period of decreasing NOx and VOC emissions (1998-2013). We find that decreasing ozone trends generally occur in the summer, in less urbanized areas, and at the upper end of the ozone distribution. Conversely, increasing ozone trends generally occur in the winter, in more urbanized areas, and at the lower end of the ozone distribution. The 95(th) percentile ozone concentrations decreased at urban, suburban, and rural monitors by 1-2 ppb/yr in the summer and 0.5-1 ppb/yr in the winter. In the summer, there are both increasing and decreasing trends in fifth percentile ozone concentrations of less than 0.5 ppb/yr at urban and suburban monitors, while fifth percentile ozone concentrations at rural monitors decreased by up to 1 ppb/yr. In the winter, fifth percentile ozone concentrations generally increased by 0.1-1 ppb/yr. These results demonstrate the large scale success of U.S. control strategies targeted at decreasing peak ozone concentrations. In addition, they indicate that as anthropogenic NOx emissions have decreased, the ozone distribution has been compressed, leading to less spatial and temporal variability.

The development and uses of EPA’s SPECIATE database

SPECIATE is the U.S. Environmental Protection Agency’s (EPA) repository of volatile organic compounds (VOCs) and particulate matter (PM) speciation profiles of air pollution sources. These source profiles can be used to (1) provide input to chemical mass balance (CMB) receptor models; (2) verify profiles derived from ambient measurements by multivariate receptor models (e.g., factor analysis and positive matrix factorization); (3) interpret ambient measurement data; and (4) create speciated emission inventories for regional haze, climate, and photochemical air quality modeling. This paper describes the SPECIATE v4.2 database, provides specific examples of its use, and makes recommendations for future improvements.

SPECIATE – EPA’s Database of Speciated Emission Profiles

SPECIATE is the U.S. Environmental Protection Agency’s (EPA) repository of total organic compound (TOC) and particulate matter (PM) speciation profiles for emissions from air pollution sources. The profiles are key inputs to air quality modeling and source-receptor modeling applications. This paper addresses Version 4.0 of the SPECIATE Database.

Trends in chemical composition of global and regional population-weighted fine particulate matter estimated for 25 years

We interpret in situ and satellite observations with a chemical transport model (GEOS-Chem, downscaled to 0.1° × 0.1°) to understand global trends in population-weighted mean chemical composition of fine particulate matter (PM2.5). Trends in observed and simulated population-weighted mean PM2.5 composition over 1989-2013 are highly consistent for PM2.5 (-2.4 vs -2.4%/yr), secondary inorganic aerosols (-4.3 vs -4.1%/yr), organic aerosols (OA, -3.6 vs -3.0%/yr) and black carbon (-4.3 vs -3.9%/yr) over North America, as well as for sulfate (-4.7 vs -5.8%/yr) over Europe. Simulated trends over 1998-2013 also have overlapping 95% confidence intervals with satellite-derived trends in population-weighted mean PM2.5 for 20 of 21 global regions. Over 1989-2013, most (79%) of the simulated increase in global population-weighted mean PM2.5 of 0.28 μg m-3yr-1 is explained by significantly (p < 0.05) increasing OA (0.10 μg m-3yr-1), nitrate (0.05 μg m-3yr-1), sulfate (0.04 μg m-3yr-1), and ammonium (0.03 μg m-3yr-1). These four components predominantly drive trends in population-weighted mean PM2.5 over populous regions of South Asia (0.94 μg m-3yr-1), East Asia (0.66 μg m-3yr-1), Western Europe (-0.47 μg m-3yr-1), and North America (-0.32 μg m-3yr-1). Trends in area-weighted mean and population-weighted mean PM2.5 composition differ significantly.