My research is focused on improving the ability of satellites to measure smoke particles from space. Forest fires have existed for as long as there have been forests, and that means that the smoke particles put into the atmosphere have been affecting the climate for just as long. Because wildfires tend to happen in the wild, day and night, all over the world, the only practical way to measure how many/how big/how black or white or brown the smoke particles are that are going into our atmosphere is by using satellites.
But these all-seeing satellites do have limitations. They rely on sunlight reflected at specific angles (think from the sun, to the smoke on the planet surface, and then back out to space where the satellites orbit.) From that single pixel of information, we are trying to determine how many smoke particles there are, what color they are, and how big they are. I think of it as seeing a grocery receipt and trying to determine how many chocolate bars I bought. For $23, I could have bought 23 chocolate bars for $1 each, or 20 chocolate bars plus two bags of gummy bears for $1.50 each, etc. etc. The point is, there are too many variables that could be put into the equation and give us the same result.
To get around this, we make assumptions about the smoke properties. To continue the grocery bill analogy this would be like assuming "all chocolate bars cost between $0.90 and $1.10" and "the bill only contains chocolate bars." For converting satellite pictures into pollution measurements, we use other clues to establish that a pixle probably has information about smoke in it, and then we say that smoke is probably made of particles larger than 90 nm in diameter, but smaller than 500 nm in diameter. This allows us to then say approximately how many of these particles might be present in the pixel, reflecting light back into space. One problem is that we aren't very certain about how big these particles are, or what color they are. Experiments in the lab show that they can be all different sizes, as well as a variety of colors and shapes. So, to figure out what the best assumptions were for the smoke optical properties, we built a special tool that measures what direction light is scattered when it hits smoke. We call it the Laser Imaging Nephelometer. We flew this tool on the NASA Airborne Laboratory through various wildfires in the US and directly measured the optical properties of the smoke. Other instruments on the aircraft also measured the particle size, number, and composition.
The next step is to connect the optical measurements with the size and shape measurements and make sure that we have a good set of assumptions for converting the satellite images into good measurements of air pollution.
- Ahern, AT; Robinson, ES; Tkacik, DS; Saleh, R; Hatch, LE; Barsanti, KC; Stockwell, CE; Yokelson, RJ; Presto, AA; Robinson, AL; Sullivan, RC; Donahue, NM (2019), Production of Secondary Organic Aerosol During Aging of Biomass Burning Smoke From Fresh Fuels and Its Relationship to VOC Precursors. Version: 1 JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 124 (6) 3583-3606, issn: 2169-897X, doi: 10.1029/2018JD029068
- Sinha, A. S. Rawad, E.S. Robinson, A. T. Ahern, D.S. Tkacik, A.A. Presto, R.C. Sullivan, A.L. Robinson, N.M. Donahue (2018), Mass accommodation coefficients of fresh and aged biomass-burning emissions. Aerosol Sci. Technol. Version: 1 52 (3) 300-309, doi: 10.1080/02786826.2017.1413488
- Tkacik, DS, ES Robinson, A Ahern, R Saleh, C Stockwell, P Veres, IJ Simpson, S Meinardi, DR Blake, RJ Yokelson, AA Presto, RC Sullivan, NM Donahue and AL Robinson (2017), A dual-chamber method for quantifying the effects of atmospheric perturbations on secondary organic aerosol formation from biomass burning emissions. J. Geophys. Res.-Atmos. Version: 1 122 (11) 6043-6058, issn: 2169-897X, ids: EY6YW, doi: 10.1002/2016JD025784