I am heavily involved in developing retrieval algorithms for both ground- and space- based instruments. These algorithms calculate the amount of trace gases in the atmosphere, such as CO2 and NO2, from measurements of light passing through the atmosphere. Since 2019, I have been working on the retrieval used by the Total Carbon Column Observing Network (TCCON), a worldwide network of ground based instruments, to measure CO2, CH4, N2O, CO, H2O, HDO, and many other gases. I am also currently supporting the Orbiting Carbon Observatory 2 and 3 missions, which observe CO2 from space, and the Atmospheric Infrared Sounder, which measures a number of reactive gases in the atmosphere.
When plants take in CO2 to photosynthesize, this causes a decrease (also called a drawdown) of CO2 concentrations near the surface. By measuring the diurnal cycles of CO2, we can gain information about how much carbon is being taken up by plants. The ideal measurement to constrain this is in many ways a boundary layer partial column - that is, the amount of CO2 integrated between the surface and the top of the turbulent part of the atmosphere near the surface. Because it is integrated, it isn't affected by mixing within that boundary layer diluting CO2 near the surface, but a partial column will be more sensitive to changes cause by plants compared to a total column from the surface up to the top of the atmosphere.
The latest TCCON data includes three measurements of CO2 made from light at slightly different wavelengths. Each measurement is most sensitive to a different part of the atmosphere, so by combining all three we should be able to derive this near-surface partial column. I am interested in using that data to measure how much carbon get taken up by plants in different parts of the world, to help us understand better how large the land carbon sink is and how it will change in the future.
TCCON stations provide detailed timeseries at specific locations, but to understand the carbon sink further away from these stations will be better served by space-based measurements that can cover a wide area. Our longest space-based CO2 measurements (from the GOSAT and OCO-2 satellites) measure at one local time of day, but OCO-3 measures at different times of day and future missions like GeoCarb will provide even better diurnally resolved information. I hope to combine these data with TCCON measurements to fill in a wide area picture of carbon uptake.
As part of my Ph.D., I showed that we can use measurements from the OMI satellite instrument to infer changes in NOx lifetime on multi-year time scales. The newer TROPOMI instrument, launched in 2017, offers the chance to look at month-to-month changes in NOx lifetime. With the dramatic reductions in NOx emissions during 2020 due to the COVID-19 pandemic, we have a chance to learn how urban NOx chemistry will change as we move to lower and lower NOx emission scenarios.
We can classify what chemical regime dominates chemistry in a given location by looking at how NOx lifetime changes with NOx concentration. When lifetime decreases with concentration, we are in a NOx-limited regime, and when lifetime increases with concentration, we are in either a VOCx-limited regime or (if NOx concentrations are very small) an alkyl nitrate dominated one. Knowing this helps us plan how to reduce ozone concentrations; in a NOx-limited regime, reducing NOx is most effective at reducing ozone, and in a VOC-limited regime, reducing VOCs is. (If we make it to an alkyl nitrate dominated regime, ozone production will already be very small.)
In some very preliminary work, I found that NOx lifetime increased during the COVID-19 pandemic for many cities around the world. That suggests that as we find ways to make pandemic-like emissions reductions permanent (though without such massive personal and economic dislocation), these cities will see reductions in their ozone levels.