Surface-atmosphere exchange is the exchange of water vapor, energy and trace species (including gaseous chemicals and atmospheric particles) between the atmosphere and the Earth’s surface. The energy balance at the surface and vegetative evapotranspiration drive atmospheric dynamics (weather and climate) and are key to understanding the water cycle. Exchange (emission and/or uptake) of trace gaseous species (e. g., methane, nitrogen oxides, biogenic hydrocarbons, carbon dioxide) is critical for understanding various issues in climate, air quality and ecosystem dynamics. Interactions between the physics and chemistry of the atmosphere and the biology and ecology of the biosphere are vital for accurate predictive computational models. Deposition (both wet and dry) of gases and particles is the major removal mechanism for many atmospheric trace species and may alter chemical balances of sensitive ecosystems. These kinds of processes drive much of what happens in the lower atmosphere and thereby affect weather, climate and air quality. Scientists at ATDD perform research in surface-atmosphere exchange to better understand how these processes influence the behavior of the atmosphere and affect our daily lives through the weather and climate we experience and the air we breathe.
ATDD scientists use the new knowledge gained in surface-atmosphere exchange research to improve computer models employed by NOAA’s National Weather Service (NWS) to forecast air pollution episodes over the entire U. S. The NWS’s National Air Quality Forecasting Capability (NAQFC) provides 48-hour forecasts of surface ozone and atmospheric fine particles (PM2.5). Accurate air quality forecasts enable communities to take actions that may reduce the severity of episodes (e.g., encourage people to telecommute or take mass transit vehicles rather than personal automobiles). These predictions also allow individuals to take protective actions (such as limiting outdoor exercise or just staying indoors) to minimize their own exposure to poor air quality. The research done by ATDD scientists to increase understanding of surface-atmosphere exchange is motivated by the need to improve the simulation of these processes in the large-scale air quality models used by the NAQFC to generate these forecasts.
Exposure to high concentrations of PM2.5 has been linked to numerous health problems including asthma and cardiovascular disease. NAQFC forecasts of PM2.5 and ozone help local communities and individuals respond appropriately to the occurrence of poor air quality.
Forests are a dominant source of biogenic hydrocarbons that are emitted into the air, accounting for nearly 80 percent of all non-methane hydrocarbons that are released into the global atmosphere. Once in the atmosphere, these hydrocarbons undergo chemical reactions that profoundly impact the formation of ozone and atmospheric fine particles. The modeling system being developed at ATDD is referred to as the Atmospheric Chemistry and Canopy Exchange Simulation System (ACCESS). It is designed to provide a more physically, chemically and biologically consistent and robust representation of important processes affecting the exchange of biogenic hydrocarbons between the forest canopy and the atmosphere than can be included in current state-of-the-science air quality models such as those used in NOAA’s NAQFC. In conjunction with chemical data from intensive field measurement campaigns, ACCESS is being used to help understand how important small-scale physical and chemical processes within forest canopy environments are to the prediction of ground-level ozone and fine particle concentrations in large-scale air quality models.
Another investigation is focused on dry deposition of PM2.5 from the atmosphere to the Earth’s surface. This process is one of the main removal mechanisms for PM2.5, but has been identified as one of the most uncertain processes affecting predictions of fine particle concentrations in air quality models such as the NAQFC. In particular, the largest uncertainty in particle deposition occurs over landscapes dominated by forests. In this research, a variety of different algorithms are being tested which attempt to simulate the particle deposition process. Results from computer model simulations set up to focus on the southeastern U. S. (which has extensive forest cover) are being compared to data from an intensive field measurement campaign that occurred during the summer of 2013 (Southern Atmosphere Study). Early results from this research indicate that the choice of particle dry deposition algorithm does substantially impact surface concentrations of PM2.5, but has a much larger impact on predicted total deposition of fine particles to the Earth’s surface. These computer simulations, if corroborated by data, may have significant implications for our understanding of the deposition of harmful pollutants to sensitive ecosystems.