Climate change is driven by the alterations in atmospheric chemistry and composition, scientists say, and understanding these changes aid in the preparation of adaptive or mitigating responses. However, there are still some gaps in the current available chemistry data and models.
A research project funded by the National Oceanic and Atmospheric Administration (NOAA) conducted the most detailed and extended survey of atmospheric chemistry ever achieved, spending years in analysis – identifying and quantifying organic compounds. The data set gathered by a team of international scientists over an area of ponderosa pine forest in Colorado provided ample information that they “were able to describe the organic compounds in the atmosphere in a more comprehensive way than had ever been possible to figure out what’s really going on.”
“The goal was trying to understand the chemistry associated with organic particulate matter in a forested environment,” Jess Kroll, MIT associate professor and co-author, explains. These organic substances found in Colorado forest play a significant role in the atmospheric chemical processes, which due to their complexity, remain poorly understood. These compounds had never been sampled, quantified, and studied accurately before.
The team utilized five different devices, with three devices used for the first time, and some are newly developed by the team specifically for the project to target hard-to-measure compounds. These hard-to-measure compounds are called semi-volatile and intermediate-volatility organic compounds (SVOC’s and IVOC’s), which may play a vital role in the formation and alteration of tiny airborne particles, called aerosols, that can result to smog and nucleation of rain, and thus, affecting the climate. The results of the project are published recently in the journal Nature Geoscience, with 24 contributors.
The measurements performed, nevertheless, could not determine the specific chemical reactions occurring that converted a compound to another. This kind of analysis requires simulation in a controlled environment. With this information on hand will enable the generation of accurate atmospheric chemical models.
