Environmental Engineering Reference
In-Depth Information
(called bottom-up approaches) [
125
]. Current approaches often estimate
parameters based on available data, instead of resolving budgets, allowing models
to be tuned to best match observations at a site, before applying that model to
other regions to extrapolate to regional and global budgets [
126
]. Thus under-
standing atmospheric biogeochemistry of important compounds can facilitate
a better understanding of the land and ocean biogeochemistry, using inverse
modeling approaches.
Future Directions
The study of atmospheric biogeochemistry as a field is just beginning, although
some of the most important elements, such as the carbon cycle, have been studied
for many years. Our knowledge, however, of even the carbon cycle is insufficient to
understand how global carbon dioxide levels will respond in the future, even
assuming that human emissions can be predicted [
2
]. Important nutrient cycles
highlighted here include the carbon, nitrogen, phosphorus, sulfur, iron, and oxygen
cycles. All of these cycles in some way are heavily impacted by human activities,
and in addition, feedback onto our climate and environment in important ways.
Many of the important innovations over the last few years have involved under-
standing how the different cycles interact. Thus atmospheric biogeochemistry
remains an important field for continued research and innovations.
The atmosphere is unique with respect to the other components of the earth
system in our ability to easily observe many layers using remote sensing. This
means that the atmosphere provides a location where biogeochemistry as a whole
can be better understood. Inverse methods and modeling, in addition to the many
observations, may allow us to improve our understanding of not just atmospheric
biogeochemical cycles, but land and ocean biogeochemical cycles.
Acknowledgments The author would like to thank NSF (0932946, 0832782, 0758369) and NASA
(NNG06G127G), as well as Rachel Scanza for assistance on the manuscript.
Bibliography
Primary Literature
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10.1038/ngeo689
2. Friedlingstein P, Cox P, Betts R, Bopp L, Von Bloh W et al (2006) Climate-carbon cycle
feedback analysis, results from the C4MIP Model intercomparison. J Clim 19:3337-3353
3. Thornton P, Doney S, Lindsay K, Moore JK, Mahowald N et al (2009) Carbon-nitrogen
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