(480c) Towards Improved C and N Footprints and Understanding Their Nexus | AIChE

(480c) Towards Improved C and N Footprints and Understanding Their Nexus

Authors 

Singh, S. - Presenter, The Ohio State University


Carbon and Nitrogen are the two most disrupted bio-geochemical cycles over their natural states.  There have been several works that relate the impact of C on various components of N cycle such as N stocks in soil and vice versa. Similarly, the role of anthropogenic activities on different components of these natural cycles has also been quantified using the Ecologically Based Life Cycle Assessment (Eco-LCA).  The realizations of extent of anthropogenic impact on the C and N flows have led to development and extensive use of C and N footprint measures.  This is mainly due to the fact that footprint measures have become standard and easy way of quantifying environmental impacts.  

Carbon footprint has become an essential metric in any Life Cycle study along with several studies that have indicated efforts to enhance the strength of this metric. On the other hand, Nitrogen footprint is a new entrant in the group of footprint measures but is rapidly gaining importance. However, the current C and N footprint metrics are not without limitations since these miss several components of flow of the natural C & N cycles.  In this work, these limitations of current metrics are realized and improved C and N metrics are proposed to study the impacts of any process or product.  The development of new metrics will be explained based on several flows that are not accounted in current metric calculations. Even though both the C footprint and N-footprint can be calculated according to the present definitions of these metrics there have been hardly any studies that have looked into the relation of these metrics.  Hence, in this work along with the comparison of new and old C & N footprint measures, the relation between the C & N footprint will also be studied.  A case study on bio-fuels will be presented to study the utility of using newly defined metrics for C & N over old C & N metrics and the relation among C & N metrics itself.