Efforts
to compile life cycle inventory (LCI) data at more geographically
refined scales or resolutions are growing. However, it remains poorly
understood as to how the choice of spatial scale may affect LCI results.
Here, we examine this question using U.S. corn as a case study. We
compile corn production data at two spatial scales, state and county,
and compare how their LCI results may differ for state and national
level analyses. For greenhouse gas (GHG) emissions, estimates at the
two scales are similar (<20% of difference) for most state-level
analyses and are basically the same (<5%) for national level analysis.
For blue water consumption, estimates at the two scales differ more.
Our results suggest that state-level analyses may be an adequate spatial
scale for national level GHG analysis and for most state-level GHG
analyses of U.S. corn, but may fall short for water consumption, because
of its large spatial variability. On the other hand, although county-based
LCIs may be considered more accurate, they require substantially more
effort to compile. Overall, our study suggests that the goal of a
study, data requirements, and spatial variability are important factors
to consider when deciding the appropriate spatial scale or pursuing
more refined scales