5. Conclusions
In agricultural practice, the use of crop-rotation effects is an essential
strategy. These effects are, for instance, based on improvements of
nutrient availability, phytosanitary conditions and soil structure. This
leads to increased yields and allows lower application rates of fertilizers
and plant protection products. Against this background, crop-rotation
effects are clearly relevant for assessing environmental impacts of
agricultural crops.
Existing LCA practices have a limited ability to fully reflect these
crop-rotation effects. Existing approaches are limited to particular effects
only, such as shifts in individual nutrients. Limited consideration
of crop-rotation effects within LCA was identified as a reason for the
free-rider phenomena between the crops of crop rotations. These
situations can affect overall LCA results.
To avoid such situations, a new method was proposed to supplement
the established LCA methodology according to ISO 14040. This
new crop-rotation approach adapts the system boundary to the level
of the crop rotation for the LCI and uses an agriculture-specific allocation
step to allocate inputs to their respective outputs. We suggest
using the Cereal-Unit allocation approach, which represents animal
feeding value. The new method allows practitioners to model the agricultural
system over realistic time frames and includes fundamental
agricultural consistencies such as crop-rotation effects in LCA methodology.
The examples of crop-rotation effects given are well known in
agricultural science.
The method integrates entire crop rotations in agricultural LCAs, including
crop-sequence effects and establishing a performance-oriented
attribution of environmental impacts between all agricultural outputs
of the entire crop rotation. Positive crop effects are mirrored by improved
yields in the entire crop rotation. The approach does not affect
the functional unit and the Goal and Scope Definition. Thus, the method
is suited to product-specific LCAs. The new approach helps LCA models
to draw a more realistic picture of interactions between crops in a crop
rotation and thus may help to further increase the reliability of LCA results.
However, the approach should be tested using real-world case
studies, and its results should be compared to LCA results performed
using other recent methods. We encourage researchers to publish
their results using this approach. These results would help practitioners
understand whether the recommendations drawn from LCAs using this
crop-rotation effect approach become more robust and whether the
approach could help reach the target of sustainable development.