Modelling greenhouse gas emissions and cumulative energy demand of energy crops in rotation using the Life Cycle Assessment approach : challenges and potential solutions
Sustainability of energy cropping is in the focus of an increasingly critical public debate. At the moment few empirical data are available regarding the impact of energy crops and their management on different sustainability indicators. As a result, the limitation of information in combination with the risks for the farmer of establishing new cropping systems were leading to a concentration on a limited number of energy crops, mostly maize. Consequently, appropriate assessment tools are needed to detect sustainable energy cropping systems especially in the context of greenhouse gas (GHG) emission mitigation and energy efficiency. Different Life Cycle Assessment (LCA) tools are available for the evaluation of agricultural crop production systems. However, most of these tools are lacking the ability to fully reflect current agricultural practices. These tools can account for differences in local agricultural management practices, pedoclimatic conditions, and farming technologies but all are lacking the consideration of the characteristics of perennial crops and crop rotations and their effects. The aim of this thesis was to develop a tool to calculate and analyze the GHG emissions and energy efficiency of energy crop cultivation in rotations. Furthermore, the challenges and special features of energy crop rotation modeling were investigated including the review of currently available tools for GHG emission assessments as well as an analysis of GHG emissions calculation methods from energy crop cultivation and a demonstration of the performance of the newly developed tool. Energy crop cultivation is a dynamic and complex system influenced by many factors as e.g. pedoclimatic conditions. This complexity hampers a sufficient realistic representation of GHG emission from energy crop cultivation using a model. In this thesis medium effort regional specific GHG emission assessment approaches were identified, which (1) require little additional effort compared to global approaches and (2) improve the accuracy of the estimate of land-based GHG emissions from fertilization and soil organic carbon change. Typical LCA studies from annual energy crops take only one vegetation period into account and disregard the interactions between the previous crops on the assessed crop (crop rotation effects). Ignoring these effects may lead to incorrect interpretation of LCA results. The review of 44 currently available agricultural environmental assessment calculators revealed that 18 calculators were capable of assessing GHG emissions from energy crop cultivation following the IPCC guidelines and using the LCA approach. Only seven out of these 18 could calculate GHG emissions from energy crop rotations but none of these calculators were able to consider actual crop rotation effects. To overcome the shortcomings of available LCA tools, a new tool called Model for integrated Life Cycle Assessment in Agriculture , short MiLA was developed. MiLA can calculate the GHG emissions and cumulative energy demand (CED) of cropping systems by taking the characteristics of crop cultivation in rotation into account. Furthermore, differences in local agricultural management practices, pedoclimatic conditions, farming practices and energy crop specifications are considered. MiLA was applied to a case study, which showed that including crop rotation effects influenced the GHG emission result of the individual crop by -34% up to +99% and the CED by -16% up to +89 %. Consequently, taking the whole crop rotation into account helps to draw a more realistic picture of the interactions between crops while increasing the reliability of the LCA results.MiLA tool indicator results can also be combined with other indicator results as demonstrated in a case study, analyzing the resource efficiency (area use, energy and economic efficiency) of different crop rotations at various sites. The results revealed that the efficiency of each crop rotation is dependent on the regional condition and related management, and that the efficiency indicators were strongly correlated. Consequently, the design of crop rotation adapted to regional site conditions can be a useful tool for steering and optimizing resource efficiency. However, in order to determine sustainable energy cropping systems, it will be indispensable to extend MiLA by including additional indicators to cover all indicators of sustainability assessment. This thesis was able to demonstrate, that MiLA tool results have a wide range of application possibilities and through the consideration of crop rotation effect in LCA studies a better reflection of agricultural reality was achieved and modelling uncertainties could be reduced. These aspects should be considered in national GHG emission agricultural inventory accountings in order to derive reliable and regionally adopted GHG emission reduction plans.
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