Life Cycle Assessment (LCA) and approaches such as Eco-Efficiency Analysis and SEEBALANCE have proven useful tools for a quantitative sustainability assessment along value chains and across industry sectors. However, there is a need for new methods to holistically assess sustainability in agriculture. To date, most if not all of the systems established to assess sustainability in agriculture are not based upon a LCA approach. This talk will discuss BASF approaches and case studies. AgBalanceTMcombines LCA with environmental, economic and social impact indicators, generalized to varying spatial scales. The methodology comprises up to 70 sustainability indicators, based on a significantly larger number of input data and parameters. The indicators are grouped into the three dimensions environment, society and economy. Sensitivity and scenario analyses can be employed to study the robustness of the model results, and to investigate trade-offs or the response to external influences. In a case study, AgBalance was used to identify key drivers of sustainability in the production of soybean, corn and cotton in Brazil. Two farms in the Cerrado biome were compared with respect to their sustainability performance. Different fertilizer and pesticide regimes together with different professional training and social inclusion practices were revealed as the factors most critical for the different sustainability performances of both farms. It was shown that a more efficient fertilizer use in the less performing farm could result in savings of energy equivalent to the average consumption of approximately 2000 households per year. In a similar vein, AgBalance will be used by BASF and its partners to assist strategic decision-making of farming operations, facilitate the identification of product and process improvements, enhance product differentiation as well as to support the dialogue with key influencers in the agri-food value chain.

Measuring sustainability in the agri-food sector: BASF's AgBalance� analysis

248th National Meeting (2014)

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