Coupling optimization with territorial LCA to support agricultural land-use planning

The life cycle assessment framework was adapted to the territorial level (the “territorial LCA”) to assess the environmental impacts and services of land-use planning scenarios. Given the various geographical conditions of the territory, the potential alternatives of land-use scenarios could be enormous. To prevent the iterative process of proposing and comparing alternative scenarios, this work aims to move one step further to automatically generate optimal planning scenarios by linking the novel territorial LCA with multi-objective optimization (MOO). A fuzzy optimization approach is adopted to deal with the trade-offs among objectives and to generate optimized scenarios, minimizing the environmental damages and maximizing the satisfaction level of the desired land-use functions subjected to constraints such as area availability and demand. Geographical Information System (GIS) is employed to manipulate geographic datasets for spatial assessment. An illustrative case study tests the novel integrated method (the territorial LCA, MOO, and GIS) on its ability to propose optimal land-use planning for bioenergy production in a region in Belgium. The study results reveal the competition of land uses for different energy products, the trade-offs among impact categories, and potential impacts on other territories if implementing optimal land planning for the territory under study. The optimization outcomes can help decision-making on the optimal locations for different crop types (i.e., miscanthus, willow, and maize in the case study) and utilizations (i.e., electricity, heat, biogas, and bioethanol in this study) complying with the objectives and constraints. This integrated tool holds the potential to assist policymakers when deciding on how to use the territory facing the global context of increasing demands for multiple uses of bio-based products, such as for food, feed, fuel, fiber, and chemicals. Limitations of the current method and its potential for real-world applications are discussed, such as expanding the scope to include life cycle sustainability assessment and taking farmers’ behavior and crop rotation into account.