Accounting for environmental awareness in wheat production through Life Cycle Assessment

TL;DR

This paper develops an agent-based modeling framework for Italian wheat farms that integrates environmental impact assessments via Life Cycle Assessment, enabling farms to make more sustainable decisions considering human health and ecosystem impacts.

Contribution

It introduces a novel modeling approach that combines decision-making processes with environmental impact indicators in an agent-based wheat production system.

Findings

Farms can optimize input use considering environmental impacts.

Environmental awareness influences farm decision-making.

The framework quantifies human health and ecosystem impacts of wheat production.

Abstract

This paper presents a modeling framework for simulating the decision-making processes of artificial farms populating an agent-based model for the Italian wheat production system. The decision process is based on a mathematical programming model with which farms (i.e., agents) decide the target yield (production per hectare) and the mix of inputs needed to obtain such production, namely 1) fertilizers, 2) herbicides, and 3) insecticides. The environmental impacts of conventional production practices are assessed through a Life Cycle Assessment (LCA), using the ReCiPe 2016 methodology at the Endpoint level. Agents are made aware of the environmental consequences of their choices through two indicators: Disability-Adjusted Life Years (DALYs), which capture human health impacts, and the number of species lost per year, reflecting impacts on ecosystems. By internalizing this information, agents can make more balanced and sustainable production decisions.