Agent-based modeling of agricultural plastic waste generation: A first approach

• An agent-based modeling framework linking crop-specific Plastic Waste Index (PWI) values with spatial land-use data was developed. • Two complementary ABMs were implemented: a generic exploratory model in NetLogo and a spatially explicit model for an area in the Puglia region using Mesa/Python. • Model outputs were consistent with patterns reported in existing analytical and mathematical plastic waste models. • Directional transport processes (wind and runoff) significantly influenced the spatial redistribution of plastic waste toward coastal boundaries. Agricultural Plastic Waste (APW) has grown to be a serious environmental problem of late, especially for countries or regions that rely mostly on intensive farming. There is no denying that the use of plastics increases crop yield and production of quality cultivation in general. But most of the time, this is overshadowed by poor waste management practices that eventually damage soil and contribute to the polluting of the environment by microplastics. In this work, a framework based on Agent-Based Modeling (ABM) is presented for simulating the process APW is produced and accumulated at the local scale as well as for exploring the influence of different management approaches in APW accumulation. Two complementary ABM approaches were implemented in this research: a simple prototype built in NetLogo that tries to mimic land use and introduces simplified environmental APW transport mechanisms such as wind and water runoff, and a spatially explicit model using Python/Mesa, which incorporates land use data and crop-specific plastic usage. Though limited in scope, these models produce results that are plausible and consistent with existing literature, indicating that small and simple interventions can accomplish measurable reductions in APW. The proposed framework can be scaled up, to be implemented in areas with similar cropping systems and it would pave the way for localized decision-support APW management. To our knowledge, this is the first ABM built to quantify the problem of APW accumulation in a stochastic/dynamic fashion using crop-specific, Geographic Information System (GIS)-derived Plastic Waste Index (PWI) inputs, linking spatial heterogeneity with the temporal accumulation at the parcel level.