Assessing the Environmental, Social, and Economic Values of Green Infrastructure Plans Using Agent-Based Modeling and Monte Carlo Simulation

Traditional green infrastructure (GI) plans tend to prioritize managing stormwater within budget limits, often overlooking the wider range of benefits spanning environmental, social, and economic aspects that GIs could offer. This approach might undervalue GIs and miss their full range of potential benefits. Therefore, an agent-based model integrated with Monte Carlo simulation was developed to evaluate the environmental, social, and economic benefits associated with GI plans. Using Newark, NJ, as a case study, three greening sub-models (i.e., school greening, private property greening, and public housing property greening) were developed to model the implementation of green roofs, permeable playgrounds, and rain gardens across private and public land parcels. The findings emphasize the importance of sustained maintenance for realizing higher economic benefits from GIs in the long term. Also, the findings gave insights into the importance of adopting strategies and policies in GI planning that prioritize equality in the spatial distribution of green infrastructure to foster a more inclusive and sustainable urban environment. This paper adds to the body of knowledge by providing decision-makers with a valuable modeling and simulation workflow to evaluate the different benefits of GI programs and policies.