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Agent-based modelling of interactions between air pollutants and greenery using a case study of Yerevan, Armenia

Akopov, Andranik S., Beklaryan, Levon A., Saghatelyan, Armen K.
Environmental modelling & software 2019 v.116 pp. 7-25
air pollutants, air pollution, algorithms, case studies, cities, factories, models, planting, pollution control, trees, vegetation, Armenia
Urban greenery such as trees can effectively reduce air pollution in a natural and eco-friendly way. However, how to spatially locate and arrange greenery in an optimal way remains as a challenging task. We developed an agent-based model of air pollution dynamics to support the optimal allocation and configuration of tree clusters in a city. The Pareto optimal solutions for greenery in the city were computed using the suggested heuristic optimisation algorithm, considering the complex absorptive-diffusive interactions between agent-trees (tree clusters) and air pollutants produced by agent-enterprises (factories) and agent-vehicles (car clusters) located in the city. We applied and tested the model with empirical data in Yerevan, Armenia, and successfully found the optimal strategy under the budget constraint: planting various types of trees around kindergartens and emission sources.