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

Environmental Modelling and Software. 2019. Vol. 116. P. 7–25.
Akopov A. S., Beklaryan L. A., Saghatelyan A. K.

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.

Research target: Earth Sciences Mathematics Computer Science
Priority areas: IT and mathematics business informatics mathematics
Language: English
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Keywords: АрменияArmeniaагентное моделированиеurbanized greeneryair pollution dynamicsagent-based modellingevolutionary algorithmssimulation of complex environmental systemsдинамика загрязнения воздухаэволюционные алгоритмымоделирование сложных экологических системозеленение города
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