A System Dynamics Based Policy Simulation Approach to Reduce Plastic Waste Flow for Inland and Riverine Area in Khulna City of Bangladesh

Abstract

Abstract A comprehensive analysis of regional plastic waste flow in both land and marine ecosystem is mandatory to tackle potential hindrance towards a cumulative sustainable growth accompanied with green taxonomy. The severity of plastic pollution in most of the coastal cities around the world are augmenting the plastic waste footprint not only in those land areas but also in the oceans and aquatic lives. This study has been conducted to shed lights on presently mismanaged flow of plastic waste in the coastal gateway city of Khulna and to develop effective policy measures for reducing the plastic waste footprint around the city. To achieve the stated goal, a system dynamics (SD) model has been constructed with numerous knitted factors that has a potential applicability beyond specific regional boundaries. Baseline simulation results show that the per capita plastic waste generation increases to 11.6 kg by 2040 from 8.92 Kg in 2023. Moreover, an extensive quantity of 69.7 thousand tons of piled up plastic waste at landfills along with a riverine discharge of 834 ton from the city side has given rise to the plastic waste footprint index (PWFI) value to 24 by 2040. Furthermore, the absence of technological initiatives is responsible for logarithmic rise of the non-recyclable plastic waste to 1.35 thousand tons. The annual turnover of recycle shops has been found decreasing from 381 million BDT to 245 million BDT by 2040, due to the shutting down of recycle shops. This study has also evaluated two policy scenarios to illustrate that preventing riverine plastic discharge, encouraging govt. incentives for recycle and manufacturing industries innovative techniques such as converting discarded plastic to manufacture end products is obligatory. In this regard policy 2 has been adequate enough from a sustainability perspective with lowest PWFI value of 1.07 with a per capita plastic waste generation of 10 kg by 2040. Finally, through sensitivity analysis the parameter boundary adequacy and robustness of developed SD model has been checked to suffice its efficient applicability for policy analysis to reduce plastic waste flow in identical spatiotemporal regions.