Effective policy mix for plastic waste mitigation in India using System Dynamics

Highlights

• The paper models various policy mix impacts on the plastic waste stock in India.

• Four policies and their combinations are simulated using System Dynamics model.

• Plastic ban is a detrimental policy without adequate monitoring and substitutes.

• Phased kerbside recycling with unit disposal fee is the most effective policy mix.

• The paper equips policymakers with a roadmap and novel insights on policy mix.

Abstract

Mitigation of plastic waste is a serious concern for policymakers. The present waste management system in India is grossly ineffective, with a significant proportion of mismanaged plastic waste. This paper identifies the effective policy mix to mitigate the plastic waste problem in India using system dynamics modelling. It simulates four major policy interventions - charging disposal fee, provision of recycling subsidies, provision of kerbside recycling facilities and a new intervention - imposing a plastic ban - and studies their relative impacts on the accumulated plastic waste stock under different implementation scenarios and combinations. The findings suggest that while composite combinations of policies offer more effective policy mix than individual policy interventions, a suitable choice of policy mix along with its timing and extent is crucial. Phased implementation of policies has a better impact than the constant rollout of equivalent magnitude. A phased composite mix of the provision of kerbside recycling facilities with either charging disposal fee or provision of recycling subsidies is the most effective policy mix, followed by the phased mix of charging disposal fee and provision of recycling subsidy. The plastic ban has a detrimental impact in the absence of proper enforcement mechanisms and substitutes. The paper presents a reliable roadmap to policymakers for the rollout of the effective policy mix. It contributes to theory-building by providing few novel insights about different policy mix and suggests new research directions.

Introduction

Plastic pollution is undisputedly a critical environmental concern worldwide. Plastics, a basket of a wide range of hundreds of organic materials, have gained popularity and extensive applications due to their durability, malleability, affordability, and relatively easier technology (PlasticsEurope, 2016). Plastic adoption has increased over 200-fold since 1950 (Ritchie and Roser, 2018), with an annual growth rate of around 8.4 per cent. However, the very long decay time due to their low biodegradability results in accumulation in landfills or the natural environment (Geyer et al., 2017). It creates significant negative environmental externalities such as contamination of freshwater and terrestrial habitats, as well as the formation of debris in oceans (Jambeck et al., 2015; Walker and Xanthos, 2018). The lack of comparable and equally affordable alternatives, and the harmful chemicals and pollution resulting from attempts to transform, incinerate or landfill plastic waste pose severe challenges in controlling it (Aryan et al., 2019). Plastics in various forms contribute to a significant proportion of the total waste generated in the ecosystem. The estimated mismanaged plastic waste ranges from a low of two per cent in the US to a high of 89 per cent in developing economies such as Myanmar (Jambeck et al., 2015). Mitigation of plastic waste pollution and its effects poses severe challenges to policymakers.

India, an emerging Asian economy, is one of the important producers and consumers of various kinds of plastic. The scenario of waste management in India is grossly ineffective with very negligible source segregation, little recovery and a significant proportion of waste ending up in dump yards and haphazard littering (DownToEarth, 2019). India generated around 1.64 per cent of the total global plastic waste and had a mismanaged plastic waste share of 85 per cent in 2010 (Jambeck et al., 2015). Of around 9.64 million tons of plastic waste India generates annually, 40 per cent goes uncollected and completely unmanaged (BusinessLine, 2019). Plastics comprised a significant 6.92 per cent of the total municipal solid waste (MSW) collected in 2018 (CPCB, 2018)¹. The plastic waste processing capacity of India is a meagre 15 per cent of the waste generated (The Economic Times, 2019). Being a land-scarce country with high population density, the capacities of dump yards and landfill sites are inadequate (DownToEarth, 2019). The flagship Swachh Bharat mission of the government has pitched in some initiatives, but most of the measures, being short-term oriented and localised, are far from adequate. Some of the policy combinations and the assessment system could even be counter-productive. As such, proper alternative policy interventions, and appropriate combinations thereof, followed with diligent implementation, are imperative for sustainable plastic waste management.

Extant literature on waste management and control suggests a wide range of policies for mitigation of various categories of waste. While some of these such as disposal fee, recycling subsidies (Dinan, 1993) and kerbside collection and recycling facilities (Kinnaman and Fullerton, 2000) are applicable for a wide range of waste materials including plastic waste, recently introduced policies such as a selective plastic ban are targeted specifically at the control of plastic waste. Moreover, the literature predominantly focuses on the analysis of an individual policy or relative comparison of multiple policies. While such analysis is essential, policymakers cannot rely on individual policies but require suitable policy combinations (Palmer and Walls, 1997; Hao et al., 2019). Few papers stress on the importance of the combination of policies and analyse the implications of different policy mix. Even there, the analysis is limited to a maximum of two policies. The prime units of analysis are the waste quantity and cost (economic and environmental) versus benefits. They have majorly concentrated on the developed world and western countries, with little focus on developing economies. The analysis of policy mix specific to plastic waste is also limited. Most analyses on waste management policies are either empirical based on past data, or generic based on analytical results. They generate different meaningful perspectives but suffer the drawback of prescriptive perspective due to the linearity assumptions and static, short-term nature of recommendations. This paper addresses some of these shortcomings using a long-term oriented system dynamics approach, which enables us to assess the effectiveness of different potential policy mix from a holistic perspective.

System Dynamics (SD) modelling approach, introduced by Forrester in 1960s, is a powerful tool to understand the existing behaviours of systems, and to visualise the interdependencies among different actors and variables in complex systems (Sterman, 2010). SD serves as a decision support system to analyse the policy implications using a holistic approach to wicked problems (Mingers and White, 2010) such as waste management and climate change. Literature has demonstrated remarkable success using SD for analysing different types of waste management problems from varied perspectives (Hao et al., 2019; Tseng et al., 2019; Yuan and Wang, 2014), but its application for analysis of plastic waste has been limited. Table A.1 (Appendix A) highlights the positioning of this paper by summarising the relevant literature.

This paper demonstrates the interdependencies and collective impacts of potential policy mix on the plastic waste stock in India for over 15 years. It uses four major policies – charging disposal fee, provision of recycling subsidies, provision of kerbside recycling facilities and plastic ban - and identifies the most effective policy combinations to minimise the waste stock. It studies the relative effectiveness of policy mix by generating scenarios for the simultaneous combination of multiple policies and also deliberates on the timing and the magnitude of intervention through phased implementation scenarios. It is among the first attempts to study the impact of the plastic ban as a policy instrument in detail. It provides a flexible framework to test for more policy interventions using suitable factors for potential endogenisation. It contributes to theory-building by verifying the relative impacts of different policy impacts, and by providing new insights about potential combinations. For the policymakers, it provides a visual decision-support system, which enables them to choose the most relevant policies from a long-term perspective.

The rest of the paper is structured as follows. The next section synthesises the relevant literature. Section 3 introduces the methodology, while section 4 builds the detailed SD model and discusses the variables, model relationships, parameters, data sources, and model testing. Section 5 describes the simulation results, followed by detailed discussion and analysis. Section 6 concludes with policy implications and future research scope.