Plastic Flow Diagram as a Tool for Plastic Waste Management System Assessment (Case Study: Banyuwangi Regency and Jembrana Regency)

Plastic waste is one of the biggest problems faced by Indonesia as the second largest contributor of plastic waste to the oceans in the world. The leakage of plastic waste from land to sea is generally caused by the lack of waste management in Indonesia. There are still many unsafe waste management practices carried out by Indonesian people. Therefore, an assessment and evaluation of waste management is needed to determine the appropriate intervention in waste management so as to reduce the leakage of plastic waste into the environment. Plastic Flow Diagram (PFD) applies the principle of Material Flow Analysis (MFA) that can rapidly and systematically assess the plastic waste management system and show the fates of plastic waste in the environment. The results of mapping the plastic waste flow show that waste handling in Banyuwangi Subdistrict and Negara Subdistrict has reached the national target that is 86,63% and 81,89%. Meanwhile, waste handling in Muncar Subdistrict and Jembrana Subdistrict is still far from the target, as much as 39,77% and 34,54%. Plastic waste leakage occurs at every stage of waste management. However, the highest leakage comes from sources. Platic waste that leaks into the environment ends up in drainage system, enters water bodies, retained on land, and burnt.


Introduction
Plastic waste is one of the biggest problems faced by Southeast Asian countries because it is estimated that more than 50% of plastic waste in the ocean comes from that region [1].Indonesia as a Southeast Asian country is the second largest plastic waste contributor in the world [3].Estimated that only around 61% plastic is managed in the waste management system.The rest of it are burned, buried, dumped into water system, or retained on land and has the potential to be carried away by rainwater into water system and ends up in the sea [11].However, the methods of quantfying plastic waste in the environmental compartment and assessing plastic leakage from waste management system are limited.Infact, these datas are important to evaluate the performance of the activities that have been carried out to achieve the target [14].Waste Flow Diagram (WFD) is a tool to systematically assess the plastic waste management system and to estimate the leakage of plastic waste to the environment [2].The purpose of this study are to determine the quantity of plastic waste generation and estimate the quantity of plastic waste leakage to the environment, evaluate performance of the existing plastic waste, and compare the existing plastic waste management system with alternative systems in accordance with the implemented policies using Plastic Flow Diagram (PFD).

Research method
In this study, two subdistrict were selected in each location study, namely Banyuwangi and Muncar Subdistrict as well as Jembrana and Negara Subdistrict.The method used in this study is a combination of quantitative descriptive and qualitative research.

Primary data collection
The primary data collection techniques for this study were surveys with questionnaires, structured interviews, observation, documentation, and direct measurement.Determination of the population for the questionnaire, measurement of generation and characterization of waste using the Yamane formula (1967) with an error of 10% [15].The results of the calculation show that the sample size fpr domestic sector needed for the study is 100 respondents representing each household in Banyuwangi Regency and Jembrana Regency.The sample size for analysis and characterization is around 100-200 samples that number is enough to represent a population [6].Determination of population size for non-domestic facilities and procedures for measuring the generation and characterization of waste refers to SNI 19-3964-1994 about Methods for Collection and Measurement of Generation and Composition of Urban Waste.While determining the number of samples for observation and interviews of waste facilities using the snowball method.

Secondary data collection
Secondary datas are obtained from several government agencies or other agencies.The secondary datas needed in this research are population data, data about the number of non-domestic or public facilities, a list of official municipal solid waste management facilities, a map of solid waste services and the number of households or agencies served, the number of waste transportation vehicles and their service areas, study of waste problems at the study site, data on road sweeping activities, data about drainage cleaning activities and river cleaning activities.

Calculation for plastic flow diagram
In principle, mapping the waste flow with PFD applies Material Flow Analysis (MFA) with the waste studied from source to final disposal is only plastic waste.The formation of MFA includes several stages, namely collecting and calculating urban waste generation and composition data, identification of waste collected and sorted by the formal and informal sectors, analysis of residual waste that is not processed by the formal and informal sectors, quantification of leakage of plastic waste into the environment, and determination the fate of plastic waste that leaks into the environment.
Leakage of plastic waste will be seen from various aspects related to infrastructure and waste management practices starting from waste collection, processing or sorting, transportation, to final disposal.PFD divides the location of the fate of leaked waste into four fates, namely burnt, retained on land, retained in drainage, and entered water bodies.

Evaluation of plastic flow diagram
PFD evaluation is carried out based on an assessment of several indicators, some of these indicators are the effectiveness of the waste recycling rate, the effectiveness of waste collection and the burden of waste collection [5].In addition, the evaluation is also seen from the percentage value of waste leakage into the environment.Selection of alternative scenarios using the Multi-Criteria Decision Analysis (MCDA) method with weight values determined by the Entropy method.

Plastic waste generation
The generation of plastic waste was obtained by direct measurement of municipal waste generation and characterization in Kecamatan Banyuwangi, Muncar, Jembrana, and Negara.The results show that Muncar Subdistrict produces more plastic waste than Banyuwangi Subdistrict while in Jembrana Regency, Jembrana Subdistrict produces more waste than Negara Subdistrict.This is because the population in Muncar and Negara Subdistricts is higher than in Banyuangi and Jembrana Subdistricts.The total population has a strong relationship with waste generation where an increase in waste generation can increase with increasing population [9].

Plastic flow diagram
The MFA of each Subdistrict can be seen in   The plastic waste collected by the formal and informal sectors will then go through a sorting process or be transported directly to the landfill.A total of 31.76 tonnes/year (1.13%), 499.72 tonnes/year (9.87%), 367.92 tonnes/year (8.7%), and 394.20 tonnes/year (7, 26%) of plastic waste is sorted by the formal sector for recovery in Banyuwangi, Muncar, Jembrana, and Negara Subdistrict.A total of 221.20 tonnes/year (7.86%), 0 tonnes/year (0%), 676.71 tonnes/year (16.01%), and 3,724.83tonnes/year (68.59%) plastic waste is sorted by the informal sector for recovery in Banyuwangi, Muncar, Jembrana, and Negara Subdistrict.
Unsorted plastic waste becomes residue and is immediately transported to the landfill.The landfill that receives waste from Banyuwangi and Muncar Subdistricts is Blimbingsari Landfill while the landfill that receives waste from Jembrana and Negara Sudistricts is Peh Landfill at Jembrana TPST.Plastic waste that goes to the landfill from Banyuwangi, Muncar, Jembrana and Negara Subdistricts is 2,187.81tonnes/year (77.75%), 1,513.24tonnes/year (29.89%), 415.68 tonnes/year ( 9.83%), and 328.17 tonnes/year (6.04%).

Plastic waste leakage quantity and fates
Leakage of plastic waste is viewed from every stage of waste management from source, collection, sorting, transport to landfill, and from landfill itself.The amount of leaked plastic waste at each stage of the waste management system is shown in Table .2.The study shows that the highest leakage of plastic waste is at the source for each study location.This is because waste collection at the study site has not been fully served by formal and informal sector.

Evaluation of plastic waste management
Presidential Regulation Number 97 of 2017 concerning National Policy and Strategy for the Management of Household Waste and Household-like Waste Article 5 paragraph 1 states that the target for household waste and household-like waste handlingt is 73% of the generation rate in 2022.When compared with these targets, plastic waste management in Banyuwangi and Negara Subdistrict has reached the national treatment target where the management of plastic waste is estimated at 86,63% and 81,89% of the number of plastic waste generated.Meanwhile, waste handling in Muncar and Jembrana Subdistricts has not yet reached the national target where waste management is only 39,77% and 34,54%.
Based on Central Bureau of Statistics in each regency in 2021, Banyuwangi Subdistrict and Negara Subdistrict have higher population densities than Muncar Subdistrict and Jembrana Subdistrict so that the classification of Banyuwangi Subdistrict and Negara Subdistrict are urban areas, while Muncar Subdistrict and Jembrana Subdistrict are rural areas.Population density can influence people's behavior in waste management.Communities in areas with a lower population density tend to dispose of their waste locally, while people in areas with a higher density tend to move away their waste because the generated waste exceeds the environmental capacity of their area [7].If viewed from the existing waste facilities, Banyuwangi Subdistrict and Negara Subdistrict have more wastefacilities than Muncar Subdistrict and Jembrana Subdistrict so their waste handling capacity is also higher.The lack of waste facilities combined with the low knowledge and awareness of the community regarding waste management can cause the community to carry out hazardous waste management practices such as dumping them directly into water bodies, landfilling, or burning them [12].Based on the evaluation results, the effectiveness of recycling plastic waste collected in Banyuwangi and Muncar Districts is significantly lower than the effectiveness of its collection.The low ability of waste facilities to recycle can be caused by contamination of other household waste with plastic waste that is affecting the quality of plastic waste or the absence of a recycling method for plastic waste that is difficult to recycle such as diaper waste, multilayer plastic packaging, used plastic toys, and other plastic waste [8].

Alternatives scenarios
The handling of plastic waste in Muncar and Jembrana Subdistricts which has not met the national target indicates that it is necessary to develop a waste management system in these two locations.Alternative scenarios are conditioned for 2025 so that a projection of plastic waste generation is carried out for 2025 and an analysis of the plastic waste management system for that year.Based on the evaluation results of the plastic waste management system in Muncar and Jembrana Subdistricts, leakage occur at every stage of waste management but the highest leakage of plastic waste comes from sources, so it is necessary to increase the effectiveness of collection.Therefore, a scenario for a plastic waste management system was formed so that the target of handling plastic waste by 2025 of 70% can be achieved.
The three scenarios are formed to develop a waste management system in Muncar and Jembrana Subdistricts, the scenarios are as follows. Scenario 1: Improving the quality of the waste management system by improving waste management practices from collection to final disposal. Scenario 2: Additional capacity for plastic waste collection and sorting facilities by 2 units for Muncar Subdistrict and 3 units for Jembrana Subdistrict. Scenario 3: Improving the quality of waste management system practices by increasing the capacity of plastic waste collection and sorting facilities (a combination of scenario 2 and scenario 3).Table 3. shows the performance of the plastic waste management system for each scenario including the business-as-usal (Bau) scenario.The evaluation shows that the BaU scenario and scenario 1 do not achieve the national waste management target, while scenarios 2 and 3 do the opposite.It shows that just improving quality of waste management system (scenario 1) is still not enough to reach the national waste management target and so only scenario 2 or 3 will be chosen as the alternative system.The results of the scenario weighting of the plastic waste management system are shown in Table 4.The alternative scenario chosen was scenario 3.   Analysis of PFD as a tool to assess plastic waste management system PFD is formed using the MFA based on plastic waste generation data at the source, data of plastic waste entering the recovery and final disposal facilities, and the results of observations of waste management practices at each stage of the waste management system.To obtain the total coverage of plastic waste collected, PFD applies retrospective calculations based on the methodology in SDG 11.6.1 61 where the collected plastic waste is the sum of the plastic waste that enters the processing/recovery facilities and final disposal facilities.MFA is formed by analyzing existing incoming and outgoing waste throughout the waste management chain by calculating the amount of waste in each link of the system and substracting unmanaged waste [13].In this case, the PFD model satisfies the material balance at each stage but in terms of the system the equilibrium is not met due to the unstable value for the amount of waste collected.The PFD model can be further enhanced by applying direct measurements related to collection coverage in order to better represent actual conditions.The calculation of plastic waste lekage at each stage of the waste management system is influenced by the potential level of leakage which has different factors so that it can represent the amount of plastic waste that is likely to leak into the environment.The value of the leakage factor in the WFD model is by the judgement of experts [2].The expert judgment method is generally used as a last resort and is used when data is so sparse, non-existent, or cannot be applied to the problem being researched that a critical decision must be made [3].However, because it is an opinion or conjecture, this method can have cognitive biases that reduce the credibility of information if it is not done properly [10].Based on this, the accuracy of determining the value of the leakage factor for plastic waste can be increased if it is accompanied by direct experiments that are not influenced by cognitive biases as is the case with expert assessment methods.

Conclusions
In Banyuwangi Regency, the generation of plastic waste in Muncar Subdistrict (0,099 kg/capita/day) is greater than Banyuwangi Subdistrict (0,064 kg/capita/day).In Jembrana Regency, plastic waste generation in Jembrana Subdistrict (0,201 kg/capita/day) is greater than in Negara Subdistrict (0,168 kg/capita/day).However, the percentage of waste handling in Muncar and Jembrana Subdistricts (39,77% and 34,54%) are still lower than Banyuwangi and Negara Subdistricts (86,63% and 81,89%).This can be caused by a lack of awareness from the public who are still carrying out dangerous waste management practices such as open burning, throwing or burying the waste, and throwing the waste into water bodies.The results showed that plastic waste lekage occurred at every stage of waste management from source to final disposal with the highest leakage of plastic waste originating from sources, so that it is necessary to improve the quality of waste management practices, facilities and infrastructure as well as increase the capacity of collection and sorting services in Muncar and Jembrana Subdistrict.

Table 1 .
Plastic Waste Generation in 2022

Table 3 .
Effect of Implementing Alternative Scenarios on Evaluation Indicators

Table 4 .
Results of the Selection of Plastic Waste Mangement System Scenarios Sensitivity analysis were performed to determine the robustness of the results and to show how different relative weights affected the final result of the MCDA.Sensitivity analysis is done by changing the weight of each criterion.Changes in the value of this weight is done with 5 conditions as follows.1.The weight value is determined by the Entropy method.2. Balanced weight values 3. The weight value is 50% for profitable indicators and 50% for unprofitable indicators.4. The weight value is 60% for profitable indicators and 40% for unprofitable indicators. 5.The weight value is 70% for profitable indicators and 30% for unprofitable indicators.