Designing Sustainable Waste Management Systems for a Traditional Market: A Life Cycle Assessment Case Study from Central Java, Indonesia

Traditional markets are more than retail spaces: they are daily infrastructures that connect peri-urban producers, urban consumers, and informal livelihoods. At the same time, they often function as municipal solid waste (MSW) “hotspots” because food-handling practices, high perishables turnover, and packaging practices generate mixed residues that are difficult to manage with conventional collection routines. Recent syntheses of solid waste management emphasize that the environmental burden of current practices, especially disposal-oriented pathways, remains substantial, while implementation gaps persist in many cities where waste segregation and treatment capacity are limited [1, 2]. In this context, waste systems in and around traditional markets deserve specific attention because interventions must fit tight spatial constraints, fluctuating volumes, and the everyday realities of vendors and cleaners.

A growing body of work links more sustainable waste management with broader climate and sustainability objectives. Reviews have highlighted the role of circular economy strategies in moving waste systems toward carbon neutrality by reducing reliance on landfilling and increasing recovery and valorization of materials and organics [3]. At the same time, the policy literature stresses that the quality of evidence behind environmental decision-making matters; life cycle assessment (LCA) is increasingly used as a decision support method because it can identify trade-offs that are otherwise hidden when attention is focused only on one stage of a system [4, 5]. This is particularly relevant in waste management, where technologies that look “clean” locally may shift impacts to upstream energy supply or downstream emissions.

Within waste systems, organic fractions are often decisive. Innovations in composting and biological treatment continue to evolve, with recent work documenting advances in organic solid waste composting and the conditions that influence performance and environmental outcomes [6]. For energy-and-resource recovery, anaerobic digestion (AD) is frequently discussed as a pathway to reduce methane-forming disposal and to produce biogas, and research on food-waste co-digestion continues to expand the technical options for stabilizing and valorizing wet organics [7]. In parallel, the challenge of mixed materials, especially plastics, has sharpened attention on upstream waste prevention and packaging reduction, consistent with the waste hierarchy emphasis on avoiding single-use products and moving toward higher-value options [8]. For Indonesia specifically, debates on plastic flows and regulation underscore that downstream management alone cannot fully address systemic pressures from consumption and trade [9, 10].

Traditional markets introduce additional socio-technical dynamics. Evidence from market contexts suggests that participation-related behaviors, such as traders’ willingness and capacity to sort waste, can materially shape operational feasibility and outcomes [11, 12]. Market waste volumes can also vary day-to-day, and forecasting models for market waste collection have been proposed to support more responsive planning [13]. These insights imply that “one-size-fits-all” municipal waste strategies may underperform when applied to markets without design adaptation for local routines, stakeholder roles, and the temporal rhythm of waste generation.

Despite the growing LCA literature, an important gap remains: many studies evaluate waste technologies at city scale or for specialized waste streams (e.g., hospital waste or biodegradable plastics), while fewer studies treat traditional markets as a distinct system boundary with primary field data and design-oriented scenario testing [14, 15]. Moreover, the LCA community has increasingly recognized methodological issues such as temporal dynamics and system modeling choices that affect decision relevance, reinforcing the need for transparent assumptions and context-specific inventories [16, 17]. For market settings, where operational patterns and stakeholder practices strongly influence outcomes, scenario design must be grounded in observed practices rather than generic parameter values.

This study addresses these gaps by designing and evaluating alternative waste management system configurations for the Kartasura Traditional Market, Indonesia, using a LCA approach based on primary field measurements. The analysis compares three system designs: (i) conventional collection and landfill disposal, (ii) partial source segregation with composting of organics, and (iii) advanced segregation combined with composting and AD, reflecting a transition from disposal to recovery-oriented management. The LCA was structured to quantify Global Warming Potential (GWP100), Acidification Potential (AP), Eutrophication Potential (EP), and Photochemical Ozone Creation Potential (POCP), with all scenario results normalized to a functional unit of 1 tonne of market waste, while daily waste generation data were used to characterize field variability. By treating the market as a socio-technical system and explicitly comparing practical design scenarios, the novelty of this paper lies in: (1) producing a market-specific life cycle inventory (LCI) derived from on-site data rather than secondary averages, (2) translating LCA results into system design insights aligned with the waste hierarchy and circular economy, and (3) providing evidence that is directly usable by market managers and local governments for prioritizing interventions. The study, therefore, contributes to design-for-sustainability research by connecting quantifiable environmental impacts with implementable waste management system configurations.

In order to ensure that these scenarios are actionable for planning and implementation purposes, these three scenarios were carefully chosen to depict a practical and incremental transition from a predominantly linear waste management practice towards a more circular waste management practice under conventional market conditions (limited space, presence of informal economy, fluctuating waste generation, and limited investment potential). S1 represents conventional practice with mixed collection, transport, and landfilling, which is a baseline for current environmental impacts [18]. S2 presents an intermediate solution with source separation and composting for the dominant organic waste fraction, which is more easily implemented with relatively lower technological and investment demands, while at the same time reducing landfill waste quantities. S3 is an extension of this approach with AD for energy production from organics and a controlled landfill for residuals, which is a more circular approach with methane avoidance and energy substitution benefits [18].

The comparison, though artificial, has significant importance because it is not common for market actors and local governments to directly adopt a new system that bypasses a baseline system that relies on landfills and immediately transitions to an advanced system of circular economy, as this would require incremental steps that call for an increase in levels of segregation performance, operational control, and institutional coordination, as implied by progressing through levels of system sophistication, as defined by S1 → S2 → S3 [19].

From a conceptual perspective, this approach is consistent with widely discussed waste hierarchy and circular economy transition logics in which organics diversion is prioritized, composting is considered an early intervention, and AD is considered when stable segregation and utilization pathways (digestate management and off-take) can be secured [19]. In addition, previous LCA studies on this topic suggest that the relative effectiveness of composting and AD technologies is also strongly influenced by local factors such as transport distances, emission controls, methane leakage, and substitution credits, thereby supporting a clear comparison of these staged approaches using a transparent LCA methodology framework [19].

3.1 Waste generation dynamics and implications for system design

Measured daily waste generation at Kartasura Traditional Market showed clear temporal variability across the monitoring period. Over 23 valid weighing days, the mean daily waste mass was 2,730.9 kg day⁻¹, with a median of 2,200 kg day⁻¹ and a wide range from 1,480 to 5,150 kg day⁻¹, indicating substantial fluctuations between low and peak trading days. This variability suggested that “typical-day” assumptions could underestimate the operational requirements for collection and downstream treatment capacity, particularly during short-term surges that may create overflow risks and increase leakage to informal storage or unmanaged disposal. The observed dispersion also implied that LCA foreground inventories should reflect real market-specific variation rather than a single average, because scaling errors at the inventory stage can propagate into LCIA results and distort scenario comparisons when the system is sensitive to loads and logistics. Such temporal instability is consistent with evidence that market waste streams exhibit fluctuating collection patterns and that forecasting approaches can improve planning for waste services in market contexts.

The descriptive statistics of measured daily waste generation are summarized in Table 2.

Table 2. Summarizes the descriptive statistics used to anchor the functional-unit scaling

Figure 3 illustrates the day-to-day pattern in measured waste generation, while Figure 4 shows the distribution of daily mass and highlights the tail of high-generation days relevant for capacity design [13].

Figure 3. Daily waste generation time series measured at Kartasura Traditional Market

Figure 4. The distribution of daily mass highlights the tail of high-generation days relevant for capacity design

3.2 Waste composition baseline from the survey

Figure 5 shows the respondents' dominant type of waste generated per day (n = 224). Plastic was most often identified as the dominant fraction at 58.0%, followed by organic waste at 39.3%, with paper and other waste types at 0.4% and 2.2%, respectively. This pattern suggests that any staged intervention pathway should not have a sole focus on organic recovery but must combine organic diversion with plastic reduction and recovery measures to reflect the fractions perceived as most prominent by market actors. While this evidence is perception-based, it provides an important socio-operational baseline for the design of feasible source-separation strategies in traditional markets.

Figure 5. Respondents reported dominant daily waste type (n = 224): Plastic 58.0%, organic 39.3%, paper 0.4%, and others 2.2%

Most respondents identified plastic as the dominant daily waste type (58.0%), followed by organic waste (39.3%). This suggests that staged interventions should prioritize organic diversion (composting/AD) while simultaneously strengthening plastic reduction and recovery pathways to address the largest perceived fraction.

3.3 Scenario routing summary and inventory implications

For the functional unit of 1 tonne of market waste, the scenarios follow a stepwise diversion pathway. In S1, waste is collected as mixed waste and disposed of in a landfill. In S2, the dominant organic fraction is diverted to composting, while the remaining fraction is landfilled as residual waste. In S3, the organic fraction is treated through a combination of composting and AD, and the remaining fraction is landfilled under a more controlled management approach.

The scenario routing summary for the functional unit is presented in Table 3.

Table 3. Scenario routing summary for the functional unit (1 tonne of market waste)

The total LCIA results can be obtained by summing up all burdens associated with collection, transport, treatment, and disposal for all scenarios. In addition, for S2 and S3, avoided-burden credits are subtracted from the total burdens to obtain net impacts (net = burdens - credits), where credits represent substitution effects of compost/digestate replacing synthetic fertilizer and (in S3) biogas electricity replacing grid electricity.

Scenario routing alters the major drivers of inventory. For instance, reducing waste going to landfills has implications for methane potential, while improving biological treatment can increase emissions of process-related gases such as ammonia and nutrient emissions if composting is not managed properly. In Scenario S3, AD for energy production has another offset that can impact the net greenhouse gas potential.

3.4 Life cycle assessment scenario comparison results

Based on the routing and inventory assumptions described in Section 3.3, we present the results for Scenarios S1–S3 per functional unit (1 tonne of market waste managed). We report net impacts (i.e., burdens minus credits), where credits account for resource recovery, including compost or digestate substituting synthetic fertilizer and, in S3, biogas-based electricity substituting grid electricity. We assess four midpoint indicators—GWP100 (kg CO₂-eq), AP (kg SO₂-eq), EP (kg PO₄³⁻-eq), and POCP (kg C₂H₄-eq)—to compare the scenarios and identify potential trade-offs, before examining hotspot and contribution results.

Table 4. Net life cycle impact assessment (LCIA) results for the three scenarios (functional unit: 1 tonne of market waste)

Table 4 presents the net LCIA comparison. The climate change potential substantially decreases from S1 to S2 to S3: 980 → 520 → 180 kg CO₂-eq t⁻¹. The data demonstrate that diverting waste away from landfills and harnessing energy through AD can significantly reduce greenhouse gas emissions. The acidification potential decreases step by step: 3.20 → 2.70 → 2.20 kg SO₂-eq t⁻¹. The decrease reflects reduced waste disposal to landfills and reduced waste transport to the disposal sites. Eutrophication potential shows us that S2 has a higher eutrophication potential than S1. The eutrophication potential of S2 is 1.40 kg PO₄³⁻-eq t⁻¹, while that of S1 is 1.10 kg PO₄³⁻-eq t⁻¹. However, the eutrophication potential of S3 is 1.00 kg PO₄³⁻-eq t⁻¹, indicating that the nutrient losses are minimized through AD. The photochemical ozone creation potential also decreases stepwise: 0.85 → 0.78 → 0.60 kg C₂H₄-eq t⁻¹. The decrease suggests that the smog formation potential is lower.

In Figure 6, landfill methane is the major contributor to the global warming potential of S1, which comprises the major portion of the total impact. For S2, even though the reduction of organics reduced the landfill impact, the addition of composting impact still kept the impact much lower than S1 due to reduced landfill impact and fertilizer substitution credits. For S3, the reduced impact of landfill due to the substitution of electricity with biogas resulted in the lowest impact, with avoided electricity contributing to the net impact.

Figure 6. Relative scenario contribution (%) to GWP, AP, EP, and POCP (FU = 1 tonne of market waste)

Figure 7. Normalized life cycle impact assessment (LCIA) comparison of scenarios using a radar chart (FU = 1 tonne)

The normalized comparison of the four midpoint indicators across scenarios is shown in Figure 7. In the analysis, it is observed that the hotspot for greenhouse gas emissions in Scenario 1 is landfill methane. Moving towards Scenario 2, the burdens decrease, and the composting burdens increase. The fertilizer substitution credits keep the overall impact low. Finally, in Scenario 3, the overall impact is driven by the avoidance of electricity from biogas, with the lowest global warming potential of all the scenarios. The process-level contribution analysis for GWP is presented in Table 5.

Table 5. Contribution analysis for Global Warming Potential (GWP) (kg CO₂-eq per FU = 1 tonne; net = burdens – credits)

Table 6. Sensitivity of net Global Warming Potential (GWP) to landfill gas management assumptions (kg CO₂-eq per tonne)

The sensitivity analysis adjusted the absolute numbers for the absolute global warming potential for landfill gas management but did not affect the ranking between the scenarios. The sensitivity of net GWP to landfill gas management assumptions is summarized in Table 6. The ranking remained the same: S3 < S2 < S1, proving that the design approaches that emphasize recovery are still better than the others.

3.5 Implications for life cycle assessment interpretation and design-for-sustainability

Taken together, the measured waste dynamics and the survey evidence indicated that the environmental performance of market waste management was shaped by both physical flows and human behavior. High variability in daily generation underscored the importance of logistics design (collection frequency, storage adequacy, and contingency capacity), while the prominence of plastics in trader perceptions pointed to the continuing relevance of waste-prevention and packaging interventions alongside organic recovery strategies. From an LCA standpoint, these insights implied that the comparative scenarios should be interpreted not as purely technological substitutions, but as socio-technical packages whose performance depended on compliance and operational discipline. This perspective aligned with LCA scholarship that positions LCA as a decision tool best used with transparent assumptions, context-specific inventories, and scenario definitions grounded in realistic operational conditions [4, 5, 17].

For the functional unit of 1 tonne of market waste, scenario routing followed a progressive diversion logic. S1 routed 100% of waste to the landfill. S2 diverted the dominant organic fraction to composting while residuals were disposed of in a landfill. S3 increased organics recovery through combined composting and AD, while residuals were disposed of in a controlled landfill. Net LCIA results are reported by aggregating burdens from collection, transport, treatment, and disposal, and subtracting avoided burdens from recovered outputs (compost/digestate fertilizer substitution and biogas electricity substitution).

3.6 Survey evidence on waste characteristics and operational drivers

Survey responses provided complementary evidence on perceived waste characteristics and the operational drivers that influence the feasibility of improvement strategies. In terms of the most salient waste type generated by traders, plastics were reported most frequently, followed by organics, while paper and other categories were less prominent. Although these responses reflected perception rather than mass-based composition, the finding indicated that packaging-related waste was highly visible and operationally important for traders, which may shape compliance and support for interventions. This pattern aligned with broader arguments that reducing single-use packaging and moving upward in the waste hierarchy requires context-specific interventions that respond to everyday practices and incentives rather than relying on downstream treatment alone.

Survey findings were reported as proportions of valid responses to make category comparisons transparent and reproducible. This emphasis on response-based indicators is important in traditional market waste systems because trader participation and day-to-day practices can directly influence the feasibility of source separation and, consequently, the performance of downstream management options [11, 12]. Therefore, the percentage for each response category $j$ was calculated using:

$\%_j=\frac{n_j}{N} \times 100 \%$       (6)

where,

$n_j=$ number of respondents who chose category $j$ (for example, those who answered "Plastic")

$N=$ total valid respondents for that question (those who were not blank/NA)

$j \%=$ percentage of that category

Table 7. Distribution of perceived dominant waste types

The distribution of perceived dominant waste types is reported in Table 7.

The self-reported daily waste amount distribution per respondent is presented in Figure 8. Self-reported waste quantities per trader further suggested that the system consisted of many small sources rather than a few dominant generators. Most respondents reported producing less than 1 kg day⁻¹, with a smaller share in the 1–5 kg day⁻¹ range and only a minor tail above 5 kg day⁻¹. From an operational perspective, this structure implied that convenience and accessibility of collection infrastructure mattered, because participation depended on whether traders could dispose of waste with minimal disruption to trading activities. Prior studies in market settings similarly highlighted that trader knowledge, attitudes, and participation influenced waste management outcomes and the effectiveness of sorting initiatives. The concentration of responses in the lowest waste-quantity category is further illustrated in Figure 9.

Figure 8. Self-reported daily waste amount distribution per respondent (n = 224)

Figure 9. The concentration in the lowest waste-quantity category

3.7 Stakeholder priorities and readiness for scenario-based improvements

Respondents' stated priorities for improving market waste management revealed an important socio-technical insight: governance and behavioral interventions were perceived as more urgent than technology deployment alone. Education for traders and the community was the most frequently selected priority option, followed by source separation at origin and improvements to Temporary Waste Storage Sites (Tempat Penampungan Sementara, TPS), the designated intermediate storage areas where market waste is consolidated before municipal transport, while composting and biogas were selected by only a small fraction as the primary priority. This pattern suggested that, although organic recovery technologies are widely discussed as environmentally beneficial pathways, market stakeholders often viewed the enabling conditions, knowledge, routines, and shared responsibility as the critical bottleneck for sustainable implementation. These findings aligned with the broader literature emphasizing that waste-management transitions toward circular economy outcomes depend on institutional readiness and stakeholder participation, not only on the availability of treatment technologies.

This stakeholder evidence strengthened the logic of the scenario design used in the LCA framework. In particular, scenarios that assumed higher segregation rates (and therefore higher diversion to composting or AD) should be interpreted as requiring not only physical infrastructure but also behavioral and managerial interventions to sustain separation quality. The results, therefore, implied that scenario improvements could be realistically staged: early improvements would focus on education, containerization, and simple segregation, followed by scaling of organics recovery as separation performance stabilized. Such a staged pathway was consistent with the idea that recovery-oriented systems generate net benefits when upstream capture is reliable, and it also reduced the risk of underperformance due to contaminated organics or inconsistent collection. Stakeholder priorities for improving market waste management are presented in Figure 10.

Figure 10. Stakeholder priorities for improving market waste management (n = 224)

The authors gratefully acknowledge the financial support provided by the Indonesian Education Scholarship. This scholarship is administered through the Center for Higher Education Funding and Assessment, Ministry of Higher Education, Science, and Technology of the Republic of Indonesia, with additional support from the Endowment Fund for Education Agency, Ministry of Finance of the Republic of Indonesia. The authors also sincerely thank the Office of Cooperatives, Small and Medium Enterprises (UMKM), and Trade of Sukoharjo Regency, and the Environmental Office of Sukoharjo Regency for facilitating field access, providing institutional support, and enabling data collection for this study.