Scenario-Based Extended Cost–Benefit Analysis for E-Waste Metal Recovery in Low-Income Countries: Evidence from an Integrated Model in Burkina Faso

Abstract

The value of electronic waste as an urban mine has been extensively demonstrated, particularly regarding its rich content in precious metals. However, little is known about the economic feasibility in informal recovery contexts like in Burkina Faso. Previous studies were focused on formal and industrialized systems, overlooking informal dynamics in low-income countries. This study addressed that gap by applying a scenario-based Extended Cost–Benefit Analysis to assess metal recovery pathways in Burkina Faso. Six scenarios were modeled, combining technological selectivity, variations in local collection costs, and policy incentives such as Extended Producer Responsibility and eco-taxes as well as socio-environmental co-benefits. Results showed that e-waste recovery in the informal sector became economically viable when technological, financial, and policy instruments were combined. At a reduced e-waste cost of 5 USD/kg, manual dismantling and bioleaching technologies allowed for net benefits of 6.34 and 6.85 USD/kg, respectively, corresponding to improvements of 136% and 133% compared to baseline losses. Even at 10 USD/kg, both methods remained viable with positive returns and benefit–cost ratios above 1.06. It is impossible to generate net benefits with an e-waste purchase price of 10 USD/kg without EPR or eco-tax mechanisms, unless the price is reduced to 5 USD/kg; this could impose enormous constraints on collection activities. These findings confirmed that no single factor is sufficient to achieve profitability, highlighting the need to integrate supportive policies, technological appropriateness, and environmental co-benefits, a combination that aligns with circular economy principles and is essential to unlock the full potential of e-waste recovery in low-income countries.

1. Introduction

1.1. Informal E-Waste Management Realities in Low-Income Countries Like Burkina Faso

In low-income countries like Burkina Faso, the management of electronic waste (e-waste) remains almost entirely informal, shaped by fragmented value chains and the absence of fully implemented national legislation regulating e-waste flows. Even when policies exist, they are not enforced, and responsibilities among producers/distributors, consumers, and public institutions remain unclear [1,2,3]. Consequently, most devices are collected and processed by informal actors [4]. These informal circuits are characterized by highly variable purchase prices, context-specific valuation criteria, and environmentally harmful practices such as open burning or uncontrolled acid leaching [5]. For example, an investigation conducted at the Katr-Yaar collection site in Ouagadougou, Burkina Faso, revealed that PCBs and processors are sorted and traded at prices ranging from XOF 2800 to XOF 17,500 (approximately USD 4.67 to USD 29.17 per kilogram), depending on perceived metal content [6]. Although a few actors such as the Association Burkinabè pour la Promotion des Emplois Verts (ABPEV) conduct dismantling activities and export PCBs for formal recycling, most of the processing remains largely dominated by informal actors. This situation raises fundamental concerns about health and environmental risks but also highlights a missed economic opportunity. The lack of structured recycling pathways prevents the full valorization of materials contained in e-waste, despite their latent potential [7]. Burkina Faso represents a prototypical case of a low-income context where data gaps, informal labor dynamics, and the absence of economic incentives complicate any transition toward sustainable e-waste management [8]. Previous studies identified valuable materials that can be recovered from e-waste, such as steel and plastic [9,10], rare earth elements [11], metal, and glass [10]. Valuable metals that can be recovered from e-waste include gold (Au), silver (Ag), palladium (Pd), copper (Cu), tin (Sn), and platinum (Pt) [12,13]. According to [14,15], printed circuit boards (PCBs) are components of electronic equipment that contain precious metals. Despite growing attention to metal recovery technologies, most studies have focused on industrialized contexts, overlooking the realities of informal systems where e-waste is managed differently. Addressing this gap requires context-sensitive economic analysis and policy frameworks that integrate informal actors and align with circular economy principles.

1.2. Intrinsic E-Waste Value in Low-Income Countries

Although e-waste has great potential for recovery, especially due to its content in precious metals, it is important to recognize that it is not a homogenous waste stream. Its composition varies significantly depending on the origin and quality of the electronic devices, which are often lower in low-income countries where the market is primarily supplied with used or lower-grade electronic equipment [16,17]. However, recent studies suggest that certain categories of devices still present high recovery potential [7,8]. This reinforces the need to move beyond average composition figures and consider the specific characteristics of equipment streams. Indeed, the intrinsic value of e-waste varies not only between countries but also within the waste stream itself. As illustrated in

Table 1. Metal contents in waste PCBs from high- and low-income countries.

Context	Cu (g/kg)	Au (g/kg)	Ag (g/kg)	Pd (g/kg)	Equipment
Japan (high-income country) [18]	~400	0.3–0.4	~0.5	~0.01	Fresh e-waste (phones, computers)
Finland (high-income country) [19]	>400	-	~0.6	-	Formally collected devices
Italy (high-income country) [20]	~350	~0.25	~0.4	~0.015	Old mobile phones
Africa (low-/middle-income countries) [16]	<300	<0.02	<0.3	<0.01	Used, obsolete imports
Local study (Burkina Faso) [7]	295	0.021	0.373	0.001	PCBs from phones, computers, RAM, and processors

, while high-income countries report copper concentrations in PCBs often exceeding 400 g/kg and gold content up to 0.4 g/kg, studies from low-income countries report values below 300 g/kg for copper and under 0.02 g/kg for gold [16]. A local study from Burkina Faso by [7] measured the average copper content at 295 g/kg and gold at 0.021 g/kg, close to the lower end of global values. This same study also showed that certain types of devices, such as mobile phones, computers, RAM modules, and processors, contain significantly higher concentrations of valuable metals than others. This evidence confirms that, despite the general perception of e-waste in low-income countries being of limited value, there are specific device categories that act as “urban mine” deposits. Supporting this view, ref. [8] proposed a typology of e-waste in Burkina Faso, identifying a subset of devices with significantly higher precious metal concentrations. These include cell phones, laptops, tablets, digital cameras, DVD players, central units, and printers. Recognizing and isolating these richer fractions is key to designing cost-effective and scalable recovery strategies.

1.3. Disparities in Formal and Informal E-Waste Recycling

E-waste management systems differ significantly between high-income and low-income countries. In high-income countries, e-waste management is governed by well-established regulatory frameworks that promote safe and efficient collection, recycling, and material recovery. Certified companies operate within formal infrastructure, and consumers are often required to return their end-of-life devices to designated collection points. Extended Producer Responsibility (EPR) schemes and eco-contributions at the point of purchase further support these systems [21,22].

In contrast, low-income countries typically lack such formal structure. For example, there are oftentimes no regulations addressing e-waste management specifically in West African low-income countries, except in Ghana, Nigeria, and Côte d’Ivoire [1,2,3]. Even where laws exist, implementation is weak or nonexistent. In such contexts, e-waste management is governed by informal actors who operate outside any legal or environmental oversight. Consumers are not incentivized to return their devices; instead, they often sell them directly to waste collectors, who determine value based on a visual assessment of recoverable components.

This contrast increasingly emphasizes the need for tailored e-waste management approaches within broader circular economy agendas. The African Union’s Agenda 2063 and the African Circular Economy Alliance (ACEA) highlight sustainable resource use and green job creation as strategic priorities [23,24]. Similarly, global frameworks such as the European Green Deal and the Basel Convention promote Extended Producer Responsibility and regulated cross-border waste movements [5,25]. However, most of these frameworks offer limited guidance on how to integrate informal actors or adapt regulatory mechanisms to low-income contexts. This study contributes to bridging that gap by focusing on the specific economic levers that could make recovery viable in such settings.

1.4. Review of Existing Economic Analyses

Growing attention has been given to the economic feasibility of metal recovery from e-waste, particularly in industrialized countries. Numerous studies have demonstrated that under formalized systems, recovery operations can generate positive profits, create employment, and mitigate environmental damage [20,26,27]. These analyses often rely on standardized assumptions regarding material composition, pricing, and infrastructure [22,28]. However, such findings are difficult to translate to low-income countries, where the informal sector dominates, device quality is lower, and recovery processes vary greatly and are largely uncontrolled [2,17]. Even when precious metals are present, the costs of collection, treatment, and labor combined with the absence of regulatory support may prevent recovery from being economically viable. In many cases, studies overlook these context-specific factors [4,13]. Moreover, economic analyses rarely capture the full scope of social and environmental benefits associated with informal recovery systems. Non-market co-benefits such as avoided CO₂ emissions, reduced soil and water contamination, and local job creation are generally excluded from traditional cost–benefit frameworks, despite their significance in low-income contexts [29,30,31]. This gap limits the ability of existing models to inform inclusive and sustainable policy design. Finally, little is known about how different technological choices interact with informal pricing structures and socio-environmental impacts in low-income countries. Although some studies have explored various recovery technologies, whose characteristics are summarized in

Table 2. Overview of key characteristics of metal recovery technologies that are relevant to cost–benefit analysis in low-income countries.

Criteria	Pyrometallurgy	Hydrometallurgy	Solvometallurgy	Manual Dismantling	Bioleaching
Initial investment cost	High	Moderate	Variable	Low to moderate	Moderate
Processing cost per ton	High Energy and maintenance costs increase the cost per ton	Variable It depends on the cost of chemical reagents and effluent management	Non-available Specific data on costs per ton are limited	Low. Mainly related to labor costs	Low Microorganisms can be grown at low cost, but the process is slower
Local adaptability	Low Requires advanced industrial infrastructure	Medium Can be implemented with medium-sized facilities and proper management	Low Emerging technology requiring R&D investment	Very high Accessible to local waste pickers and artisans	Medium Requires technical support and knowledge of microbiology
Advantages	Effective for processing large volumes Capable of recovering multiple types of metals simultaneously	Suitable for processing smaller streams Allows for selective metal recovery	High selectivity for some precious metals Can operate at lower temperatures than pyrometallurgy	Low cost of entry Local job creation	Eco-friendly method with a reduced carbon footprint Capable of processing complex materials
Inconvenient	High energy consumption Potential toxic gas emissions requiring pollution control systems	Requires rigorous management of chemical waste to avoid pollution Can generate toxic effluents	Technology is still in development with limited availability Complex management of spent solvents	Slow and labor-intensive process Risk of exposure to toxic substances without adequate protective equipment	Slower process than chemical or thermal methods Requires precise control of biological conditions

, such as hydrometallurgy, pyrometallurgy, solvometallurgy, manual dismantling and bioleaching, most assume there is access to formal infrastructure and skilled labor [32,33,34,35,36,37]. Consequently, a growing consensus calls for more context-sensitive assessments that reflect the operational realities of informal e-waste economies [8,21]. Additionally, the volatility of gold prices on international markets introduces a significant variable in the economic modeling of e-waste recovery. As gold is one of the most valuable metals in PCBs, its price fluctuations can substantially affect the profitability of recovery operations. Historical trends showed considerable variation in gold market prices [38]. Incorporating sensitivity analyses based on gold price dynamics could improve the robustness of economic assessments.

1.5. The Gap and the Need for an Extended Cost–Benefit Analysis

The realities observed in low-income countries like Burkina Faso underscore a critical limitation of current research: there is no robust economic framework that simultaneously considers local cost structures, informal pricing dynamics, and the monetization of environmental and social co-benefits. While the intrinsic value of e-waste may be lower than in high-income countries, the opportunity for value creation remains, provided that recovery strategies are adapted to local contexts. A cost–benefit assessment is therefore necessary to determine the conditions under which metal recovery becomes viable in informal systems. Such an approach must go beyond traditional financial modeling to include broader political, societal, and environmental dimensions. These include Extended Producer Responsibility (EPR) and eco-tax mechanisms, the value of emissions avoided by recycling versus mining, the benefits of reduced local pollution, and the contribution of recovery activities to employment. At present, no study has examined how these factors interact within an integrated economic model tailored to the informal e-waste management sector in low-income countries. This knowledge gap left policymakers and practitioners without reliable tools to guide investments, design incentives, or assess the long-term sustainability of recovery pathways. This study addresses that gap by applying an Extended Cost–Benefit Analysis (ECBA) framework to simulate multiple metal recovery scenarios in Burkina Faso. The ECBA is needed to integrate detailed local and contextualized data to reveal under what combinations of technology, policy, and cost conditions e-waste recovery can generate net economic returns.

1.6. Objectives and Research Questions

This study aims to evaluate the economic viability of e-waste metal recovery in Burkina Faso by developing a scenario-based Extended Cost–Benefit Analysis (ECBA) model. The model integrates context-specific variables including informal purchase prices, technological recovery options, processing and labor costs, and the monetized value of social and environmental externalities. In contrast to previous studies, this research does not rely on standardized assumptions. Instead, it is grounded in empirical data gathered locally, including e-waste composition, collection dynamics, and informal pricing behaviors. The ECBA framework enabled the comparison of six recovery scenarios combining different technologies, cost structures, and policy instruments (e.g., EPR subsidies, eco-taxes). The study is guided by the following research questions: (i) Under what conditions do metal recovery technologies become economically viable in informal settings like Burkina Faso? (ii) How do local collection costs, recovery methods, and policy incentives affect the profitability of recovery pathways? (iii) To what extent can environmental and social co-benefits influence decision-making toward sustainable recovery models? Based on the literature review and contextual evidence, the study formulated the following hypothesis: “E-waste metal recovery in low-income countries can become economically viable when appropriate recovery technologies are combined with supportive policy instruments and the monetization of environmental and social co-benefits.” By testing this hypothesis, the study contributes both a methodological innovation and a practical decision-making tool to support circular economy transitions in low-income and informally structured e-waste systems.

2. Materials and Methods

2.1. Study Area

This study was conducted in Ouagadougou (1°31′05″ W, 12°21′58″ N), the capital city of Burkina Faso. Burkina Faso is a low-income country in West Africa with a GDP per capita of USD 874.1 in 2023 [39,40]. The population of Burkina Faso is 20,505,155 inhabitants [41] and the capital, Ouagadougou, represents 11.78% of this size, that is 2,415,266 inhabitants [42]. The commune of Ouagadougou has an area of 518 km² and is subdivided into 12 districts and 55 sectors [43] (Figure 1).

2.2. E-Waste Collection and Local Cost Information

E-waste used in this study was collected from 25 households (7 of low standing, 6 of high standing and 12 of medium standing) in Ouagadougou. These households were identified based on a preliminary survey during which they agreed to contribute to the study over a one-year period, allowing e-waste collection at their places. Bins were placed in these households, especially for e-waste collection. Each household was committed to reporting as soon as the bin was filled, so that the collection could take place. The collection of a wide variety of e-wastes was carried out over 13 months (from May 2023 to May 2024). It is important to clarify that the unit of analysis in this longitudinal survey was not the household itself, but the electronic equipment collected. The 25 households served as access points of collection. This approach allowed for a focused analysis on device-level recovery potential, rather than household-level representativeness. After the collection phase, sorting was performed based on the classification made by [8]. Therefore, sorting led to the identification of five (05) categories of e-waste with more valuable and precious metals, including phones (coding in this work from PH01 to PH16), tablets (TB01 to TB03), computers (CP01 and CP02), TVs (TV01 to TV04), and decoders and DVD players (DD01 and DD02). All TVs identified had light-emitting diode (LED) screens, which was in line with the classification.

Informal discussions were held with actors from ABPEV to collect local data on PCB purchase prices. Based on their extensive field experience, these actors can assess the potential value of different types of e-waste by estimating the expected quantity of recoverable metals. This practical knowledge allowed them to classify devices into informal categories and assign indicative prices in XOF per kilogram of PCB. These estimations, although not formally regulated, reflect prevailing market dynamics and were used as cost inputs in the economic analysis.

2.3. Extended Cost–Benefit Analysis for Optimizing Metal Recovery Activities

An Extended Cost–Benefit Analysis (ECBA) was carried out to identify the best combination of metals and technologies to prioritize for recovery activities. The analysis was performed in Python 3 considering the following:

• The market values of the metals: These are the prices on the international market of recoverable metals (Cu, Au, Ag, Pd, Fe) obtained via sources such as [38,44]. They made it possible to calculate the potential revenue per kilogram of processed PCB waste.
• Average quantities of metals per kg of PCBs: They are variable according to the type of equipment (phones, computers, TVs, tablets and decoder and DVD players), and they were used to estimate the real extractive potential of electronic waste. These average metal quantities were derived from authors’ experimental data (in preparation for publication).
• The cost of purchasing e-waste: This is the price at which recyclers buy the PCBs from the collectors. Considering these factors made it possible to better assess the total costs related to recovery activities.
• The recovery rates of target metals were determined based on a combination of peer-reviewed literature sources [12,26,32,33,35,36,37,45] and local field insights gathered through collaboration with ABPEV, particularly regarding manual dismantling practices observed in Burkina Faso. The assumed recovery efficiencies for each treatment technology are summarized in Table 3 as follows:
• It is also important to consider the purity level of recovered metals, which directly influences their market value and acceptance by formal buyers. Technologies such as bioleaching and solvometallurgy can yield varying purity levels depending on operational conditions. Ref. [31] demonstrated that selective recovery processes can achieve industrial-grade purity for gold, which is assumed in this study.
• Processing and labor costs per technology: These include energy, reagents, equipment, and estimated wages per kilogram of PCBs. Based on studies on workers’ wages conducted by [29,46,47] for low-income countries in Africa, it was assumed that the labor costs for recovery by technology are 1.5 USD/kg, 1.2 USD/kg, 1.8 USD/kg, 2.5 USD/kg, and 0.8 USD/kg for pyrometallurgy, hydrometallurgy, solvometallurgy, manual dismantling and shredding, and bioleaching, respectively. Studies carried out by [26,32], allowed us to set reasonable reference values of e-waste treatment costs at 20 USD/kg, 15 USD/kg, 18 USD/kg, 5 USD/kg, and 10 USD/kg for pyrometallurgy, hydrometallurgy, solvometallurgy, manual dismantling and shredding, and bioleaching, respectively. As these amounts are subject to probable variations depending on the context, a sensitivity text was performed with a variation of ±20% to better understand its influence on the profitability of recovery activities.
• Socio-environmental impacts: These include (i) CO₂ emissions avoided by recycling activities (vs. natural mining) valued at USD 50 per ton based on carbon market estimations [30], (ii) avoided pollution (soil, water, air) valued at USD 1.5 per kilogram of improperly managed e-waste [31], and (iii) locally created jobs considering that each full-time equivalent (FTE) position generates an average societal benefit of USD 2000 per year [29], scaled to the treated mass. Consideration of these impacts has made it possible to monetize the positive non-market externalities and integrate these benefits into the model to reveal the systemic value of recycling beyond the simple economic benefit. However, these valuations remain approximations based on generalized estimates that should be refined in further context-specific research using pilot projects reflecting real-world local socio-economic realities.
• EPR subsidy and an eco-tax: Based on the work of [21] and considering the context of low-income countries, we assumed an EPR subsidy of 3 USD/kg of treated PCBs to encourage recycling. Depending on the low purchasing power in low-income countries, an eco-tax of 1–3% maximum (converted to approximately 2 USD/kg of treated PCBs) is acceptable to encourage consumers to contribute to the management of the e-waste they produce.

Table 3. Assumed recovery rates (%) for target metals by treatment technology.

Technology	Cu	Fe	Ag	Au	Pd	Justifications
Manual dismantling	70	90	30	60	10	High recovery for visible metals like Cu and Fe; limited access to precious metals.
Bioleaching	60	20	50	85	35	Effective for Au, Cu, and Ag under optimized microbial conditions; Fe and Pd recovery remains low.
Hydrometallurgy	85	40	60	95	40	Proven efficiency for Au and Cu; moderate recovery for Ag and Pd; Fe is less targeted.
Pyrometallurgy	95	50	40	90	30	High recovery for Cu and Au; Ag and Pd partly lost in slag; Fe oxidized or diluted.
Solvometallurgy	80	30	70	97	50	High recovery for Cu; high selectivity for Au and Pd; emerging technique with promising results for Ag.
Sources: [12,26,32,33,35,36,37,45], and field observations with ABPEV

Table 3. Assumed recovery rates (%) for target metals by treatment technology.

Technology	Cu	Fe	Ag	Au	Pd	Justifications
Manual dismantling	70	90	30	60	10	High recovery for visible metals like Cu and Fe; limited access to precious metals.
Bioleaching	60	20	50	85	35	Effective for Au, Cu, and Ag under optimized microbial conditions; Fe and Pd recovery remains low.
Hydrometallurgy	85	40	60	95	40	Proven efficiency for Au and Cu; moderate recovery for Ag and Pd; Fe is less targeted.
Pyrometallurgy	95	50	40	90	30	High recovery for Cu and Au; Ag and Pd partly lost in slag; Fe oxidized or diluted.
Solvometallurgy	80	30	70	97	50	High recovery for Cu; high selectivity for Au and Pd; emerging technique with promising results for Ag.
Sources: [12,26,32,33,35,36,37,45], and field observations with ABPEV

Metal recovery costs, revenues, and net profits are calculated using the following formulas:

$$Total Cost=\sum [\left(Processing cost\right)\times \left(Labor cost\right)\times \left(Purchase price\right)]$$

(1)

$$Total Revenue=\sum [\left(Metal content\right)\times \left(Price\right)\times \left(Recovery rate\right)]$$

(2)

$$Net Benefit=Total Revenue-Total Cost$$

(3)

Several scenarios were formulated as shown in Table 4 to identify the optimal conditions under which recovery activities become economically viable.

Table 4. Different scenarios formulated for the ECBA.

Scenario	Description
Scenario 0	It made a gross cost–benefit assessment with the available data and serves as a basis to identify the aspects that could be improved with the aim to optimize the model.
Scenario 1	This scenario focused only on the recovery of the most significant metals (based on quantities and market costs) to judge their economic impact on recovery. It simulated the recovery of the most significant metals in the richest equipment.
Scenario 2	It simulated the recovery of the most significant metals in the richest equipment.
Scenario 3	The scenario proposed a variation in the purchase price of e-waste by recyclers to optimize recovery revenues.
Scenario 4	It was based on strategic and political recommendations proposing an EPR subsidy and an eco-tax on the purchase of equipment.
Scenario 5	This scenario evaluated the economic impact of the EPR subsidy and eco-tax associated with the valuation of all socio-environmental benefits (CO2 emissions and pollution avoided as well as locally created jobs). This simulation was based on Scenario 2, without changing the current purchase costs of e-waste.
Scenario 6	This scenario combined all the benefits and conditions to optimize the profitability of metal recovery activities. This included technical and operational adjustments (focusing on the recovery of the most significant metals in the richest equipment), EPR subsidies and eco-taxes, CO2 emissions and pollution avoided, and jobs created. Scenario 6 added fixed purchase prices for e-waste based on Scenario 3.

Table 4. Different scenarios formulated for the ECBA.

Scenario	Description
Scenario 0	It made a gross cost–benefit assessment with the available data and serves as a basis to identify the aspects that could be improved with the aim to optimize the model.
Scenario 1	This scenario focused only on the recovery of the most significant metals (based on quantities and market costs) to judge their economic impact on recovery. It simulated the recovery of the most significant metals in the richest equipment.
Scenario 2	It simulated the recovery of the most significant metals in the richest equipment.
Scenario 3	The scenario proposed a variation in the purchase price of e-waste by recyclers to optimize recovery revenues.
Scenario 4	It was based on strategic and political recommendations proposing an EPR subsidy and an eco-tax on the purchase of equipment.
Scenario 5	This scenario evaluated the economic impact of the EPR subsidy and eco-tax associated with the valuation of all socio-environmental benefits (CO2 emissions and pollution avoided as well as locally created jobs). This simulation was based on Scenario 2, without changing the current purchase costs of e-waste.
Scenario 6	This scenario combined all the benefits and conditions to optimize the profitability of metal recovery activities. This included technical and operational adjustments (focusing on the recovery of the most significant metals in the richest equipment), EPR subsidies and eco-taxes, CO2 emissions and pollution avoided, and jobs created. Scenario 6 added fixed purchase prices for e-waste based on Scenario 3.

3. Results and Discussion

3.1. Classification and Collection Prices of PCBs

Understanding how different types of e-waste are valued in practice is important for a cost–benefit analysis, given the central role of informal pricing in shaping recovery incentives. Figure 2 presents the variability of PCB purchase prices across five equipment categories (phones, tablets, computers, TVs, and DVD players) based on local market estimates obtained with ABPEV. The boxplot shows that tablets and phones command the highest purchase prices. For tablets, the interquartile range (IQR) extends from approximately 16.87 USD/kg to 20.83 USD/kg, with values ranging between 5.00 and 20.83 USD/kg. Phones show a narrower IQR from 12.50 to 20.83 USD/kg, but with consistently high values clustered near the upper quartile. Computers exhibit the widest price dispersion among all categories, with values ranging from 5.00 to 29.17 USD/kg and an interquartile range spanning from 7.08 to 25.21 USD/kg. TVs display moderate price variability, with values ranging from 0.25 to 6.67 USD/kg and an IQR between 0.25 and 6.67 USD/kg. DVD players show the lowest and most compressed price range, with most values lying between 0.25 and 5.00 USD/kg and a median at 2.62 USD/kg. These differences illustrate how recyclers estimate value based on perceived recovery potential: phones, tablets, and some computer components are considered to be rich in precious metals, while DVD players and standard TV cards are seen as low-yield devices. The average price across all categories based on average PCB prices per equipment category, adjusted by their estimated contribution to the overall stream, was approximately 13 USD/kg. Field interviews also revealed a striking paradox: although ABPEV is an officially recognized recycler that exports dismantled PCBs to certified partners in Europe, it buys PCBs at significantly lower prices, sometimes half the concurrence prices. ABPEV explained that its European partners strictly assess the recoverable metal content of e-waste and define prices based on environmental rather than profit-driven objectives, resulting in marginal or near-zero profit margins (field interview with ABPEV representative, 2024). High international transport costs for hazardous materials are likely to contribute to limiting profitability. In contrast, informal actors in Ouagadougou can offer much higher purchase prices, raising unresolved questions about the valorization circuits and economic models that sustain their activities.

3.2. Cost–Benefit Assessment for Metal Recovery from PCBs

Scenario 0 provides a baseline assessment of the economic viability of metal recovery without policy incentives or environmental co-benefits, reflecting the real constraints faced in low-income contexts.

Table 5. Economic performance and sensitivity analysis of metal recovery technologies.

Recovery Technology	Revenue (USD/kg)	Total Cost (USD/kg)	Net Benefit (USD/kg)	Net Benefit with Sensitivity Test (USD/kg)
				−20% Treatment Costs	+20% Treatment Costs
Manual dismantling	2.88	20.5	−17.62	−16.62	−18.62
Bioleaching	3.14	23.8	−20.66	−18.66	−22.66
Hydrometallurgy	3.94	29.2	−25.26	−22.26	−28.26
Solvometallurgy	3.86	32.8	−28.94	−25.34	−32.54
Pyrometallurgy	4.07	34.5	−30.43	−26.43	−34.43

presents the results of Scenario 0 of the cost–benefit analysis, which estimates the net benefit of metal recovery activities by integrating the value of metals per kilogram of PCBs, purchase costs, PCB processing costs, and labor and metal recovery rates by technology. All technologies appear to have a negative net benefit in this scenario. This is due to the high average purchase cost of PCBs (13 USD/kg), combined with high processing costs. Nevertheless, it is remarkable that manual dismantling followed by bioleaching is the least loss-making method; therefore, it is the most economically viable method in this context. Although pyrometallurgy is the most expensive option due to high energy and infrastructure requirements, it can achieve high recovery rates and enable better pollution control when operated in formal contexts [27]. The application of ±20% on processing costs shows that no technology achieves profitability (i.e., no positive value). The same variation of ±20% applied to the gold price also results in a negligeable average change of only 1.42% in net benefit across technologies. Manual dismantling and bioleaching remain the best recovery methods to achieve better profitability because they generate the net benefits closest to the break-even point and are quite stable in the face of processing costs that could vary according to the local context of each country. While bioleaching involves lower capital and operating costs, its environmental benefits depend strongly on factors such as the type of microorganisms used, leaching duration, and the treatment of effluents, which may contain residual acids or toxic ions [12]. While this study demonstrates that low-capital-intensive technologies such as bioleaching and manual dismantling are more suited to the economic realities of low-income countries, refs. [32,33] identified pyrometallurgy and hydrometallurgy as efficient in the formal context of high-income countries.

Six different scenarios were proposed following this first one with the aim of finding the best conditions and adjustments that promote the optimization of the net benefits of metal recovery activities from e-waste. Each scenario combines specific assumptions regarding recovery technologies, waste PCB purchase prices, policy incentives, and the inclusion or exclusion of non-market socio-environmental co-benefits.

Table 6. Key parameters and assumptions for each scenario used in the ECBA.

Scenario	Technology Scope	PCB Price	Policy Instruments	Co-Benefits Included	Objective
0	All	13 USD/kg	None	No	Baseline economic assessment
1	Cu and Au only	13 USD/kg	None	No	Prioritize valuable metals
2	Cu and Au in richest devices	13 USD/kg	None	No	Equipment-targeted optimization
3	Cu and Au in richest devices	5 USD/kg or 10 USD/kg	None	No	Cost-based viability simulation
4	Cu and Au in richest devices	13 USD/kg	EPR + Eco-tax	No	Policy-based incentive simulation
5	Cu and Au in richest devices	13 USD/kg	EPR + Eco-tax	Yes	Policy + socio-environmental valuation
6	Cu and Au in richest devices	5 USD/kg or 10 USD/kg	EPR + Eco-tax	Yes	Optimized integrated model

summarizes these keys parameters and assumptions.

Figure 3 presents results of net-benefit that could be generate while using each of the five recovery technologies according to the different scenarios. For each technology, the net benefit is displayed under two waste PCB collection cost assumptions: (a) 5 USD/kg and (b) 10 USD/kg. The results highlight how variations in collection cost, policy incentives, and co-benefit monetization affect the viability of each technology.

Scenario 1 (Base) prioritized the recovery of the most profitable metals, that are gold (Au) and copper (Cu), as previously identified to determine if these two key metals can effectively be sufficient to make recovery profitable. The results of this scenario have shown that no technology achieved profitability under the current conditions. However, manual dismantling remained the closest to the break-even point, followed by bioleaching with net benefits of −17.64 USD/kg and −20.67 USD/kg, respectively. These results were virtually identical to those of Scenario 0 and suggested that the recovery of copper and gold alone is not sufficient to offset the costs, despite their value. It is therefore necessary to think of other additional adjustments. Indeed, the findings of [7] insisted that the presence of valuable metals in greater quantities in e-waste compared to natural mines is a factor in attracting investors to the recycling sector. However, the present results suggest that this aspect is not sufficient to guarantee profitability under the current operating conditions in low-income countries. Structural barriers, such as collection and technological costs, are likely to dilute the potential net benefits of high-value metals. This underscores the need to not only prioritize copper and gold but also to improve recovery efficiency, streamline collection processes, and consider supportive policy mechanisms such as subsidies or incentives for green investment to truly unlock the potential of “urban mining” highlighted in the literature.

Scenario 2 (Rich Equipment) prioritized the recovery of the most profitable metals from the richest equipment (telephones and computers). This scenario has proven to have a considerable reduction in losses, and manual dismantling and bioleaching are close to the break-even point. Bioleaching, with a loss of 7.89 USD/kg, is closer to the break-even point than manual dismantling (loss of 8.38 USD/kg) compared to the previous scenarios. These results demonstrated the usefulness of focusing on the recovery of the most profitable metals (Cu and Au) from the richest equipment. This suggested a local strategy for presorting equipment before treatment to optimize profitability. Although this study prioritizes high-value e-waste categories such as phones and computers to optimize metal recovery, the gradual inclusion of other types of equipment, such as televisions and decoders and DVD players, remains a strategic opportunity. A selective approach based on the material content and economic recovery potential of each category would allow for the efficient scaling of the recycling system. This view is consistent with [21], who advocate for phased and resource-efficient expansion of waste management systems, particularly in resource-constrained environments. However, in cases where the metallic content of certain equipment is too low to justify metallurgical recovery, alternative valorization pathways, such as energy recovery, material recycling (e.g., plastics, glass), or safe disposal, should be considered. The study of [20] emphasizes the importance of diversifying recycling strategies to maximize the overall environmental and economic benefits from heterogeneous e-waste streams. Scenarios 1 and 2 make it possible to identify an “Optimizing Urban Mine Deposit Model” based only on the optimization of the quantities of metals to be recovered from e-waste.

Scenario 3 first simulated a gradual reduction in the purchasing cost of PCBs to identify the break-even point (maximum PCB purchase cost) that suits each technology to achieve profitability. The simulation was performed top-down from 13 USD/kg (current average purchase price of waste PCBs) to 0 USD/kg (indicating the case where the e-waste is received free of charge by recyclers). According to this scenario, the purchase cost must be 5 USD/kg, 4.5 USD/kg, and 2 USD/kg maximum for metal recovery activities through bioleaching, manual dismantling, and hydrometallurgy to reach the break-even point, respectively. Solvometallurgy and pyrometallurgy are unprofitable even if the PCBs are received free of charge. If recyclers can buy PCBs for less than 5 USD/kg, some technologies become viable (manual dismantling and bioleaching). The scenario subsequently tested two different PCB purchase costs (5 USD/kg Collection Only in Figure 3a, and 10 USD/kg Collection Only as shown in Figure 3b) based on the idea that recovery targets the most profitable metals and the richest equipment. The benefits when the purchase cost of PCBs is 5 USD/kg reach the break-even point (−0.38 USD/kg and +0.11 USD/kg, respectively, for manual dismantling and bioleaching) while when this cost is reduced to 10 USD/kg, the benefits become largely negative (−4.89 USD/kg and −5.38 USD/kg for manual dismantling and bioleaching, respectively). The main issue is sorting and accessing inexpensive waste PCBs. This leads to the “Reduced Collection Cost Model”. These results further confirm the interest in focusing on bioleaching and manual dismantling, which makes it possible to keep PCB purchase costs the highest and practically identical. In high-income countries, waste generators are often required to deliver their e-waste to collection points free of charge or even to pay fees for the disposal of certain categories of devices, as part of the application of the ‘polluter pays’ principle [21]. This is completely different from what is happening in low-income countries, where informal sector dynamics dominate, and collection remains largely dependent on the value of recoverable materials and market incentives. To reduce collection costs and improve recovery rates, short-term strategies could include promoting voluntary drop-off schemes, municipal subsidies for local collection centers, and partnerships with existing informal collection networks, as suggested in the literature [27].

Scenario 4 (Combined) was a “Policy Support” scenario that simulated a combination of EPR subsidy (3 USD/kg) and ecological tax (2 USD/kg) by maintaining the cost of purchasing PCBs at its actual average amount (13 USD/kg). Considering these financial incentives, the net benefits were approaching the break-even point with values of −2.89 USD/kg and −3.38 USD/kg for bioleaching and manual dismantling, respectively. These results allowed us to deduce the “Partially Incentivized Model” that highlighted the potential of policy support (EPR and eco-taxes) for the profitability of e-waste recycling activities. In most low-income countries, the major electronic producers are not directly established locally. The devices enter the market through importers, distributors, and retailers. In this context, [46] recommended adopting EPR schemes by assigning responsibility to the first entity placing products on the national market rather than the original manufacturers abroad. This recommendation is consistent with that of [21], who emphasized the importance of designing flexible, context-specific EPR frameworks in low-governance environments. Financing mechanisms, such as advanced recycling fees or eco-contributions applied at the point of importation, could represent viable options for sustaining recovery systems without overburdening local governments. Although phones and computers should be prioritized initially because of their high recovery potential, televisions, tablets, and decoders should also be progressively incorporated into national strategies given their growing market share.

Scenario 5 suggested considering, in addition to policy support (EPR and eco-tax), the valuation of socio-environmental benefits, that is, CO₂ emissions and pollution avoided, as well as locally created jobs. This scenario worked by maintaining the purchase cost of PCBs at a current value of 13 USD/kg. It was built focusing on recovering the profitable metals in the richest equipment and accumulating all the benefits (policy support and socio-environmental benefits), making it possible to achieve quasi-profitable net benefits. The values of these benefits are −1.15 USD/kg and −1.66 USD/kg for bioleaching and manual dismantling, respectively. These results confirmed the usefulness of exploiting the socio-environmental benefits generated by the recovery of e-waste. Developing local carbon credit schemes or integrating recycling into national climate strategies, as recommended by [30], could transform socio-environmental benefits such as avoiding CO₂ emissions and pollution reduction into tangible financial incentives. These mechanisms would not only enhance the sustainability of recovery systems but also broaden their contribution to national and global environmental goals. Refs. [29,30,31] recognized the value of these co-benefits, but few studies quantified them in comprehensive economic models. This study quantifies them, demonstrating their essential role in the economic balancing of recovery in informal contexts.

Scenario 6 cumulated the EPR subsidy, eco-taxes, and socio-environmental benefits and reduced PCB purchasing costs to 5 USD/kg and 10 USD/kg. The results showed that for a PCB purchase cost of 5 USD/kg, the benefits are positive for almost all technologies except for pyrometallurgy. These benefits were still quite significant only for bioleaching (net benefit = 6.85 USD/kg) and manual dismantling (net benefit = 6.34 USD/kg). This model is economically ideal for e-waste recovery activities. However, it has a considerable influence on the e-waste collection stage, which is upstream from the recovery stage. The model requires a reduction of up to almost a third of the current collection cost. When the purchase cost of PCBs is set at 10 USD/kg, the benefits are still positive for bioleaching and manual dismantling, even though they have decreased considerably. In this context, bioleaching brings a net benefit of +1.85 USD/kg of PCBs treated, and manual dismantling brings +1.34 USD/kg. These benefits are also interesting, and the model becomes even more inclusive by preserving the viability of e-waste collection activities as much as possible. This scenario, associated with Scenario 5, lead to the “Extended Socio-Environmental Model”, and highlights the possibility of achieving economic viability for e-waste recovery in low-income contexts through the strategic combination of EPR mechanisms, eco-tax financing, socio-environmental benefit monetization, and the partial reduction of collection costs. Importantly, the analysis suggests that no single lever alone suffices to ensure profitability; rather, it is the cumulative effect of multiple interventions that unlock the sector’s potential. However, this integrated model remains vulnerable to external shocks such as fluctuations in metal prices, policy discontinuities, or variations in operational costs. The finding that bioleaching and manual dismantling outperform more technologically intensive methods reinforces the importance of promoting simple, scalable recovery techniques that are well suited for resource-constrained environments. Furthermore, the observation that positive net benefits can still be achieved even when PCB purchase costs are adjusted to 10 USD/kg suggests a degree of resilience in the model, which makes it adaptable to real-world collection dynamics. Overall, these findings underscore the need for integrated context-specific strategies combining economic, environmental, and social levers to sustainably optimize e-waste recovery in emerging economies.

To better illustrate the financial performance of the two most promising recovery technologies (bioleaching and manual dismantling) in the different modeled scenarios, their respective net benefits are plotted in Figure 4. The results reveal that the two methods follow a remarkably similar profitability trend, with only marginal differences observed in most scenarios. This convergence suggests that, under informal system conditions and with appropriate cost or policy adjustments, either technology can be a viable recovery option. Scenario 6, which incorporates all optimization levers, offers the highest returns for both technologies, with bioleaching slightly outperforming dismantling.

Despite their promising cost–benefit performance, both manual dismantling and bioleaching present practical challenges that must be addressed prior to scale-up. Manual dismantling exposes workers to physical risks such as sharp components and dust, but these can be mitigated through protective equipment and proper training [48,49], as already practiced by a local initiative such as ABPEV. Bioleaching, although environmentally preferable to chemical alternatives due to its lower toxicity, requires longer processing times and careful control of microbial activity and residue management [32]. These should be seen as negative externalities that warrant careful evaluation. This reinforces the need for pilot implementations to better capture these unintended effects, assess feasibility and safety through a Life Cycle Assessment (LCA), and guide operational optimization before any large-scale deployment. Moreover, although this study focused on base and precious metals, future research could explore the integration of rare earth elements (REEs) into recovery models. Despite their low concentrations, REEs such as neodymium and terbium are critical for modern electronics and could enhance the strategic value of e-waste recycling in low-income countries [11].

Figure 5 presents a comparison between the recovery of e-waste with reduced collection costs to either 5 USD/kg or 10 USD/kg, considering the socio-environmental benefits, but without the introduction of an EPR subsidy and eco-tax. The results show that without the application of EPR and eco-taxes, it would be impossible to make positive net benefits by adopting a PCB purchase cost of 10 USD/kg. It would be necessary for these costs to be reduced to 5 USD/kg, which would impose enormous constraints on collection activities. This analysis completes the “Reduced Collection Cost Model” and confirms the need to review the costs of e-waste collection. For consumers of electronic equipment, who are also, at the same time, the sellers of e-waste to collectors, there is a need to raise awareness of the importance of the sustainable management of e-waste and their responsibility in this sector. Thus, it will be easier to opt for a considerable reduction in the prices of e-waste collection at their level or the application of an eco-tax on the equipment purchased, depending on the context.

Under Scenario 6 (Figure 3), which combines EPR subsidies, eco-tax mechanisms, and monetized socio-environmental benefits, metal recovery becomes economically viable for both bioleaching and manual dismantling. At a reduced PCB purchase cost of 5 USD/kg, the net benefit reaches 6.85 USD/kg for bioleaching and 6.34 USD/kg for manual dismantling, corresponding to profitability improvements of 133% and 136%, respectively, compared to the baseline scenario. Even when the purchase cost is raised to 10USD/kg, both methods maintain positive net benefits of 1.85 USD/kg for bioleaching and 1.34 USD/kg for manual dismantling with BCRs of 1.08 and 1.06, demonstrating relative resilience. These results confirm that no single factor is sufficient to achieve profitability; rather, it is the integration of supportive policies, technological appropriateness, and environmental co-benefits that unlock the potential of e-waste recovery in low-income countries. These results are contrary to what can be expected in high-income countries. Indeed, ref. [27] have shown that in industrialized countries with formal systems, recovery is cost-effective even without subsidies. Ref. [20] also confirmed profitability in a formal context, but without integrating the role of the informal sector.

This study provides more than a technical evaluation of metal recovery options. It delivers practical insights for shaping inclusive circular economy strategies in low-income countries, grounded in realistic behavioral and economic constraints. Key findings have implications that extend beyond the local context of Burkina Faso and speak to broader policy and trade agendas. First, the study demonstrated that recovery profitability is not solely a function of technology performance but depends on a combination of factors including purchase prices, labor costs, environmental and social co-benefits, and policy support mechanisms. The scenario analysis clearly showed that without policy intervention, all recovery options result in negative net benefits. This underscores the inadequacy of relying purely on market mechanisms for managing e-waste in informal settings, which is a key insight for designing EPR schemes under the Basel Convention [5] or African Union model legislation [24]. It reinforces the case for integrating subsidies, eco-taxes, or material-specific incentives when attempting to shift from informal to sustainable recovery chains. Second, the analysis showed that manual dismantling and bioleaching consistently perform best under varying assumptions, especially in terms of resilience to cost fluctuations. These findings offer concrete guidance for low-capacity environments seeking to develop viable recovery infrastructures. For the African Circular Economy Alliance [23] and related regional initiatives, this evidence supports investment prioritization in low-barrier technologies that can be scaled through local skills and small enterprise networks, especially in low-income urban contexts. These technologies also offer potential for labor-intensive green job creation; a stated objective of the Agenda 2063 [24]. Third, the valuation of non-market benefits such as avoided CO₂ emissions, pollution reduction, and job creation showed that the integration of these factors can push recovery systems closer to profitability. This has implications for climate finance mechanisms [50] and green investment frameworks [51]. Projects aligning with this logic may qualify for blended finance or carbon credit schemes under global green deals [25], positioning e-waste recovery as part of national climate strategies (e.g., NDCs or Just Energy Transition Partnerships). In that sense, this study supports a reframing of e-waste not just as a liability, but as an urban resource base with climate and equity dividends. Fourth, the observed gap between formal and informal pricing mechanisms, particularly the discrepancy in PCB valuations between actors like ABPEV and informal traders, highlights a need for transparent and standardized valuation criteria in cross-border e-waste movements. As the EU and other regions strengthen due diligence regulations on waste exports, such empirical insights can inform fair pricing protocols and certification standards [21]. Finally, the modeling approach itself, combining field-informed composition data, recovery scenarios, and cost–benefit simulations, offers a scalable template for urban mining assessments in other low-income countries. It can support evidence-based planning and policy design not only in Burkina Faso but across the African continent and beyond, especially for national circular economy roadmaps and international partnerships on resource efficiency.

4. Conclusions

This study set out to assess the economic viability of different e-waste recovery strategies in low-income settings, using Burkina Faso as a case study. By modeling four distinct policy and cost scenarios, it identified the conditions under which resource recovery becomes financially and socially sustainable, even within informal systems. The model integrated local pricing dynamics, metal recovery rates, treatment costs, and monetized environmental and employment co-benefits. Key findings include the following: (i) Reducing the PCB purchase cost to 5 USD/kg allows bioleaching and manual dismantling to reach the break-even point (Reduced Collection Cost Model) and even generate positive net benefits in optimized scenarios. (ii) When all enabling factors are combined including EPR subsidies, eco-taxation, and monetized co-benefits such as avoided pollution, emissions, and job creation, net benefits exceed 6 USD/kg for both technologies. However, this result is only achievable under a sharply reduced collection cost of 5 USD/kg, which may be difficult to implement in practice given current informal market dynamics where PCB prices average 13 USD/kg. (iii) Even when the purchase cost is moderately reduced to 10 USD/kg, both technologies remain profitable under the integrated model, although with more modest returns (Extended Socio-Environmental Model). This suggests a degree of resilience but also underscores the fact that partial cost adjustments alone may not be sufficient to unlock full economic viability. These results showed that no recovery technology achieves profitability under the current cost structure without external incentives.

The results support a reframing of informal e-waste recovery as a strategic opportunity rather than a liability. This study contributed to the circular economy policy agenda by offering a practical decision-making framework tailored to low-income contexts. The scenario models can inform national strategies and regional cooperation by highlighting the importance of combining fiscal instruments with low-barrier technologies. In line with Agenda 2063, the African Circular Economy Alliance, and international frameworks such as the Basel Convention, these findings offer a realistic pathway to scaling urban mining initiatives, green jobs, and climate-resilient recovery systems.

Beyond the specific case of Burkina Faso, the modeling approach developed in this study is designed to be transferable to other low-income contexts where informal e-waste management systems dominate. Many of the core assumptions such as the predominance of manual dismantling, limited regulatory frameworks, and the use of informal waste PCB pricing are shared across low-income countries. Moreover, recovery rates and basic processing costs for recovery technologies tend to remain stable across contexts. However, successful replication requires a minimum set of locally contextualized inputs, such as accurate data on e-waste collection market prices and informal labor dynamics.

Nevertheless, this research has some limitations. It is based on modeled assumptions, particularly regarding processing costs, recovery rates, and monetized externalities. Real-world pilot programs and field data are needed to validate and refine these parameters. Moreover, the model does not fully account for dynamic factors such as fluctuating metal prices, evolving waste streams, or synergies between formal and informal actors. Future research should integrate life cycle and value chain assessments and explore how hybrid governance models could enhance both efficiency and inclusiveness in the e-waste sector. In conclusion, this study provides a clear analytical foundation for designing economically viable and socially inclusive e-waste recovery systems in low-income countries. By identifying the technical and policy levers required to unlock value from discarded electronics, it offers a scalable tool to support informed policymaking and investment in the transition toward a global circular economy.