Towards Sustainable Municipal Solid Waste Management: An SDG-Based Sustainability Assessment Methodology for Innovations in Sub-Saharan Africa

Abstract

In sub-Saharan Africa, municipal solid waste management faces significant challenges, including inadequate infrastructure, increasing waste generation, and limited resources, leading to severe environmental and public health issues. Innovations in waste management are essential to address these pressing problems, as they can enhance efficiency, reduce pollution, and promote sustainable practices while fostering sustainable development. To select sustainable and contextually relevant solutions, it is vital to investigate their potential sustainability impacts based on the Sustainable Development Goals (SDGs) beforehand and to involve local stakeholders in the innovation process. Besides, engaging stakeholders increases community buy-in and fosters collaboration, leading to more effective and sustainable outcomes. This paper develops and applies a sustainability assessment methodology for innovations in municipal solid waste management systems in sub-Saharan Africa, with a case study in Ethiopia. The proposed methodology emphasizes the importance of involving local stakeholders in the SDG-based indicator assessment and offers suggestions for a data collection strategy. The case study on a composting process in Bishoftu Town demonstrates that stakeholder participation in selecting innovations positively influences the outcomes. However, the analysis indicates mixed effects of the innovation in the three sustainability dimensions, highlighting areas for optimization. Consequently, the presented method can support the innovation process of municipal solid waste management systems, fostering sustainable municipal development.

1. Introduction

Waste management is a critical global issue, particularly as highlighted in the Sustainable Development Goals (SDGs) Report 2022 [1], which identifies the triple planetary crises of climate change, biodiversity loss, and pollution. These crises are exacerbated by an increasing reliance on natural resources and unsustainable consumption patterns, as less than 10% of materials used globally are currently maintained in a closed loop [2]. With their rapidly growing population, urban areas face escalating municipal waste challenges, where waste generation often outpaces the capacity of waste management systems [3,4]. Waste management systems develop over time, and the path from waste to resource management often evolves in stages [5]. Generally, there are five phases of waste management development, namely waste generation and disorderly disposal (1), orderly landfilling (2), separation (3), recovery (4), and circular economy (5) [6]. Nevertheless, effective municipal solid waste management (MSWM) is vital for achieving all 17 SDGs, including SDG 3, good health and well-being, and SDG 12, responsible consumption and production, thereby playing a pivotal role in sustainable development [2,6,7].

The challenges of waste management in sub-Saharan Africa (SSA) are particularly acute. Although the region currently generates less waste per capita compared to industrialized nations, projections indicate that waste generation will increase rapidly, placing immense pressure on already limited waste management infrastructures [8,9]. Informal waste management systems play a pivotal role in SSA; however, they often operate outside government oversight and lack formal recognition, resulting in underreported recycling rates and missed opportunities for resource recovery [8,9,10,11]. In SSA most commonly waste is landfilled, often openly burned or dumped, partly separated, and seldom recycled [8,9,10,11,12]. Consequently, the majority of MSWMSs are currently in a transitional phase between stages 2 and 4 [6]. Nevertheless, it is evident that waste management systems are an essential lever to fulfil the SDGs, and waste production in SSA is projected to increase; therefore, targeted solutions for MSWMSs are quintessential.

The unique waste composition in SSA, which often includes a high percentage of organic materials, requires targeted approaches that differ markedly from those applied in the Global North [10]. A method designed to identify targeted solutions must engage local stakeholders and be practically applicable.

Country-specific sustainability standards from the Global North frequently fail to account for the socio-economic realities and infrastructural constraints faced by SSA countries [13,14]. These standards are often based on advanced technological frameworks and resources unavailable in many developing regions. Moreover, the governance structures, data availability, and informal practices prevalent in SSA render the introduction of appropriate innovations in the waste management sector that are customized to local needs difficult. Furthermore, the sustainability assessment of MSWM systems cannot be aligned to standards from the Global North as the circumstances and stages of the systems vary greatly [6,10]. In recent years several attempts were made to better access MSWMSs over the entire life cycle, using different sets of indicators [15,16,17,18,19,20]. However, not all dimensions of sustainability are considered [18,20], the indicators are based on non-globally applicable targets [16,20], only a hotspot analysis is targeted by the assessment [15], or stakeholder interests were not considered [17,18]. An overarching challenge for comprehensive sustainability assessments is the lack of readily available socio-economic and material flow data on waste management systems and a generic data collection approach to close this gap. Ceraso and Cesaro [21] identified life cycle thinking tools as an appropriate attempt to assess MSWMSs; however, they stress the necessity of considering the methodologies’ effects on stakeholders. A broader concept, such as the framework of the 17 SDGs provided by the UN in 2015, should be considered to assess the sustainability of a system to achieve universal applicability of the method and target all dimensions of sustainability, as well as stakeholders from different contexts [22]. Yet, the SDGs are not ready-to-use tools for any kind of question posed and thus require adaptation. Consequently, there is a critical gap in the literature regarding the adaptation of waste management strategies that are sensitive to the specificities of SSA’s socio-economic landscape [16].

This paper seeks to address these gaps by introducing a comprehensive methodology for assessing the sustainability status of MSWMSs in SSA. Grounded in a holistic Life Cycle Sustainability Assessment (LCSA) framework, the proposed methodology evaluates social, economic, and environmental impacts while determining the potential implications of proposed innovations (ex ante methodology). The methodology operationalizes a holistic Life Cycle Sustainability Assessment framework and is based on Sustainable Development Goal (SDG) indicators and a Life Cycle Assessment (LCA). Furthermore, the developed methodology is applied in a case study, providing deeper insight into data collection strategies and stakeholder involvement.

2. Materials and Methods

2.1. Literature Review—State of the Art of Methodologies

A literature review was conducted to identify the state of the art of assessment methodologies in waste management. MSWMSs can be divided, according to the literature [19,21], into 5 life cycle stages, namely “waste generation”, “collection”, “transportation”, “final disposal”, and “resource recovery (material and energy)”. Depending on the system under consideration, collection and transportation can be considered together, as the same people and companies are responsible for the processes. This is often the case in the SSA region, which is why the collection and transportation (C&T) life cycle phases are combined in this study. An ex ante assessment method by Wang et al. [19] was identified, which deals with waste management systems and their evaluation based on SDGs. The methodology provides a solid framework for the further development of the methodology presented in this paper. The methodology structure deals with the 3 stages of goal and scope definition, modeling, and interpretation, in line with Guinée’s LCSA framework, taking into account the 3 dimensions of sustainability [19,23,24,25]. To further dissect and develop the method of Wang et al. [19] on a broader spectrum, emphasis is placed on the following 3 aspects:

• Choice of tailored innovation and assessment method;
• Thematic priorities of stakeholder interests;
• Transparent scoring system.

Local stakeholders highly influence the choice of a tailored innovation as they are needed to identify a macro goal for the system within the first stage of goal and scope definition which—together with the context structuring—predefines suitable innovations needed for the scenario building.

Thematic priorities of the stakeholders are considered by the choice of indicators made for the assessment in the stage of modeling, as recommended by Wang et al. [19]. When dealing with sustainability topics that are relevant for stakeholders, it is much more likely that the innovation succeeds. Therefore, stakeholder inclusion and participation is a crucial point for further research [16]. Furthermore, it is necessary to suggest a data collection strategy that helps to close the data gap for conducting such LCSA studies.

The scoring system of the assessment must be transparent enough to provide a comprehensive result. Based on scoring transparency and the ability to provide comprehensive results, the LCSA scoring system of Henzler et al. [24] was adopted, in which an improvement of 10% or more for quantitative indicators in the comparison scenario leads to a score of +1, a deterioration in the comparison scenario leads to a score of −1, and a change of less than 10% leads to a score of 0. N/A is assigned for a lack of data or unclear changes. The steps of the methodology are outlined in Figure 1 and described in more detail in the following section, Section 2.2, while the possibilities for stakeholder inclusion are discussed in Section 2.3.

2.2. Life Cycle Sustainability Assessment Methodology—Methodological Steps

2.2.1. Goal and Scope Definition

The first step of the methodology is the definition of the goal and scope. Initially, for the goal and scope definition, so-called macro goals must be identified following the approach by Wang et al. [19]. A macro goal is an overarching goal set by the municipality or the country. For the LCSA framework here, it is essential to incorporate stakeholders’ perspectives on the research object [19]. Examples of macro goals in waste management could be easing the pressure on landfills, reducing greenhouse gases, securing jobs, and increasing the recycling rate. The macro goals of the cities in the waste management system under consideration can be determined by using current literature or via interviews with experts and waste management stakeholders to inquire about the current goals. Having set the macro goal of the MWMS, the context structuring follows. By way of definition, context structuring describes the environment, the region, the climate, the population, the established industries in the area under consideration, key points on waste regulation, and other factors that help describe the circumstances. This is conducted through literature research and by using data from field studies. This creates a better understanding of the focused area. The scope of time, area, and processes must be set as performed in LCAs and LCSA frameworks [19,26]. Also, a comparison scenario must be built by depicting an innovation. According to correlations that occurred in the baseline scenario, changes and impacts from the innovation on the system must be considered. For the innovation selection, it is crucial to include local stakeholders and experts for the reasons mentioned above. The final innovation and its mode of implementation must be concluded by local experts. Once an innovation has been chosen, a comparison scenario can be built from the baseline scenario, for example, with the help of a technology system map [27], which tangibly describes the innovation.

2.2.2. Modeling

In the modeling phase, a life cycle inventory (LCI) is performed, both for the current state (baseline scenario) and the comparison scenario, to assess the system within all 3 dimensions of sustainability, resulting in positive, no, or negative changes that come along with the chosen innovation. The LCI is used for data collection and calculations to quantify the inputs and outputs of a system. Here, those inputs and outputs consist of the typical material and energy flows that are needed for a material flow analysis (MFA) and LCA. It also consists of information on economic and social conditions. The socio-economic and environmental data needed are determined by the selected SDG-based assessment parameters—described in more detail in the next chapter. The baseline scenario data can be obtained via primary data collection with questionnaires and interviews as well as by conducting literature research. It is helpful to visualize occurring correlations in the system as this facilitates the prediction of potential changes in the comparison scenario, which must include the selected innovation. This means that material flows, processes, and resources of the baseline scenario must be adapted to represent the system with the selected innovation. In the modeling phase, an MFA should be conducted, since it serves as the basis for carrying out the LCA [16]. An LCA using the standardized ISO 14040 [26] procedure is the most developed assessment method in sustainability assessment and can be used to model the environmental aspects of the waste management system [23]. The socio-economic changes between the baseline and comparison scenarios are assessed semi-quantitatively with the help of literature, questionnaires, and assumptions [19]. To assess changes that are not covered by the LCA, indicators based on the SDGs can be used. The SDG-based indicator set chosen for this methodology applied to MSWMSs in SSA is based on outcomes of the SuCCESS24 project, to be found on the project’s website [28]. The indicator set must be adapted for this methodology. The generic methodology is intended to be applicable to the entire sub-Sahara region, which is why only impact category groups that were considered relevant by both Ethiopian and Ghanaian stakeholders were selected. Indicators must apply to all life cycle stages, have a clear connection to waste management, and should be single-point indicators. The indicator set is subdivided into the 3 dimensions of sustainability. Under each sustainability dimension impact category group(s) can be found referring to different SDGs, within an impact category group one or more impact categories can be found that define the group further, and finally indicators refer to the impact categories. An overview of the impact categories is given in

Table 1. Indicator system.

Sustainability Dimension	Impact Category Group	SDG	Impact Category
Environmental	Climate	13	Climate change
Economic	Energy supply and efficiency	7, 8, 9	Energy usage
			Energy intensity
	Poverty	1	Standard of living
			Income
Social	Education and skill development	4	Training/education
			Effectiveness of education/training
			Quality of training/education
	Effective, accountable, and inclusive institutions	16	Cost of waste management services
			Effectiveness of waste management services
			Inclusivity
			Accountability
	Health and safety	3	Accidents and health incidents
			Human toxicity
	Access to improved solid waste management facilities	11, 12	Frequency of waste management services
			Waste treatment efficiency

and the complete indicator set is to be found in the Appendix A. Under the 3 sustainability dimensions 7 impact category groups are listed, which in turn are divided into 16 impact categories and 27 indicators.

For each sustainability dimension, the proposed impact category groups, impact categories, addressed SDGs, and linkage to MSWM in Ethiopia are explained.

• Environmental Dimension

Under the environmental sustainability dimension, the impact category group “climate” with the impact category “climate change” is considered. Since the widely used LCA can be applied for environmental assessment, this method is the only one within the 3 dimensions that is solely quantitative [19].

Climate change (SDG 13): The climate crisis is one of the most critical issues faced by our society nowadays and must be addressed through a variety of approaches. SDG 13, “climate action”, has the goal to limit global warming to 1.5 °C above a pre-industrial level by “taking urgent action to combat climate change and its impacts” [22] and thereby underlines the Paris Agreement. By 2030, greenhouse gas emissions will need to fall by 42%, according to the Intergovernmental Panel on Climate Change (IPCC) [29]. Current national commitments are insufficient to meet the 1.5 °C target; instead, following the current track, a global warming of 3 °C is projected [29]. Immediate emission reductions are needed in all sectors to reach a tipping point for a sustainable future [29]. The SSA region is highly affected by climate change through droughts as well as heavy rainfalls [30]. Solid waste, at its various stages of management, is a source of greenhouse gas emissions; transport, but especially landfilling, produces greenhouse gases (GHGs), primarily methane (CH₄), which is one of the most potent GHGs [31]. Waste globally accounted for 3.4% of GHGs in 2020 [32]. Thus, proper integrated waste management can help reduce resource use and mitigate emissions directly and indirectly [31]. Innovation in the MSWMSs could impact the GHG emissions arising from the waste sector and, therefore, should be explored and assessed.

In this impact category, the CO₂ equivalents (CO₂e) generated by the processes in the waste management system are modeled and assessed. CO₂e is a unit of measurement for standardizing the climate impact of different greenhouse gases, such as methane, carbon dioxide, or nitrous oxide [33]. With the quantitative indicator global warming potential (GWP), the contribution of a process and its material and energy flows to climate change can be made measurable. The emission factors must be determined for all the different processes in the waste management stream. Some emission factors such as landfill gas emissions, composting emissions, open-burning emissions, etc., can also be calculated according to equations from the IPCC [34]. If, in the comparison scenario, the introduction of an innovation results in fewer greenhouse gases being emitted by the waste management system, the innovation would have a positive impact in this impact category.

2

Economic Dimension

Under the economic dimension of sustainability, 2 impact category groups can be found, namely “poverty” and “energy supply and efficiency”, including a total of 4 impact categories.

Energy supply and efficiency (SDG 7): Energy consumption is an indicator of a prosperous economy, as it reflects the existence of purchasing power and technological progress [25]. SDG 7 calls for “ensur[ing] access to affordable, reliable, sustainable, and modern energy for all” [22]. Therefore, the source and efficiency of energy must be assessed. In 2019, not even 30% of the electricity consumed worldwide came from renewable sources [35]. In MSWM, many types of energy are used for transportation, equipment, recycling, and treatment. In most developing countries today, much of the work involved in waste management is still performed by manual labor. For instance, waste collection with sacks and carts or sorting the different waste components is still performed manually. Manual labor in the waste sector is exhausting and challenging, which is why the use of machines and, thus, higher energy consumption can be seen as a positive change for the workforce. Nevertheless, responsible use of all equipment and energy should be promoted. Therefore, considering both indicators, primary energy consumption (renewable and fossil) and energy intensity, is recommended.

Poverty (SDG 1): SDG 1 has the goal to “end poverty in all its forms everywhere” [22]. Yet poverty is on the rise again. Due to multiple crises, such as COVID-19 or the war in Ukraine, inflation is rising, and many people have lost their jobs [1]. Poverty manifests itself in hunger, malnutrition, limited educational opportunities, discrimination, and exclusion and is thus intertwined with many other SDGs. Hence, poverty is much more than the absence of financial income and has far-reaching consequences for those affected [36]. The international poverty line had an income of less than $1.90 per day until 2022 [37]. In Ethiopia, 30.8% of the population lived below this international poverty line in 2015 [37]. In September 2022, the global poverty line was updated and set to $2.15 per person per day [38]. According to the UN, Southern Asia and SSA are expected to have the largest increase in poverty due to the above-mentioned reasons. Projections indicate that 6% of the world’s population will still be living in poverty in 2030, which would mean failing SDG 1 [36]. Every effort should be made to meet the goal, and the impact of a waste management system should not be underestimated. The solid waste management industry currently offers a wide range of jobs in both the formal and informal sectors. According to Coffey and Coad [7], up to 6 jobs are provided per 1000 inhabitants. This offers great potential for jobs that can help reduce poverty. Nevertheless, the contemporary wages of unskilled labor in the waste sector are relatively low [7]. An innovation in the waste management system could impact the quantity and nature of jobs, as well as wages, and therefore should be assessed [19]. Indicators in this impact category take into account the changes in income for people working in the waste sector and living under the national poverty line and the minimum basket of living compared to the real consumption of the workers is going to be considered. The impact category group “poverty” also considers workers’ expenditures, as this may provide a more accurate representation of poverty in a local context than just referring to income from their job in the waste sector [39]. Many individuals often need to hold multiple jobs to sustain their standard of living [35]. The suggested indicators for SDG 1 are “worker’s expenditures compared to Minimum Expenditure Basket”; “income of formal workers by occupation, living below the international/national poverty line”; “rate of formal workers, by occupation, living below the international/national poverty line”.

3

Social Dimension

Social aspects are often left out in assessments, but they remain an area that mostly affects stakeholders. Here, 4 impact category groups are found, including a total of 11 impact categories. Social conditions should not only be safeguarded from decline but also actively enhanced. This is emphasized by the SDGs and the identified indicators, which need to be evaluated within the LCSA framework [40].

Education and skill development (SDG 4): SDG 4 has the goal to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all” [22]. In SSA, only 29% of children completed secondary school in 2019 [22]. The growing rate of people completing secondary school is the lowest worldwide, leaving the SSA region behind [41]. It can be assumed that the COVID-19 pandemic has reduced this number again, as poor and vulnerable children, in particular, are affected by inadequate educational opportunities [41]. Nevertheless, not only children are affected but also teenagers and adults. SDG 4 aims to achieve lifelong learning by making workers more resilient and adaptable to economic shocks or technological advances and improving living conditions. To create a more resilient and adaptable workforce, broader participation in education and training is needed. Prior to the COVID-19 pandemic, the global participation rate in formal and nonformal education was estimated at 25% [41]. The education of the population is the key to making workable systems. Irrespective of a sophisticated waste management system, the best recycling system will be ineffective if the users lack the technical know-how. An innovation in the waste management system might require new skills, hence an improvement or change of training might be essential. Some indicators suggested by Ferreux and Henzler [42] need minor adaptations to create a clear link to waste management and to ease the indicator by taking shares instead of total numbers into account. Also, indicators that cannot be linked to all life cycle stages are suggested to be left out. Consequently, this paper suggests the social indicators “the proportion of workers reporting having personally felt discriminated against or harassed or stigmatized or not appreciated within a set period of time due to their work in the waste sector”; “share of people applying knowledge”; “provision of training/campaigns”; “participation rate of training/campaigns”; “social participation in solid waste separation”; “satisfaction of the people with their training”.

Effective, accountable, and inclusive institutions (SDG 16): SDG 16 intends to strengthen institutions, “promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable, and inclusive institutions at all levels” [22]. Transparency, integrated decision-making, and participation are keywords to this SDG. This means that institutions have a major role in society and can promote gender equality, sustainable development, and combat all kinds of discrimination. Here, this impact category group considers the effectiveness, accountability, and inclusivity of solid waste management institutions. The impact category group “effective, accountable, and inclusive institutions” will look at whether institutions deliver on the promises they make to their workers, whether different population groups are included in the institution, the cost and effectiveness of the system or institution, and whether people who use the service and those who work in the system have opportunities to give feedback or make complaints. The suggested indicators for SDG 16 are “costs of waste management services for operating stakeholders involved in the waste management (e.g., disaggregated by the municipality, associations (formal and informal sector))”; “rate of waste collected/transported/disposed of”; “rate of female and male and diverse workers, by occupation, age, and persons with disabilities and ethnicity in decision-making institutions (municipality/association) (formal and informal sector)”; “proportion of workers who believe that decisions regarding waste management were implemented by the municipality/association (formal and informal sector) as agreed upon”; “availability of a complaint unit”.

Health and safety (SDG 3): With SDG 3 the UN aims to “ensure healthy lives and promote well-being for all at all ages” [22]. This includes a variety of measures to provide clean air, good nutrition, and good conditions of services at work for mental and physical health. This is an important goal in the waste sector, as the waste sector is responsible for keeping cities clean and thus minimizing the negative health impacts of accumulated waste on the population. Persistent organic pollutant emissions can be a consequence of uncontrolled waste incineration, and vector-borne diseases, such as cholera or dengue fever, spread with ease through accumulated waste and clogged drains, to name just a few of the health risks posed by waste [9]. In addition, following SDG 3, the health conditions of workers in the waste sector, as they are exposed to, e.g., hazardous substances, fumes, and heavy objects daily, should be assessed [9]. In the impact category group “health and safety”, the risk of accidents, health incidents, and human toxicity is therefore considered as an impact category. Since accidents, unlike in Wang et al. [19], are also taken into account in this impact category group, the impact category group was titled “health and safety”. This had been conducted analogously to Maier et al. [25] and Henzler et al. [24]. The indicators suggested are “workers’ risk of accidents (e.g., disaggregated by sex and migrant status/ethnicity)”; “workers’ perceived risk of health issues”; “particulate matter (PM) formation”; “human toxicity potential”.

Access to improved solid waste management facilities (SDG 12): SDG 12 is dedicated to responsible consumption and production, to “ensure sustainable consumption and production patterns” by 2030 [22]. As material consumption increases globally, the overarching economic system must ensure that end-of-life consumer goods are handled responsibly, which can only be achieved if the consuming population has access to a waste management system [1]. This impact category group was not included in the methodology by Wang et al. [19]. However, it was proposed to be included by the experts of the SuCCESS24 team [42]. “Improved” in this context means that waste is properly managed and not openly dumped or burned and addresses the fact that the closer the system to a circular economy is, the better. Suggested indicators are “proportion of solid waste (disaggregated into different sectors) managed out of total waste generated” and “waste recovery and waste recycling rate”.

The indicators build the basis for questionnaires and literature research needed for the data collection in the modeling phase for the LCI. For data collection, it is recommended to host a workshop, which is described in more detail in the section “Stakeholder Involvement”. Based on the collected data and modeling in the LCI, an impact assessment can then be carried out. The indicators are evaluated individually to assess the changes of the indicators between the baseline and comparison scenario, and the scale of Henzler et al. [24] is used with the scores +1, 0, −1, and N/A. All indicators are weighted equally, and the impact category and impact category group, respectively, are evaluated according to Formulas (1) and (2).

$${\mathrm{s}}_{\mathrm{i}\mathrm{m}\mathrm{p}\mathrm{a}\mathrm{c}\mathrm{t} \mathrm{c}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{g}\mathrm{o}\mathrm{r}\mathrm{y} \mathrm{x}}={\displaystyle \frac{{\mathrm{s}}_{\mathrm{i}\mathrm{n}\mathrm{d}\mathrm{i}\mathrm{c}\mathrm{a}\mathrm{t}\mathrm{o}\mathrm{r} 1}+{\mathrm{s}}_{\mathrm{i}\mathrm{n}\mathrm{d}\mathrm{i}\mathrm{c}\mathrm{a}\mathrm{t}\mathrm{o}\mathrm{r} 2}+\dots +{\mathrm{s}}_{\mathrm{i}\mathrm{n}\mathrm{d}\mathrm{i}\mathrm{c}\mathrm{a}\mathrm{t}\mathrm{o}\mathrm{r} \mathrm{n}}}{\mathrm{n}}}$$

(1)

$${\mathrm{s}}_{\mathrm{I}\mathrm{C}\mathrm{G} \mathrm{x}}={\displaystyle \frac{{\mathrm{s}}_{\mathrm{I}\mathrm{C}\mathrm{G} 1}+{\mathrm{s}}_{\mathrm{I}\mathrm{C}\mathrm{G} 2}+\dots +{\mathrm{s}}_{\mathrm{I}\mathrm{C}\mathrm{G} \mathrm{n}}}{\mathrm{n}}}$$

(2)

where s = score; n = number of indicators, respectively, in impact categories; and ICG = impact category group.

2.2.3. Interpretation

The results are then visualized in charts for a better overview and interpretation within the third phase. For every impact category group, an evaluation, discussion, and interpretation are to be given. The results will be summarized, and a recommendation must be made in favor or against the implementation of the innovation concerning its potential impacts in all 3 dimensions of sustainability. The results are intended to help decision-makers obtain an accessible overview of the possible impact of the considered innovation and see hotspots within the current MSWMS.

2.3. Stakeholder Involvement

This section focuses on how best to involve local stakeholders in the proposed LCSA methodology. Stakeholders can be all waste practitioners, from people in administration to workers who carry out the processes in the waste management system. Local stakeholders are system experts and therefore extremely important for the holistic assessment of the system. They know characteristics, weaknesses, and strengths of a system, which cannot necessarily be gleaned from publicly available data. Especially in the informal sector, local experts know structures that might never have been documented before but are crucial to understanding and improving the system. Stakeholders from the public and private as well as from the formal and informal sectors should be identified to obtain an overall picture of the system. For stakeholder identification, it is helpful to ally with local NGOs or waste experts from local universities that possibly have further contacts in the waste sector.

As pointed out in the previous section, there are 4 main points where stakeholders and local experts must be consulted. Their participation is crucial for the following:

• Macro goal identification;
• Selection of an innovation;
• Selection of the indicator set;
• Data collection.

2.3.1. Macro Goal Identification

For the macro goal identification, it is recommended to carry out prior extensive literature research. Goals that have been laid down, e.g., laws, proclamations, and visions of the state under consideration, can serve as initial points of reference for possible macro goals. In the next step, local waste management experts, for example from local universities, should be consulted. Those local experts know local challenges best and can presumably estimate well which measures are expedient to mitigate the challenges (e.g., job creation, occupational safety or health, reduction of greenhouse gases/other emissions).

2.3.2. Selection of an Innovation

Also, the definition of the innovation for the waste management system should not be based solely on literature research but also on the experience and recommendations of local waste management experts and practitioners [19]. Experts can be university members, NGOs, and members of the municipality, all of whom are involved in waste management issues. A pre-selection of innovations can be given to the experts based on the identified macro goal. One innovation can be chosen following an iterative process, as shown in Figure 2 and explained in the following.

For defining an innovation, the following iterative process is proposed in this paper:

• Researching general possible innovations in the context under consideration (data collection);
• Preparing a list with suitable innovations according to the sustainability study conductor and their respective possible impacts on the waste system (pre-selection of innovations);
• Presenting the list to local waste experts and limiting the selection based on the expert’s knowledge and feedback (consulting experts/stakeholders);
• Listing the reduced number of proposed possible innovations with their detailed description, advantages, and possible challenges (basic comparison scenario building) (data collection);
• Identifying lacking data for a sound decision, e.g., in a stakeholder workshop (data collection);
• Stakeholder workshop—defining problems in detail and collecting missing data;
• Discussing and deciding on an innovation and mode of implementation with experts based on the innovation list, available data, and system problems (consulting experts/stakeholders to define the final selection of an innovation).

The innovation should be selected according to the following 2 key criteria: urgency to achieve the macro goal and economic feasibility. Furthermore, the innovation should be defined precisely based on the baseline scenario (e.g., location, capacity, etc.).

2.3.3. Selection of the Indicator Set

For the selection of the indicator set for MSWMSs in SSA, several SDG Stakeholder Workshops were held with stakeholders and experts from Ghana and Ethiopia. A pre-selection of possible sustainability topics was given out to the stakeholders and 2 main points were discussed with the workshop attendees: firstly, whether the topic is important for the stakeholders in terms of its sustainability impacts on MSWM; and secondly, whether there is a high or low scope for action for the stakeholders within this topic [42]. Those 2 discussion points define the relevance of a sustainability topic. The SDG Stakeholder Workshop aimed to ensure that stakeholder interests were included and the possibility of action-taking was given as a result of the sustainability assessment. In further workshops, Ghanaian and Ethiopian waste experts decided jointly on suitable indicators under those impact category groups, which form the indicator set considered for this methodology. For adapting the indicator set to the MSWMS analyzed, it is strongly encouraged to inquire and implement the feedback of the aforementioned MSWM experts on the indicators.

2.4. Data Collection

To assess the systems, data are needed. Especially socio-economic data are hardly found in the literature and specifically essential to obtain tailored results in the analysis. Therefore, it is recommended that data be collected from stakeholders directly. For several reasons, it is suggested that a data collection workshop be held before giving out the questionnaires. It is culturally determined to explain in detail why the data are needed and how the assessment and possible measures could improve their working conditions, as it is unusual, especially in Ethiopia, to give out data for no reason. When holding such a data collection workshop, it must be considered that the participants have a loss of earnings during participation, so the duration of the workshop must be compensated. In order to make the workshop accessible to various stakeholders, further costs such as transportation to and from the workshop should also be provided free of charge, and occurring travel costs should be reimbursed. The workshop must provide information on why the data are collected, the benefits for the system and the stakeholders, and explain why the chosen indicators reflect stakeholder interests and what the innovation may look like. Afterwards, the data collection should take place using the provided questionnaires. Communication with the stakeholders in the local language should be ensured to facilitate a successful knowledge transfer and minimize language barriers in the data collection.

3. Results

The above outlined methodology is now applied in a case study of the municipal solid waste management system in Bishoftu Town, Ethiopia. The study area depicts a town in central Ethiopia with a formal and informal waste management system, including a landfill and composting facility. A more precise description of the study area is found in context structuring.

3.1. Goal and Scope Definition

This study aims to examine the MSWMS in the city of Bishoftu Town, located in the Oromia Region of Ethiopia. With the help of an LCSA framework including an SDG-based indicator set, sustainability hotspots in the current MSWMS should be identified. Based on the hotspots, an innovation that could improve the system should be suggested. Furthermore, the impact on the environmental, economic, and social dimensions of the suggested innovation is to be assessed. Based on the assessment, the implementation of the innovation should be recommended or not recommended to decision-makers. Additional suggestions and recommendations that support an introduction of the innovation are to be given.

The system to be examined is defined in the scope definition. This case study examines the MSWM and its processes in the Ethiopian city of Bishoftu Town (Debre Zeyt) for the year 2022. Recycling of materials such as metal, glass, paper, and plastic occurs outside the city limits, which is why these processes are not included in the calculations. The life cycle stages of C&T, recycling, and final disposal will be covered. The context structuring will help narrow this study’s scope [19].

3.1.1. Macro Goal Identification

The Integrated Urban Sanitation and Hygiene Strategy of Ethiopia from 2017 [43], as well as earlier-released proclamations and policies such as the environmental policy of Ethiopia (1997) [44] and the Ethiopian Solid Waste Management Proclamation No. 513/2007 [45], set out visions and goals for solid waste management. Recycling should be strengthened. This includes the fact that informal workers should be better supported, as they take over a large part of the recycling [43]. In addition, composting should be encouraged at household, small and micro enterprise (SME), and municipal levels. It is a form of recycling that effectively addresses the high amounts of organic waste, and it can lead to a reduction in the use of chemical fertilizers, which is beneficial [43,44]. For better implementation, it is helpful if households already separate waste [43]. Generally, solid waste treatment improves social and economic circumstances [45].

A study [46] of Bishoftu Town’s waste management system revealed the problems of open waste burning and dumping, insufficient waste collection coverage, and large amounts of landfilled waste with an especially high share of organic matter.

Together with the local experts from the Addis Ababa University and municipality, it was identified that the landfilled organic waste is one major issue and thus should be reduced—which is in line with the 2021 Nationally Determined Contribution (NDC) [47]. Therefore, the recycling of the organic matter should be strengthened. This was decided due to the high share of organic matter and the potential use of compost in urban gardening projects and general farming. The concluded macro goal is the following:

Composting should be promoted, as the large share of organic waste in the waste composition offers great potential for recycling this waste fraction. Waste recycling has generally positive effects on the environment and human health. Bishoftu Town is a pioneer in the field of composting with its existing composting plant and could become a role model for other cities in SSA through further development in this field.

3.1.2. Context Structuring—Bishoftu Town, Ethiopia

Ethiopia is a landlocked country in the so-called “Horn of Africa”, located in the eastern SSA region. “With about 117 million inhabitants in 2021, Ethiopia is the second most populous nation in Africa” [48]. It has the fastest growing economy, yet also represents one of the poorest countries, clearly categorized as a low-income and developing country [48]. Ethiopia was ranked 175th out of 191 in the 2021 Human Development Index. The situation in the country is described as volatile. Peaceful general elections were possible in 2021; nonetheless, the conflict in the northern part of Ethiopia with the Tigray people and ongoing droughts have triggered food insecurity, human rights violations, and many more regressions [48,49]. A study [50] indicates that 23.5% of Ethiopia’s population are living below the national poverty line.

Bishoftu Town is located in the Oromia regional state, close to the capital of Ethiopia, about 61.9 km southeast of Addis Ababa [51]. It is situated on a trade route that is frequented by freight traffic between Djibouti and Ethiopia. Bishoftu Town is divided into 14 districts or kebeles, as known in Ethiopia. As this case study focuses on Bishoftu Town, the city boundaries here will represent the system boundaries in terms of area. The climate in Bishoftu Town is temperate with average temperatures ranging from 7.4 °C to 30.2 °C, which makes an average of 18.8 °C [51]. Bishoftu Town receives rainfall between July and September and averages around 860 mm, with sunny and dry winds [51].

The city municipality and administrations, usually financially supported by the government, are responsible for the overall waste management, including developing action plans and measures and implementing those into the waste management system at the city or the respective lower administration level [52,53].

The stage of C&T is of major importance in the waste management system in developing countries, as it represents the highest expenditure of the municipal budget and has the greatest impact on the population and urban life [7]. In Bishoftu Town, waste C&T is partly covered by the municipality, nine enterprises, and some informal scavengers. Nevertheless, not all waste is picked up, and about 30% remains in households and on streets [46], which is common in low-income settlements [7]. The waste is collected directly from households (once a week) and commercial businesses (daily) and brought to an unofficial transfer station close to the landfill site and Bishoftu’s composting site. The enterprises work independently and generate income through collected waste fees directly from households and commercials.

The responsibility for the landfill lies with the municipality, while the responsibility for the composting plant lies with three independent enterprises. Recyclables are collected by scavengers, and there are no comprehensive estimates of informal scavengers in the city [46].

3.1.3. Scenario Building

The baseline scenario can be built based on the context structuring and questionnaires for data collection can be prepared.

To build the comparison scenario, an innovation must be chosen. The innovation must be suitable for the area under consideration, especially regarding capital and technology, as those are the main constraints that hamper sustainable development in the waste sector [54]. Due to the close cooperation with local waste experts within the SuCCESS24 project in which the case study took place, the decision for an innovation was made in an iterative process narrowing down the options of innovations. First, a list with general possible innovations and their respective possible impacts on the waste system was prepared including innovations in the field of composting, incineration, mechanical–biological treatment, plastic recycling, and waste banks. Those innovations were presented to waste experts from the University of Addis Ababa and narrowed down based on experts’ knowledge and experience. Further research was needed to determine the innovations left, namely in the field of composting. In another meeting with the experts, the expansion of the existing composting plant in Bishoftu as well as the building of a new plant were discussed as a means for handling the large share of organic waste in Bishoftu Town. Missing data on the existing plant were identified, such as its capacity. Besides, the conduction of the stakeholder workshop was identified as crucial for bringing clarity concerning the real problems in the field of composting.

The data collection workshop in Bishoftu Town was hosted in January 2023 [55]. Herein, stakeholders clarified that the capacity of the current composting plant is not fully used and will not be used. This is due to the fact that there is no market for compost since farmers do not know about the concept of compost and are instead familiar with the use of chemical fertilizer. The result was that neither the expansion nor a newly built plant would address this issue. The issue of an absent market for compost needs to be addressed and opportunities to increase the flow rate should be explored to foster innovation. After further consultation with waste experts, the innovation was ultimately defined as follows: six manual rotating compost sieves and six new wheelbarrows will be introduced so that each composting enterprise will acquire two of the respective devices. Suitable equipment was taken as a reference [56,57]. The number of devices was agreed upon with the managers of the composting enterprises and was considered reasonable [58]. Photos of the composting plant in question as well as the content of the data collection workshop in Bishoftu Town are provided on the project website [55].

3.2. Modeling

The life cycle modeling is intended to help answer the following question: can the targeted introduction of wheelbarrows and compost sifters contribute to a more sustainable city?

For the case study, the SDG-based indicator set suggested in the sustainability assessment methodology needed some adjustments according to the local context of Bishoftu Town and its MSWMS. The adjustments to the indicators proposed in the methodology for sub-Saharan cities can be found below.

• Indicator: Provision of training or campaigns (workers/residents)

According to the experts, and the suggested methodology for Ethiopian cities, this indicator should include formal and informal offers of training and campaigns. A clear clarification of what a formal and an informal offer is, is not given. All offers given by the Bishoftu municipality and enterprises are formal such as door-to-door awareness creation, job trainings for the workers, and posters. As those can be categorized as formal offers, there will not be a subdivision into formal and informal offers.

• Indicator: Proportion of workers reporting having personally felt discriminated against, harassed, stigmatized, or not appreciated within 2022 due to their work in the waste sector

This indicator is not recommended for application in the case study as the correlation between awareness-raising campaigns and discrimination is very low, according to the Ethiopian SuCCESS24 partners [59]. There is a wide range of reasons why people might feel discriminated against, harassed, or stigmatized, which they cannot clearly allocate to their work in the waste sector. For this case study the indicator is left out.

• Indicator: Social perception towards waste management

This indicator primarily addresses the inhabitants of Bishoftu Town and their perception towards the waste management activities in the MSWMS. Due to the limited resources of this case study, the residents’ perception towards MSWM was not inquired after for all life cycle stages. Instead, information on the residents’ level of satisfaction with the waste removal system collected by Admassu [46] could be provided for the modeling phase.

• Indicator: Cost of waste management services for operating stakeholders involved in waste management (e.g., disaggregated by municipality, associations (formal and informal sector))

This indicator is defined more precisely; the distinction between the informal and formal sectors is omitted, as no data on informal processes can be collected in Bishoftu for the case study. Thus, the indicator is called “cost of waste management services for operating stakeholders involved in waste management disaggregated by municipality and enterprises”. For the disaggregation and to have a single-point indicator in the end, the indicator is divided into (a) costs of waste management services for the municipality and (b) costs of waste management services for enterprises.

• Indicator: Rate of female and male and diverse workers, by occupation, age, and persons with disabilities and ethnicity in decision-making institutions/municipality/associations (formal and informal sector)

For cultural and political reasons, the category of diverse is becoming obsolete [60]. In order to avoid any unpleasant situations or even legal consequences for the workers, the category “diverse” was removed from the indicator. Another sensitive issue is ethnicity which is also removed from the indicator to avoid creating precarious situations for the interviewees. Besides, as the operating units in Bishoftu’s MSWMS are called enterprises, the term “associations” will be replaced by the term “enterprises”. The municipality is the decision-making institution in Bishoftu, hence only naming the municipality is sufficient. As stated previously, the informal and formal sectors cannot be differentiated in this case study. In conclusion, the indicator in this case study is called “rate of female and male workers, by occupation, age, and persons with disabilities in municipality/enterprises”. Furthermore, to obtain a single-point indicator in the end, the indicator is subdivided into the categories of gender (indicator a), age (indicator b), and ability (indicator c). The occupation will be covered by applying the indicator to all life cycle stages.

• Indicator: Proportion of workers who believe that decisions regarding waste management were implemented by the municipality/association (formal and informal sector) as agreed upon

This indicator is found in the impact category group “effective, accountable, and inclusive institutions”. As decisions regarding waste management in Bishoftu Town are only made by the municipality (decision-making institution), the indicator must be adapted to the “proportion of workers who believe that decisions regarding waste management were implemented by the municipality as agreed upon” [61].

• Indicator: Availability of a complaint unit

Due to the small-scale task distribution in Bishoftu Town, there is no general unit for complaints where complaint information is stored. Everyone can contact the waste management officer via phone, but this cannot be counted as a complaint unit. Therefore, the indicator is changed to “availability of a contact person for official complaints in the waste sector”.

• Indicator: Workers’ risk of accidents disaggregated by sex and migrant status/ethnicity

In analogy to the social indicator above, the question of origin and ethnicity must also be adjusted here. The topic of ethnicity is too sensitive and is therefore not included. The data availability for accident risks as a function of gender is limited in Bishoftu Town, which is why this aspect must also be omitted. In addition, it is important to show that accidents are dependent on certain work processes or life cycle stages, as this can also be reflected in other MSWMSs. Therefore, the indicator should refer to workers’ accidents in general and be called “workers’ risks of accidents”.

• Indicator: Workers’ perceived risk of health issues

This indicator must be taken with caution because the workers might have health issues or symptoms that occur during their work that do not necessarily have to be related to their work in the waste sector [61]. The indicator stays, but the potentially low correlation must be considered. In order to emphasize the perceived risk, the case study refers to reported health risks.

• Indicator: Particulate matter formation

There are generally no data on particulate matter formation in SSA, especially in its waste management system. The indicator cannot be assessed without accurate data on the African continent. Therefore, the indicator is removed from the indicator set.

• Indicator: Human toxicity potential

Due to a lack of data, the indicator is removed from the indicator set.

• Indicator: Proportion of solid waste (disaggregated into different sectors) managed out of total waste generated

The data available for this indicator were insufficient for an in-depth assessment. Only the generated waste from different sectors could be identified but the municipality of Bishoftu Town could provide no data regarding the following waste streams. Yet, the proportions can be calculated according to the MFA [46], neglecting the disaggregation into different sectors. Moreover, in the case study, only municipal solid waste is examined which is why this should be specified in the indicator. Therefore, the indicator is renamed to “proportion of municipal solid waste managed out of total municipal solid waste generated”.

• Indicator: Waste recovery and waste recycling rate

The waste recovery and recycling in the case study of Bishoftu Town is only allocated to the life cycle stage of recycling. There is no recycling in the stage of C&T and also no resource recovery on the landfill (final disposal). The indicator must be omitted because it cannot be applied to all life cycle stages. However, the information on the recycling rate can be taken as additional information from the previous indicator “proportion of municipal solid waste managed out of total municipal solid waste generated”.

• Indicator: Income of formal workers by occupation, living below the international/national poverty line (disaggregated into municipality, association, private company)

As the life cycle stages of Bishoftu’s MSWMS already clearly disaggregate the responsibility (C&T—enterprises; waste recovery and recycling—enterprises; final disposal—municipality), there is no need for mentioning a disaggregation into entities in the indicator. Furthermore, the exact income is very sensitive and data cannot be collected on this issue. Hence, it is suggested to leave out this indicator and only focus on the indicator “rate of formal workers, by occupation, living below the international/national poverty line”. The most recent data on poverty lines could be found on the international poverty line; therefore, the indicator will only refer to the international poverty line [38]. The indicator used in the case study is “rate of formal workers, by occupation, living below the international poverty line”.

Of the 27 indicators proposed in the outlined ex ante sustainability assessment methodology for sub-Saharan cities and MSWMSs, 18 are applied in the case study in Bishoftu Town. Two of those indicators are subdivided into a, b, and c. The indicator set applied in the case study is shown in

Table 2. Indicator set applied in the case study of Bishoftu Town.

Sustainability Dimension	ICG	IC	Indicator
Social	Education and skill development	Training/education	1. Provision of training/campaigns
			2. Participation rate of training/campaigns
		Effectiveness of training/education	3. Share of people applying knowledge
			4. Social participation in solid waste separation
		Quality of training/education	5. Satisfaction of the people with their training
	Effective, accountable, and inclusive institutions	Cost of waste management services	6. Cost of waste management services for operating stakeholders involved in the waste management disaggregated by municipality and enterprises
			a. Cost of waste management services for the municipality
			b. Cost of waste management services for enterprises
		Effectiveness of waste management services	7. Rate of waste collected and transported/recycled/disposed of
		Inclusivity	8. Rate of female and male workers, by occupation, age, and persons with disabilities and in municipality and enterprises
			a. Rate of female and male workers in municipality and enterprises
			b. Rate of workers, by age, in municipality and enterprises
			c. Rate of workers with disabilities in municipality and enterprises
		Accountability	9. Proportion of workers who believe that decisions regarding waste management were implemented by the municipality as agreed upon
			10. Availability of a contact person for official complaints in the waste sector
	Health and safety	Accidents and health incidents	11. Workers’ risk of accidents
			12. Workers’ perceived risk of health issues
	Access to improved solid waste management facilities	Waste treatment efficiency	13. Proportion of municipal solid waste formally managed out of total municipal solid waste generated
Economy	Energy supply and efficiency	Energy usage	14. Primary energy consumption (renewable and fossil)
		Energy intensity	15. Energy intensity
	Poverty	Standard of living	16. Worker’s expenditure compared to the Minimum Expenditure Basket
		Income	17. Rate of formal workers, by occupation, living below the international poverty line
Environmental		Climate change	18. Global warming potential

. Additional information is collected on waste collection coverage, frequency of waste collection, and social perception towards waste management.

3.2.1. Remarks and Assumptions

One important point to note about the assessment is that potentials are identified, and no consequential assessment is performed. Therefore, e.g., the potential of saving time is shown and it is not considered whether or not activities could be performed in the saved time [62]. During the modeling, it was evident that the indicators are hardly applicable to all four life cycle stages. The first stage, “waste generation”, appears to be a passive stage and should, therefore, be evaluated as a material input as in the MFA, instead of a life cycle stage. In order to make the indicators for the case study in Bishoftu Town applicable, they will be limited exclusively to the life cycle stages of “collection and transportation”, “recycling”, and “final disposal”.

To enable ex ante modeling and evaluation of the comparison scenario, the following seven assumptions must be made:

Assumption 1:

Increased demand for compost.

The system is very limited to improve in terms of a higher recovery rate for organic matter, as the lack of a compost market limits the production. Yet, the market for compost cannot be directly influenced as the market is located outside of the system boundaries of this case study. Nonetheless, it has to be assumed that the demand for and thereby the consumption of compost increases; otherwise, the potential of the innovation would be dismissed, and the innovation will not have any influence on the system. It is assumed that the increased demand for compost is driven by the provision of information campaigns and trainings for farmers around the area (mode of implementation). This assumption leads to the total utilization rate of the capacity of the composting plant. Hence, 9983 t of organic waste are processed in the composting plant in the comparison scenario.

Assumption 2:

The quantities and composition of the generated waste stay the same as in the baseline scenario.

The comparison scenario is an adaptation of the baseline scenario and, therefore, also refers to the year 2022, hence the generated waste quantities and composition stay the same.

Assumption 3:

Waste composition at the transfer station.

It is assumed that the waste composition at the transfer station corresponds to the waste composition of the waste generated excluding the recyclable fractions of paper, plastic, and metal. This assumption applies to the baseline scenario and the comparison scenario and is necessary due to a lack of more precise data.

Assumption 4:

Compost turning/rotating.

In the compost processing, it is assumed that during one period of compost making (3 months) the windrows must be turned 12 times with the turning machinery [63]. Usually, it is dependent on the compost temperature, but to facilitate the calculations, the turning is performed 12 times a quarter year. It is also assumed that in the comparison scenario, the windrows still must be turned 12 times during a composting period. There will not be more windrows due to limited space; the existing six windrows will just get more voluminous. Therefore, the fuel consumption of the turning machinery stays the same in the comparison scenario as in the baseline scenario because the distance covered remains the same.

Assumption 5:

Worker’s income.

It is assumed that the income of workers changes with the working hours. The income correlates proportionally to the working time.

Assumption 6:

Working hours in the composting plant.

The working hours in the composting plant are proportional to the amount of waste processed, only the time required for the rotation process remains the same regardless of the amount of compost, as the machine can also convert larger quantities.

Assumption 7:

Health risks correlate with working hours.

It is assumed that any kind of health risks as well as accidents are related to the time people spend carrying out their jobs.

3.2.2. Data Collection

Based on the built scenarios, modeling is conducted, which first requires data collection. Questionnaires were prepared to collect socio-economic data from the following stakeholder groups: municipality, enterprises (Composting, C&T), workers (composting, C&T, landfilling), and households. A data collection workshop was held in Bishoftu Town in January 2023 previous to data collection, where all stakeholder groups, except households, were present. The circumstances and necessity of the study were explained and the requirements for data collection were outlined. Data were then collected via the questionnaires with the help of local support. Material flow analysis (MFA) data has already been collected throughout a previous study at the University of Addis Ababa, Ethiopia in Bishoftu Town [46]. This MFA data could be used for this study as well. Each SDG-based indicator was then calculated for the baseline scenario and the comparison scenario, and an indicator score showing a potential positive or negative impact of the innovation was assigned. In the following, the assessment of two impact category groups is exemplarily shown.

3.2.3. Assessment of the Impact Category Group Health and Safety

Workers’ Risk of Accidents

The risk of accidents is calculated according to the working hours. Here, it is assumed that the longer people work the more likely accidents become (if accidents occur in the baseline scenario) [62]. In the baseline scenario, 13 accidents happened in the stage of C&T in 2022. In the stage of recycling, two accidents occurred during a total of 4754.4 working hours in 2022. Landfilling takes 8320 h annually with zero reported accidents in 2022.

The innovation does not cause any change in the collected and transported waste and consequently also no change in the working time at C&T; therefore, the probability of accidents does not increase and a score of 0 is given here. In the life cycle stage of recycling, i.e., composting, the working time is significantly extended in the comparison scenario, thus increasing the probability of accidents at work and a score of −1 is set. In the landfilling phase, the workload is reduced by 23.39% due to the reduced amount of waste landfilled. As no accidents were reported in 2022, it can be assumed that no accidents will occur in the comparison scenario as the risk cannot be further reduced. The score is set to 0.

Workers’ Perceived Risk of Health Issues

Waste in general but especially landfills pose a risk to human health as they are often the source of infectious diseases [64,65]. Bishoftu’s landfill is placed on the outskirts of the city and fenced off so that no direct settlement can take place at or nearby the facility. This minimizes waste-related health problems for the city’s inhabitants; however, the waste workers are exposed to odors and harmful emissions on a daily basis. Furthermore, the work in the waste sector is physically demanding, which is another reason for health issues, like back pain, related to the MSWMS. In the questionnaires, the following examples of health issues were given: coughing, irritation of the eyes, headache, nausea, breathing difficulties, and back pain.

A total of 60% of the workers across all life cycle stages report having experienced health issues at work at some point. In the life cycle stage of C&T, 60% of workers experienced health issues, of which 35% experience those issues sometimes and 25% often. In the recycling stage, 50% of workers reported health issues in 2022. The responses are evenly split between sometimes- and often-occurring symptoms, with the rest of the workers never having experienced health problems at work. The workers in the final disposal stage of the life cycle, i.e., at the landfill, have all sometimes experienced health issues in 2022.

In the comparison scenario there is again no change allocated to the C&T stage; therefore, a score of 0 is set. As the working hours for composting increase in the comparison scenario, the risk of health issues increases significantly, and thus is scored −1. The working hours for landfilling will decrease; therefore, the risk of health issues experienced by the workers will decrease, and thus is scored +1.

Table 3. Scores of the impact category: accidents and health incidents.

Indicator	C&T	Recycling	Final Disposal
Workers’ risk of accidents	0	−1	0
Workers’ perceived risk of health issues	0	−1	+1
Total	0	−1	+0.5

summarizes the indicator scores for the impact category accidents and health incidents. The impact category shows no change in the C&T phase, a negative change in the stage of recycling, and a slightly positive change in the stage of final disposal due to the innovation.

As there is only one impact category under the impact category group of health and safety, the total scores of the impact category group equal the scores of the impact category, showing no change in the stage of C&T, a negative change in the stage of recycling, and a slightly positive change in the stage of final disposal.

3.2.4. Assessment of the Impact Category Group “Climate”

Several GHG emissions must be taken into account when calculating the global warming potential. The different emission factors for the processes and greenhouse gases can be found in the Appendix A (

Table A1. Emission factors of heavy-duty vehicle.

	GHG	Value	Unit	Source
Heavy-duty (diesel) trucks 7.5 to 16 t (conventional)	Carbon dioxide	0.486	g/km	[82]
	Methane	0.085	g/km
	Nitrous oxide	0.029	g/km

,

Table A2. Fuel and energy consumption.

Type	Consumption	Value	Unit	Source
Heavy-duty (diesel) trucks 7.5 to 16 t (conventional)	Fuel	182	g/km	[82]
	Energy	7.77	MJ/km

and Table A3).

Diesel-powered tractors are used for waste collection and transportation. The tractors have a capacity of 8.9 t and make a total of 50 trips per day from the city to the landfill and composting plant. Each of the nine C&T enterprises has a tractor and the municipality supporting C&T with its task force owns another nine tractors. These emitted 9.92 t CO₂e in 2022 resulting in 0.34 kg CO₂e per tonne of transported waste [66,67]. Compared to the other life cycle stages, the global warming potential is lowest in the C&T phase.

In the recycling and resource recovery stage, the CMC ST 350 machine for turning the open windrows is used. The machine is also powered by a tractor and thus releases CO₂ emissions caused by diesel combustion during its use. Furthermore, fugitive emissions of CH₄ and N₂O emissions are released during the composting process [68]. In the baseline scenario, a total of 44.78 t CO₂e are emitted in the recycling stage (composting).

During the stage of final disposal, GHG emissions are released from dumpsites, open burning, and the landfill. Open burning of MSW usually occurs in an uncontrolled manner leading to an incomplete combustion, which results in several harmful emissions such as carbon monoxide (CO), NO_x, dioxins, and particulate matter (PM) [69,70]. Dumping and landfilling mainly cause methane emissions. Also, GHGs from fuel combustion are considered. The emissions are calculated based on IPCC 2007 [34]. No primary data are available on SSA-specific emissions, which is why default values and secondary data provided by the IPCC are needed for the calculation. In the baseline scenario, a total of 31,467.63 t CO₂e is emitted in the stage of final disposal.

The GWP of all life cycle stages in the baseline and comparison scenario can be viewed in Figure 3. No change is recorded in the C&T stage as the same amount of waste is transported by the tractors and thus the same emission arises. In the recycling stage, the GHG emissions rise significantly (by 3723.87%) to a total of 1712.33 t CO₂e due to the higher amount of organic waste being composted. Hence, a score of −1 is set here. Yet, the emissions arising in the recycling stage are minor compared to the GHG emissions from the stage of final disposal. Thus, the recycling stage accounts for 0.14% and 6.46% of the total GWP in the baseline and comparison scenario, respectively. A decrease in emissions can be observed predominantly due to the reduced amount of landfilled MSW. An amount of 21.22% of CO₂e are saved in this life cycle stage; thus, a score of +1 is set. The scoring results of the impact category “climate change” can be seen in

Table 4. Scores of the impact category “climate change”.

Indicator	C&T	Recycling	Final Disposal
Global warming potential	0	−1	+1
Total	0	−1	+1

.

The assessment values of the impact category group “climate” equal the assessment values of the impact category “climate change” with no change in the stage of C&T, a negative change in the stage of recycling, and a positive change in the stage of final disposal.

3.3. Interpretation

3.3.1. Presentation and Evaluation

The assessment of the innovation indicates an overall potential positive impact on the MSWMS in Bishoftu Town, even though the innovation does not show any positive or negative impact on the C&T stage and a slightly negative impact on the stage of final disposal. In Figure 4, the results for the seven impact category groups are visualized for the three life cycle stages with the use of net diagrams.

According to the assessment, the innovation would potentially not have positive or negative impacts in the C&T stage as the innovation is placed in a later-occurring life cycle stage and is not expected to impact the C&T processes in the MSWMS in Bishoftu Town.

In the recycling stage, mostly positive impacts but also negative impacts are recorded. In the impact category group “health and safety”, a potential negative influence of the innovation is identified due to the extended working hours needed to process larger amounts of organic waste. The impact category “climate” is negatively influenced due to higher emissions from composting compared to the baseline scenario. However, this result must be viewed critically. While in the life cycle stage of recycling, greenhouse gas emissions increase, and more than 5000 t CO₂e (15.90%) are saved for the whole system compared to the baseline scenario, resulting in an overall positive effect of the innovation on the climate impact of the MSWMS, which negates the negative impact in the life cycle stage of recycling. As the assessment methodology does not aim to aggregate the results over the life cycle stages and the overall impact cannot be seen from the individual scores, this additional information needs to be considered when deciding on the introduction of the innovation. Besides, the positive effects of the innovation would become even more evident if the offsets caused by the compost were included. In a minor sensitivity analysis, the offsets of compost were analyzed.

Positive impacts in the life cycle stage of recycling are projected for the impact category groups of “education and skill development”, “effective, accountable, and inclusive institutions”, “access to improved solid waste management facilities”, “energy supply and efficiency”, and “poverty”. Education and skill development will be improved by offering trainings to the composting workers needed to handle the new tools. The improvement in the impact category group “effective, accountable, and inclusive institutions” will be expected through improved working conditions in the composting plant due to new tools and a generally higher recycling rate, making the system more effective. The increasing demand for compost is expected to facilitate a higher composting rate and utilization rate of the plant. In turn, access to improved solid waste management facilities (here composting plant) is expected. More energy is needed to process higher amounts of organic waste in the composting plant which leads to higher energy consumption in the recycling stage, standing for economic prosperity. Poverty is expected to be reduced for the workers at the composting plant due to extended working hours resulting in higher incomes from their jobs in the MSWM sector.

The life cycle stage of final disposal is expected to have slightly more negative effects on the sustainability of the MSWMS. There are positive impacts expected through the innovation in the impact category groups “health and safety” and “climate”, as can be seen in Figure 4. No change in “education and skill development” and “poverty”, and negative changes for the impact category groups “effective, accountable, and inclusive institutions”, “access to improved solid waste management facilities”, and “energy supply and efficiency” are expected. The positive change for health and safety can be accredited to the reduced working time as less waste is landfilled in the comparison scenario. In the impact category group “climate”, a potential positive effect of the innovation is identified as it would result in less organic matter being landfilled. Negative consequences in the impact category group “effective, accountable, and inclusive institutions” are to be assessed critically. The change in the indicator rate of waste disposed of is scored negatively as a decrease in the MSW disposed of can be seen in the comparison scenario. This results in a negative result for the impact category group. However, the reduced amount of MSW does not diminish the effectiveness of the entire MSWMS. Only in the stage of final disposal do fewer waste quantities appear, which are instead composted. Thus, not fewer quantities of waste are managed over the entire life cycle, which also does not impair the effectiveness of the system. Thus, the negative impact in the impact category group “effective, accountable, and inclusive institutions” in the final disposal life cycle stage is negligible and, therefore, should be seen as additional information. The same applies to the impact category group “access to improved solid waste management facilities”. A negative impact occurs here in the final disposal stage, as the total amount of MSW that ends up in landfills decreases. The amount of unmanaged MSW (dumping and open burning) in the life cycle stage remains unchanged. In addition, the share of waste that is no longer landfilled in the comparison scenario is composted instead and thus remains managed, but in a different life cycle stage. Here, a comparison should also be made with the total managed waste across all life cycle stages. This would not result in any change in the final disposal and recycling phase and the negative effects are, therefore, negligible. Furthermore, it can be noted that composting is preferred to landfilling, as the waste gets value added. Therefore, composting is more of an “improved” SWM facility in comparison to landfilling and thus the indicator provides clearer insights when looking at the whole system and not just the separate life cycle stages.

The innovation of wheelbarrows and compost sifters is fairly easy to introduce; the costs for the wheelbarrows and compost sifters can be amortized quickly through the sale of compost, possibly also through micro-credits or sponsoring. The difficulty of the innovation lies mainly in the mode of implementation. The concept of compost must be disseminated through educational offers by municipalities and enterprises to create a sales market. This mode of implementation and the potential of these educational offers lie outside the system boundaries drawn here but should be evaluated in further work, as they are a basic prerequisite for the successful introduction of the innovation.

3.3.2. Recommendations for Bishoftu Town

Based on the results, the introduction of the innovation is recommended. The innovation will most likely contribute to the SDGs no poverty (SDG 1), quality education (SDG 4), gender equality (SDG 5), decent work and economic growth (SDG 8), sustainable cities and communities (SDG 11), responsible consumption and production (SDG 12), climate action (SDG 13), and peace, justice, and strong institutions (SDG 16). The results and needed actions are summarized in the following.

• The effectiveness and inclusivity of the MSWMS in Bishoftu Town will be improved as the recycling rate increases and the working conditions for women improve. Women must be actively employed to ensure improved inclusivity;
• The health impacts for the workers at the composting plant might worsen while the health impacts for workers at the landfill might improve. Therefore, safety clothes should be handed out to composting workers to compensate for possible negative health impacts of the innovation;
• The access to improved solid waste management facilities (especially composting) will improve;
• More energy (fuel) is needed for composting, while less energy is needed for landfilling;
• More people must be employed at the composting plant with extended working hours;
• The rate of workers in the recycling stage living under the poverty line might decrease;
• GHG emissions arising from Bishoftu’s MSWMS can be reduced by approximately 5010.91 t CO₂e per year (−15.90% CO₂e/a);
• A decrease in landfilled organic matter is recorded (−9722 t/a);
• Waste generation and C&T are not influenced by the assessed innovation.

There are five main points that are recommended to the municipality and the enterprises of Bishoftu Town to successfully implement the innovation:

• Workers’ salaries in the composting plant must correlate to the working time (e.g., 1500 ETB for 72 h a month increase to 4000 ETB for 192 h a month);
• Safety clothes (e.g., masks, shoes) should be handed out to composting workers to compensate for possible negative health impacts of the innovation;
• Women must actively be employed to improve inclusivity;
• Negative economic impact must be taken into consideration (energy usage). The trade-off between economic, social, and environmental impacts should be considered;
• Data from the informal sector should be collected and assessed in order to find optimization potentials.

In particular, it is essential that the mode of implementation is given special attention, because if compost demand does not increase, the system is too limited for change and positive development is hardly possible. Therefore, it is suggested that educational offers for farmers around Bishoftu Town and other potential compost costumers be created to establish a knowledge base for compost. The municipality as well as the three composting enterprises should be responsible for those programs. The educational offers should present the benefits of compost for the farmers/compost users, such as lower costs compared to chemical fertilizer, local market, and general information on the application and impact of compost, e.g., information on reduced GHG emissions, soil quality, and fertility.

After a knowledge base is set, the compost should be advertised, and a market must be established. This will probably take a while as behavioral change “is a complex issue that needs […] intense stakeholder engagement to achieve success” [71] (p. 142). However, the economic benefits should facilitate the change. When the demand for compost rises, the production must increase simultaneously. Slowly, the utilization rate of the composting plant can be increased, potentially leading to more and more staff needed. The higher staff costs could be offset by higher compost prices and sales.

Once a positive trend in compost demand is noted, the innovation of six compost sifters and six wheelbarrows should be introduced.

4. Discussion

4.1. Strengths of the Methodology

This paper presents the further development of the sustainability assessment methodology by Wang et al. [19] for MSWMSs in SSA. By engaging with stakeholders, the baseline scenario could be described in great detail, the indicator set could be adapted to align with local circumstances and priorities, yet still representing the SDGs, and an adapted and practically feasible innovation could be defined and assessed in accordance with the thematic priorities of the stakeholders. This stakeholder-centric approach enables the method to be tailored in any system and context, particularly in the area of SSA. This is advantageous because the approach does not rely solely on well-established frameworks, such as those from the European Union, or exclusively on LCA indicators. In contrast to the assertion made by Ceraso and Cesaro [21], here, the socio-economic impacts on specific stakeholder groups are not neglected, as they are weighted equally. The provision of questionnaires constituted a streamlined procedure for data collection. Furthermore, the definition of stakeholder involvement facilitated the applicability of the methodology. The methodology was proven to be effective, and it was illustrated that it enables the user to formulate recommendations for decision-makers. It furthermore successfully shows the flexibility of the SDG-based approach and its usefulness for decision support for specific situations beyond standard LCSA mostly focused on industrial contexts and European conditions. The case study applied here, as well as future case studies that apply the methodology, provide a baseline to monitor the assessed innovation and produce ex post studies, which might be helpful for other ex ante sustainability assessments in the MSWM sector. This is particularly important as the number of sustainability assessments of waste management systems in SSA is generally low, and there has not yet been any study specifically on Ethiopia [21].

4.2. Limitations and Outlook

The biggest challenge of the method application in the case study is data availability and data quality as well as the resulting effort for modeling and assessment. This limits the validity of the analysis and the ex ante evaluation, as several assumptions must be made and estimates of the stakeholders were relied on. The practical implementation of the selected and assessed innovation must be discussed with decision-makers in the following course to reconfirm assumptions. Besides, assessing further MSWMSs with the proposed methodology is necessary to build a reliable database for sustainability assessments. For example, data on fuel consumption, GHG emissions from waste management processes in SSA, and particulate matter formation should be compiled to increase the robustness of the assessment results and to address further relevant indicators [72]. In this paper, the decision-making institution is allocated to the municipality; however, there need to be further discussions on the position of local enterprises in this regard.

Furthermore, as the methodology focuses on collecting and using primary data for the baseline scenario, limitations to the data collection process are especially evident when applying the personal interview method. Data collectors must be proficient in the local language, and it is suggested that local researchers conduct such studies. Additionally, in case various researchers conduct the interviews, it is important to note that the interviewers may interpret questions differently and consequentially may provide divergent explanations on the questionnaires. The personal characteristics of the interviewers may also influence the responses of the interviewees (e.g., sex, age, ethnicity), resulting in interviewer bias that influences the outcome [73].

Additionally, a strategy to collect data from the informal sector should be developed to also include informal structures in the system boundaries. Furthermore, the method is limited to municipal solid waste and should be extended to include industrial waste in the future.

The case study shows that potentials outside of the system boundaries must be considered, otherwise great potentials might be left out. Therefore, minor sensitivity analyses should be added to the methodology in case there are foreseeable impacts outside of the system boundaries.

In conducting a holistic sustainability assessment of a waste management system, it is imperative to delineate the scope of analysis meticulously. This is particularly pertinent when the monitoring of the system or a comparison of the assessment results across different systems is anticipated. Typically, the delineation of waste management systems is determined by administrative boundaries [19], yet adjustments to these boundaries require a change of the analysis’ system boundaries. For instance, the planned merging of the municipalities of Dukem and Bishoftu Town, amongst others [74], would necessitate a redefinition of relevant processes, material and energy flows, and stakeholders, within the new MSWMS boundaries. Consequently, the methodology must be flexible to accommodate new boundary conditions and dynamic changes within the system. However, this flexibility also significantly increases the complexity of data collection.

The methodology stipulates that all impact category groups are to be assigned equal weighting, given that all dimensions of sustainability address different stakeholder interests and should thus be regarded as equal components in the sustainability assessment. Nevertheless, to assist stakeholders in making informed decisions, it is recommended to provide supplementary important metrics. These additional metrics are designed to facilitate a more nuanced comprehension of the assessment methodology and enhance the interpretive capacity of decision-makers. To illustrate this point, consider the example of the GWP, where an enhancement in the final disposal phase, accompanied by a decline in recycling (each assigned a score of +1 and −1, respectively), results in no significant change for the whole MSWMS, even though an overall positive impact of the innovation on the MSWMS is projected.

5. Conclusions

The paper describes an ex ante LCSA methodology for waste management systems in SSA emphasizing stakeholder involvement. In particular, local conditions, stakeholder interests, and constraints were incorporated into the analysis and assessment methodology to take into account the relevant characteristics. The methodology includes a set of process descriptions, an adaptable SDG-based indicator set subdivided into impact categories and impact category groups, questionnaires for data collection, as well as assumptions and standard values to systematize and simplify the application.

The developed methodology was applied in a case study in Bishoftu Town, Ethiopia. Following the methodological steps proposed, hotspots and social, economic, and environmental impacts of Bishoftu’s MSWMS could be identified. The assessment of the selected innovation, i.e., the total usage of the composting capacity and introduction of six wheelbarrows and six compost sifters, showed that those technical changes could have an overall mainly positive sustainability impact on the MSWMS. Therefore, the investigated innovation could be recommended to the decision-makers.

Applying the methodology in Bishoftu Town highlights the weaknesses of municipal solid waste management and social, economic, and environmental data gaps in the study area. To improve the application of the methodology and for a more detailed sustainability analysis of MSWMSs in other cities, more research is needed in the fields of questionnaires’ improvement, baseline data in the SSA context, estimations of uncertainties, and the transferability to other SSA MSWMSs.