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Erratum : It has come to the attention of the publisher that the article, Hazen, B.T., Russo, I., Confente, I. and Pellathy, D. (2020), “Supply chain management for circular economy: conceptual framework and research agenda”, published in The International Journal of Logistics Management , Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJLM-12-2019-0332 , contained a number of errors.
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The errors were either introduced during the editorial process or by the authors, but were not corrected prior to publication due to a production error. All errors have now been corrected in the online version. The figures now feature in the respective sections in the body of the article, the further reading section has been removed, figure 4 has now been corrected to show the correct workflow and the reference Zhu et al., 2018 has now been changed to Liu et al., 2018.
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The proposal of an economy that is circular and without the need for material or energy input has an irresistible appeal to those who recognize the precautionary concept of planetary boundaries and acknowledge that resources are limited. Thus, in the public discourse, its narrative outperforms other lines of arguments when it comes to keeping radical critics of destructive extractivism and the growth imperative in check and averting discussion of degrowth, post-growth, or other systemic alternatives by larger segments of the population and government bodies. Moreover, the myth of a circular economy has the additional benefit that it can win over parts of the environmental movement that is apprehensive of radical and transformative change, particularly in the urban milieus of a middle class that enjoys the privileges of the current social order. In this paper, I argue that the circular economy narrative tends to hinder the necessary systemic transformation while entailing a wide range of specific measures that deserve to be recognized for their merit.
Introduction.
Now that the narrative of recycling has lost its luster, the circular economy has become the new buzzword for sustainability advocates. After decades of promoting reuse and recycling, a growing amount of waste ended up feeding into a flourishing recycling industry without tackling the problem of production-associated emissions or increased consumption of raw materials (Alfredsson et al., 2018 ). In contrast, a sustainable and circular economy would allow a progressive reduction in resource input by creating closed loops, guaranteeing the well-being of future generations, while creating jobs and saving energy (Geissdoerfer et al., 2017 ; Stahel, 2016 ). This proposal was also picked up by political actors like the European Commission which framed the circular economy as a regenerative growth model for a sustainable economic system (European Commission, 2020 ), a framework which however has been criticized as inconsistent and imprecise on the ground that it does not reckon with the inability to use natural resources many times over without the need to extract them anew, and thus struggles with a low degree of circularity (Kovacic et al., 2020 ). On the backdrop of unabated man-made climate change (IPCC, 2023 ), deteriorating biodiversity and ecosystem functions (IPBES, 2019 ), and the coming of a new geological epoch termed the Anthropocene to substitute the relative stability of the Holocene (Crutzen and Stoermer, 2000 ; Steffen et al., 2007 ), it must be discussed if the circular economy proposal will entail sufficient transformative change of the existing socioeconomic metabolism which is indispensable to overcome the current conundrum (Krausmann et al., 2018 ). Furthermore, I argue that the apparent logic and beauty of the circular economy concept indeed obfuscates the need for a radical reduction and redistribution of energy (Millward-Hopkins et al., 2020 ) and overall consumption (Wiedmann et al., 2020 ), including the renunciation of continued exploitation of raw materials from formerly colonized geographies (Alcoff, 2022 ) that upholds an unsustainable ‘imperial’ mode of living (Brand et al., 2017 ).
Even if not endorsed by classical economic theory, economic activity operates within the natural environment and is subject to the laws of nature that set limits to human endeavor. Without naming the proposal of a circular economy explicitly, Boulding ( 1966 ) introduced the concept of the Earth System as a closed loop where material entropy that occurs outside of natural processes can only be countered by constant energy input. Yet, under the premises of the Laws of Thermodynamics, the energy contained in a closed system is unchangeable, and irreversible spontaneous processes will increase entropy in the sense of homogeneous distribution of energy or matter to a maximum (Sandler and Woodcock, 2010 ; Starikov, 2021 ). Drawing on these considerations, the economist Nicholas Georgescu-Roegen scrutinized the relevance of the Second Law of Thermodynamics (the Entropy Law) for the economic process and emphasized that it operates on a unidimensional timeline where energy is dissipated and natural resources are depleted, which renders a growth economy, or even a steady-state economy, impossible in the long-term (Georgescu-Roegen, 1971 ).
The ideas of Boulding and Georgescu-Roegen inspired the concept of Degrowth that proposes a radical transformation of the societies in the global North to reduce their ecological metabolism and resource avidity (Bonaiuti, 2018 ; Kallis et al., 2012 , 2018 ; Kerschner, 2010 ). While critics observe that Georgescu-Roegen might have misinterpreted the Second Law of Thermodynamics drawing an improper analogy between the entropy of energy and the entropy of material substance, his work is still a valid contribution to the economic discussion about the theoretical impossibility of full recycling due to the distinction between stocks—non-renewable in any circumstances—and funds which are renewable if exploited at a sufficiently low rate (Khalil, 2004 ).
When Leonardo da Vinci postulated the impossibility of a perpetuum mobile within the physical conditions of planet Earth (Bera, 2021 ), he could not have imagined that a similar concept would be resurrected five centuries later. But the ancient dream of humanity to create an apparatus that would work incessantly without the additional input of human labor, or an external source of energy or material, awoke to new life: the congenial concept of a circular economy promises to transform waste into wealth and to warrant the pursuit of exponential—yet sustainable—economic growth forever. But while the idea of a circular economy has become increasingly popular, it still draws, albeit not explicitly, on prior concepts of industrial ecology and industrial symbiosis that support the sustainable development agenda (Cecchin et al., 2021 ).
Before the industrial revolution set off, global economic activity was almost entirely circular but the advent of mass production and the increasing use of fossil fuels that promoted more effective extraction of other natural resources transformed circularity into a linear process that started to deplete natural resources and created large amounts of waste (Bali Swain and Sweet, 2021 ). More than 50 years ago, the report on the Limits to Growth , commissioned by the Club of Rome and compiled by a team of international scientists at the Massachusetts Institute of Technology (Meadows et al., 1972 ), unmasked the unsustainability of the make-use-dispose process of the linear economy, and it became necessary to create a renewed public perception regarding waste management and resource use (Blomsma and Brennan, 2017 ), if the fundamentals of the capitalist economy were to remain unquestioned. Hence, framing waste as a resource (Zaman, 2022 ) not only created the opportunity for collective action and research, based on an experience of shared ideas and values but also granted the possibility to encompass resource use and waste production within the limits of the current economic system.
Scrutinizing the circular economy and conceptualizing it as an umbrella concept that connects previously unrelated constructs to create a new paradigm, can create an understanding of its consolidation as a new narrative that is characterized by continuing to branch out and becoming more and more complex over time (Blomsma and Brennan, 2017 ). As Hirsch and Levin ( 1999 ) point out, an umbrella construct can be particularly useful in fields that lack a solid theoretical background but where its validity tends to be less challenged by a nonacademic constituency. Understanding the circular economy as an umbrella concept could therefore contribute to decoding the popularity of the circular economy proposal, despite its shortcomings and inconsistencies that have been detailed.
In their revision of the circular economy concept, Kirchherr et al. ( 2017 ) mustered a plethora of 114 definitions which in itself illustrates its heterogeneity and the need to resort to frameworks like the umbrella concept to maintain the notion of a coherent explanatory model. After an iterative coding process that embraced 17 dimensions, the authors came up with a definition of the circular economy as “ an economic system that is based on business models which replace the ‘end-of-life’ concept with reducing, alternatively reusing, recycling and recovering materials in production/distribution and consumption processes, thus operating at the micro level (products, companies, consumers), meso level (eco-industrial parks) and macro level (city, region, nation and beyond), with the aim to accomplish sustainable development, which implies creating environmental quality, economic prosperity and social equity, to the benefit of current and future generations ” (Kirchherr et al., 2017 : pp. 224–225). Additionally, they underscored the necessity of renouncing subverted definitions of the circular economy that are mostly framed as a path to economic prosperity and are pushing the social and environmental goals into the background while not recognizing ‘Reduce’ as a top priority to surpass only incremental improvements and to bring about effective and transformative change. Indeed, only three of the 114 definitions that were analyzed entail all elements of the final definition. Consequently, the imperative of reduction clashes with the business models of the real economy that are built on the pursuit of growth and profit, within the framework of the capitalist market economy, thus hampering the ‘strong’ sufficiency practices that would be in line with the comprehensive definition of a circular economy that Kirchherr et al. ( 2017 ) bring forward. This dilemma is unscored by a study in a sample of 150 companies that proactively communicate their commitment to sustainability and sufficiency but refrain from actually encouraging the refusal to consume (Bocken et al., 2022 ).
Even if acknowledging the concept of a circular economy as a useful contribution towards socioeconomic system change, measuring the effective reduction of environmental and social damage that it promotes must be tackled, particularly when excessive resource use is not adequately priced and does not include additional future costs of current resource extraction (Stephan, 2022 ). Considering that the main strategies for implementing a circular economy include the preservation of the product itself and its function, retrieval of its components, and the recovery of embodied materials and energy, a framework of indicators to embrace these dimensions might consider operating under the concept of Life Cycle Thinking to analyze potential (present and future) impacts and the overall burden or benefit for the environment in comparison to linear processes (Moraga et al., 2019 ). However, reports on interventions at different levels (micro, meso, and macro) do generally not consider the ‘use phase’ of the life cycle and information on systemic interactions between interventions on different levels is scarce which is particularly unfortunate as the results of interventions on the product level can foster large and unintended rebound effects on the societal or macro level (Makov and Vivanco, 2018 ).
The concept of planetary boundaries aims to define precautionary safeguards for the functioning of the Earth system that should not be surpassed without setting off the risk of abrupt and non-linear environmental shifts that endanger and threaten the safe operating space for humanity (Rockström et al., 2009 ). Currently, possibly six out of nine planetary boundaries have been breached, including biosphere integrity and climate change (Richardson et al., 2023 ), which is consistent with the warnings on the rapid deterioration of biodiversity and ecosystem function by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES, 2019 ) and the 2023 Synthesis Report on Climate Change by the Intergovernmental Panel on Climate Change (IPCC, 2023 ) that alerts on the effects of human-caused climate change on weather and climate extremes which will continue to intensify.
While socioeconomic and (unfavorable) Earth Systems trends have been accelerating since the industrial revolution, mainly due to the activity of OECD countries and, more recently, due to the emerging economies of the so-called BRICS countries, including Brazil, Russia, India, China and South Africa (Steffen et al., 2015 ), the General Assembly of the United Nations approved the 2030 Agenda for Sustainable Development (United Nations, 2015 ), comprising 17 Sustainable Development Goals (SDGs) and 169 targets. Also, the “New Circular Economy Action Plan for a cleaner and more competitive Europe”, that was adopted by the European Commission to accelerate the transformations required by the European Green Deal (European Commission, 2020 ) refers explicitly to the Agenda for Sustainable Development. Yet, in both documents, the notion of sustainability remains rather vague and undefined, being “sustainable” mostly used as an axiomatic justification for policy proposals and goals otherwise deemed desirable such as, for instance, poverty eradication, food security, or economic growth.
Also, seemingly unambiguous definitions of sustainable systems as something that survives or persists (Costanza and Patten, 1995 ) do not give real meaning to the concept as long as they leave out other dimensions of sustainability such as time, space, or scope. Following Salas‐Zapata and Ortiz‐Muñoz ( 2019 ), the purposes and meanings that can be ascribed to sustainability include (1) a set of social‐ecological criteria that guide human action, (2) a vision of humankind that is realized through the convergence of the social and ecological objectives of a particular reference system, (3) an object, thing or phenomenon that happens in certain social‐ecological systems, or (4) an approach that entails the incorporation of social and ecological variables into the study of an activity, process or human product (Salas‐Zapata and Ortiz‐Muñoz, 2019 : p. 159). The scope of sustainability might therefore be delimited at the level of values (1) and at the macro (2), meso (3), and micro (4) levels. But additionally, the time horizon can be either short (election cycle), medium (lifetime of current generations), or long-term (future generations), while the spatial scale is local, regional, or global. Thus, only using a definition of ‘strong’ sustainability (Spash, 2017 ) that encompasses a comprehensive scope of social-ecological values and systems on a long-term and global scale shall be consistent with the need for guaranteeing a safe operating space for humanity that is faced with challenges such as climate (in)stability, biodiversity loss, or the endangered balance of the Earth system.
Critics of the concept of sustainable development point out that even apparent progress toward its goals generally conceals ongoing environmental devastation (Bendell, 2022 ; Zeng et al., 2020 ). Furthermore, the aim of ensuring sustainable consumption and production patterns (SDG 12) seems impossible to attain without effectively reducing production and consumption instead of relying on increased efficiency (which has well-known rebound effects), while the pursuit of economic growth (SDG 8) actually hinders the accomplishment of SDG 12 (Bengtsson et al., 2018 ). Analyzing the impact of economic growth (SDG 8) on resource consumption Hickel ( 2019 ) emphasized that (any) GDP growth would require the decoupling of resource use at a far superior rate than has been achieved historically to effectively reduce the global material footprint (Parrique et al., 2019 ; Tilsted et al., 2021 ; Ward et al., 2016 ). Following a similar line of argument in her critique of SDG 8 that is based on the unsustainability of economic growth, Chertkovskaya ( 2023 ) proposes a reframing of the sustainable development agenda into a well-being agenda where human well-being and the need to reduce resource throughput could inform the envisioned socio-ecological transformation.
Besides the antagonism between SDG 8 and 12, in complex dynamic systems like the Sustainable Development Agenda where policies towards a specific goal act on the capacity to accomplish others, it may be expected that these effects are detrimental and create undesirable tradeoffs (Kroll et al., 2019 ), or even induce unwanted feedback loops, in particular when those goals that would reduce human impact on the Earth system are not prioritized within the framework (Skene, 2021 ). Supporting this observation, a system-based analysis of local and national policies in Brazil that were informed by the concept of sustainable development concluded that the results were at least inconsistent, both on the economic and the ecological level, while only social goals were (partially) achieved (Donaires et al., 2019 ).
A reality check on the circularity of the global economy shows that currently only 8.6% can be considered circular, down from 9.1% just two years before, while global material consumption exceeded for the first time 100 Gt of raw materials in 2019, up from 28.6 Gt in 1972 when the Club of Rome’s report on the Limits to Growth was first published (Circle Economy, 2022 ). Hence, overall material consumption roughly quadrupled while the world population doubled during the same period (Worldometers.info, 2022 ) and thus decoupled from population growth, a trend that has been observed for more than a hundred years (Marín-Beltrán et al., 2022 ). Furthermore, the circular economy does not necessarily lead to a reduction in the use of critical primary raw materials because a shift to different raw materials elsewhere in the life cycle can be observed (Schaubroeck, 2020 ). In this context, the World Bank Group recognizes that by 2050 the transition to purportedly renewable energy production will require over 3 billion tons of minerals and metals, notably graphite, lithium, and cobalt, corresponding to an increase of up to 500%, to stay within the climate goals of the Paris Agreement, while in regard to suitable minerals like copper and aluminum even doubling the rate of recycling would not meet demand (Hund et al., 2020 ).
Ageing material stocks accumulated in buildings, infrastructure, and machinery, which have increased 23-fold since the beginning of the 20th century and continue to grow, represent another challenge for the circular economy concept and require continuous energy and material flows for maintenance, dismantling, and (re)construction with a current recycling rate of just 12%, and an anticipated need for disposal of 35% over the period from 2010 to 2030 due to the end of their service lifetimes (Krausmann et al., 2017 ). Against this backdrop, only a substantially lower level of material stocks would allow achieving a global reduction in greenhouse gas emissions to keep global warming at bay (Krausmann et al., 2020 ). Thus, circularity must be combined with the concept of longevity to overcome inherent limitations and address material turnover, in an effort to increase eco-efficient resource use (Figge et al., 2018 ), while rebound effects due to efficiency gains need to be addressed comprehensively (Zink and Geyer, 2017 ). Moreover, the attempt to avoid landfill within the European Union and to comply with the goal of a circular economy often displaces the treatment of waste towards the global South, feeding into international recycling networks that burden people and environments with cleaning up a problem that they did not cause (Gregson et al., 2015 ).
Overall, critical reviews of the circular economy point out the flaws of definition and the uncertain overall results, but also the neglect of established knowledge and issues of feasibility, including the limitations due to unaccounted secondary energy and material input due to inefficient limited repurposing or recycling potential (Corvellec et al., 2022 ; Cullen, 2017 ). But, additionally, the underlying “ideological agenda” that includes the emphasis on entrepreneurship, business models, and the infinite possibility of technical solutions also derives its strength from the seductive appeal of the circle as the archetype of perfection and completeness, thus turning the metaphor mythical and irresistible (Corvellec et al., 2022 ).
The umbrella concept of the circular economy relates closely to the concept of lifestyle in high-income countries of the global North. As laid out by Mikael Jensen ( 2007 ), the concept of lifestyle can be defined on four levels, from global to individual, and entails the notion of consumer identity which, besides the manifestations of national, cultural, and subcultural identities, expresses identity on an individual level through the process and type of material consumption. Products perceived as environmentally friendly and fairly traded embody a message of ethical concern and humanitarian consciousness and consumers associate them with a positive moral value that allows to dress up consumption as pro-environmental behavior. Hence, environmentally concerned people tend to achieve self-realization through “green” consumption patterns but don’t forego necessarily consumption and resource use itself, focusing instead on measures that are promoted within the concept of a circular economy, like (zero-)waste and recycling, to maintain consistent personal narratives (Connolly and Prothero, 2003 ) or to enhance their positional value in the peer community (Kesenheimer and Greitemeyer, 2021 ). As emphasized by Lorek and Fuchs ( 2019 ), this type of ‘weak’ sustainable consumption represents foremostly purchasable efficiency gains that are available to affluent consumers and occur without effective environmental gains, an observation that is also supported by Moser and Kleinhückelkotten ( 2018 ). On the contrary, ‘strong’ sustainable consumption requires embracing sufficiency and the reduction of overall consumption in high-consuming classes which could grant a dignified life for all and replace the growth paradigm (Sandberg, 2021 ; Sandberg et al., 2019 ).
Indeed, higher household income is closely associated with a greater ecological footprint (Adua, 2022 ; Alfredsson et al., 2018 ; Feng et al., 2021 ; Hardadi et al., 2021 ) and individual environmental concerns and pro-environmental behavior in the private sphere do not necessarily reduce household carbon footprint (Csutora, 2012 ; Huddart Kennedy et al., 2015 ). Thus, the example of air travel, which represents a major share of individual greenhouse gas emissions, particularly in high-income urban populations (Czepkiewicz et al., 2019 ; Ivanova et al., 2020 ) and is rarely relinquished, demonstrates that even people with internalized knowledge about climate change show a large gap between attitude and practice (Jacobson et al., 2020 ). This finding is supported by the analysis of representative datasets of the UK population which also showed no association between pro-environmental values and concerns and the reduction of non-work-related flying behavior (Alcock et al., 2017 ).
The apparent inconsistencies between pro-environmentalism, “green” lifestyle, and environmentally harmful habits like travel patterns with high climate impact seem difficult to explain at first glance. However, alongside denial mechanisms that are similar to those that erect psychological barriers to shifting from material comfort to a low-energy behavior (Stoll-Kleemann et al., 2001 ), moral disengagement triggered by aggressive advertising of long-distance travel contributes to the blanketing out of its climate effects (Stubenvoll and Neureiter, 2021 ). Additionally, the effect of moral licensing may further enable the denial of existing contradictions between material and energy consumption, associated greenhouse gas emissions, and the narrative of a sustainable circular economy. In moral psychology, ethical behavior is closely linked to the self-perceived value of moral acts that interfere with self-interest. But while past transgressions increase the resolve to engage in ethical behavior, the boost to the moral self after acting ethically can provoke subsequent licensing of egoistic and unethical attitudes, particularly when there is a conflict between self-interest and an abstract value or goal, or self-construal is based on social roles and relationships (Blanken et al., 2015 ; Mullen and Monin, 2016 ; Xiong et al., 2023 ).
Under the assumption that purchasing environmentally friendly products might prompt subsequent unethical behavior, Mazar and Zhong ( 2010 ) studied the effect of moral licensing in an experimental study on Canadian students that showed a positive association between the prospect of green consumption and high moral and social values. However, while the mere exposure to environmental-friendly products had a favorable effect on altruistic behavior, the actual purchase of these products led to a decrease in altruistic behavior and even to clearly unethical conduct. In a similar study on the potential of behavior change initiatives and policies to increase overall pro-environmental behavior (positive spillover), Clot et al. ( 2022 ) studied the effect of ”green licensing” in a group of 85 undergraduates at a UK university and concluded that licensing actually provoked a negative spillover and worse pro-environmental behavior in other domains. Additionally, engaging in moral licensing can contribute significantly to the rebound effect that is observed after efficiency gains through technological improvements, in particular regarding heating and mobility, thus expanding on a mere economic explanation of rebound (Dorner, 2019 ; Dütschke et al., 2018 ).
Complementing this argument within a larger moral self-regulation framework, Shalvi et al. ( 2015 ) emphasize that self-serving justifications act in protection of the moral self, either in advance of intentional unethical behavior, resorting to mechanisms of ambiguity, self-serving altruism, and moral licensing, or afterward, using physical or symbolic cleansing, partial confessing, and distancing with pointing to others’ moral failures. Thus, in analogy, the peril of the circular economy narrative lies in its apparent logical serenity and opportune resolution of the psychological intricacies that characterize the conflict between ‘green lifestyles’, enacted pro-environmentalism, and engrained consumption patterns, while its mainstream meanderings refrain from substantially transforming the growth economy.
The concept of zero-waste, recycling, and a circular economy does not only operate on an individual level to justify unsustainable consumption patterns but can also be understood as an attempt to render the challenging of industrial capitalism impossible, removing it from the political sphere towards a depoliticized question of consumer behavior (Valenzuela and Böhm, 2017 ). But even when consumers turn to recycling fetishism, in a symbolic effort of redemption that suppresses the acknowledgment of wasteful behavior and intends to obtain moral permission for future consumption, the cleaves and cracks of the current global socioeconomic system become visible. Hothouse Earth pathways loom on the horizon (Steffen et al., 2018 ) and disruptive behaviors of the Earth system are not science fiction anymore but a real prospect (Bernardini et al., 2022 ). The call for environmental justice and decolonization can no longer be ignored (Sultana, 2023 ) and resounds with proposals for a degrowth future in the global North (Singh, 2019 ; Sultana, 2023 ). Thus, “ideas such as those of subsistence-living, the balance between all living beings and reciprocity, self-sufficiency, and self-reliance open the possibility for debates in which both sets of movements can contribute”, thus co-creating convivial technologies and alternative economic systems that refuse neoliberal growth narratives (Rodríguez-Labajos et al., 2019 : p. 182). Moreover, the current social and ecological crises require imagining “other ways of being, and transformative change to our economic life”, where “the social body, with a shared commitment to life in common, is a common goal that unites diverse struggles, including environmental justice and degrowth movements. The success of these diverse struggles in fostering collective subjectivity and postcapitalist alternatives will depend on the ability of these diverse movements to come together, stand in solidarity, learn from each other, and tell alternate stories about how we are to live the Anthropocene” (Singh 2019 : p. 141).
Natalie Ralph’s proposal of conceptual merging of circular economy, degrowth and conviviality design approaches might represent a first step in the direction of circular futures while reappropriating the idea of a circular economy for a framework that embraces local sourcing of raw materials, the possibility of local manufacturing, and the inclusion of users’ creativity in the design process, thus creating products that fulfill an effective need and not an artificially induced desire, are widely accessible, contribute to future sharing and learning, and can be modified or improved without restriction during an extended life cycle and repaired by an average person (Ralph, 2021 ). This proposal, however, requires engaging in a participated policy process which is critical to achieve indispensable popular support (Kongshøj, 2023 ) and will be characterized by the need to address complex problems within the uncertainties of post-normal science where decision stakes are high (Funtowicz and Ravetz, 1994 ). Hence, a circular economy discourse that aims to reach beyond variations of the R’s of waste management and resource use will necessarily have to embrace systemic socio-ecological transformation and a “plurality of alternatives” to envision participated circular futures (Calisto Friant et al., 2020 ). Alongside the acknowledgment of planetary boundaries, the formulation of societal boundaries is mandatory to enable a fair and conscious decision process that creates the conditions for a good life for all within a framework of collective self-limitation which overcomes the imperial mode of living at the expense of others (Brand et al., 2021 ).
The transformation of social structures that allows us to envision a future that entails elements of the circular economy without succumbing to its vicissitudes will possibly require the shift from market relations to human relations, within a framework of “intentional sharing and togetherness” (Jarvis 2019 : p. 270). Renouncing explicitly the idea of a consumption-orientated sharing economy, Jarvis puts forward a concept of “real places and co-present realities” that might occur in collective endeavors like co-housing or food cooperatives which, in turn, shape relational human values. This framework entails individual agency, collective intentionality and ‘we-intentions’, participatory democratic procedures, and the defense of ecosystems and ideals of social justice within practices inspired by the degrowth mindset, understood as a “radical niche innovation” to counter the dynamics of growth capitalism and to create diverse—pluriversal—pathways towards alternative practices and systemic change (Kothari et al., 2019 ; Vandeventer et al., 2019 ).
The amazing diversity of circular economy definitions seems to allow picking and choosing those that are most suited to one’s preferences and particular circumstances, without changing the dynamics of the industrial growth economy or demanding radical individual and systemic transformation. Thus, the utopia of circularity apparently sanctions the maintenance of privileged habits of conspicuous consumption, within a framework of green lifestyles and pro-environmental behaviors, to end up reinforcing the status quo of unsustainable exploitation of the Earth’s resources while only a small—and diminishing—fraction of materials is reused or recycled, and global consumption continues unabated. Psychological mechanisms like moral licensing can hinder transformative behavioral change even in groups that exhibit high moral standards and acknowledge the predicament of the destruction of the biosphere, particularly when its members enjoy the economic privileges that entitle them to an environmentally destructive lifestyle. In contrast, ‘strong’ sustainability and an all-embracing circular economy require prioritizing ‘Reduce’ without losing sight of social and environmental justice. Thus, without a paradigm shift in overall societal goals from economic growth towards sustainable and regenerative practices, the current conflict between self-interest, interwoven with dominating societal norms, and consistent pro-environmental behavior remains irresoluble, except in fringe groups that operate outside of the mainstream society and either are driven by strong moral values or bound to vernacular lifestyles that are directly threatened by the industrial growth economy.
Data sharing is not applicable to this research as no data was generated or analyzed.
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Waste management is the main challenge in the transition away from the linear "take-make-dispose" economy. Incorporating the principles of circularity in waste management would facilitate the achievement of Sustainable Development Goals. This paper aims to provide state-of-the-art research about circular waste management in the fulfillment of the 2030 Agenda. For this purpose, bibliometric analysis by VOSviewer and SciMat software is used to define the evolution and to detect research trends. Based on the main gaps identified in studies, a research agenda to guide for further opportunities in this field is suggested. The results obtained four clusters that address sustainable industrial infrastructure, biological waste management, recycling in developing countries and recovery processes. Four research propositions are established, focusing on plastic waste management and generation trends, circular municipal waste management, more sustainable landfill management, and enablers such as indicators and legislation. The transformation towards more bio and ecological models requires social, regulatory and organizational tools that consider the best interests and capacity of companies, public authorities and consumers. In addition, policy implications are considered.
Circular economy (CE) is a regenerative and restorative system, which allows the conservation of the value of raw materials by breaking with the concept of end-of-life of products, minimizing waste and emissions and increasing efficiency, through recycling, reusing, and remanufacturing, among others (Ellen MacArthur Foundation 2017 ). This paradigm represents a further step towards sustainability supported by its three fundamental pillars—economic, environmental and social sustainability (Muñoz-Torres et al. 2018 ). The circular system is based on the principle of material balance, seeking regeneration of natural systems, which implies the minimisation of waste and pollution. In this way, changes already begin to emerge in the design phase (Foschi et al. 2021 ) and go beyond the production system, reaching the development of new patterns of consumption and use by maintaining or reusing products and materials (Vanapalli et al. 2021 ). From an environmental economics point of view, it implies that all material or waste streams must be considered (Andersen 2007 ). Products have a longer lifetime, new applications and are reintroduced into the production system, closing the loop. The social aspect is fundamental to this, and coordination and cooperation with suppliers and customers must be facilitated (Martín Martín et al. 2022 ). In addition, making this new paradigm shift requires a new behavioural and cultural framework.
Waste management involves the transportation, collection, processing, disposal or recycling of waste materials, originating from industries, manufacturing processes and municipal solid waste. This process or system presents one of the main challenges in the transition towards circular business models (Smol et al. 2020 ). CE involves a waste management system that combines changes in the entire supply chain (Johansen et al. 2022 ), from designers and choice of materials to operators and recycling issues (Salmenpera et al. 2021 ).
Circular waste management comprises both the reduction in the generation of residual and household waste, but also the reintroduction of these wastes back into the production system. This reduction is achieved through the eco-design of products, by reducing waste generated in transport, by conserving material value through recycling and by achieving a longer lifetime of products (Salmenpera et al. 2021 ). Once the waste has been generated, it must be incorporated into the production system from the CE, either by using parts or as a source of energy through the reintroduction of biological waste, thus closing the material flow cycle (Zeller et al. 2019 ).
Although interest in waste management research, applying the principles of circularity, is growing, it is necessary to know state-of-the-art research trends in this area. Previous bibliometric or analytical method studies have analysed the relationship between “circularity and “waste” or “waste management” but from a different perspective to the research conducted. Recent studies have provided a qualitative view of the relationship but from very specific aspects -considering a type of waste, a geographical area or time period or one of the dimensions of sustainability-. Some research focuses on one type of waste such as Tsai et al. ( 2020 ) who analyse the link between municipal solid waste and the circular economy or Sundar et al. ( 2023 ) who examine e-waste. Ranjbari et al. ( 2021 ) examines the application of circularity in waste management, including the “closed loop” concept, up to 2020. Circular economy and closed-loop material cycles are deeply connected; however, the concept of closed-loop material cycles arose with the beginning of industrialization (Kara et al. 2022 ). Negrete‑Cardoso et al. ( 2022 ) considers “circular economy” to be related to “waste” and its impact on the post-Covid period. Chioatto and Sospiro ( 2023 ) discuss European economic policy issues that have promoted waste management from a circularity perspective. From a systematic literature review approach Di Vaio et al. ( 2023 ) analyse the accountability and management accounting practices of waste management related to the circular economy.
Our study presents three differentiating contributions with respect to previous studies. Firstly, we focused specifically on “circular economy” and “waste management” from a holistic perspective considering environmental, economic and social aspects. Secondly, by considering the year 2021 in the period under study, this includes one of the years with the most research on the effect of COVID-19 on waste management. The unprecedented increase of waste generated by this pandemic requires further research to enable the construction of a comprehensive circular economy model (Ranjbari et al. 2023 ). Thirdly, we established a relationship between our results and their contribution to the fulfilment of the 2030 Agenda. Although previous work has recognised the contribution of circular waste management to the 2030 Agenda (Di Vaio et al. 2023 ), a full analysis of the contribution of research by specific targets has not been carried out. Further than considering the main topics of the 2030 Agenda in the different clusters obtained, this paper establishes the relationship between the Sustainable Global Goals (SDGs) associated with waste management and the different research streams found.
The purpose of this study is to provide state-of-the-art research on the relationship between circular economy and waste management. This bibliometric analysis examines the historical evolution of research and identifies trending themes to uncover the conceptual building blocks of this field. Moreover, is setting out a research agenda about future opportunities for practitioners, policymakers, and researchers. This paper contributes to filling the existing gap on scientific literature for guiding research in the implementation of circular waste management, which is fundamental to achieving the goals outlined in the 2030 Agenda. Hence, considering the current scientific literature, we propose the following research questions:
The paper is divided as follows: following the introduction, the literature overiew on waste management and 2030 Agenda is covered, then the methodology section is presented, describing the different phases of the process. The bibliometric results are exposed as productivity measures, considering the historical evolution of documents published in the field of waste management and circular economy and the most representative journals by authors sorted by institution, country, number of documents published and total citations. Through co-occurrence analysis, using VOSviewer software and SciMat software which displays strategic diagrams and clusters with the main motor, research topic trends in the field were identified whether basic, emerging or disappearing, and developed or isolated themes. Finally, discussions and conclusions within a research agenda are presented.
Waste generation has increased significantly in recent years in relation to consumer patterns, activities and lifestyles. Therefore, waste management is of great environmental value (Martín Martín et al. 2022 ). Inappropriate waste generation has negative environmental, social and economic impacts in terms of damage to biodiversity and pollution, human health problems and the costs involved, respectively. Coping with the costs of environmental and social impacts must be considered worse than developing new and more efficient waste management systems (Sharma et al. 2021 ). To reduce these negative effects, the introduction of sustainable and circular issues to manage waste generation, and the collection of waste throughout the life cycle of products is required (Tsai et al. 2021 ). This need has been accentuated by recent crises in areas such as health, safety and energy during 2021 and 2022 (Vanapalli et al. 2021 ; Gatto 2022 ; Mišík 2022 ). However, these adverse historical events provide an opportunity for reflection, forcing governments and businesses to promote long overdue energy and ecological transition policies and practices (Gatto 2022 ; Mišík 2022 ). Given the need to consolidate this trend, the implementation of circularity enhances sustainability and requires a new vision in waste management (Minoja and Romano 2021 ).
In 2015 the United Nations adopted Agenda 2030 as a roadmap to achieving higher levels of sustainability, striving towards satisfying its 17 Sustainable Development Goals (SDGs) with the commitment of public actors, industry and society (Schulze et al. 2022 ). Several theories have been used in the literature to analyse these SDGs. Resource-based theory regarding natural resources is widely studied to examine waste practices that protect the environment (Agyabeng-Mensah et al. 2021 ). Due to the environmental impacts, some of the theories focus on pro-environmental attitudes and behaviour, such as social-practice theory (Munir 2022 ) and the theory of planned behaviour (Goh and Jie 2019 ). Regarding the association between SDGs and supply chains, a redesign towards sustainable practices is required. Transactions and economics theory have highlighted the need for changes to the decision-making process during production cycle stages to achieve sustainability goals. In addition, stakeholder and agency theories enable the achievement of SDGs, since both the collaboration and the alignment of interests in fulfilling the 2030 Agenda are required (Agrawal et al. 2022 ).
The relationship between waste management and the 2030 Agenda is closely linked, as it affects many SDGs. It is therefore essential that this relationship be studied. According to SDG 2, the listed items of: ‘end hunger, achieve food security, improved nutrition and promote sustainable agriculture’ require, among other factors, the minimisation of food loss and food waste to achieve efficient and sustainable agricultural production. Similarly, factors such as increasing food availability or achieving more resilient food systems would facilitate this goal (Wieben 2016 ). SDG 3, ‘Ensure healthy lives and promote well-being for all at all ages’, in order to reduce illness linked to water, pollution and hazardous chemicals by means of smart waste management (Fatimah et al. 2020 ). SDG 6 ‘ensure access to water and sanitation for all’ aims to reduce the percentage of untreated wastewater and increase recycling and reuse (Tortajada 2020 ). SDG 7 ‘ensure access to affordable, reliable, sustainable and modern energy’ proposes increasing the use of renewable energy and facilitating access to research on clean energy, including renewable sources (Taifouris and Martín 2023 ). SDG 9 ‘build resilient infrastructure, promote sustainable industrialisation and foster innovation’ advocates for the modernisation and conversion of industries towards cleaner and more sustainable models as they are required to use resources more efficiently and rationally (Dantas et al. 2021 ). SDG 11 ‘make cities and human settlements inclusive, safe, resilient and sustainable’ focuses on building more sustainable cities, with particular attention to air quality and municipal and other waste management. This also implies resource efficiency and waste generation-collection services (Sharma et al. 2021 ). SDG 12, ‘ensure sustainable consumption and production patterns’ seeks to achieve the sustainable management and efficient use of natural resources. This goal emphasises the importance of reducing different types of waste throughout the life cycle of a product or service through prevention, reduction, recycling and reuse activities (Principato et al. 2019 ). With regard to agro-food waste, a reduction of both food losses and food waste in the production and supply chains is proposed. SDG 13, ‘take urgent action to combat climate change and its impacts’, can affect waste treatments relevant to their environmental impact through using greener and cleaner technologies, such as anaerobic digestion (Kakadellis et al. 2021 ). SDG 14, ‘conserve and sustainably use the oceans, seas and marine resources’ is also linked to plastic waste management, according to marine pollution minimisation. SDG 15, ‘sustainably manage forests, combat desertification, halt and reverse land degradation, halt biodiversity loss’ can be mitigated by protection and restoration, avoiding landfill waste. Finally, SDG 17 ‘revitalise the global partnership for sustainable development’, can be enhanced owing to waste treatment development, enabled by new treatments technologies (Sharma et al. 2021 ).
SDGs achievement is a priority and takes on even greater importance considering the fact that eight years prior to the deadline set in the 2030 Agenda, some reports show that we are still far from meeting most of the goals. The Food and Agriculture Organisation (FAO) estimates that around 35% of employment is a direct result of food systems and the promotion and implementation of sustainable practices in the food system -including food waste and loss- which is still low, referring to unfulfilled SDG 2 (Torero 2020 ). Uncollected waste is one of the major issues. In terms of municipal solid waste management, proper collection is key, as mismanagement of these services can lead to dumping into waters, which directly affects SDG 6 achievement (Sharma et al. 2021 ). To enable both sustainable energy and industrialisation a transition towards the use of renewable and cleaner energy is necessary. Waste can be adopted as an energy resource, such as biomass waste and pyrolysis (Moya et al. 2017 ). However, fossil fuels are still strongly present in several industries, which negatively impact on SDG 7, 9 and 11. Waste management systems’ disruptions in relation to current situations -COVID-19 pandemic and supply crisis- have minimised recovery and recycling activity. For instance, the plastic waste proliferation caused by the pandemic resulted in both water and air pollution, due to poor and non-effective waste management. Thus, SDG 12, 13 and 14 premises are failing (Sharma et al. 2021 ). This also adversely affects halting biodiversity loss and the land degradation (SDG 15). In addition, there are advances in waste treatment thanks to new technologies which are starting to be implemented. For instance, anaerobic digestion and waste-to-energy technologies (Moya et al. 2017 ), but their application is still scarce, not satisfying SDG 17. Consequently, there is an urgent need to take additional measures to facilitate the implementation of the various sustainable measures included in the plan.
This study combines a bibliometric analysis carried out by VOSviewer and SciMat software, and an in-depth literature review of the articles published during the year 2021. Figure 1 shows the phases of this work: Phase 1) data collection, phase 2) bibliometric analysis, and phase 3) systematic literature review and research agenda.
Methodological process
In the first phase, documents from the Web of Science Core Collection database were collected from the period 2009 up to September 2021. The keywords used were ‘circular economy’ and ‘waste management’. This generated a total of 1.395 papers. Then, it was selected articles by topic, which includes title, abstract and authors’ keywords. retrieving 966 documents. Thereafter, we sorted the data into groups of Social Sciences Citation Index, Science Citation Index Expanded, Arts and Humanities Citation Index, taking only articles into consideration, reaching a total sample of 576 articles that were extracted and including in this analysis after a double checked in order to eliminate inconsistences.
Bibliometric methodology identifies research trends providing the knowledge structure about a specific field. By examining recent published articles, network analysis shows emerging fields (Hettiarachchi et al. 2022 ). In the second phase, bibliometric approach was performed using VOSviewer and SciMat software to understand the latest trends in the fields of waste management and circular economy. VOSviewer is more visual and allows for the examination of co-occurrence, analysis of authors, institutions and countries (Van Eck and Waltman 2010 ). In this paper, SciMat completes VOSviewer analysis since it carries out the co-occurrence analysis in time periods and the evolution of these periods can be seen on an evolution map. Additionally, SciMat illustrates strategic diagrams which uncover the main research themes (Cobo et al. 2012 ). Furthermore, it allows one to observe the clusters of each keyword, making the analysis more complete and comprehensive.
Following on from this, VOSviewer conducts a citation analysis of the most representative journals and the most prolific authors and from here, a co-occurrence analysis is displayed. Via the SciMat tool a co-word analysis is also developed, displaying the strategic diagrams and clusters with relevant keywords, divided up into three periods according to the number of documents published, years 2009–2019 (Period 1), 2020 (Period 2) and 2021 (Period 3).
In the third and last phase, a literature review of the articles related to circular economy and waste management is carried out, in accordance with 51 documents from the motor themes of the SciMat analysis in the third period, during the year 2021, to determine the latest trends and research in the field. Finally, a research agenda is exposed regarding trending topics analysed in this work.
Figure 2 shows the historical evolution of documents published in the field of waste management and circular economy from 2009 to September 2021, considering a total sample of 576 articles. Waste management towards circularity is gaining momentum in academia according to the number of documents published in the field since 2015, coinciding with ‘The 2030 Agenda for Sustainable Development’ (United Nations 2015 ). In addition, other European strategies and legislative challenges took place, such as ‘Communication on closing the loop. An EU action plan for the Circular Economy’ (European Commission 2015 ) and ‘Communication on a monitoring framework for the Circular Economy’ (European Commission 2018 ) considering waste management as one of the main challenges in the transition to circular business models.
Historical evolution of publications in the field of waste management and circular economy
Table Table1 1 shows the ten most representative journals sorted by number of total documents published and citations. These journals represent 60,25% of the total sample formed by 132 sources. The Journal of Cleaner Production is the most influential with 79 articles published in the field of circular economy and waste management, and a total of 1.343 cites. It should be noted that almost all sources belong to the "environmental sciences" category. None of the most cited journals belong to the social sciences.
Most representative journals and authors’ institution and countries sorted by number of documents and total number of citations
( ) | ||||||||||||
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N | % | N | % | |||||||||
Journal of Cleaner Production | 11.072 Q1 (24/279) | Environmental Sciences | 79 | 13,72% | 1343 | Ferronato, N | Italy | University of Insubria | 9 | 1,56% | 129 | 11 |
Sustainability | 3.889 Q2 (57/127) | Environmental Studies | 77 | 13,37% | 445 | Torretta, V | Italy | University of Insubria | 8 | 1,39% | 129 | 31 |
Waste Management | 8.816 Q1 (36/279) | Environmental Sciences | 50 | 8,68% | 658 | Somplak, R | Czech Republic | BRNO University of Technology | 8 | 1,39% | 33 | 12 |
Resources, Conservation and Recycling | 13.716 Q1 (12/279) | Environmental Sciences | 43 | 7,47% | 862 | Smol, M | Poland | AGH University of Science and Technology | 6 | 1,04% | 92 | 18 |
Waste Management & Research | 4.432 Q2 (107/279) | Environmental Sciences | 26 | 4,51% | 143 | Azapagic, A | United Kingdom | University of Manchester | 5 | 0,87% | 156 | 60 |
Science of the Total Environment | 10.753 Q1 (26/279) | Environmental Sciences | 23 | 3,99% | 474 | Zorpas, A. A | Cyprus | Open University of Cyprus | 5 | 0,87% | 67 | 31 |
Journal of Environmental Management | 8.910 Q1 (34/279) | Environmental Sciences | 14 | 2,43% | 269 | Ragazzi, M | Italy | University of Trento | 4 | 0,69% | 106 | 34 |
Environmental Science and Pollution Research | 5.190 Q2 (87/279) | Environmental Sciences | 13 | 2,26% | 121 | Lu, W | China | University of Hong Kong | 4 | 0,69% | 101 | 33 |
Journal of Industrial Ecology | 7.202 Q1 (49/279) | Environmental Sciences | 12 | 2,08% | 536 | Bao, Z | China | University of Hong Kong | 4 | 0,69% | 101 | 7 |
ACS Sustainable Chemistry & Engineering | 9.224 Q1 (13/142) | Engineering, chemical | 10 | 1,74% | 79 | Irabien, A | Spain | University of Cantabria | 4 | 0,69% | 73 | 51 |
R ranking, N number of documents, % from the total sample of documents (N = 576), TC total number of citations
The most influential authors are sorted by number of documents published and total citations, indicating the institutions and country which they work in, and the h-index –impact and productivity measure-. The most prolific author is Navarro Ferronato from the University of Insubria in Italy with 9 papers published and a total of 129 cites, followed by Vicenzo Torreta (8, 129) from the same institution. The prevalence of Italian researchers is in line with the country's overall recycling rate for all types of waste which reaches 68%, well above the EU average (57%) published in the “Third Report on the Italian circular economy in 2021” (ENEA 2021 ). Additionally, in 2020 several legislative decrees came into force that facilitated the implementation of EU directives on waste and the circular economy.
Institutions include the University of Hong Kong whose role in integrated and sustainable waste management is significant both at the research level (Hossain et al. 2021 ) and practical level in running the campus and encouraging waste reduction and recycling among all stakeholders (The University of Hong Kong 2021 ).
Co-occurrence analysis by vosviewer software.
Co-occurrence analyses the most frequent keywords in a research field regarding their jointly mention, represented by clusters (Callon et al. 1983 ). This method is widely used to identify research trend topics about a particular subject area according to the keyword frequency (Donthu et al. 2021 ). The closer two items are from each other, the higher the connection. Accordingly, those keywords with a higher association appear closer.
This analysis used the full counting network technique which points the total number of occurrences a concept appears in all documents. The normalisation parameter method with association strength was performed by VOSviewer, to normalise the link strength between keywords (Van Eck and Waltman 2010 ).
Performing the analysis, different occurrence thresholds have been used to observe the network structure. VOSviewer software permits to perform a data cleaning to visualise a map created by text data merging terms using a thesaurus file (Van Eck and Waltman 2010 ). In our co-occurrence analysis we created a thesaurus to merge different keywords referring to the same item, such as ‘LCA’ and ‘life cycle assessment’, or ‘municipal solid waste’ and ‘municipal-solid waste’. Finally, a minimum of 13 occurrences of a keyword has been chosen from 2.868 words. 41 keywords met the threshold that represents the main items of each cluster. The keywords are divided up into main four groups of clusters coloured in red, green, blue and yellow in Fig. 3 . The red cluster named ‘Industrial ecology and more sustainable infrastructure’ -SDG 9- focuses on the circular economy and industrial ecology with the aim of making industrial buildings and construction and demolition waste more sustainable, and on the challenges and barriers posed by these new models. The green cluster ‘Waste management through biological and assessment processes’ -SDGs 6, 7, 11 and 12- links the food waste and municipal solid waste and how anaerobic digestion and biogas can achieve a reduction in the use of energy and low emissions. Water treatment is associated with optimisation through new technologies. These studies use the life cycle assessment as a main tool for measurement. Sustainable development and recycling, considering indicators and behaviors in developing countries are shown in the blue cluster named ‘Sustainable development and recycling in developing countries’ -SDG 12-. Finally, the cluster in yellow studies the need to establish new policies and designs that would allow for improved waste management through resource recovery, such as the extension of producer responsibility beyond the sale of the product or service. It is therefore titled ‘New procedures for the recovery of resources’ -SDG 12-.
Co-occurrence analysis of keywords by vosviewer
Science mapping analysis displays how items from a particular field are linked to each other, determining the evolution and cognitive structure (Small 1999 ). In this study, keywords are the items used. The bibliometric mapping tool used to show the strategic diagrams is SciMat software. From the set of documents, it generates a knowledge base, in this case, the relationships between keywords are stored following a co-occurrence analysis. SciMat software grouped by plural to find similar items during the de-duplicating process (Cobo et al. 2012 ). For instance, keywords such as system and systems.
SciMat tracks a longitudinal framework that analyses the conceptual and intellectual evolution of a field. The normalisation measure chosen was the equivalence index. And to obtain the scientific map and the associated clusters and subnets, the clustering algorithm method followed was simple centers algorithm. The analysis is performed dividing the sample into three periods: period 1 with a total of 214 articles of year 2009 up to year 2019, period 2 with 155 articles of the year 2020, and period 3 with 189 articles of the year 2021. From a sample of 2,819 words, a total of 77 words have been considered, selecting only keywords with a minimum of 10 associated documents. As can be seen in Fig. 4 , the stability index (0.99 and 0.99) indicates that there is a balance between the number of words from one period to the next.
Overlapping map. Periods 1, 2 and 3 by scimat software
The evolution map shows the results of the longitudinal analysis. The thick lines show the clusters that share a main theme, and the dashed lines are those that share themes other than the main theme (Cobo et al. 2012 ). In the first period the motor theme is circular economy, while in the second period the focus is on municipal solid waste.
Figure 5 shows the difference between periods 1 and 2, from the more general to the more specific, with municipal solid waste oriented towards sustainable development -SDG 11-. In the third period focus returns to circular economy, with more dispersion apparent than in period 2, yet more specificity, as the number of clusters expands again. The massive generation of plastic waste generated during COVID-19 (Khoo et al. 2021 ; Vanapalli et al. 2021 ) could explain the interest in municipal solid waste management during period 2 and the emergence of concepts with plastics management in period 3. As a result, an evolution from the first period can be observed, with a strong focus on the implementation of circular economy and energy generation towards a circular economy centered on municipal solid waste.
Evolution map. Periods 1 and 2 by scimat software
This analysis is focused on the third period to gain better attention about the recent evolution of this field. Figure 6 shows a strategic diagram of Period 3 (year 2021) with four quadrants of the main thematic nodes according to the co-word analysis performed by SciMat. The strategic diagram displays the motor themes: ‘circular economy’, ‘life cycle assessment’ and ‘China’, developed thereafter, the basic themes: ‘recovery’ as a very specific and underdeveloped topic, it suggests a strategy towards circularity that is beginning to be considered, because many policies were only focused on promoting recycling (Ghisellini et al. 2016 ). The emerging or disappearing themes: ‘generation’, an emerging theme related to e-waste which is working on the reuse of products -SDG 12-, but circular economy is not applied in-depth. Regarding sustainable development and waste management, the environmental impacts are still a very large gap in the literature; ‘plastic waste’ is an emerging theme for circular economy, and it is studied within the pyrolysis and recycling process and new designs to improve the circularity -SDG 9 and 12-. ‘Sector’ appears as an isolated theme from circular economy, the literature is very cohesive in density due to its links with waste management case studies in different industries -SDG 9-.
Strategic diagram. Period 3 (2021) by scimat software
Based on Fig. 6 ‘circular economy’, ‘China’ and ‘life cycle assessment’ appear as motor themes. These keywords present high density and centrality, thus they have been intensively and highly studied in literature. Which is why the following analysis is focused on them. ‘Circular economy’ is linked with ‘sustainability’ and ‘sustainable development’ according to the origin of circularity (Ghisellini et al. 2016 ). Likewise, the keyword ‘recycling’ relates to circular economy as a part of 3Rs principles, due to circular policies and their focus on recycling practices and strategies rather than other options -SDG 12-. ‘Municipal solid waste’ and ‘management’ is one of the most developed topics in the studies analysed and published during 2021 towards circular economy -SDG 11-.
‘China’ is a pioneering country in the implementation of circular economy policies, and strategies based on sustainability (Lieder and Rashid 2016 ). From a broad CE perspective, the country has incorporated these schemes due to the country’s rapid industrialisation and its growing efforts in research (McDowall et al. 2017 ). Indeed, the country is the largest producer of municipal solid waste (Wang et al. 2021 ) increased by COVID-19 (Vanapalli et al. 2021 ) and given its large industrial sector. The country is developing research that allows it to establish symbiotic relationships, to find new ways of using resources or converting waste into energy -SDG 7, 9 and 11-. It would be framed within the so-called industrial symbiosis, defined as the process by which waste from one industry or industrial process is converted into raw material for another (Provin et al. 2021 ).
‘Life cycle assessment’ appears far removed from circular economy, focusing more on waste demolition and construction management (Ahmed and Zhang 2021 ; Lu et al. 2021 ) -SDG 9-, and on plastic waste generation (Hossain et al. 2021 ; Pincelli et al. 2021 ).
A systematic literature review was performed, considering the core documents with highest impact –those that appear at a minimum two nodes (Cobo et al. 2012 )- from SciMat report. Selecting those articles from the three clusters that are presented as motor themes for period 3 (year 2021): ‘circular economy’, ‘China’ and ‘life cycle assessment’. Firstly, it was considered those papers with at least one citation (N = 51). Secondly, an in-depth analysis of those articles was carried out, compiling findings and future research lines of the 20 leading articles by number of citations (Table (Table2) 2 ) according to the SciMat core documents.
Findings and future research lines of the main articles related with circular economy and waste management during year 2021
72 | Vanapalli et al. ( ) | Science of the Total Environment | Theoretical | Actions and recommendations to reduce plastic waste related with Covid-19 designing policies, new technologies and products innovation (circular products), improving environmental behaviour, local production and consumption, incentives to recycling and efficiency | Extend the analysis with available data (empirical). Replicate the analysis to a post-pandemic scenario |
16 | Jeswani et al. ( ) | Science of the Total Environment | Empirical | Life Cycle Assessment shows that climate change impacts of chemical recycling and the production of circular plastics by pyrolysis are lower than energy's recovery and fossil resources | Improve the sensitive analysis. Consider other geographical areas. Future use of technologies treatment of end-of-life is needed |
14 | Sommerville et al. ( ) | Resources Conservation and Recycling | Empirical (44 commercial recyclers) | The quantitative assessment reveals a lack of circular thinking for the batteries end-of-life. It is necessary to have more options in reuse and recycling, closing the loop; and policies incentives improving circular practices | Increased knowledge about the recycling process of some of the components, their recovery and follow-up are required |
14 | Salmenpera et al. ( ) | Journal of Cleaner Production | Empirical (case study in Finland) | Economy, technology, culture and legislation solutions are considered for coordinate actions to identify critical factors in the promotion of circularity focusing on developers and intermediaries | Extend the analysis to other geographical areas and industries |
11 | Loizia et al. ( ) | Science of the Total Environment | Empirical (Municipal Solid Waste in Cyprus) | The study provides key performed indicators toward circularity and sustainable development goals, showing that more effectively citizens' participation in waste strategies, such as awareness activities is required | Extend the analysis to other geographical areas |
10 | Vardopoulos, et al. ( ) | Environmental Sciences and Pollution Research | Theoretical | Creating urban sustainable indicators of the environmental impacts from human activities, providing the correct strategy (DPSIR model) for optimizing MSW management effectiveness and efficiency in Greek | Lack of MSW generation data collection for comparison in the long-term. A need to amplify the indicators |
9 | Abou Taleb and Al Farooque ( ) | Journal of Cleaner Production | Empirical (waste recycling in Egypt, 27 councils) | Providing a model in municipal waste recyclable management from an accounting approach, with the highest circular economy gains and the lowest costs (cost-effective). Results show that developing countries must improve their circular and sustainable practices | Extend the data sample and periods for generalize the results. Apply to other industries |
9 | Massaro et al. ( ) | Business Strategy and the Environment | Theoretical | Improving circularity towards industrial waste management, focused on smart services. And how Industry 4.0 can be integrated in waste management: optimization software, robots, mobile applications | Considering more case studies is required and analyse separately the professional and scientific issues |
9 | Kazancoglu et al. ( ) | Business Strategy and the Environment | Empirical (Case study textile firm in Turkey) | The most important circular barriers are the lack of requirements and responsibilities for suppliers or manufacturers, and support from the government. Furthermore, one of the most fundamental factors is recycling policies for waste management | Differences of applying the model in other sectors. Extend the study to other geographical areas. The complementary use of different decision-making models is required, also considering other barriers |
7 | Di Foggia and Beccarello ( ) | Sustainable Production and Consumption | Empirical (Case study in 4.732 municipalities in Italy) | The use of landfill could be reduced by increasing waste-to-energy conversion. The study provides ideas for more efficient waste management with the use of new technologies | Comparative cost-effectiveness is necessary in future studies and extend the model to other geographical areas |
7 | Wu et al. ( ) | Sustainable Production and Consumption | Theoretical | Developing collective network-based bricolage process and adaptive institutional governance is an effective strategy for establishing an industrial-level circular economy towards the transition | Verifying the process in other geographical areas |
7 | Lombardi et al. ( ) | Journal of Cleaner Production | Empirical (Italian plastic packaging management) | Italian material flow analysis of the plastic packaging management and its circularity comparing the results with EU countries, showing positive rates on Italian recycling and energy recovery. The waste management efficiency must continue improving referring to its landfill levels | Calculate the eco-efficiency indicators and related material cycles. Limitations with the material flow analysis methodology such as the available data or the varying quality |
6 | Van Straten et al. ( ) | Sustainable Production and Consumption | Empirical (Case study 3 Dutch hospitals) | Showing the evaluating options of a hospital for calculating the save cost towards circularity: recycling the instruments, repairing for extending the life cycle of instruments, melting the steel into raw material and saving in handling waste costs | Extend the period under study (only 6 months are considered). A sensitive analysis for further understanding |
6 | Minoja and Romano ( ) | Journal of Cleaner Production | Theoretical | Studying Italian waste management and the TBL contribution to sustainability if its commitment is integrated from a managerial and governance process. Proactive participation of stakeholders is also fundamental for business models; and public firms are more suitable to sustainable issues | Ownership results are only replicable to other industries with the same institutional and legal circumstances. Further in-depth analysis of IC and sustainability is required. Extend the study to other geographical areas and industries |
6 | Sharma et al. ( ) | Business Strategy and the Environment | Theoretical | Investigating the prospects, impediments, and prerequisites in the transition to circular economy in SMEs in India conducting by a semi-structured interview. Financial issues, awareness, lack of experience and recycling subject are the main impediments. Prerequisites are related to innovation and motivation | Extending the sample under study for generalize the results. Applicate the analysis to other geographical areas |
5 | Jagodzinska et al. ( ) | Journal of Cleaner Production | Empirical (landfill case study in Belgium) | Studying close the loop with energy efficiency technologies towards circular economy by mining of existing landfills with the study of refuse-derived fuel of a waste excavated landfill in Belgium submitted to pyrolysis | Lack of data. The use of a more efficient technique of separation. Further analysis of the application is required |
5 | Elgie et al. ( ) | Resources, Conservation and Recycling | Empirical (Grenada case study) | Estimating the material flows waste stream of plastic, motor oil and tires for improving solid waste management towards circularity. This can be achieved by improving data collection, banning certain materials, applying the "polluter pays" principle, and developing a resource management plan for problematic materials | Lack of data. Extending the study to other geographical areas for further analysis |
5 | Woodard ( ) | Journal of Cleaner Production | Empirical (100 England SMEs) | Findings show the necessity of improving the efficiency of SMEs from England in waste management because of the use of household services to dispose of waste. Legislation, develop a holistic waste management system more effective, and increase the waste's awareness are key to achieve circularity | Comparison with other geographical areas. More in-depth review of local authorities |
5 | Foschi et al. ( ) | Environmental Science and Pollution Research | Empirical (Emilia Romagna región case study) | Promoting consumer's awareness, eco-design, a deposit-refund system, reduction of plastic waste, investing in a new industrial infrastructure of recycling, and the support to remanufacturers are the main recommendations of the work | Stakeholders’ participation is required and extend the analysis to other geographical areas |
4 | Khoo et al. ( ) | Journal of Hazardous Materials | Theoretical | Recommendation and future prospect and challenges in plastic waste management highlighting: increase awareness, policies, incentives and regulations, production with recycling purposes, new technologies for packaging, | More in-depth analysis about plastic waste during and post-COVID19 pandemic. Applicate to a real case of study |
TC total number of citations
Citation analysis is a measurement widely used that considers a paper highly cited as relevant in a field (Zupic and Cater 2014 ), enabling us to evaluate the influence of a research topic. Also is used as a tool to detect emerging and research trends (Chen 2006 ).
Municipal Solid Waste (MSW) -SDG 11- is one of the main topics. Many of the papers related are case studies such as Vardopoulos et al. ( 2021 ) which developed a Driver-Pressure-State-Impact-Response (DPSIR) model to evaluate and assess the Municipal Solid Waste practices in Greek municipalities. Abou Taleb and Al Farooque ( 2021 ) concentrate on full cost accounting in 27 Egypt councils designing pricing model ‘Pay-As-You-Throw (PAYT)’ for municipal waste recycling. Wielgosinski et al. ( 2021 ) performed an analysis of the Polish municipal solid waste management through a balance model for assessing the impact of increasing the level of recycling, whilst Istrate et al. ( 2021 ) studied the municipal solid waste management in Madrid with a material flow analysis. Similarly, Tong et al. ( 2021 ) analyses the solid waste management system and the cause-effect relationship of households in Vietnam. Di Foggia and Beccarello ( 2021 ) highlighted the fact that the waste management chain in Italy focuses on waste-to-energy plants, calculating market measures towards circularity. In addition, in the region of Brescia, Italy, Bertanza et al. ( 2021 ) examined the evolution of municipal solid waste evolution with mass flow analysis of medium firms. Solid waste management in Brazilian universities is explored in the Nolasco et al. ( 2021 ) paper, which developed a qualitative-quantitative analysis, identifying factors of university campus waste management.
Plastic waste management is greatly studied in connection with circularity practices in many of the articles published during 2021, such as the case studies carried out by Foschi et al. ( 2021 ) on the Emilia Romagna plastic waste recycling system, following the European Commission Plastic Strategy. Similarly, Wu et al. ( 2021 ) outlines how Taiwan achieves circular economy in plastic waste from an industrial level, owing to collective bricolage. Some of the papers outline COVID-19 and the excessive use of plastics, coinciding with the most cited article of the sample (Vanapalli et al. 2021 ) which address COVID-19 plastic waste generation and the use of more sustainable technologies. The Khoo et al. ( 2021 ) paper provides recommendations for adopting effective plastic waste management due to excessive use during the COVID-19 pandemic. Pikon et al. ( 2021 ) shows the influence of COVID-19 on waste management from an economic impact perspective, highlighting the changes in municipal solid waste during the pandemic in the Polish market. Furthermore, increasing attention is being paid to biodegradable plastics as an alternative to conventional plastics. Ghosh and Jones ( 2021 ) examine upcoming trends, potential future scenarios, and the material value chain perspective of biodegradable plastics, whilst Kakadellis et al. ( 2021 ) categorizes qualitative data about biodegradable plastic strategies in United Kingdom -SDG 12-.
In the studies examined, the management of food waste is also analysed -SDG 11 and 12.- Zarba et al. ( 2021 ) analyses the Italian agri-food effectiveness towards circular economy regulatory; Provin et al. ( 2021 ) examines the reuse of food industry waste for the manufacture of biotextiles in the framework of the circular economy and the SDGs. This inter-industry collaboration would be part of the industrial symbiosis referred to above -SDG 9-.
In a similar vein, and related to SDG 9, the last process analysed by the most cited studies is the pyrolysis process, which allows thermal degradation of waste, associated with landfill mining, extracting valuable materials from the remains of materials deposited in landfills (Jagodzinska et al. 2021 ). Martínez ( 2021 ) discusses the opportunities and challenges of pyrolysis in Latin America.
This section is based on the results obtained from the bibliometric clusterisation, and the review of the 20 most cited articles. The number of articles published in the field have increased since 2015, corresponding to the United Nations Agenda 2030 and the 17 Sustainable Development Goals focused on improving and achieving education, health, economic growth and reducing inequality, as well as preserving forests and oceans (United Nations 2015 ). It is also remarkable to note the growth between years 2019 and 2021 due to new strategies and worldwide circular policies implemented in the field of waste management, such as the ‘Circular Economy Action Plan for a greener and more competitive Europe’ based on the prevention of waste and seeking improved local waste and raw material management (EU 2020 ; Camana et al. 2021 ). Although the "Agenda 2030" or "SDG" themes were not found in any of the clusters, the rest of the themes are closely related to their fulfilment. Moreover, circular waste management not only contributes to several SDGs, but also creates synergies between the goals.
A significant trend in the literature has focused on waste recycling (SDG 11 and 12), which is essential, yet insufficient if sustainable production and consumption is to be achieved by 2030. The main research topics analysed in the articles published during year 2021 focus on (1) Municipal Solid Waste (MSW) with the design of new municipal waste recycling models such as the Pay-As-You-Throw (PAYT) pricing model (Abou Taleb and Al Farooque 2021 ), (2) the importance of plastic waste (Khoo et al. 2021 ) and its recovery as a tool in the implementation of circularity principles (Ferreira et al. 2021 ), increased by the generation of plastic waste during the COVID-19 pandemic (Khoo et al. 2021 ), and (3) the reduction of food waste or its application in bio-textiles (Provin et al. 2021 ) or as an energy source -SDG 9 and 11-.
Going one step further should be considered in achieving further targets of this goal. On the one hand, a reduction in waste generation and a search for more sustainable disposal options for waste that cannot be recycled are required, e.g., through new processes such as waste pyrolysis (Jagodzinska et al. 2021 ) -SDG 9-. On the other hand, extending the lifetime of products by finding additional, new uses for them, eliminating planned obsolescence or repairing the product at a cost lower than buying a new product (Ghisellini et al. 2016 ) -SDG 12. Complementarily, waste generated in one sector can be used as a raw material in another sector or as a source of energy in the case of organic waste -SDG 7 and 9-.
The research agenda provides guidance to scholars in future related-research directions. The agenda is based on the previous in-depth analysis of the 20 articles included in the review. Considering the analysis and the ensuing discussion, the following proposal is put forward for the circular management of waste management to accelerate the fulfilment of the 2030 Agenda. Moreover, this could fill gaps and give opportunities for further development. Figure 7 collects the research agenda propositions.
Research agenda propositions diagram
One of the most researched materials in the most cited papers is the use of plastic -6 of the 20 papers analyse this issue-. Firstly, because of the significant increase in waste associated with it after COVID-19 (Vanapalli et al. 2021 ; Khoo et al. 2021 ). Secondly, because of the need to progressively replace it with other materials such as biodegradable plastics, which implies the use of renewable raw materials. In short, solutions must be proposed to current plastic waste, the quantity of which threatens the habitat of numerous species, and measures must be taken to curb its expansion and offer alternatives in sustainable materials.
It is worth noting that no studies have been found that analyse the legislative challenges associated with the progressive elimination of plastic in products such as bags or single-use items.
Proposition 1: To deepen new trends in plastic waste management and generation.
The second line of the proposal relates to circular municipal waste management -SDG 11-, a topic of great interest in recent research (Abou Taleb and Al Farooque 2021 ), growing due to recent global crises. However, the approach that has analysed this topic focuses mainly on waste recycling.
A broader focus is needed, considering other alternatives such as the reduction of waste generation, reuse and the use of Organic Fraction of Municipal Solid Waste (OFMSW) as a raw material or energy source in other sectors. Compared to incineration, which is highly polluting if the organic waste is mixed with other types of waste, there are more sustainable and energy-efficient alternatives such as anaerobic digestion (Kakadellis et al. 2021 ) -SDG 7-. This requires consumer awareness and training –SDG 12- in waste separation, adequate facilities for the process and greater cooperation between industries (Foschi et al. 2021 ; Vanapalli et al. 2021 ) For the latter option, it is recommended that tools such as industrial symbiosis be explored in greater depth -SDG 9-.
Proposition 2: To expand the alternatives towards more sustainable options in municipal waste management with the cooperation of consumers and industries.
In contrast to traditional landfill management, new infrastructures, treatments and smart technologies are proposed to improve recycling and waste disposal. Among them, (1) the construction of waste-to-energy plants makes it possible to burn solid waste to power electricity generators (Di Foggia and Beccarello 2021 ) –SDG 7-; (2) pyrolysis process for thermal degradation of waste, reducing waste accumulation (Jagodzinska et al. 2021 ) –SDG 11- or (3) Industry 4.0 can be applied in waste treatment -SDG 9- for more efficient technique of separation models in waste management addressing circular economy practices (Wang et al. 2021 ). This line of research has a profound relationship with municipal waste management, given the importance of municipal waste in current landfills.
Proposition 3: To improve the operation and efficiency of landfills through new infrastructures, treatments and technological tools.
Optimising waste management processes requires the establishment of measurement indicators. These indicators should be of a different nature and go beyond the economic or environmental quantification of targets. They should include social aspects such as awareness raising (Loizia et al. 2021 ; Van Straten et al. 2021 ). Additionally, along with technological and economic tools, the creation of a legislative framework is a critical factor in the implementation of circularity in waste management operations (Salmenpera et al. 2021 ; Woodard 2021 ).
Proposition 4: Establishment of measurement and policy enablers.
Circular waste management focuses on reducing the amount of waste generated and reintroducing the waste, once treated, as new material or energy in production, keeping the material in a cyclical flow within the same or another sector (Demirbas 2011 ; Salmenpera et al. 2021 ). It, therefore, implies reaching a new level of treatment, complementing the recycling option with a holistic view of the problem. The application of circularity principles in waste management can contribute significantly to the fulfilment of the 2030 Agenda, as it impacts several of the SDGs -6, 7, 9, 11 and 12-.
According to the research questions presented, the scientific literature structure of the field of waste management and circular economy (RQ1) has been analysed, showing that the most productive sources come from the field of environmental sciences, which conditions the main topics investigated and shows a clear lack of attention to social sciences. The most prolific authors come from two countries with a strong interest in environmental research in general and waste management in particular—Italy and China. In the case of China, this is due to its strong productive fabric and a prominent role in the generation of waste from the COVID-19 pandemic.
Concerning RQ2, four clusters have been obtained related to industrial ecology -SDG 9-, waste management from the application of bio-based processes -SDGs 6, 7, 11 and 12-, water treatment, sustainable development and recycling in developing countries -SDG 12- and the cluster on new procedures for the recovery of resources -SDG 12-.
To conduct analysis of the central topics and the patterns we used SciMat software, dividing the articles published in the field into three periods (2009–2019, 2020 and 2021) showing the scientific literature development, as can be seen in the evolution map (Fig. 5 ). The motor themes showed in the strategic diagram of the third period are circular economy, life cycle assessment and China; recovery is a basic theme; the emerging themes are generation and plastic waste; and sector is a developed theme. Referring to RQ3, the results provided from the systematic literature review are in line with the central topics pointed out previously. Many of the studies published during 2021 pertain to motor themes circular economy and China, and to plastic waste as an emerging theme.
The most cited articles and the previous bibliometric analysis have shown the great interest generated among scientists in the management of urban waste and plastic waste, which has increased in the last two years in relation to sanitary waste. The circular economy means that recycling is not enough in the management of this waste. In addition to the reduction in the generation of waste, the incorporation of the "bio" concept in its treatment, which allows fibres, bioplastics and other biomaterials to be obtained, has been added. Along the same lines, the treatment of food waste allows it to be converted into animal feed, biofuels or even textiles. However, among the most cited articles, no research related to the use and recycling of wastewater was found -SDG 6-. Further research is needed to enable its use for biomass production or as a source of nutrients for micro-organisms of interest (Kaszycki et al. 2021 ).
The establishment of three research propositions completes this research (RQ4). In this way, it is crucial to develop three fundamental aspects. First, the use of new technologies to meet the various needs raised. Secondly, a new approach to urban waste management is required. And thirdly, to develop research from a holistic perspective that will require the use of theories and sciences from the environmental, social and economic fields.
The results of this study offer academic contributions about circular waste management. Among the theoretical contributions is the establishment of state-of-the-art research on waste management linked to the circular economy, which will guide future research and fill existing gaps. To offer the most complete research review possible, a mixed methodology—bibliometric and systematic review of the most cited recent research—has been used. A bibliometric analysis was carried out with two software tools, taking advantage of the potential of both. Using complementary software validates the analysis results. In addition, this article provides a framework for research as a guiding point in waste management.
Thus, lack of social research is a major drawback that requires urgent incorporation of new social or multidisciplinary studies. It can be considered that social and economic issues have not been sufficiently addressed in the literature. None of the clusters obtained have these dimensions as their motor theme. Dropping SDGs such as 8 -decent work and economic growth-.
A guideline for practitioners about circular waste management is required. Findings reveal the need for a reference framework for scholars, practitioners and institutions.
This article implies practical contributions for governments to achieve a transition towards more circular waste management. The research shows the technical feasibility of substituting certain materials, mainly plastic, or applying techniques that allow a step beyond recycling. It is necessary to focus on actions based on recovery, reduction, remanufacturing and redesign of plastic waste to fill this gap (Olatayo et al. 2022 ). Highlight the policy spillover effect, which means that support for some public fees—for example, plastic bag fees—may imply greater support for other environmental policies related to waste reduction (Thomas et al. 2019 ). This could facilitate positive transitions towards environmental behavioural changes. In addition, public–private coordination is required in the implementation of new legislation (Foschi et al. 2021 ).
The significant "bio" trend has spread to different types of waste and sectors. Thus, the circular management of waste will require the development of infrastructures, technologies and processes oriented to its application, which means waste management with less environmental impact, but also a generation of value of the product derived from the waste. This value can be manifested in new products -whether or not related to the original sector of the product from which the waste is derived- or renewable and sustainable energies (Ferreira et al. 2021 ; Kaszycki et al. 2021 ). For this, these processes require the establishment of cooperation tools between industries in such a way that we can establish symbiosis between them (Provin et al. 2021 ).
Addressing the limitations of this study, it’s worth underscoring the fact that WoS was the exclusive Database used to retrieve the final sample under analysis, and only articles published in English are studied, other languages were not considered. Despite the use of VOSviewer to display the co-occurrence analysis, the interpretation of the results is subjective, in accordance with the papers reviewed. In future works, other software can be combined such as CiteSpace or HistCite to visually create scientific maps.
Regarding future research lines, the following aspects are considered a research agenda in the field of waste management and circular economy. The need to incorporate into waste management from a circular perspective such as: circular bioeconomy models, the construction of more robust eco-efficiency indicators to improve measurement and comparison between regions, and the consideration of new processes and techniques in the management of urban, food and plastic waste. Research is also required to manage waste in the construction and demolition of buildings and infrastructures from a sustainably innovative standpoint.
The challenges facing waste management in meeting the 2030 Agenda are considerable. Circular economy facilitates the pathway but is not a miracle tool. The contribution of companies and industries requires the collaboration and awareness of consumers. To this end, public institutions must generate policies, regulations and incentives that create the most favorable framework possible. Having already surpassed half of the set timeframe towards meeting the SDG targets, urgent measures are required, and the Academy must lend its support in this regard.
All authors contributed to the study conception and design. Conception or design of the work: Rocío González Sánchez and Sara Alonso Muñoz. Data collection: Rocío González Sánchez and María Sonia Medina Salgado. Data analysis and interpretation: Rocío González Sánchez and Sara Alonso Muñoz. Drafting the article: Rocío González Sánchez and Sara Alonso Muñoz. Critical revision of the article: Rocío González Sánchez and Sonia Medina Salgado.
Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This paper has been supported by Project PID2021-124641NB-I00 of the Ministry of Science and Innovation (Spain).
Declarations.
The authors have no relevant financial or non-financial interests to disclose. The authors have no competing interests to declare that are relevant to the content of this article.
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The world’s current model for economic development is unsustainable. It encourages high levels of resource extraction, consumption, and waste that undermine positive environmental outcomes. Transitioning to a circular economy (CE) model of development has been proposed as a sustainable alternative. Artificial intelligence (AI) is a crucial enabler for CE. It can aid in designing robust and sustainable products, facilitate new circular business models, and support the broader infrastructures needed to scale circularity. However, to date, considerations of the ethical implications of using AI to achieve a transition to CE have been limited. This article addresses this gap. It outlines how AI is and can be used to transition towards CE, analyzes the ethical risks associated with using AI for this purpose, and supports some recommendations to policymakers and industry on how to minimise these risks.
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Over the past 50 years, natural resource extraction has tripled globally, with this trend accelerating since the turn of the century (Oberle et al. 2019 ). Based on the current trajectory, demand will require more than two planets’ worth of natural resources by 2030 and three by 2050 (Osborne 2006 ). Excessive demand for resources leads to higher levels of greenhouse gas emissions from mining and extraction, the creation of monocultures that harm the natural ecosystem, and individual health deteriorating due to environmental degradation, such as worsening air quality. Waste is also extensive. For instance, the global food system currently produces enough food to feed the world’s population, but roughly a third is wasted in the supply chain and the process of consumption (Ellen MacArthur Foundation and Google 2019 ). The “circular economy” (CE) has been proposed as an economic model that can help overcome these developmental challenges.
Although there is no agreed-upon definition of CE (Kirchherr et al. 2017 ), the term is generally used to refer to an economy “based on the principles of designing out waste and pollution, keeping products and materials in use, and regenerating natural systems” (Ellen MacArthur Foundation 2017 ). This contrasts with the so-called “linear economy”, the current and dominant consumption-based economic paradigm described above, which is characterised by taking resources, making goods to be sold, and disposing of everything one does not need, including the product at the end of its lifecycle (Sariatli 2017 ). Products are typically made to be consumed and discarded by the user once they are no longer considered valuable. Similarly, by-products in the creation process of products are frequently discarded rather than utilised.
To address the harms associated with a linear economy, public and private sector CE policies and initiatives have emerged since at least the 1990s. Germany was an early pioneer of integrating CE into national law by enacting the “Closed Substance Cycle and Waste Management Act” (1996), which placed waste-management responsibilities on those who produce, market, and consume goods. Since the turn of the century, interest in this model amongst policymakers and businesses has continued to grow (Geissdoerfer et al. 2017 ). For example, the Chinese government passed a CE promotion law in 2008, published a national strategy for achieving CE in 2013, and emphasised implementing CE in its previous four national 5 years plans (Mathews and Tan 2016 ). Likewise, the European Commission announced a Circular Economy Action Plan in 2015 and the subsequent New Circular Economy Action Plan in 2020 , which look to transition the EU towards a regenerative growth model through enacting a “future-oriented agenda for achieving a cleaner and more competitive Europe” (New Circular Economy Action Plan 2020 ). In other states—such as Brazil, India, and the United States (US)—industry has been leading CE initiatives (Geng et al. 2019 ), with companies such as Xerox and Caterpillar integrating CE principles into their business models (Stahel 2016 ).
Digital technologies are a crucial enabler of CE ambitions (Preston 2012 ). Policymakers and businesses recognise this. For instance, the European Commission’s Circular Economy Action Plan explicitly states that “digital technologies, such as the Internet of things, big data, blockchain, and artificial intelligence will… accelerate circularity” (New Circular Economy Action Plan 2020 , p. 4). Similarly, numerous businesses across the globe have looked to digital technologies to further circularity, such as using sensors to more effectively monitor and maintain products (Nobre and Tavares 2017 ; Reuter 2016 ).
In this article, we centre our analysis on artificial intelligence (AI), understood here as a cluster of smart technologies, ranging from machine learning software, to natural language processing applications, to robotics, which have unprecedented capacities to reshape individual lives, societies, and the environment (Roberts et al. 2021 ). Two reasons determined our choice. First, AI technologies have several novel features, including an ability to process vast amounts of data, autonomously or semi-autonomously, to make inferences, predictions, decisions, or to generate content. These features mean that of all digital tools and technologies, those that utilise AI have the most transformational potential for CE; for instance, through facilitating widespread smart automation or breakthroughs in fundamental science that could scale CE solutions exponentially. Footnote 1 At the same time, these novel features mean that AI technologies pose unique ethical risks to fundamental rights that deserve special attention (Floridi and Taddeo 2016 ; Tsamados et al. 2021 ). Second, there has been significant growth in the use of these technologies in recent years (The State of AI in 2021 2021 ), with academics, businesses, and policymakers increasingly interested in applying these technologies for CE initiatives (Ellen MacArthur Foundation and Google 2019 ). Hence, it is not just a hypothetical consideration.
To date, research at the intersection of AI and CE has focused on how these technologies can be used to aid CE ambitions (Acerbi et al. 2021 ). By contrast, the potential for harms to emerge from using AI to achieve this circular transition has not been comprehensively analysed. This is a significant omission, given the well-documented ethical risks associated with many uses of AI, including uses to foster socially and environmentally good outcomes (Cowls et al. 2021 ; Taddeo et al. 2021 ; Tsamados et al. 2021 ). In this paper, we address this gap by (i) assessing the potential ethical issues associated with using AI to achieve CE targets, and (ii) providing policy recommendations designed to promote the ethical use of AI for achieving CE ambitions. The remainder of this paper is structured as follows. Section two establishes a background for the analysis with a brief overview of the history and concept of the circular economy, including common criticisms. Section three considers how AI can aid the transition to a circular economy. Section four assesses the ethical risks of using AI technologies to support CE strategies. Section five offers some policy recommendations for governments and industry that can be adopted to achieve more ethical outcomes when using AI for CE initiatives. A brief conclusion closes the article.
CE is a model for economic development that seeks to decouple growth from the unrestrained consumption of finite resources through introducing regenerative practices (The Circular Economy In Detail , n.d. 2022 ). The CE concept has been touted in various forms since at least the late 1970s as a solution to the environmental sustainability issue (Geissdoerfer et al. 2017 ) and as a new model for economic prosperity (Kirchherr et al. 2017 ). Although perspectives on what CE is differ significantly, there are several commonalities at the heart of most understandings. CE typically centres around ideas of reduction, reuse (including repair), and recycling (hereafter the “3Rs”) Footnote 2 of products, components, and materials to minimise waste (Kirchherr et al. 2017 ). The 3Rs are often understood as functioning in a “waste hierarchy”: reduction is the top priority to ensure that resources are extracted at a level where nature can recover. Next, reuse is promoted, so that excessive waste is not created unnecessarily. Recycling is the last resort on account of being the most wasteful (Ellen MacArthur Foundation 2017 ).
Many understandings of CE distinguish between biological and technical cycles. Circularity is often the default in “natural” biological systems, with waste from specific processes becoming resources for others (Stahel 2016 ). The water and carbon cycles, and processes such as composting, are examples of circular living systems regenerating themselves (U.S. Chamber of Commerce Foundation 2017 ). CE initiatives seek to emulate “natural” cycles when using biological materials in production, such as through regenerating soil and using renewable resources in the manufacturing process (Ellen MacArthur Foundation and Google 2019 ). Technical cycles are for materials that have been processed by humans and cannot easily be returned to nature. A prominent example is the extraction of rare metals and their transformation into mass-market consumer electronics. These materials should be (re)used as efficiently as possible to minimise resource extraction and transformation (Gaustad et al. 2021 ; Silvestri et al. 2021 ). In practice, products are often a mix of biological and technical materials. To ensure that cycles are effectively maintained, it is essential to separate materials at the point of recycling, or to develop technical materials that emulate biological ones that can be more easily returned to nature. Footnote 3
Unlike the idea of sustainability, which has often been criticised on account of being too vague to be implementable (Phillis and Andriantiatsaholiniaina 2001 ), CE provides a tangible model that can be adopted for reusing (Floridi 2019 ) or cutting down waste and promoting more environmentally friendly growth (Geissdoerfer et al. 2017 ).
Several policy initiatives have been released to promote a transition to a CE model. For example, the EU’s Waste Electrical and Electronic Equipment Directive (2013) stipulates that all producers of phones need to accommodate a take-back system, and the New Circular Action Plan ( 2020 ) introduces a comprehensive set of product requirements for circularity. In China, the Circular Economy Promotion Law (2008) notes that senior officials should be evaluated against CE targets and indicators, which were established in the country’s subsequent 5 years plans (McDowall et al. 2017 ). Finally, although the US has been less active in promoting CE, the Environmental Protection Agency’s National Recycling Strategy ( 2021 ) explicitly focuses on circularity (National Recycling Strategy 2021 ) and a handful of local initiatives have been undertaken, including San Francisco’s Zero Waste scheme (Mathews and Tan 2016 ).
Industry initiatives are also being pioneered across private sectors. The technology company Philips has begun offering “lighting as a service”, where it focuses on selling maintenance and repair agreements rather than lighting products. The products sold as part of these agreements are often smart technologies that only provide lighting when needed (Achieving a Circular Economy 2015 ). Ikea has recently opened its first second-hand store and an associated buy-back scheme to encourage consumers to return their unwanted goods for reuse (Fleming 2020 ). Smaller private initiatives are also on the rise. Prominent examples include Fairphone Footnote 4 and BackMarket, Footnote 5 social enterprise companies that apply the CE model to the mobile phone and computer industries, by encouraging the refurbishing, repair, and reuse of phones and laptops.
These initiatives are promising, but the transition towards circularity is still nascent. Despite predictions that the circular economy will replace the linear economy by 2029 (Hippold 2019 ), a 2022 report showed that only 8.6% of the world economy was circular in 2020, which is, in fact, a decline from 2018, when 9.1% of the global economy was circular (de Wit and Haigh 2022 ) Footnote 6 . This indicates that significant progress still needs to be made if a meaningful circular transition is to take place.
The concept of a CE is not without its critics. Notably, the focus on socially good outcomes is generally lacking in CE narratives (Barbier 1987 ; Purvis et al. 2019 ), while the idea of sustainability often includes economic, environmental, and social elements (Bibri 2018 ). Because of this, it is unclear whether the circular economy would prove beneficial for social outcomes, including whether it would improve individual well-being (Geissdoerfer et al. 2017 ), or lead to greater
“social equality, in terms of inter- and intra-generational equity, gender, racial and religious equality and other diversity, financial equality, or in terms of equality of social opportunity” (Murray et al. 2017 , p. 376)
Even if CE proved to be socially beneficial, it remains unclear how to ensure or even facilitate these beneficial aspects.
Some scholarship has been critical of the theoretical robustness of the CE concept, which has predominantly been developed by policymakers and businesses. This includes questions over the foundational premise that the earth is a closed loop where materials and energy cycle through the system, with scientists pointing out that the earth is, in fact, an open system (Skene 2018 ). Other criticisms include the potentially damaging effects of “Jevon’s paradox” ( i.e. eco-efficiency leading to more consumption) (Korhonen et al. 2018 ), and the objection that long-lasting products may not be the most environmentally friendly choice on account of the difficulty of disposal Footnote 7 (Murray et al. 2017 ) or due to the prolonged use of eco-inefficient products (Blunck et al. 2019 ).
Perhaps, most problematically, the lack of theoretical robustness of the CE concept could lead organisations to appropriate the term without overhauling business practices in a meaningful way. For instance, many proposed definitions of CE do not include the idea of a waste hierarchy, meaning companies could make incremental improvements in recycling and claim that they are introducing circular and sustainable business practices, irrespective of the kind of material used (and disposed) in production processes (Kirchherr et al. 2017 ). Large transnational corporations leading the discourse on, and investments in, CE initiatives also create a risk of co-option, whereby powerful actors that are already prospering because of the current developmental model set the standards for CE, while also securing a position of capital accumulation within this new model (Mah 2021 ; Ponte 2019 ). This could undermine market competition and consumer choice.
Finally, some even question whether CE is sufficient to fix the current “take-make-waste” model, given that it still promotes consumption and growth (Blühdorn and Welsh 2007 ; Mah 2021 ). This problem has given rise to a “degrowth” movement amongst environmental activists and scholars, who advocate for a radical political economy reorganisation that concentrates mainly on the “reduction” principle that is also found in CE (Schröder et al. 2019 ).
Despite these documented drawbacks, it would be wrong to dismiss the CE model. While imperfect, in many circumstances, it offers a marked improvement on the status quo and can facilitate tangibly sustainable outcomes. Nonetheless, for a sustainable and effective implementation of CE to succeed, ongoing scrutiny and anticipation of potential harms are needed. This includes scrutinising the digital technologies that are being used to support CE as part of a “green plus blue” approach to global challenges in the twenty-first century (Floridi 2020 ). We undertake this analysis in the following sections, specifically focusing on AI.
AI is a key enabler of CE and the focal point of this paper on account of its potential to bring about significant benefits and risks. Footnote 8 However, it is important to acknowledge from the outset that AI does not function in a vacuum; AI systems are typically developed and deployed in tandem with other digital technologies. For example, Internet of things (IoT) devices may be used to collect data for an AI system to subsequently analyse (Askoxylakis 2018 ; Reuter 2016 ). Accordingly, while our analysis centres on the use of AI in support of CE, we consider the use of other digital technologies insofar as they complement AI in relevant contexts. The remainder of this section considers how AI can aid CE goals by Sect. ( 3.1 ) designing and maintaining circular products and Sect. ( 3.2 ) facilitating circular businesses.
AI can support the design, development, and maintenance of circular products. This can happen in two notable ways.
First, a product needs to be designed and developed with the 3Rs in mind to meet CE parameters. In particular, products should be designed to ensure a long product life and in a way that enables the separation of components that are a part of the biological cycle (e.g. cardboard) from those that are part of a technical cycle (e.g. plastic), which would enhance its recycling potential (Ellen MacArthur Foundation and Google 2019 ). AI can support designers by suggesting initial designs for eco-friendly products or adjusting designs based on environmental parameters and/or considerations of other actors in the circular value chain (Acerbi et al. 2021 ; Gailhofer et al. 2021 ). For instance, parameters could be established for designing a product based on local or recycled materials, which would, in turn, lessen resource extraction and emissions associated with the transport of materials. Similarly, AI can help design new materials to substitute unsustainable resources, such as harmful chemicals. This design could enhance the durability of products and ease recycling at the end of the product lifecycle. An example is the project ‘Accelerated Metallurgy’ which used AI to develop novel metal alloy combinations that take into account circular economy principles such as non-toxicity, design for use and reuse, extending the use period and minimising waste (Gailhofer et al. 2021 ). AI could also help predict how materials change over time, including considerations of durability and potential toxicity of materials (Ellen MacArthur Foundation and Google 2019 ). This information can be contained in a “product passport”, which would help facilitate reverse logistics (Charnley et al. 2019 ). These solutions could address some of the concerns outlined above about the long-term issues of eco-inefficiencies and disposal issues surrounding circular products (Blunck et al. 2019 ; Murray et al. 2017 ).
Second, regarding the maintenance of CE products, AI could be used to monitor products and make data-driven decisions. For example, AI-powered digital twins—virtual models that accurately reflect physical objects—can help study performance over time and generate possible improvements (What Is a Digital Twin? n.d. 2022 ). These systems, which rely on IoT sensors to collect data on functionality, can help ensure the longevity of products through understanding product performance and condition in near-real-time (Askoxylakis 2018 ; Okorie et al. 2018 ). These data can then be used to make decisions about a product, such as whether interventions are needed, optimising performance and extending the product lifespan (Bressanelli et al. 2018 ). More generally, AI can be used to analyse data collected over a product’s lifecycle to either make real-time efficiency improvements or to determine whether a returned product should be reused, remanufactured, or recycled (Blunck et al. 2019 ). Since 2019, Apple has used on-device machine learning to predict the usage patterns of iPhone users, allowing more efficient battery charging, which it claims can extend the chemical age and thus the lifespan of the popular smartphone. Footnote 9 Meanwhile, Google and DeepMind have used AI to optimise battery usage based on predicted usage patterns and thus save power and potentially reduce charge cycles. Footnote 10 Beyond conventional business-to-consumer markets, these could be effective methods of maintaining product quality in a sharing economy business model.
AI could also support circular business. In this case, at least three points of intervention are promising.
First, AI can be used to develop innovative circular business models, like AI-based dynamic pricing. If products are sold as a service or recycled products marketed, it is unlikely that standardised pricing could be used, given the multitude of variables impacting the price of a product. Relying on individuals to price each returned product manually would be time-consuming and could not scale effectively. Dynamic pricing algorithms could be used to analyse many variables that should be considered in pricing, such as age of the product, wear and tear, and market conditions to calibrate price-points efficiently. Platforms like eBay already offer second-hand sellers price suggestions based on the current market for similar items in similar conditions. Footnote 11 Likewise, matching algorithms can help connect buyers and sellers more effectively (Gailhofer et al. 2021 ). These business models are already being tested in existing sharing economy models, such as for bikes, indicating the potential viability of exporting them into circular product markets (Ellen MacArthur Foundation and Google 2019 ). Indeed, product-as-a-service has been identified as a potentially significant opportunity for existing companies, not just market disruptors (Antikainen and Valkokari 2016 ).
Second, AI could facilitate circular businesses by supporting the recycling infrastructure needed for a functioning circular economy. Effective sorting is required, because CE involves reusing, repairing, and recycling products. AI-powered image recognition can identify and differentiate waste, minimising resource loss. For instance, Unilever and Alibaba recently partnered to trial an AI-enabled sorting machine that distinguishes between different types of plastic, with the project aiming to introduce large-scale, closed-loop, plastic recycling in China (Moore 2021 ). Similarly, in the electronic waste sector, robots are being integrated into disassembly lines to retrieve and recycle valuable and hazardous materials at the end of a product’s lifecycle (Renteria and Alvarez-de-los-Mozos 2019 ). For example, Apple’s Daisy robot can “take apart up to 200 iPhone devices per hour, removing and sorting components to recover materials that traditional recyclers can’t—and at a higher quality” (Apple Recycling Program 2018 ). This facilitates higher value recovery of materials, creating secondary product markets (Fletcher and Webb 2017 ; Renteria and Alvarez-de-los-Mozos 2019 ). This type of sorting is crucial for minimising waste at the end of a product’s lifecycle and providing the materials for new circular products.
Third, AI can help with necessary infrastructural elements, to ensure that the resources underpinning circular businesses are themselves sustainable. Energy consumption for storage and processing of data is a notable example. Data centres are heavily energy-intensive. Some predictions suggest that data centres could use as much as 13% of the world’s electricity by 2030, compared to 1% in 2010 (Andrae and Edler 2015 ). If data-intensive circular businesses require electricity consumption at this level, then many of the environmental aspirations of the circular economy could be undermined. This is a risk that has been recognised by some of the world’s largest data providers, many of whom are turning to AI to assist in areas such as cooling and optimising energy use. For instance, in 2016, DeepMind developed an AI system that tuned Google data centres’ cooling systems based on the weather and other factors, thus reducing the cooling energy bill by 40% (Jones 2018 ).
We have seen that using AI for developing CE products and businesses offers many potential benefits. However, without proper consideration or ethical scrutiny, the use of these technologies could undermine their utility on account of being harmful and rejected by society (Floridi et al. 2020 ). The unethical use of AI presents several plausible risks, as we detail in the remainder of this section. Sub-Sects. ( 4.1 ) and ( 4.2 ) will focus on the potential direct harms from AI systems for CE, while Sects. ( 4.3 ) and ( 4.4 ) will focus on broader structural considerations of using these technologies.
CE concerns relationships and processes between multiple parties. A single actor does not “close the loop” given the connectedness of supply chains; circularity can hardly be achieved without collaboration (Alexandris et al. 2018 ; Larsson and Lindfred 2019 ; Sankaran 2020 ). This poses a pressing need for cooperative networks, and data and interoperable systems are critical to this end (Ramadoss et al. 2018 ). Data fuel these intra- and inter-organisational networks by informing stakeholders about the various attributes of underlying assets, such as location, condition, and availability. At the same time, without AI, it would be extremely difficult to make sense of these data and use them to aid in designing and maintaining products, supporting circular businesses, or achieving a high degree of circularity in the economy. However, this data collection and analysis could also exacerbate privacy risks.
Regarding data collection, the proliferation of tracking and measurement devices, such as IoT, into personal spaces is often a prerequisite for AI-powered CE products. This poses a significant ethical risk (Bressanelli et al. 2018 ; Ramadoss et al. 2018 ). Take the collaboration between Cisco, Cranfield University, and The Clearing in developing a circular model for producing and consuming sport shoes. Each pair of shoes was fitted with an IoT component that tracked the location and shoe condition to identify replacement and upgrade needs. At the end of the product’s life, customers were recommended a location to return the shoes for remanufacturing (Nobre and Tavares 2017 ). While this model sought to minimise environmental waste, it did so at the cost of revealing an individual’s geospatial data, which can act as a proxy for many other pieces of information about an individual, including their work, hobbies, and other behavioural patterns. Accordingly, the use of AI in support of CE tacitly encourages increased data collection through allowing data analysis capabilities to be scaled, in turn threatening consumer privacy.
A potential retort to this ethical risk is that personal data, including geospatial data, are already collected and analysed by numerous applications on our phones (Binns et al. 2018 ). However, the fact that ethically contentious data collection is already taking place does not act as a justification for further collection. How the data from tracking-enabled CE devices are used and by whom are key questions that would need to be addressed if geospatial data or other personal data are to be used ethically for CE products. A recent public engagement exercise by the Geospatial Commission—an expert committee housed within the UK Government’s Cabinet Office—revealed that individuals were concerned that geospatial data are not being used in their best interests, that they could not control the use of these data meaningfully, and that there were real risks of the data being misused or breached (Maxwell et al. 2021 ). The responses to this engagement exercise indicate that collecting geospatial data from circular products for subsequent analysis through AI applications pose a significant risk to public trust.
Regarding data analysis, the individual or group inferences that AI systems can make could also prove ethically problematic (Floridi 2014 ; Taylor et al. 2016 ). Consider the example of smart meters, which, as of 2020, account for over 30% of all energy meters in homes and small businesses in the UK (Smart Meter Statistics in Great Britain 2020 ). AI can analyse data from these meters to improve energy consumption, resulting in lower costs for consumers and a waste reduction. While energy data may not seem sensitive, patterns in energy usage can point to when individuals wake up, go to sleep, go to work, are away, have guests over, amongst many other things. Previous studies have indicated that it is even possible to infer how frequently an individual puts on the kettle and how much water is used to fill it (Murray et al. 2016 ). This example is indicative of how AI can make precise inferences about individual behaviours, even through seemingly banal applications. Potential CE benefits could be undermined by pernicious uses of these data, such as for unwanted targeted advertising or punitive behaviours against customers not following regimented policies, like black-box trackers on cars for specifically profiled drivers.
The above examples refer to intra-organisation data collection and analysis. The situation can become even more contested when inter-organisation data sharing is considered. As mentioned, this connectivity is a necessary step for “closing the loop”, yet it raises questions over how organisations can share data in a meaningful way while still ensuring privacy (Antikainen et al. 2018 ). Data security and liability risks are heightened within a highly interoperable ecosystem where one compromised node could impact many others (Allam and Dhunny 2019 ; Luthra and Mangla 2018 ), with the effects of security breaches especially damaging in these complex and interdependent systems involving multiple stakeholders. If left unaddressed, these risks could affect the potential successful adoption of a connected circular economy or make its implementation more problematic than it needs to be through undermining public trust.
CE literature is generally positive about adopting algorithmic-based business models, such as automated dynamic pricing and matching. AI can be used to scale circular business practices by pricing reused products and/or matching them with potential consumers automatically, for example, based on demand, the condition of the product, or the profile of consumers. However, many existing experiments with automated dynamic pricing and algorithmic profiling in the wider economy have led to unfair or discriminatory outcomes. Here, we will focus our discussion on the former. Footnote 12 Recent examples of unethical outcomes from automated dynamic pricing include an online Scholastic Assessment Test (SAT) preparatory course provider discriminating based on ZIP codes, which act as a proxy for ethnicity, leading to Asians being almost twice as likely to be offered higher prices than non-Asians (Angwin et al. 2015 ); the dating app Tinder’s pricing algorithm discriminating against individuals over 30 (Heikkila 2022 ); and Uber charging higher fare prices to individuals in Chicago neighbourhoods that have larger non-white and higher poverty level populations (Pandey and Caliskan 2021 ).
Taking this last case of Uber as an example, fare pricing is generally determined by duration and length of trips and a “surge multiplier”, which is based on relative demand and supply within a specific location. Uber’s current algorithmic model is influenced by drivers’ preferences and biases, such as whether to collect individuals from some areas of a city or specific passengers based on information provided, like name and rating. Ge et al. ( 2020 , p. 1) found that in Boston, US
“Uber drivers were twice as likely to cancel an accepted ride when travellers were using [an] African American-sounding name”.
Pandey and Caliskan ( 2021 ) argue that one possible reason specific neighbourhoods, and thus demographic groups, are charged higher prices is because a lower proportion of drivers are willing to provide services in some areas, impacting surge pricing. These example shows how harmful biases can creep into dynamic pricing business models and suggest that applying this model to CE poses a significant ethical risk. While using personal characteristics for pricing CE products may seem implausible at first, there are clear precedents in personalised marketing (Miller and Hosanagar 2019 ). On top of this, risks could materialise even if protected characteristics, like race or gender, are avoided, due to the potential for other attributes to act as proxies, as was seen in the above example. As such, it is not unreasonable to imagine tailored pricing and advertising of circular products including a variable that correlates with a protected characteristic and inadvertently leads to indirect discrimination (e.g. the inclusion of consumer’s ZIP code as a variable, so as to minimise transport emissions).
It should be stressed that harmful biases are not unique to automated pricing and other algorithmic business models. Individuals manually pricing CE products may show similar biases, as seen in many other sectors previously (Ayres 1991 ; Chander 2017 ). However, AI systems could standardise specific types of harmful biases at scale, with the “black box” nature of some of these systems exacerbating this risk by making harms less traceable (Pasquale 2015 ). Additionally, because of the proliferation of AI-as-a-service—off the shelf AI systems that organisations can buy—and due to the complex allocation of responsibilities, redressing these biases might become extremely challenging. This indicates that careful consideration of design ex-ante and regular monitoring ex-post are needed if companies are to adopt an ethically sound automated dynamic pricing system.
On top of the direct harms to individuals from AI systems for CE, these technologies could also have negative structural impacts. In terms of social and economic outcomes, significant risks are associated with the current realities of AI development and deployment. This is true both internationally and domestically.
Internationally, as several nations in Europe, North America, and Asia pilot circular projects, including smart cities, Global South countries have fewer resources to promote an AI-powered circular transition. A study by McKinsey estimates that leading countries could capture an additional 20–25% in net economic benefits from AI adoption. In comparison, Global South countries may capture only about 5–15% (Notes from the AI Frontier 2018 ). Thus, the application of AI may widen the digital divide between nations rather than close it.
As a solution, Ghoreishi and Happonen ( 2020 ) propose that Global North countries could use their AI technologies to help developing countries move towards CE. However, this approach would merely plaster over the broader issue of how contemporary AI value chains are structured. In the Global South, critical roles in the AI value chain include extracting raw materials, manufacturing hardware, and low-skilled tasks such as data labelling (Crawford and Joler 2018 ; Gray and Suri 2019 ). In contrast, the underlying research, design, and maintenance of products typically occur in the Global North (Weber 2017 ). Accordingly, merely relying on AI exports to the Global South for a CE transition could further exacerbate many problematic dependency-agency issues that characterise current AI dynamics (Weber 2017 ), and which have long been criticised by international development scholars (Frank 1986 ). Indeed, without a wider restructuring of the AI value chain that empowers high value-added tasks being completed in the Global South, other risks from simply exporting AI could materialise, such as the use of harmfully biased or unrobust models on account of deployment in a context the system was not trained for (Danks and London 2017 ).
Domestic inequalities and exclusion could also materialise within Global North states, which is where most AI-driven CE initiatives presently occur. CE’s reduction of linear consumption will change the labour structure from creating products to maintaining products-as-a-service. This will mean a greater emphasis on higher skilled work designing and maintaining products, and a lesser emphasis on factory floor product creation. The resultant shift would be a polarisation in the types of occupations available, thus leading to wage inequality (Lawrence et al. 2017 ). In countries like the U.S., where nearly 50% of digital service jobs exist in only ten metropolitan areas, a shift from manufacturing to design roles may result in further geographic inequality (Muro 2020 ).
Domestically, social exclusion is also a real possibility. On a regional scale, cities like Stockholm, Copenhagen, Amsterdam, and Reykjavik have created digital suggestion platforms, where citizens can provide information about the city’s infrastructure and environment. The intention of developing these platforms is to collect data and encourage civic engagement while improving social and environmental conditions towards a circular economy. However, these tools tend to “exclude non-digital people like the elderly or simply less-informed” (Blunck et al. 2019 ). In the UK, for example, 99% of adults aged 16–44 years were recent internet users, compared with 54% of adults aged 75 years and over. Additionally, 81% of disabled adults are internet users, compared to 91% of adults more generally (Internet Users UK: 2020, 2021 ). Likewise, the increasing attention and resources being used on smart cities to leverage the most innovative technologies for social, economic, and environmental activities could come at the expense of suburban and rural areas (Allam and Dhunny 2019 ; Ziosi et al. 2022 ). While the use of AI in support of CE would not be entirely to blame for these domestic inequalities—which are already materialising due to the development and deployment of other digital technologies—the potential exacerbation of these inequalities from using AI in support of CE is an important ethical consideration.
A final ethical consideration concerns whether current, relevant, scientific knowledge makes the use of AI in CE innately risky. Nature is a complex and balanced ecosystem. The risk is that one may over-simplify the ecosystem, adopting a reductionist approach, formalising what cannot be reduced to formulae, and using mathematical modelling in which crucial variables are removed (Murray et al. 2017 ). This is problematic, because, for AI to benefit the environment, one needs to “ask the right ecological questions to have a clear understanding of the problem” and how to tackle it (Blunck et al. 2019 , p. 31). There is still much unknown about the environmental dimensions of CE (Larsson and Lindfred 2019 ). For example, water reuse is an excellent opportunity to apply CE principles. However, there are many concerns and unknowns about the impact of the quality of recycled water, specifically on human health (Voulvoulis 2018 ). The same observation has been made about plastic recycling which consumes resources and produces its own set of waste and emissions (Korhonen et al. 2018 ; Mah 2021 ). More generally, existing work on the environmental aspect of the circular economy is unbalanced, with scholars pointing out that biodiversity is often a forgotten element of CE narratives (Geissdoerfer et al. 2017 ). This risks inadvertently deploying AI or optimising algorithms in a harmful manner because of a flawed or narrow understanding of what a good environmental outcome should look like (Murray et al. 2017 ).
Designing or optimising for specific notions of good environmental outcomes is ethically risky due to the inevitable complex balances and trade-offs involved. The rapid development and manufacturing of advanced machinery for CE will lead to extensive use of resources, causing emissions and pollution (Blunck et al. 2019 ). For instance, many “clean” technologies, such as hybrid car engines, also rely on rare-earth metals that are mined at considerable environmental cost (Tremblay 2016 ). Indeed, if done incorrectly, the disposal of these products could also prove challenging, with electrical and electronic equipment becoming one of the fastest-growing waste streams in the EU (New Circular Economy Action Plan 2020 ). Likewise, data collection, analysis, and storage processes in AI development require much computational power, which consumes enormous amounts of energy (Cowls et al. 2021 ; Kouhizadeh et al. 2019 ). This energy consumption is increasing with the development of bigger AI models, with the computing power needed to train state-of-the-art models increasing by over 300,000 times from 2012 to 2018. Footnote 13 Consequently, using AI to fulfil a narrow set of CE ambitions could come at the cost of other environmental priorities. In fact, given that AI standardises and scales specific decisions, the risk associated with using these systems is particularly high, if trade-offs are not adequately understood and considered.
CE literature often considers how a transition from a linear economy can occur at three levels: micro, meso, and macro (Acerbi et al. 2021 ; Ghisellini et al. 2016 ; McDowall et al. 2017 ; Milios 2018 ). These categories are used slightly differently across academic literature, with our usage as follows. Micro recommendations refer to intra-organisation policies. Meso recommendations refer to industry-specific policies and/or inter-organisation relationships. Macro recommendations refer to national or global-level policies. To help avoid or mitigate the potential risks outlined above, we offer policy recommendations at each level. These recommendations are meant to be realistically implementable and help guide the policy and practice of AI in support of CE in the near and medium-term.
Organisations looking to develop circular products or transition to a circular business model should look to the debates in AI and digital ethics literature. Several innovative solutions can be found within this field for mitigating the harms outlined above. Here, we will focus on two practices that can support the ethical use of AI: privacy-enhancing technologies and AI auditing. These practices align with addressing the ethical risks outlined in Sects. 4.1 and 4.2 , respectively.
Privacy-enhancing technologies (PETs) is a catch-all phrase for any technical solution protecting individual privacy or personal data (Privacy Enhancing Technologies for Trustworthy Use of Data 2021 ). This ranges from simple tools such as ad-blockers to more advanced techniques like homomorphic encryption. PETs can minimise the risks associated with data collection from devices, including IoT-embedded CE products, and subsequent inferences made by AI technologies. Regarding data collection, IoT and similar devices could be combined with privacy-enhancing measures like federated analytics which analyses data locally. Given that attempts to apply PETs to IoT devices are still immature (Garrido et al., 2021 ), this is likely a medium-term solution that technology companies will probably need to pioneer. Footnote 14 For inferences about those using circular products, privacy-preserving techniques such as differential privacy (Dwork 2008 ) and synthetic data can offer protection by obscuring the individual within datasets. The former does so by enabling population-level insights and the latter by augmenting datasets with realistic, generated data. These techniques will likely involve a trade-off between the degree of privacy preserved and the granularity of insights provided about products. Accordingly, deciding whether to use PETs should be a case-by-case decision that organisations make, based on factors such as level of risk.
AI auditing can mitigate the risk of harmful algorithmic bias in the CE, such as that posed by circular business models that incorporate automated dynamic pricing. Several auditing approaches can detect whether AI systems are exhibiting bias. Governance audits can be used to determine whether there are appropriate organisational measures in place for the use of AI systems; empirical audits can be used to assess the inputs and/or outputs of an algorithm for signs of bias; and technical audits can assess features of the dataset and/or model (Auditing Algorithms 2022 ). These audits could be undertaken internally, based on regulator, academic, or industry guidance (Raji et al. 2020 ; Mökander et al. 2021 ; Mökander and Floridi 2021 ), Footnote 15 or by an external organisation offering AI auditing services. Detecting harmful biases allows CE businesses to modify their systems to mitigate these harms. It is important to stress that the field of AI auditing is still relatively nascent, meaning research is necessary for determining which framework is appropriate for a specific product or organisation. That being said, regulatory guidance on auditing will become clearer as policy measures like the EU’s AI Act begin to take shape.
Addressing the structural inequalities associated with a shift to CE is challenging. Developing new industry-wide norms, particularly within the technology sector, could be a beneficial first step. An open source approach offers possible mitigation for the international geographic inequalities that currently characterise the use of AI in the CE. Patent wavers (e.g. as done by Tesla), open source software (e.g. Meta/ Linux’s PyTorch), and open data (e.g. Google’s Dataset Search) could all support organisations that currently do not have access to large datasets or possess the capabilities to integrate AI into their processes (Zhang et al. 2019 ). This opening of capabilities can stimulate circular businesses and higher quality jobs in the Global South. Moreover, it could improve the overall innovation ecosystem, speeding up the transition to a CE. However, the limitations of this proposal should also be stressed. Structural inequalities, such as those relating to education and infrastructure, mean that any claims of geography being a thing of the past are fallacious (Anwar and Graham 2022 ). Likewise, open source does not mean that capabilities are democratised, given that the underlying designs and logics of systems and datasets are controlled by very few entities (Crawford and Joler 2018 ). Accordingly, open source can provide a promising first step for reducing global inequalities, but it is necessary to recognise the limited change it can make within wider power structures.
The private sector should also develop best practices for an inclusive CE transition. One aspect of this is reskilling programmes. Current reskilling initiatives are left mainly to individual organisations; these initiatives can help manage immediate business needs but are inadequate for managing longer term occupational shifts, due to their frequent disconnect and parochial focus. Sector skills councils, non-profit organisations that help a single sector identify and close the specific skill gap, could provide a strong foundation for addressing the needed structural transition for CE (Chopra-McGowan and Reddy 2020 ). A second element of an inclusive use of AI for CE is the promotion of diversity in the development of applications and products. An important first step is to ensure that diversity, equity, and inclusion are prioritised when undertaking public engagement on policies or products. More generally, for AI-powered CE products to be designed inclusively, those creating the systems must be reflective of a society’s diversity. While this is true for all digital technologies, it is particularly important for AI, given that many systems are (semi-)autonomous and opaque, making it more difficult to detect and rectify issues ex-post . Correcting the diversity gap in the technology sector is necessary, and it will require a range of industry-wide remedies, including funding university outreach and scholarships, partnering with, and supporting interest groups that seek to support minorities within the sector, and transparent reporting about diversity statistics. Failing to do so will lead to the development of AI products that only work well for specific demographic groups.
At a macro-level, governments can help address the epistemological risks associated with AI for CE through supporting research and developing wide-ranging guidance. Regarding the former, the concept of CE has generally been developed and progressed by policymakers and industry, with several scientists questioning some fundamental premises around CE (Korhonen et al. 2018 ; Skene 2018 ). The first port of call is for governments to increase the funding available for research into foundational questions associated with CE and how to operationalise it in a way that minimises harmful trade-offs. There are already promising signs of such investment beginning to materialise. For instance, in 2021, UK Research and Innovation (UKRI) pledged £30 million to support a major research programme into CE, encompassing 30 universities and over 200 industry partners. Footnote 16
Guidance can help ensure that scientifically supported best practice is followed when using AI for CE. The needed guidance ranges from repositories of existing successful uses, to codes of practice, to standards defining appropriate variables when optimising AI for different CE problems. Examples of best practice for guidance or standards can be drawn from several adjacent fields, including environmental governance. For instance, the European Commission is set to introduce a standard methodology for quantifying the environmental footprint of private sector products and services in the first half of 2022, which is designed to mitigate “greenwashing”. Footnote 17 Similar methodologies could be proposed for measuring the carbon cost of AI systems, so as to understand the environmental trade-offs associated with their use for CE.
Finally, the epistemic risks that we highlighted in Sect. 4.4 call for a joined-up and flexible approach to the governance of AI for CE and CE in general. As our scientific understanding of complex environmental dynamics is still evolving, governance mechanisms aiming at supporting sustainable practices need to be able to accept and adapt quickly to new knowledge to ensure that AI for CE is a success. The risk here is that governance policies may standardise the wrong trade-offs and thus scale harms. Deep collaboration between governments, academia, and industry, potentially through new and dynamic institutions, will be necessary for overcoming this risk.
CE offers an alternative vision to the current linear economic model. Circularity would facilitate more environmentally sustainable development and a broader societal shift from consumption to quality experiences and relationships. AI will be crucial to realising this transition. It can support the design and maintenance of circular products and the creation of circular business models. Policymakers, industry, and academics are all taking a keen interest in these potential opportunities.
However, there has been little scrutiny of the ethical consequences of using AI to transition to CE and how to address potential risks. Using AI to develop and maintain circular products and businesses may pose significant challenges. Privacy, equality, and well-being could all be harmed through the unethical use of AI. Moreover, positive social and environmental outcomes could be undermined by a disjointed, uneven, or misguided application of AI in transitioning to a circular economy. These risks can be minimised and, in some cases, avoided altogether. To this end, we have proposed three sets of recommendations that can guide the ethical adoption of AI for fulfilling circular economy ambitions.
At the micro-level, adopting AI ethics best practices within organisations, such as using privacy-enhancing technologies and AI ethics-based auditing, will help mitigate potential risks from privacy infringements and harmful biases. At the meso-level, the promotion of open source, industry-wide collaboration on reskilling, and supporting inclusive design, could help minimise the exacerbation of social and economic inequalities, both internationally and domestically. At the macro-level, governments can help to address some of the epistemological questions associated with using AI for CE by providing further funding for research and developing guidance and standards collaboratively. Adopting these recommendations would leverage the good potential of AI to foster CE. AI and CE can be mutually supportive, and an ethical “AI4CE” is an important project. It must also become an urgent priority.
Not Applicable
For instance, the development of new types of plastic that are more environmentally friendly. See https://www.deepmind.com/blog/putting-the-power-of-alphafold-into-the-worlds-hands
The 3Rs are typically adopted, though many scholars go further through adding other ‘Rs’ pertaining to CE behaviours.
This point will be discussed in greater depth later in the paper.
https://www.fairphone.com/en/
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One important caveat is that this does not necessarily suggest that CE initiatives are shrinking in real terms. Instead, this figure may be indicative of higher levels of overall consumption.
For example, bamboo chopsticks are less energetically expensive than a highly specialised plastic fork. When both of these products are inevitably disposed, the bamboo chopsticks can be easily re-assimilated into nature through bio-degradation, while the fork may require multiple processes and machines for its recycling (Murray et al. 2017 ).
As mentioned in the introduction, this is on account of the novel features of AI which include (i) an ability to process vast amounts of data, (ii) autonomously or semi-autonomously, and (iii) to make inferences, predictions, decisions, or to generate content.
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This is not to say that algorithmic profiling is not problematic. A significant amount of literature has considered how biases can emerge during profiling; for instance, see (Sweeney 2013 ). Rather, the choice to focus only on the case of dynamic pricing was made to ensure a concise analysis.
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Huw Roberts’ research is supported by a research grant for the AI*SDG project at the University of Oxford’s Saïd Business School. Mariarosaria Taddeo wishes to acknowledge that she serves as non-executive president of the board of directors of Noovle Spa.
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Huw Roberts
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Luciano Floridi
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Conceptualisation: LF, MT, and HR. Data collection and analysis: HR and JZ. Paper writing: HR and JZ. Paper review and revisions: HR, JZ, BB, JC, BG, PJ, AT, MZ, MT, and LF. Supervision: LF and MT.
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Roberts, H., Zhang, J., Bariach, B. et al. Artificial intelligence in support of the circular economy: ethical considerations and a path forward. AI & Soc 39 , 1451–1464 (2024). https://doi.org/10.1007/s00146-022-01596-8
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Waste management is the main challenge in the transition away from the linear "take-make-dispose" economy. Incorporating the principles of circularity in waste management would facilitate the achievement of Sustainable Development Goals. This paper aims to provide state-of-the-art research about circular waste management in the fulfillment of the 2030 Agenda. For this purpose, bibliometric ...
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This paper aims to provide state-of-the-art research about circular waste management in the fulfillment of the 2030 Agenda. For this purpose, bibliometric analysis by VOSviewer and SciMat software ...
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the process is called the circular economy. The circular economy is a new economic model in. which materials and value circulate and added value is generated by services and smart. operations ...
The concepts of circular economy (CE) and sustainability (S) have lately gained momentum among scholars, theorists, academics, and practitioners. Although these concepts are considered necessary to solve many of the existing global environmental and social challenges (e.g., climate change, nature conservation and social equity), it seems there is no consistency relating to their content. Some ...
In both sustainable development and circular economy research, the urgency of the issues under investigation often push the analyses of phenomena towards the solving of problems even before phenomena are fully understood. Under such circumstances it is important to take a precautionary approach (Komiyama and Takeuchi, 2006; Sala et al., 2015).
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In the second stage, a research framework is proposed to integrate Industry 4.0 technology (big data analytics powered artificial intelligence) adoption, sustainable manufacturing and circular economy capabilities.,This research extends the knowledge base by providing a detailed review of Industry 4.0, sustainable manufacturing, and circular ...
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The proposal is to answer the following question: based on previous studies, which are the new paths and challenges related to the circular economy (CE) and Industry 4.0 (I4.0)? To answer this question, the research objective is to analyze studies approaching the interface between CE and I4.0.
e circular economy: Preserve and enhance natural capital by controlling finite stocks and balancing the flow of. enewable resources. Optimize resource yields by circulating products, components, and materials in use at the highest possible. els at all times. Make the system more effective by eliminating ne.
A framework for a responsible circular economy. The move towards a Circular Economy (CE) from the perspective of a 'just transition' necessitates an approach which deems stakeholder knowledge and agency as central. Under this paradigm the transition to a CE is conceived not as a technocratic challenge, but as a process of socioeconomic ...
Circular economy (CE) initiatives are taking hold across both developed and developing nations. Central to these initiatives is the reconfiguration of core supply chain management (SCM) processes that underlie current production and consumption patterns. ... Finally, the paper presents a series of research proposals meant to encourage SCM ...
Ranjbari et al. (2021) examines the application of circularity in waste management, including the "closed loop" concept, up to 2020. Circular economy and closed-loop material cycles are deeply connected; however, the concept of closed-loop material cycles arose with the beginning of industrialization (Kara et al. 2022).
Tools and techniques for building research in a circular economy Life cycle assessment (LCA) and material flow analysis (MFA) are well established techniques for sustainability studies in the built environment which could both be extended to CE research. Genovese et al. (2015) adopted a hybrid LCA methodology in a study on sustainable
The proposal of an economy that is circular and without the need for material or energy input has an irresistible appeal to those who recognize the precautionary concept of planetary boundaries ...
Purpose -Circular economy (CE) initiatives are taking hold across both developed and developing nations. Central to these initiatives is the reconfiguration of core supply chain management (SCM ...
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The purpose of this project proposal is to outline a comprehensive plan for implementing circular economy initiatives to promote sustainable development. Circular economy aims to minimize waste generation, maximize resource efficiency, and create a regenerative economic system. By adopting circular practices, we can reduce environmental impacts, enhance resource productivity, and drive ...
The world's current model for economic development is unsustainable. It encourages high levels of resource extraction, consumption, and waste that undermine positive environmental outcomes. Transitioning to a circular economy (CE) model of development has been proposed as a sustainable alternative. Artificial intelligence (AI) is a crucial enabler for CE. It can aid in designing robust and ...
The development of regional circular economy, will have an adjustment of traditional industrial structure, increase research and development of environmentally sound technologies, and enhance the comprehensive competitiveness of the region. ... In order to collect these indicators, as part of the draft proposal for a Circular Economy Framework ...
Despite growing awareness of the need for sustainable solutions, research on implementing circular economy principles in plastic waste management remains insufficient, especially in the developing economies. In response to this research gap, this study aims to conduct a systematic literature review focusing on circular economy strategies for ...
The circular bioeconomy is an intersection of circular economy and bioeconomy in which these two concepts complement each other , resulting in a sustainable framework and contributing to resolving ...