Developing an Urban Circular Economy Framework Based on Urban Metabolism

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INOM

EXAMENSARBETE TEKNIK, GRUNDNIVÅ, 15 HP

,

STOCKHOLM SVERIGE 2020

Developing an Urban Circular

Economy Framework Based on

Urban Metabolism

SAGA STUGHOLM

KTH

SKOLAN FÖR ARKITEKTUR OCH SAMHÄLLSBYGGNAD

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Developing an Urban Circular

Economy Framework Based

on Urban Metabolism

SAGA STUGHOLM

Degree Project in Engineering in environment and energy, AL127X Date: June 3, 2020

Supervisor: Asterios Papageorgiou Examiner: Monika Olsson

School of Industrial Technology and Management

Swedish title: Utveckling av ett urbant ramverk för cirkulär ekonomi med grund i urban metabolism

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Abstract

There is an urgent need to transition to more sustainable cities and to do so we must identify in what ways and where cities are unsustainable. Urban metabolism offers a way to provide insight into how to move from linear to more sustainable, circular flows of energy and material in the urban area. Incorporating circular economy principles into the urban metabolism concept offers a promising way to reduce urban resource flows and increase the sustainability of the urban system. This thesis aims to combine an urban metabolism framework with circular economy indicators to create an urban circular economy framework, to support the transition towards more sustainable cities. This was achieved by identifying urban metabolism frameworks at the urban scale as well as several circular economy indicators, and then developing criteria for assessing them.

It was found that several of the urban metabolism frameworks lacked an inclusion of hinterlands and a life cycle perspective, but provided various approaches to the urban metabolism. Assessment of the identified circular economy indicators showed that there is a lack of flow-based indicators that evaluate the social dimension of sustainability. To assess this in an adequate way there is a need to develop flow-based circular economy indicators, or alternatively urban metabolism frameworks which incorporate the social aspects. Furthermore, there is a need to develop more evaluation criteria and a

categorisation for assessing the circular economy indicators. This would ensure that all sectors and some scales of delineation are addressed and provide a holistic understanding of the circular economy.

Still, a somewhat holistic view can be gained from the combination of several indicators, as shown in the circular economy framework developed in this thesis. The framework was developed by combining a multilevel urban metabolism framework with 17 of the selected circular economy indicators. Out of these, 16 could be applied directly to the multilevel framework and together they cover all assessment criteria for circular economy indicators. This new framework is extensive and can be used to evaluate circular economy from a sustainable point of view. However, it is not fully holistic since it does not cover all sectors and could use a larger set of indicators. Still, by providing an example of an urban circular economy framework, this thesis offers a step towards the development of urban circular economy frameworks.

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Sammanfattning

Det finns ett akut behov att övergå till mer hållbara städer, och för att kunna göra det måste vi identifiera på vilka sätt städer är ohållbara. Urban metabolism är ett koncept som ger insikt i hur det är möjligt att gå från linjära till mer hållbara, cirkulära flöden av energi och material i urbana områden. Integrationen av principer från cirkulär ekonomi i den urbana metabolismen erbjuder ett lovande sätt att minska urbana resursflöden och därmed öka städers hållbarhet. Denna uppsats kombinerar ett ramverk för urban metabolism med indikatorer för cirkulär ekonomi och skapar på så sätt ett ramverk för urban cirkulär ekonomi. Syftet med det nya ramverket är att kunna stödja övergången till mer hållbara städer. Detta uppnåddes genom att identifiera ramverk för urban metabolism på urban skala, samt flera indikatorer för cirkulär ekonomi, samt utveckla kriterier för att utvärdera dessa.

Det visade sig att flera av ramverken för urban metabolism inte behandlade påverkan på kringliggande områden och ett livscykelperspektiv, men gav olika tillvägagångssätt för att undersöka den urbana metabolismen. Utvärdering av de identifierade indikatorerna för cirkulär ekonomi visade att det saknas flödesbaserade indikatorer som bedömer den sociala dimensionen av hållbarhet. För att bättre kunna bedöma detta bör det utvecklas flödesbaserade indikatorer för cirkulär ekonomi, alternativt ramverk för urban

metabolism som integrerar de sociala aspekterna. Dessutom finns det behov av att utveckla fler utvärderingskriterier för att bedöma indikatorerna, samt en kategorisering av dessa. Detta skulle säkerställa att alla sektorer och vissa detaljnivåer av flöden tas upp och ge en bättre helhetsförståelse för den cirkulära ekonomin.

Utan dessa förbättringar kan dock ändå en något holistisk uppfattning erhållas från kombinationen av flera indikatorer, vilket visas i det skapade ramverket för cirkulär ekonomi. Ramverket utvecklades genom att kombinera ett flernivåigt ramverk för urban metabolism med 17 av de valda indikatorerna för cirkulär ekonomi. Av dessa kunde 16 tillämpas direkt på olika nivåer i nivåstrukturen från DPSIR Multilevel Framework.

Tillsammans täcker de alla bedömningskriterier för indikatorer för cirkulär ekonomi.

Detta nya ramverk är omfattande och kan användas för att utvärdera cirkulär ekonomi ur ett hållbarhetsperpektiv. Det är dock inte helt holistiskt eftersom det inte täcker alla sektorer och skulle kunna använda en större uppsättning indikatorer. Genom att ge ett exempel på ett ramverk för urban cirkulär ekonomi, erbjuder denna avhandling trots detta ett steg mot utvecklingen av ramverk för cirkulär ekonomi.

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Acknowledgments

First and foremost I want to acknowledge my supervisor, Asterios Papageorgiou, for all of his support and ideas. I also want to thank my Examiner, Monika Olsson, for making this thesis possible. Lastly, I want to thank my family and friends for their unlimited support and cheer when writing this thesis.

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List of Abbreviations

UM Urban Metabolism

CE Circular Economy

UMF Urban Metabolism Framework

DPSIRMF DPSIR Multilevel Framework MEF Modified Eurostat Framework

UMCF Urban Metabolism Characteristics Framework UMAn Urban Metabolism Analyst Framework

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Chapter 1 Introduction

Earth’s life-support systems are threatened by water, air and soil pollution, resource depletion, biodiversity loss, climate change and more (Rockström et al., 2009). These threats are causing challenges in economic, ecological and socio-technical systems. This, in turn, has developed a need to transition to more sustainable systems through

sustainable development (Geissdoerfer et al., 2017). Sustainable development is defined by the Brundtland Commission (1988) as "development that meets the needs of the present without compromising the ability of future generations to meet their own needs".

In the year 2018 about 55% of the world’s population lived in urban areas. This is expected to increase to 68% in 2050 (UNDESA, 2019). Cities are estimated to be responsible for 70% of the global greenhouse gas emissions, while taking up just about 2% of the world’s land (UNHSP 2011). Cities also account for 60-80% of global energy consumption, 75% of carbon emissions and more than 75% of the world’s natural

resource consumption (Swilling et al., 2013). The current rapid pace of urbanization is in itself posing a threat to urban areas, and a convergence of rapid urbanization and climate change can increase the magnitude of these threats (UNHSP 2011).

Seeing as urban areas account for a great environmental impact, making them more sustainable must be a priority. This is reflected in the UN Sustainable Development Goals (SDGs) where goal 11 is dedicated to sustainable cities and communities, and goal 12 is committed to ensuring responsible consumption and production (United Nations, 2015). The socio-technical systems are today so intertwined that policy efforts result in incremental rather than radical changes. This creates a situation where the measures taken are rather ineffective for coping with the current sustainability

challenges (Markard, Raven, and Truffer, 2012), signalling a need to intervene in the right places to achieve a sustainable transition.ne

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2 CHAPTER 1. INTRODUCTION

One method or process to help identify the challenges and possibilities for urban

sustainability is urban metabolism (UM). By observing an urban area as an organism or an ecosystem from a system approach it is possible to effectively quantify flows of material and energy to, from and within a city (Zhang, Yang, and Yu, 2015; Musango, Robinson, and Currie, 2017). Analysing these flows can give information on how to move from linear to more sustainable, circular flows.

According to Kalmykova and Rosado (2015) integrating circular economy principles (CE) into the UM is one of the most promising ways to reduce urban resource flows and their environmental impacts, as well as a factor for a sustainable UM. The European Environment Agency (2016) argues that a more circular economy in Europe would provide more benefits than only limiting the environmental impact. It would also improve resource use, the environment, the economy and social aspects (job creation, consumer patterns and similar). However, CE principles have in general been applied on the product or company level (Elia, Gnoni, and Tornese, 2017; Mayer et al., 2019) and few UM studies have incorporated CE (Kalmykova and Rosado, 2015), leaving a knowledge gap on the use of UM and CE principles at the urban level. By combining these principles it should be possible to achieve an urban CE framework which can investigate both the urban metabolism and circular economy, closing the knowledge gap.

1.1 Background

1.1.1 Urban Metabolism

Urban Metabolism (UM) does not have any universally accepted definition but one commonly used is the one by Kennedy, Cuddihy, and Engel-Yan (2007): "sum total of the technical and socio-economic processes that occur in cities, resulting in growth, production [and use] of energy, and elimination of waste". This definition has been expanded by several authors to provide a more holistic understanding of UM (Newell and Cousins, 2015; Currie and Musango, 2017). The expanded definition by Currie and Musango (2017) will be used for this thesis to better quantify environmental and

sustainability effects of the UM, and is as follows: "collection of complex socio-technical and socio-ecological processes by which flows of materials, energy, people, and

information shape the city, service the needs of its populace, and impact the surrounding hinterland". This definition has been adopted by amongst others UN Environment in their report on UM (Musango, Robinson, and Currie, 2017).

It is common to use some sort of resource flow study, such as a Material Flow Analysis

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CHAPTER 1. INTRODUCTION 3

(MFA) or Input-Output analysis (I/O), when analysing a UM. However, these methods have mainly been used on a national or even international level (Currie and Musango, 2017; Mayer et al., 2019). Furthermore, when Musango, Robinson, and Currie (2017) analysed 165 UM assessments only one-third of them studied cities in the global south and out of those a majority concerned China. Musango, Robinson, and Currie (2017) suggests that a bottom-up approach, instead of the currently more common top-down, or a combination of both could benefit cities in the global south where data scarcity often is an obstacle for UM assessments.

Data scarcity is one of the four main challenges when analysing a UM (Currie and Musango, 2017) and is also a problem in the global north since material flow data often is available only on the national scale (Musango, Robinson, and Currie, 2017). The other three main challenges are summarised by Currie and Musango (2017) as: tracking informal flows, a lack of standardised methods for urban resource flow assessment and that urban systems are open systems.

Urban Metabolism frameworks operate on a standard model of thought where an urban system has inputs and outputs. This standard model can be seen in Figure 1.1.

Depending on the level of detail of the urban flows, three modelling strategies can be distinguished (Beloin-Saint-Pierre et al., 2017). The Black Box model only has

information on inflows and outflows. The Gray Box model is slightly more complex and disaggregates the inflows and outflows for different components (e.g. buildings, parks, services, etc.). The Network model extends the Gray Box model by disaggregating the inflows and outflows for different components and describing the links between them (Beloin-Saint-Pierre et al., 2017). See Table 1.1 for a summary of the benefits and drawbacks of each modelling approach.

Inputs EnergyMass

Urban System

Outputs EnergyMass

Figure 1.1: Basic model of a UM framework.

1.1.2 Circular Economy

Circular economy (CE) is a concept which has gained momentum since the 1970s (EMF, 2013). There are numerous definitions of CE (Geissdoerfer et al., 2017; Kirchherr, Reike, and Hekkert, 2017), but the general idea is to create circular flows by closing loops. There are two types of loop closings in a CE: socioeconomic and ecological loop

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Table 1.1: Benefits and drawbacks of different UM modelling approaches. Source (Beloin- Saint-Pierre et al., 2017).

Approach Benefits Drawbacks

Black Box Less data required, useful for

long time-series. No information on flows inside the urban system.

Gray Box Some understanding of internal

flows. No information on links between

components.

Network model Can inform on environmental im-

pact for each component. Requires more data, challenging implementation.

closings (Mayer et al., 2019). The socioeconomic loop closings are made by using waste material as raw material (and thereby minimizing the flow of absolute waste), the

ecological loop closings are made by using renewable biomass.

The European Union (EU) sees creating a circular economy as necessary for higher resource efficiency, as well as a promoting measure to achieve sustainable economic growth (COM, 2014). Major economical benefits are expected from integrating CE principles into the EU economy. The Ellen MacArthur Foundation (EMF) estimates that CE principles could increase the EU resource productivity by 3% annually, resulting in a total annual benefit of €1.8 trillion and a 48% reduction of CO2emissions by 2030, compared to a €0.9 trillion benefit and 31% reduction, respectively, on the current development path for Europe (EMF, 2015).

The EMF definition is widely used to define a circular economy: "an industrial economy that is restorative or regenerative by intention and design" (EMF, 2013). The European Environmental Agency (EEA, 2016) has also defined CE but as an economy including waste management, waste prevention and resource efficiency, excluding ecosystem resilience and human well-being. Thus, the implementation of a circular economy does not necessarily guarantee achieving a resilient and green economy. As shown by Haupt and Hellweg (2019) the environmental perspective is often not assessed in CE strategies since the strategy often is considered to reduce environmental impact by default.

However, that is not always the case which is why a holistic view on CE strategies is important to avoid making counterproductive decisions (Haupt and Hellweg, 2019).

Based on previous literature Corona et al. (2019) proposes the following eight requirements to ensure a holistic assessment of a CE:

1. Reducing input of resources, especially scarce ones

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CHAPTER 1. INTRODUCTION 5

2. Reducing emission levels (pollutants and GHG emissions) 3. Reducing material losses/waste

4. Increasing input of renewable and recycled resources 5. Maximising the utility and durability of products 6. Creating local jobs at all skill levels

7. Value added creation and distribution 8. Increase social wellbeing

These eight requirements are based on the CE definition by Kirchherr, Reike, and Hekkert (2017). They studied 114 definitions of CE and synthesised them into one comprehensive definition which will be used in this study: "an economic system that replaces the ‘end-of-life’ concept with reducing, alternatively reusing, recycling and recovering materials in production/distribution and consumption processes. It operates 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, thus simultaneously creating environmental quality, economic prosperity and social equity, to the benefit of current and future generations. It is enabled by novel business models and responsible consumers".

Circular economy indicators (CE indicators) can be used to assess progress towards a CE. There is yet no widely accepted monitoring framework to do this (Parchomenko et al., 2019), resulting in numerous CE indicators without a standardized approach. In a review of 55 CE indicators by Saidani et al. (2019) only 1 was explicitly made for assessing progress on an urban scale.

1.2 Aim and Objectives

This thesis aims to investigate the possibility of creating circular economy frameworks to support the transition towards more sustainable cities. More specifically through

combining urban metabolism frameworks and circular economy indicators.

The objectives of the study follows:

1. Identify different established applied and theoretical UM frameworks as well as urban level CE indicators.

2. Establish criteria for evaluating the potential and limitations of said CE indicators and UM frameworks on an urban scale, with a focus on sustainability aspects.

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3. Create a comprehensive assessment of CE indicators and UM frameworks and their suitability at the urban level.

4. Create an example of a CE framework by combining a UM framework with CE indicators.

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Chapter 2 Method

The methodology of this thesis can be roughly divided into the five steps seen in Figure 2.1: (1) Initial reading and positioning on key terms such as UM and CE, (2) selection of UM frameworks and CE indicators, (3) development of evaluation criteria for UM frameworks and CE indicators, (4) assessment of UM frameworks and CE indicators by use of developed criteria, and lastly (5) the construction of a CE framework through combining the most suitable UM framework and CE indicators.

Saidani et al. (2019) argues that the term "circular economy" should be explicitly defined due to the many different and ambiguous definitions. This also applies to "urban

metabolism". The definitions used in this thesis is, as previously stated, the one from Kirchherr, Reike, and Hekkert (2017) for circular economy and from Currie and Musango (2017) for urban metabolism. Note that both these definitions include sustainability, which is key to create a CE framework that can support the transition towards more sustainable cities. The use of other definitions such as that proposed by Kennedy, Cuddihy, and Engel-Yan (2007) for UM would not ensure the integration of sustainability.

The UM frameworks and CE indicators to be assessed can be found in Table 3.1 and 3.3 respectively. The UM frameworks were selected based on their different approaches to urban metabolism. Only evaluating a few frameworks is a limitation of this study. The CE indicators were selected from reviews or compilations of CE indicators. Using a smaller number of reviews to identify indicators is also a limitation of this study. There are several hundred different CE indicators (Geng et al., 2012; Fusco Girard and Nocca, 2019), therefore screening criteria were developed to choose the most relevant for this study. The criteria developed were firstly for the indicator to be constructed for the urban scaleand secondly for the indicator to provide quantitative information on material and

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8 CHAPTER 2. METHOD

Initial Step Initial Reading

Positioning on CE & UM

−→

Selection UM frameworks CE indicators

−→

Development Criteria UM

Criteria CE Indicators

−→

Assessment UM frameworks CE indicators

−→

CE Framework

Based on previous assessment Analyse strengths/weaknesses Figure 2.1: Workflow and research process of the thesis

energy flows. These screening criteria were developed with the motivation that they together capture the essential characteristics of a UM, an urban framework based on energy and material flows. From this screening approximately 60 indicators were found, however, some were measuring the same thing. From the identified indicators a selection of 33 distinctive indicators was made, the full selection is presented in Table 3.3.

The indicators and frameworks will be evaluated on how well they asses UM and CE respectively through a set of defined criteria. These criteria will be based on the previously stated definitions and relevant literature on circular economy and urban metabolism, again with a focus on including sustainability. Once assessed the most suitable UM framework will be developed into a CE framework by the implementation of suitable CE indicators.

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Chapter 3 Results

3.1 Identified Urban Metabolism Frameworks

The 5 selected frameworks can be seen in Table 3.1 and specifics are presented in their respective subsection below.

Table 3.1: Identified UM frameworks and their sources

Name of framework Source

Urban Metabolism Framework (UMF) (Ferrão and Fernández,

2013)

DPSIR Multilevel Framework (DPSIRMF) (Ferrão and Fernández, 2013)

Modified Eurostat Framework (MEF) (Voskamp et al., 2017) Urban Metabolism Characteristics Framework (UMCF) (Rosado, Kalmykova, and

Patrício, 2017)

Urban Metabolism Analyst Framework (UMAn) (Rosado, Niza, and Ferrão, 2014)

3.1.1 Urban Metabolism Framework (UMF)

The Urban Metabolism Framework (Ferrão and Fernández, 2013) is a conceptual UM framework based on energy and material flows of urban activities rather than economic sectors. The three kinds of focus activities for this framework is the provision of:

habitable space, goods and services and the movement of goods and people. These urban

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10 CHAPTER 3. RESULTS

activities are broadly defined at the mesoscopic and macroscopic levels (not on the individual level). Some of the most important services provided include air, water, food and waste removal.

This framework is a simplified model of a UM and it is therefore not possible to expect that it will capture everything. However, the authors argue that a simplified model like this are useful by illustrating mainly four things: (1) energy and material flows from urban socioeconomic activities, (2) relationships of biogeochemical processes, (3) interactions between socioeconomic and biogeochemical activities and (4) how to delineate critical positive or negative behaviours of the urban zone (Ferrão and Fernández, 2013).

The Urban Metabolism framework is based on a standard UM framework model such as the one seen in Figure 1.1. The inputs and outputs are classified into active and passive, passive being, for example, water and air and active being, for example, energy and biomass.

3.1.2 DPSIR Multilevel Framework (DPSIRMF)

The DPSIR Multilevel Framework (DPSIRMF) is a combination of two frameworks suggested by Ferrão and Fernández (2013): the DPSIR framework and the multilevel framework. Both frameworks are first described individually and then together.

Drivers Population Climate

Urban Activites

Pressures Energy Materials Land Use Emissions

State Urban Env.

Regional Env.

Global Env.

Impact Urban Quality Env. Services

Response

Figure 3.1: Outline of the DPSIR framework adapted from Ferrão and Fernández (2013).

Env. = Environment

DPSIR stands for Drivers, Pressure, State, Impact and Response. The purpose of the DPSIR framework is to properly integrate human-ecological interactions and urban ecosystems, since one or the other is often too simplified to represent accurate system dynamics (Ferrão and Fernández, 2013). The outline of the DPSIR framework and the

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CHAPTER 3. RESULTS 11

relationship between the factors can be seen in Figure 3.1. The thought behind DPSIR can easily be explained by a very simplified example: urban consumption (D) drives pressure in terms of emissions from manufacturing (P). These pressures, in turn, changes the state of the environment by polluting the air (S). Higher air pollution impacts the health of people (I) and the society responds by for example implementing policies on emission limits (R affecting P) or by recommending the wear of protective masks (R affecting I). The response can address any or all of the D, P, S and I factors. Furthermore, one driver may have many pressures which can have several state changes and so on.

The key to a successful application of the DPSIR framework is to quantify each D, P, S, I and R element as well as their connections. This is a demanding task which requires data. Ferrão and Fernández (2013) have some suggestions on how to achieve that. The DPSIR framework allows the inclusion of hinterland, or regional and global state. The authors note that a successful framework is one that provides support for policy-making.

The DPSIR framework has five purposes, listed as: (1) systematic identification of urban sustainability dimensions, (2) monitoring of the evolution and interaction of the major indicators, (3) target setting, (4) evaluation of the efficiency of adopted policies, and (5) public information and communication.

The multilayer UM framework has seven layers: (1) urban bulk mass balance, (2) urban materials flow analysis, (3) product dynamics, (4) material intensity of economic sectors, (5) environmental pressure of material consumption, (6) spatial location of resource use and (7) transportation dynamics (Ferrão and Fernández, 2013). By integrating the dimensions of the DPSIR framework into the multilayer one it should be possible to better define the relationship between the DPSIR elements. Table 9.9 in Ferrão and Fernández (2013) suggests how to incorporate DPSIR elements in each layer in the multilevel framework. For each layer they also suggest tools, methods, sources as well as data inputs and outputs for achieving an evaluation of said layer. Furthermore, Ferrão and Fernández (2013) suggest that national material flow data could be allocated to the urban or regional level through the use of population and business data.

3.1.3 Modified Eurostat Framework (MEF)

The Modified Eurostat Framework (MEF) is based on an urban application of the European Economy Wide MFA or Eurostat method by Eurostat (2001) which is

originally intended for use on the national scale. The Eurostat method was adapted and applied to the urban scale by Hammer et al. (2003). Several deficiencies of this urban Eurostat method were found, more notably the exclusion of drinking water and

wastewater flows, the black box character and the exclusion of renewable energy (only

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fossil fuels were accounted for). Therefore this method was extended and modified by Voskamp et al. (2017) to achieve a more comprehensive analysis of a UM, creating the MEF. The following modifications to the Hammer et al. (2003) method were made:

• Inclusion of drinking water and wastewater flows.

• Accounting of stormwater and groundwater which enters the sewers.

• Incorporation of renewable energy (local sourcing, import, export).

• Categorization of waste according to its origin, type, process and location of treatment.

• Incorporation of recovered materials and energy from waste as a local sourcing category.

• Classification of import and export flows in less aggregated categories.

• Analysing of throughput flows.

Through the less aggregated categories as well as the introduced flows a more

comprehensive understanding of the UM can be found. Something to note is especially the inclusion of water flows which are otherwise often left out. Also note the delineation of throughput flows, meaning the high level of detail with which flows that pass through the urban system are described. If these throughput flows are not specified they add to the consumption flows, creating a false understanding of the material consumption. To develop this extension of the urban Eurostat framework Voskamp et al. (2017) performed both a literature review and stakeholder consultations, the latter especially leading to the development of the accounting of stormwater and groundwater which enters the sewers.

3.1.4 Urban Metabolism Analyst Framework (UMAn)

The Urban Metabolism Analyst Framework (UMAn) by Rosado, Niza, and Ferrão (2014) is an urban application of the Eurostat method from Eurostat (2001) which is based on the Material Flow Accounting (MFA) method. The Eurostat method was, as previously mentioned, developed for use on the national scale and includes a defined set of

indicators and five classes of materials. Rosado, Niza, and Ferrão (2014) identified several flaws with the method when downsizing it to the urban scale, the most prominent one being that material flows are overly aggregated. For example, the Eurostat class fossil fuels includes both fuels and plastic, meaning that plastic flows cannot be identified for recycling.

The authors identified in total seven general knowledge gaps with urban applications of the MFA method including the general black box characteristic, a lack of data on urban material flows and the large aggregation of flows. To overcome these gaps the following four actions were taken in UMAn:

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• Establishing 28 distinctive material types to account for in flows, aggregated into six classes of flows.

• Disaggregating data both spatially and by economic sector as well as addressing the life cycle phase of products.

• Include information on product lifespan to gain more understanding on the accumulation of material.

• Separating export and input flows from flows which just pass through the system, here referenced to as "cross flows".

UMAn uses top-down Eurostat standard statistical data for products which increases the data availability, the authors also suggest sources for data and some relations that can be used to scale data from national to urban scale. They also created databases on the material composition of products, the average lifespan of products and one which identifies the current life cycle phase of each product (is it livestock, raw material, an intermediate product, a final product, or waste?) (Rosado, Niza, and Ferrão, 2014). All these measures are helpful when addressing the issue of lack of data, however, these are all based on European data and the UMAn framework is therefore mainly suitable at the European level.

3.1.5 Urban Metabolism Characteristics Framework (UMCF)

The Urban Metabolism Characteristics Framework (UMCF) was developed by Rosado, Kalmykova, and Patrício (2017) and is based on the UMAn model by Rosado, Niza, and Ferrão (2014). The authors have extended the UMAn model by adding eight UM

characteristics based on combining indicators from the UMAn, see section 3.1.4 for more details. These characteristics aims to allow an identification of different UM profiles to provide more insight into the UM. The eight characteristics can be listed as:

• Needs

• Accumulation

• Dependency

• Support

• Efficiency

• Diversity of Processes

• Self-Sufficiency

• Pressure on the Environment

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Needsaims to assess the total material needs connected to the final consumption needs of an urban area. It could be used as policy support for resource management policies.

Accumulationassesses the accumulation of materials in an urban area. This

characteristic can be used for information on the potential amount of materials to be recycled, providing an effective opportunity for urban mining ("reuse of urban stock"

(Currie and Musango, 2017)). Efficiency is assessed as the share of the material consumption that is recovered through recycling, reuse, energy recovery or biological treatment. When the efficiency of a UM increases the material needs decrease, meaning that this characteristic can provide insight into possibilities for economic growth.

Diversity of Processesis a characteristic which is based on the similar behaviour of an urban system to an ecosystem. A diverse ecosystem is more resilient and the authors argue that the same applies for urban systems. This characteristic can therefore indicate how resilient an urban area is. The Support characteristic is using the amount of exports to assess how the investigated urban area supports other systems by meeting their needs.

The Dependency characteristic is a measure of the opposite, in other words how dependant on other systems the urban area is. This can also be seen as how vulnerable the area is. Self-Sufficiency compares available local resources (stock and extraction) with the amount of material consumption to assess the Self-Sufficiency of an urban area.

Pressure on the Environment is divided into two components: outputs to nature and contribution to depletion of resources. The outputs to nature estimates the environmental pressure caused by the amount and types of material output from the system. The

depletion component assesses the share of renewable material of the material input.

3.2 Assessment Criteria for Urban Metabolism

Frameworks

The assessment criteria for UM frameworks were found from literature, focusing on the urban scale and sustainability. The criteria are presented in Table 3.2 as well as described more thoroughly below.

The first criterion, that the framework is dynamic and not static, was found from (Beloin-Saint-Pierre et al., 2017). The authors argue that a static number is not useful and that a comparison over time is necessary to get information on improvement. This is especially important when taking sustainability evaluations into account, an isolated number on for example carbon dioxide emissions might not be as telling, or useful as policy support, as a comparison over time.

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Table 3.2: Assessment criteria for UM frameworks and their sources. Y= yes, N = no, P

= possibly or partially, H = high, M= medium, L = low.

Criteria Evaluation Source

Dynamic? Y/N/P (Beloin-Saint-Pierre et al., 2017)

Includes Hinterlands? Y/N/P From definition

Opens the Black Box? Y/N/P (Ferrão and Fernández, 2013) Support for Policy-making? Y/N/P (Ferrão and Fernández, 2013) Life Cycle Phase of Flows? Y/N/P (Rosado, Niza, and Ferrão, 2014) Top-down or Bottom-up? Top/Bottom/Both

Data Availability? H/M/L (Ferrão and Fernández, 2013)

Ease of Application? H/M/L

The second criterion is the inclusion of the impact the urban area has on the surrounding hinterland. This criteria was developed directly from the (Currie and Musango, 2017) definition used in this study, which explicitly mentions including the hinterlands. This criteria is, however, also supported by (Beloin-Saint-Pierre et al., 2017). The spatial limitation is a key question for urban metabolism frameworks and without including the hinterlands the information from the UM framework would not assess the urban

sustainability comprehensively.

The third criterion is the characteristic of the framework, as discussed in Section 1.1.1.

For a complete assessment of the sustainability of a UM, it is not enough to evaluate only inflows and outflows (black box character) (Ferrão and Fernández, 2013;

Beloin-Saint-Pierre et al., 2017).

The fourth criterion is based on the discussion by Ferrão and Fernández (2013) on the usefulness of the UM framework. They claim that the ultimate success of a UM framework is found when policymakers can use the information from it (more specifically having "the ability to act upon feedback loops") for a more informed policy-making. This criterion is assessed based on if explicit consideration to policy support has been taken in developing the framework.

The Life Cycle Phase criterion is based on a knowledge gap on the origin and destination of flows in UM studies (Rosado, Niza, and Ferrão, 2014). By characterising the life cycle phase of flows it would be possible to identify the origin of flows, the transformation of

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material in the urban system and their end of life destination (Rosado, Niza, and Ferrão, 2014). The authors argue this information is crucial as policy support for achieving more sustainable flows.

The Top-down or Bottom-up criterion is not as straight forward as the other UM framework criteria, but still important information for implementing a framework. A general discussion can be found in literature on the preferred use of data collection (Ferrão and Fernández, 2013; Currie and Musango, 2017; Musango, Robinson, and Currie, 2017). One common argument for Top-down data is that the data is easily accessible from for example national databases (Ferrão and Fernández, 2013). One argument against it is that frameworks based on Top-down data will only be applicable in the global North since comprehensive databases on material and energy flows are not commonly found for countries in the global South. One common argument for the use of Bottom-up data is that it is more detailed and more accurate than scaling down data from the national or regional scale to the urban scale (Currie and Musango, 2017). The main argument against it is that it is very resource-intensive (Currie and Musango, 2017).

Data Availabilityis one of the main obstacles when assessing the UM of a city (Ferrão and Fernández, 2013). This criterion will be evaluated on a scale from high to low depending on whether the authors have discussed possible strategies or sources for data collection or not when presenting the framework. For example, a framework solely based on the Eurostat dataset will have a high data availability while one which requires several databases and lack of data was acknowledged when presenting the framework will have medium or low data availability depending on the scale of these issues.

The last criterion, Ease of Application, is also evaluated on a scale from high to low. A black box characteristic framework will, for example, be easier to apply than one with a network characteristic which is the most difficult. This criterion also takes into account how "ready to implement" the presented frameworks are. A conceptual framework without an outline of specifically which flows to assess and how is harder to apply than a case study where the authors have presented how to scale down data, how to weigh flows and similar.

3.3 Identified CE Indicators

The 33 identified CE indicators are presented in Table 3.3. The indicators are categorised under the three subcategories of sustainable development: environmental, economical and social. As can be seen from Table 3.3 a majority of the indicators fall under the environment category, a few under the economical and none under the social. To enable a

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holistic assessment of the circular economy and its sustainability an extended selection of CE criteria was made based on the same source documents. For this second selection, the screening criteria of providing quantitative information on material and energy flows was not used. The additional economic and social CE indicators are presented in Table 3.4.

Table 3.3: Identified CE indicators, their units and sources. [1] = Fusco Girard and Nocca (2019), [2] = Geng et al. (2012), [3] = Wang et al. (2018). * in the unit field means that the unit is either not presented or clear from the source.

Nr Name of Indicator Unit Source

Environmental

1 Annual amount of greenhouse gas emissions tons/year [1]

2 Percentage of reduction of greenhouse gas

emissions %/year [1]

3 Air pollution and greenhouse gas emissions

associated to transport Tons/year [1]

4 Recycling rate of municipal waste %/year [1]

5 Percentage of household waste reused or re-

cycled %/year [1]

6 Amount of resources saved * [1]

7 Amount of recycled resources * [1]

8 Amount of reused resources * [1]

9 Amount or percentage of recycled material Tons/year or %/year [1]

10 Amount or percentage of products reused Tons/year or %/year [1]

11 Amount or percentage of products recovered Tons/year or %/year [1]

12 Average amount of materials retained in the

cycle per citizen per year Kg/year [1]

13 Amount or percentage of waste separation Tons/year or %/year [1]

14 Percentage of recycling of the solid waste gen-

erated in the city %/year [1]

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Table 3.3 (continued)

Environmental

15 Percentage of recycle of packaging waste %/year [1]

16 Water efficiency (water issues regarding its

treatment and distribution) * [1]

17 Absolute (kWh) and relative (%) reduction of

yearly electricity consumption kWh/year or %/year [1]

18 Percentage of renewable or recycled energy

use %/year [1]

19 Renewable energy production on total energy

production MWh/year/total [1]

20 Fossil-fuel-free transport sector % [1]

21 Low-impact and non-toxic materials used in

production processes % [1]

22 Percentage of incoming/outgoing flows %/year [1]

23 Tonnage of waste diverted via repair, reuse,

recovery and upcycling activities Tons/year [1]

24 Amount of waste produced in the city Tons/year [1]

25 Amount or percentage of waste avoided Tons/year or %/year [1]

26 Primary resources used Tons/year [1]

27 Recycling rate of wastewater % [2]

28 Safe treatment rate of municipal rubbish % [2]

Economical

29 Resource usage: total raw material productiv-

ity GDP/tons of input [1]

30 Environmental costs (costs of exhaustion, water pollution, CO2-emissions, toxicity and land use in € per kilogram)

GDP/tons of input [1]

31 Water resources productivity (yuan/ton) [3]

32 Resource productivity (yuan/ton) [3]

33 Energy productivity (yuan/ton) [3]

Social

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Table 3.4: Extended identification of CE indicators in the social and economic dimension and their units. [1] = Fusco Girard and Nocca (2019)

Economical

34 Sustainability of investments from the munici-

pality €/year [1]

35 Gross value added €/year [1]

36 Revenue from recycled goods sold €/month or €/year [1]

37 Potential value of the material after recovery/re-

use € [1]

38 Money saved (in a year) for average household due to reducing the amount of products thrown away

€/year [1]

39 Value of re-usable or recyclable used goods sent

to landfill € [1]

Social

40 Public transport usage % [1]

41 Proportion of green and recreational areas per

capita % [1]

42 Number of new green jobs N./year [1]

43 Percentage of new jobs related to the circular

economy % [1]

44 New businesses that have integrated circularity

into their development process N./year or %/year [1]

45 Percentage of population that shows an increase

in circular behaviour % [1]

3.4 Assessment Criteria for Circular Economy

Indicators

The assessment criteria for CE indicators were found in literature, more specifically the eight validity requirements developed by Corona et al. (2019). The authors constructed these criteria were found through a literary review with a foundation in a sustainability perspective on CE and are presented both in Section 1.1.2 and Table 3.5. The first five criteria (reducing input, reducing emission, increasing renewable input, and maximising

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utility and durability) evaluate the environmental scope of the indicators and the last three (job creation, value added, increasing social wellbeing) the economic and social scope. Together they can, therefore, cover the whole sustainability perspective of CE as embraced by the CE definition used in this thesis.

Table 3.5: Assessment criteria for CE indicators. The criteria are taken from (Corona et al., 2019). Y= yes, P = possibly

Criteria Evaluation

Reducing input of resources, especially scarce ones Y/P Reducing emission levels (pollutants and GHG emissions) Y/P

Reducing material losses/waste Y/P

Increasing input of renewable and recycled resources Y/P Maximising the utility and durability of products Y/P

Creating local jobs at all skill levels Y/P

Value added creation and distribution Y/P

Increase social wellbeing Y/P

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Chapter 4 Discussion and Analysis

4.1 Assessment of Urban Metabolism Frameworks

A comprehensive assessment of the UM frameworks can be found in Table 4.1. The frameworks are discussed individually in the respective subsection below. A general discussion can be held on the level of detail, the wideness of scope and ease of

application. For this thesis, a wider scope has been chosen to enable the integration of a holistic sustainability perspective. As presented in Section 3.2 a black box model has for example been deemed less useful than other models because of its lack of detail.

However, it is also this less detailed approach which makes it easier and less

resource-intensive to implement. This, in turn, provides an opportunity to assess a UM more often and enable a dynamic view of the UM through a comparison over time.

In other words, there is a conflict between the level of detail and the ease of application which is important to address. There are different approaches to take in this matter, however, due to the importance of a holistic perspective of sustainability in this thesis the sustainability assessment will be deemed more important than the ease of application.

Another important general point to lift is the scale of applicability of the frameworks.

MEF, UMCF and UMAn are all more or less based on the Eurostat method which is in turn based on European data. This implicates that an application of said frameworks on a non-European framework would prove challenging. In this thesis a European focus will not affect the ease of application criteria negatively.

21

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22 CHAPTER 4. DISCUSSION AND ANALYSIS

Table4.1:EvaluationofUMframeworksfromdevelopedcriteria.NS=notspecified.

Nameofframe-work DynamicIncludesHinter-lands OpenstheBlackBox LifeCy-clePer-spective SupportforPolicyMaking DataAvail-ability Top-downorBottom-up? Easeofapplica-tion Source UMFPossiblyNoYesNoYesMediumNSMedium(FerrãoandFer-nández,2013)DPSIRMFPossiblyYesYesYesYesMediumTop-down Hard(FerrãoandFer-nández,2013)MEFPartiallyNoPartiallyNoYesMediumBothMedium(Voskampetal.,2017)UMCFPartiallyNoYesNoYesMediumTop-down Medium(Rosado,Kalmykova,andPa-trício,2017)UMAnPartiallyNoYesYesYesHighTop-down Medium(Rosado,Niza,andFerrão,2014)

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CHAPTER 4. DISCUSSION AND ANALYSIS 23

4.1.1 Urban Metabolism Framework (UMF)

The UMF is a conceptual framework, meaning that there has not been an application of the framework in an urban area. This makes it harder to properly assess since all details of the framework are not explicitly explained, such as what kind of data would be used for the framework. Furthermore, the authors do not specify what kind of material flows are included to a greater extent than "material imports. At the same time, it is a simple model of a UM framework which has both benefits and drawbacks as briefly presented in the Results. By being based on urban activities rather than economic sectors this

framework presents another approach than the others. Perhaps the delineation of three of the most important services of an urban area combined with a simple framework can offer a balance between the level of detail and ease of application. Yet, the ease of application is assessed as medium both due to the delineation of flows as well as an uncertainty regarding what an actual application would look like.

The authors involve policy support in their description of the framework and also state that a simple framework like the UMF is useful for illustrating factors of the UM and their positive and/or negative effect, which is directly applicable as policy support. The UMF is not a black box model but rather a grey box model since biogeochemical cycles and the urban activities, as well as their interactions, are delineated in the system. Even though no direct information on data sources is given the data availability is assessed to be medium since there is more details than in a black box model. By using retroactive data the UMF could provide a dynamic view of the UM, since no data sources or strategies were mentioned however this criteria is assessed as possibly.

4.1.2 DPSIR Multilevel Framework (DPSIRMF)

The DPSIRMF is the most comprehensive and also most complicated framework

analysed in this thesis. It offers a holistic view of material and environmental dimensions of a UM and integrates policy support in all layers. The authors are clear with that the DPSIRMF should be based on available statistical data and offers examples and methods for downscaling and obtaining data to a larger extent than most of the analysed

frameworks. Due to the large scope of the framework, the data availability is however still assessed as medium.

By combining the two frameworks the DPSIRMF promises not only an assessment of flows on different levels through the multilevel framework, but also their interactions and feedback loops through the DPSIR framework. The black box is therefore opened and this framework is based on a network model because of all the connections between inner

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flows. Furthermore, the framework has an entire layer dedicated to accounting for the environmental pressure of the urban metabolism. Because of the large scope, network characteristic and possible integration of both hinterlands but also global impact the application of this framework was assessed as hard.

4.1.3 Modified Eurostat Framework (MEF)

The MEF is based on the Eurostat method which is a black box model. However, the inclusion of local sourcing of secondary resources, such as waste as an energy source as well as delineation of flows means that the MEF has more of a, but not fully a, grey box characteristic. The framework uses partly retrospective data, but some of the data is year specific which is why it is assessed as partially dynamic. It should be an effective

approach to look for gaps in one method and then develop another which closes those gaps, as the authors did when creating the MEF. It is the only assessed framework that actively uses both bottom-up and top-down data collection which is seen as an advantage here given previous discussions. However, to achieve a holistic view of a sustainable UM this framework is missing an inclusion of hinterlands as well as a life cycle perspective.

Using Eurostat data this framework should have a high data availability, but because of the extension of the model more data is needed. The authors could have had a more detailed discussion on how to provide this data and the thus data availability is assessed as medium. Some advantages of this framework are mainly the delineation of throughput flows, which is not as explicitly made in several of the other analysed frameworks, but also the inclusion of water flows.

4.1.4 Urban Metabolism Characteristics Framework (UMCF)

The UMCF does not include water. This can be deemed as a weakness given the mass of the water flows in an urban area. Furthermore, it is worth noticing that the efficiency characteristic can be misleading since energy recovery is less superior than recycling and reuse from a circular economy perspective (Rosado, Kalmykova, and Patrício, 2017). By delineating the local resources and resilience of an urban system the UMCF opens up the black box and is based on a grey box model. The political dimension is clearly integrated into the framework from the needs characteristic.

By using standard Eurostat top-down data there is an opportunity for using retrospective data and provide a dynamic view of the urban flows, however, this is not specifically

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discussed by the authors. Because of the Eurostat data, the data availability was at first assessed as high, but given the delineation and data need of the eight characteristics it was assessed as medium. The ease of application was assessed as medium given that the authors thoroughly explained the process and made an applied example of the framework through a case study.

4.1.5 Urban Metabolism Analyst Framework (UMAn)

The UMAn provides an elaborate method on how to obtain and downscale data through presenting both created databases and useful relations. The combination of this

information and the usage of the Eurostat database motivates an assessment of data availability as high. The framework delineates flows from the Eurostat method and disaggregates data to such an extent that it is based on a grey box model. It has a large focus on creating a life cycle perspective both by addressing life cycle phase and product lifespans. Thus it has the most details on a life cycle perspective of all the analysed frameworks.

Policy support is not discussed by the authors and hinterlands are not included in the framework. These are clear disadvantages for assessing the sustainability of a UM.

However, this framework has been developed and used as policy support (Eliasson and Johnsson, 2018). Furthermore, the UMAn delineates throughput flows which is an advantage since not doing so provides a false view of the urban consumption. By using established Eurostat categories and methods and expanding them the ease of application is assessed as medium.

4.2 Assessment of Circular Economy Indicators

A comprehensive assessment of all the selected CE indicators against the developed criteria can be found in Table 4.2. As can be seen in the table few indicators cover more than three criteria and one single indicator therefore cannot provide a holistic

understanding of CE. A combination of indicators could be a way forward to provide a more complete view of the CE, this approach is attempted in Section 4.3. By combining indicators based on the assessment made it is possible to include all the developed criteria.

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Table4.2:EvaluationofCEindicatorsfromdiscussedcriteria.Y=yes,blank=no,P=possibly.Theextendedindicatorsbeginatthedashedline

#NameResour-ces Emiss-ion WasteRen.share UtilityJobsValueAdded Socialwell-being1Annualamountofgreenhousegasemissions Y 2Percentageofreductionofgreen-housegasemissions Y 3Airpollutionandgreenhousegasemissionsassociatedtotransport Y 4RecyclingrateofmunicipalwasteYYY5Percentageofhouseholdwastereusedorrecycled YYY

6AmountofresourcessavedYYY7AmountofrecycledresourcesYYY8AmountofreusedresourcesYYY9Amountorpercentageofrecycledmaterial YYY 10Amountorpercentageofproductsreused YY 11Amountorpercentageofproductsrecovered YY 12Averageamountofmaterialsre-tainedinthecyclepercitizenperyear YYY

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Table4.2(continued) #NameResour- ces Emiss- ion

Waste

Ren. share

UtilityJobs

Value Added

Social wellbeing asYYYsepa-tewofepercentagormount13 ration teYYYsep-14asweofpercentagorAmount aration YYYofpackagingcleofePercentag15recy waste aterre-issues16(wefficiencyaterW tribu-disandtreatmentgardingits tion) and(%)erelativWh)(kbsoluteA17 reductionofyearlyelectricitycon- sumption

P 18Percentageofrenewableorrecy- cledenergyuseY 19Renewableenergyproductionon totalenergyproductionY 20Fossil-fuel-freetransportsectorY 21Low-impactandnon-toxicmateri- alsusedinproductionprocessesY 22Percentageofincoming/outgoing flowsYY

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Table4.2(continued)

#NameResour-ces Emiss-ion WasteRen.share UtilityJobsValueAdded Socialwell-being23Tonnageofwastedivertedviare-pair,reuse,recoveryandupcyclingactivities YYYP 24Amountofwasteproducedinthecity Y

25Amountorpercentageofwasteavoided YY 26PrimaryresourcesusedY27RecyclingrateofwastewaterY28Safetreatmentrateofmunicipalrubbish Y

29Resourceusage:totalrawmaterialproductivity YY 30Environmentalcosts(costsofex-haustion,waterpollution,CO2-emissions,toxicityandlandusein€perkilogram) YY

31WaterresourcesproductivityYP32ResourceproductivityYP33EnergyproductivityPYP34Sustainabilityofinvestmentsfromthemunicipality P

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Table4.2(continued) #NameResour- ces Emiss- ion

Waste

Ren. share

UtilityJobs

Value Added

Social wellbeing 35GrossvalueaddedYP cledYsoldgoodsvenuerecyfromRe36 ialYYafterYmaterofvaluePotential37the recovery/re-use a-eravyear)for(invedsayMone38 thereducingtoduehouseholdeag amountofproductsthrownaway

YY 39Valueofre-usableorrecyclable usedgoodssenttolandfillYY 40PublictransportusageY 41Proportionofgreenandrecre- ationalareaspercapitaY 42NumberofnewgreenjobsYY 43Percentageofnewjobsrelatedto thecirculareconomyYY 44Percentageofnewjobsrelatedto thecirculareconomyPP 45Percentageofpopulationthatshows anincreaseincircularbehaviourP

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From Table 4.2 it is furthermore possible to identify that indicators focused on recycling, such as indicators number 4-9 look identical according to the criteria assessment.

However they are vastly different, take for example number 7 amount of recycled resourcesand number 8 amount of reused resources. In the "reuse, reduce, recycle"

hierarchy of CE reuse has the highest value and recycling the lowest. It is also important to separate indicators such as number 14 recycling of urban solid waste and number 4 recycling of municipal waste. First of all, there is a scale difference between them, number four is at the municipality scale while number 14 is at the urban scale. Secondly, we have to make a distinction between solid waste and general waste, these are different scales of delineating flows. In the same way, there is a difference between number 7 recycled resourcesand number 9 recycled material, material and resources are not necessarily the same and might overlap in scope.

That these differences in scale and scope are not visible in the assessment suggests that a categorisation of indicators addressing those could be a way forward. In order to apply CE indicators to a UM framework which delineates transport flows it would be useful to know which indicators address these specific flows. This set of criteria and categories could also provide a better overview of indicator scopes, enabling an insurance that not only all CE criteria are addressed, but also all sectors (transport, industry etc.) and scales of delineation investigated in the UM framework (waste, solid waste, household solid waste etc.).

The social aspects (social wellbeing and jobs) are not addressed at all before the

extension of the indicators. However, the indicators identified from the extended search are not based on energy and material flows, something that makes them less straight forward to apply to a UM framework. At the same time, the overall assessment of a circular economy from a sustainability perspective cannot be deemed holistic without the social aspects. This motivates an attempt to apply non-flow based indicators to UM frameworks.

4.3 Suggestion of a Circular Economy Framework

The DPSIRMF is the most comprehensive framework analysed in this thesis and it also offers a holistic view through its several layers and network characteristic. Based on this reasoning and the previous assessment the DPSIRMF will be expanded into a CE framework through the integration of CE indicators. The chosen indicators should together cover all the CE criteria and be feasible to incorporate into the DPSIRMF.

Unique to this particular framework is the multilayer approach and this has to be kept in

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mind when suggesting suitable CE indicators to integrate.

Table 4.3: Suggested indicators to incorporate into the DPSIRMF and the framework layer they could be applied to.

# Motivation Layer

Environmental

1 Provides a static and straightforward insight into urban emis-

sions 1

2 Provides a dynamic perspective on emissions and therefore also an appreciation of what progress has been made. 1 3 Delineates emissions and provides more detail in the transport

sector 7

6, 7, 8 Together they delineate the total circular activity of waste. Im- portant to highlight the reduce, reuse, recycle hierarchy of CE. 2 12 Provides insight into durability and urban stacks of material 3 . 18 Provides a static and relative view of how sustainable the en-

ergy is. 1

22 Overall view of total circularity as well as urban stocks. 1 23 Provides an overall view of the circularity of waste. 2 24 Provides a static view of waste production. Could possibly be

extended to show the percentage of reduction as well. 1

Economical

30 Provides an economic perspective of environmental pressure

from the urban system. 5

31, 32, 33 Together they provide an economic perspective on the three main types of flows: water, resources and energy. 1

Social

40 Provides an insight into the public transport usage and an extension of this indicator could also investigate the sustainability of the transport fleet

7

43 Provides a narrow social perspective on the UM. Hard to integrate since it is not based on material or energy flows, however, required data should be possible to obtain

N/A

The suggested CE indicators to incorporate into the UM framework as well as which layer of the framework they should belong to are presented in Table 4.3. Together they

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cover all the eight CE criteria, but there is an under-representation of mainly indicators covering the social aspect. This issue was also reflected in the Results, where no indicators of social aspects based on material and energy flows were found. One of the two indicators for social aspects could not be directly integrated into the DPSIRMF and the other indicator only provides a narrow insight into the social aspects. Perhaps it could be possible to expand the DPSIRMF further by adding a social layer. If possible, this would provide an easier and more straightforward way to properly assess the social dimension of sustainability with this CE framework.

It should also be noticed that not all of the different layers of the DPSIRMF are

addressed by the CE indicators. Layers 4, material intensity of economic sectors, and 6, the spatial location of resource use, could probably provide insight into the circular economy of the urban area with the right indicators. There are also several other aspects of the framework which could be addressed by CE indicators but are not, such as

providing a dynamic perspective on the share of renewable energy. In other words, this suggested CE framework is not as comprehensive as it could have been, yet it is a first step towards an urban CE framework focusing on sustainability.

4.4 Future studies

There are still many knowledge gaps in the field of urban CE frameworks and future studies will have the responsibility of finding ways to create probably urban CE frameworks which incorporate sustainability in its whole. Particularly research should focus on how to incorporate especially social, but also economical aspects into

frameworks. As already discussed there is also the conflict between level of detail and ease of application. There are several ways to approach this conflict. One way forward could be by creating a compromised framework which offers a balance between these factors, such as the UMF. Another could be by creating two complementary frameworks where one is highly detailed and the other is easy to apply. Either way this conflict should be addressed in future studies given the importance of achieving an urban CE framework which is feasible enough to apply to an urban area.

As already presented in Section 4.2 developing the assessment criteria for CE indicators could provide a better approach to select appropriate ones when creating new CE frameworks. Instead of assessing them against only the eight criteria used in this thesis perhaps more criteria could be added and more important a type of categorisation, which was out of the scope of this thesis. These categories should cover both the three

sustainability dimensions, but also factors such as sector and scale of delineation.

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Furthermore, by assessing more CE indicators than those identified by this thesis it should be possible to categorise these into a comprehensive mapping where it is an easier task to choose suitable CE indicators to provide a holistic view.

Another question for future studies is how to make a framework applicable for all city types and for cities located in both the global South and the global North. This was out of the scope of this thesis but it is nevertheless an important question to research. Three out of five UM frameworks analysed in this report are based on the European Eurostat model and also its data which is only valid for European countries. In other words, these

frameworks are difficult to apply outside of Europe and this is a fundamental weakness when creating a universal model for a urban CE framework based on urban metabolism.

To answer the question about an universal framework we must first study if something like it is plausible. Taking into account the vast differences in economy and development for rural cities compared to megacities in the same country it is reasonable to assume that it is not. In that case a categorisation of city types such as that by Dhawan and Beckmann (2018) or the five-layer approach by Musango, Robinson, and Currie (2017) could be a way forward.

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Chapter 5 Conclusions

To support the transition towards sustainable cities there is a need to develop tools that can identify where the greatest possibilities and challenges for sustainability are found in a city. UM frameworks have been used for this purpose but are not extensive enough.

Integrating CE principles, in the form of CE indicators, into UM frameworks to create urban CE frameworks offers a promising approach to better assess the sustainability of an urban area.

The results of this thesis provide knowledge on challenges and possibilities for creating these urban CE frameworks. Main challenges include properly integrating the social dimension of sustainability and identifying comprehensive UM frameworks, especially those including hinterlands and providing a life cycle perspective. Main possibilities include downscaling approaches to easier obtain data and the integration of sustainability into CE and UM principles.

Furthermore, the CE framework created in this report, by incorporating CE indicators into the DPSIR Multilevel Framework, shows that this is a feasible approach for creating CE frameworks. Of the 17 suggested CE indicators, all but one could be applied directly to the UM framework. Together these indicators covered all of the criteria developed for assessing CE indicators, as well as all three sustainability dimensions. This framework offers an extensive approach and can be used to evaluate circular economy from a sustainable point of view. However, it is not fully holistic since it does not cover all sectors and could use a larger set of indicators.

The possibility to incorporate CE indicators directly into the different levels of the DPSIR Multilevel Framework is a major strength. It provides a straightforward and easy way to both incorporate and expand the set of indicators. A drawback is the lack of a social

34

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CHAPTER 5. CONCLUSIONS 35

layer, meaning that the incorporation of CE indicators assessing the social dimension of sustainability is unsatisfactory and difficult. Still, this thesis, as well as the suggested CE framework, provide a promising foundation for the development of CE frameworks.

Developing an Urban Circular Economy Framework Based on Urban Metabolism

Developing an Urban Circular

Economy Framework Based on

Urban Metabolism

SAGA STUGHOLM

Developing an Urban Circular

Economy Framework Based

on Urban Metabolism

SAGA STUGHOLM

Abstract

Sammanfattning

Acknowledgments

Contents

List of Abbreviations

Chapter 1

Introduction

1.1 Background

1.1.1 Urban Metabolism

1.1.2 Circular Economy

1.2 Aim and Objectives

Chapter 2

Method

Chapter 3

Results

3.1 Identified Urban Metabolism Frameworks

3.1.1 Urban Metabolism Framework (UMF)

3.1.2 DPSIR Multilevel Framework (DPSIRMF)

3.1.3 Modified Eurostat Framework (MEF)

3.1.4 Urban Metabolism Analyst Framework (UMAn)

3.1.5 Urban Metabolism Characteristics Framework (UMCF)

3.2 Assessment Criteria for Urban Metabolism

Frameworks

3.3 Identified CE Indicators

3.4 Assessment Criteria for Circular Economy

Indicators

Chapter 4

Discussion and Analysis

4.1 Assessment of Urban Metabolism Frameworks

4.1.1 Urban Metabolism Framework (UMF)

4.1.2 DPSIR Multilevel Framework (DPSIRMF)

4.1.3 Modified Eurostat Framework (MEF)

4.1.4 Urban Metabolism Characteristics Framework (UMCF)

4.1.5 Urban Metabolism Analyst Framework (UMAn)

4.2 Assessment of Circular Economy Indicators

4.3 Suggestion of a Circular Economy Framework

4.4 Future studies

Chapter 5

Conclusions