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Regional circular economy of building materials: Environmental and economic assessment combining Material Flow Analysis, Input-Output Analyses, and Life Cycle Assessment



The construction industry is responsible for large quantities of construction and demolition waste and almost 50% of the worldwide annual resource consumption, putting the environment, its natural resources, and ecosystems under high pressure. Therefore, governments are implementing regional policies that support a circular economy (CE). But how do we know whether these developments will lead to a shift toward a CE on a regional scale? How can we identify hotspots in a value chain and regional economy to support decision-makers and to develop regional policies? We propose an integrated assessment method that considers indicators for environmental impacts and economic benefits by combining Material Flow Analysis (MFA) and Life Cycle Assessment (LCA) with Input-Output Analysis (IOA) as the connecting element. It provides the necessary data and indicators for a holistic and comprehensive evaluation of a region or industry. We demonstrate its benefits and limitations taking the Swiss canton of Aargovia as an example. We analyze which processes in the material flow system of construction minerals are decisive for formulating mass-related or financial policies encouraging a CE. We show that a shift toward a CE can only be captured by combining material and money flows in a joined model, because a significant increase of services—mainly waste management—is a core element in this development. It can only be covered sufficiently by combining environmental and economic assessment. Our model captures the degree to which a regional economy is advanced in the transition toward a CE to compare different regions or analyze scenarios of future developments.
DOI: 10.1111/jiec.13205
Regional circular economy of building materials
Environmental and economic assessment combining Material Flow Analysis,
Input-Output Analyses, and Life Cycle Assessment
Ronny Meglin1,2Susanne Kytzia2Guillaume Habert1
1Department of Civil, Environmental and
Geomatic Engineering, ETH Zurich, Zurich,
2Institute for Civil and Environmental
EngineeringUniversity of Applied Sciences
Eastern Switzerland, Rapperswil, Switzerland
Ronny Meglin, Oberseestrasse 10, CH-8640
Rapperswil, Switzerland.
Editor Managing Review: Wei-Qiang Chen
Funding information
This work was supported by the Swiss National
Science Foundation (SNSF) within the frame-
work of the National Research Programme
“Sustainable Economy: resource-friendly,
future-oriented, innovative”(NRP 73).
The construction industry is responsible for large quantities of construction and
demolition waste and almost 50% of the worldwide annual resource consumption,
putting the environment, its natural resources, and ecosystems under high pressure.
Therefore, governments are implementing regional policies that support a circular
economy (CE). But how do we know whether these developments will lead to a shift toward
a CE on a regional scale? How can we identify hotspots in a value chain and regional econ-
omy to support decision-makers and to develop regional policies?We propose an integrated
assessment method that considers indicators for environmental impacts and economic
benefits by combining Material Flow Analysis (MFA) and Life Cycle Assessment (LCA)
with Input-Output Analysis (IOA) as the connecting element. It provides the necessary
data and indicators for a holistic and comprehensive evaluation of a region or indus-
try. We demonstrate its benefits and limitations taking the Swiss canton of Aargovia
as an example. We analyze which processes in the material flow system of construc-
tion minerals are decisive for formulating mass-related or financial policies encourag-
ing a CE. We show that a shift toward a CE can only be captured by combining material
and money flows in a joined model, because a significant increase of services—mainly
waste management—is a core element in this development. It can only be covered suf-
ficiently by combining environmental and economic assessment. Our model captures
the degree to which a regional economy is advanced in the transition toward a CE to
compare different regions or analyze scenarios of future developments.
building materials, circular economy, Input-Output Analysis (IOA), Life Cycle Assessment (LCA),
Material Flow Analysis (MFA), regional assessment
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any
medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
© 2021 The Authors. Journal of Industrial Ecology published by Wiley Periodicals LLC on behalf of Yale University
562 Journal of Industrial Ecology 2022;26:562–576.
The construction industry is responsible for almost 50% of the worldwide annual resource consumption (OECD, 2019). In 2011, 37 gigatons of non-
metallic mineral materials were extracted,with an expected increase to 86 gigatons in 2060. At the same time, the anthropogenic stock is a potential
source of raw materials for the construction industry. An average of 1.68 kg of construction and demolition waste (CDW) is “emitted” per person
and day,which can be used as secondary building material (Kaza et al., 2018). Considering the high consumption of natural resources and the equally
high production of CDW, the environment, naturalresources, and ecosystems are under high pressure (OECD, 2020; Pomponi & Moncaster, 2017).
For that reason, various governments and organizations aim to increase resource efficiency and establish a sustainable1economy (BAFU, 2020;
Ellen MacArthur Foundation, 2013; European Commission, 2020) including principles of a circular economy (CE)2. In Switzerland, for example, the
“Ordinance on the Avoidance and the Disposal of Waste” came into force in 2016, which aims “to encourage the sustainable use of natural raw
materials through the environmentally sustainable recovery of waste” (ADWO, 2020).
The increasingly dynamic developments represent a major challenge for the phlegmatic building material industry (Abuzeinab et al., 2017;
Giannoni et al., 2018). A large number of barriers and enablers affect these developments (Hart et al., 2019; Kliem & Scheidegger, 2020), such
as public policies (spatial planning, standards norms, etc.), but also alternative business models (Schaltegger et al., 2016). Traditional business mod-
els in the building materials industry link economic success to material turnover. The higher the material turnover, the higher the economic success
(Spoerri et al., 2009). This promotes an inefficient use of natural resources and contradicts macroeconomic objectives, such as circular material
flows and reduced material consumption. This ultimately leads companies to change their traditional linear business models to alternative models
(Bocken et al., 2016; Halme et al., 2007; Kliem & Scheidegger, 2020).
But how do we know whether these developments will lead to a transition toward a CE on a regional scale? How can we avoid unintended side effects
on economic growth and emissions, or problem shifts to other regions? How can we identify hotspots in a value chain and/or a regional economy to support
decision-makers and to develop regional policies?
These questions are particularly important because this fundamental transition to a CE also includes a change from a material-oriented economy
to a service-oriented economy (Stahel, 2016) which must not necessarily be regarded as sustainable (Geissdoerfer et al., 2017;Zink&Geyer,2017).
Studies even show that in specific cases a CE can have greater environmental impacts (Blum et al., 2020; Bracquené et al., 2020)orevencreatea
linear economy lock-in (Coenen et al., 2015; Greer et al., 2021). Therefore, to identify suitable strategies and support decision-makers in the formu-
lation of sustainability policies, all responsible stakeholders must have a transparent and comprehensive decision basis for a better understanding
of an industry and region (Haas et al., 2016; Mayer et al., 2018).
In a federal state like Switzerland, the constraints for policies in each region are very different, especially in terms of resource availability, spatial
planning, or economic performance. For this reason, the implementation of CE policies remains with local actors (European Green Deal, 2021;Smol
et al., 2017; Virtanen et al., 2019). A model-based assessment on a regional scale enables policymakers to fall back on a unified basis and thus make
policy decisions that take a factor in sustainability considerations (Virtanen et al., 2019). A regional approach is seen to have a significant advantage
compared to a mere product-level approach (McCarthy et al., 2018; Vercalsteren et al., 2020).
In recent years, more and more scientists developed methods to evaluate CE from different perspectives. Recent review papers on CE in the
construction and CDW industry, highlighta single method focus on the product- or building-level, instead of regional or industry level (Hossain et al.,
2020). Most studies focus on resource efficiency of the construction industry (construction waste minimization and recycling) and neglect business
and economic perspectives (Lieder & Rashid, 2016; Parchomenko et al., 2019). Ghisellini et al. (2018, p. 636) conclude that “the environmental
impactsofapplying CE principles (...) are generallymuchmoreinvestigated (...)thaneconomic impacts.” López Ruiz et al. (2020, p. 12) also point
out, that “Research (...) has mainlyfocusedon aspects regardingreuseand recycling from anenvironmental performance perspective” and that
“integration of economic criteria is still limited.”
As there is no harmonized method available to quantitatively assess sustainability-aspects of a CE yet (Peña & Civit, 2020), it is necessary to
develop a more holistic multidisciplinary assessment methodology to evaluate the environmental, economic, and social aspects of CE and to con-
sider business perspectives, technological developments and policies (Haberl et al., 2016; Haupt & Hellweg, 2019; López Ruiz et al., 2020; Nußholz
et al., 2019). Such an assessment would improve communication with all stakeholders and provide a link to the Sustainable Development Goals
(United Nations, 2015) at all levels (Di Maio et al., 2017; Mayer et al., 2018).
We would like to close a part of this research gap and develop an applied instrument that evaluates the environmental and economic effects of
public policies on a region or a company in terms of a sustainable and circular building materials industry. We propose an assessment model, which
a. assess the economic and environmental impacts of the building materials industry of a region,
1Sustainability: Balanced integration of economic performance, social inclusiveness, and environmental resilience, to the benefit of current and future generations (Geissdoerfer et al., 2017).
2Circular economy: Regenerative system in which resource input and waste, emission, and energy leakage are minimised by slowing, closing, and narrowing material and energy loops through
long-lasting design, maintenance, repair, reuse, remanufacturing, refurbishing, andrecycling (Geissdoerfer et al. (2017).
TAB LE 1 Types of analysis and associated issues of concern adapted from (Bringezu & Moriguchi, 2002;OECD,2008)
Issue of concern
Environmental impacts, supply security, technology
development within businesses, countries, regions
General environmental and economic impacts of materials
and goods
Objects of interest Substances Materials Products Businesses Economic activities Countries,regions
Type of analysis Substance Flow
Analysis (SFA)
Material Flow
Analysis (MFA)
Life Cycle
Business level
Analysis (IOA)
b. identify key processes of the industry under study for promoting a CE on a regional scale,
c. compare the building materials industry of different regions with varying degrees of resource availability in terms of resource efficiency and
value creation and
d. to estimate the effects of a developing CE in a regional context.
In this paper, we present a model that combines proven methods and opens new possibilities for interpretation that would not be possible with
the individual methods. With the proposed novel combination, we can investigate a regional industry in detail and indicate the impacts of changing
material flows on the life cycle most relevant for generating value-added, causing emissions, and consuming natural resources on a regional level.
We conduct a case study of the Swiss canton of Aargovia to demonstrate the methods’ abilities and indicate its potential use for policymakers.
We can use the model to anticipate hotspots where the largest effects of public policies or changing materials flows can be expected. The results
highlight the impact of specific business models and their effects on the environmental and economic performance of a regional building materials
industry. These insights will help decision-makers formulate policies to promote a CE.
To analyze the circularity of an industry on a regional scale an integrated assessment model (IAM) based on complementary methods must be devel-
oped (Crawford et al., 2018; Loiseau et al., 2012; Moriguchi & Hashimoto, 2016; Säynäjoki et al., 2017; Singh et al., 2021; Teh et al., 2017). An IAM
addresses different stakeholders, who on the one hand have different background knowledge, and on the other hand, pursue different objectives.
This is aggravated by the fact that policies related to regional sustainability goals can have negativeeffects, especially on traditional economic activ-
ity. It is therefore of great importance for policymakers to consider conflicting economic and environmental constraints (Reif & Osberghaus, 2020).
Therefore, the goal of an IAM is not only to generate analytical insights but also to link the different stakeholders with a “common” language and
to create a common basis for decision-making (Kytzia, 2010; Mayer et al., 2018). This should allow us to
better estimate future developments (scenario analysis),
obtain initial findings in the context of policymaking (policy evaluation), and
establish a possible prioritization for further developments (Weyant et al., 1996).
2.1 Current state of assessment methods integrating economic and environmental goals
Bringezu and Moriguchi (2002) already proposed different methods for different objects of interest (Table 1).
Material Flow Analysis (MFA), Input-Output Analysis (IOA), and Life Cycle Assessment (LCA) have proven to be the most appropriate methods
to perform an environmental and economic assessment of products and systems (Bovea & Powell, 2016; Dossche et al., 2017; Hawkins et al., 2007;
Moriguchi & Hashimoto, 2016). Nevertheless, none of the methods can provide a comprehensive economic and ecological assessment of a complex
system in the context of a CE in isolation. Each method has different system boundaries, benchmarks, calculating techniques, and scopes, as shown in
Tabl e 2(Haaset al., 2016; Joshi, 1999; Nakamura et al., 2007). However, since these single methods are accepted and widely used by the professional
community, they provide the starting point for our study.
We propose an IAM that considers indicators for environmental impacts of building materials with indicators for regional economic benefits. We
use the different scopes and advantages of the respective methods combining MFA and LCA with an IOA as a connecting element. Our approach
will combine the different levels of interests (product level, regional level) and overcome the individual shortcomings presented in Table 2.
There are already attempts to combine different methods to investigate severalaspects on multiple levels. However, these methods use different
combinations as various objectives are pursued under different boundary conditions. For example, some studies using similar approaches to assess
TAB LE 2 Comparison of methods
Description Method to investigate the technical processes
of a socioeconomic system and its
dependencies in a defined boundary (space
and time)
Is performed according to the first law of
thermodynamics; the basic condition is that
the input must always equal the output
including all stock changes
Top-down economic tool for analyzing
interindustrial interdependencies in an
Describes the distribution of goods and
services by using a system of linear equations
Bottom-up methodological framework
encompassing all the impacts of a product
system from cradle to grave
A decision-support tool used to promote
sustainable management as well as
sustainable construction and to assess and
plan CE strategies
System definition Functional or geographical Geographical or political Functional
Regionalization possible
Advantage Flexibility regarding model assumptions
Mass balancing (filling data gaps)
Basis for impact assessment methods
Represents the whole economy/industry
Public data available (on nationwide level)
Possibility to extend to broaden the scope
(multiple regions MRIO or environmental
extensions EEIO)
Detailed evaluation of a product
Product comparisons
Possible prob-
Availability of data
Monetary flows (e.g., services) are not
Low resolution due to high aggregation
partial simplifications and assumptions
Spatial boundaries
Truncation error; subjectivedefinition of the
system boundary (e.g., End-of-Life [EoL]
Choice of allocation
Selection of key
(Brunner & Rechberger, 2017; Fischer-Kowalski
et al., 2011; Krausmann et al., 2018)
(Farhauer & Kröll, 2013; Joshi, 1999; Miller &
Blair, 2009; Schaffartzik et al., 2014; Suh,
2010; Weisz & Duchin, 2006)
(Frischknecht, 2020; Jolliet et al., 2016;Peña&
Civit, 2020;Reapetal.,2008;Suhetal.,2004)
material efficiency and its links to service provision (Haberl et al., 2017; Pauliuk et al., 2020). Others use LCA-based combinations to investigate
the environmental impacts of individual regions or national economies (Dias et al., 2018; Kovanda, 2020; Lausselet et al., 2020; Lavers Westin et al.,
2019; Sigüenza et al., 2020). Input-output approaches are often used to enable a top-down investigation of specific regions or industries (Dias et al.,
2018; Kovanda, 2020; Teh et al., 2017). However, the proposed combination of MFA, LCA, and IOA, represents a novel combination in the context
of sustainability assessment (Sassanelli et al., 2019).
Combining MFA and LCA offers advantages for the assessment of complex systems, such as industrial sectors or regions (Laner & Rechberger,
2016; Lopes Silva et al., 2015). Laner and Rechberger (2016, p. 316) state, that “MFA can be applied both as a tool for environmental impact assess-
ment itself and as a basis for impact assessment methods such as life cycle impact assessment” but has a different perspective than LCA. Using
MFA as a basis for the analysis, we increase consistency, robustness, and transparency of the input data (Brunner & Rechberger, 2017). Therefore,
MFA-Data is used as Input for the bottom-up IOA for value chains on a regional scale and further evaluation in combination with LCA-data. This is
in line with Säynäjoki et al. (2017, p. 164) who state in their study, that “IO-LCA with comprehensive supply chain information is the better option
for LCA if the focus of the study is to understand the economy-wide implications of construction-sector products.” Also, Teh et al. (2017, p. 313)
conclude that the combination of LCA and IOA (i) “unites the precision of process-based LCA with the comprehensiveness of IOA” and (ii) solves
the“aggregationlimitationinIOA(...) bydisaggregating selectedsectorsintospecificproductstoprovidebettergranularity.”Thisisalsoconfirmed
by Aguilar-Hernandez et al. (2018), who propose to disaggregate products and sectors in more detailed categories to avoid the deficiency in the
resolution of IOA.
2.2 Integrated environmental and economical assessment for CE
The model for an integrated environmental and economic assessment is based on an MFA covering all necessary processes and products of the
mineral building materials industry from raw material extraction to the end-of-life (EoL) phase (see figure S1 in Supporting Information S1). The
MFA is translated into a physical input-output table (PIOT), which represents the processes and interindustrial dependencies of the region under
investigation in mass units (denoted by a P). As the PIOT’s processes correspond exactly to the MFA processes, material flows in the MFA can be
transferred directly (see flow numbers in the MFA in figure 1, and the process numbers in the PIOT in figure S2 in Supporting Information S1).
This PIOT is used to set up an input-output model consisting of a final demand vector (Y), an input-output coefficient matrix (A), and an output
vector (X). The coefficient matrix (A) describes the system under investigation by showing the input needed for one unit of output of the respective
sector within the region. The output vector (X) corresponds to the sum of the final demand (Y) and the intermediate demand.
By multiplying the material flows with the respective costs/prices, we obtain the monetary input-output table (MIOT) in monetary units (denoted
by an M). The conversion into monetary units is intended to enable a consistent and more comprehensible assessment of environmental influ-
ences and “can improve our understanding of the effects of physical flows on the socioeconomic system” (Bruel et al., 2019, p. 17). Beaussier et al.
(2019, p. 409) also state, that “valuating environmental benefits into monetary units can facilitate communication with a broad audience and raise
societal awareness about environmental issues.” The conversion from physical to monetary units makes it necessary to change the position and flow
direction of various processes in the change of PIOT to MIOT. This is especially necessary for services, where material and money flows in the same
direction in contrast to goods/products where material is traded against money, leading to flows in opposite directions. For example, the imports
of excavated material and CDW, which are listed in the PIOT in the Input-matrix, are listed in the MIOT in the Output-matrix. This is because the
import leads to a positive monetary flow and must be credited to the result of the services landfill or waste management.
The relationship between input and output can be illustrated as follows using the core equation of IOA according to Leontief (1986)withn
XPorM =(IAPorM
)1×YPorM (1)
XPorM vector of the output of each process in monetary or physical units of material, dimension n×1
YPorM vector of final demand of each process in physical or monetary units of material, dimension n×1
Iidentity matrix, dimension n×n
Amatrix of input coefficients for material based on monetary or physical relations, dimension n×n
Using formula (1), we can calculate the impact of a change in demand (ΔY) on the region/industry under consideration (ΔX) as follows:
)1×ΔYPorM (2)
TAB LE 3 Results that can be obtained from the PIOT and MIOT
PIOT/physical IOA MIOT/monetary IOA
Material flows per sector
Mass related indicators (see Supporting Information) to
investigate material consumptions and recycling rates
Effects of changes in demand
Leontief-multipliers (see 2.5)
Revenue per sector
Value-added (VA) per sector (see 2.4)
Effects of changes in demand
Leontief-multipliers (see 2.5)
After this step, two separate, but linked input-output tables (IOTs) are available, one in physical units (PIOT), another in monetary units, and two
separate IOAs according to the Equation (1) in physical and monetary units. From these two data sets, the following results can be obtained and
used for further calculations:
The assessment of environmental burdens and economic impacts is based on the MIOT/monetary IOA to include products and services. In the
MIOT waste management services are represented as output flows of demolition and recycling processes and input flows to material production
and construction industries. This reflects the economic logic driving the MFA system. The monetary IOA represents the relation between the eco-
nomic value of goods and services providing a value proportional allocation in the assessment model. To link the material flows with the corre-
sponding emissions, the MIOT is extended with a vectorof defined environmental burden coefficients. The burden coefficients are defined for each
environmental burden under study in relation to each process’s output in monetary units. They are estimated based on the corresponding PIOT and
environmental impacts from databases (see Section 2.4). Therefore, an environmental vector b is introduced to Equation (2) leading to the following
eVector of environmental burdens by each process in the unit of the burden used for environmental assessment, dimension n×1
bVector of direct environmental burdens defined as the amount of burden (in the unit of the chosen burden) related to the input of each process
in monetary units, dimension n×1
In the same way, the change in value-added (VA) based on formula (2) can be calculated as follows:
ΔVA =va ×ΔXM=va ×(IAM)1×ΔYM(4)
VA Vector of value-added by each process in monetary units, dimension n×1
va Vector of value-added by each process related to the input of each process in monetary units obtained from the MIOT (Table 3), dimension
2.3 System boundary and functional unit
To define the system boundary and the functional unit, we focus on an explicit industry in a defined region. All necessary processes of the value
chain of the building materials under study (gravel, cement, concrete, and excavation material), from raw material extraction to the EoL-Phase are
included (see figure S1 in Supporting Information S1). However, the use phase of the building material in the building is neglected. To consider
the environmental impacts of imported raw materials or additives, we integrate a second region in the model as “Hinterland” (Kytzia et al., 2004;
Schiller et al., 2020). This “Hinterland” is not modeled in detail but provides the necessary imports directly connected to the value. The use of this
approach enables us to better illustrate dependencies, especially regarding the supply of raw materials. As functional unit, we chose the “output of
the buildings materials-industry in the region of interest over a specified period.”
2.4 Economic and environmental assessment
The economic assessment of the region or company is based on revenue (income produced by the sector) and value-added (VA), which can be
extracted from the MIOT. The VA represents factor income generated by labor and capital on a regional scale. On a company scale, this factor income
TAB LE 4 The environmental indicators used in this study
Impact category Unit Description Source
Global warming
kg CO2-eq. GWP (IPCC 2013, 100y) Emissions of processes/products over a chosen
period of time relative to that of CO2indicated
in kg CO2-equivalent
Cumulative energy
MJ CED Balances and adds up the consumption of primary
energy in relation to various sources,
distinguishing between renewable and
non-renewable resources
(Frischknecht et al.,
Ecological scarcity Ecopoints Environmental impacts (e.g., climate change,
resource depletion) are weighted according to
the ecological objectives of the respective
country; summarized to create a
(Frischknecht &
Büsser Knöpfel,
is analyzed for each process in the production chain (including internal transports) by subtracting material and energy costs from the revenueselling
the material.
To calculate the environmental impacts, we set up an LCA Inventory (LCI) based on the market data sets (including average transports) of all pro-
cesses (see Supporting Information). We assess the environmental impacts using the following indicators: global warming potential (GWP); cumu-
lative energy demand (CED) and the method of ecological scarcity (see Table 4). GWP and CED as impact categories have been selected as they
are the most frequently used in studies of the built environment and therefore allow comparison with other studies (Bovea & Powell, 2016). The
ecological scarcity is an end-point indicator that is used especially in the Swiss context of this study (Frischknecht & Büsser Knöpfel, 2013; Knoeri
et al., 2013).
Consumption of natural resources is directly assessed based on the PIOT. An overview of mass-related indicators can be found in the Supporting
Information. In an additional step, environmental indicators and mass-related indicators (per VA and per capita) help to connect to the UN SDGs
(United Nations, 2015), in particular SDGs 8, 9, and 12, and thus expand the spectrum of the evaluation.
2.5 Assessment of regional circularity
As mentioned before, aspects of CE are often assessed regarding resource efficiency and recycling and reuse of waste/secondary materials. This
does not capture the economic aspects of a CE. To capture those aspects, we suggest using indicators from regional economics: Leontief multipliers
calculated based on IOTs (Dubois, 2015; McLennan, 1995). In most studies, they are used to evaluate which processes/industries are pivotal to
economic activity in a region (Lenzen, 2003;Wen&Wang,2019) by indicating how much additional turnover is generated by an additional output
of a specific process/industry. We assume that these values increase as a regional economy advances in the transition toward a CE because linear
value chains are replaced by circular value chains. This increases the interlinkages within a regional economy and results in higher values for Leontief
multipliers for specific processes as well as the overall system.
To calculate the Leontief multipliers, we use the Leontief inverse matrices (IAPorM
)1of the physical and monetary IOAs (Holub & Schnabl,
1994a, 1994b). Three different characteristic values (multipliers) can be distinguished here:
(i) The cell-value cij at the intersection of line iand column jof the Leontief inverse indicates the change in output of sector irequired to create
one additional unit of the respective sector jfor final demand.
(ii) The sum of the inverse coefficients cij of the column of a sector jindicates what all sectors (including sector j) must, directly and indirectly,
produce in addition for sector jto create one additional unit for final demand and
(iii) the sum of the inverse coefficients cij of the row of a sector iindicateswhatsectorimust generate in total, based on direct and indirect signals,
for each of the sectors to create one additional unit for final demand.
In the context of this study, we focus on the cell values cij and the column sum. The row multiplier is still shown in the results for completeness,
but not considered in detail.
2.6 Case study
To demonstrate the functionality of the model, we perform a regional assessment of the Swiss canton Aargovia for the year 2018. We chose this
canton because there is a high availability of raw materials on the one hand, but also a high construction activity. It covers all the major material
flows considered in this study and is therefore considered an adequate sample region. Key figures for the assessment can be found in the Supporting
2.6.1 Data of material flows
The material flows are obtained from the database “KAR-Modell” (Rubli, 2020). The KAR-Model is an institutionalized database of regional and
interregional material flows of building materials (K =Kies/gravel; A =Aushub/excavated material; R =Rückbaumaterial/CDW) of various cantons
in Switzerland. As the KAR-Model does not provide detailed data sets for material flows in concrete production and building industries, we addi-
tionally use data provided by studies that examine the material flows of the Swiss building stock in detail (Gauchet al., 2016; F. Guerra & Kast, 2015;
Rubli, 2016), as well as regional statistics (Kiefer et al., 2020). Key numbers used for this assessment can be found in the Supporting Information.
2.6.2 Economic data
Economic data are used from national statistics of the federal government or regional statistics of the canton. Average prices were determined
based on the public price lists of around 170 building materials producers throughout Switzerland (see the Supporting Information). These prices,
as well as costs and internal price structures, were validated in interviews with various producers. By grouping the individual sectors according to
the Swiss General Classification of Economic Activities (NOGA), we can make a more detailed analysis of the turnover and VA (see the Supporting
Information). Using key figures from the Swiss value-added statistics (BfS, 2020) we can estimate personnel costs, other operating costs, and the
amount of amortizations in addition to expenditure on goods and materials. These values, even if these are only rough estimates based on statistics
averaged over Switzerland, allow us to assess an industry in more detail and compare it with other sectors.
2.6.3 Environmental coefficients
The environmental indicators are calculated based on datasets from ecoinvent (Wernet et al., 2016). In the case of construction and demolition pro-
cesses, no data records are available in ecoinvent. Therefore, processes from German Database Ökobaudat (BMI, 2020) were used instead. Note,
that for the construction and demolition processes, values for ecological scarcity were not available. The recycling processes of mixed and concrete
granulate are set up according to Tschümperlin et al. (2020) using datasets from ecoinvent. We use an economic allocation approach based on pub-
lished average values to include the emissions of alternative and secondary raw materials in cement production (see the Supporting Information).
Alternative fuels are allocated according to the average fuel mix of the Swiss cement production. Transportation is accounted according to the
respective Swiss market data sets. Electricity is modeled according to the average Swiss electricity mix which is available in ecoinvent. The detailed
environmental impacts of the considered inputs can be found in the Supporting Information.
3.1 Economic and environmental results
The results of the assessment are visualized in Figure 1. The detailed results can be found in the Supporting Information. Based on these diagrams,
we can identify hotspots in the industry under study but also processes with increased resistance to change caused by policies. We assume that
resistance to change correlates with VA—creating jobs and capital income in the region.
The evaluation of material output in comparison to VA (Figure 1a) shows that various sectors have a high material turnover but generate only
little VA. These sectors can thus be identified as intermediate sectors, where policies are likely to have only a minor effect on the regional economy.
The sectors “Cement plant,” “Buildings” and “Gravel pits” can be identified as hotspots. They handle large amounts of material and generate high
VA. This also means that these sectors are likely to show high resistance to policy-induced changes in material flows. The position of the sectors
“Demolition” and “Recycling Plant” in the figure indicates that the recycling of demolition material still creates far less VA compared to sectors
using primary materials. This suggests that these sectors are more open to policies stimulating alternative business models.
From an environmental perspective (Figure 1b–d), the cement sector is the single most important process in the Canton of Aargovia, as it
is home to two of the six Swiss cement plants. For this reason, the environmental impacts of the cement sector are of paramount importance
in this canton. The remaining sectors, especially the gravel pits, gravel plants, and quarries show higher environmental impacts, as they are
not only resource-intensive but also transport-intensive. It should be noted that due to the data situation (see Section 2.6), the environmental
FIGURE 1 Results of the assessment: (a) Comparison of sectors in terms of material output and VA; (b) comparison of sectors in terms of GWP
and VA; (c) comparison of sectors in terms of CED and VA; (d) comparison of sectors in terms of eco-scarcity and VA; for better readability, the
x-axes in (b), (c), and (d) have been scaled to logarithmic ones. Underlying data used to create this figure can be found in Supporting Information S1,
table S10
impacts of the construction processes (building and infrastructure) can only be mapped to a limited extent and should therefore be treated with
3.2 Assessment of regional circularity
The two tables below show the physical (Table 5) and monetary (Table 6) Leontief inverse matrix and the multipliers described in 2.5. A high aggre-
gated multiplier indicates a high degree of interdependence in the industry, while a multiplier of 1.0 rather indicates a “pass-through sector.” The
column multiplier of the sector “Demolition” in the physical matrix shows a value of 3.973, which indicates that for one unit of output the sector
“Demolition” triggers a material turnover of 3.973 in the entire system. It indicates that “Demolition” is a key process for the material manage-
ment system and of paramount importance in the transition toward CE. Yet, this does not reflect economic reality. The construction industry is
represented in the physical matrix as a “supplier” to demolition, although the economic relation is vice versa. Demolition supplies the construction
industry with a waste management service. This becomes visible only in the monetary inverse. In consequence, the multiplier for demolition in the
monetary Leontief-Inverse is much lower. It only amounts to 1.176 because demolition is connected only with the recycling plant and the landfill.
Only in this way, the service of “Demolition” becomes visible. This reinforces the statement mentioned before, that monetary data should be used
for a realistic evaluation of a service-oriented CE. However, this high physical multiplier shows the importance of the sector “Demolition” in terms
of CE and material usage. The demolition process triggers all other processes in the construction industry and a higher rate of demolition and use of
CDW would therefore probably strengthen the linkage.
In the monetary matrix (Table 6), building construction shows the highest column multiplier of 2.06. This means an increase in construction
spending of CHF 1 million triggers a total output of the construction industry of CHF 2.06 million. It can be concluded that the construction of
buildings has the greatest influence on achieving a CE. The same applies to the “concrete plant” sector or the sector “gravel plant,” which has a
TAB LE 5 Physical Leontief inverse matrix of the building materials industry in Aargovia in 2018 and the Leontief multipliers
To/to (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
(1) Gravel pits 1.000 0.896 0.265 0.459 0.384 0.449 0.421 0.013 3.887
(2) Gravel plant 1.000 0.296 0.512 0.429 0.501 0.470 0.014 3.222
(3) Recycling plant 1.084 0.115 0.152 0.120 0.134 0.004 1.610
(4) Quarries 0.033 1.000 0.668 0.147 0.094 0.021 0.053 0.002 2.017
(5) Cement plant 0.050 1.000 0.220 0.141 0.031 0.079 0.002 1.523
(6) Concrete plant 0.232 1.025 0.657 0.144 0.367 0.011 2.435
(7) Buildings 0.313 0.033 1.044 0.073 0.496 0.015 1.974
(8) Infrastructures 0.405 0.043 0.057 1.094 0.642 0.020 2.260
(9) Demolition 0.717 0.076 0.101 0.167 1.138 0.035 2.235
(10) Terrain 0.338 0.347 0.109 0.190 0.127 0.206 0.167 0.178 0.173 1.000 0.695 3.532
(11) Landfill 1.000 1.000
Column-multiplier 1.338 2.243 3.503 1.190 1.795 2.836 3.225 2.778 3.973 1.000 1.811
TAB LE 6 Monetary Leontief inverse matrix of the building materials industry in Aargovia in 2018 and the Leontief multipliers
CHF/CHF (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
(1) Gravel pits 1.000 0.660 0.107 0.165 0.053 1.986
(2) Gravel plant 1.000 0.162 0.088 0.069 1.319
(3) Recycling plant 1.000 0.018 0.028 0.029 0.159 1.233
(4) Quarries 1.000 0.064 0.028 0.030 0.002 1.160
(5) Cement plant 1.000 0.435 0.184 0.019 1.638
(6) Concrete plant 1.000 0.423 0.043 1.466
(7) Buildings 1.000 1.000
(8) Infrastructures 1.000 1.000
(9) Demolition 0.074 0.132 1.000 1.205
(10) Terrain 0.011 0.002 0.001 0.001 1.000 1.014
(11) Landfill 0.067 0.007 0.017 1.000 1.091
Column-multiplier 1.000 1.671 1.000 1.000 1.064 1.751 2.060 1.354 1.176 1.000 1.000
multiplier of 1.795 and 1.671, respectively. Here, too, it can be assumed based on the multipliers and the linkages, that policies considering those
sectors have high leverage in the building materials industry.
To evaluate the leverage effect of policies on the sector in more detail, we can use Equations (3)and(4) from Section 2.2 to calculate the changes
in impacts when the demand Ychanges. As an example, we will use the sector “Buildings,” and the induced output of CHF 2.06 million CHF for an
investment of CHF 1 million. Figure 2shows in which sectors this investment would havethe greatest impact. For VA, the sector “buildings” itself has
the dominant impact, followed by gravel pits and concrete plants. Furthermore, the cement plant contributes the largest share to the environmental
impacts. However, a large share of the environmental impacts, especially the ecological scarcity, is caused by the gravel pits and plants.
Every model is a simplification of reality and highly depends on the data used and assumptions made. The Material Flow data have a certain
amount of uncertainty as it is based on general statistics and expert opinions. Our main data source for MFA, the KAR-model, however, has been
validated over several years. Considering the calculation of environmental impacts, the existing data sets also have a significant influence on the
uncertainty. For example, there is little data available on the environmental impacts of construction and demolition processes. However, by using
periodically updated and peer-reviewed data of institutional LCA databases, we assume uncertainties related to the data quality to be low in
FIGURE 2 Share of economic and environmental impacts from the increase in demand in the building construction sector by CHF 1 million;
Underlying data used to create this figure can be found in Supporting Information S1, table S12
the context of this study. Further uncertainty arises in the economic evaluation, as average market prices were used for calculation. In the con-
struction industry, however, prices vary from region to region and sometimes from project to project, so that a certain degree of uncertainty is
transferred to the model. Since the data basis for prices is based on public price lists or a few data points from official statistics, prices are the
largest source of uncertainty for the assessment model in this study. Reliable statistics on construction and material costs would improve the
Nevertheless, the model is not about detailed product comparisons, but about a general evaluation of regions and industrial sectors to identify
hotspots and general changes in material flows and the related impacts. It can therefore be assumed that the assumptions derived from the model
analysis are justified and that the identified uncertainties do not have a significant impact on the results and the final evaluation. Ultimately, the
developed model is not primarily intended to evaluate the sustainability of an industry. Rather, it is designed to distill the necessary data and indica-
tors and to identify hotspots to support decision-makers, and develop regional policies. For these use cases, instead of high-precision data, general
insights for policymakers are relevant.
The consideration in this study is limited to a regional building materials industry. In principle, the processes of the model can be divided into raw
material extraction, intermediate product, and end product. Thus, we believe, that this model can be transferred to other regional heavy industries
with a high proportion of raw material extraction (e.g.,metal). In a very complex high-tech industry, however, the model would reach its limits due to
the many sub-sectors and global value chains.
Bruel et al. (2019) have pointed out, that we have to go beyond the physical study of material flows by studying the socioeconomic consequences
of flows. With our model, we are taking a first step toward a better understanding of the environmental and economic aspects of the transition
toward a service-oriented CE and indicate the critical hotspots for policymakers. Our model offers the possibility to provide all necessary data for
a holistic decision basis and to assess different regions and formulate specific policies promoting CE on a regional level (Smol et al., 2017;Virtanen
et al., 2019). This was made possible by the combination of the established methods MFA, IOA, and LCA and the calculation of environmental and
economic indicators on a physical and monetary basis. The range of different indicators enables a transparent and comprehensive evaluation on
different levels, a necessity highlighted by several scholars (Harris et al., 2021; Haupt & Hellweg, 2019; Nikolaou et al., 2021).
Through an exemplary assessment of the canton of Aargovia, we could demonstrate the benefits of the model. We were able to show which sec-
tors in the building materials industry are pivotal in the transition toward CE and where political incentives and business model innovations could
have the greatest effect (Dubois, 2015;Wen&Wang,2019). Mass-related policies (e.g., green public procurement or recycling quotas) must be
related to material-intensive sectors to achieve the greatest effect. Values of the physical Leontief multipliers identified demolition and recycling
plants as material-intensive sectors. This confirms current development in CDW-legislation in Switzerland (ADWO, 2020) that requires 100% recy-
cling of all mineral CDW. However, the monetary Leontief multipliers show, that incentive-based environmental policies (e.g.,a levy on virgin gravel
to improve CDW’s financial competitiveness) would rather be applied to the sectors of building construction, concrete plants, and gravel plants
since financial decisions have a greater influence there. The use of secondary resources highly depends on purchase decisions in these sectors.
Public policies in Switzerland start to recognize this and new legislation on public tender encourages including criteria for sustainable procurement
(UREK, 2020). Our findings support this initiative and could help to focus it more clearly on CE.
Building on these initial findings, we see further applications of the model. For example, a comparison of different regions could identify relevant
regional characteristics and constraints. These would help to formulate tailor-made and efficient regional policies to address different challenges
and barriers (B. C. Guerra & Leite, 2021; Hart et al., 2019). The model provides the basis for recommendations for actors from politics and admin-
istration for the development of measures and instruments for a CE in the building materials industry and the promotion of efficient use of mineral
raw materials (Wilts et al., 2016). Another potential option would be scenario analyses, which would make it possible to consider the different
processes in the building materials industry. This is particularly important in the context of various possible strategies of the cement and concrete
industry to minimize raw material demand and reduce CO2emissions (Favier et al., 2018;Habertetal.,2020; Obrist et al., 2021). For this, the
model provides improved decision bases for companies in the construction industry to further develop their business models toward sustainable
The authors would like to thank the reviewers for their comments, which contributed to the enrichment of this paper, and Dr. Simon Hoell and
Daniel Kliem for their feedback on earlier drafts of the paper.
The authors declare no conflict of interest.
The data that supports the findings of this study are available in the supporting information of this article.
Ronny Meglin
Guillaume Habert 3533-7896
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How to cite this article: Meglin R, Kytzia S, Habert G. Regional circular economy of building materials: Environmental and economic
assessment combining Material Flow Analysis, Input-Output Analyses, and Life Cycle Assessment. J Ind Ecol. 2022;26:562–576.
... This makes the comparison among results meaningful and reliable. As such, the EIO-LCA becomes one of the more popular assessment models at the aggregate sector level [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52]. The transaction table in the IO model is composed of the production and the demand (consumption) information dimension. ...
... This makes the comparison among results meaningful and reliable. As such, the EIO-LCA becomes one of the more popular assessment models at the aggregate sector level [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52]. ...
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The purpose of this paper is to evaluate the monetary GHG reduction benefits and health co-benefits for the industrial sector under the imposition of a carbon charge in Taiwan. The evaluation proceeds from 2023–2030 for different rates of carbon charge for the GHGs by a model of “Taiwan Economic Input Output Life Cycle Assessment and Environmental Value” constructed in this study. It is innovative in the literature to simulate the benefits of GHG reductions and health co-benefits of air pollutions for the industrial sector under the imposition of a carbon charge comprehensively. The results consistently show benefits whether the charge is imposed on the scope 1 and scope 2 GHG emissions or on the scope 1 emissions only. The health co-benefits are on average about 5 times those of GHG reductions benefits in 2023–2030. The average total benefits with the summation of GHG reduction benefits and health co-benefits are 821.9 million US dollars and 975.1 US million US dollars per year, respectively. However, both the GHG reduction benefits and health co-benefits are consistently increasing at a decreasing rate in 2023–2030. The increased multiple for the rate of the carbon charge is higher than the increased multiple of the total benefits and this result shows that the increase of the carbon charge becomes less effective.
... However, the application of each methodology at a time does not allow a fully comprehensive environmental impact assessment [8,29]. Different research groups have proposed methodologies combining LCA and MFA, especially in circular economy models and urban stock calculation [8,[29][30][31]. ...
... However, the application of each methodology at a time does not allow a fully comprehensive environmental impact assessment [8,29]. Different research groups have proposed methodologies combining LCA and MFA, especially in circular economy models and urban stock calculation [8,[29][30][31]. ...
There is a growing demand in Latin America and the Caribbean for building materials to satisfy the need for adequate housing and infrastructure in urban areas. This paper examines the consumption of materials and environmental impact of ready-mix concrete produced in the Metropolitan Region of Buenos Aires in a certain period of time. Material flow analysis and life cycle assessment (LCA) were performed. The average composition concrete was estimated by means of surveys conducted with ready-mix concrete producers. The material efficiency (ME), CO2 equivalent emissions (ECO2eq), materials and energy use were used as environmental indicators. Feasible impact reduction strategies and their influence on the LCA were also explored. 7.16 Mt of materials were required to produce 2,604,862 m3 of ready-mix concrete, within 99.1% corresponded to raw materials, while 0.9% corresponded to secondary raw materials. 5.36 Mt (∼78.6%) of the extracted materials belong to aggregate production and they represent ∼19.5% of the ECO2eq. Portland cement is the largest contributor to ECO2eq and the constituent material with the lowest ME. Using recycled aggregates is the strategy that contributes the most to the reduction of the use of raw materials (∼8.9% lower use of raw material by using 20% recycled coarse aggregate), while replacing Portland cement with supplementary cementitious materials (SCM) is the one that reduce the most the ECO2eq (the use of Portland cement without SCM would increase ECO2eq by ∼13.6%). This research provides a novel approach that quantifies the effect of modifying the concrete mix and replacing raw materials by secondary raw materials, bringing a new understanding to the sustainability of building materials.
... In the next sections, some of the contributes listed in the matrix of previous Table 1 are discussed highlighting the potential of integration in terms of a larger comprehension of the phenomenon under analysis. Meglin et al. (2022a;2022b) integrated Material Flow Analysis (MFA) and Life Cycle Assessment (LCA), with Input-Output Analysis (IOA) as the connecting element. Such an assessment method considers indicators for environmental impacts and economic benefits and provides the necessary data and indicators for a holistic and comprehensive evaluation of a region or industry. ...
... An application to the construction sector of a Swiss canton is proposed to show the potential of the method. Extending their work, Sensitivity Analysis and Monte Carlo Simulation were used (Meglin et al., 2022b) to check the robustness of the model and to see if it has reasonable uncertainties to confirm the combination of MFA and LCA with an IO approach leads to a reliable assessment of a region. The authors then use the uncertainties and sensitivities to formulate initial indications of how business models are affected by the shift to CE and conclude that vertical integration of different sectors makes sense regarding a CE to buffer price volatilities, but also to secure the supply of raw materials. ...
Technical Report
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This deliverable of the ReTraCE project further elaborates the results and conceptual frameworks presented in previous reports, dealing with impacts and performance assessment of circular economy policies and processes. This report presents a “conceptual and practical model” that aims at identifying the key stakeholders involved in the transition to a circular economy (CE). Including local communities which assert the roles of both civil society and consumers, these stakeholders span across different organisations and institutions such as companies, state law, and public administration. The transformations that occur at a micro, meso, and macro system level along with the accompanying innovation patterns due to the CE transition, can be evaluated by employing existing sustainability tools, grasping which are the potential costs and benefits of implementing CE patterns as well as which are main barriers and challenges in implementing them. Therefore, the intended audience of this deliverable will find tools, applications, procedures, and guidelines for an evaluation as complete and organised as possible of the supportive information needed for realising and monitoring the transition from the linear to the CE model in agreement with the three sustainability pillars (environment, economy, and society).
... We developed an IAM to assess a regional industry in terms of environmental and economic indicators and combine Material-Flow-Analysis (MFA) and Life-Cycle-Assessment (LCA) using an inputoutput approach. We use comprehensive MFA-data of a Swiss database of regional material flows of mineral building materials (Rubli, 2020) in combination with environmental data from the LCA database ecoinvent (Wernet et al., 2016) by using an input-output approach (Meglin et al., 2021). From this combination, we create an environmental extended input-output analysis (EEIOA) that allows us to assess a regional building materials industry for mineral building materials, in our case sand, gravel, cement, concrete as well as excavation material and CDW (see supplementary material) The MFA data is first transferred to a physical input-output table (PIOT). ...
... Argovia has the largest impacts as it is home to two of the six Swiss cement plants. A comparison with the two other regions shows that the cement industry is decisive in the environmental assessment of the regions (Meglin et al., 2021). In Zurich or Thurgovia, the direct emissions are much lower since there are no significant CO 2 and energy-intensive processes. ...
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National policies are increasingly being introduced worldwide to establish a sustainable economy that includes principles of a circular economy (CE). The construction industry is particularly in focus with such policies, as it is responsible for almost 50% of the worldwide annual resource consumption and waste production. The Implementation of CE policies remains with local actors, and it is important to better understand the regional context of this transition to support policy- and decision-makers. This paper aims to contribute to the understanding of regional aspects of a CE and identify regional differences in the building materials industry. To identify these different boundary conditions, we formulate hypotheses, which we then test based on various regional case studies. We use an integrated assessment model to assess a regional industry in terms of environmental and economic indicators and combine Material-Flow-Analysis and Life-Cycle-Assessment using an input-output approach. The results suggest that imports and exports, especially in smaller regions, can hinder the implementation of CE. CE policies should therefore be developed for functional areas rather than political boundaries to effectively manage material flows. This is also in the light of environmental impacts. Consideration of inter-industry linkages in the industry shows that policies should be formulated specifically for the construction processes, as they have the greatest leverage for policy-induced changes within the industry. The financial analysis shows that incentives should be created to minimize the extraction of primary raw materials and to avoid the landfilling of demolition and excavation material.
... El consumo de materiales requerido por la industria de la construcción en el mundo es cada vez mayor (Meglin et al., 2021). Esto obedece, en gran medida, a la demanda de edificaciones e infraestructuras por el incremento de la población y al aumento del nivel de ingresos en muchos países (Bilal et al., 2020;Reza Esa et al., 2017a). ...
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En la actualidad, los residuos de construcción y demolición (RCD) representan grandes retos para la industria de la construcción. Esto se debe en buena medida a los impactos ambientales negativos que conlleva su alta disposición en vertederos, los bajos niveles de aprovechamiento y el desconocimiento generalizado sobre prácticas de circularidad en el sector. Las estrategias con enfoque de economía circular (EC) brindan una serie de oportunidades para mejorar la gestión de estos residuos en las diferentes fases de un proyecto constructivo. En Colombia, la normativa para el manejo, control y aprovechamiento de los RCD está estipulada en la Resolución No. 0472 de 2017, la cual se convierte en un hito para la implementación de medidas de EC en el país. En este orden de ideas, el presente artículo tuvo como propósito discutir el potencial de la EC como dinamizadora en la gestión de los RCD y examinar tanto los procesos como las percepciones de los gestores de los RCD que se encuentran inscritos en el Área Metropolitana del Valle de Aburrá (AMVA), Colombia. Para ello, se llevó a cabo un estudio cualitativo y descriptivo en la revisión de las prácticas de circularidad en el ámbito regional y mediante enfoque exploratorio, se recurrió a la aplicación de entrevistas semiestructuradas y análisis documental para conocer la situación y la madurez de las empresas gestoras de los RCD. Como resultados se presentaron la descripción de los procesos y las materialidades gestionadas en el área metropolitana, las limitaciones y los avances percibidos por los gestores de RCD en el AMVA. De este modo, se encontró una región con un gran potencial de aprovechamiento donde actualmente casi todos los RCD son direccionados a la disposición final (aprox. 99.5 %); por tanto, se requiere de más actores que ingresen a este ecosistema y que desde la esfera estatal se brinden las condiciones para evitar las limitaciones descritas en este estudio.
... First, MFA is integrated with evaluation methods to assess the economic or environmental benefits of ME strategies on a regional level. Such integrations are important to evaluate the sustainability of strategies to enable a regional circular economy (Meglin et al., 2021;OECD, 2020). For example, environmental layers are added to study the impact of strategies in municipal or electronic waste management systems on an urban and regional level using integrated MFA-LCA models (De Meester et al., 2019;Thushari et al., 2020;Turner et al., 2016). ...
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Material efficiency (ME) strategies are pursued by governments and companies to reduce environmental emissions, improve supply chain resilience, and enhance cost competitiveness. Material flow analysis (MFA) methods are useful to quantify raw material stocks and flows and assess the potential impacts of ME strategies. Although the popularity of MFA methods is increasing, there are methodological limitations that hinder its use as a decision support tool for prospective assessments. To overcome some of these, MFA is increasingly integrated with other methods from different research fields. This paper categorizes integrated MFA methods by identifying and explaining the methods and their applications. A semi‐structured literature review screened a wide range of methods integrated with MFA prospective analysis and evaluated their applications from 158 studies. This showed that integrated MFA can be used to: (1) include economic, social, and environmental layers; (2) improve the technical foundation of MFA by including entropy and exergy analyses and process engineering methods; (3) include economic mechanisms and link the economic system to the material system; and (4) improve the representation of materials in existing methods and models. Our research demonstrates that integrated MFA should be a central method in planning and designing ME strategies for companies and governments. This paper provides an important knowledge base of integrated MFA methods and creates a discussion point on MFA, where the research field is currently at or indeed where it could be heading in the future, that is, “Quo Vadis” MFA.
... Müller, 2006), and its principle has been applied, amongst others, in dynamic building stock models (Mastrucci et al., 2017a). Some review articles on MFA (Allesch and Brunner, 2015;Augiseau and Barles, 2017;Göswein et al., 2019;Guo and Huang, 2019;Lanau et al., 2019;Müller et al., 2014) show that recent MFA studies particularly focused on bottom-up models that are more data-intensive (e.g. more detailed building archetypes) (Heeren and Fishman, 2019), often in combination with other tools, such as GIS , LCA (Meglin et al., 2021), and system dynamic models (Tang et al., 2021;Yang et al., 2021). The MFA model of (Heeren and Hellweg, 2019) employed GIS data, building inventory data, and lifetimes of buildings and components to characterize the Swiss residential building stock, which has the potential to geographically aggregate future materials flows to different regional levels. ...
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Urban mining is regarded as an important strategy to replace primary raw materials in the building sector. This study presents a bottom-up dynamic building stock model to explore the potential of urban mining to reduce primary material consumption and greenhouse gas (GHG) emissions in the residential building sector of the Netherlands. The model builds upon geo-referenced individual buildings, making it possible to analyze the spatiotemporal pattern of material supply from demolition and material demand for construction and renovation. The main results can be summarized as three points. (1) Urban mining cannot meet future material demand due to the new construction caused by population increase and its limited ability to supply the required kinds and amounts of materials. Therefore, large amounts of primary materials still have to be consumed in the future. (2) The generation of demolition wastes and the requirement for materials will be mainly concentrated in the big cities (e.g. Amsterdam, Rotterdam, and The Hague). (3) The GHG emission reduction potential of urban mining is very small and is not as large as the transition to a greener electricity mix. Recycling together with a greener electricity mix would reduce annual GHG emissions by about 40% in 2050 compared to 2020. This study provides a tool to link future material inflows and outflows in space and time. It further helps to assess the performance of strategies aimed at closing the material loops and reducing GHG emissions in the building sector.
Given the fragmentation, a holistic perspective of the construction value chain is necessary in driving a systematic Circular Economy (CE) implementation in the construction industry. Therefore, the study adopted a Systematic Literature Review (SLR) to systematically analyze the current knowledge body of CE in the construction value chain perspective. Thereby, the study aims to propose a theoretical framework called ‘Construction Industry Circular Value Chain Framework’ to drive systematic CE implementation in the construction industry. 43 CE strategies were identified under the reformed circular value chain that was also proposed by the study for the construction industry. Different operational initiatives were also identified under each of these CE strategies and their contribution to the Built Environment Applications of the ReSOLVE framework actions was also established. The study contributes to theory by developing a means of breaking down the business actions of CE implementation into CE strategies along the construction value chain and building up these CE strategies contribute towards business actions of CE implementation in the construction industry. The findings of the study can be made use by the practitioners to revisit their value chains and by policy makers to develop necessary infrastructure in driving systematic CE implementation in the construction industry.
Current methods available to calculate eco-efficiency require a sample of products and are not applicable for one product only. Furthermore, the methods require a weighting process. Thus, they contain subjectivity, or it is possible that the weighting factors' values do not match stakeholders' values. This paper proposes a new method of measuring the eco-efficiency ratio. The numerator is the contribution of a product's life cycle to the economy, and the denominator is the economic burden caused by a product's life cycle. The economic contribution is calculated using the input-output method. The economic burden is calculated by estimating the health damage caused by pollutant emissions over a product's life cycle. The damage is expressed in Disability Adjusted Life Years (DALY) and is valued using the human capital approach. The applicability of the proposed method is presented by calculating the eco-efficiency of electricity generations in Indonesia. The proposed method shows that the eco-efficiency ratio of a product depends on the income and tax multiplier, supply chain process efficiency, value of the product, GDP per capita, and the level of emissions. The proposed method enhances the decision-making process because it is more straightforward, free from subjectivity, and applicable for one product only.
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Global industrialization and excessive dependence on nonrenewable energy sources have led to an increase in solid waste and climate change, calling for strategies to implement a circular economy in all sectors to reduce carbon emissions by 45% by 2030, and to achieve carbon neutrality by 2050. Here we review circular economy strategies with focus on waste management, climate change, energy, air and water quality, land use, industry, food production, life cycle assessment, and cost-effective routes. We observed that increasing the use of bio-based materials is a challenge in terms of land use and land cover. Carbon removal technologies are actually prohibitively expensive, ranging from 100 to 1200 dollars per ton of carbon dioxide. Politically, only few companies worldwide have set climate change goals. While circular economy strategies can be implemented in various sectors such as industry, waste, energy, buildings, and transportation, life cycle assessment is required to optimize new systems. Overall, we provide a theoretical foundation for a sustainable industrial, agricultural, and commercial future by constructing cost-effective routes to a circular economy.
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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 scholars consider these two concepts identical, while others contemplate them as different. Several theoretical approaches have been presented to clarify the content of these two concepts and to provide effective ways to solve the social and environmental problems. The goal of this paper is to examine the existing literature regarding the content of CE and S based on a triple-level analysis (micro, meso, and macro level) across different scientific fields: economic/management and engineering/natural science. Our findings show many theoretical approaches with several relationships, similarities, and differences among CE and S at the micro, meso, and macro-levels within engineering and management scientific fields. Based on these findings, a future research agenda on CE and S is also proposed.
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The European Union has vowed to transition from a linear to a circular economy (CE). Many innovations, new business models, and policies have begun to emerge to support the push for further institutionalizing CE practices. A large portion of these attempts are based on transforming a flow currently labeled as a waste stream into a value proposition, i.e. a resource. However, this ironically increases the risk of creating a demand for these waste streams, which thereby may become commodified. In this article, we unpack the inherent dilemmas and implications created by this phenomenon, which we define as the Waste-Resource Paradox (WRP). Understanding the WRP is highly relevant, as its manifestation may lead to situations in which the further establishment of “circular” practices may reinforce linear economy by sustaining a waste (over)production in the system or causing undesired social or environmental repercussions. This can tighten a lock-in of the existing linear structures counteractive to CE that have not been explicitly identified or explored to date. We observed that the WRP may evolve and morph throughout time, across boundaries or respective to different societal sectors. Based on our findings, we highlight the profound implications of the WRP for the future of circularity and the potential consequences for a transition to CE.
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The current global interest in circular economy (CE) opens an opportunity to make society's consumption and production patterns more resource efficient and sustainable. However, such growing interest calls for precaution as well, as there is yet no harmonised method to assess whether a specific CE strategy contributes towards sustainable consumption and production. Life cycle assessment (LCA) is very well suited to assess the sustainability impacts of CE strategies. This position paper of the Life Cycle Initiative (hosted by UNEP) provides an LCA perspective on the development, adoption, and implementation of CE, while pointing out strengths and challenges in LCA as an assessment methodology for CE strategies.
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Circular economy (CE) offers a pathway towards sustainable, closed-loop resource systems, but widespread adoption across industrial sectors is limited by fragmented knowledge and varied implementation approaches. This article reviews sector-specific challenges and opportunities associated with implementing and measuring the benefits of CE strategies. Literature mapping highlights progress towards CE implementation in food, chemicals, metals, consumer electronics, and building and infrastructure sectors, and towards measuring CE outcomes via systems analysis methods like life cycle assessment (LCA) and material flow analysis (MFA). However, key challenges were also identified that point to future research and demonstration needs. First, research on CE adoption typically exists as case studies that are closely linked to a sector. But literature has not effectively synthesized knowledge gained across domains, particularly understanding underlying barriers to CE and where they occur in product life cycles. Second, research on CE outcomes often applies well-established methods without adapting for unique attributes of CE systems. A key opportunity is in integrative methodological advances, such as expanded use of consequential LCA, development of physical Input–Output tables, and integrating MFA with dynamical models. Finally, regardless of sector, new CE business models are seen as a critical enabler to realize success, but theoretical frameworks in literature are not well-tested in practice. The review also highlights opportunities to harness other emerging trends, such as big data, to provide better information for system modelers and decision-oriented insight to guide CE stakeholders. Graphic abstract
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The present study investigates long-term energy consumption and CO2 emission pathways of the Swiss cement industry, including pathways towards net zero CO2 emissions by 2050. Cement production accounts for 8% (12.8 PJ) of the final energy consumption and 36% (2.5 Mt) of the CO2 emissions in the Swiss industrial sector in 2015. Using a techno-economic bottom-up optimization model based on the TIMES (The Integrated MARKAL-EFOM System) modeling framework, this study applies an advanced modeling technique for the Swiss TIMES Energy system Model (STEM) that expands the modeling of energy flows with additional material and product flow modeling. This allows a more detailed technology representation as well as to account for process related emissions in the cement sector. This modeling framework is applied for a scenario analysis focusing on energy efficiency as well as decarbonization, which ultimately contributes to an improved understanding of energy technology development and identifies policy strategies for the realization of a decarbonized cement industry. The results show that, in accordance with current trends, future cement production reduces its specific energy consumption from 3.0 GJ/tcement in 2015 to 2.3 GJ/tcement in 2050. Simultaneously, cement production decreases its CO2 emission intensity from 579 kgCO2/tcement in 2015 to 466 kgCO2/tcement in 2050 due to the decreasing average clinker content in cement and energy efficiency improvements. Even without major climate policy intervention in the future, it is economically beneficial to replace and improve the existing equipment with more energy efficient technologies. However, our results show that for a drastic reduction of the CO2 emissions in order to comply with the goals of the Paris Agreement, the cement sectors relies on CO2 capture because of the process related emissions. The results show that a minimum CO2 tax of 70 EUR/tCO2 is required for the CO2 capture technologies to become economically competitive.
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Circular business models (CBMs) and their potential environmental benefits have been widely assessed by using life cycle assessment (LCA). However, most LCA studies consider static systems and assume instant and full technology adoption, limiting the analysis of the implications of circular transitions. Considering technology diffusion in LCA models may bring a better understanding of the environmental implications of the adoption of CBMs. Nevertheless, diffusion is also related to stock dynamics, which are difficult to represent in classic LCA models. To overcome these issues, we propose a modeling framework that integrates three modeling families to assess the environmental impacts and material implications of the adoption of CBMs: diffusion of innovations, product stock dynamics, and LCA. We present a method of application and illustrate it with a theoretical case study. This framework might be useful in the socio‐economic analysis of systems transitioning to CBMs, especially in systems that involve long‐lived products.
Increasing environmental concerns and resource scarcity risks have drawn attention to a Circular Economic (CE) model during the last decade. Nevertheless, literature related to the state of practice of CE in the built environment in the United States (U.S.) is still limited. In this context, this study investigates U.S. architectural, engineering, and construction (AEC) industry stakeholders’ awareness of CE. The investigation also covers major barriers for the implementation of strategies aligned to the CE model, and enabling factors for a transition from a linear economic model to a CE model in the construction industry in the U.S. A mixed-methods approach was deployed through a combination of online survey and interviews with AEC industry stakeholders from different regions of the U.S. Results revealed that some strategies are widely disseminated (i.e., open-loop recycling, selective demolition, and prefabrication), whereas others are hardly adopted (i.e., design for disassembly, design in layers, closed-loop recycling). Additionally, findings indicate budget and upfront costs, project schedule and timeline, lack of awareness and regulations, and current business models as major barriers for the implementation of strategies aligned to a CE model. Furthermore, four enabling factors for a transition to a CE model in the construction industry were identified (i.e., education and cultural change, data availability, policies and incentives, and novel voluntary stewardships). Notably, contributions of this study include fostering a much needed debate around circular construction and its challenges, and expanding the limited existing body of knowledge.
Insights from research into transitions of socio-technical systems start to influence policy design, pushing for more sustainable production and consumption systems. Policy implementation is often met with resistance from a variety of actors and faces systemic inertia to change. We examine this resistance and the role of business models within industry-sector transitions through a case study on the Swiss construction material industry. Business model logics can form barriers to change and inhibit the diffusion of alternative logics. Using a system dynamics perspective, we identify feedback loops that form barriers to transitions. These feedback structures promote the understanding of an organisation’s role in a changing environment and to anticipate problematic future scenarios. Causal loop diagramming explicates the need for participative governance as it builds on shared mental models among relevant key actors. This study demonstrates the value of using dynamic systems thinking to understand the role of business models in industry sector transitions.