Comparing a territorial-based and a consumption-based approach to assess the local and global environmental performance of cities

Journal of Cleaner Production xxx (2016) 1e12

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Comparing a territorial-based and a consumption-based approach to assess the local and global environmental performance of cities Aristide Athanassiadis a, b, c, *, Maarten Christis d, e, Philippe Bouillard b, An Vercalsteren f, Robert H. Crawford c, Ahmed Z. Khan b a

Belgian Fund for Scientific Research (F.R.S.-FNRS), Brussels, Belgium Building, Architecture and Town Planning Department e Universit
e Libre de Bruxelles, Brussels, Belgium Faculty of Architecture, Building and Planning e The University of Melbourne, Melbourne, Australia d Policy Research Centre for Sustainable Materials Management, Kasteelpark Arenberg 44, 3001, Leuven, Belgium e University of Ghent, St. Pietersnieuwstraat 33, 9000, Ghent, Belgium f VITO NV, Boeretang 200, 2400, Mol, Belgium b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 25 February 2016 Received in revised form 4 October 2016 Accepted 14 October 2016 Available online xxx

In the framework of pressing local and global environmental challenges it is essential to understand that cities are complex systems dependent on and linked to the rest of the world through global supply chains that embody an array of environmental flows. Cities are thus a complex articulation that intertwine local and global challenges which rely at their extended hinterland for their resource use and pollution emission. To assess the environmental sustainability of an urban area in a comprehensive manner, it is not only necessary to measure its local and direct environmental performance but also to understand and take into account its global and indirect environmental counterparts. This paper presents a comparative analysis of a territorial-based and a consumption-based approach to estimate both direct and embodied resource use and pollution flows for the case of Brussels Capital Region (Belgium). The territorial-based approach is based on local energy, water and material consumption measured data as well as measured data on waste generation and pollution emissions. The estimation of indirect resource use and pollution emissions (or consumption-based approach) is based on the regional IO-tables of the city-region of Brussels extended with multi-region input-output tables, taking into account the global flows of consumption. The comparison of these two approaches is particularly relevant in the case of cities that have limited productive activities and limited or no extraction of materials as the impact on the hinterland is often underestimated or neglected by local (environmental) policies which are only based on territorialbased figures. The results show that the indirect primary energy use, GHG emissions and material use estimated by the consumption-based approach is more than three times higher than local measures indicate. The embodied water use, estimated via IOA, was over 40 times higher than the local water consumption. These results show that territorial-based approach using local data underestimate the resource needs and pollution emissions of a city and can therefore be insufficient or even be misguiding. By mapping the origin of embodied flows it is in fact possible to illustrate the open character of an urban economy and its dependence on the global hinterland. Finally, this paper discusses the possibility and relevance to combine these two approaches to create a hybrid framework that measures the full environmental performance of cities both accurately and comprehensively. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Urban metabolism (UM) Multi-region input-output analysis (MRIO) Environmental footprint of cities Direct and indirect flows Local and global consumption EW-MFA

1. Introduction

* Corresponding author. Department BATir e Building, Architecture & Town
Libre de Bruxelles (ULB), Avenue F.D. Roosevelt 50, CP 194/2, Bplanning, Universite 1050, Brussels, Belgium. E-mail address: [email protected] (A. Athanassiadis). URL: http://batir.ulb.ac.be/index.php/people/249

During the last century, the global extraction of fossil energy carriers increased by a factor of 12, ores and industrial minerals by a factor of 27, and construction minerals by a factor of 34 (Krausmann et al., 2009). This unprecedented use of natural resources was largely triggered by the expansion and creation of new cities, and

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Please cite this article in press as: Athanassiadis, A., et al., Comparing a territorial-based and a consumption-based approach to assess the local and global environmental performance of cities, Journal of Cleaner Production (2016), http://dx.doi.org/10.1016/j.jclepro.2016.10.068

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their respective built environment and infrastructure, resulting in major environmental issues globally. Through this unprecedented use of resources, urban areas are now widely acknowledged to have a considerable effect on the environment. In fact, it is estimated that urban areas use 67e76% of global energy supply and contribute for 71e76% of global CO2-emissions caused by energy use (Seto et al., 2014). In addition, while resource use of urban areas is already posing serious stress in relation to resource depletion (Prior et al., 2012), sustainable provision of ecosystem services (Corvalan et al., 2005) and to human health (McMichael et al., 2008), these threats could worsen in the future as urban population continues to grow (UN, 2014). The incumbent creation and expansion of urban areas due to the increase of urban population will increase direct resource use and its associated environmental effect. In addition, the construction of new urban infrastructure will add a considerable embodied environmental effect both locally and globally (Müller et al., 2013). Indeed, urban areas are open systems depending on the outside world or hinterland to provide materials and products and to absorb and process waste (Bai, 2007). In other words, cities are nodes of a complex global network that receive and distribute information, capital, and population but also matter, energy and water flows in various forms. Therefore, cities can be seen as neuralgic nodes of resource consumption that mobilize resource flows and stocks from around the world to fulfil both its inhabitants and economic needs. To consider an urban area as sustainable it is necessary that its inflows of material and energy and its disposal of waste and generation of pollution do not exceed the capacity of its hinterland (Kennedy et al., 2007; Rees and Wackernagel, 1996). To manage and mitigate existing and future environmental pressure coming from cities, it is first necessary to have a clearer idea of how urban areas function. Aside from a comprehensive monitoring of resource use and pollution emissions it is important to have a better understanding of the origin of these flows as well as the responsible actors. However, the environmental assessment of a city is complex and currently there is no commonly accepted and widely adopted methodology (Loiseau et al., 2012). A number of accounting methods and tools have been used for to measure and understand the metabolism of cities such as, amongst others, material flow accounts, ecological footprint, substance flow analysis, emergy analysis, exergy analysis, environmentally extended input-output analysis, physical IO-tables, ecological network analysis, process analysis, and hybrid IO life cycle assessment (Dias et al., 2014). Baynes and Wiedmann (2012) distinguished two main approaches for assessing urban environmental sustainability: the production or territorial-based approach and the consumptionbased approach. These two approaches often use different accounting methodologies showing two different sides of urban resource use and pollution emissions. The former generally uses local and often more accurate data reporting direct resource flows and pollution flows entering and exiting urban areas due to local consumption and production regardless of whether these activities are serving the local inhabitants or people outside the city boundaries (Minx et al., 2011). On the other side of the spectrum, the consumption-based approach encompasses all the flows needed to satisfy the consumption of a city, directly and indirectly, wherever in the world these may occur (Minx et al., 2011). This approach uses local (when available), national and multi-region (MR) environmentally-extended IO-tables to approximate consumption of a city as physical flows that can be imported or exported from around the globe, or in other words the environmental flows embodied in trade. While the territorial approach can, in principle, be considered as more accurate in quantifying the direct impact of a territory, this

only presents a partial view of urban consumption and pollution as cities are rarely self-sufficient (Baynes et al., 2011). Indeed, the territorial-based approach falls short in modelling and expressing the complex articulation and interconnectedness between cities and the rest of the world through the global economy (Lenzen et al., 2012; Lenzen and Peters, 2010). On the other hand, the consumption-based approach can encapsulate a more complete picture of urban consumption, however results represent estimates that cannot be physically validated in their entirety. Therefore, putting side to side the results of these two approaches is particularly relevant in order to assess both the local and global environmental pressure of cities especially for cities that have limited productive activities and limited or no extraction of materials. While both approaches study the same urban area they have a major difference in the definition of their system boundaries. The territorial approach focuses only at the city level accounting all flows entering and exiting the urban area disregarding all other flows. The consumption-based approach focuses on the environmental performance of the same urban area, but takes into account all flows that are directly or indirectly mobilised for the city's consumption across the entire globe. Therefore, in the consumption-based approach the system boundaries are nested including both the local and global simultaneously. Munksgaard et al. (2005) stress that accounting for environmental pressure on a purely territorial basis may be appropriate for impacts such as localized urban pollution or urban microclimate. However, an assessment of global effects such as climate change needs to take into account indirect contributions from outside the city boundary. The present study addresses the challenge of putting together both a local and global environmental assessment of a city by comparing a territorial– and a consumption-based approach for the case of Brussels Capital Region, ‘Brussels’ shortly (Belgium). After providing a more thorough description of these two approaches, their results are compared to highlight the advantages of each one, to discuss how they present different views of a city's environmental performance or sustainability and analyse the discrepancies between them. It is important to mention here that the territorialbased results will mainly be estimated through local and precise data, whereas the consumption-based results will be measured through multi-regional input-output analysis. The results of each approach and their comparison will focus on a number of flows such as energy, water, materials and air pollution explicating how much the territorial approach underestimates the environmental unsustainability of Brussels. In order to validate the consumptionbased approach results and to discuss how the results of each approach could feed each other, MRIOA was also used to produce territorial based results. This article will conclude by underlining the importance of developing a hybrid methodology combining territorial-based and consumption-based approaches to streamline more comprehensive urban environmental assessments. 2. Methodology This section describes the two approaches that are used to assess the local and global resource use and atmospheric pollution emissions of Brussels. It contains a brief overview of territorial and consumption-based approaches in the framework of urban environmental assessments. The methodological framework of each approach, that were used to arrive at the presented results for the case of Brussels in 2007, will then be outlined, compared and discussed concerning their relevance in terms of environmental assessment and policy-making. To compare the territorial-based and the consumption-based approach, the case of Brussels (Brussels Capital Region) was chosen. Brussels is one of the three administrative regions of Belgium,

Please cite this article in press as: Athanassiadis, A., et al., Comparing a territorial-based and a consumption-based approach to assess the local and global environmental performance of cities, Journal of Cleaner Production (2016), http://dx.doi.org/10.1016/j.jclepro.2016.10.068

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along with Wallonia and Flanders, that have their own government and parliament. In this research we chose Brussels for its specificity of being a city-region (administratively speaking), offering thus a considerable advantage for data availability and especially for the availability of a regional IO-table that will be then nested in global MRIO tables needed for the consumption-based approach. As it will be described in the following section the latter can be very challeging to be found at the urban scale. Therefore, in our case, the consumption-based approach can describe more accurately the local-global articulation of Brussels with its global hinterland. The year 2007, was chosen for this comparison as it was the most recent year for which both local data and a local input-output table were available. To better contextualize the results of Brussels presented in the next sections it should be noted that in 2010, Brussels covered 161.4 km2, hosted 1,090,000 inhabitants and generated a GDP of 67,746 million euros, or 18.5% of Belgian GDP of which 89.6% from the tertiary sectors (IBSA, 2014b). Further contextual pieces of information about the case study of Brussels as well as their evolution including its built environment and socio-economic facets can be found in Athanassiadis and Bouillard (2013) and Athanassiadis et al. (2016). 2.1. Territorial-based approach (using local data) Territorial-based approach (TBA) uses a number of accounting methodologies such as Material Flow Analysis, Ecological Footprint, Emergy and Exergy analysis, Input-Output Analysis and others in order to measure or estimate the direct environmental performance or direct urban metabolism (UM) of a territory (Zhang et al., 2015). Territorial-based approach comprehensively considers all resource use and pollution emissions flows entering and exiting an urban area regardless if these flows are satisfying the needs of local inhabitants or of foreign economies (Minx et al., 2011). Case studies frequently focus on a particular flow entering, being stocked or exiting a specific urban system or of a specific economic sector. These flows can range from resource flows (i.e. energy, materials and water), to pollution flows (i.e. GHG emissions and heavy metals), to the assessment of materials being added to the material stock of the city (Barles, 2007; Huang and Hsu, 2003; Kennedy et al., 2011; Kenway et al., 2011; Kral et al., 2014). TBA studies can thus be of great relevance to propose local environmental policies for a specific flow but also to monitor the environmental state of urban areas as an overview (Zhang et al., 2015). However, due to relative novelty of the field and great discrepancy of data (both in accuracy and comprehensiveness) that describe a city's direct metabolism, there is still no consensus on the methodology to be used. Most case studies choose, adapt or even develop their accounting methodology depending on the data availability and the specific case study (Barles, 2009; Niza et al., 2009; Voskamp et al., 2016). In some cases, the assessment can come down to a “large data collection exercise” (Kennedy and Hoornweg, 2012). This loose assessment framework can result in case studies having very different levels of disaggregation, precision and comprehensiveness. The lack of a well-founded methodology can be a critical shortcoming when comparing studies. However, this study focuses on another limitation of territorialbased urban environmental assessment. As mentioned previously, it only covers the direct environmental flows (i.e. resource and pollution flows) of cities and does not account for the indirect environmental flows that are embodied in trade and induced by local consumption in other parts of the world. Due to the interconnected character of the global economy (Lenzen et al., 2012), cities can be seen as nodes on a global production-consumption network that require natural resources, goods and services to function on the one hand, and that emit pollution of different forms

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Fig. 1. Main flows included in for the establishing the direct urban metabolism or territorial based approach results.

on the other, both locally and globally. Therefore, not taking into account the effects that cities have on their hinterland overestimates the sustainability of cities (Lenzen and Peters, 2010) and can result in the local implementation of social, economic and environmental policies that have contradictory or undesired effects at other scales. 2.1.1. Methodology and data used for this case study This section provides further detailed information about the methodology used in this study for establishing the territorialbased results focusing on providing a picture of the direct metabolism of Brussels as precisely and reliably as possible. In fact, these results provide not only a first overview of Brussels environmental profile but also facilitate the validation of the consumption-based results based on MRIOA. While, MRIOA is also used to provide territorial-based approach results, this specific part will be described in the consumption-based approach as both results use the same methodology. In this paper, 6 different flows are detailed for the direct metabolism of Brussels: namely energy, water inflows and outflows, material inflows and outflows (including waste) and atmospheric pollution (see Fig. 1). Whenever possible, these flows are disaggregated by sector use or by source. The energy flow (measured in GJ) is disaggregated into different energy sources (natural gas, electricity, petroleum products and others) and sectors of consumption (industry, tertiary, residential and transport1). It is important to note here, that natural gas and electricity use is data obtained from meters, whereas petroleum product use is obtained from fuel pumps located within the Brussels territory (IBGE, 2009). In the case of water, input and output water flows are differentiated. Natural flows of water from precipitations or from rivers flowing in Brussels are not considered. Input water flows are expressed in supplied and used water for drinking and production activities (HYDROBRU, 2010). Similarly to energy flows, input water flows or water use (measured in 103 m3) is obtained from meters and can be subdivided into activity sectors (VIVAQUA, 2014). For the water flows exiting the Brussels territory, only wastewater treated by the water treatment plants is presented in Table 1. All natural water from rivers flowing out of Brussels as well as nontreated precipitations are not considered (SBGE, 2011). As Brussels has a combined sewer that collects both waste water coming from water use and surface runoff, the output flows covers a significant amount of precipitations that are not absorbed by the

1 Due to its insignificant contribution, the use of energy in the agricultural sector was not included.

Please cite this article in press as: Athanassiadis, A., et al., Comparing a territorial-based and a consumption-based approach to assess the local and global environmental performance of cities, Journal of Cleaner Production (2016), http://dx.doi.org/10.1016/j.jclepro.2016.10.068

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Table 1 Urban metabolism flows disaggregated by sector use for 2007 of Brussels. Indicators

Unit

Total

Residential

Tertiary

Industry

Transport

Source

Energy Electricity Natural gas Petroleum products Others Water Supply Consumption (use) Wastewater Atmospheric pollution GHG (CO2, CH4, N2O, F) CO2 CO SOx NOx Particles Solid waste Waste generated

TJ TJ TJ TJ TJ

81,158 21,369 31,068 28,044 583

32,823 5296 20,499 6439 595

25,351 13,691 9517 2901 247

2483 1315 1055 109 8

19,519 1068 21 17,727 703

(IBGE, (IBGE, (IBGE, (IBGE, (IBGE,

103 m3 103 m3 103 m3

67,436 59,169 130,513

e 39,548 e

e 16,767 e

e 1511 e

e 546 e

(VIVAQUA, 2014) (VIVAQUA, 2014) (SBGE, 2011)

kt kt t t t t

3937 3652 8424 980 5850 679

1650 1643 3021 666 993 63

747 745 520 276 486 16

73 72 69 10 171 4

897 885 4725 5 3838 277

(IBGE, (IBGE, (IBGE, (IBGE, (IBGE, (IBGE,

kt

2162

482

290

1350

40


, 2010; IBGE, 2008) (Bruxelles-Proprete

ground. Finally, as the two largest water treatment plant of Brussels are installed in 2007, there is no reliable data for this year, therefore data for 2010 were used instead. Materials inflows include imported materials while material outflows combine exported materials as well as solid waste (measured in kt). However, contrary to energy and water flows, material flows were much harder to quantify precisely. The results of imported and exported materials correspond to the sum of materials that are unloaded and loaded in Brussels, respectively (IBSA, 2014a; Port de Bruxelles, 2014). These flows can be further disaggregated by mode of transportation (road, rail and water) but not by material type. In addition, with the available information it is currently impossible to know whether imported materials are locally used (and by which activity sector) or are only transiting through Brussels territory. For exported materials, it is also impossible to know whether they are locally produced or if they are simply transiting imports. Due to the number of uncertainties around these data material imports and exports results should be used with great caution. The solid waste flows exiting Brussels territory are estimated, but the estimation should be considered as a first approximation and used with care. The amount of municipal and assimilated waste collected by the regional agency of waste collection, the amount of waste incinerated and the incineration residues are available for
, 2010). The rest of the solid waste pro2007 (Bruxelles-Proprete duced from a range of activities including industrial, construction and demolition, and others was estimated for the year 2005. The environmental administration of Brussels compiled an overview of these flows (IBGE, 2008). Finally, the atmospheric pollution flows can be described using a number of indicators (in t). These include aggregated indicators such as Greenhouse Gas (GHG) emissions (in CO2-eq.) but also CO2, CO, SOx, NOx and particles. These flows could be further disaggregated into the activity sectors (IBGE, 2014). A summary of all data from the UM-approach is provided in Table 1 for the year 2007. The emissions inventory of Brussels Capital Region is compiled by the environmental administration of Brussels (Bruxelles Environnement, IBGE) using the IPCC methodology as well as a local and national methodology (IBGE, 2012). The emissions are mainly calculated by multiplying the activity data by an emission factor. Typically, emission factors used in the Brussels inventory are from the IPCC methodology and sometimes estimated on the basis of research projects funded by Brussels Environment or other regions (IBGE, 2012). Activity data mainly from the Regional Energy Balance

2009) 2009) 2009) 2009) 2009)

2009) 2009) 2009) 2009) 2009) 2009)

(IBGE, 2009). The different sectors covered in the inventory of emissions Brussels reflect the characteristics of a strict urban environment. Virtually all emissions of this urban environment from energy use of the residential, tertiary and road transport sector. More specifically, the atmospheric emission factors by fuel type are available for the residential (IBGE, 2001b), tertiary (IBGE, 2001c), industry (IBGE, 2001a) and transport sector (IBGE, 2001d). 2.2. Consumption-based approach (using IOA methodology) Consumption-based approach (CBA) comprehensively considers all direct or indirect resource use and pollution emissions flows required to satisfy local consumption regardless if these flows are occurring locally or globally (Minx et al., 2011). In contrast with the territorial-based approach, the consumption-based approach includes all flows that are associated with imports and exports and thus provide and a description of both the direct and indirect metabolic profile of cities (from the consumption perspective). Munksgaard et al. suggest IOA as a comprehensive and consistent assessment technique to measure the consumption-based resource use and pollution emissions of cities (Munksgaard et al., 2005). IOA is an established accounting methodology based on national accounts. It takes on a meso-perspective to analyse the economyenvironment relationship and to analyse value chains or production networks. These tables contain the input structure of economic sectors (aggregated production processes of similar goods or services into sectors) and a description on their output flows (Rose and Miernyk, 1989; Yamano and Ahmad, 2006). Next to the intermediate (flows between sectors) input, the value added that is generated in sectors is included. The intermediate output is separated from deliveries to final demand. So, the core of an IO table is the recording of all monetary flows between economic actors, both producing and consuming (Wixted et al., 2006). Data on, for example, the amount of emissions a sector generates or the number of employees that are engaged in an activity, are provided via environmental and social extension tables. Satellite accounts or extension tables in IO databases provide both sector-specific and country-specific data on emissions, water use, energy use, raw material use, etc. The extension tables are based on national accounts of both production and consumption per activity, for a specific region and usually for the period of one year (Eurostat, 2008). This coherent structure enables the IO tables to be extended with different types of environmental data (Tukker et al., 2006). EE IO analysis enables for a rapid assessment of a wide range

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of activities including upstream (indirect) flows and identification of the sectors responsible for these flows. Multiregional input-output (MRIO) tables group local or national IO-tables into one balanced model often including a model for representing the rest of the world economy (Tukker and Dietzenbacher, 2013). Recent developments in MRIO-databases including environmental extensions, e.g. EXIOBASE (Tukker et al., 2009), WIOD (Dietzenbacher et al., 2013; Timmers, 2012), Eora (Lenzen et al., 2013), GTAP (Narayanan et al., 2012), GRAM (Wiebe et al., 2012), enable the assessment of the complete global production network of goods and services, including all directly and indirectly related flows. MRIOA captures the effects of globally entangled production chains linked to local production and consumption (Inomata and Owen, 2014). Adding countries to MRIO tables, improves the model by adding country-specific characteristics to it (Tukker and Dietzenbacher, 2013). More details about this methodology and the equations behind MRIOA are provided in SI. The assessment of resource use and environmental flows at city scale can be subdivided into direct or local flows and indirect or upstream flows which occur both locally and abroad. Direct environmental flows of a production activity are, for example, emissions emitted by combustion processes on the production site itself; indirect environmental flows of a production activity are, for example, emissions emitted during the production process of combustion fuels which are used as an input on the production site. Both direct and indirect flows are triggered by production and consumption activities. A production activity is carried out under the responsibility, control and management of an institutional unit using inputs of labour, capital and products to produce outputs of goods and services. Final consumption consists of products used by individuals or the community to satisfy their individual or collective needs and wants (Eurostat, 2008). Using resources and products generate environmental effects inside and outside the city territory. In addition to these effects, products carry a rucksack of effects that were generated during the production process. Some of them occur within city boundaries, but as it will be further illustrated, in the globalized economy most of them occur abroad. Some examples of the use of IOA in city level analysis focus for example on: wastewater (Lin, 2009), material flows (Zhang et al., 2014), emissions (Dias et al., 2014; Li et al., 2015), water (Okadera et al., 2006) and energy (Lenzen et al., 2004). As it has been pointed out in a number of studies (Heinonen et al., 2013; Lenzen et al., 2008), local consumption patterns are greatly affected by the heterogeneity of lifestyles. Thus, to accurately capture urban consumption patterns it is necessary to use city scale data (Ala-Mantila et al., 2014; Dias et al., 2014; Heinonen et al., 2013; Lenzen and Cummins, 2011; Minx et al., 2013). Although these studies use IOA as a technique to assess a city's metabolism, especially for capturing the total effects, Zhang (2013) acknowledges that IOA results remain a rough simulation, especially as IOA at a city level often makes use of regional or national data. In addition, as CBA results are obtained through MRIOT that model a quasi-infinite amount of supply-chains that are involved through urban consumption it is almost impossible to validate them. A combination of different techniques is a possibility to overcome this disadvantage of IOA. For example, Chen and Chen (2015) use three accounting approaches, including IOA, to compare on the basis of their different insights into sectoral and total energy consumption at the city level. Their results show the added value of combining different techniques. Sovacool and Brown (2010) compare the carbon footprint of 12 metropolitan areas. One of their conclusions emphasizes that further research and better data would enable more rigorous comparison of metropolitan carbon footprints. Second, their results show large variation in carbon

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footprints between cities determined by the characteristics of a city, like mobility, production activities, agriculture, energy waste systems etc. These results indicate the lack of a commonly accepted and widely adopted methodology to assess the environmental footprint of a city and the need for a methodology coping the potential differences in characteristics between cities. Minx et al. (2013) use a hierarchical hybrid methodology (local, regional and national level data) for estimating the carbon footprints of cities and other human settlements with the focus on linking global value chains to local consumption activities and associated lifestyles. They also acknowledge the major challenge in the availability of comprehensive, consistent and transparently documented data. The need to complement territorial emissions accounting by approaches that include upstream or embodied emissions is highlighted. Their hybrid methodology combines information on global production from a global multi-regional input-output model with local geo-demographic consumer lifestyle information. As inputoutput models comprise macro level data, these authors devise a methodology for estimating final consumption at the local level. Finally, Baynes et al. (2011) compare individual household-based to a regional accounting approach of energy use for Melbourne in order to bring a better understanding to energy use but also to discuss their respective relevance for energy policies. The authors further underline the complementarity of these two approaches and how they provide different perspectives on urban energy use. 2.2.1. Methodology and data used for this case study The city IO tables of Brussels Capital Region (2007 data), compiled by the Belgian Federal Planning Bureau, details 118 sectors and 119 products (Avonds, 2008). The monetary tables contain an inter-industry matrix Z, a final demand matrix F and a value added matrix K. Extensions are not included in the IO-table. Expenditure accounts for Brussels are gathered from the Household Budget Survey (HBS). This dataset (1978; 1999e2010; 2012 data) provides revenues, expenses and assets (in euro) per capita, per household and totals for the Brussels Capital Region. Expenditures are subdivided based on the COICOP-nomenclature (Classification of Individual Consumption According to Purpose). The sample size (n ¼ 657; population size N ¼ 500,249) is considered sufficient to distinguish between the main COICOP-categories (2digit level). These main categories are for example: food and nonalcoholic beverages, clothing and footwear, and health (DGSIE, 2014). The extension data in city IO tables are not always available and if available the level of detail can be insufficient. If coefficients on the city level are lacking, a possible solution is to use national coefficients from (MR)IO tables. The city IO tables of Brussels contain no extensions. We used extension data (converted into coefficients) of Flanders instead. This choice only has implication for the estimation of territorial flows and could partly explain differences between results from IOA and UM. WIOD (world input-output database) (1995e2011 data) is a global EE-MRIO constructed as part of a project of the 7th Framework Programme funded by the European Commission. The database covers 35 sectors across 40 regions/countries and 1 Rest of World region, with approx. 50 items in the extension tables (Dietzenbacher et al., 2013). Belgium is one of the regions in the model and the country extensions are assumed to also represent Brussels Capital Region. The WIOD-extensions contain country and sector specific data on (1) gross energy use (in TJ) subdivided over 27 categories, including for instance diesel, hard coal, gasoline, and natural gas, (2) emissions to air (in tonnes) including 8 emissions to air and aggregates like greenhouse gas emissions, (3) land use (in 1000 ha) for 4 subcategories, (4) both used and unused material use (in tonnes) in 12 categories and aggregates on biomass, fossils and minerals and (5) water use (in 1000 m3) in 3 categories. For this city

Please cite this article in press as: Athanassiadis, A., et al., Comparing a territorial-based and a consumption-based approach to assess the local and global environmental performance of cities, Journal of Cleaner Production (2016), http://dx.doi.org/10.1016/j.jclepro.2016.10.068

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3.1. Territorial-based approach results of Brussels using local data

Fig. 2. The consumption, production and territorial perspective of environmental flows or footprints.

analysis, the following extensions were used: total water use, biomass (animals, feed, food, forestry and other), fossil (coal, gas oil and other), minerals (construction, industrial and metals), total gross and total net energy use and emissions to air (CO2, CH4, N2O, NOX, SOX, CO, NMVOC and NH3). Material use and environmental flow indicators or footprints are calculated from three perspectives: the consumption, the territorial and the production perspective (EEA, 2013). The consumption perspective includes resource use and environmental flows during the use phase (direct or use) and the production phase (indirect and import) of the consumed products. The production phase can be subdivided into a domestic part (indirect) and an abroad part (export). The territorial perspective includes all resource use and environmental flows on the domestic territory. It equals the use phase and the domestic production phase, independent of its destination. Both production for domestic consumption (indirect) and foreign consumption (export) are counted in the territorial perspective. These three perspectives are summarised in Fig. 2.

3. Results The environmental flows crossing the borders of Brussels are estimated in detail by the territorial-based approach using local data (Table 1 and Fig. 3) and more broadly by the territorial-based approach using IOA (TBA-IOA) approach. The effects on the hinterland are only estimated by the consumption-based approach using IOA (CBA-IOA) approach. On the one hand they distinguish imports, direct use, indirect use and exports (Table 2) and on the other hand they show the country or region from where imports originate (Table 3). In addition, an Economy Wide-Material Flow Analysis (EWMFA) of Brussels Capital Region and Belgium in 2007 is constructed using the CBA to underline the differences between the metabolic profile of a nation and a city. Finally, the comparison of both approaches enables a more comprehensive understanding of the footprint of all activities inside Brussels. A clear distinction is made between flows inside the city territory and flows in the rest of the world. By a comparison of the results, the discussion section shows how the results from each method can complement each other for a more comprehensive and complex urban environmental assessment.

Fig. 3. A schematic overview of Brussels' direct urban metabolism in 2007, disaggregated by sectors.

The territorial-based approach (TBA) results of Brussels for 2007 are summarised in Table 1 and Fig. 3. Numbers from Table 1 may not add up to the total as a negligible amount is attributed to other activities such as agriculture. As illustrated, in 2007 Brussels used 81,158 TJ of energy out of which 38% was natural gas, 26% was electricity, 34% was petroleum products (combining light and heavy fuel as well as gasoline) and 2% was from other type of energy sources. It is also possible to subdivide energy use by sector use: residential 40%, tertiary 31%, transport 24%, industry 3%, and 2% for non-energetic use (for instance for the use of lubricants or solvents) which is not represented in Table 1 and Fig. 3. Of all energy use, only 4% is produced locally, mainly by waste incineration, while the rest is imported (IBGE, 2009). In 2007, Brussels used approximately 59,169,000 m3 of water. Similar to energy, the great majority was used by households (67%), followed by tertiary activities (28%), industry (2%) and an insignificant amount (<1%) by the transport sector. Water supply for 2007 was approximately 10 million m3 more than water use (HYDROBRU, 2010), however it was not possible to retrieve information about the sectoral disaggregation of this supply. This difference is due to network losses and the use of water by municipality and firefighting services. Similar to the energy flow, 97% of the water supply is imported from the Walloon Region, while only 3% is locally extracted from Brussels territory. The water flow exiting Brussels is defined here as the waste water treated by the two water treatment plants situated in the territory of Brussels region which accounted for 130,513,000 m3 for 2010 as no data was available for 2007 (SBGE, 2011). These data did not offer a sectoral disaggregation, but the figures of wastewater released by sectors should be very similar to those of water use. The rest of the wastewater released originates mostly from precipitation. Due to the lower quality and accuracy of the data on material flows, these data were not disaggregated (except for the solid waste flow). Imports of materials were estimated at 8459 kt out of which 51% was imported by road, 5% was imported by rail and 43% was imported by water. Similarly, export of materials was estimated at 4833 kt, where 84% was exported by road, 2% was exported by rail and 13% was exported by water (Institut Bruxellois de Statistique et d'Analyse (IBSA), 2014a). These data are insufficiently aggregated to accurately determine the input and output material quantities for different types of goods or sectors. For 2007, the waste flow was subdivided into four main categories, namely: municipal waste (482 kt), industrial waste (500 kt), construction and demolition waste (600 kt) and other types of waste (580 kt). These other types of waste include office waste (100 kt), incineration residues (121 kt), dredging (123 kt), commercial waste (80 kt), transport waste (40 kt), health activities waste (40 kt), restaurant and hotels waste (35 kt), educational activities waste (35 kt), and cleaning wastes (6 kt) (Bruxelles
, 2010; IBGE, 2008). In 2007, around 500 kt of waste was Proprete incinerated (mostly coming from municipal solid waste). To avoid double counting and only account for the waste flow exiting Brussels the following calculation was performed: Total waste flow exiting Brussels (1783 kt) ¼ Total waste generated (2162 kt) e waste incinerated (500 kt) þ waste coming from incineration (121 kt). Finally, atmospheric pollution was reported by sectors and by pollution flows (GHG,2 CO2, CO, SOX, NOX and Particles). GHG

2 GWP is calculated as GHG-emissions including carbon dioxide (impact factor 1), methane (impact factor 21) and nitrous oxide (impact factor 310) Intergovernmental Panel on Climate Change (IPCC), 2007.

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Table 2 Estimations of flows of material use and emissions imported and used/emitted on the territory of Brussels in 2007, resulting from eq. (2) of SI. Indicators

Unit

Total (1) þ (2) þ (3) þ (4)

Import (1)

Direct or use (2)

Indirect (3)

Export (4)

Water

103 m3

2,474,844.6

Biomass

kt

5635.6

Minerals

kt

16,515.3

Metals

kt

2531.9

Fossil energy carriers

kt

6487.9

Gross energy use

TJ

416,359.2

Net energy use

TJ

288,478.1

CO2

kt

15,489.1

NOX

t

40,441.6

SOX

t

30,686.6

CO

t

193,007.8

2,415,412.9 97.6% 5571.5 98.9% 14,422.5 87.3% 2531.9 100.0% 6487.9 100.0% 304,572.5 73.2% 177,814.1 61.6% 9957.7 64.3% 32,651.0 80.7% 27,901.4 90.9% 176,717.8 91.6%

43,983.9 1.8% 0.0 0.0% 0.0 0.0% 0.0 0.0% 0.0 0.0% 54,644.5 13.1% 54,644.5 18.9% 3260.9 21.1% 2424.4 6.0% 1876.7 6.1% 13,348.2 6.9%

5259.1 0.2% 9.7 0.2% 530.6 3.2% 0.0 0.0% 0.0 0.0% 16,578.8 4.0% 16,172.3 5.6% 691.7 4.5% 1720.2 4.3% 224.4 0.7% 709.0 0.4%

10,188.7 0.4% 54.4 1.0% 1562.2 9.5% 0.0 0.0% 0.0 0.0% 40,563.4 9.7% 39,847.2 13.8% 1578.9 10.2% 3646.0 9.0% 684.1 2.2% 2232.8 1.2%

Values in italics represent the share of imports, direct use, indirect use and exports compared to the total value. Table 3 Origin of a selection of imported flows. EU-countries (excl. Belgium) and Turkey are aggregated to improve readability, resulting from Eq. (2). of SI. Origin

Gross energy use

Net energy use

Water use

Biomass

Minerals

Metals

Fossil energy carriers

CO2 emissions

Unit

TJ

TJ

103 m3

kt

kt

kt

kt

kt

Rest of Belgium

29,020 9.53% 130,652 42.90% 936 0.31% 2567 0.84% 3929 1.29% 24,169 7.94% 5707 1.87% 1298 0.43% 4756 1.56% 3368 1.11% 728 0.24% 18,027 5.92% 2114 0.69% 12,757 4.19% 64,546 21.19% 304,573

20,932 11.77% 75,091 42.23% 715 0.40% 1718 0.97% 3115 1.75% 16,627 9.35% 3865 2.17% 831 0.47% 2793 1.57% 1677 0.94% 463 0.26% 11,963 6.73% 1284 0.72% 7147 4.02% 29,594 16.64% 177,814

179,056 7.41% 446,807 18.50% 7009 0.29% 197,619 8.18% 78,441 3.25% 198,362 8.21% 116,454 4.82% 54,694 2.26% 3499 0.14% 114 0% 4781 0.20% 41,765 1.73% 3106 0.13% 84,203 3.49% 998,475 41.34% 2,415,413

1455 26.12% 124 2.23% 26 0.47% 598 10.73% 63 1.13% 263 4.72% 138 2.48% 53 0.95% 2 0.04% 2 0.04% 8 0.14% 20 0.36% 0 0% 110 1.97% 1595 28.63% 5571

2751 19.08% 4371 30.31% 60 0.42% 139 0.96% 194 1.35% 2642 18.32% 477 3.31% 57 0.40% 110 0.76% 77 0.53% 48 0.33% 670 4.65% 36 0.25% 436 3.02% 2355 16.33% 14,422

0 0% 167 6.60% 278 10.98% 152 6.00% 64 2.53% 251 9.91% 80 3.16% 122 4.82% 0 0% 0 0.00% 17 0.67% 208 8.21% 0 0% 42 1.66% 1151 45.46% 2532

0 0% 2057 31.70% 192 2.96% 36 0.55% 165 2.54% 629 9.69% 168 2.59% 79 1.22% 1 0.02% 1 0.02% 27 0.42% 1189 18.33% 0 0% 162 2.50% 1781 27.45% 6488

1364 13.70% 3659 36.74% 47 0.47% 54 0.54% 126 1.27% 1243 12.48% 278 2.79% 55 0.55% 149 1.50% 99 0.99% 27 0.27% 640 6.43% 87 0.87% 397 3.99% 1733 17.40% 9958

EU-26 þ Turkey Australia Brazil Canada China India Indonesia Japan Korea Mexico Russia Taiwan United States Rest of World Total

includes emissions from CO2, CH4, N2O and F gases and for 2007, Brussels emitted 3937 kt of CO2 which originated from the residential sector (42%), the tertiary sector (19%), the industrial sector (2%) and the transport sector (23%). 3.2. Consumption-based and territorial-based approach results of Brussels using input-output analysis This section presents the results obtained using the IOA

methodology. The IOA methodology demonstrates the large differences between the city and country level in terms of material demand, availability and export. These pieces of information are expressed in per capita EW-MFA indicators for Brussels and Belgium (Fig. 4). For instance, Fig. 4 shows that both for Brussels and Belgium, the domestic extraction is smaller than the amount of imports and there is considerable more imports compared to the export. Meaning both Brussels and Belgium are net-material importers. In addition, it can be seen that the ratio of imports to

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Fig. 4. Economy Wide-Material Flow Analysis of Belgium (top) and Brussels Capital Region (bottom) in 2007, in tonnes per capita, resulting from Eqs. (3) and (4) of SI. DE ¼ Domestic extraction; IM¼Imports; IM_RME ¼ Imports in Raw Material Equivalents; EX ¼ Exports; EX_RME ¼ Exports in Raw Material Equivalents; DMC ¼ domestic material consumption; RMC ¼ raw material consumption.

imports expressed in their raw material equivalents differs between Brussels and Belgium. This difference emphasizes that Belgium imports a higher fraction (51%) of products in an early production stage (raw materials) and a lower fraction (23%) of products in a late production stage (finished products) compared to Brussels (importing fractions of 15% and 65%, respectively). Also, the amount of traded materials per capita is smaller for Brussels compared to Belgium. These findings are linked to the discrepancy between the EW-MFA of Brussels and Belgium reiterating how cities are often centres of consumption with little productive capacities, highly depending on their hinterland to satisfy their needs. Finally, it can be pointed out that while the raw material consumption (RMC; Eq. (4) of SI) for Brussels and Belgium are comparable and vary around 25e28 ton/cap, the domestic material consumption (DMC; Eq. (3) of SI) differs at 10 and 22 ton/cap, respectively. With comparable RMC and lower DMC, the impact on the hinterland is much larger comparing the city of Brussels with the nation Belgium. The results from the IOA are synthesized in Table 2 (point estimates, no data on uncertainty is available). This table shows a number of indicators from which both the production, territorial and consumption perspectives can be constructed (Fig. 2). Imported flows are linked to domestic consumption and exclude imported flows linked to exports. Exports only include the domestic production linked to foreign consumption. A striking finding here is that for the majority of flows, imports represent the highest share of total use/emissions ranging from 61.6% for the net energy use to 100% for the fossil energy use carriers and metals. The flow with the highest contribution of direct use is CO2 emissions followed by energy use (approximately 20%). This is logical as both flows are closely related and directly caused by heating and transportation. Most of the other flows have a share less than 10% and some are inexistent (biomass, minerals, metals and fossil energy carriers). For the indirect use, all of the flows have a share lower than 5% except for net energy use (5.6%). Finally, exports also represent a small share of the total amount of flows exiting Brussels. The flows with the highest share are net energy use (13.8%) and CO2 emissions (10.2%). While Table 2 stresses the dependence of Brussels on the imports from its hinterland, Table 3 further details the origin of these (virtually) imported flows. This supplementary information

enables a better understanding of the distance that separates the origin of some flows and its recipient. The figures of imported flows presented in Table 3 are expressed across the 40 countries and the 1 Rest of World region available from the WIOD database. Brussels and the Rest of Belgium are expressed as two different regions. In addition, the 26 other European member states and Turkey are aggregated to synthesize results. The analysis highlights that the countries/regions from which Brussels imports the most are EU26 þ Turkey, the Rest of the World and rest of Belgium with exceptions (>10%) for biomass (Brazil), metals (Australia), minerals (China), fossil energy carriers (Russia) and CO2-emissions (China). This shows that for most of the flows presented in Table 3, the environmental flows and material use triggered by Brussels consumption is linked to a large variety and fragmented set of countries across the world. The fragmentation is different per indicator, which makes its precise tracing and (environmental) regulation much more difficult. For example, Brussels imports insignificant amounts from Australia for most of the examined flows, but Australia is the second largest provider of metals for Brussels consumption needs. To better grasp the full complexity of Brussels' hinterland the results are spatially represented in SI (Fig. 2 of SI) for the case of embodied metal use in Brussels’ final demand. This shows that it is necessary to provide different analytical and representation tools to comprehend all the different perspectives that IOA results can offer. To conclude this section, it is worth mentioning that results from the CBA-IOA offer valuable information about the interrelationships between an urban system and its hinterland as well as its spatial context. 3.3. Comparing results from an territorial-based approach using local data and consumption-based and territorial-based approach results of Brussels using input-output analysis In summary let us remind that TBA results using local data are more accurate data, generally more frequently published and enabling a more detailed temporal evolution. In addition, due to its flexible methodology it is most appropriate at the urban scale, can be easily used by local administrations and has a large pool of existing case studies. Finally, spatializing TBA using local data can help to identify local drivers of resource use and pollution flows.

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However, the TBA fails to take into account the embodied resource consumption and pollution flows taking place outside the city boundaries associated with trade. On the other hand, the CBA and TBA using Input-Output Analysis methodology is based on local, national IO and MRIO tables as well as their environmental extensions which have limited availability and need experts to use them. However, the IOA methodology uses a robust and systemically complete methodology which can measure production-, territorial- and consumption-perspective indicators on resource use and pollution flows. While this approach is still relatively new at the urban scale (Baynes et al., 2011; Baynes and Wiedmann, 2012; Chen et al., 2016; Chen et al.; Wiedmann et al., 2016) and suffers from limitations due to the uncertainties associated with IO data and estimates, it can provide valuable additions to the more accurate aspect of the metabolism balance. The advantages of the CBAIOA expansion includes spatializing the environmental hinterland of urban systems and providing a better understanding of the macro-scale drivers leading to resource use and pollution flows. Table 4 presents a direct comparison of the TBA using local data and TBA-IOA and CBA-IOA results. In other words, IOA methodology results illustrate both the consumption-based approach (CBA-IOA) and the territorial-based approach (TBA-IOA). The CBA-IOA/TBA ratios illustrate how usual TBA underestimates the environmental pressures it generates through the resource use and pollution flows that are embodied in trade to satisfy Brussels’ final demand. A TBAIOA/TBA ratio closer to 1 provides a stronger validation of the IOA results (TBA-IOA) compared with the TBA results using local data. The results for the CBA-IOA/TBA ratio show that Brussels is using approximately 3 times more final energy, 42 times more water, 3 times more materials (the TBA value considered for this ratio is the one of imports) and emits 4 times more GHG-emissions, 23 times more CO-emissions and 31 times more SOX-emissions than the values measured by the TBA using local data. These high ratios offer compelling evidence for the need to implement more comprehensive environmental policies. The ratio indicates the significance of the global hinterland in regard to the resource needs and emissions of Brussels. It also highlights a different and more complete, compared to TBA, environmental profile of Brussels that takes into account its global environmental pressure and responsibility. On a separate note, the TBA-IOA/TBA ratios from Table 4 show

9

some encouraging findings as the difference between TBA and TBAIOA results is not very high for some flows and the highest difference between TBA and TBA-IOA results is a factor of 2.8. In the case of gross energy and water use the TBA-IOA/TBA ratio is very close to 1 meaning that TBA and TBA-IOA results portray comparable direct environmental profiles of Brussels. In addition to the consumption and production perspective (Table 4), a detailed, disaggregated sectoral perspective is given in Table 5. The disaggregation details the comparison between TBA using local data and the TBA-IOA results on a sector level. The focus is on territorial flows, but only for two indicators: energy use and water use. The comparison in Table 5 reveals differences in the sectoral contribution to water use and energy use, expressed by the TBAIOA/TBA ratio. The sequence and order of magnitude of sectors is the same using the TBA using local data and TBA-IOA approaches. From Table 4, the results show the small overall difference for energy use and water use of 1.37 and 1.06, respectively. At the more disaggregated sector level, a number of over- and underestimations appear. In conclusion, it is important to point out that the residential sector that represent the highest contribute has a relatively low ratio which implies that a large share of territorial based consumption is well represented by the IOA methodology.

4. Conclusion and discussion The main objective of this paper was to compare the territorialbased and consumption-based approaches on their capabilities and relevance to assess the local and global resource use and pollution emission flows. In other words, we compare and understand the differences between an accurate overview of the direct metabolism balance of a city (TBA) and the comprehensive model results describing both the direct and indirect environmental effects due to urban consumption needs (CBA). To do this we used Brussels as a case study for the year 2007. The comparison of the two approaches as well of their results provides new findings that contribute to the scientific communities of both approaches and provide a more comprehensive framework to the environmental assessment of urban areas. Firstly, the CBA results demonstrate how much Brussels relies on

Table 4 Comparing territorial-based approach using local data and consumption-based and territorial-based approach results of Brussels using Input-Output Analysis to assess the direct and indirect resource use and pollution emissions of Brussels Capital Region in 2007. Flow

Energy

Water Materials

Air pollution

Final energy use per source Electricity Natural gas Petroleum products Others Gross energy use Total water use Imports Local consumption Exports Solid waste GHG (CO2, CH4, N20 þ F gases) CO2 CO SOx NOx

Unit

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

TBA

Import IOA

Direct IOA

Indirect IOA

Export IOA

CBA-IOA (2 þ 3þ4)

TBA-IOA (3 þ 4þ5)

CBA-IOA/TBA (6)/(1)

TBA-IOA/TBA (7)/(1)

TJ

81,158

177,814

54,644

16,192

39,953

248,651

110,790

3.06

1.37

TJ TJ TJ TJ TJ 103 m3 kt kt kt kt kt-CO2eq

20,754 31,068 28,044 583 118,612 59,169 8459 e 4833 2160 3937

21,127 41,423 42,138 73,125 304,573 2,415,413 29,014 e e e 13,282

6651 14,175 32,381 1438 54,644 44,810 e 0 e e 3293

6301 6235 3617 40 16,599 5651 e 540 e e 738

15,079 14,979 9825 71 40,670 12,267 e e 1617 e 1656

34,079 61,833 78,136 74,603 375,816 2,465,874

28,030 35,389 45,822 1548 111,913 62,728

1.35 1.14 1.63 2.66 0.94 1.06

27,937

540

17,313

e 5687

1.64 1.99 2.79 127.96 3.17 41.68 e 3.43 e e 4.40

kt t t t

3652 8424 980 5850

9958 176,718 27,901 32,651

3261 13,348 1877 2424

692 709 224 1722

1582 2234 685 3657

13,911 190,775 30,003 36,798

5535 16,292 2786 7804

3.81 22.65 30.61 6.29

1.52 1.93 2.84 1.33

1.44

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Table 5 Sector-level comparison of territorial-based approach results using local data (TBA) and using the input-output analysis methodology (TBA-IOA) to assess energy use and water use of Brussels Capital Region in 2007. Sector contribution Energy (TJ)

Water (103 m3)

Industry Tertiary (excl. transportation) Transportation Residential Industry Tertiary (excl. transportation) Transportation Residential

its global hinterland. Indeed, the results of this study not only show a more complete environmental footprint of Brussels compared to a traditional TBA study, but also allow the origin and destination of input and output flows as well as the spatial representation of Brussels hinterland to be traced. The CBA-IOA/ TBA ratio in Table 4 underlines that current urban environmental policies of Brussels only target a small percentage of its actual total environmental footprint. These findings should in fact change the focus of current policies from energy and water savings strategies towards circular and sharing economy strategies. In fact, while in direct metabolic (or TBA) terms consumer products are often only accounted as materials flows, in indirect metabolic terms (or CBA) the same products are also accounted for all the energy, water, pollution emissions and other flows that were necessary along their entire supply chains. The CBA-IOA/ TBA ratio as well as the results from Table 4 also gives a better understanding of the environmental responsibility of Brussels. For instance, while in the TBA results, Brussels receives all of its water use (mostly drinkable water) from a relatively small radius (within Belgium), in CBA results (Table 3) it is possible to see that Brussels only receives 7.5% of its water needs from Belgium. Nevertheless, the results from Table 4 also showed that for most of the considered flows, TBA and TBA-IOA results are, in the case of Brussels, roughly similar. This implies that IOA methodology could also be used as a first approximation of a TBA when some local data are missing (provided that local IO tables and expenditure data are available). In addition, the latter finding is essential for the IOA methodology as it enables to provide a rough validation to IOA-based figures that are usually criticized to have important uncertainties. However, there is still a lot of work needed to understand how the results from these two approaches are linked and why there are discrepancies between the two results. One factor that could explain this discrepancy is the fact that for this paper we used another's Belgian region extension database (Flanders region). While at first hand we considered that the economic activities in both Belgian regions had the same environmental effects, this could in fact not be the case. Table 5 provides a first way to address the discrepancies identified in Table 4. By further disaggregating the results of Table 4 by sectoral or economic activities it becomes possible to isolate which part are not accurately modelled by the IOA methodology and try to understand why is that. Furthermore, another way to better understand how the TBA results using local data and the IOA methodology are linked would be to focus on the downstream flows (such as waste). Therefore, at this stage it is perhaps safer to use TBA-IOA results as general overview more than results that could be used for environmental policy-making. Finally, to ensure the validity of IOA-based results found in this study it would interesting to examine the consistency of the TBA-IOA/TBA and CBA-IOA/TBA ratios for other years, for other cities as well as for other MRIO databases (Moran and Wood, 2014). In fact, it is

TBA

TBA-IOA

TBA-IOA/TBA

2484 25,628 19,584 32,825 1507 16,767 546 39,548

4715 40,690 10,575 54,644 1440 13,682 311 44,810

1.90 1.59 0.54 1.66 0.96 0.82 0.57 1.13

important to reiterate that the results from this study are specific to a city with little or no productive activities. If this exercise was carried out for an urban area with extractive and productive activities (Baynes et al., 2011) results could be polar opposite (CBAIOA/TBA equal or even lower than 1) and the associated environmental policies would also be very different. This study therefore points out that IOA could be a starting point for a first estimation of environmental footprints at the city level. The results could help TBA research using local data to refine the search for data and narrow the focus of a more in-depth analysis. As a top-down approach, IOA provides a complete estimation of indicators, which in turn can be structurally refined with bottom-up TBA data. The analysis carried out for Brussels enables adding a more global perspective to traditional TBA studies by tracing the origin of direct and indirect environmental flows. In addition, this analysis enables to validate IO results at a city-scale which might foster the use of IO-results to suggest urban environmental policies that cover the entire hinterland of urban areas. To conclude, the comparison of TBA and CBA results opens a new path for research in terms of urban environmental assessment by underlining the need for a hybrid methodology combining accuracy and comprehensiveness. This methodology, should produce results for different flows (and their sub-categories) but also for their respective sectoral use. As such, it would be possible to trace how local economic sectors influence the global network of production/consumption and which economic policies affect most local and global environmental pressures. Future research could also investigate the similarities and differences between TBA and IOA-TBA drivers to produce more coherent and holistic environmental policies that take into account the local and global parameters that influence resource use and pollution emissions. These policies should not only focus on the use of resources locally but also globally for the local needs of cities. Finally, this study underlines the need for a methodological framework linking the TBA using local data and the IOA methodology to connect local socioeconomic and territorial challenges with their associated global environmental consequences. In fact, in a context of hyperconnected and globalized urban economies, this methodology could become an essential tool for cities enabling them reduce their local environmental pressure and addressing their local challenges on the one hand, while making sure that they simultaneously do not burden other parts of the world from a social, economic or environmental perspective, on the other. Acknowledgements Aristide Athanassiadis was funded through a research fellowship (aspirant FNRS) from the Belgian Fund for Scientific Research F.R.S.-FNRS, a WBI World excellency scholarship and a BRIC scholarship. In addition, parts of this research were also conducted in the framework of an IBGE-BIM project on the quantification of Brussels'

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urban metabolism. Maarten Christis is granted by a research project of the Flemish Policy Research Centre of Sustainable Materials Management (steunpunt SuMMa). We would also like to thanks all the reviewers for their valuable comments that enables to enhance the quality of this paper. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.jclepro.2016.10.068. References Ala-Mantila, S., Heinonen, J., Junnila, S., 2014. Relationship between urbanization, direct and indirect greenhouse gas emissions, and expenditures: a multivariate analysis. Ecol. Econ. 104, 129e139. Athanassiadis, A., Bouillard, P., 2013. Contextualizing the urban metabolism of Brussels: correlation of resource use with local factors. In: Proceedings of CISBAT 2013, International Conference, Cleantech for Smart Cities & Building from Nano to Urban Scale. EPFL-Lausanne, Lausanne. Athanassiadis, A., Bouillard, P., Crawford, R.H., Khan, A.Z., 2016. Towards a dynamic approach to urban metabolism: tracing the temporal evolution of Brussels' urban metabolism from 1970 to 2010. J. Ind. Ecol. http://dx.doi.org/10.1111/ jiec.12451. € Avonds, L., 2008. Raming Van Een Regionaal Input-output Systeem Voor Belgie Working Paper 18-08. Federaal Planbureau, Brussel. Bai, X., 2007. Industrial ecology and the global impacts of cities. J. Ind. Ecol. 11, 1e6. Barles, S., 2007. Feeding the city: food consumption and flow of nitrogen, Paris, 1801e1914. Sci. Total Environ. 375, 48e58. Barles, S., 2009. Urban metabolism of Paris and its region. J. Ind. Ecol. 13, 898e913. Baynes, T.M., Wiedmann, T., 2012. General approaches for assessing urban environmental sustainability. Curr. Opin. Environ. Sustain. 4, 458e464. Baynes, T., Lenzen, M., Steinberger, J.K., Bai, X., 2011. Comparison of household consumption and regional production approaches to assess urban energy use and implications for policy. Energy Policy 39, 7298e7309.
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Please cite this article in press as: Athanassiadis, A., et al., Comparing a territorial-based and a consumption-based approach to assess the local and global environmental performance of cities, Journal of Cleaner Production (2016), http://dx.doi.org/10.1016/j.jclepro.2016.10.068