Regional Material Flow Accounting and Environmental Pressures: The

Jan 16, 2015 - This paper explores potential contributions of regional material flow accounting to the characterization of environmental pressures. Wi...
0 downloads 0 Views 2MB Size
Article pubs.acs.org/est

Regional Material Flow Accounting and Environmental Pressures: The Spanish Case Sergio Sastre,*,† Ó scar Carpintero,§ and Pedro L. Lomas‡ †

Institute of Marine Sciences, ICM-CSIC, Passeig Marítim de la Barceloneta, 37-49, E08003, Barcelona, Spain Department of Applied Economics, University of Valladolid, Avda. Valle Esgueva, 6, 47011 Valladolid, Spain ‡ Institut de Ciència i Tecnologia Ambientals (ICTA), Universitat Autònoma de Barcelona (UAB), E08003, Bellatera, Spain §

S Supporting Information *

ABSTRACT: This paper explores potential contributions of regional material flow accounting to the characterization of environmental pressures. With this aim, patterns of material extraction, trade, consumption, and productivity for the Spanish regions were studied within the 1996−2010 period. The main methodological variation as compared to whole-country based approaches is the inclusion of interregional trade, which can be separately assessed from the international exchanges. Each region was additionally profiled regarding its commercial exchanges with the rest of the regions and the rest of the world and the related environmental pressures. Given its magnitude, interregional trade is a significant source of environmental pressure. Most of the exchanges occur across regions and different extractive and trading patterns also arise at this scale. These differences are particularly great for construction minerals, which in Spain represent the largest share of extracted and consumed materials but do not cover long distances, so their impact is visible mainly at the regional level. During the housing bubble, economic growth did not improve material productivity.



territories. Hence zooming in on the material flows at the regional scale is crucial in order to identify current and future environmental pressures and provide decision-makers with more precise information. The number of studies on Regional Material Flow Analysis (RMFA) has grown steadily during the last 20 years and comprehensive reviews of studies in this field have already been made.15−17 However, the lack of harmonized statistical data at the regional level has led to methodological heterogeneity and, to date, there are no data series on RMFA and very few case studies. In early attempts to carry out RMFA, Frias and Naredo18 reported the monetary, material, energy, water, and waste flows for the region of Madrid. As in the other publications in the field prior to the publication of the first standardized MFA guidelines,19−21 these early attempts followed nonharmonized methodological procedures. In 2001, the first standardized methodological framework was published,2 but the regional application of such guidelines is still subject to difficulties.16,22,23 Kovanda and colleagues,24 dealing with the RMFA of the Czech Republic, and Li and Zhang,25 dealing with the Chinese regional economy, are the most complete published references in the field to date. The present contribution goes one step further: it presents the results of the RMFA of Spain covering the period 1996−

INTRODUCTION Consumption of materials and energy exerts a general environmental pressure. Materials are extracted to produce goods and services throughout the socioeconomic system (conceived as an open subsystem of the biosphere). Some of them are recycled and others are finally released back into the environment in the form of waste. Economy-wide material flow analysis (EW-MFA) has been acknowledged as a key assessment tool for examining the material exchanges between human activity and the environment through a set of consistent and comparable indicators. Some of the current environmental challenges related to resource depletion or sinks exhaustion can be framed, quantified, and analyzed from an EW-MFA perspective, complementing the understanding of the environmental dimension associated with economic development.1 The importance of this type of analysis for environmental policy is already fairly visible through the international initiatives entailing resource use efficiency strategies, in turn supported by EW-MFA indicators.2−7 EW-MFA has been widely applied to entire countries,8−11 global regions,12−14 and cities.15 However, most case studies have been carried out at the national scale, for which the first standardized methodological guidelines were originally devised and for which data are often readily available. The application of EW-MFA at the regional level involves several methodological drawbacks, of which lack of data is the most important.16 Additionally, environmental pressures tend to be related to enterprises and households located in specific urban and rural environments, which are not regularly distributed across © 2015 American Chemical Society

Received: Revised: Accepted: Published: 2262

September 10, 2014 January 3, 2015 January 16, 2015 January 16, 2015 DOI: 10.1021/es504438p Environ. Sci. Technol. 2015, 49, 2262−2269

Article

Environmental Science & Technology

The two main features of the period were the strong influence of the construction sector and the coexistence of different extractive profiles. The construction sector influenced DE in two manners. First, it drove DE to a maximum in absolute and per capita terms in almost all regions around 2007. This point coincides with the onset of the global financial crisis, the end of the housing bubble and the beginning of the recession on the national and regional level. Second, the share of renewable materials extraction (i.e., biomass) in all the regions until 2007 decreased independently of the starting values. This decrease was particularly sharp (over 20%) in the case of Cantabria, Galicia, Castilla-Leon, and Extremadura, typically agricultural regions in gross value added terms. Construction minerals drove the changes in the structure and level of extraction during the period (Figure 1). The dominance

2010 for the whole of its regions at the NUTS2 scale (for the explanation of this term, see notes). The main aim of this article is to explore potential contributions of RMFA to the characterization of environmental pressures. To this end, the Spanish case was examined with the specific aim of shedding light on (1) the similarity of the structure of domestic material extraction and consumption across regions within the same country; (2) the role and structure of interregional and international trade in domestic material consumption; and (3) regional performance in terms of resource use efficiency (and associated environmental pressures) during the last period of economic growth in Spain.



METHODS General issues of compiling an EW-MFA database at the regional scale have been addressed elsewhere.16,26 A regional database covering the main material flows was compiled26 following standardized guidelines.27 On the basis of this framework, a set of standard EW-MFA indicators can be calculated, namely domestic extraction (DE), physical trade balance (PTB), and domestic material consumption (DMC). Extraction comprises biomass, fossil fuels, metals, industrial minerals, and construction minerals. Trade is split into interregional (IrT) and international (InT) exchanges. The focus of this work is on direct flows. The importance of the upstream requirements of imports and the share of nonused DE has been stressed elsewhere28 but this information is not included herein. Nevertheless, the main structural features and trends can be still analyzed and the data set may serve for future calculation of the material footprint of consumption.29 Detailed information on methods, data sources, specific coefficients and estimations are provided in the online Supporting Information (SI) files (Tables S1 and S2). System boundaries were set by balancing both statistical availability and analytical relevance. NUTS2 regions accomplished both because statistics are reported directly at this scale (except in the case of trade by pipeline, which was modeled), and these boundaries coincide with the main Spanish regional administrative borders: autonomous communities (ACs). IrT was addressed separately from InT in order to broaden the analytical depth. To the authors’ knowledge, this is the first work including such data for a whole country. Splitting trade into these two categories offers a gain in resolution and a better understanding of the allocation of environmental loads through commercial exchanges.14,30

Figure 1. Level and composition of regional domestic extraction per capita. Note: The first bar represents values for 1996, the middle bar represents the year with maximum values (see Table S6), and the third bar represents values for 2010. Region codes: AN, Andalusia; AR, Aragon; AS, Asturias; BI, Balearic Islands; CI, Canary Islands; CN, Cantabria; CL, Castilla-Leon; CM, Castilla-La Mancha; CT, Catalonia; VL, Valencia; EX, Extremadura; GL, Galicia; MD, Madrid; MR, Murcia; NV, Navarre; BC, Basque Community; and RJ, La Rioja. Source: compiled by the authors from sources shown in SI Table S1.

of construction minerals in DE per capita (DEpc) is a common feature in the physical structure within developing and industrialized countries, particularly in the European Union (EU).33 However, the values obtained in some ACs exceeded the maximum values found until now in the EU (17.8 t/cap in the case of Finland in 2000) or China, where DEpc was below 10 t/cap. Castilla-La Mancha extracted a maximum of 28.2 t/ cap of construction mineral, and six other regions (Aragon, Cantabria, Murcia, Navarre and La Rioja) reached values over 20 t/cap. A second significant feature is the coexistence of different extractive profiles between regions of Spain with high and low population densities. Madrid, a small and densely populated region in which the capital city is located, has the lowest share of renewable materials (3.9%−7.3%) whereas other regions with lower population densities have shares of biomass extraction close to preindustrial metabolic regimes.34 This is the case of Castilla-Leon with almost 45% and Extremadura with 70% (2010 figures). DEpc reached its maximum value at some point near 2007, followed by a sharp descent, which in 2010 led to lower values than those registered in 1996 in nine regions. Madrid and the Canary Islands showed the lowest values (2.4−6.4 and 2.3−5.8 t/cap, respectively), 60% lower than the average for Spain. The figures for Madrid match particularly well with the general



RESULTS AND DISCUSSION Information on the administrative borders of the Spanish regions is provided in SI Figure S1. SI Tables S4 and S5 include intensive and extensive socioeconomic indicators for every autonomous community. In order to contextualize the economic performance of Spain between 1996 and 2010, it should be borne in mind that it was affected by both the onset of the global financial crisis in 2008 and the bursting of the “housing bubble” in 2007.31,32 Domestic Extraction (Used): Common Trends for Differing Metabolic Profiles. The magnitude of DE in Spain rose from 446.4 Mt in 1996 (equivalent to 11.3 tons per capita [t/cap], 882 t/km2) to 482.5 Mt in 2010 (10.3 t/cap and 954 t/km2), peaking at 770.5 Mt in 2007 (17 t/cap and 1,523 t/km2)(SI Table S6). 2263

DOI: 10.1021/es504438p Environ. Sci. Technol. 2015, 49, 2262−2269

Article

Environmental Science & Technology

Physical Trade Balances: The Role of International and Interregional Trade in Regional Metabolism. The largest share of physical commercial trade of the Spanish regions was in interregional exchanges (70% of total exports, 60% of total imports). The most prominent importers at the regional level (SI Table S7) were Madrid, Valencia, Catalonia, Castilla-Leon, and Castilla-La Mancha, which together accounted for 54% of regional imports. Madrid’s imports were ten times those of the islands and La Rioja, and more than doubled the average. Catalonia, the main interregional exporter, and Castilla-La Mancha, Valencia, Andalusia, and Madrid together accounted for 52% of regional exports. Catalonia’s exports were one hundred times those of the Balearic Islands, ten times those of the Canary Islands and Extremadura, and double the average. The main importers of international products, Catalonia, Andalusia, and the Basque Community, accounted for 49% of international imports. Catalonia imported three times the average value. International exports were concentrated in Catalonia, Andalusia and Valencia, which together accounted for 52% of international exports, and their individual exports were one hundred times greater than those of La Rioja and the Balearic Islands. Catalonia and Andalusia both tripled the average value and Valencia more than doubled it. A variety of profiles can be observed. Some regions traded mainly with other Spanish regions. Castilla-La Mancha and La Rioja were the most extreme cases, with over 90% of their trade made at the regional level. Castilla-Leon, Aragon, Extremadura, Cantabria, Navarre, La Rioja, Cantabria, and Madrid showed a diversity of trading structures (Figure 2). Castilla-La Mancha was a net regional exporter of raw and semimanufactured products, particularly biomass and nonmetallic minerals, as was Castilla-Leon, which included a larger share of biomass among

profile of global industrialized metropolitan areas such as Paris35 and Prague,24 where per capita domestic extraction is significantly lower than in other regions. A different pattern seems to appear in the islands, although there is as yet little literature for comparisons on the metabolism and particularities of the islands.36 Regions with a low population density, such as Castilla LaMancha, Castilla-Leon, and Aragon, where agriculture has traditionally played a more important role in terms of gross value added and employment, showed the highest values. Castilla-Leon (34.2−51.4 t/cap) had double the average values for Spain and five and almost ten times the values for Madrid and the Canary Islands, respectively. These regions have particularly high per capita values of biomass extraction due to livestock feeding products. Over 10 t of biomass per capita are produced in Extremadura, Castilla-Leon, and Castilla-La Mancha. In Extremadura, approximately 70% of the biomass extraction was devoted to livestock feeding. By the end of the period the differences in DEpc among regions rose from a factor of 8 to a factor of 10. In terms of environmental pressure Madrid led with 1903 to 4530 t/km2, followed by Murcia, the Basque Community and Cantabria. In contrast, the larger regions with low population density, namely Extremadura, Aragon, Castilla-La Mancha, and Castilla-Leon, showed the lowest values. However, it multiplied by a factor of 4.8 in Castilla-Leon and 3.4 in Murcia when the maximum was reached in 2007, whereas the average value for Spain had barely doubled. Madrid showed a DE of 43 000 t/ km2 of construction materials in 2003, a very high value in comparison with those of other European urban regions such as Prague24 Paris35 and Manchester,37 none of which exceeded 3000 t/km2, the maximum value across the EU countries, and in comparison with Asia and the Pacific countries, where only Singapore showed higher values according to the CSIRO database. Investigating further into structural features, almost 70% of biomass extraction was concentrated in five regions representing 65% of the Spanish territory: Castilla-Leon, Andalusia, Castilla-La Mancha, Extremadura, and Galicia. Andalusia, Castilla-Leon, and Extremadura extracted half of the total agricultural biomass and Galicia more than 40% of the forest and fishing products. With regard to fossil fuels, Spain has low fossil fuel reserves in comparison with its apparent consumption. The extraction of fossil fuels, mostly coal, fell from 28 Mt in 1996 to 5 Mt in 2010. The main coal reserves were located in Galicia, CastillaLeon, Asturias, Aragon, and Castilla-La Mancha. Galicia led extraction of coal (lignite) until 2008, when it completely stopped due to reserve depletion and Kyoto Protocol−related legislation on sulfured coals. The remaining regions extracted other types of coal and anthracite. Extraction of crude oil and gas on the coasts of Catalonia and the Basque Community is insignificant. Metal ores are found in Andalusia (sulfur complexes, copper, zinc, lead, and gold), Extremadura (nickel, zinc), Cantabria (gold) and Asturias (gold, copper). However, only Andalusia extracted significant quantities. Metal ore extraction in Spain collapsed by 2004, although the current price rise has recently led to the reopening of the most profitable mines in Andalusia. Catalonia led industrial mineral extraction for the fertilizer industry, followed by Cantabria and Valencia, which also extracted salt.

Figure 2. Level and composition of the accumulated interregional physical trade balances. Note: The left bar for every region represents IrPTB accumulated values (1996−2010) of raw materials, the central bar represents IrPTB accumulated values (1996−2010) of semimanufactured products and the right bar represents IrPTB accumulated values (1996−2010) of manufactured products. Region codes: AN, Andalusia; AR, Aragon; AS, Asturias; BI, Balearic Islands; CI, Canary Islands; CN, Cantabria; CL, Castilla-Leon; CM, Castilla-La Mancha; CT, Catalonia; VL, Valencia; EX, Extremadura; GL, Galicia; MD, Madrid; MR; Murcia; NV, Navarre; BC, Basque Community; and RJ; La Rioja. Source: compiled by the authors from sources shown in SI Table S1. 2264

DOI: 10.1021/es504438p Environ. Sci. Technol. 2015, 49, 2262−2269

Article

Environmental Science & Technology

both the international and interregional context were largely composed of manufactured goods and semimanufactured forms of energy carriers. In turn, Murcia was a net interregional exporter of raw and semimanufactured products and a net importer of manufactured products from the rest of Spain. International and interregional trade are highly influenced by fossil fuels. Hence, regions where refineries are located have overall negative values for the IrPTB (i.e., they are net exporters). The remaining regions are net importers. However, as we look more closely at their structural features, the picture becomes more diverse. Castilla-Leon, Castilla-La Mancha, Galicia, Murcia, and Andalusia are net interregional providers of biomass. Moreover, Andalusia and Castilla-Leon are the main interregional suppliers of metals. Figure 4 shows net cross-regional flows of nonmetallic minerals (indicating environmental load displacement related

its exports. Madrid played precisely the opposite role as a net importer of nonmetallic minerals and energy carriers. The Canary Islands were more closely connected to the rest of the world than to Spanish regions in both imports and exports, which makes sense considering their distant location. Their trade structure is determined by the absence of profitable fossil fuels in the area and therefore an inherent dependence on raw and semimanufactured energy carriers imported from abroad (Figure 3). This situation is similar for the rest of the products except for biomass, for which the situation is more balanced.

Figure 3. Level and composition of the accumulated international physical trade balance. Note: The left bar for every region represents InPTB accumulated values (1996−2010) of raw materials, the middle bar represents InPTB accumulated values (1996−2010) of semimanufactured products and the right bar represents InPTB accumulated values (1996−2010) of manufactured products. Region codes: AN, Andalusia; AR, Aragon; AS, Asturias; BI, Balearic Islands; CI, Canary Islands; CN, Cantabria; CL, Castilla-Leon; CM, Castilla-La Mancha; CT, Catalonia; VL, Valencia; EX, Extremadura; GL, Galicia; MD, Madrid; MR, Murcia; NV, Navarre; BC, Basque Community; and RJ, La Rioja. Source: compiled by the authors from sources shown in SI Table S1. Figure 4. Cross-regional accumulated physical trade balances of nonmetallic minerals. Units: thousand tons. Note: This covers 90% of the overall flows between 1996 and 2010. F, From; T, To. Region codes: AN, Andalusia; AR, Aragon; AS, Asturias; BI, Balearic Islands; CI, Canary Islands; CN, Cantabria; CL, Castilla-Leon; CM, Castilla-La Mancha; CT, Catalonia; VL, Valencia; EX, Extremadura; GL, Galicia; MD, Madrid; MR; Murcia; NV, Navarre; BC, Basque Community; and RJ, La Rioja. Source: compiled by the authors from sources shown in SI Table S1.

Other regions showed a mixed profile in terms of origin of their imports and destination of their exports determined by the absence of fossil fuels in the Spanish territory and consequently by the location of infrastructures for crude oil and gas storage and refinement. Andalusia, Catalonia, Galicia, and Asturias imported mostly fossil fuels from other countries, whereas around 60% of their exports were delivered to the rest of the Spanish regions. Their structural features, particularly regarding exports, are diverse. Andalusia was a net exporter of raw and semimanufactured energy carriers on the regional level, balanced by the large share of fossil fuels imported from abroad. Imports of fossil fuels were also important in Galicia, as were metals and biomass, while exports to other Spanish regions were mainly in the form of animal products and semimanufactured energy carriers. However, most of the international imports of Catalonia were energy carriers and exports were mainly manufactured products. In Asturias, international imports of metals and energy carriers were related to its heavy industry, while exports were more diversified. The Basque Community and Murcia also had a profile highly influenced by the presence of refineries, the largest share of their imports being fossil fuels from the rest of the world and semimanufactured metallic products in the case of the Basque Community. In contrast, the Basque Community’s exports in

to the housing bubble). These flows follow the typical pattern of nonmetallic minerals, showing limited mobility because they are cheap and relatively abundant.24,33 In consequence, adjacent territories supported the material requirements of regions where the construction sector was more dynamic. This fact makes RMFA particularly important if pressures derived from construction activities (the largest flows in volume) are to be revealed: the limited mobility of construction minerals might make their pressures invisible on the national level. In the case of Spain, Castilla-La Mancha and Castilla-Leon were among the main providers of Madrid, Valencia and the Basque Community. Castilla-La Mancha and Castilla-Leon largely covered Madrid’s demand. Murcia, Aragon, and Castilla-La Mancha covered Valencia’s demand. Finally, Castilla-Leon, 2265

DOI: 10.1021/es504438p Environ. Sci. Technol. 2015, 49, 2262−2269

Article

Environmental Science & Technology Aragon, Navarre, Cantabria, and La Rioja covered the Basque Community’s demand. In aggregated terms, Madrid was a net importer, with the highest values of IrPTB, while Andalusia and Murcia were the main net exporters, with negative values. In terms of environmental pressures, this means that Madrid exported the greatest pressure to the remaining regions of Spain, in addition to the high pressure placed on its own territories, as stated above. The Spanish economy as a whole has been supported by a physical trade deficit during the last few decades.10 The same occurs at the regional level. Extremadura and Castilla-La Mancha are the only net exporters in the international context. Extremadura sold gas to Portugal on a few occasions and Castilla-La Mancha exports mainly nonmetallic minerals, cereals, legumes and animal products. Given the importance of the energy carriers for both interregional and international trade, net flows of electricity comprehensively enrich the analysis of several regions. The electricity balance complements the international imports of energy carriers to Galicia and Asturias and the interregional imports of energy carriers to Castilla-Leon, Aragon, and Extremadura. Madrid is again the largest net importer, along with the Basque Community and Valencia. This is important considering that CO2 emissions are not measured where electricity is consumed but where it is produced.38 Domestic Material Consumption. The magnitude of DMC ranged from 12.6 to 20.9 t/cap at the national level although a significant variability can be observed beneath the aggregated values: DMCpc varied by a factor of 4 in 1996 and 6 in 2010 across the Spanish regions, so the last period of economic growth in Spain resulted in an increased difference in DMCpc and in DEpc (SI Table S8). This variability is larger and the trend was the opposite of those found across European countries,33 where DMC per capita has varied by a factor of 3 in a converging pattern since 1970. Globally, differences have also grown during the last few decades.14 The trends are similar to those of DE: general growth until 2007, followed by a sharp decrease to values close to and even below those of 1996. Asturias reached very high values (41.6 t/ cap), whereas the Canary Islands and Madrid had low values, both peaking at around 12 t/cap and decreasing below 6 t/cap in 2010. Low DE/DMC ratios highlight the dependency of the Spanish regions on international imports of fossil fuels and metals. The situation is balanced for biomass and nonmetallic minerals, with the exception of Madrid and the islands, where 18% and 50% of the biomass consumed is extracted domestically. Nonmetallic products are extracted in the region where they are consumed and in nearby territories, as stated above. Only the Basque Community, the Canary Islands and Madrid domestically extracted less than 90% of the nonmetallic minerals consumed. Furthermore, as the housing bubble progressed and the exacerbated use of nonmetallic minerals increased, so did the overall material dependency of the Spanish regions. The structure of DMCpc varies greatly across regions (Figure 5). Aragon, Castilla-La Mancha, Castilla-Leon and Extremadura showed a significantly larger share of biomass: over 20% during the whole period. Other regions such as Andalusia and Galicia started and finished the period with values over 20% of biomass. However, as the housing bubble evolved the share of biomass dropped, which is the general trend. All the regions experienced an increase in the share of nonmetallic minerals,

Figure 5. Level and structure of domestic material consumption per capita of the Spanish regions. Note: The first bar for every region represents values for 1996, the middle bar represents the year with maximum values (see SI Table S8), and the third bar represents values for 2010. Region codes: AN, Andalusia; AR, Aragon; AS, Asturias; BI, Balearic Islands; CI, Canary Islands; CN, Cantabria; CL, CastillaLeon; CM, Castilla-La Mancha; CT, Catalonia; VL, Valencia; EX, Extremadura; GL, Galicia; MD, Madrid; MR; Murcia; NV, Navarre; BC, Basque Community; RJ, La Rioja. Source: compiled by the authors from sources shown in SI Table S1.

with the exception of Murcia, the Basque Community and the Balearic Islands, where the share of energy carriers attenuated this trend. Extreme values of the share of nonmetallic minerals were found in Murcia (73%), Cantabria (78%), and Valencia (83%). Material Intensity, Dematerialization and Environmental Kuznets Curves. The direct material requirements (and associated environmental pressures) of the regional economies in order to produce €1000 of GDP followed the same path as DE and DMC (SI Table S9). First, they grew to a maximum (the most extreme case was Murcia, where direct material requirements doubled in 2007, whereas the value for Spain multiplied by a factor 1.2) and then they fell to values lower than those of 1996, with the sole exception of La Rioja. This means that, as GDP grew, so did resource inefficiency. No evidence of absolute dematerialization39 was found. Relative dematerialization was observed in the case of Galicia, Navarra and the Canary Islands, where GDP grew faster than DMC between 1996 and 2008. The performance of the regional indicators did not generally meet the environmental Kuznets curve hypothesis (inverted-U shape).40 However, a strong positive linear relationship between DMC and GDP and between CO2 and GDP was found in most of the regions. A Pearson coefficient above 0.8 was obtained in 12 of the 17 ACs for DMC. The polynomial adjustments fitted worse in r2 terms in regions where the Pearson coefficient was below 0.8: Navarre (0.5), Cantabria (0.4), Galicia (0.3), the Balearic Islands (0.2) and the Canary Islands (0.1). Regarding CO2 emissions, 9 of the 17 ACs had a Pearson coefficient over 0.8 for a linear positive adjustment. Asturias, Madrid and Galicia showed a particularly good fit for a second-degree polynomial function (r2 > 0.7), which can be explained by the substitution of coal for electricity generation in the case of Galicia and Asturias. In the case of Madrid, it is related to the methodological approach.38



DISCUSSION This work includes the results of the RMFA of Spain based on a new data set. This is one of the first cases studies in which data series of the entire set of the direct indicators for a whole country at the regional level have been compiled. 2266

DOI: 10.1021/es504438p Environ. Sci. Technol. 2015, 49, 2262−2269

Article

Environmental Science & Technology

factor for identifying environmental pressures given that the largest share of physical commercial exchanges occur across regions. This fact is important regarding displacement of environmental loads through trade. Production and consumption processes in the global economy can be disconnected in space, as has been claimed in the international context.14,44−46 Our results suggest that these processes might be quantitatively more important across regions. Seemingly, regions are able to play different physical commercial roles (e.g., act as raw material suppliers) in the regional and the international context similar to the roles played by countries.9,46,47 Patterns of extractive and commercial specialization are also likely to appear at the regional level. Consequently, the implications of IrT for climate change and material productivity policies emerge as a relevant issue.48−50 Further research will be required in order to soundly address these issues. Finally, applying material flow accounting to the regional scale opens a new space for understanding and interpreting indicators. Madrid stood out as a “black hole” of materials and electricity in absolute terms. The pressure exerted in its own territory by the extraction of natural resources exceeds any value known until now across the EU and most of the world. Furthermore, Madrid has succeeded in displacing a large share of its demand for nonmetallic minerals to the nearby regions, particularly Castilla-La Mancha. However, DEpc and DMCpc in Madrid, the islands, the Basque Community, Valencia and Catalonia were lower than expected. Densely populated regions containing big cities might be expected to have higher per capita values for consumption than less populated areas and rural regions, but this is not the case. This counterintuitive fact appears regularly in material flow studies and has been explained with several arguments to which this study can contribute.33 First, methodologically, EW-MFA does not account for indirect flows, so the extent to which the material requirements of a region are supported by upstream requirements coming from other systems remains unknown. Given the quantitative (size) and qualitative (patterns of commercial specialization) dimensions of IrT, the influence of this factor might be crucial at the regional scale. Approaches focusing on consumption might be more suitable for assessing this issue. Second, electricity is not accounted for, so the material requirements of electricity generation are not included as imports. This point is crucial on the regional level. Finally, economies of scale and agglomeration arise in densely populated urban areas, where common public services and infrastructures might be used more efficiently.51 RMFA is a powerful tool for exploring environmental pressures hidden within country-level indicators. On the basis of these data, additional research in the field of regional division of labor26,52,53 (i.e., sources and sinks) and the evaluation of environmental policies on the regional level53 is currently being carried out. Further discussion, additional case studies and complementary methodological approaches (raw material equivalents, the water footprint, and unequal ecological exchange) will hopefully expand the range of applications for this compilation.

The results for the RMFA of Spain must be placed in the context of an economic growth and subsequent recession linked to global financial trends and the strong performance of the national construction sector (see SI Table S10). Evidence has been found for a strong influence of construction sector dynamics (the housing bubble) on the regional metabolic trends and profiles. The most important consequence is that economic growth driven by these dynamics worsened material productivity, thus increasing augmenting the pressure exerted on the environment in order to produce one unit of GDP. Conversely to what has previously been observed in developing countries,41 neither material efficiency nor CO2 emissions were clearly reduced during the economic growth period (1996− 2008). On the contrary, a generalized “rematerialization” of the regional economies occurred as GDP grew in both absolute and relative terms. Future research in other countries and regions must test whether the decrease in resource productivity and increased environmental pressure is a general feature of housing bubbles. Another effect of these dynamics is the reduction in the share of renewable materials for domestic extraction and consumption across regions, including those with a pronounced agricultural profile. This is a common feature in developing and developed countries, but its effect is greater at the regional level, reaching very high values in Madrid and Asturias. Moreover, extraction and consumption trends reached their historical maximum levels in aggregate terms in at least the last 50 years.10 In addition to the geographic distribution of natural resources such as metals, and suitability for agriculture linked to soil fertility and climatic conditions, construction minerals played a leading role in the quantitative and qualitative extractive profile across regions. The last period of economic growth in Spain caused changes in the structure of the DE and DMC of regions through a massive increase in the use of nonrenewable materials. In addition, differences across regions in DEpc, DMCpc, and resource efficiency were more pronounced in 2010 than in 1996, so economic growth entailed an increase in the regional differences in material extraction and consumption. This work can serve as a first illustration of the regional environmental consequences of economic growth driven by a housing bubble. The most obvious outcome of the Spanish housing bubble is soil sealing as a result of the spread of artificial surfaces (i.e., urban areas). Following the results obtained by the Corine Land Cover Project (CLC), artificial surfaces grew by 52% from 1987 to 2006. Between 2000 and 2005, conversion into artificial surfaces progressed at a rate of 3.4 ha/hour, doubling the transformation ratio reached from 1986 to 2000.42 Most of the surfaces transformed were fertile agricultural areas (73%). A case study focusing on Madrid43 revealed that given the limited capacity of CLC for capturing artificial surfaces due to its spatial resolution, this transformation might have occurred faster and the total area of artificial surface could actually be larger (CLC identified 13% of the surface as artificial, whereas the case study based on detailed planimetry photo interpretation obtained 20%). Therefore, apart from causing a loss of material efficiency, the Spanish housing bubble amplified existing land artificialization trends. Environmental policies in search of an efficient use of resources may take this phenomenon into account and seek to discourage and counteract it in the future. The physical sizes of IrT and InT are for the first time compared with each other and between regions. IrT is a crucial



ASSOCIATED CONTENT

S Supporting Information *

Table S1. Data sources for domestic extraction categories following Eurostat (2013) classification. Table S2. Estimation 2267

DOI: 10.1021/es504438p Environ. Sci. Technol. 2015, 49, 2262−2269

Article

Environmental Science & Technology

(5) Towards Green Growth: Monitoring Progress. OECD Indicators; OECD Green Growth Studies; OECD Publishing: Paris, France., 2011; p 144. (6) Measuring Progress Towards a Green Economy; UNEP: Geneva, Switzerland, 2013. (7) World Resources Forum. Countries Should Annually Report on Resource Efficiency, WRF Concludes, 2013. (8) Schandl, H.; West, J. Material Flows and Material Productivity in China, Australia, and Japan. J. Ind. Ecol. 2012, 16, 352−364. (9) West, J.; Schandl, H. Material use and material efficiency in Latin America and the Caribbean. Ecol. Econ. 2013, 94, 19−27. (10) Carpintero, O. El Metabolismo de la Economiá Española. Recursos Naturales y Huella Ecológica (1955−2000); Fundación Cesar Manrique: Lanzarote, 2005; p 638. (11) Kovanda, J.; Hak, T. Historical perspectives of material use in Czechoslovakia in 1855−2007. Ecol. Indic. 2011, 11, 1375−1384. (12) Schandl, H.; Eisenmenger, N. Regional patterns in global resource extraction. J. Ind. Ecol. 2008, 10, 133−147. (13) Krausmann, F.; Gingrich, S.; Eisenmenger, N.; Erb, K.-H.; Haberl, H.; Fischer-Kowalski, M. Growth in global materials use, GDP and population during the 20th century. Ecol. Econ. 2009, 68, 2696− 2705. (14) Giljum, S.; Dittrich, M.; Lieber, M.; Lutter, S. Global Patterns of Material Flows and their Socio-Economic and Environmental Implications: A MFA Study on All Countries World-Wide from 1980 to 2009. Resources 2014, 3, 319−339. (15) Rosado, L.; Niza, S.; Ferrão, P. A Material Flow Accounting Case Study of the Lisbon Metropolitan Area using the Urban Metabolism Analyst Model. J. Ind. Ecol. 2014, 18, 84−101. (16) Hammer, M.; Giljum, S.; Bargigli, S.; Hinterberger, F. Material Flow Analysis on the Regional Level: Questions, Problems, Solutions; NEDS Working Paper; 2; Hamburg, 2003; p 56. (17) Kennedy, C.; Cuddihy, J.; Engel-Yan, J. The changing metabolism of cities. J. Ind. Ecol. 2007, 11, 43−59. (18) Frías Díaz, J. M.; Naredo Pérez, J. M. Los flujos de agua, energia,́ materiales e información en la Comunidad de Madrid y sus contrapartidas monetarias. Pensam. Iberoam. 1987, 275−326. (19) Brunner, P.; Daxbeck, H.; Henseler, G.RESUB-Der Regionale Stoffhaushalt im unteren Bünztal, 1990. (20) Bringezu, S.; Schütz, H. Die stoffliche Basis des Wirtschaftsraumes Ruhr. Ein Vergleich mit Nordrhein-Westfalen und der Bundesrepublik Deutschland. Raumforsch. Raumordn. 1996, 54, 433− 441. (21) Baccini, P. A city’s metabolism: Towards the sustainable development of urban systems. J. Urban Technol. 1997, 4, 27−39. (22) Almenar, R.; Bono, E.; Garcia, E. La Sostenibilidad Del Desarrollo. El Caso Valenciano; Universitat de Valencia. Fundacio Bancaixa: Valencia, 1998. (23) Niza, S.; Rosado, L.; Ferrão, P. Urban Metabolism. J. Ind. Ecol. 2009, 13, 384−405. (24) Kovanda, J.; Weinzettel, J.; Hak, T. Analysis of regional material flows: The case of the Czech Republic. Resour. Conserv. Recycl. 2009, 53, 243−254. (25) Li, N.; Zhang, T. Estimation of regional physical imports and exports of EW-MFA in China using monetary input-output tables. Front. Environ. Sci. Eng. 2013, 7, 242−254. (26) El metabolismo económico regional español (The Spanish Regional Economic Metabolism); FUHEM: Madrid, 2014. (27) Eurostat. Economy-wide Material Flow Accounts (EW-MFA) Compilation Guide 2013; Luxembourg, 2013. (28) Schoer, K.; Weinzettel, J.; Kovanda, J.; Giegrich, J.; Lauwigi, C. Raw Material Consumption of the European UnionConcept, Calculation Method, and Results. Environ. Sci. Technol. 2012, 46, 8903−8909. (29) Wiedmann, T. O.; Schandl, H.; Lenzen, M.; Moran, D.; Suh, S.; West, J.; Kanemoto, K. The material footprint of nations. Proc. Natl. Acad. Sci. U. S. A. 2013, 1−6. (30) Bruckner, M.; Giljum, S.; Lutz, C.; Wiebe, K. S. Materials embodied in international tradeGlobal material extraction and

details and specific coefficients for the calculation of grazed biomass, wood, firewood, hay and metal ores. Table S3. Correspondence between economy-wide material flow analysis categories and trade classifications for freight transport (NSTR/ 2007) and Eurostat’s categories based on Eurostat (2013). Table S4. Extensive socioeconomic indicators of the Spanish autonomous communities. Table S5. Intensive socioeconomic indicators of the Spanish autonomous communities. Table S6. Domestic Extraction. Absolute, per capita and per surface area values and biomass share. Table S7. Accumulated interregional (Ir) and international (In) imports, exports, physical trade balance, and accumulated electricity balances. Table S8. Domestic material consumption. Absolute, per capita and per surface area values and biomass share. Table S9. Material intensity and Pearson coefficient of domestic material consumption and CO2 related to GDP (1996−2008). Figure S1. Spanish administrative borders and regions at the NUTS 2 scale (autonomous communities and autonomous cities). This material is available free of charge via the Internet at http:// pubs.acs.org.



AUTHOR INFORMATION

Corresponding Author

*Phone: +34 620006072; e-mail: [email protected]. Author Contributions

All authors have given approval to the final version of the manuscript. Notes

The authors declare no competing financial interests. For the purpose of this article we distinguish between urban material flow analysis, focusing strictly on cities/metropolitan areas, and regional material flow analysis, set between a national level and the city administrative borders, and therefore dealing with counties and provinces. NUTS (Nomenclature of Territorial units for Statistics) refers to the geocode standard for referencing the subdivision of European Union members for statistical purposes (similarly to the Combined Statistical Areas of the United States). NUTS are hierarchically organized into 3 nested levels (NUTS1, NUTS2, NUTS3). Spain is divided into 19 NUTS2 regions known as autonomous communities.



ACKNOWLEDGMENTS The authors acknowledge the contribution of time and data made by Ó scar Souto, Carmen Marchán, Isabel Suárez, Francesc Maynou, and Mariá Dolores Barrio, as well as the insightful comments of three anonymous reviewers. This work was conducted as part of the Basic Statistics of Socioeconomic Metabolism project directed by Ó scar Carpintero and funded by FUHEM.



REFERENCES

(1) Fischer-Kowalski, M.; Krausmann, F.; Giljum, S.; Lutter, S.; Mayer, A.; Bringezu, S.; Moriguchi, Y.; Schütz, H.; Schandl, H.; Weisz, H. Methodology and Indicators of Economy-wide Material Flow Accounting. J. Ind. Ecol. 2011, 15, 855−876. (2) Economy-Wide Material Flow Accounting; European Communities: Luxembourg, 2001. (3) Tackling the Challenges in Commodity Markets and on Raw Materials; COM(2011) 25 Final; European Commission, 2011. (4) Recommendation of the Council on Material Flows and Resource Productivity; OECD: 2004. 2268

DOI: 10.1021/es504438p Environ. Sci. Technol. 2015, 49, 2262−2269

Article

Environmental Science & Technology consumption between 1995 and 2005. Glob. Environ. Chang. 2012, 22, 568−576. (31) Naredo, J.; Carpintero, O.; Marcos, C. Patrimonio inmobiliario y balance nacional de la economiá española (1995−2007); Colección FUNCAS: Madrid, 2008. (32) García Montalvo, J. De la quimera inmobiliaria al colapso financiero; Marcial Pons: Madrid, 2008. (33) Weisz, H.; Krausmann, F.; Amann, C.; Eisenmenger, N.; Erb, K.-H.; Hubacek, K.; Fischer-Kowalski, M. The physical economy of the European Union: Cross-country comparison and determinants of material consumption. Ecol. Econ. 2006, 58, 676−698. (34) Krausmann, F.; Fischer-Kowalski, M.; Schandl, H.; Eisenmenger, N. The Global Sociometabolic Transition. J. Ind. Ecol. 2008, 12, 637−656. (35) Barles, S. Urban Metabolism of Paris and Its Region. J. Ind. Ecol. 2009, 13, 898−913. (36) Murray, I. Geografies del capitalisme balear: poder, metabolisme ́ socioeconòmic i petjada ecològica d’una superpotència turistica. PhD Dissertation; Universitat de les Illes Balears: Palma de Mallorca, 2012. (37) Resource flow audit for sustainability: A framework strategy for the North West; 4 sight: Manchester, 2001. (38) Roca, J.; Alcántara, V.; Arto, I.; Padilla, E.; Serrano, M. La Responsabilidad De La Economiá Española En El Calentamiento Global; Los libros de la Catarata: Madrid, 2013. (39) Cleveland, C.; Ruth, M. Indicators of dematerialization and the materials intensity of use. J. Ind. Ecol. 1998, 2, 15−50. (40) Dinda, S. Environmental Kuznets Curve Hypothesis: A Survey. Ecol. Econ. 2004, 49, 431−455. (41) Steinberger, J. K.; Krausmann, F.; Getzner, M.; Schandl, H.; West, J. Development and dematerialization: an international study. PLoS One 2013, 8, e70385. (42) Prieto, F.; Campillo, M.; Fontcuberta, X. Cambios en la ocupación del suelo en el Reino de España. Primeros análisis a partir del proyecto Corine Land Cover; 2006. (43) Naredo, J. M.; García Zaldívar, R. Estudio Sobre La Ocupación Del Suelo Por Usos Urbano-Industriales Aplicado a La Comunidad De Madrid (1956−1980−2005); Ministerio de Medio Ambiente and Universidad Politécnica de Madrid: Madrid, 2008. (44) Schoer, K.; Weinzettel, J.; Kovanda, J.; Giegrich, J.; Lauwigi, C. Raw Material Consumption of the European UnionConcept, Calculation Method, and Results. Environ. Sci. Technol. 2012, 46, 8903−8909. (45) Schoer, K.; Wood, R.; Arto, I.; Weinzettel, J. Estimating Raw Material Equivalents on a Macro-Level: Comparison of Multi-Regional Input−Output Analysis and Hybrid LCI-IO. Environ. Sci. Technol. 2013, 47, 14282−14289. (46) Kovanda, J.; Weinzettel, J. The importance of raw material equivalents in economy-wide material flow accounting and its policy dimension. Environ. Sci. Policy 2013, 29, 71−80. (47) Ducruet, C.; Itoh, H.; Joly, O. Material flows and local economic structure: port-region linkages in Europe, Japan, and the United States; World Conference on Transport Research (WCTR) SIG-2: Antwerp, Belgium, 2012. (48) Webber, C. L.; Matthews, H. S. Embodied Environmental Emissions in U.S. International Trade, 1997−2004. Environ. Sci. Technol. 2007, 41, 4875−4881. (49) Peters, G. P.; Hertwich, E. G. CO2 Embodied in International Trade with Implications for Global Climate Policy. Environ. Sci. Technol. 2008, 42, 1401−1407. (50) Mahmoudifard, S. M.; Ko, S.; Mohammadian, K. Assessing Sustainable Freight Policies; Madison, 2014. (51) Fujita, M.; Krugman, P.; Venables, A. The Spatial Economy: Cities, regions, and International Trade; MIT: Cambridge Mass, 2001. (52) Delgado, M.; Carpintero, O.; Lomas, P. L.; Sastre, S. Andaluciá en la división territorial del trabajo dentro de la economiá española. Una aproximación a la luz de su metabolismo socioeconómico. 1996− 2010. Revista de Estudios Regionales 2014, 100, 197−222.

(53) Ginard-Bosch, J.; Murray, I.; Sastre, S.; Lomas, P. L.; Carpintero, O. Social Metabolism of a tourism-based economy in times of financial euphoria. The case of the Balearic Islands (1996−2010). Submitted.

2269

DOI: 10.1021/es504438p Environ. Sci. Technol. 2015, 49, 2262−2269