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Global Distribution of Used and Unused Extracted Materials Induced by Consumption of Iron, Copper, and Nickel Kenichi Nakajima, Shoichiro Noda, Keisuke Nansai, Kazuyo Matsubae, Wataru Takayanagi, and Makoto Tomita Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b04575 • Publication Date (Web): 31 Dec 2018 Downloaded from http://pubs.acs.org on December 31, 2018

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Environmental Science & Technology

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Global Distribution of Used and Unused Extracted Materials

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Induced by Consumption of Iron, Copper, and Nickel

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Kenichi NAKAJIMA*1,2, Shoichiro NODA2, Keisuke Nansai1,3, Kazuyo Matsubae4, Wataru

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Takayanagi1, and Makoto Tomita5

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*Corresponding author (E-mail: [email protected]; Phone: +81-29-850-2744) 1

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Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki, 305-8506, Japan 2

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Integrated Sustainability Analysis, School of Physics, Faculty of Science, The University of Sydney, NSW, 2006, Australia.

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Department of Environment Systems, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8563, Japan

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Center for Material Cycles and Waste Management Research, National Institute for

Department of Environmental Studies for Advanced Society, Graduate School of Environmental Studies, Tohoku University, Miyagi, 980-8579, Japan

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Department of Arts, School of Humanities and Culture, Tokai University, 4-1-1 Kitakaname, Hiratsuka, Kanagawa, 259-1292, Japan

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ACS Paragon Plus Environment


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Abstract

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In today’s global economy, sustainable resource management requires a consumption

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perspective of resource use and insight into actual resource use through the global supply chain.

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The estimated global amount of used and unused extraction caused by mineral extraction of iron,

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copper, and nickel more than doubled from 1990 to 2013 (iron: 2.8 to 6.7 Pg; copper: 2.7 to 5.5 Pg;

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and nickel: 0.19 to 0.60 Pg). By incorporating global material flow into a global link input–output

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model (GLIO, a hybrid multiregional IO model), we estimated the total used and unused extraction

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caused by iron, copper, and nickel mining induced by Japanese final demand to be 0.44 Pg, 0.52

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Pg, and 0.043 Pg in 2011, respectively, equivalent to 7.1% of the total global extraction amount

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caused by iron mining, 11% of the amount caused by copper mining, and 10% of the amount caused

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by nickel mining. Whereas the world extraction total caused by iron, copper, and nickel mining

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rapidly increased from 2005 to 2011, the extraction amount induced by Japanese final demand for

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the same period either stayed about the same (iron) or decreased slightly (copper, 99% of the 2005

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amount; nickel, 92%).

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Keywords

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Material flow analysis (MFA), nickel, copper, iron and steel, consumption

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Graphical Abstract


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1. Introduction

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Economic growth is associated with a rapid rise in the use of natural resources within the

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economy1,2, and sometimes greater implementation of green technologies has triggered a rapid rise

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in the use of some metals and minerals. Because the successful achievement of the United Nations

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Sustainable Development Goals and the implementation of the Paris Agreement will require

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technologies that utilize vast quantities of a wide range of minerals, global resource governance to

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achieve sustainable and responsible mining will be required for sustainable development3.

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Although the materials refined from minerals play a crucial role in modern society, the rising

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demand for them has been tailored to the current high levels of mineral extraction and emission. In

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recent years, the mining industry has been under considerable pressure to improve its

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environmental and social performance. Halada et al.4 clarified huge amounts of “hidden”

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extractions underlying mineral production, and the World Resource Institute (WRI)5 and Durán

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et al.6 mapped global indicators of ecosystems and communities that are vulnerable to the negative

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impacts of mining. These reports indicated a significant overlap between the world’s active mines

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and strictly protected areas. Each of these studies indicates the importance of identifying areas

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prone to negative environmental impacts by mineral extraction induced by economic activities.

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Especially in today’s global economy, each country has indirect flows supporting its

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economic activities, and international trade chains influence environmental burdens far removed

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from the places of consumption (e.g., material footprint7,8; land footprint9-11; biodiversity

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footprint12; carbon footprint13; PM2.514). Under these conditions, it is important to examine

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negative and positive impacts of economic activates as a global systemic phenomenon to manage

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the burdens far removed from the place of consumption, rather than viewing production and

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producers in isolation. Ali et al.3 also pointed out the urgent necessity to establish a system for


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tracking mineral use along the entire value chain from source to end of life to achieve global

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resource governance.

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Adriaanse et al.15 established an accounting method for the total material requirements

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(TMRs) of nations and enabled international comparisons of used and unused mineral extractions,

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work that was expanded by Bringezu et al.16 and Kovanda et al.17. Used extraction refers to

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materials that are extracted from the environment and subsequently used in production processes,

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whereas unused extraction (i.e., hidden flow) refers to material flows that occur in the course of

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resource extraction but that do not directly enter the economic system (e.g., waste rock and

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overburden from mining operations). TMR studies have revealed the presence of huge amounts of

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unused extractione.g.4, 15-19. Economy-wide material flow analyses (MFA) studies have used Input-

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Output (IO) analysis to allocate used extraction to final consumption. For example, Kovanda and

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Weinzettel20 calculated raw material consumption as a consumption indicator based on raw

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material equivalents (RMEs), and Wiedmann et al. 7 calculated the material footprint of nations by

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expressing national resource consumption as RMEs. The material footprint of a nation based on a

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multiregional input–output (MRIO) model incorporating economy-wide MFA data provides a

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consumption perspective of resource use for that nation. Although the above-mentioned studies did

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not detail the country-specific distribution of extraction amounts, they bridged the gap between

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human activities and the related extraction amounts caused by mining activities.

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In this study, we focused on iron, copper, and nickel, whose global demands have risen

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rapidly in recent years, to examine the global distribution of extraction amounts of used and unused

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materials. The global demand for metals has rapidly increased as the global economy has grown,

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and huge amounts of social material stocks have been created1,

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consumption of iron, copper, and nickel were 1.7 Pg, 20 Tg, and 2.1 Tg, respectively, in 2010,


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The levels of apparent


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which represented increases by factors of 2.1, 1.6, and 1.7, respectively, from 19951. Global

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extraction of metal ores also grew by more than 250% between 1970 and 2010, and the extraction

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of iron ore and copper ore accounted for more than half of the global extraction of metal ores

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(UNEP IRP 2016). The development of technologies for a low-carbon society requires new

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infrastructure that will consume a mix of minerals that differs from current consumption, including

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not only critical metals such as the rare earths3,22, but also vast amounts of common metals such as

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nickel22, copper22, 23, and steel23,23.

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We estimated the global distribution amounts of used and unused mineral extractions caused

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by iron, copper, and nickel mining from 1990 to 2013, and demonstrated linkages between national

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economies and global impacts based on a global link input–output (GLIO) model24. Because Japan

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is a major importer of these minerals and a leading metal-producing country, we also quantified

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the links between Japan’s final demand and the global supply chain. The Japan analysis was

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performed using 2005 and 2011 data because the Japanese IO table is fixed.

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2. Materials and Methods

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2.1 Material flows in global trade

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Nansai et al.25 elaborated an MFA approach that created a complete global MFA system

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boundary. In our previous studies1,11, we estimated the global flow of iron, copper, and nickel

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associated with international trade among 231 countries from 1995 to 2010 with this global MFA

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method. In the present study, we updated these global flow estimates by adding flows for 2011. We

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recompiled the dataset, 𝑡(𝑘,𝑖) 𝑝𝑞 , which indicates the amount of substance i moving from country p to

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country q contained in the trade of commodity k (see Table S1 in the Supplementary Materials for

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a complete list of countries and regions). The number of trade commodities (k) considered to


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contain the substances of interest was 543 (4-digit: 196 commodities; 6-digit: 347 commodities)

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for iron, 288 (4-digit: 196 commodities; 6-digit: 92 commodities) for copper, and 303 (4-digit: 205

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commodities; 6-digit: 98 commodities) for nickel (see Table S2 in the Supplemental Materials for

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a complete commodity list). The commodities selected for each metal are listed in Nakajima et al.

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(2018) 1.

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2.2 Used and unused extraction: Total material requirement (TMR)

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TMR measures the amount of used and unused extraction caused by mining activities, which

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helps to clarify the huge extraction amounts caused by material consumption and production4, 26.

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We calculated the annual amount of used and unused extraction (𝐿𝑞,𝑖) caused by mining activities

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in each country and region: 𝐿𝑞,𝑖 = 𝑔𝑞,𝑖𝑡𝑖 , where 𝑔𝑞,𝑖 is the amount of substance 𝑖 embodied in

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extracted minerals mined in country q as published in United States Geological Survey (USGS)

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mineral statistics (e.g. iron27, 28; copper29, 30; nickel31, 32), and 𝑡𝑖 is material intensity factor (TMR

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coefficient) of substance 𝑖 embodied in the extracted minerals26. We also examined the amount of

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used and unused extraction (𝐿𝐽𝑃𝐷 𝑞,𝑖 ) caused by iron, copper, and nickel mining in country q induced

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𝐽𝑃𝐷 𝐽𝑃𝐷 by local consumption in Japan: 𝐿𝐽𝑃𝐷 is the amount of substance 𝑖 𝑞,𝑖 = 𝑔𝑞,𝑖 𝑡𝑖, where 𝑔𝑞,𝑖

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embodied in extracted minerals mined in country q that is induced by local consumption in Japan,

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which was calculated as described below.

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The material footprint of a country based on a MRIO incorporating economy-wide MFA data

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provides a consumption perspective of resource use for that country7. It expresses resource

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consumption as an ore-based weight for a given metal taking into consideration the metal content

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of the mineral ore. We calculated the Japanese material footprint of each substance (iron, copper,



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and nickel), that is, the amount of global extraction directly and indirectly caused by the Japanese

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economy, with a GLIO model8 that incorporated the global material flow (𝑡(𝑘,𝑖) 𝑝𝑞 ) compiled in

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Section 2.1. The material footprint of each substance was quantified not as an ore-based weight but

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as a content-based weight (g-Fe, g-Cu, and g-Ni). The GLIO model is a hybrid (mixed unit) MRIO

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that allowed us to define sectors with high resolution (more than 400 sectors for Japanese products)

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in the country of interest (Japan) and included 230 nations and regions other than Japan. As noted

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in our previous paper11, one key advantage of using a GLIO model in combination with an MRIO

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to calculate the footprints is that it enables quantification of the amount of mineral extraction

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generated by final consumption of commodities all the way back up global supply chains. Detailed

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descriptions and calculation formulas are available in our previous papers8, 11.

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3. Results

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3.1 Global distribution of used and unused extraction induced by the global economy

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The total used and unused extraction caused by iron, copper, and nickel mining were

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estimated to be 6.7 Pg, 5.5 Pg, and 0.6 Pg in 2013, which increased by factors of 2.4, 2.0, and 3.1

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since 1990, respectively (Table 1). The amount of extracted iron was quite large compared to the

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extracted amounts of copper and nickel: iron ore extraction was 1.4 Pg-Fe28, copper ore extraction

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was 16 Tg-Cu30, and nickel ore extraction was 2.0 Tg-Ni32. However, the results show that the total

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amount of used and unused extraction caused by copper and nickel mining in 2013 was not

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negligible as compared with the amount caused by iron mining.

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Oceania and Asia had the largest amount of used and unused extraction in 2013, followed by

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Latin America. Used and unused extraction caused by iron, copper, and nickel mining in these three

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regions have drastically increased since 1990. The sum of the changes in the three regions accounts


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for the majority of the total change in the extraction amounts for each metal (3.7 Pg, 2.5 Pg, and

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0.35 Pg, respectively). In particular, the extraction amount caused by nickel increased remarkably

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in recent years. In Asia, it increased by 1099% since 1990, and reached about 15% of the extraction

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amount caused by iron mining in the region in 2013. In Western Europe, the extraction amount

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caused by nickel mining increased from 6% of the amount caused by iron mining in 1990 to 10%

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in 2013, whereas the extraction amounts caused by iron and copper mining during the period in

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that region were almost constant.

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The top 20 countries and regions identified as having the largest amount of used and unused

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extraction caused by each of iron, copper, and nickel mining in 1990 and 2013 are shown in Figures

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1 and 2, respectively (see additional details in the Table S3 in the Supplementary Material). The

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three countries and regions with the largest extraction caused by iron mining accounted for 67% of

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the total extraction caused by iron mining in 2013, the top 10 accounted for 92%, and the top 20

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accounted for 99%. The three countries and regions with the largest extraction caused by copper

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mining accounted for 48% of the total extraction caused by copper mining in 2013, the top 10

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accounted for 80%, and the top 20 accounted for 94%. The three countries and regions with the

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largest extraction caused by nickel mining accounted for 54% of the total extraction caused by

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nickel mining in 2013, the top 10 accounted for 88%, and the top 20 accounted for 98%.

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The amount of used and unused extraction in most of the mining countries and regions with

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iron, copper, or nickel mining in 2013, including China, Australia, and Chile, which had the largest

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extraction amounts, increased rapidly since 1990. However, the amount of used and unused

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extraction in Russia and the United States decreased during that period because iron and copper

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mining in Russia and copper mining in the United States decreased. China and Australia, the major

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iron mining countries, showed drastic increases in the extraction amounts caused by iron mining



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as compared with the amounts caused by copper and nickel mining. In China, the extraction amount

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caused by iron mining increased by a factor of 5.0 since 1990; iron mining induced extraction of

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1.3 Pg, copper mining induced 0.48 Pg, and nickel mining induced 0.019 Pg in 2013. In Australia,

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the extraction amount caused by iron mining increased by a factor 5.9 since 1990; iron mining

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induced extraction of 2.1 Pg, copper mining induced 0.30 Pg, and nickel mining induced 0.047 Pg

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in 2013. In Chile, which had the greatest extraction of copper minerals, the extraction amount

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caused by copper mining increased by a factor 3.6 since 1990; iron mining induced extraction of

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0.045 Pg whereas copper mining induced 1.7 Pg in 2013. The extraction amount caused by copper

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mining relative to that of iron increased from a factor of 19 in 1990 to a factor of 38 in 2013.

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Significant changes were also observed in Brazil, a major producer of iron ore, where the amount

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of used and unused extraction caused by iron mining increased by a factor of 2.1 since 1990, the

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extraction amount caused by copper and nickel mining reached 8% equivalent and 3% equivalent

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of the extraction amount caused by iron mining in 2013. In Indonesia, the extraction amount caused

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by nickel and copper mining, respectively increased by factors of 12 and 3.1 since 1990.

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3.2 Global distribution of used and unused extraction induced by the Japanese economy

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Incorporating global material flows into the GLIO model, the material footprints of iron,

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copper, and nickel associated with Japanese final demand (Japanese domestic final demand plus

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exports) were detected to be 84 Tg-Fe, 1.8 Tg-Cu, and 0.23 Tg-Ni for 2005 and 88 Tg-Fe, 1.7 Tg-

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Cu, and 0.21 Tg-N for 2011. The total used and unused extraction caused by iron, copper, and

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nickel mining induced by Japanese final demand were estimated to be 0.43 Pg-Fe, 0.53 Pg-Cu, and

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0.047 Pg-Ni for 2005, 0.45 Pg-Fe, 0.52 Pg-Cu, and 0.043 Pg-Ni for 2011. These values were

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equivalent to 7.1% of the total world extraction amount caused by iron mining in 2011, 11% of the


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amount caused by copper mining, and 10% of the amount caused by nickel mining (Table 2). In

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2011, the total used and unused extraction induced by Japanese final demand was mainly induced

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in Latin America and Oceania, followed by Asia. Changes in the importing partners for iron and

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copper ore from Asia to Latin America and Oceania (UN Comtrade database33) are reflected in the

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extraction amounts caused by iron and copper mining in Asia. The trend differs between total world

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extraction and the extraction induced by the Japanese economy. Whereas the world extraction total

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caused by iron, copper, and nickel mining rapidly increased from 2005 to 2011, the extraction

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amount induced by Japanese final demand for the same period either stayed about the same (iron)

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or decreased slightly (copper, 99% of the 2005 amount; nickel, 92%). The extraction amounts

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caused by copper and nickel mining induced by Japanese final demand were the equivalent of 117%

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and 9.6% of the amount caused by iron mining in 2011, whereas the comparable global values were

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77% and 6.5%, respectively.

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Table 3 shows the total amount of used and unused extraction induced by Japanese final

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demand in 2011, as well as the contributions of each final demand category. Domestic final demand

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can be broken down into five categories: household consumption, government expenditure, public

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fixed-capital investment, private fixed-capital investment, and “other”. Here, public fixed-capital

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investments comprise domestic acquisition of fixed assets (purchase and transfer) such as buildings,

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machines, and devices by government service producers and public enterprises. The scope of

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private fixed-capital investments is the same as that of public fixed-capital investments. The main

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entities that exercise capital investments are industries (including public enterprises), non-profit

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private service producers, and households. The category with the highest contribution to the

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extraction induced by Japanese domestic final demand is private fixed-capital investment. The

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amount of used and unused extraction caused by iron, copper, and nickel mining induced by



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Japanese domestic final demand for this category was estimated to be 0.11 Pg (equivalent to 50%

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of total extraction caused by iron mining induced by Japanese domestic final demand), 0.14 Pg

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(51%), and 0.01 Pg (52%) in 2011, respectively.

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Figure 3 shows the top 20 countries and regions identified as having the largest amount of

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used and unused extraction caused by iron, copper, and nickel mining induced by the Japanese

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economy in 2011. The extraction amounts caused by iron, copper, and nickel mining in each of

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these countries and regions are also shown (see additional details in Table S4 in the Supplementary

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Material). The three countries and regions with the largest extraction amounts caused by iron

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mining induced by Japanese final demand accounted for 91% of the total extraction caused by iron

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mining in 2011, the top 10 accounted for 99%, and the top 20 accounted for approximately 100%.

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The three countries and regions with the largest extraction amounts caused by copper mining

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accounted for 70% of the total extraction caused by copper mining in 2011, the top 10 accounted

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for 92%, and the top 20 accounted for 98%. The three countries and regions with the largest

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extraction amounts caused by nickel mining accounted for 67% of the total extraction caused by

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nickel mining in 2011, the top 10 accounted for 96%, and the top 20 accounted for approximately

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100%. The extraction amounts induced by the Japanese economy was highly concentrated in the

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top few countries, especially the top three, as compared with the extraction amounts caused by the

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world economy. The three countries and regions with the largest extraction caused by iron mining

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induced by the world economy accounted for 65% of the total extraction caused by iron mining

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induced by the world economy in 2011, 48% of the extraction caused by copper mining, and 43%

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of the extraction caused by nickel mining. The amounts of used and unused extraction caused by

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iron, copper, and nickel mining induced by the Japanese economy were highly concentrated in

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Australia, Chile, and Brazil.


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4. Discussion

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4.1 Policy relevance

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The cumulative amounts of used and unused extraction caused by iron, copper, and nickel

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mining around the world from 1990 to 2013 were 95 Pg, 95 Pg, and 6.8 Pg, respectively (see

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additional details in Table S5 in the SI). Human activities and processes, such as forest clearing

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and urban expansion, impact natural capital. For example, mining activities have impacts on the

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removal of native vegetation and its destruction by the deposition of mine wastes (e.g. overburden

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and waste rock) 5. Actions for sustainable resource management, including following options, will

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be required to achieve sustainable development.

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Thinking in terms of a circular economy and “closing the loop”34 would help to significantly

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reduce pressure on natural resources and lead a transition to a sustainable economic system that

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encompasses the concept of decoupling resource use and economic growth. Remanufacturing,

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refurbishment, and repair and direct reuse (RRRDR) practices35 to expand product lifetime would

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play key roles in any transition. In addition to the implementation of RRRDR practices, improved

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material recycling to avoid the loss of substances in their anthropogenic cycles and closing material

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cycle loops36, 37 would reduce the consumption of natural resources and contribute to the reduction

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of negative impacts on the environment and human health. Dynamic MFAs38,39 have shown the

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potential impacts of the use of secondary resources from social stocks, but they also show gaps

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between demand and supply of resources. To cope with these gaps, dematerialization40,41,

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decoupling of natural resource inputs from economic outputs40,42, and resource productivity

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changes2,40 are necessary.



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The World Economic Forum, United Nations Development Programme, Columbia Center

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on Sustainable Investment, and Sustainable Development Solutions Network described the

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contributions by mining sectors to advance the Sustainable Development Goals43. New green

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mining technologies and regulations could significantly improve mining efficiency and reduce

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environmental impacts. When compared to surface mining, which requires overburden removal

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prior to ore extraction, underground mining operations tend to have lower stripping ratios (the

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amount of overburden that must be moved in order to extract a given amount of ore) because of

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increased selectivity. Cave mining methods (e.g., block caving and sublevel caving) for mass

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mining can improve stripping ratios44, 45 and contribute to a reduction in unused extraction. Lèbre

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et al.46 proposed a context for sustainable mining and tested a framework that makes use of MFA

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indicators to assess the metabolism of a mine site. This framework and the use of green mining

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technologies could contribute to managing used and unused extraction at mine sites.

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This study showed the potential impacts of the Japanese economy to influence the amount

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of used and unused extraction caused by mining. Final demand in Japan accounts for 7.1% of the

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total global extraction caused by iron mining, 11% by copper mining, and 10% by nickel mining

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(Table 2). Although these materials are not mined domestically, Japan should still be involved in

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their sustainable resource management. The study also revealed the strong influence of private

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fixed-capital investments and household consumption on the amounts of used and unused material

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extraction induced by Japanese domestic final demand (Table 3). A reduction of material intensity

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in these production sectors should reduce natural resource consumption outside of Japan.

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Minimization of material losses induced by demand would also work toward closing the material

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cycle loop and can be realized via material recovery not only from end-of-life products but also

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from pre-consumer materials.


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4.2 Limitations and future tasks

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This study demonstrated linkages between a national economy and global impacts based on

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a GLIO model and showed the important of tracking used and unused material extraction induced

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by national economies within the global supply chain. Our results showed drastic changes in the

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distribution of the extraction amounts caused by iron, copper, and nickel mining from 1990 to 2013

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and highlighted the importance of tracing the ever-changing global supply chain of natural

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resources.

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Recent rapid progress in the development of MRIO models7, 8, 47 has provided the means to

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analyze the linkages between national consumption and the global economy more reliably than

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before. However, the method possess the limitations mentioned in the above-mentioned MRIO

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studies. The input–output structure of GLIO allows a detailed description of Japan’s input–output

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structure (with 406 sectors of domestic commodities and 406 sectors of imported commodities)

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and the inclusion of 230 countries and regions as international sectors. The most salient feature of

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the GLIO is its description of targeted domestic commodity sectors with very high sectoral

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definition. On the other hand, each of the foreign sectors is consolidated into only a single sector.

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Hence, the GLIO allows the detail representation of an input–output relation on domestic

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commodities with foreign countries, but it is unable to describe the structure among foreign

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countries at the commodity level. This restriction lowers the model’s accuracy with respect to the

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indirect effects of metal consumption among countries other than Japan.

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In addition to model limitations, data uncertainty needs to be addressed. Data for mine

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production (e.g. USGS27-32, International Organizing Committee for the World Mining Congress48,

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British Geological Survey49), international trade (e.g. UN Comtrade33, BACI50), and material



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composition of commodities51-53 include uncertainties. For example, there are some slight

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discrepancies for data on mine production by type of database. Even within the same database, the

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reported values published in a given year were sometimes modified in accordance with later

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updates from the data sourcee.g.28. A major problem with the trade database (i.e. the Comtrade

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database33) is inconsistencies in trade volumes between countries that export commodities and

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those that import them50,54. To address this problem, this study employed the BACI database50,

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which improves on the Comtrade database to resolve these types of inconsistencies. Uncertainties

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in the material composition of commodities estimated by the Waste Input-Output MFA (WIO-

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MFA) model were discussed in our previous paper53. These data uncertainties influence the

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reliability of the material flows estimates, but unfortunately, no quantified uncertainties have been

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provided by individual data developers. Addressing these sources of uncertainty remains as a future

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task, as is determining their impacts on the results.

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To examine the amount of used and unused mineral extraction as a global systemic

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phenomenon, this study adopted the material intensity factor expressed by Katagiri et al. 26 and did

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not consider technological and regional variations of mine sites. For example, the stripping ratio is

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an important indicator to take into account to estimate the material that must be removed to reach

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the ore. The stripping ratio of mines and the ore grade of deposits are both related to the actual

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amount of unused extraction at each mine site.

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We acknowledge that estimating TMR based on the footprint approach does not provide

334

information on the actual amounts of used and unused mineral extraction; rather, it only provides

335

information indicating the huge amount of materials hidden behind mineral extraction induced by

336

national economies. A true decoupling of natural resource consumption from economic growth,

337

however, can only be achieved by not only reducing the total mass of material consumption but


Page 16 of 33

Page 17 of 33


17

338

also the induced amount of used and unused mineral extraction. Although the process is far from

339

inexpensive, incorporating the operational data of each mine site55 for the estimation model and

340

including sensitivity analyses, could help determine the actual material intensity for each mining

341

activity. As Ali et al. 3 pointed out, it is necessary to establish a system for tracking mineral use

342

along the entire value chain, from source to end-of-life. Our approach contributes to this goal by

343

tracking used and unused mineral extraction induced by national economies within the global

344

supply chain.

345 346

Acknowledgments

347

This research was partially supported by the Japan Society for the Promotion of Science

348

(KAKENHI 18KT0010), the Environment Research & Technology Development Fund (1-1601)

349

of the Japanese Ministry of Environment, the Sumitomo Foundation (183291), and the Japan

350

Science and Technology Agency (JST-Mirai Program Grant Number JPMJMI17C3).

351 352

Supplementary Materials

353

The supplementary material provides a summary of the countries and regions studied (Table S1);

354

commodity groups for each substance (Table S2); the distribution of the 20 countries and regions

355

with the largest amount of used and unused extraction caused by iron, copper, and nickel mining

356

in 1990 (Table S3-1, Figure S1) and 2013 (Table S3-2, Figure S2); the distribution of the 20

357

countries and regions with the largest amounts of used and unused extraction caused by iron, copper,

358

and nickel mining induced by the Japanese economy in 2005 (Table S4-1, Figure S3) and 2011

359

(Table S4-2, Figure S4); and the amounts of used and unused extraction caused by iron, copper,

360

and nickel mining around the world from 1990 to 2013 (Table S5).



18

361


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19

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26

515

Figure/Table Captions

516

Figure 1. Distribution of the 20 countries and regions with the largest used and unused extraction

517

amounts caused by iron, copper, and nickel mining in 1990.

518 519


520

amounts caused by iron, copper, and nickel mining in 2013.

521 522


523

amounts caused by iron, copper, and nickel mining induced by the Japanese economy in 2013.

524 525

Table 1. Global distribution of used and unused extraction amounts in 1990 and 2013

526 527

Table 2. Global distribution of used and unused extraction induced by the Japanese economy in

528

2005 and 2011

529 530

Table 3. Amount of used and unused extraction induced by Japanese final demand by category in

531

2011


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Table 1. Global distribution of used and unused extraction amounts in 1990 and 2013 1 Asia

2 Middle East

3 Central-Eastern Europe and Russia

4 Western Europe

1990

2013

Increasing rate

[Tg]

[Tg]

[%]

iron

460

1,853

303

copper

261

793

204

nickel

23

281

1,099

9

121

1,214

copper

24

70

191

nickel

0

iron

iron

681

633

-7

copper

408

585

43

nickel

58

66

15

iron

124

124

0

copper

138

140

1

8

37

388

iron

294

321

9

copper

713

564

-21

nickel

39

45

14

iron

655

1,244

90

copper

679

2,410

255

nickel

23

62

169

iron

169

276

63

copper

311

582

87

nickel

13

25

94

iron

363

2,113

483

copper

149

333

123

nickel

30

84

176

iron

2,754

6,684

143

copper

2,683

5,477

104

195

600

208

nickel 5 North America

6 Latin America

7 Africa

8 Oceania

World total

0-

nickel



Page 28 of 33

Table 2. Global distribution of used and unused extraction induced by the Japanese economy 2005 2011 Increasing rate in 2005 and 2011 [Tg] [Tg] [%] 1 Asia

iron

2 Middle East

3 Central-Eastern Europe and Russia

4 Western Europe

5 North America

39

24

-37

copper

105

60

-43

nickel

24

24

-1

iron

0

0

15

copper

1

2

223

nickel

0

0-

5

6

19

copper

iron

15

15

-2

nickel

3

3

-16

iron

1

2

12

copper

2

4

51

nickel

0

1

193

iron

4

5

24

28

35

27

copper nickel 6 Latin America

4

3

-13

iron

111

133

21

copper

296

331

12

3

2

-44

nickel 7 Africa

8 Oceania

SUM [1 to 8]

World total

iron

19

16

-16

copper

5

10

88

nickel

2

2

-29

250

260

4

copper

iron

77

66

-14

nickel

10

9

-6

iron

429

447

4

copper

529

523

-1

nickel

47

43

-8

iron

4,299

6,306

47

copper

4,503

4,844

8

293

409

40

nickel


Page 29 of 33


Table 3. Amount of used and unused extraction induced by Japanese final demand by category in 2011

Num. Final demand category

Used and unused extraction [Tg] Iron

Copper

Nickel

[1]

Household consumption

55

78

5

[2]

Governmental expenditure

10

13

1

[3]

Public fixed-capital investment

27

29

3

[4]

Private fixed-capital investment

108

137

11

[5]

Other

13

14

1

[6]

Export

233

251

21

Total domestic ﬁnal demand (sum of [1] to [5])

214

271

22

Total ﬁnal demand (sum of [1] to [6])

447

523

43



Figure 1. Distribution of the 20 countries and regions with the largest used and unused extraction amounts caused by iron, copper, and nickel mining in 1990. ACS Paragon Plus Environment

Page 30 of 33

Page 31 of 33


Figure 2. Distribution of the 20 countries and regions with the largest used and unused extraction amounts caused by iron, copper, and nickel mining in 2013. ACS Paragon Plus Environment


Page 32 of 33

Figure 3. Distribution of the 20 countries and regions with the largest used and unused extraction amounts caused by iron, copper, and nickel mining induced by the Japanese economy in 2011. ACS Paragon Plus Environment

Page 33 of 33


Graphical Abstract


Global Distribution of Used and Unused Extracted ... - ACS Publications

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