This analysis of material use and resource efficiency trends in the Asia Pacific region provides an important update to a study conducted 15 years ago on the same subject. Our findings indicate that some of the concerning trends identified in the earlier study have since moderated, with regional material demand plateauing in recent years. Resource efficiency improvements have continued and even accelerated over the decade to 2020. The impact of these trends is evident in a series of IPAT analyses, which indicate that improvements in the Technology factor used (Materials Intensity) were finally sufficiently strong to enable the region to continue raising living standards without notably increasing materials demand. As these empirical outcomes were not anticipated in the earlier study, we explore potential explanations for these trends. One consideration is whether the resource efficiency improvements indicated in an IPAT analysis of the most recent data provides support for Environmental Kuznets Curve (EKC) dynamics, a hypothesis largely dismissed in the previous study. Additionally, we examine whether the unprecedented expansion of productive infrastructure in the region during the early 21st century may now be sufficient to accommodate further infrastructure development in the region's lower-income countries, thereby reducing the need for continued growth in material throughput. Finally, revisiting the observations made in the 2010 paper highlighted the need to develop and use GDP measures that remain stable over time. We propose one such measure and demonstrate why a consistent GDP basis is essential for ratio-based metrics, such as resource efficiency, when used to monitor long-term performance.

Global metal extraction is increasing, owing to rising mineral demands from infrastructure development and the growing need for metal-intensive renewable energy technologies to mitigate climate change and phase out coal mining. However, extraction of metal ores also drives impacts on land use, water resources and biodiversity. In this Review, we evaluate mining trends of 47 metal ores between 1970 and 2022 and explore the environmental consequences. Global extraction of crude metal ores has nearly quadrupled, from 2.7 gigatonnes (Gt) in 1970 to almost 9.4 Gt in 2022, with the greatest increases in Oceania (+1,222%), South America (+929%) and Asia (+285%). Ore-specific mining activities are generally concentrated, with the top-five producers contributing on average 82.7% of the global supply in 2022. The impacts of mining are also concentrated. In 2022, about 50% of the 100,000 km2 global mining areas were located in Russia, China, Australia, the United States and Indonesia. Mining-induced water consumption, pollution and biodiversity loss substantially affect local ecosystems, with tropical rainforests and deserts being especially vulnerable. Around 70% of global metal extraction is linked to international supply chains. Enhanced environmental assessments, stricter implementation of policies, and coordinated actions across sectors throughout supply chains (mining, processing, consumers and financial markets) can help to mitigate the environmental impacts of mining. Global metal ore extraction has increased almost fourfold since 1970. This Review explores the drivers, patterns and environmental consequences of the growth of metal ore extraction and discusses interventions to reduce negative impacts across metal supply chains.

Sand and gravel, providing essential physical foundations for modern societies, are facing increasing demand due to urbanization and rural construction. This surge stems from the widespread use of these materials in building, roads, and other infrastructure, which has raised increasing concerns about the “sand crisis” and environmental damages from overexploitation. Addressing such concerns requires understanding patterns of global and national sand and gravel cycles, yet this remains hitherto unexplored. Here, we quantified historical stocks and flows of sand and gravel in buildings and infrastructure in 184 world countries from 1970 to 2019. We show that global gravel consumption is more than twice that of global sand consumption, albeit with a more stable growth rate. However, in international trade, sand dominates, with trade volumes 1.9 times larger than those of gravel, and Singapore is the leading importer. This suggests that sand supply is more vulnerable to geopolitical and market fluctuations. Over the past decades, per capita sand in-use stocks have increased in nearly all countries, whereas per capita gravel in-use stocks have saturated or even declined in many industrialized countries. Asia accounted for half of global sand in-use stocks and China has a large share of gravel stocks in residential buildings, both reflecting the impact of urbanization mode. These insights can inform policies for securing sustainable aggregate supply chains, improving resource efficiency, and mitigating environmental risks associated with overexploitation.

Producing essential, widely used materials such as steel, cement, paper, plastics and rubber requires substantial freshwater resources, which may exacerbate water scarcity. Despite this, comprehensive research on freshwater embodied in material production remains limited. Here we assess the blue water footprint (WFblue) of 16 metallic and non-metallic material categories across 164 regions, using a multiregional input-output model and the hypothetical extraction method. Our findings indicate that the global WFblue of material production doubled from 25.1 billion m(3) in 1995 to 50.7 billion m(3) in 2021, raising its share in global blue water consumption from 2.8% to 4.7%. The East, South Asia and Oceania regions saw an alarming 267% surge in WFblue for material production, with China-already facing medium-high water stress-experiencing a dramatic similar to 400% increase. As material production is expected to grow, we underscore the urgency of a water-materials nexus approach, particularly in water-stressed countries.

Accurate assessments of global primary material extraction, trade of primary materials and products, material use, waste, and emissions support the development of policies that facilitate the decoupling of economic activity, natural resource use, and related environmental impacts. Here, we quantify all crucial aspects of global and country-by-country material requirements needed to fuel economic activities, covering both territorial- and demand-based indicators. These data have been assembled by a consortium of research partners that compile the global material flow and resource productivity online database for the International Resource Panel, which contributes to the global dataset for the System of Environmental–Economic Accounting (SEEA) framework and is employed to monitor progress for the Sustainable Development Goal (SDG) indicators 8.4 and 12.2. We present the main findings of the 2024 update, including methodological improvements and result differences, and discuss the main findings and limitations. Since the last update, we have identified a slowing of global materials extraction since about 2014, a continuation of solid growth in direct trade of materials and products, persistent inequality in resource use between high- and low-income countries, and a prolonged improvement in global material productivity. The full dataset used herein can be downloaded from the Global Material Flow Database hosted by the United Nations Environment Program International Resource Panel.

The influence of international trade on the United Nations Sustainable Development Goals is multi-faceted. International trade can either promote or hinder progress, thus directly impacting people, economies and livelihoods. Here we explore the relevance of consumption-based proxies, which capture global demand for goods and services, to assess progress towards Sustainable Development Goals. We link these proxies to environmental and social issues for understanding trends in international outsourcing of resource and pollution-intensive production. We undertake a temporal assessment from 1990 to 2018 for the Global North and South to highlight polarizing trends that are affecting progress on achieving Sustainable Development Goals. We conclude that global trade can lead to both polarizing and equalizing trends that can influence a country’s ability to meet the 2030 Agenda for Sustainable Development. The role of international trade in achieving the UN Sustainable Development Goals is complex and affects multiple factors differently depending on the development context of each country. This study analyses historic trends and shows how global trade can either promote or hinder progress towards the Sustainable Development Goals.

Economic water productivity, gross value added per volume of water use, is a widely used metric by international and national organizations to monitor the impacts of economic activity on water use. In fact, this metric is often used synonymously with water efficiency. Considering this, our study analyzes the adequacy of economic water productivity as a Key Performance Indicator (KPI) for monitoring if water use has become more efficient. Using 15-year panel data for the 27 European countries and carrying out a sensitivity analysis with seven Asian countries to extrapolate our results, we address our hypothesis that changes in economic water productivity are not driven by increases in physical water efficiency but mostly originate from different sources of economic growth. Our results show that the improvements in economic water productivity are not necessarily associated with improvements in water efficiency but with advances in capital intensity and, hence, in labor productivity. Accordingly, we encourage policy-makers to replace this indicator – which is based solely on an economic vision rather than ecological concerns – with indicators that report the actual pressure on the water resources (e.g., absolute water consumption or physical water-efficiency indicators) or those that at least include their driving factors in the analysis (e.g. capital intensity, labor productivity). This would allow decision makers designing policies that are more effective and genuinely ensure sustainable water management. Otherwise, economically biased political assessments likely will provide erroneous results, leading to policy recommendations causing undesired environmental impacts in the medium and long term.

Metal mining plays a significant role in the Brazilian economy since its foundation as an overseas colony. The rapid increase in ore extraction brings along pressures on the country's water resources, as mining is a particularly water-intensive activity. However, site-specific data on water input and management are scarce. We propose a methodology for estimating water input in mining at a high geographical resolution. We focus on the three key metals mined in Brazil: iron, aluminum (i.e. bauxite ore), and copper, and derive water input coefficients for all mines from governmental and corporate sources as well as from the literature. We estimate that overall, the sum of the water inputs estimated for Brazilian bauxite, copper, and iron ore mining decreased by 15% from an average of 506.5±62.4 hm3 in 2014 to an average of 408.4±67.2 hm3 in 2017. The regions where most water was appropriated were Northern (Pará state) and Southeast (Minas Gerais) for iron, Northern (Pará) for aluminum, and Northern (Pará) and Central West (Goiás) for copper. We show that there are still significant consistency and data availability gaps, and that further work is still necessary to improve site-specific reporting and open access to data collected by public institutions.

EXIOBASE 3 provides a time series of environmentally extended multi-regional input‐output (EE MRIO) tables ranging from 1995 to a recent year for 44 countries (28 EU member plus 16 major economies) and five rest of the world regions. EXIOBASE 3 builds upon the previous versions of EXIOBASE by using rectangular supply‐use tables (SUT) in a 163 industry by 200 products classification as the main building blocks. The tables are provided in current, basic prices (Million EUR). For any questions regarding access, support or licence clarification please email: exiobase-support@googlegroups.com . The database is provided free of charge to users under a CC-BY-SA license. There is a discussion about different licence options, please reach out for information. For help in use of EXIOBASE data for spend-based emission factors, email exiobase-support@googlegroups.com EXIOBASE 3 is the culmination of work in the FP7 DESIRE project and builds upon earlier work on EXIOBASE 2 in the FP7 CREEA project and EXIOBASE 1 of the FP6 EXIOPOL project. These databases are available at the official EXIOBASE website. A special issue of Journal of Industrial Ecology (Volume 22, Issue 3) describes the build process and some use cases of EXIOBASE 3. This includes the article by Stadler et. al 2018 describing the compilation of EXIOBASE 3. Further informations (data quality, updates, ...) can be found in the blog post describing a previous release at the Environmental Footprints webpage. Various concordance tables for the database are available here. For more (background) information see the Readme file. For any questions regarding access, support or licence options please email: exiobase-support@googlegroups.com Previous EXIOBASE 3 Versions Some previous versions (3.7, 3.8) are also available on Zenodo. The even earlier public releases of the data (EXIOBASE v3.3 and v3.4) are available upon request. We recommend, however, to use the latest version due to significant updates of the economic data as well as major differences in water and land use accounts. End year The original EXIOBASE 3 data series ends 2011. In addition, we also have estimates based on a range of auxiliary data, but mainly trade and macro-economic data which go up to 2022 when including IMF expectations. A lot of care must be taken in use of this data. It is only partially suitable for analyzing trends over time! New data incorporating a full update for all SUTs to 2020 is soon available on request, reach out to exiobase-support@googlegroups.com The basic description of the process employed is in the relevant deliverable (link to pdf download).. As of v3.8 (doi: 10.5281/zenodo.4277368), the end years of real data points used are: 2015 energy, 2019 all GHG (non fuel, non-CO2 are nowcasted from 2018), 2013 material, 2011 for most others, land, water. More details are available in the readme file. The EXIOBASE country disaggregated dataset EXIOBASE3rx provides land updates to 2015. Some work is going on to update the extensions, but other collaborative efforts are more than welcome. Bulk Download To allow the download of specific years we uploaded the data as zip archives per year and mrio type (industry by industry: ixi, and product by product: pxp). If you need all data, we recommend the excellent zenodo_get python utility for the download. After installing the tool, you can download the latest version with: zenodo_get 10.5281/zenodo.3583070 Previous versions are available by replacing the latest DOI with previous record numbers. Alternatively, you can contact us at exiobase-support@googlegroups.com for alternative access options. IOT download and Pymrio integration If your are only interested in the IO tables, Pymrio (version >= 0.4.5) includes an automatic EXIOBASE 3 download function which works with the EXIOBASE upload on zenodo. The EXIOBASE 3 files can then be parsed and analysed directly. Nomenclature Archives: IOT_YYYY_ixi.zip - MRIO archive for Year YYYY in industry by industry format IOT_YYYY_ixi.zip - MRIO archive for Year YYYY in product by product format MRSUT_YYYY.zip - Multi-regional Supply-Use table for year YYYY SUT.zip - Domestic Supply Use for each country and year Content of IOT*.zip: (the archive can be read directly by pymrio without unpacking). The economic core is stored in the root of the archive, containing among others: Z.txt - flow/transactions matrix A.txt - matrix/inter-industry coefficients, (direct requirements matrix) Y.txt - final demand x.txt - gross/total output unit.txt - Units of the flow data We provide two set of extension data (stored in the sub-folders with the same name): satellite - uncharacterized stressors data - e.g. CO2 emissions, land use per category, etc. impacts - characterized stressors (=> impacts) - e.g. total GWP100, total land use, etc The total list of stressors and impacts are in the index of all files, most conveniently in the 'unit.txt'. Both extension subfolder contain: F.txt - Factors of productions/stressors/impacts F_Y.txt - Stressors/impacts of the final demand, S.txt - Direct stressor/impact coefficients S_Y.txt - Stressor/impact coefficients of the final demand M.txt - MRIO extension multipliers (total requirement factors of consumption) D_cba.txt - Consumption based accounts per sector D_pba.txt - Production based accounts per sector D_cba_reg.txt - Consumption based accounts per region D_pba_reg.txt - Production based accounts per region D_imp_reg.txt - Import accounts per region D_exp_reg.txt - Export accounts per region unit.txt - Absolute units of the stressor and impacts The unit of the coefficient data M and S are given be the unit of the satellite account per unit of the economic core (e.g. kg CO2eq/Million Euro) Announcements We use the EXIOBASE google group for announcing new versions of the database. For any questions regarding access, support or licence options please email: exiobase-support@googlegroups.com

Sustainable development depends on decoupling economic growth from resource use. The material footprint indicator accounts for environmental pressure related to a country’s final demand. It measures material use across global supply-chain networks linking production and consumption. For this reason, it has been used as an indicator for two Sustainable Development Goals: 8.4 ‘resource efficiency improvements’ and 12.2 ‘sustainable management of natural resources’. Currently, no reporting facility exists that provides global, detailed and timely information on countries’ material footprints. We present a new collaborative research platform, based on multiregional input–output analysis, that enables countries to regularly produce, update and report detailed global material footprint accounts and monitor progress towards Sustainable Development Goals 8.4 and 12.2. We show that the global material footprint has quadrupled since 1970, driven mainly by emerging economies in the Asia-Pacific region, but with an indication of plateauing since 2014. Capital investments increasingly dominate over household consumption as the main driver. At current trends, absolute decoupling is unlikely to occur over the next few decades. The new collaborative research platform allows to elevate the material footprint to Tier I status in the SDG indicator framework and paves the way to broaden application of the platform to other environmental footprint indicators. Despite the wide acceptance of the role of the material footprint indicator in sustainability, no reporting facility at present provides sufficient information on countries’ material footprints. This study presents a new research platform that regularly provides detailed global material footprint accounts.

Water productivity is broadly used as an indicator to measure the success of policies aiming at efficient water management. Focusing on the agricultural sector, this paper provides the first critical analysis of the appropriateness of water productivity for this type of assessment. We apply Logarithmic Mean Divisia Index (LMDI) decomposition analysis together with descriptive statistical analysis to test our main hypothesis that is natural resources do not generate value added, and therefore changes in water productivity are related to well-known drivers of economic growth rather than to improvements in water efficiency. We use three different models with different levels of decomposition detail to identify the drivers of water productivity changes. Results show that indeed there is a weak relationship between changes in water productivity and water efficiency. In contrast, changes in water productivity are driven by changes in labor productivity and capital intensity. Thus, we discourage policy makers from using the indicator to monitor the progress on efficient water management or on decoupling between economic growth and water consumption. Rather, indicators independent from economic development such as biomass per volume of water should be used and the absolute volumes of water appropriated by society monitored.

To reduce society's use of natural resources, actors in policy, business and society require awareness of the relevance of resource use in the context of sustainable development as well as of current unsustainable trends. This article illustrates how monitoring and management of resource use is reflected in international as well as German policies. It describes the development process, structure and key results of the new report series of the German Environment Agency (UBA) called 'Resource Use in Germany'. This series is meant to complement existing statistics and reports by addressing a broad range of stakeholders and making the topic more tangible. The reports should inform and motivate readers to become responsible and active citizens and aim at supporting the implementation of the Resource Efficiency Programme (ProgRess) of the German Federal Government.

Under the Paris Agreement, nations of this world aim to limit temperature increase to well below 2 degrees C above preindustrial levels and to pursue efforts to further limit the increase to 1.5 degrees C. Putting a price on CO2 emissions has been suggested as one approach to tackling global warming. This paper uses the results of suggested carbon pricing systems in the context of the Paris Agreement that consider biophysical boundary conditions for CO2 emissions. The impact of such carbon pricing is estimated statically for two ores - iron ore and bauxite - and four metals/ alloys - steel, aluminium, copper and gold - at a commodity level and a company level for some of the largest mining companies in the world. The authors conclude that at the commodity level the upper-bound impact of carbon pricing on metal prices would still be within the market driven price variations of recent years for copper and gold. The situation however looks different for steel and aluminium and for the companies, where prices and profitability would be significantly impacted, in some cases even by the minimum carbon prices used in this study, which would make mining unprofitable.

The authors of this article propose a major revision of the processes used for assembling the metal ores component of economy wide material flow accounts (EW-MFA). The case for doing this is built by describing in detail important shortcomings of current metal ores reporting systems, introducing the key features of the revised system being proposed, and then illustrating the way in which the new system both solves old shortcomings and adds important new capacities. The new capacities added are of particular interest with regard to organizing the data required for a range of practical resource and environmental monitoring and management tasks, at national and smaller scale. The various components of the case for change are explained largely using illustrative examples. The direct motivations behind this work are twofold. First, the proposed system will improve the accuracy and fitness for current uses of the metal ores accounts being assembled. Second, and more importantly, the additional capabilities of the revised system as a resource and environmental management tool will make the process of assembling EW-MFA accounts more clearly relevant to the concerns of developing countries, which are increasingly being prevailed upon to compile these accounts. In addition to the direct benefits of improved resources and environmental management that should be enabled by the revised system, it is expected that expanding the utility derived from the EW-MFA process will provide a stronger incentive for its institutionalization and maintenance by individual nations.

In various international policy processes such as the UN Sustainable Development Goals, an urgent demand for robust consumption-based indicators of material flows, or material footprints (MFs), has emerged over the past years. Yet, MFs for national economies diverge when calculated with different Global Multiregional Input-Output (GMRIO) databases, constituting a significant barrier to a broad policy uptake of these indicators. The objective of this paper is to quantify the impact of data deviations between GMRIO databases on the resulting MF. We use two methods, structural decomposition analysis and structural production layer decomposition, and apply them for a pairwise assessment of three GMRIO databases, EXIOBASE, Eora, and the OECD Inter-Country Input-Output (ICIO) database, using an identical set of material extensions. Although all three GMRIO databases accord for the directionality of footprint results, that is, whether a countries' final demand depends on net imports of raw materials from abroad or is a net exporter, they sometimes show significant differences in level and composition of material flows. Decomposing the effects from the Leontief matrices (economic structures), we observe that a few sectors at the very first stages of the supply chain, that is, raw material extraction and basic processing, explain 60% of the total deviations stemming from the technology matrices. We conclude that further development of methods to align results from GMRIOs, in particular for material-intensive sectors and supply chains, should be an important research priority. This will be vital to strengthen the uptake of demand-based material flow indicators in the resource policy context.

Metal mining has significant impacts on the land it uses. With increasing demand for metals, these impacts will continue to intensify. One way to look at land use and related environmental impacts is the concept of ecosystem services (ES), defined as the benefits people derive from services provided by ecosystems. This paper estimates the costs of the reduction of ES due to metal mining's global land use by analysing four key metal ores - bauxite (aluminium), copper, gold and iron, and by doing so, provides also novel information from which biomes those metals are extracted. The overall ES cost caused by metal mining is estimated at about USD 5.4 billion/year (2016), with about two thirds in forested areas. If added to prices, it would lead to increases of between 0.8 % and 7.9 % for the four commodities studied. The authors do not understand ES valuation as a market-based, stand-alone tool to lower the land impact of metal mining. Other policy tools would have to play a leading role, such as zoning regulations, environmental minimum standards or closure legislation. However, it would be a useful support for such policy tools in all stages of mining where land use aspects play a role.

1Institute for Ecological Economics, Vienna University of Economics andBusiness, Vienna, Austria 2Institute for Social Ecology, University ofNatural Resources and Life Sciences, Vienna, Austria 3Commonwealth Scientific and Industrial ResearchOrganisation, Canberra, Australia 4Fenner School of Environment and Society, AustralianNational University, Canberra, Australia 5School of Earth and Environment, University of Leeds, Leeds, UK Correspondence StefanGiljum, Institute forEcological Economics, ViennaUniversity ofEconomics andBusiness, Welthandelsplatz1/D5, 1020Vienna,Austria. Email: stefan.giljum@wu.ac.at Funding Information Thisworkwas supportedby funding fromthe Organisation forEconomicCo-operationand Development (OECD)under the contractsNo. 500050077andNo. 500061944, aswell as by theEuropeanCommissionunder theERC ConsolidatorGrant “FINEPRINT” (GrantNo. 725525).AnneOwen's timewas fundedbya UKEngineering andPhysical SciencesResearch Council FellowshipGrant (EP/R005052/1). EditorManagingReview:RichardWood Abstract In various international policy processes such as the UN Sustainable Development Goals, an urgent demand for robust consumption-based indicators of material flows, or material footprints (MFs), has emerged over the past years. Yet, MFs for national economies diverge when calculated with different Global Multiregional Input–Output (GMRIO) databases, constituting a significant barrier to a broad policy uptake of these indicators. The objective of this paper is to quantify the impact of data deviations between GMRIO databases on the resulting MF. We use two methods, structural decomposition analysis and structural production layer decomposition, and apply them for a pairwise assessment of threeGMRIOdatabases, EXIOBASE, Eora, and theOECD InterCountry Input–Output (ICIO) database, using an identical set of material extensions. Although all three GMRIO databases accord for the directionality of footprint results, that is, whether a countries’ final demand depends on net imports of rawmaterials from abroad or is a net exporter, they sometimes show significant differences in level and composition of material flows. Decomposing the effects from the Leontief matrices (economic structures), we observe that a few sectors at the very first stages of the supply chain, that is, raw material extraction and basic processing, explain 60% of the total deviations stemming from the technology matrices. We conclude that further development of methods to align results from GMRIOs, in particular for material-intensive sectors and supply chains, should be an important research priority. This will be vital to strengthen the uptake of demand-basedmaterial flow indicators in the resource policy context.

In recent years socially responsible investing has become an increasingly more popular subject with both private and institutional investors. At the same time, a number of scientific papers have been published on socially responsible investments (SRIs), covering a broad range of topics, from what actually defines SRIs to the financial performance of SRI funds in contrast to non-SRI funds. In this paper, we revisit Markowitz’ Portfolio Selection Theory and propose a modification allowing to incorporate not only asset-specific return and risk but also a social responsibility measure into the investment decision making process. Together with a risk-free asset, this results in a three-dimensional capital allocation plane that allows investors to custom-tailor their asset allocations and incorporate all personal preferences regarding return, risk and social responsibility. We apply the model to a set of over 6,231 international stocks and find that investors opting to maximize the social impact of their investments do indeed face a statistically significant decrease in expected returns. However, the social responsibility/risk-optimal portfolio yields a statistically significant higher social responsibility rating than the return/risk-optimal portfolio.