International Trade Drives Global Resource Use: A Structural Decomposition Analysis of Raw Material Consumption from 1990-2010.

Globalization led to an immense increase of international trade and the emergence of complex global value chains. At the same time, global resource use and pressures on the environment are increasing steadily. With these two processes in parallel, the question arises whether trade contributes positively to resource efficiency, or to the contrary is further driving resource use? In this article, the socioeconomic driving forces of increasing global raw material consumption (RMC) are investigated to assess the role of changing trade relations, extended supply chains and increasing consumption. We apply a structural decomposition analysis of changes in RMC from 1990 to 2010, utilizing the Eora multi-regional input-output (MRIO) model. We find that changes in international trade patterns significantly contributed to an increase of global RMC. Wealthy developed countries play a major role in driving global RMC growth through changes in their trade structures, as they shifted production processes increasingly to less material-efficient input suppliers. Even the dramatic increase in material consumption in the emerging economies has not diminished the role of industrialized countries as drivers of global RMC growth.

Built structures influence patterns of energy demand and CO2 emissions across countries.

Built structures, i.e. the patterns of settlements and transport infrastructures, are known to influence per-capita energy demand and CO2 emissions at the urban level. At the national level, the role of built structures is seldom considered due to poor data availability. Instead, other potential determinants of energy demand and CO2 emissions, primarily GDP, are more frequently assessed. We present a set of national-level indicators to characterize patterns of built structures. We quantify these indicators for 113 countries and statistically analyze the results along with final energy use and territorial CO2 emissions, as well as factors commonly included in national-level analyses of determinants of energy use and emissions. We find that these indicators are about equally important for predicting energy demand and CO2 emissions as GDP and other conventional factors. The area of built-up land per capita is the most important predictor, second only to the effect of GDP.

The misinterpretation of structure effects of the LMDI and an alternative index decomposition.

Changing the structure of the economy is often considered an option to reduce environmental impacts - for example, by changing the mix of sectors in the economy, the energy mix of production, or the mix of origin countries for imported products. To study the effect of such structure (or mix) effects, researchers often use index decomposition analysis (IDA). This study uses experimental data to show that most existing IDA methods, especially the widely used LMDI (logarithmic mean divisia index), yield results that are difficult to understand and easily misinterpreted. We use formal proof to demonstrate that:•The LMDI interpretation problem is due to the use of shares to describe the considered mix.•We developed an alternative method, the Marshall-Edgeworth with Structure Effects (MESE).•The MESE defines structure effects by comparing each observation to a hypothetical average, which better reflects the common understanding of structure effects.We compared empirical data on the LMDI and the MESE, analysing the effect of the changing sector mix on energy use in the USA from 1995 to 2016, and found that results from the two tools differed significantly. We therefore recommend using the MESE when structure effects are included in IDA.

Compilation of an economy-wide material flow database for 14 stock-building materials in 177 countries from 1900 to 2016.

International datasets on economy-wide material flows currently fail to comprehensively cover the quantitatively most important materials and countries, to provide centennial coverage and to differentiate between processing stages. These data gaps hamper research and policy on resource use. Herein, we present and document the data processing and compilation procedures applied to develop a novel economy-wide database of primary stock-building material flows systematically covering 177 countries from 1900- 2016. The main methodological novelty is the consistent integration of material flow accounting and analysis principles and thereby addresses limitations in terms of transparency, data quality and uncertainty treatment. The database systematically discerns four processing stages from raw materials extraction, to processing of raw and semi-finished products, to manufacturing of stock-building materials. Included materials are concrete, asphalt, bricks, timber products, paper, iron & steel, aluminium, copper, lead, zinc, other metals, plastics, container and flat glass. The database is compiled using international and national data sources, using a transparent and consistent 10-step procedure, as well as a systematic uncertainty assessment. Apart from a detailed documentation of the data compilation, validations of the database using data from previous studies and additional uncertainty estimates are presented. • Systematically compiled historical database of primary stock-building material flows for 177 countries. • Consistent integration of economy-wide material flow accounting and detailed material flow analysis principles. • Methodological enhancements in terms of transparency, data quality and uncertainty treatment.

Do material efficiency improvements backfire?: Insights from an index decomposition analysis about the link between CO2 emissions and material use for Austria.

To keep global heating and other negative consequences of socioeconomic activities within manageable boundaries, industrialized countries must undergo substantial decarbonization, requiring the exploitation of synergies with other environmental endeavors. Improving resource efficiency-that is, reducing the resources required to generate a unit of economic output-is a prominent goal pursued across levels of scale. How does resource efficiency relate to decarbonization? Do economies decrease their emissions as they become more efficient? We examine this relationship for Austria from 2000 to 2015 by conducting an index decomposition analysis at the sectoral level by using consumption-based indicators from the multi-regional input-output model Exiobase. Our analysis shows that for Austria, the currently popular pursuit of material efficiency appears to run the risk of coinciding with higher emissions, suggesting that the opportunities to achieve both decarbonization and dematerialization are limited. The Austrian service sectors could contribute to a reduction of the CO2 footprint via material efficiency improvements, but strong economic growth foils this possibility coming to fruition. The Austrian economy would do well to either curb demand for goods and services driving global CO2 emissions or to produce imported goods and services domestically in an environmentally more benign manner.