Provincial and sector-level material footprints in China

Abstract

High-income countries often outsource material demands to poorer countries along with the associated environmental damage. This phenomenon can also occur within (large) countries, such as China, which was responsible for 24 to 30% of the global material footprint (MF) between 2007 and 2010. Understanding the distribution and development of China’s MF is hence critical for resource efficiency and circular economy ambitions globally. Here we present a comprehensive analysis of China’s MF at the provincial and sectoral levels. We combine provincial-level input–output data with sector- and province-specific trade data, detailed material extraction data, and the global input–output database EXIOBASE. We find that some provinces have MFs equivalent to medium-sized, high-income countries and limited evidence of material decoupling. Lower-income regions with high levels of material extraction can have an MF per capita as large as developed provinces due to much higher material intensities. The higher-income south-coastal provinces have lower MF per capita than equally developed provinces. This finding relates partly to differences in economic structure but indicates the potential for improvement across provinces. Investment via capital formation is up to 4 times more resource-intensive than consumption and drives 49 to 86% of provincial-level MFs (the Organisation for Economic Co-operation and Development average is 37%). Resource-efficient production, efficient use of capital goods/infrastructure, and circular design are essential for reductions in China’s MF. Policy efforts to shift to a high-quality development model may reduce material intensities, preferably while avoiding the further outsourcing of high-intensity activities to other provinces or lower-income countries.

Global distribution of material inflows to in‐use stocks in 2011 and its implications for a circularity transition

“…More than 90% of the inflow of non-metallic minerals to in-use stocks was accumulated in the form of buildings and infrastructure (see nonmetallic spreadsheet in Data_S1 in the Supporting Information). This finding confirms the conclusions of previous studies regarding the importance of circular strategies in the construction sector (Jacobi et al, 2018;Jiang et al, 2019;Krausmann et al, 2018).…”

“…On average, high income regions (e.g., Europe and North America) accumulated three times more material inflows to in-use stocks than lower upper and lower middle income economies (e.g., Asian-Pacific and African countries). This is comparable to resource consumption patterns at different levels of economic development, which supports the hypothesis that capital formation is a key aspect of material use in a country or region (Jiang et al, 2019). The use of non-metallic minerals and steel constituted almost 95% of all material added to stocks across regions.…”

Chinese environmentally extended input-output database for 2017 and 2018

“…As the world’s second largest economy, leading consumer of various resources and energy, and dominating producers of emissions and waste, China has been one of the foci in environmental footprint analyses. China-specific EEIO models have been developed and applied to study a variety of environmental footprints in China such as carbon footprint 1 – 4 , water footprint 5 – 7 , energy footprint 8 , 9 , material footprint 10 , 11 , and atmospheric Hg footprint 12 – 14 . While the data sources used to construct EEIO databases in these studies are largely the same, the developed EEIO databases are rarely made publically available.…”

Improving Subnational Input–Output Analyses Using Regional Trade Data: A Case-Study and Comparison

“…Each region includes data on 48 sectors. We refer to the Supporting Information (SI) and earlier work 5 for the detailed procedures for harmonizing and processing the two IOTs.…”

“…3 For example, studies have investigated subnational regions in China, 5,7,16,18−24 Brazil, 25,26 Australia, 27 and EU countries. 28−30 These studies highlight three main issues: (1) treating a very large nation (e.g., China, which drives ∼30% of global material flow) as a homogeneous entity within a global multiregional input−output table (GMRIO) may mean researchers are unable to analyze important dynamics in the trade; 5,20,31 (2) it may bring bias to national results in total, 26,32−34 and (3) policymakers may struggle to convert messages from global and national analyses to regional strategies and targets. 18,22,24,25,31,32 Early EE-IO studies often used a single-region input−output (SRIO) table.…”