EXIOBASE 3: Developing a Time Series of Detailed Environmentally Extended Multi‐Regional Input‐Output Tables

Self Cite

163

107

SummaryMost countries show a relative decoupling of economic growth from domestic resource use, implying increased resource efficiency. However, international trade facilitates the exchange of products between regions with disparate resource productivity. Hence, for an understanding of resource efficiency from a consumption perspective that takes into account the impacts in the upstream supply chains, there is a need to assess the environmental pressures embodied in trade. We use EXIOBASE3, a new multiregional input-output database, to examine the rate of increase in resource efficiency, and investigate the ways in which international trade contributes to the displacement of pressures on the environment from the consumption of a population. We look at the environmental pressures of energy use, greenhouse gas (GHG) emissions, material use, water use, and land use. Material use stands out as the only indicator growing in both absolute and relative terms to population and gross domestic product (GDP), while land use is the only indicator showing absolute decoupling from both references. Energy, GHG, and water use show relative decoupling. As a percentage of total global environmental pressure, we calculate the net impact displaced through trade rising from 23% to 32% for material use (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011), 23% to 26% for water use, 20% to 29% for energy use, 20% to 26% for land use, and 19% to 24% for GHG emissions. The results show a substantial disparity between trade-related impacts for Organization for Economic Cooperation and Development (OECD) and non-OECD countries. At the product group level, we observe the most rapid growth in environmental footprints in clothing and footwear. The analysis points to implications for future policies aiming to achieve environmental targets, while fully considering potential displacement effects through international trade.

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Growth in Environmental Footprints and Environmental Impacts Embodied in Trade: Resource Efficiency Indicators from EXIOBASE3

Wood

Stadler

Simas

et al. 2018

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163

107

“…The intervention‐screening method can be linked to any EE I‐O database providing the required level of sector detail. The current analysis uses EXIOBASE 3 (Stadler et al ; Wood et al ) (taking year 2011), which provides a high and consistent product resolution (200 products) with a specific focus on environmentally relevant sectors (agriculture, renewable energy, and waste treatment). EXIOBASE provides multiple environmental and social extensions (air and water emissions, land and material inputs, labor).…”

Section: Case Studiesmentioning

confidence: 99%

Prioritizing Consumption‐Based Carbon Policy Based on the Evaluation of Mitigation Potential Using Input‐Output Methods

Wood¹,

Moran²,

Stadler³

et al. 2017

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SummaryCarbon footprints aim to engage consumers in contributing to climate-change mitigation. Consumption-oriented policy measures attempt to cause voluntary or incentivized interventions that reduce environmental impact through the supply chain by utilizing demand drivers. A large body of life cycle assessment studies describe how specific actions can reduce the environmental footprint of an individual or household. However, these assessments are often conducted with a narrow focus on particular goods and processes. Here, we formalize a counterfactual method and operational tool for scoping the potential impact of such actions, focusing on economy-wide impact. This "quickscan" tool can model shifts and reductions in demand, rebound effects (using marginal expenditure), changes in domestic and international production recipes, and reductions in the environmental intensity of production. This tool provides quick, macro-level estimates of the efficacy of consumer-oriented policy measures and can help to prioritize relevant policies. We demonstrate the method using two case studies on diet and clothing using the EXIOBASE3 multiregional input-output database, giving spatially explicit information on where environmental impact reductions of the interventions occur, and where impacts may increase in the case of rebounds. Keywords:carbon footprints climate policy industrial ecology input-output analysis life cycle assessment (LCA) rebound Supporting information is linked to this article on the JIE website

“…In addition, agricultural emissions of nitrogen and phosphorous to water are included (see Stadler et al. [] for a more extensive description of EXIOBASE 3).…”

Section: Methodsmentioning

confidence: 99%

Headline Environmental Indicators Revisited with the Global Multi‐Regional Input‐Output Database EXIOBASE

Steinmann

Schipper

Stadler

et al. 2017

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SummaryEnvironmentally extended multiregion input-output (EEMRIO) databases are used to quantify numerous environmental pressures and impacts from a consumption perspective. However, for targeted communication with decision makers, large sets of impact indicators are unfavorable. Small sets of headline indicators have been proposed to guide environmental policy, but these may not cover all relevant aspects of environmental impact. The aim of our study was to evaluate the extent to which a set of four headline indicators (material, land, water, and carbon) is representative of the total environmental impact embedded in an EEMRIO database. We also used principal component analysis combined with linear regression to investigate which environmental indicators are good candidates to supplement this headline indicator set, using 119 environmental indicators linked to the EEMRIO database, EXIOBASE. We found that the four headline indicators covered 59.9% of the variance in product-region rankings among environmental indicators, with carbon and land already explaining 57.4%. Five additional environmental indicators (marine eco-toxicity, terrestrial eco-toxicity, photochemical oxidation, terrestrial acidification, and eutrophication) were needed to cover 95% of the variance. In comparison, a statistically optimal set of seven indicators explained 95% of the variance as well. Our findings imply that there is (1) a significant statistical redundancy in the four headline indicators, and (2) a considerable share of the variance is caused by other environmental impacts not covered by the headline indicators. The results of our study can be used to further optimize the set of headline indicators for environmental policy.