SummaryEnvironmentally extended multiregional input-output (EE MRIO) tables have emerged as a key framework to provide a comprehensive description of the global economy and analyze its effects on the environment. Of the available EE MRIO databases, EXIOBASE stands out as a database compatible with the System of Environmental-Economic Accounting (SEEA) with a high sectorial detail matched with multiple social and environmental satellite accounts. In this paper, we present the latest developments realized with EXIOBASE 3-a time series of EE MRIO tables ranging from 1995 to 2011 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 (SUTs) in a 163 industry by 200 products classification as the main building blocks. In order to capture structural changes, economic developments, as reported by national statistical agencies, were imposed on the available, disaggregated SUTs from EXIOBASE 2. These initial estimates were further refined by incorporating detailed data on energy, agricultural production, resource extraction, and bilateral trade. EXIOBASE 3 inherits the high level of environmental stressor detail from its precursor, with further improvement in the level of detail for resource extraction. To account for the expansion of the European Union (EU), EXIOBASE 3 was developed with the full EU28 country set (including the new member state Croatia). EXIOBASE 3 provides a unique tool for analyzing the dynamics of environmental pressures of economic activities over time.
Nearly 30% of global greenhouse gas emissions are associated with the production of capital goods. Consumption-based emission calculations based on multiregional input-output (MRIO) models allocate emissions occurring in the production of intermediate goods to the final goods produced in an economy. Like intermediate goods, capital goods are used in production processes; yet the emissions associated with their production are not allocated to the industries using them. As a result, the carbon footprint of final consumption as well as emissions embodied in trade are currently underestimated. Here, we address this problem by endogenizing capital transactions in the EXIOBASE global MRIO database, thereby allocating emissions from capital goods to final consumption. We find that endogenizing capital substantially increases the carbon footprint of final consumption (by up to 57% for some countries), and that the gap between production-based and consumption-based emissions increases for most countries. We also find that the global emissions embodied in trade increase by up to 11%, and that current patterns of bilaterally traded emissions are amplified. Furthermore, endogenizing capital leads to a 3-fold increase in the carbon footprint of certain product categories. The results suggest that our approach constitutes an important improvement to current input-output methodology.
Summary The investment in capital goods is a well‐known driver of economic activity, associated resource use, and environmental impact. In national accounting, gross fixed capital formation (GFCF) constitutes a substantial share of the total final demand of goods and services, both in terms of monetary turnover and embodied resources. In this article, we study the structure of GFCF and the environmental impacts associated with it on a global scale, and link it to measures of development. We find that the share of GFCF as part of the total carbon footprint (CF) varies more across countries than GFCF as a share of gross domestic product (GDP). Countries in early phases of development generally tend to invest in resource‐intensive assets, primarily infrastructure and machinery, whereas wealthier countries invest in less resource‐intensive assets, such as computers, software, and services. By performing a structural decomposition analysis, we assess the relative importance of investment structure and input‐output multipliers for the difference in carbon intensity of capital assets, and find that the structure of investments plays a larger role for less‐developed countries than for developed countries. We find a relative decoupling of the CF of GFCF from GDP, but we can neither confirm nor rule out the possibility of an absolute decoupling.
Hybrid life cycle assessment (HLCA) strives to combine process‐based life cycle assessment (PLCA) and environmentally extended input–output (EEIO) analysis to bridge gaps of both methodologies. The recent development of HLCA databases constitutes a major step forward in achieving complete system coverage. Nevertheless, current applications of HLCA still suffer from issues related to incompleteness of the inventory and data gaps: (1) hybridization without endogenizing the capital inputs of the EEIO database leads to underestimations, (2) the unreliability of price data hinders the application of streamlined HLCA for processes in some sectors, and (3) the sparse coverage of pollutants in multiregional EEIO databases limits the application of HLCA to a handful of impact categories. This paper aims at offering a methodology for tackling these issues in a streamlined manner and visualizing their effects on impact scores across an entire PLCA database and multiple impact categories. Data reconciliation algorithms are demonstrated on the PLCA database ecoinvent3.5 and the multiregional EEIO database EXIOBASE3. Instead of performing hybridization solely with annual product requirements, this hybridization approach incorporates endogenized capital requirements, demonstrates a novel hybridization methodology to bypass issues of price unavailability, estimates new pollutants to EXIOBASE3 environmental extensions, and thus yields improved inventories characterized in terms of 13 impact categories from the IMPACT World+ methodology. The effect of hybridization on the impact score of each process of ecoinvent3.5 varied from a few percentages to three‐fold increases, depending on the impact category and the process studied, displaying in which cases hybridization should be prioritized. This article met the requirements for a Gold—Gold JIE data openness badge described at http://jie.click/badges.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.