Summary: Environmentally 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.

Summary: We analyze the environmental impact of household consumption in terms of the material, water, and land‐use requirements, as well as greenhouse gas (GHG) emissions, associated with the production and use of products and services consumed by these households. Using the new EXIOBASE 2.2 multiregional input‐output database, which describes the world economy at the detail of 43 countries, five rest‐of‐the‐world regions, and 200 product sectors, we are able to trace the origin of the products consumed by households and represent global supply chains for 2007. We highlight the importance of environmental pressure arising from households with their consumption contributing to more than 60% of global GHG emissions and between 50% and 80% of total land, material, and water use. The footprints are unevenly distributed across regions, with wealthier countries generating the most significant impacts per capita. Elasticities suggest a robust and significant relationship between households’ expenditure and their environmental impacts, driven by a rising demand of nonprimary consumption items. Mobility, shelter, and food are the most important consumption categories across the environmental footprints. Globally, food accounts for 48% and 70% of household impacts on land and water resources, respectively, with consumption of meat, dairy, and processed food rising fast with income. Shelter and mobility stand out with high carbon and material intensity, whereas the significance of services for footprints relates to the large amount of household expenditure associated with them.

This article provides an overview of how generalised multi-regional input–output models can be used for carbon footprint applications. We focus on the relevance and suitability of such evidence to inform decision making. Such an overview is currently missing. Drawing on UK results, we cover carbon footprint applications in seven areas: national emissions inventories and trade, emission drivers, economic sectors, supply chains, organisations, household consumption and lifestyles as well as sub-national emission inventories. The article highlights the multiple uses of generalised multi-regional input–output models for carbon footprinting and concludes by highlighting important avenues for future research.

While it is understood that cities generate the majority of carbon emissions, for most cities, towns, and rural areas around the world no carbon footprint (CF) has been estimated. The Gridded Global Model of City Footprints (GGMCF) presented here downscales national CFs into a 250 m gridded model using data on population, purchasing power, and existing subnational CF studies from the US, China, EU, and Japan. Studies have shown that CFs are highly concentrated by income, with the top decile of earners driving 30%–45% of emissions. Even allowing for significant modeling uncertainties, we find that emissions are similarly concentrated in a small number of cities. The highest emitting 100 urban areas (defined as contiguous population clusters) account for 18% of the global carbon footprint. While many of the cities with the highest footprints are in countries with high carbon footprints, nearly one quarter of the top cities (41 of the top 200) are in countries with relatively low emissions. In these cities population and affluence combine to drive footprints at a scale similar to those of cities in high-income countries. We conclude that concerted action by a limited number of local governments can have a disproportionate impact on global emissions.