Durable Goods Drive Two-Thirds of Global Households' Final Energy Footprints

Material and Carbon Footprints of Machinery Capital

Machinery and equipment, integral as technology-specific capital goods, play a dual role in climate change: it acts as both a mitigator and an exacerbator due to its carbon-intensive life cycle. Despite their importance, current climate mitigation analyses often overlook these items, leaving a gap in comprehensive analyses of their material stock and environmental impacts. To address this, our research integrates input-output analysis (IOA) with dynamic material flow analysis (d-MFA) to assess the carbon and material footprints of machinery. It finds that in 2019, machinery production required 30% of global metal production and 8% of global carbon emissions. Between 2000 and 2019, the metal footprint of the stock of machinery grew twice as fast as the economy. To illustrate the global implications and scale, we spotlight key countries. China's rise in machinery material stock is noteworthy, surpassing the United States in 2008 in total amount and achieving half of the US per capita level by 2019. Our study also contrasts economic depreciation─a value-centric metric─with the tangible lifespan of machinery, revealing how much the physical size of the capital stock exceeds its book values. As physical machinery stocks saturate, new machinery can increasingly be built from metals recycled from retired machinery.

Energy Intensity of Final Consumption: the Richer, the Poorer the Efficiency

To maintain perpetual economic growth, most energy transition scenarios bet on a break in the historical relationship between energy use and gross domestic product (GDP). Practical limits to energy efficiency are overlooked by such scenarios, in particular the fact that high-income individuals tend to buy goods and services that are more energy intensive. Detailed assessments of the energy embodied in regional final consumption are needed to better understand the relationship between energy and GDP. Here, we calculate the energy necessary to produce households and governments' final consumption in 49 world regions in 2017. We correct prices at the sector level and account for the energy embodied in the whole value chain, including capital goods. We find that high-income regions use more energy per unit of final consumption than low-income ones. This result contradicts the common belief that a higher GDP is correlated with a better efficiency and questions the feasibility of mainstream energy transition scenarios based on universal GDP growth.

Sustainable Consumption in the Baltic States: The Carbon Footprint in the Household Sector

Sustainable consumption is one of the main aspects while implementing sustainable development goals. The main feature of sustainable consumption is the reduction of environmental impact. Thus, it is vital to understand and evaluate the environmental impact caused by consumption. In this paper, carbon footprint analyses of the Baltic States for the period of 2000–2019 were used to study sustainable consumption and pro-environmental behavior development. The results show not only how carbon footprint changes in different consumption categories (e.g., mobility, housing, food, and services), but whether it is related to changes in pro-environmental behavior as the promotion of sustainable consumption is crucial to reduce the consumption-based carbon footprint. The results from multi-regional input-output analyses show that in the Baltic States 62–71% of all the household carbon footprint is attributed to the three main consumption categories—transport, food, and housing. These categories are also responsible for 53–56% of the household expenditure. Consequently, changes in our mobility, food consumption, and housing management practices can significantly reduce the household environmental impacts. However, to minimize carbon footprints, behavioral changes are not enough; structural changes in the agro-food, housing, energy, and transport systems are also needed.

Integrating the inter- and intra-annual dynamic features of capital into environmental footprint assessment: Revisiting China's greenhouse gas footprints, 1995-2015

Assessments of the displacement of pollution emissions or other resources through trade attribute local production to remote consumers, yielding environmental footprints for the respective regions. Recently, the previously neglected temporal dimension of capital goods-built up in the past and continuously serving production activities in the future-has received increasing attention in environmental footprint assessments. Based on an inter-annual dynamic capital-endogenised multi-regional input-output model, this study further integrates the intra-annual dynamic features of capital production and consumption. We quantify the greenhouse gas (GHG) emissions embodied in China's capital consumption over the past two decades and assign this part of GHG emissions into finished goods and services over time. Our results show that China's GHG footprint in 2015 would be 7 Gt if capital-related GHG emissions were considered. This figure is 28% higher than the GHG footprints of China's final consumption estimated by conventional consumption-based accounting (CBA) and 41% lower than that of China's final demand estimated by conventional CBA. Overall, around 8% of GHG footprints would be overestimated if we do not consider the intra-annual dynamic feature of capital in the assessment. The inter-annual allocation shows that the capital-related GHGs of China's final consumption emitted on average in the last six years, which is still increasing owing to the long lifespans of capital assets. In light of the synergies among capital development, environmental sustainability, and human needs satisfaction, it is vital to uphold economic and environmental efficiency in capital development decision-making.