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As a key material for manufacturing clean energy technologies, steel is crucial for energy transition, but its production causes 2.6 Gton of CO _2 emissions at global level each year. In 2020 the European Union (EU) set a net-zero emissions target by 2050, fostering innovation in the steel industry to reduce its environmental impact. However, a scenario-oriented and technologically comprehensive analysis assessing prospected environmental and market implications of steel decarbonisation strategies remains a gap, which is addressed in this paper. The analysis adopts a hybrid input-output-based life-cycle assessment model built in the MARIO framework, extending the Exiobase database to represent the supply chains of the most promising low-carbon steelmaking technologies in the EU, such as hydrogen- or charcoal-injected blast furnaces and natural gas- and hydrogen-based direct reduction routes. The penetration of these technologies is explored by formulating scenarios resembling European climate targets. The results show a reduction in the carbon footprint of steel across all scenarios, ranging up to −26% in 2030 and to −60% in 2050. However, the extent of footprint reduction is highly dependent on the share of clean electricity in the European supply mix, highlighting the relevance of holistic decarbonisation strategies. Economic implications affect steel prices, which rise up to 25% in 2030 and 56% in 2050, opening discussions on the need for suitable policies such as CBAM to avoid protectionism and encourage international technological progress.

The introduction of the new biomass industry exerts influences that change the interactions among economic sectors by drawing the resources for generating electricity, pricing alterations from the existing market and competitively selling electricity to the power grid. These influences should be described and identified to ensure the benefits to the local economy. In this article, we deem to test the potential of hybrid I-O analysis to analyze the economic impacts and address the change in characteristics of the economic impacts of the biomass power plant. The resource utilization data from the existing biomass power plant located in Kochi Prefecture (Japan) is collected and then analyzed by a hybrid input-output (I-O) analysis. We found that (1) the use of cutoff function could determine the new economy's structure included the biomass power plant where the allocation of resource in the economy is changed according to the consumption and production of the biomass power plant, (2) The power plant increases the total production of Kochi prefecture's economy, and this benefit overthrows the negative effect of the loss of resource demand of the existing economic sectors. The use of the hybrid I-O to forecast the economic impacts on the local economy could enhance the decision made by the policymaker. [ABSTRACT FROM AUTHOR]

Connected and automated vehicles (CAVs) are emerging technologies expected to bring important environmental, social, and economic improvements in transportation systems. Given their implications in terms of air quality and sustainable and safer movement of goods, heavy‐duty trucks (HDTs), carrying the majority of U.S. freight, are considered an ideal domain for the application of CAV technology. An input–output (IO) model is developed based on the Eora database—a detailed IO database that consists of national IO tables, covering almost the entire global economy. Using the Eora‐based IO model, this study quantifies and assesses the environmental, economic, and social impacts of automated diesel and battery electric HDTs based on 20 macro‐level indicators. The life cycle sustainability performances of these HDTs are then compared to that of a conventional diesel HDT. The study finds an automated diesel HDT to cause 18% more fatalities than an automated electric HDT. The global warming potential (GWP) of automated diesel HDTs is estimated to be 4.7 thousand metric tons CO2‐eq. higher than that of automated electric HDTs. The health impact costs resulting from an automated diesel HDT are two times higher than that of an automated electric HDT. Overall, the results also show that automation brings important improvements to the selected sustainability indicators of HDTs such as global warming potential, life cycle cost, GDP, decrease in import, and increase in income. The findings also show that there are significant trade‐offs particularly between mineral and fossil resource losses and environmental gains, which are likely to complicate decision‐making processes regarding the further development and commercialization of the technology. [ABSTRACT FROM AUTHOR]

Different regions in China have different energy consumption characteristics and changing trends. This paper focuses on analyzing trends in energy consumption changes along the timeline for 30 regions in China. Using the Hybrid Input-Output Model, this paper decomposes energy consumption in 30 regions in 2007, 2012 and 2016 into energy embedded of final consumption expenditure, gross capital formation, inflow and outflow. We use these four dimensions as coordinates to draw a regional radar map. According to the changing characteristics of the radar map, 30 regions are divided into three groups. By analyzing the reasons for the changes in three regions, we draw the following conclusions. For regions where energy consumption is mainly inflow, the economically developed regions have to form a low energy consumption environment while achieving economic growth. The economically underdeveloped regions need to carry out energy conservation and emission reduction as well as ensuring the level of economic development. For some outflow regions with moderately economic development, it is necessary to balance the economic development and energy consumption control according to regional characteristics. For resource-rich regions which are in the process of transformation from agriculture to industrialization, they have to maintain the rapid development speed and strengthen their infrastructure with less energy consumption of buildings.

This paper presents a new and improved method of hybrid input-output (I-O) to evaluate the economic impact of a biomass power plant's resource production and consumption. The effect of resource consumption induces a change in an economy's production structure and alters the technical coefficient of the hybrid I-O table, which should not be changed. Our study examines this problem based on two cases: a small cut-off ratio from the existing industry, in which the change in the technical coefficient can be ignored, and a large cut-off ratio from the existing industry, in which the technical coefficient is amended using the pre-adjustment method. Consequently, the biomass power plant using the large cut-off ratio from the existing industry case contributes about 1114 million yen to the local economy. A comparison of these two cases shows that the error caused by ignorance of the technical coefficient adjustment could result in 291.78 million yen less in total economic production, which is about 36% of the total additional production using the small cut-off ratio from the existing industry case. The losses in total economic production clearly increase in economic sectors that are related to the resource consumption of the biomass power plant. [ABSTRACT FROM AUTHOR]

This paper presents a new and improved method of hybrid input-output (I-O) to evaluate the economic impact of a biomass power plant’s resource production and consumption. The effect of resource consumption induces a change in an economy’s production structure and alters the technical coefficient of the hybrid I-O table, which should not be changed. Our study examines this problem based on two cases: a small cut-off ratio from the existing industry, in which the change in the technical coefficient can be ignored, and a large cut-off ratio from the existing industry, in which the technical coefficient is amended using the pre-adjustment method. Consequently, the biomass power plant using the large cut-off ratio from the existing industry case contributes about 1114 million yen to the local economy. A comparison of these two cases shows that the error caused by ignorance of the technical coefficient adjustment could result in 291.78 million yen less in total economic production, which is about 36% of the total additional production using the small cut-off ratio from the existing industry case. The losses in total economic production clearly increase in economic sectors that are related to the resource consumption of the biomass power plant.

This study investigates the benefits of waste management policies on gaseous emissions and resource consumption caused by the final demand, in the specific case of France and in a context of economic growth. Waste input-output analysis is implemented to compare three scenarios, depicting and combining the upward trend of final demand from 2008 to 2020, the increase in recycling rates by 2020 (encompassing the achievement of recycling objectives set by European Union Directives), and the simultaneous larger implementation of best available techniques (BAT) for waste incineration. Hybrid monetary physical input-output tables are initially derived from balanced physical supply and use tables and further complemented with process inventory data on waste treatment technologies. A dramatic reduction in the demand for primary metals (by a factor of 2.0) and for primary mining and quarrying products for construction (by a factor of 1.9) is observed in 2020, as compared to 2008, in the case of the scenario 'recycling,' despite the competition induced by the evolution of the final demand. On the contrary, considering energy requirements and fossil carbon dioxide, sulfur dioxide, and nitrogen oxide emissions caused by the French final demand, the combined improvements in recycling and incineration performances by 2020 would only limit the rise induced by the evolution of the final demand. On the basis of these results, the potential contribution of waste management policies to the decoupling of resource consumption and gaseous emissions from final demand's growth is finally discussed. [ABSTRACT FROM AUTHOR]

With respect to global climate change, energy consumption and carbon emissions of the building sector has become an increasingly crucial issue in the sustainable development of China. While process-based analyses have been performed in previous research, in the present study, we propose a hybrid input-output approach that could account for supply-chain energy and emissions by China’s building sector. In terms of energy and emission sources, three scopes are defined, primarily aimed at the entire life-cycle of building sector. By dividing the life-cycle into construction, operation, and disposal stages, both scope-based and stage-based analyses are made using domestic statistical data, within the range 1997–2012. The results demonstrate that supply-chain energy and emissions of Scope 3 contribute significantly to the overall life-cycle impacts of building sector, which might be underestimated in a process-based assessment. Although the operation stage appears to be the one with the largest consumption and emissions in the lifespan of a single building, attention should also be paid to the construction stage. The energy and emissions during construction make up the largest share (over 60%) in the life-cycle of the building sector due to the large number of building projects every year. Energy and carbon-intensive components are also evaluated, and possible measures for energy-saving and carbon reduction are discussed. Accordingly, this study provides some useful methods and relevant analysis results, which will be critical for the future of sustainable development of China’s building industry. [ABSTRACT FROM AUTHOR]

Over the past two decades, many countries have used aggressive policies such as feed-in tariffs and power purchase agreements to promote renewable energy. These policies have been very successful in several countries, initiating large changes in the structure of energy sectors, and conferring large environmental, economic, and social impacts. In this paper, we quantify these impacts over the period 2000–2010 for Portugal; a country that witnessed a substantial increase in renewable energy penetration rates, with the share of wind power in electricity production jumping from 0.4% in 2000 to 16.8% in 2010. We use a novel, hybrid energy-economic input–output model to compare the historical energy policy against a counterfactual scenario in which the surge in energy subsidies and concurrent expansion of renewable energies did not take place. We consider the impact of renewable energy policy stemming from three propagation modes – operational, investment, and opportunity costs – in both the energy sector and the rest of the economy. This is the first time such a comprehensive analysis has been undertaken. Our findings show that, in the period under consideration, the combined historical renewable energy policy and renewable energy developments yielded a clear reduction in emissions, in excess of 7.2 MtCO 2 eq, an increase in GDP of 1557 M€, and a creation of 160 thousand job-years. These estimates do not include opportunity costs from future FIT payments that projects built in this period may be entitled to. Therefore, this work will be of critical interest to RES-E and climate change policy makers, other scientists, and the public. [ABSTRACT FROM AUTHOR]

Different regions in China have different energy consumption characteristics and changing trends. This paper focuses on analyzing trends in energy consumption changes along the timeline for 30 regions in China. Using the Hybrid Input-Output Model, this paper decomposes energy consumption in 30 regions in 2007, 2012 and 2016 into energy embedded of final consumption expenditure, gross capital formation, inflow and outflow. We use these four dimensions as coordinates to draw a regional radar map. According to the changing characteristics of the radar map, 30 regions are divided into three groups. By analyzing the reasons for the changes in three regions, we draw the following conclusions. For regions where energy consumption is mainly inflow, the economically developed regions have to form a low energy consumption environment while achieving economic growth. The economically underdeveloped regions need to carry out energy conservation and emission reduction as well as ensuring the level of economic development. For some outflow regions with moderately economic development, it is necessary to balance the economic development and energy consumption control according to regional characteristics. For resource-rich regions which are in the process of transformation from agriculture to industrialization, they have to maintain the rapid development speed and strengthen their infrastructure with less energy consumption of buildings. [ABSTRACT FROM AUTHOR]

We analyze 78 case studies that applied an input-output (IO) model for waste management analyses. We categorize all IO models into four types (waste extended IO (WEIO), waste IO (WIO), physical IO (PIO) and hybrid IO (HIO)). We then define each model within a waste analysis framework, and carry out a bibliometric analysis. Our comparative analysis is twofold. Firstly, to compare the models conceptually, we analyze and discuss three characteristics of the models – the units of intersectoral flows, the modelling of waste and the relation with mass balance principle. Secondly, we analyze and discuss six criteria pertaining to the functionalities of the models, – the waste generation accounting, the purpose of the modelling, the geographical scale, the temporal dimension, the coupling of the IO models with other methods and the level of details of waste treatment sectors and waste types. Our findings are fourfold. First, there is increasing interest in assessing waste management policies with IO models; WIO models are the most applied ones, followed by WEIO models; PIO models are the least widely applied. Second, WIO models have the most mature analytical framework, and HIO models are conceptually the most powerful. Third, there is no cause-effect link between the conceptual characteristics and the functionalities of IO models. The IO models have been widely used for diverse applications in waste management at economy-wide level, but there is potential for several other applications. Fourth, the main limitation of all models is data related: future efforts should include more effective monitoring and collection of physical IO data and waste data, as well as the development of methods for consistent data mining. • We reviewed 78 studies that applied an IO model for waste management analysis in a circular economy context. • We categorized IO models into: WEIO, WIO, PIO and HIO models and defined them within a waste management framework. • WIO models have the most mature analytical framework and are the most applied. • HIO models are conceptually the most powerful but are less widely applied than WIO models. • The development of effective monitoring and methods for consistent data mining of physical IO data and waste data is highly encouraged. [ABSTRACT FROM AUTHOR]