Global Multi-regional Input Output Research Articles

Enormous inter-country inequality of embodied carbon emissions and its driving forces in South America

South America is a crucial developing region under significant pressure to reduce emissions and achieve carbon neutrality. This study fills a vital gap by comprehensively analysing the continent’s carbon emissions from both production and consumption perspectives. Utilizing the most up-to-date global Multi-Regional Input-Output (MRIO) models, we examine the emissions embodied in the internal and external trade of nine major South American countries, tracing the emission flows from their origins to final consumers and analyzing the socio-economic drivers behind these patterns. Our analysis reveals that regions bearing heavier burdens of energy-intensive production often face exacerbated economic disparities. Trade-related emissions are embodied in heavy industry and transportation, and the share of emissions attributable to developing countries is continuously climbing. Brazil is the sole net-exporter of emissions, while Colombia has become a significant net importer. Energy intensity offsets the increase in carbon emissions caused by per capita consumption, especially in Brazil. Meanwhile, Colombia experiences an increase in emissions due to its energy structure, whereas a general trend towards decreasing emissions is noted elsewhere. The impact of the industrial chain is mainly domestic and extends forward along the supply chain. Interestingly, the consumption structure reduces emissions in Argentina and Bolivia, but increases them in other countries. Key emission mitigation initiatives include Brazil enhancing its leadership in bioenergy, Chile intensifying the development of green industrial chains for high-emission sectors, and Uruguay advancing its wind energy projects to increase clean energy exports, etc. These measures could facilitate targeted and effective decarbonization while promoting equitable and sustainable economic development across South America.

Spatio-temporal evolution and driving mechanism of metal value flow networks: A global value chain perspective

The lengthening of the global value chain (GVC) and the deepening of the transnational labor division system have led to frequent cross-border flows of metal values worldwide, and the pattern of the international metal trade is facing reconstruction. This paper combines a new trade accounting framework and a complex network model to construct global metal domestic value added (DVA) and foreign value added (FVA) flow networks based on global multi-regional input‒output (MRIO) tables for 2000 and 2007–2022 and then analyzes their structural topological features and spatio-temporal evolution trends at the macro, medium, and micro levels. Then, the main driving factors are investigated using the exponential random graph model (ERGM). The results show that the DVA and FVA networks are expanding and have obvious aggregation effects and small-world characteristics, that the community divisions show a trend toward regional integration and worldwide multipolarity, and that Germany is the most important transportation hub and trade medium in the FVA network, while China and the United States are, respectively, the largest creator and consumer of the world's metal value flow. In addition, the DVA network is more susceptible to node attribute effects such as GDP, trade openness, population size and foreign direct investment, while the FVA network is more susceptible to exogenous network effects such as geographic distance and colonial ties.

Estimating the uncertainty of the greenhouse gas emission accounts in global multi-regional input–output analysis

Abstract. Global multi-regional input–output (GMRIO) analysis is the standard tool to calculate consumption-based carbon accounts at the macro level. Recent inter-database comparisons have exposed discrepancies in GMRIO-based results, pinpointing greenhouse gas (GHG) emission accounts as the primary source of variation. A few studies have analysed the robustness of GHG emission accounts, using Monte Carlo simulations to understand how uncertainty from raw data propagates to the final GHG emission accounts. However, these studies often make simplistic assumptions about raw data uncertainty and ignore correlations between disaggregated variables. Here, we compile GHG emission accounts for the year 2015 according to the resolution of EXIOBASE V3, covering CO2, CH4 and N2O emissions. We propagate uncertainty from the raw data, i.e. the United Nations Framework Convention on Climate Change (UNFCCC) and EDGAR inventories, to the GHG emission accounts and then further to the GHG footprints. We address both limitations from previous studies. First, instead of making simplistic assumptions, we utilise authoritative raw data uncertainty estimates from the National Inventory Reports (NIRs) submitted to the UNFCCC and a recent study on uncertainty of the EDGAR emission inventory. Second, we account for inherent correlations due to data disaggregation by sampling from a Dirichlet distribution. Our results show a median coefficient of variation (CV) for GHG emission accounts at the country level of 4 % for CO2, 12 % for CH4 and 33 % for N2O. For CO2, smaller economies with significant international aviation or shipping sectors show CVs as high as 94 %, as seen in Malta. At the sector level, uncertainties are higher, with median CVs of 94 % for CO2, 100 % for CH4 and 113 % for N2O. Overall, uncertainty decreases when propagated from GHG emission accounts to GHG footprints, likely due to the cancelling-out effects caused by the distribution of emissions and their uncertainties across global supply chains. Our GHG emission accounts generally align with official EXIOBASE emission accounts and OECD data at the country level, though discrepancies at the sectoral level give cause for further examination. We provide our GHG emission accounts with associated uncertainties and correlations at https://doi.org/10.5281/zenodo.10041196 (Schulte et al., 2023) to complement the official EXIOBASE emission accounts for users interested in estimating the uncertainties of their results.

Carbon emissions embodied in investment: Assessing emissions reduction responsibility through multi-regional input-output analysis

Investment makes an outstanding contribution to the global economy while significantly impacting on global carbon emissions. However, few attempts have been made to analyze temporal changes in historical emissions induced by investment, and it is difficult to determine which countries are responsible for emissions reductions. Here we investigate the evolution in the carbon emissions embodied in investment (ECI) at global and national levels with the Global Multi-regional input-output (GMRIO) model, aiming to address the question of “Who should be responsible for how much, when it comes to emissions reductions?”. Our results show that global ECI increased by 72.4% from 1990 to 2021, with intermediate input structure being the key driver. Specifically, China, the United States and India had the highest ECI, and domestic investment level was responsible for promoting the growth of investment-related emissions. Improvements in emission intensity were the primary contributor to reductions. The construction, electrical and machinery, and transport equipment sectors were the leading sectors in shaping national investment-related emissions. To enable more effective reduction policies measures of ECI reduction, serious consideration should be given to technology cooperation and sharing.

Can factor substitution reduce the shadow price of air pollution embodied in international trade? A worldwide perspective.

The calculation of trade-embodied air pollution (TEAP) and its economic losses can be reasonably used to assess the impact of transboundary air pollution. However, these air pollutants, which are associated with international trade, can be easily ignored due to their concealment. Based on this, the global multiregional input‒output model (MRIO) is used to quantify the volume of five air pollutants that are embodied in the trade of 20 countries from 2000 to 2016. Then, the shadow price of trade-embodied air pollution (SPTEAP) and the elasticity of factor substitution (EFS) are both calculated by applying the translog production function. Finally, impulse response analysis is used to study the dynamic impact of EFS on the SPTEAP. The main conclusions are as follows: (1) All countries experienced a mass transfer of TEAP, among which China and the USA are the developing and developed countries with the largest amount of TEAP transfers, respectively. (2) The SPTEAP and EFS vary greatly among countries, and these values are generally higher in developed countries than in developing countries. The relationship between the three EFSs can be expressed as [Formula: see text] in all countries, thus indicating that improving the technological level of a country is the best solution for reducing the TEAP in that country while incurring the lowest cost and the least difficulty. (3) Over the long run, the increase in [Formula: see text] and [Formula: see text] reduces the SPTEAP. Conversely, an increase in [Formula: see text] increases the SPTEAP. Therefore, policymakers should weigh these three factors according to the fluctuation of the SPTEAP and constantly adjust the allocation structure and ratio of these factors to maximize the benefits of transboundary air pollution governance.

Optimal governance strategies for air pollution embodied in Sino-US trade: Evidence from a differential game model

The discussions between countries on trade inequality and ecological inequality have become increasingly heated, making cooperation on air pollution governance a priority. Based on the global multiregional input‒output (MRIO) model for calculating Sino-US trade-embodied air pollution (TEAP), an economic compensation mechanism is introduced into a differential game model. The main conclusions are as follows: (1) In bilateral Sino-US trade, the TEAP transferred from the United States to China is 6.85 times that transferred from China to the United States, showing serious ecological inequality. (2) The optimal TEAP emissions are influenced only by domestic factors in the noncooperative game, while they are jointly controlled by factors from both countries in the cooperative game. The optimal compensation coefficient is also influenced by factors from the two countries in the noncooperative game. In addition, the optimal TEAP stock and optimal investment stock are positively correlated with the initial stock under the two game scenarios. (3) Through numerical simulation, compared with the noncooperative game with economic compensation, the cooperative game without economic compensation can significantly reduce the optimal TEAP emissions and optimal TEAP stock; however, this reduction requires more governance investment. Consequently, China and the United States should comprehensively consider the advantages and disadvantages of the two governance strategies to maximize their overall economic benefits on the basis of basic fairness.

Identifying critical sectors in the restructuring of low-carbon global supply chains

Based on recent events in the world, global supply chain (GSC) restructuring has become an important issue for industries worldwide. To develop an effective CO2 reduction strategy through GSC restructuring, this study investigated the impacts of GSC restructuring in a specific sector on the industrial global carbon footprint. Through this process, this study developed a scenario-based hypothetical extraction method (HEM) into a practical and flexible framework with a focus on the reasonable scale of relevant GSC restructuring. As a case study, this study applied the practical HEM framework to a global multi-regional input output database in 2014 and estimated the impacts of restructuring major automotive GSCs on CO2 emissions. Based on the results, this study identified the Chinese electrical equipment sector and the Russian basic metals sector, both included in the automotive GSCs as key sectors (i.e., key suppliers) for low-carbon GSC restructuring. These sectors exhibited the largest CO2 reduction effects when targeted for relevant GSC restructuring. Additionally, this study highlighted the practical potential for CO2 reduction based on a reasonable scale of relevant GSC restructuring. Finally, based on the findings, this study discusses how policymakers should formulate trade policies that prioritize intermediate products to promote GSC restructuring toward low-carbon practices and proposes an effective approach to utilize the results as benchmarks for setting CO2 reduction targets or incentives in the context of GSC restructuring.

Use of nested multi-regional input–output analysis for the evaluation of subnational emission reduction policies: A case of Japanese prefectures

Many subnational regions around the world, in their own capacity for policy formulation and implementation, have set targets for net-zero carbon dioxide or greenhouse gas emissions. However, most targets do not consider consumption-based emissions, which include emissions generated outside their borders to produce the products they consume. It is partly due to methodological difficulties and data gaps that subnational governments often face but this situation could misguide their efforts in the face of the goal of reducing global emissions. To facilitate an understanding of consumption-based subnational carbon emissions and informed subnational policymaking, this study proposes a relatively simple and less data-intensive methodology for subnational consumption-based emission analysis. It uses a nested multi-regional input–output approach by combining a publicly available global multi-regional input–output table and a subnational input–output table, whose computation is repeated for multiple regions for comparison. A case study of three Japanese prefectures with different levels of renewable electricity consumption was conducted using the 2015 datasets. The results showed that two prefectures with similar socioeconomic conditions, except for their totally different renewable electricity ratios (90 % and 4.6 %), exhibited a 25 % difference (4.4- and 6.0-ton CO2) in per capita household consumption-based carbon dioxide emissions in 2015. Counterfactual policy scenarios were analyzed using the constructed models. Application of an increased renewable electricity scenario indicated that an approximate 10 % increase in the prefectural renewable electricity ratio could reduce household per capita consumption-based emissions by 151–179 kg CO2 in those prefectures. Consumption-based emissions disaggregated by product category indicated that increasing the renewable electricity ratio had significant consumption-based emission reduction effects on not only electricity itself but also on services, particularly commerce, hotel, and restaurant services. The potential impacts of changing renewable electricity ratios on consumption-based emissions were found to be high for products whose share in household spending on local products and electricity cost in their production was large. A scenario analysis of home electrification, assuming the total replacement of household fuel gases and kerosene with electricity, resulted in a modest consumption-based emission reduction potential of less than 10 % for a prefecture with a high renewable electricity ratio and even showed a slight emission increase for a prefecture with a low renewable electricity ratio. In using commonly available datasets without the need to model trade flows between subnational regions, this study's method could realistically be applied by subnational governments to estimate consumption-based emissions of their jurisdiction, compared with other regions, and analyze the potential effects of emission reduction policy scenarios.

Burden of the global energy price crisis on households

The Russia–Ukraine conflict has triggered an energy crisis that directly affected household energy costs for heating, cooling and mobility and indirectly pushed up the costs of other goods and services throughout global supply chains. Here we bridge a global multi-regional input–output database with detailed household-expenditure data to model the direct and indirect impacts of increased energy prices on 201 expenditure groups in 116 countries. On the basis of a set of energy price scenarios, we show that total energy costs of households would increase by 62.6–112.9%, contributing to a 2.7–4.8% increase in household expenditures. The energy cost burdens across household groups vary due to differences in supply chain structure, consumption patterns and energy needs. Under the cost-of-living pressures, an additional 78 million–141 million people will potentially be pushed into extreme poverty. Targeted energy assistance can help vulnerable households during this crisis. We emphasize support for increased costs of necessities, especially for food. The Russia–Ukraine war triggered an energy crisis that affected the cost of many goods and services. Guan et al. model the direct and indirect impacts of increased energy prices across expenditure groups and countries, finding temporary increases in total household energy costs of 63–113% under different scenarios.

Global Multi-Regional Input-Output methodology reveals lower energy footprint in an alternative community project

Identifying the energy needs of citizens and taking into account different lifestyles and patterns of consumption is a first step for a global transformation towards renewable, fair and democratic energy systems. Currently, Total Primary Energy Supply (TPES) is the most widely used metric of energy consumption, which only includes the energy consumed within a country. This research addresses an alternative indicator, Total Primary Energy Footprint (TPEF), which also includes the energy embedded in imported goods and services. The research is innovative in its pioneering combination of a Global Multi-Regional Input-Output (GMRIO) methodology with household budget surveys (HBS) and consumption to production sectorial bridge matrices to calculate TPEF at a small community level. Errekaleor, the largest off-grid alternative intentional community located in Basque Country, Spain, was taken as a case study. The results show, firstly, that alternative communal living can reduce energy consumption. In terms of the specific case study, even if direct residential energy consumption (4.46 MWh·cap −1 ·yr −1 ) was shown to be 32 % and 15 % higher in Errekaleor as compared with Basque and Spanish averages, a TPEF of 31.10 MWh·cap −1 ·yr −1 per capita was determined for the community, 24 % and 14 % below the regional and national averages. Secondly, the relevance of indirect energy embedded in acquired goods and services in determining consumption-based energy use was shown. This accounts for 80.7 % of total consumption in Spain, 74.9 % in the Basque Country, and 66.3 % in Errekaleor. Within Errekaleor, individual arrangements impacted significantly, as people living in families have 33.5 % smaller energy footprints (28.45 MWh·cap −1 ·yr −1 ) than individuals living alone (42.79 MWh·cap −1 ·yr −1 ), who have a TPEF above the Basque average. Thus, the combination of GMRIO and HBS in the analyzed bottom-up case study made an important contribution in terms of clarifying the existing debate about the relative energy efficiency of alternative communities.

On the Interpretation and Measurement of Technology-Adjusted Emissions Embodied in Trade

We propose a new method for standardizing the production technology at the world average level and derive interpretations for the resulting carbon emission concepts. The technology-adjusted emission balance measures net weak carbon leakage defined as the difference between the foreign emissions avoided by exports and the foreign emissions generated by imports. We use global multi-regional input–output tables to document the variable’s spatio-temporal variation for 49 economies between 1995 and 2015. There is a positive cross-country correlation between net leakage and per-capita income. Changes in net leakage are generally small and do not account for country-specific emission trends, that is, domestic emission decreases were not offset by foreign emission increases.

The Imbalance of Embodied CO2 in China’s Imports, Exports and Its Causes

Constraining the embodied CO2 from international trade is a crucial part of China’s efforts to achieve emission peak and carbon neutrality. By referring to the WIOD, this article applies the Global Multi-Regional Input-Output (GMRIO) Model and the Value-added Trade Accounting Method to calculate the amount of embodied CO2 in China’s international trade from 2000 to 2014. Results indicate that China’s embodied CO2 in imports and exports is imbalanced in three dimensions: product, region, and industry. One direct cause of this phenomenon is China’s higher carbon emission factors compared to its trading partner. However, the real cause is the global relocation of energy-intensive industries, which leads China to undertake the production of high-carbon industries. To achieve the 3060 Dual Carbon Goal and high-quality economic development, China needs comprehensive and systematic reforms in its economic structure.

An environmentally extended global multi-regional input-output analysis of consumption-based and embodied import-based carbon emissions of Turkey.

Understanding the consumption-based accounting (CBA), production-based accounting (PBA), and emissions embodied in trade is an important prerequisite for designing climate mitigation policies. Environmentally extended input–output (EEIO) models have been developed to evaluate the linkages between economic activities and environmental impacts as well as the embodied emissions in goods and services that are traded between countries. In this study, an environmentally extended global multi-regional input–output (EE GMRIO) analysis is performed to calculate Turkey’s CBA emissions and import-based embodied emissions for the year 2015 using the Eora26 database, which is a simplified version of the Eora database adapted to 26 economic sectors. The key sectors and sectoral carbon intensities of countries are determined in terms of embodied emissions in imports for household consumption. Our results indicate that Turkey was a net importer of greenhouse gas (GHG) emissions in 2015 and about 10% of total emissions of the final consumption in Turkey have occurred in other countries. The dominant contributing sectors to a nation’s GHG emissions can be quite different for the CBA and PBA approaches and the efforts to reduce GHG emissions requires a holistic approach. Import-based household emissions are assessed in terms of countries, sector and GHG intensities. Our results indicate that Turkey was a net importer of GHG emissions in 2015 with its approximately 10% of the total and 7.7% of household final consumption emissions having occurred in other countries. This also suggests that imported goods and services for household consumption have been produced in those countries with relatively low emission intensities. Considering Turkey’s emissions reduction targets, these results provide methodological benefits that will enhance national efforts by giving invaluable inputs about the emission intensity of imported and exported goods and better guidance to policy makers about future strategies for low-carbon manufacturing and shifting consumption patterns.

From globalization to regionalization? Assessing its potential environmental and economic effects

There are increasing warns of the withering of globalization but the rise of regionalization. In this paper, we provide a quantifiable definition for regionalization in a global multi-regional input–output framework and set different scenarios of regionalization to simulate their potential effects on the environment and economy. Our results show that the “North America-Europe-Asia” tripartite regionalization would reduce the CO2 emissions in Asia (China in particular) and Europe, but increase substantial emissions in North America, leading to a slight reduction in global CO2 emissions. However, it would cause large value-added losses for some developing countries such as China, India, and Vietnam but bring value-added gains for some developed countries, enlarging the economic gap between developing and developed nations. In terms of industries, the regionalization of technology-intensive supply chains would have larger effects than other industries. Moreover, we present the results for several different scenarios of partial regionalization, which we set for capturing some more realistic regionalization cases in the future world.

How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis

AbstractThis paper presents an integrated approach combining the optimization‐based frontier model with a global multiregional input–output (MRIO) analysis for food consumption in Europe. The weighted and conventional data envelopment analysis models are coupled with production and consumption‐based environmental and economic footprint data obtained from the environmental footprint explorer database. Eco‐efficiency assessment is carried out using multiple undesirable environmental outputs such as carbon emission, total energy consumption, land use, material use, water use, and one desirable economic output, which is the gross value‐added (GVA). This assessment indicates an efficiency level of each economic activity associated with its environmental impacts and policies are made as a result of the efficiency level to propose an equilibrium between economic development and environmental impacts. Finally, a sensitivity analysis of each parameter, variability analysis between weighted and non‐weighted models, and performance improvement projections are presented. Based on the results, four countries become efficient when moving from production‐based accounting (PBA) to consumption‐based accounting (CBA). France, United Kingdom, Italy, and Sweden are efficient countries in both findings. Denmark caused the highest carbon emission from the production point of view. Germany is the largest importer in all environmental categories such as carbon emission, energy usage, material use, land use, and water use. Additionally, the weight‐restricted model indicated a noticeable difference concerning the eco‐efficiency scores under the PBA and CBA approach, where land use and material footprint categories were found to be the most sensitive parameters for eco‐efficiency scores. The authors believe that this integrated approach will aid in decision‐making and help build a composite eco‐efficiency score when comparing the performance of food consumption with multiple environmental and economic metrics.

Impacts of poverty alleviation on household GHG footprints in China

Eradicating poverty and mitigating greenhouse gas (GHG) emissions are core issues of global sustainable development goals (SDGs), and China is struggling in realizing these targets. The poverty reduction that leads to popualtion structure and lifestyle changes would have an impact on GHG emission changes. However, few studies have assessed the historical and future impacts of the poverty allevation on China's emissions. Here by linking Chinese Multi-Regional Input Output (MRIO) database to the global MRIO database EXIOBASE, and using provincial household consumption data, we identified the distribution of Chinese household greenhouse gas footprints (HGFs) by income groups in 2015 at the national and provinical levels. Moreover, we focused on the historical impact of poverty alleviation on HGFs during 2010–2015, and developed four scenarios to project future HGFs changes due to poverty alleviation by 2030. We find that eradicating extreme poverty in the secanrio S2, i.e., bringing people to an income above $1.9 daily, does not cause a large emission impact with current technological level. However, lifting people from a higher poverty line of $5.5 per day in the sceanrio S4 results in a 1.6% increase in emissions compared with the scenario S1 without any poverty reduction goals. Furthermore, realizing a higher poverty reduction target will result in an increase of emissions contribution from internatioanl supply chains due to the differences in consumption patterns among different income groups. Our study highlights the conflict between the high poverty alleviaition goal and emission reduciton in China, and reminds us of the need to make more technological efforts for avoiding the large emissions embodied in international supply chains.

Visualizing the services embodied in global manufacturing exports

Nowadays, manufacturing products contain more service value, and this trend is reshaping the global merchandise trade network. Based on a global multi-regional input–output (GMRIO) model and network analysis, we calculate the value added of services embodied in global manufacturing exports and visualize their flows across economies and industries from 2005 to 2015. More specifically, we adapt the PageRank algorithm to select the crucial economies and present four types of networks – networks of the crucial (services) supplier economies and the major user economies for their manufacturing exports, in addition to networks of the crucial manufacturing exporter economies and the major (services) supplier economies for them – at both aggregate and sectoral levels. Our results suggest that at the aggregate level, though some developing economies, such as China, India, and Brazil, are playing an increasingly important role, developed economies still dominate the networks as major users and suppliers. At the industry level, wholesale and retail, other business sectors, and finance and insurance are often recognized as the major (services) suppliers, especially those industries in the United States, Germany, Japan, and France. By contrast, developing economies are more engaged in low value-added service industries, such as transportation and storage. Our findings highlight the importance of servitization in developing economies.

Mapping the environmental footprints of nations partnering the Belt and Road Initiative

Over the past few years, the Belt and Road Initiative (BRI) proposed by China has made a notable contribution to the rapid growth of cross-border trade. This however has been accompanied by unexpected burden shifting of resource extractions and environmental emissions to less developed countries. Given that little attention has been paid to the trade-embodied resources and emissions throughout the BRI, this paper, for the first time, accounts for the water, land, carbon, nitrogen and phosphorus footprints of 65 BRI nations and traces the flows embodied in international trade between the BRI and remaining 124 economies by employing a global multi-regional input–output model. Overall, distribution of the BRI's environmental footprints shows strong spatial heterogeneity, amongst China, India and Russia have the highest total environmental footprints. Furthermore, reverse patterns of spatial distribution can be observed between the total and per capita footprints of BRI nations. When it comes to the global scale, the BRI as a whole is found to be a net exporter of trade-embodied flows except for virtual water. Remarkably, 29% of the BRI nations experience a role transition in supply chains across scales, either from net exporters on the BRI level to net importers on the global level, or in reverse. Our findings provide a holistic picture of environmental footprints at scales ranging from single nations, regions, BRI, and even globe, highlighting the significance of a global view in finding ways to tackle environmental challenges and fulfill the Sustainable Development Goals throughout the BRI countries by 2030.

Discovery of a possible Well-being Turning Point within energy footprint accounts which may support the degrowth theory

The former consensus on a link between energy consumption and improved well-being of a country has been scrutinized by scholars for decades and is, succinctly, for the time being a contested thesis. Until the 1970s the relation of energy to well-being was defined as linearly proportional, and in a later period still as an increasing logarithmic function. Recent empirical research falsified the assumption of an overt link between well-being and increased energy consumption in countries with high per-capita energy usage.Going forward, our research shows for the first time a possible proof for a negative correlation between energy consumption and well-being after a Well-being Turning Point (WTP). We used a world data set, not limited to high-income countries but including 176 nations with available data sets. Our findings could support both the logarithmic growth of well-being together with energy, as well as the contradicting saturation theses supporting degrowth, and thus opens the discussion in all directions. In this paper Energy Footprint data within Eora database and Global Multi Regional Input Output methodology have been calculated, which includes also the energy embodied in imported/exported products and services (also known as consumption-based energy accounts). The use of footprint accounts has been demonstrated in our previous research to be necessary when analysing global energy consumption trends; as it records the energy consumption reality better than the usually used Total Primary Energy Supply which is provided by the International Energy Agency. In this paper, we provide in a novel way, some statistical support for an Energy WTP, i.e. a high-energy threshold after which a further consumption increase results in a reduced Human Development Index. We tested our results for possible biases (e.g. excluding outlier countries and including a factor for considering the weight of high population countries) and concluded that a WTP is one possible interpretation of the data. Thus, we would like to open a discussion about how energy consumption could end up having a negative effect on well-being, considering its indirect impacts in citizens of a country.

From sustainability assessment to sustainability management for policy development: The case for electric vehicles

In this research, a hybrid life cycle sustainability assessment and multi-objective decision making are jointly applied to highlight how sustainability assessment results can be used for sustainable management and further country-level policymaking, and Qatar is selected as a case study to implement the proposed method. 14 macro-level sustainability indicators are quantified for four different technologies of sport utility vehicles (SUV), including internal combustion vehicles (ICV), hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV), and battery electric vehicles (BEV), using a global multiregional input–output analysis to distinguish in between regional and global supply chain-related impacts. A compromise programming model is developed based on the sustainability assessment results to determine what should be the optimal distribution of alternative vehicles based on varying importance of different sustainability indicators and scope of the analysis. The optimal vehicle distributions are determined for two different battery charging scenarios, through the existing electricity grid and solar energy. Furthermore, the optimal distributions are also investigated when the scope of the analysis is limited to regional boundary versus the total impacts encompassing the global supply chains in addition to the regional impacts. When environmental indicators are assigned the top priority (100%), the results show that HEVs should compromise over 90% of the vehicle fleet. In a balanced weighting case, the optimal vehicle distribution consists of around 81% HEV and 19% BEV if charged through the electricity grid. The proposed method can provide important insights for developing policies to achieve sustainable and efficient policies considering various aspects including the scope of assessment and relative importance of quantified sustainability indicators.