Multi-regional Input-output Model Research Articles

Analysis of the relationship between water and energy in China based on a multi-regional input-output method

The shortage of water and energy are hindering the rapid development of the regional economy in recent years. Therefore, exploring the synergy of water and energy and managing the two resources comprehensively is conducive to the sustainable development of the economy. Based on the multi-regional input-output (MRIO) model, this study proposed a new assessment framework for investigating the water-energy (WE) relationship. We used this novel framework to identify the relationships in different sectors. The achieved results are as follows. First, water and energy are closely related in many sectors, including agriculture, extractive sector, petroleum, coking, and nuclear fuel processing sector, and other sectors. However, the construction sector, textile and clothing sector, and wood processing and furniture manufacturing sector showed low correlation (p > 0.05). Second, on the whole, the WE relationship has been improving. Among the eight regions, the relationship varies greatly, and the Southern coastal region has the best relationship (r = 0.78). Third, the spatial distribution of water and energy footprints shows high agreement. Although the virtual water and energy flows alleviated the energy pressure in Coastal areas, it has aggravated the water and energy shortages in Central areas. Therefore, identification of key sectors and construction of suitable policies may help alleviate the contradiction between water and energy shortages and drive regional economic development.

Embodied Carbon Emissions and Regional Transfer Characteristics—Evidence from China

China has a considerable impact on climate change, as it is the world’s largest developing country. Its carbon emissions are also a global concern. This research employed a multi-region input–output model to estimate the local emission effect and the regional spillover effect caused by the demand for intermediate and final products, to analyze the interregional flow of carbon emissions, and to identify the main industries causing domestic carbon emissions in China from 2007 to 2012. A structural path analysis model was used to evaluate the contribution of different factors and demand types to changes in carbon emissions. The following findings were obtained in this study: (1) The regional spillover effect of carbon emissions driven by domestic demand is characterized by inland provinces’ demand leading to emissions in coastal provinces. (2) Electricity, nonmetallic minerals, and metals are the key industries for carbon emissions. (3) The results of the SDA indicate that the scale effect is the main driving force for the growth in carbon emissions caused by domestic demand in China. Fixed capital formation is the most critical demand factor influencing carbon emissions. This study provides new insights into the characteristics of regional emission transfer in China. The conclusion of this paper is helpful to China in achieving carbon peak and carbon neutrality.

Economic environmental imbalance in China — Inter-city air pollutant emission linkage in Beijing–Tianjin–Hebei (BTH) urban agglomeration

Production fragmentation makes the air pollution policy no longer at the local scale but requires accounting more about embodied emissions cross-region through supply chains. Here, we map the consumption-driven NOx networks of Beijing-Tianjin-Hebei urban agglomeration (BTH) in China using the city-level multi-regional input-output model. The results show that the construction, service, and equipment manufacturing sectors in Beijing and Tianjin indirectly drive more than half of BTH NOx emissions (54%). Moreover, 75% of NOx flows in the supply chains are traded from cities with low efficiency (high intensity) to cities with high efficiency (low intensity), which reflects the economic environmental imbalance in BTH. Especially, for the metals smelting and pressing sector and nonmetal mineral products sector, there is a wider gap in emission intensity between production-oriented cities (1.03–4.43 Mt/million yuan) and consumer-oriented cities (0.08–0.45 Mt/million yuan), which leads to additional emissions of air pollutants to increase. At the same time, for the provinces in the south and north China, the role of BTH in the supply chain is different, which leads to an economic environmental imbalance between the north and the south. Synchronous outsourcing of production and technology is the key to solving the economic environmental imbalance. The consumption-oriented high-income cities are suggested to increase the financial and technical support to improve the efficiency of pollution control in production-oriented cities.

How does global transport sector improve the emissions reduction performance? A demand-side analysis

Transport sector is one of the main global carbon emitters. Its production-side aggregated carbon intensity (i.e., the ratio of carbon emissions to GDP, AI) has been well explored, but its demand-side aggregated embodied carbon intensity (i.e., the ratio of embodied emissions to embodied value added, AEI) is always ignored, which is not conducive to improving its demand-side emissions reduction performance. Thus, using the latest world input–output table from EXIOBASE, this paper adopts the environmentally extended multi-regional input–output model and the structural path analysis model to investigate this issue from the views of globe, region, transmission layer, and final demand structure, respectively. The results indicate that: first, the AEI and AI of global transport sector contribute to global AI with 4.2% and 6.7%, respectively. The AI of global transport sector is chiefly contributed by water transport and air transport, followed by land transport, while its AEI is mainly contributed by land transport, followed by water transport and air transport. Second, transport sector highly contributing to regional AEI are mostly from the developed regions in Europe. Land transport, water transport, and air transport highly contributing to the AEI of regional transport sector are generally from the regions with low AEI of transport sector, the coastal regions, and the developed regions in Europe, respectively. Finally, the critical transmission layers of the AEI of regional transport sector have great differences in various regions, but their critical final demands are similar.

Inequality in urban and rural household CO2 emissions of China between income groups and across consumption categories

There exist large differences in household CO2 emissions (HCEs) between income groups in China, and the magnitude of difference varies significantly by consumption categories and provinces. Current studies have estimated China's interregional carbon inequality, however, details of carbon inequality between income groups and across consumption categories as well as the future view are still limited. This paper uses the environmentally extended multi-regional input-output (MRIO) model linking with the household consumption survey data to calculate the HCEs, that is, the emissions embodied in goods and services across urban and rural income groups of China's 30 provinces in 2017. Carbon inequalities of HCEs are measured by Gini coefficient and the related drivers are obtained by decomposition analysis. For assessing the carbon inequality in 2030 and 2050, this paper analyzes the income elasticity of demand for various consumption categories. The results indicated that in 2017, the top 10% of the population induced 24.7% of the HCEs, while the bottom 46% of the population were responsible for 24.6% emissions. The overall carbon inequalities of China (i.e., 0.32 in 2017 and 0.41 in 2050), urban China (i.e., 0.31 in 2017 and 0.35 in 2050) and rural China (i.e., 0.27 in 2017 and 0.34 in 2050) increase until 2050 with the demand-side growth, which can be attributed to the effect of household expenditure. More in depth, the income elasticities of demand for carbon-intensive goods, such as housing, others and transport, are larger in affluent groups, which will result in higher expenditure by rich people on carbon-intensive goods with income increase so as to widening gaps of HCEs between poor and rich individuals.

Uncovering the patterns and driving forces of virtual forestland flows in China

Nowadays, virtual land use related to consumption and trade flows has become an important part of land use. However, there has been little discussion about virtual forestland use. Therefore, this study performs the multi-regional input-output model on virtual forestland use and its changes in thirty provinces in China. And the influencing factors behind the dynamics of virtual forestland have been explored through the structural decomposition analysis. The results show that the area of virtual forestland embodied in trade was 673,277 km2 and 566,791 km2 in 2007 and 2012, equivalent to 32.14% and 27.03% of the total forestland area in China, respectively. There was north to east coast virtual forestland trade mode in China. The developed provinces or cities in China such as Shanghai, Beijing, Tianjin and Guangdong have a disproportionate share of virtual forestland imports (over 90%) from least developed provinces and forest-rich provinces. In addition, 11.06% and 7.47% of China's total forestland in 2007 and 2012 was used to supply consumption of foreign countries and regions. In addition, forestland use intensity and consumption volume were the main reasons for the dynamic changes of virtual forestland in most provinces. Through the exploration of the virtual forestland flow pattern helps to develop forestland conservation and restoration policies from the consumer side and achieve sustainable development of China's forest land.

The spatial characteristics of embodied carbon emission flow in Chinese provinces: a network-based perspective.

Combining the multi-regional input-output model with complex network technology, based on the provincial scale, this paper systematically describes the characteristics of the spatial network flow and its changing track of embodied carbon emissions among provinces in China from three dimensions of network structure, flow distribution characteristics, and spatial flow characteristics. Furthermore, the maximum spanning tree method is used to identify the spatial flow path of embodied carbon emissions between provinces and to distinguish the hierarchical status and roles of different provinces on the path. The research results show that the embodied carbon emission flow network among provinces has obvious small-world characteristics during the study, and the roles of different provinces in the network have significant heterogeneity. In general, Hebei and Inner Mongolia mainly act the role of suppliers of embodied carbon emissions, Guangdong and Zhejiang mainly act the role of consumers of embodied carbon emissions, while Zhejiang and Jiangsu mainly act as the media in the network. The spatial distribution characteristics of embodied carbon emission flow have a significant long tail effect; about 6% of the embodied carbon emission flow relationship among provinces accounts for 30% of that on the country level. The spatial flow direction of embodied carbon emissions was mainly concentrated in north China, central China, and southeast coastal region in the early stage and gradually shifted to inter-regional flows, presenting a divergent state of multiple regions and multiple centers. According to the flow path identification, it is found that Jiangsu, Guangdong, Hebei, Zhejiang, and other provinces are the key nodes on the spatial flow path of embodied carbon emissions in China, and the local center in a space is prominent. Based on the analysis and conclusions, the paper finally puts forward the corresponding countermeasures and suggestions in carbon reduction.

Carbon emissions from China’s outward foreign direct investment: Measurement based on multi-regional input-output model

Carbon emissions from China’s outward foreign direct investment: Measurement based on multi-regional input-output model

Carbon and Energy Footprint Analysis of Hungarian Transportation Activities Using a Multi-Region Input-Output Model

Carbon and Energy Footprint Analysis of Hungarian Transportation Activities Using a Multi-Region Input-Output Model

A procurement tool for streamlined Input-Output sustainability Assessment

Data collection for supply chain sustainability analysis is a difficult and time-intensive task. We have therefore developed an application-oriented tool for streamlining sustainability analysis in the supply chain. We take monetary purchase data as starting point and feed them into an environmentally extended multi-regional input-output model, based on WIOD, EORA and Exiobase, complemented by numerous other satellite accounts based on official statistics, e.g., by ILOSTAT, Eurostat or the OECD. The tool is able to differentiate by upstream tier and to allocate impacts to the countries and sectors where they arise. Thereby, we take 188 countries and 56 sectors into account. The tool can display different scenarios (e.g., years or suppliers) and present results in charts and maps, allowing to quickly identify hotspots in the supply chain. Out of the 152 indicators, 62 measure impact in monetized values and 90 measure output in physical values. We consider economic (e.g., contribution to the gross domestic product or job creation), environmental (e.g., greenhouse gas emission, waste, water consumption and pollution), and social (e.g., child labour or living wages) aspects. This results in both, footprints with negative effects and handprints with positive effects (e.g., employee training or job creation).

Quantifying the water-energy-food nexus in Guangdong, Hong Kong, and Macao regions

Water, energy, and food are indispensable resources for regional social and economic development. The cross-regional resource transfer can increase the complexity in the coordinated management of water, energy, and food in Guangdong, Hong Kong, and Macao regions. This study proposed a footprint accounting framework for cross-regional water, energy, and food nexus, which incorporates direct flows within territory and nexus flows embodied in final consumption. An environmentally extended multi-regional input-output model was established to quantify water, energy, food, water-related energy, food-related energy, energy-related water, and food-related water footprints in Guangdong, Hong Kong, and Macao regions. The results indicated that direct energy footprint was 5.3 times of food-related and water-related energy footprints, and energy-related and food-related water footprints were 3.8 times of direct water footprint. Inter-regional trade plays an important role in the management of the water, energy, and food nexus in three regions. Hong Kong and Macao outsource huge water, energy, and food nexus footprints by importing freshwater, electricity, and food from Guangdong to satisfy local demand. The proposed footprint framework could serve as indicators or tools for measuring sustainable development goals, and the results could provide the basis for the coordinated resources management of Guangdong, Hong Kong, and Macao regions.

A Multiregional Input–Output Hydro-Economic Modeling Framework: An Application to the Ebro River Basin

Sustainable water management is challenging because of the wide range of agents who need water and the different kinds of use, in a context of limited water availability. The availability of water for use, at a given point in time and space, depends on numerous physical and climatic variables, as well as upstream uses and downstream commitments. Therefore, any analysis of water use and management must inevitably be made in the context of such variability. This paper develops an integrated, multiregional, hydro-economic modeling framework to analyze the spatial and temporal dependencies between economic agents in the different regions and areas of a river basin. We combine hydro-economic modeling (partial economic equilibrium) and a multiregional input–output model (general equilibrium) to take advantage of both methodologies. Spatial variability is considered in the input–output models, but variability in both time and space is also considered by the hydro-economic model. Hydro-economic models are used to quantify direct impacts, but not indirect impacts in some specific sectors of the economy, while the input–output model reveals the relationships between all sectors and regions, and facilitates the assessment of total impacts (direct plus indirect) of a range of scenarios. While the methodology described in this paper is applicable to any river basin, the case study considered is the Ebro River Basin, in Spain. To show the potential of the modeling framework, two scenarios are simulated to assess the impacts on water use, value added, and jobs across scales. The results of these scenarios show that decreases in water availability have negative impacts on socio-economic variables (value added and employment). The trade-off between water availability and socio-economic variables depends on the temporal and spatial variability of the resource, and affects each location in the basin in a different way, demonstrating the importance of the methodology developed.

Germany’s Agricultural Land Footprint and the Impact of Import Pattern Allocation

Footprints are powerful indicators for evaluating the impacts of a country’s bioeconomy on environmental goods, both domestic and abroad. We apply a hybrid approach combining a multi-regional input-output model and land use modelling to compute the agricultural land footprint (aLF). Furthermore, we added information on land-use change to the analysis and allocated land conversion to specific commodities. Using Germany as a case study, we show that the aLF abroad is 2.5 to 3 times larger compared to impacts within the country. When allocating land conversion of natural and semi-natural land-cover types in 2005 and 2010 to import increases by Germany, conversion rates were found to be 2.5 times higher than for the global average. Import increases to Germany slowed down in 2015 and 2020, reducing land conversion attributed to the German bioeconomy as well. Our results indicate that looking at a static import pattern is not sufficient to draw a realistic picture of the land footprint of a country. For a more detailed assessment that also considers temporal dynamics and impacts of biomass use and trade, our newly developed set of indicators also captures changes of import patterns over time. The case study shows that our enhanced land footprint provides clear and meaningful information for policymakers and other stakeholders.

Assessing dependence and governance as value chain risks: Natural Gas versus Concentrated Solar power plants in Mexico

Despite geopolitics play a pivotal role in the energy sector, geopolitical aspects are often not considered in the quantitative assessment models aimed at supporting the energy investment decision-making process. To address this issue, this work proposes an Extended Multi-regional Input-Output model (EMRIO) that incorporates import dependence and governance along the value chain. As case study, two alternative energy investments in Mexico – a Natural Gas Power plant (NG) and a Concentrated Solar Power plant (CSP) – are assessed. The method quantifies the geographical diversification of suppliers and the quality of governance. The assessment of the case study shows that the supply chain of the CSP plant includes more countries and with better governance levels than the supply chain of the NG power plant. That means, a priori, that the supply risks of investing in CSP power plants will be lower, as will suppliers' endogenous geopolitical risk. However, a sensitivity analysis considering different providers of the solar plant components reveals that CSP plant value chain could also entail similar or even higher governance risks levels as the NG plant. The scenario where China provides some of the components entails a much higher governance risks, even higher than the NG base case. In consequence, we have proved that the method proposed allows the identification of hidden geopolitical risks that would otherwise go unnoticed. This paper enlarges the existing knowledge on assessment methodologies for energy policy decision-support by measuring diversification and imports dependence from countries with different levels of governance along the whole value chain.

Disparities in driving forces behind energy-related black carbon emission changes across China's provinces

Black carbon (BC) is one of the most important factors affecting the uncertainty of global climate change, as well as affecting human health by absorbing harmful substances in the environment. Understanding how human activities drive BC emissions can help formulate effective emission reduction policies. However, regional differences in social and economic activities determine the factors driving BC emission change in different regions/provinces, leading to the non-applicability of national-level emission reduction policies among the provinces. Therefore, it is necessary to develop a provincial-level analysis to shape refined policies for BC emission reduction. Here, we subdivided China's total BC emissions into 30 provinces based on previous work and used the multi-regional input-output model and complete average decomposition analysis to explore how BC emission intensity, intermediate inputs structural adjustment, local final demand, inter-provincial trade, and international exports drive BC emissions during 2007–2017. The results showed that BC emission intensity was an important emission reduction factor for all provinces in China. As for the effect of intermediate inputs structural adjustment, it had a negative effect during 2007–2012. However, during 2012–2017, as the tertiary industry had become the biggest factor in promoting economic development, the impact of the intermediate input structure on BC emissions had become a positive contribution, which showed that current industrial structure adjustment was not conducive to BC emissions reduction. Local final demand, inter-provincial trade, and international exports were the main factors causing the increase in BC emissions in each province as well. Southwestern regions and heavy industrial provinces emitted additional high BC emissions due to the huge final demand in the Eastern coastal regions. More targeted policies can be formulated by determining BC emission reduction responsibilities based on their driving factors at the provincial and sectoral levels and the development of emission reduction measures for each province.

Impacts of harmful algal blooms on marine aquaculture in a low-carbon future

The IPCC Special Report on Global Warming of 1.5 °C highlights the potential for dietary shifts to reduce greenhouse gas emissions from livestock. Reductions in the consumption of terrestrial animal protein require increases in the consumption of other food categories, to maintain food security, balanced dietary patterns, and protein intake. Aquaculture has long been suggested as one way to meet future food security needs, and marine and estuarine aquaculture in particular is associated with comparatively low greenhouse gas emissions. However, marine and freshwater aquaculture is affected by factors including harmful algal blooms (HABs), which have been increasingly documented around the world, correlated to increases in worldwide aquaculture. In this study, we applied a global multi-region input-output model to capture the direct effects as well as the indirect and induced effects HABs might pose to a global dietary transition from terrestrial livestock to increased seafood consumption from marine and estuarine aquaculture sources. We found that marine and estuarine aquaculture has a substantial potential to replace meat consumption from terrestrial livestock sources, as increases in CO2 emissions from aquaculture were more than offset by reductions in emissions from mainly cattle grazing and associated land clearing. HABs were found to have a minor monetary impact, but the impact on protein supply was found to be potentially sizeable. For example, in a future setting where 40% of terrestrial protein sources were replaced by aquaculture, a HAB-caused global loss of 5% would set in motion numerous supply-chain cascades, affecting industries auxiliary to aquaculture, indirectly and ultimately reducing protein intake by 10–20%. Such reductions have the potential for pushing parts of Sub-Saharan populations into protein-energy malnutrition. Nevertheless, there remains a significant potential for a dietary transition to increased aquaculture seafood to contribute to reductions in GHG.

A Study on Drivers of Water Consumption in China From a Complex Network Perspective

Water consumption has been one of the most important topics in the field of environment and economy. Even though the driving factors of water consumption have been well studied, it is still a daunting task to reveal the influence of the status of provinces in the entire supply chain. By combining the multi-regional input-output (MRIO) model and complex network theory, an inter-provincial virtual water transfer (V WT) network was constructed to analyze the overall structural characteristics of the network model and identify the structural roles of each province. The constructed inter-provincial V WT network exhibited the characteristics of a small-world network, that is, virtual water can be easily transferred from one province to another. Moreover, network analysis revealed that provinces with different positions in the V WT network played discrepant structural roles. Panel regression analysis was further used to quantify the impact of provincial structural roles on their water consumption. The results showed that water consumption in China largely depended on some structural role characteristics in the V WT network. Out-degree and out-strength characterizing the ability of direct exporting virtual water exerted significant positive influences, while in-closeness featuring the indirect virtual water importing rate had a significant negative effect on water usage. This indicated that adjusting the uneven provincial consumption structure, the direct production demand of downstream provinces and the indirect production activities in the supply chain would help reduce water consumption. Therefore, to come true the goal of water conservation in China, it would be necessary to improve the trade structure between direct and indirect exporters and importers in the entire supply chain.

Carbon spillover and feedback effects of the middle class in China

China's middle-class cultivation plan has been put on the agenda. The demographic transformation process is likely to be accompanied by environmental changes. Different income groups have their own characteristics, exerting different degrees of pressure on the environment. Based on a multiregional input-output model, we analyse the spillover-feedback mechanisms among eight regions with special emphasis on household consumption of the middle class in China. Our results show that the middle class, representing two-thirds of the total population, is responsible for 56% of the total carbon spillover, to which Central China and Southwest contributed the most. Central China and developed coastal areas imposed the most spillover while the Northwest bore the most spillover. To satisfy middle-class consumption, Central China is the largest carbon spillover flow net importer in domestic trade, while for the entire household, China's East Coast ranked first. Furthermore, interregional carbon spillover was mostly transferred through the electricity industry, petroleum, chemical and nonmetallic mineral products, metal products, and transport industries, supporting residents' demand for household appliances, living and transport services. Regarding the feedback effect, it is relatively minor. Therefore, we propose regional supply chain adjustment strategies and personal consumption behaviour recommendations in the context of middle-class cultivation in the eight regions of China.

A Multi-Region Input-Output Model for Optimizing Trade Under Footprint Constraints

Multi-region input-output models have been used extensively for describing and analysing the production and trade of goods. However, there have been no prior publications on the use of such models to determine optimal trade benchmarks considering footprint limits. Such benchmarks can provide valuable insights for economic planning, in the same manner that pinch analysis targets provide insights in process integration. In this work, a mixed-integer linear programming input-output model is developed to minimize environmental footprint by adjusting production and trade levels in a cluster of regions or countries with specified final demand constraints. A case study based on a simplified, low-resolution model of the Philippines using land footprint as objective function is solved to illustrate this new approach.

Unveiling Economic Co-Benefits of Virtual Water Trades: An Empirical Analysis on China’s JingJinJi Megalopolis

The development of metropolitan cities inevitably relies on natural resources beyond their boundary through trade of materials and products, particularly within the same urban agglomeration. Meanwhile trade facilitates the optimization of resource allocations under scarcity, among cities and sectors, and therefore generates economic gains. This study constructs an economic evaluation model combining a Multi-Regional Input-Output model and a Data Envelopment Analysis (DEA) to quantify the economic impacts of virtual water trades among the 13 cities in the JingJinJi region (China national capital area), one of the most water-scarce regions in China. We found that the total virtual water trade among the 13 cities amounted to 927 million m3 in 2012, among which agricultural sectors contributed 90% while the industrial sector and service sector together made up the remaining 10%. While Beijing and Tianjin are the main virtual water importers, importing respectively 300.48 and 226.92 million m3 in 2012, Shijiazhuang was the largest virtual water exporter, exporting 173.29 million m3 virtual water in the same year. Due to their more advanced economic conditions, Beijing and Tianjin also have the highest shadow prices of water, at respectively 912.21 and 831.86 CNY per m3, compared to a range of 79.31 to 263.03 CNY per m3 in cities in Hebei. Virtual water flows from cities in Hebei to Beijing and Tianjin thus generate economic gains. It is estimated that virtual water trades in the JingJinJi region have generated a net economic gain of 403.62 billion CNY in 2012, particularly owing to trades of agricultural products from Shijiazhuang to Beijing and Tianjin.