Level Of Final Demand Research Articles

Parsing India's mercury crisis: A socioeconomic take reveals the defining role of domestic consumerism

India is undergoing rapid industrialisation and globalisation, with a vast and growing population. Rising atmospheric mercury (Hg) emissions are one of the severe environmental crises the country faces as a result of this fast-paced development. India is the second largest emitter of Hg in the world. Here, we study the domestic and foreign socioeconomic drivers of India's Hg emission increases over time. We find that the growing domestic per capita final demand level is the most important driver of India's Hg emissions increase, having been responsible for 88% of the total increase of 125 tons (t) during 2004–2017. In contrast, India's changing Hg emission intensity and economic structure contributed to a cumulative decrease in emissions, albeit to a much lower extent (about 22 t). Given the importance of socioeconomic drivers, there is an urgent need to account for them in India's Hg emission mitigation efforts. The Minamata Convention on Mercury currently targets reduced manufacture, trade and use of Hg, and its reduced environmental releases among others. It must also begin to incorporate considerations of evolving socioeconomic drivers such as increasing consumerism and changing economic structures. Thereby it can inspire multi-faceted solutions to the global mercury pollution crisis.

Global economic structure transition boosts PM2.5-related human health impact in Belt and Road Initiative

The Belt and Road Initiative (BRI) is an open platform for international cooperation proposed by China to promote common global development and prosperity. The BRI can promote the optimal allocation of resources and promote in-depth cooperation in international trade. Meanwhile, it can establish a green supply chain cooperation network to help BRI countries achieve green transformation. BRI has made a notable contribution to the rapid growth of cross-border trade. However, it has also brought environmental impacts. Given that little attention has been paid to the trade-embodied particulate matter 2.5 related human health impacts (PM2.5-HHI) throughout the BRI, this study accounts for and traces the embodied PM2.5-HHI flows between the BRI countries and non-Belt and Road Initiative (non-BRI) countries. Moreover, this study also uncovers the critical socioeconomic drivers of PM2.5-HHI changes in BRI countries during 1990–2015, based on the multi-regional input-output based structural decomposition analysis (MRIO-SDA). Results show that, firstly, BRI countries had significantly increased their economic added value by exporting products to the non-BRI countries. They also have brought PM2.5-HHI to themselves. Secondly, the final demand of BRI countries was the largest potential driving force of PM2.5-HHI of BRI countries. Thirdly, the emission intensity change of BRI is the key socioeconomic factor for reducing PM2.5-HHI. While per capita final demand level change of BRI and production structure change of non-BRI are the key socioeconomic factors for increasing PM2.5-HHI. The study's findings on the one hand can help reduce the PM2.5-HHI and impacts of environmental pollution of BRI countries from a global perspective by providing scientific support. On the other hand, they can help provide relevant policy recommendations for the green transformation of BRI and the construction of green BRI.

A multidimensional factorial enviro-economic model: Approaches of retrospective decomposition and prospective projection for energy systems

Understanding the patterns of energy usage through simulation and prediction from multiple perspectives is crucial for alleviating energy-environmental conflicts and achieving sustainable energy system development. Despite their importance, multidimensional interactions among the production, demand, and supply sides have not been systematically characterized, thus representing a significant research gap. This paper aims to address this gap by developing a a multidimensional factorial enviro-economic (MFEE) model, which offers an in-depth investigation of Guangdong's energy system. This model, designed for retrospective decomposition (1997–2017) and prospective projections (2035), uniquely links historical and future analysis from systematic and sectoral perspectives through structural decomposition analysis, sectoral evolution analysis, and the Biproportional Scaling RAS method. Our findings reveal that the final demand level and Research & development (R & D) are the principal drivers of increased energy usage. We also found that the wholesale and retail sector have the most significant impact on demand and input sides, accounting for over 70 %. Furthermore, the interaction of key sectors from the production-based perspective notably influences system symbiosis. To effectively manage these dynamics, our study recommends regulating and controlling measures for the circulation sector that consider the benefits of both the energy sector and the accommodation and catering sector. This comprehensive analysis, therefore, offers scientifically-supported guidance for sustainable energy system development.

The effect of social economy-water resources-water environment coupling system on water consumption and pollution emission based on input-output analysis in Changchun city, China

With the rapid development of social economy, water resources consumed excessively and water pollution emissions increased. However, few studies have considered the feedback of water resources and water environment on social economy. In this study, a social economy-water resources-water environment coupling system was constructed by multiple regression model and system dynamic model. Five scenarios were set to investigate the relationship among industrial restructuring, pollution treatment and water conservation in Changchun city, China. Based on input-output model, this study analyzed the effect of the coupling system on the economic efficiency of sectoral water consumption and pollution emission. The driving factors were identified and the contributions were quantified using structural decomposition analysis model. The results showed that pollution treatment and water conservation promoted economic development and increased Gross Domestic Product (GDP) by 36.76%. The comprehensive effect of industrial restructuring, pollution treatment and water conservation was better than single measures, which made the GDP increment (44.39%), Chemical Oxygen Demand (COD) reduction (34.11%), Ammonia Nitrogen (NH3–N) reduction (52.50%) and total water consumption increment (7.56%) largest. Meanwhile, the comprehensive effect improved the water consumption efficiency of agriculture and service industries, reduced indirect water consumption in industrial sectors, and improved the economic benefits of pollution emissions in all sectors. The industrial restructuring further increased the contribution of population to COD emissions and the contribution of emission intensity to NH3–N emissions. Under the condition of comprehensive effect, the final demand level was the main factor for the increase of COD and NH3–N, contributing 36998.80 t and 821.07 t, respectively. Therefore, the government should pay attention to saving water resources and protecting water environment while developing social economy. The study quantified the coupling relationship between social economy, water resources and water environment, and provided guidance for water resources management in sectors.

The medium-high and high technological intensity sectors in Mexico and Brazil: a structural decomposition analysis between 2000-2014

We develop a structural decomposition analysis (SDA) to identify the importance of mid-high and high technological intensity (MH&HT) manufacturing and services to the changes in gross output for Brazil and Mexico between 2000 and 2014. We break down the output changes in the composition and level of final demand, the production technique (technical coefficients), and the trade pattern (share of imports in the total supply of inputs and final goods). The results show that the MH&HT importance tends to be pro-cyclical in the two economies, increasing during periods of more remarkable economic growth (2000-2008 for Brazil and 2010-2014 for Mexico). This relation tends to be perceived for manufacturing and less so for services.

Contributors and drivers of Shanxi’s aggregate embodied carbon intensity (2002–2017) based on input–output and multiplicative structure decomposition analysis

Success stories of low carbon transition for energy enrichment areas in developing countries are scarce. Shanxi Province is a typical coal resource-based region with the highest carbon intensity in China. Determining the main contributors and drivers of high carbon intensities is a crucial issue for China to achieve carbon neutrality. This study constructed the environment extended input–output model and calculated Shanxi Province’s aggregate embodied carbon intensity (AECI) in 2002, 2007, 2012, and 2017. Then the contributors of AECI can be analyzed at the final demand level and sector level. A multiplicative structural decomposition analysis (SDA) was employed to investigate Shanxi’s AECI change drivers. The results show that outflow to other provinces replaced exports and became the primary contributor to AECI change after 2012. The four sectors, electricity, construction, mining, and metallurgy, contribute mostly to Shanxi’s AECI. The main driver of AECI change is gradually shifting from energy intensity to production structure and final demand factors. The framework and conclusion could be extended to the energy enrichment regions of developing countries to identify the critical action of low-carbon transition.

How will Chinese cities reduce their carbon emissions? Evidence from spatial differences.

Urban regions are the dominant carbon emitter in China. Although the role of urban regions is a crucial concern in peaking China's carbon emission in 2030 or earlier, there were little focus set to the driving factors among urban regions from spatial differences. To excavate more effective abatement strategies to China's cities, this paper improved the environmental Leontief and Ghosh input-output models and structural decomposition analysis to investigate the driving factors of the spatial differences in the CO2 emissions among four municipalities. The results released that the increasing enlarged spatial differences of CO2 emission were significant. In general, the spatial differences were dramatically influenced by the per capita final demand level from the demand perspective and the sectoral energy intensity from the supply perspective. In particular, the structural factors presented an increasingly critical role. Inspired by the results, the city level "common but distinct" policy implications were formulated.

Global Trends and Drivers in Consumption- and Income-Based Emissions of Polycyclic Aromatic Hydrocarbons.

Polycyclic aromatic hydrocarbons (PAHs) are a class of the most hazardous substances. As unavoidable byproducts of petrogenic and pyrogenic processes, their emissions are dominantly linked to various economic sectors. In international trade, not only final consumption but also primary input can transfer the emissions among regions. Therefore, a long-term impact assessment of the international trade on PAH global emissions based on the final consumption and primary input could significantly benefit worldwide PAH mitigation strategies. This study investigated the changes in consumption- and income-based PAH emissions and interregional flows of worldwide regions, using the latest available data from 1999 to 2014. Results show that in 2014, 16.8 and 10.1% of global PAH emissions were transferred by consumption and primary input through international trade. Meanwhile, the production-, consumption-, and income-based emissions in most regions were decreasing. Furthermore, from the consumption-based perspective, sub-Saharan Africa surpassed China and became the largest net exporter of consumption-based emissions. From the income-based perspective, the net income-based outflows of India and the rest of Asia increased significantly, indicating the income-based emission leakage in emerging markets. From the socioeconomic perspective, emission intensity dominated the global decline in PAH emissions. As the two main factors driving the increase in emissions, the primary input structure (41%) had a larger effect than the final demand level (28%) from 1999 to 2014. Therefore, global cooperation, through the mitigation strategies of reducing emission factors and improving international trade patterns, is posited as an efficient strategy to reduce PAH pollution and related health risks.

Analysis of the development and structural drivers of raw‐material use in Germany

AbstractIn orderto reduce the negative consequences of raw‐material extraction, it is necessary to accurately report raw‐material use and to understand its drivers in society. In this study, we conduct a multi‐regional environmentally extended input–output analysis of Germany's past raw‐material use. We then perform a two‐stage structural decomposition analysis (SDA) of the development of material use in order to identify the main drivers. Although input‐based indicators of Germany's raw‐material use, which also include the material footprint of exports, show slight upward trends between 1995 and 2011, consumption‐based indicators have remained relatively steady in that time frame. On the one hand, this suggests a relative decoupling of Germany's domestic consumption from material use. On the other hand, exports, which contribute significantly to Germany's value‐added creation, have driven up input‐based indicators. The first stage of the SDA reveals that the material intensity of raw‐material provision would have by itself decreased Germany's raw‐material consumption (RMC), whereas changes in the structure of the global economy and in Germany's final demand would have increased it. The second stage of the decomposition reveals that the positive contributions to Germany's RMC are in large part due to shifts toward internationally sourced intermediate and final goods and an overall increase in the level of final demand in Germany.

Dynamic Input–Output Analysis of a Carbon Emission System at the Aggregated and Disaggregated Levels: A Case Study in the Northeast Industrial District

Research on carbon emissions of complex interactive activities in urban agglomerations is one of the hotspots of global climate change research. A comprehensive analysis of the urban agglomeration system’s carbon emissions is essential to reveal strategies for reduction and support sustainable development. The objective of this research is to develop an integrated carbon emission network model to explore the impact of different energy types on the Northeast Industrial District (NID), China. Four representative energy groups are considered. Specifically, at the aggregated sector-level, this research quantified the relative contributions of socioeconomic factors to carbon emission changes using structural decomposition analysis and examined the system efficiency and redundancy through robustness analysis. At the disaggregated level, the research investigated carbon emissions of different sectors from production-based, consumption-based, and income-based viewpoints. Moreover, emissions from specific categories of final demand and primary input were quantified. It was found that the increase of final demand level will proceed to push up the carbon emissions of the NID. Changing the production structure contributes to reducing emissions. The carbon emissions system has a high redundancy and low efficiency, illustrating that there are many emission pathways within the system. In addition, the use of crude oil significantly increases system redundancy and inhibits system efficiency. However, the major limitation of the model is that the long-term changes of the system are not considered. Moreover, considering the actual policies, emission reduction simulations could be added in the future.

Socioeconomic drivers of water use in China during 2002–2017

Rapid socioeconomic transitions have significantly influenced water use in China. This study aims to evaluate the water use implications of the changes in China’s economic development patterns and urbanization process. We quantify the relative contributions of various socioeconomic factors to water use changes during 2002–2017, based on environmentally extended input-output analysis and structural decomposition analysis. The results show that China’s water use has increased by 58 billion m3 during 2002–2012, and then decreased by 13 billion m3 during 2012–2017. Water use efficiency gains and economic structural improvements effectively offset the increase in water use, which is driven by the rising final demand level and growing population. Slight changes in inter-sectoral transactions of water intensive sectors would lead to significant influences on the effects of production structure changes on water use changes. Thus, close attention should be paid to the changes in production structures of these sectors. In addition, the effects of the urbanization process are mainly reflected by the growing gaps between water uses caused by rural and urban households, as well as increased urbanization-related water use. This is notably driven by intensive investments in construction activities. Water conservation policies in China should specially focus on the optimization of production structure, such as improving the production efficiency of sectors with large consumption-based water use.

New patterns in China’s water footprint: Analysis of spatial and structural transitions from a regional perspective

Abstract China faces a major challenge to support the operation and development of an enormous economy with limited water resources. Decoding the way that the final demand influences water consumption patterns is helpful for understanding the discrepancy between water supply and demand. Especially in the current time, when China has experienced socioeconomic transition and its government has proposed a series of water conservation policies over the years, exploring the transition in the water consumption pattern is necessary for further water conservation in China. Meanwhile, there exist distinct economic levels and stages of development among provinces, making it necessary to develop more refined water management strategies in the various provinces. This study comprehensively investigates the trend, spatial distribution and structure of the water footprint in mainland China. Furthermore, it explores the effects of socioeconomic factors on transitions in water footprint patterns with the aid of multi-regional input–output analysis, structural decomposition analysis, and linear regression. The results show that the water footprints of almost all the provinces were decoupled from economic growth from 2007 to 2012. Several northern provinces dramatically increased their water footprints, further enlarging the difference between north and south. The north also showed a wider urban–rural gap in per capita water footprint than did the south. From the viewpoint of structural transitions, household consumption (as the primary contributor) remained stable while an obvious increase in the water footprint was induced by fixed capital formation, in which agriculture and strategic emerging manufacturing played important roles. From the perspective of driving forces, water intensity improvement and changes in the final demand structure saved water. However, these effects were counteracted by the change in the final demand level and the composition of the final products. By identifying China’s water footprint patterns and its transitions, our results clarify China’s strategic water demand pattern and provide refined insights for future water conservation.

Revealing dynamic impacts of socioeconomic factors on air pollution changes in Guangdong Province, China

The rapid development of cities leads to the frequent occurrence of air pollution incidents, which seriously hinders urban sustainability. This study develops a dynamic regional air pollution analysis (DRA) model to explore the mechanism of air pollutant emission changes. Specifically, the emissions differences among various sectors are distinguished by multi-angle accounting (MAA) method, and sectors' evolutionary trajectories are described by sector evolution analysis (SEA). Through combining emission deconstruction analysis (EDA) and structural decomposition analysis (SDA), key emission patterns and decisive socioeconomic factors are identified. The empirical results indicate that different sectors play different roles in the urban emission system and differentiated regulation policies should be formulated according to their characteristics. Changes of demand and supply patterns can result in the fluctuation in regional air pollutant emissions. Exports and worker's reward are the most significant contributors to air pollution on demand and supply sides, accounting for more than 54.3% and 44.0% of total emissions, respectively. The final demand level and the primary input level are the two biggest drivers of the emission increase, while emission intensity is the most crucial factor that offsets the emission growth. Also, there are significant differences in demand and supply structure. The contribution of primary input structure to emission reduction was more significant than that of final demand structure, which contributed 14.6% in 2015. The findings in this study will provide reliable information for developing more comprehensive and effective mitigation policies.

The Drivers of China’s Regional Carbon Emission Change—A Structural Decomposition Analysis from 1997 to 2007

Using three official multiregional input–output tables and carbon emission data, we decompose the change in carbon emission for eight regions of China between 1997 and 2007. We do so according to the following seven partial effects: (i) Changes in energy end-use structure, (ii) effect of energy intensity, (iii) the added value’s share of gross output, (iv) changes in sub-industry structure, (v) changes in the substitution of import for intermediate inputs, and changes in (vi) structure and (vii) level of final demand. We find energy intensity contributes most to CO2 abatement throughout China, while other factors vary widely across the different regions. We suggest that governments consider regional disparity and CO2 flows when formulating policies; structural change with an eye toward energy-savings and general efficiency improvements, like better insulated buildings, are among measures we deem effective.

Material footprint of a fast-industrializing region in China, Part 1: Exploring the materialization process of Liaoning Province

Liaoning Province is one of the most important industrial bases in China that is confronting the challenges of resource restriction during the rapid industrialization and urbanization process. To explore the materialization process on an economy, previous studies have focused on the Material Footprint (MF), a consumption-based indicator of resource use, at the national level, but few results are available at the subdivision level, especially in rapidly developing China. In this study, a Structural Decomposition Analysis (SDA) was conducted of the MF of Liaoning to understand the key drivers behind the consumption of raw materials. The results show that Liaoning’s MF more than tripled, with an average annual growth rate of 13.4%, rising from 534 Mt to 1880 Mt during 2002–2012. Among the four material categories, nonmetallic minerals dominated the MF by 55–77% and contributed 83.3% to the total increase. From a sectoral viewpoint, construction dominated the MF by 65–85% and accounted for 90.8% of growth. In addition, among the four categories of final demand, investment played a prominent role in the MF, which more than quadrupled from 414 Mt (77.5%) in 2002 to 1701 Mt (90.5%) in 2012. The SDA results show that per capita final demand level was the strongest contributor, and that production structure was another chief contributor. In contrast, the significant improvement in material intensity and final demand composition played an important role in dematerialization of Liaoning. Optimizing investment towards less material-intensive sectors and designing mandatory targets for non-energy resources should be given more importance.

CO2 emissions from the industrialization and urbanization processes in the manufacturing center Tianjin in China

Curbing the rapid CO2 emissions and reaching the emission peak before 2030 under socioeconomic transition is a great challenge facing China. Therefore, in–depth understanding of the impact of industrialization and urbanization processes on CO2 emissions is essential for the achievement of China's CO2 emission reduction targets. In this study, we apply an analysis framework based on input–output analysis and structural decomposition analysis to analyze the CO2 emissions cost of the industrialization and urbanization processes from 1997 to 2012, using the manufacturing center Tianjin as an example. The CO2 emissions of Tianjin tripled during the 15-year studied period. The industrialization process strongly increased CO2 emissions through the rapid growth of the final demand level, while energy intensity improvement played an important role in curbing the rapid emission growth from 1997 to 2012. With respect to specific industries, with a growing share in economic structure, construction was the largest source in the overall CO2 emissions structure. As the pillar industry, transport equipment and information technology (IT) machinery industry were the largest sources in net export-related CO2 emissions, and the IT machinery industry also contributed the most to CO2 emissions growth related to production structure changes. Growing importance of tertiary industry, services (including producer services and consumer services) led to CO2 emissions growth through the growing share in net export and final demand structure during the 2007–2012 period. Besides the influence of industrialization, the rapid urbanization process resulted in a 74.1% growth in household consumption-related CO2 emissions, and the gaps between rural and urban continued to increase. The high demand for city infrastructure and building construction originated from investment also caused a great CO2 emission growth (142.5 Mt, 86.6% CO2 emission growth in Tianjin caused by investment). These results also provide policy implications for curbing the CO2 emissions increase in Tianjin as well as in other cities.

Electricity footprint of China’s industrial sectors and its socioeconomic drivers

China has become the largest electricity consumer in the world. Existing studies focus on the direct electricity use of industrial sectors and investigate the factors that influence direct electricity consumption. However, the critical sectors that play important roles as final consumers or primary suppliers and indirectly drive up the electricity use of upstream or downstream sectors are not identified. This study comprehensively quantifies the electricity footprint of the industrial sectors using consumption-based and income-based accounting methods The key drivers of changes in the consumption-based and income-based electricity footprints are also investigated using structural decomposition analysis (SDA). The results show that the accounting of the electricity footprint using consumption-based and income-based methods is quite different from that of the production-based method (i.e., direct electricity use). Moreover, the change in the energy structure (i.e., the percentage share of electricity in total energy consumption, also known as electrification level) of industrial sectors is a major driver of the increment in electricity use in addition to the final demand level and primary input level change. Improvement in the energy efficiency of sectors is the dominant factor that reduces electricity use. However, changes in the production input/output structure, final demand structure, and primary input structure are not found to have significant effects on reducing electricity use. This indicates that the role of structure change should be explored further. China can implement policies that further stimulate structural transformation, such as encouraging the consumption of less energy-intensive products and promoting primary inputs and production allocation to less energy-intensive sectors.

Understanding Water Consumption and Demand in China

The impact factors of the water consumption changes from 1999 to 2002 and from 2002 to 2007 in China are studied with structural decomposition analysis(SDA) model.Firstly, we combine the classical IPAT model with consumer endogenous input-output local closed model, then decompose the impact factors of water consumption changes with the combined model.Secondly, we analyze the direct effect of final demand on water consumption changes. The main results are as follows: (1) At the structural level, the increase of the GDP per capita is the main factor of water consumption increase, the decrease of water use intensity is the main factor of water consumption decrease.(2)At the final demand level, the total final demand change is the main factor of water consumption change, whose effect exceeds water use intensity decrease and the change of technical level. Among the components of final demand, investment is the main factor of water consumption growth, which exceeds the effects of government consumption and net exports.

Exploring China’s Materialization Process with Economic Transition: Analysis of Raw Material Consumption and Its Socioeconomic Drivers

China's rapidly growing economy is accelerating its materialization process and thereby creating serious environmental problems at both local and global levels. Understanding the key drivers behind China's mass consumption of raw materials is thus crucial for developing sustainable resource management and providing valuable insights into how other emerging economies may be aiming to accomplish a low resource-dependent future. Our results show that China's raw material consumption (RMC) rose dramatically from 11.9 billion tons in 1997 to 20.4 billion tons in 2007, at an average annual growth rate at 5.5%. In particular, nonferrous metal minerals and iron ores increased at the highest rate, while nonmetallic minerals showed the greatest proportion (over 60%). We find that China's accelerating materialization process is closely related to its levels of urbanization and industrialization, notably demand for raw materials in the construction, services, and heavy manufacturing sectors. The growing domestic final demand level is the strongest contributor of China's growth in RMC, whereas changes in final demand composition are the largest contributors to reducing it. However, the expected offsetting effect from changes in production pattern and production-related technology level, which should be the focus of future dematerialization in China, could not be found.

Analyzing the driving forces behind CO2 emissions and reduction strategies for energy-intensive sectors in Taiwan, 1996–2006

Between 1996 and 2006, CO2 emissions in Taiwan increased by approximately 60%, with the industrial sector accounting for 50% of that increase. Among all industrial sectors, iron and steel, petrochemicals, electronics, textiles, pulp and paper and cement accounted for approximately three-quarters of the total industrial CO2 emissions. Identifying the driving forces behind increased CO2 emissions in these six sectors could be valuable for the development of effective environmental policy. This study used two-tier KLEM input–output structural decomposition analysis (I-O SDA) to analyze the factors that lead to changes in CO2 emissions. Empirical results obtained in Taiwan reveal that increased exports level and elevated domestic autonomous final demand level were the main reasons for increases in CO2 emissions. Technological changes in materials and labor tended to decrease CO2 emissions, while the power generation mix contributed significantly to the increase. Relevant strategies for reducing CO2 emissions from energy-intensive sectors are also highlighted.