Impact of global value chain embedding on decoupling between China's CO2 emissions and economic growth: Based on Tapio decoupling and structural decomposition.

With the increasing fragmentation of global production, China's participation in cross-border production sharing activities has had a considerable impact on the nation's economy and carbon dioxide (CO2) emissions. This study applied the Tapio model to quantitatively evaluate the decoupling between CO2 emissions and economic growth in China, dividing the decoupling index based on global value chains (GVCs) and domestic production within the IO framework, and introducing structural decomposition analysis (SDA) to analyze the GVC-related factors to the decoupling. The relevant research results are fourfold. (1) From 2000 to 2018, China achieved weak decoupling between emissions and economic growth. Domestic and GVC effects each had a negative impact on the decoupling; however, after 2008, the GVC effect had a promotional effect and the negative domestic effect declined. (2) Emission intensity was the primary factor promoting decoupling through domestic and GVC effects, while the scale of final demand was the main hindrance. And the negative effects of GVC-related factors declined following the economic crisis. (3) The regional and sectoral structures of GVC production (58.44 % and 56.08 %) had promotional roles in the changes in GVC effects, while GVC production linkages (-20.19 %) had hindering effects. Various factors contributed to the hindering effect from the 2008 to 2011 index, whereas from the 2011 to 2018 index, all factors contributed to the promotional effect. (4) From 2000 to 2018, the average annual global value chain effect promoted the low-carbon development of China's labor-intensive and knowledge-based manufacturing. In order for GVCs to play a positive role in decoupling, China should promote trade facilitation through international platforms, support the advancement of production technology, reasonably guide China's industries to participate in the regional and industrial links of GVCs, and develop strategic emerging industries.

Aging Population, Balanced Diet and China's Grain Demand.

The need to make more accurate grain demand (GD) forecasting has become a major topic in the current international grain security discussion. Our research aims to improve short-term GD prediction by establishing a multi-factor model that integrates the key factors: shifts in dietary structures, population size and age structure, urbanization, food waste, and the impact of COVID-19. These factors were not considered simultaneously in previous research. To illustrate the model, we projected China's annual GDP from 2022 to 2025. We calibrated key parameters such as conversion coefficients from animal foods to feed grain, standard person consumption ratios, and population size using the latest surveys and statistical data that were either out of date or missing in previous research. Results indicate that if the change in diets continued at the rate as observed during 2013-2019 (scenario 1), China's GD is projected to be 629.35 million tons in 2022 and 658.16 million tons in 2025. However, if diets shift to align with the recommendations in the Dietary Guideline for Chinese Residents 2022 (scenario 2), GD would be lower by 5.9-11.1% annually compared to scenario 1. A reduction in feed grain accounts for 68% of this change. Furthermore, for every 1 percentage point increase in the population adopting a balanced diet, GD would fall by 0.44-0.73 million tons annually during that period. Overlooking changes in the population age structure could lead to an overprediction of annual GDP by 3.8% from 2022 to 2025. With an aging population, China's GD would fall slightly, and adopting a balanced diet would not lead to an increase in GD but would have positive impacts on human health and the environment. Our sensitivity analysis indicated that reducing food waste, particularly cereal, livestock, and poultry waste, would have significant effects on reducing GD, offsetting the higher demand due to rising urbanization and higher incomes. These results underscore the significance of simultaneous consideration of multiple factors, particularly the dietary structure and demographic composition, resulting in a more accurate prediction of GD. Our findings should be useful for policymakers concerning grain security, health, and environmental protection.

An interprovincial input-output database distinguishing firm ownership in China from 1997 to 2017.

Input-Output (IO) data describing supply-demand relationships between buyers and sellers for goods and services within an economy have been used not only in economics but also in scientific, environmental, and interdisciplinary research. However, most conventional IO data are highly aggregated, resulting in challenges for researchers and practitioners who face complex issues in large countries such as China, where firms within the same IO sector may have significant differences in technologies across subnational regions and different ownerships. This paper is the first attempt to compile China's interprovincial IO (IPIO) tables with separate information for mainland China-, Hong Kong, Macau, Taiwan-, and foreign-owned firms inside each province/industry pair. To do this, we collect relevant Chinese economic census data, firm surveys, product level Custom trade statistics, and firm value-added tax invoices and consistently integrate them into a 42-sector, 31-province IO account covering 5 benchmark years between 1997-2017. This work provides a solid foundation for a diverse range of innovative IO-based research in which firm heterogeneity information about location and ownership matters.

Weighing China's embodied CO2 emissions and value added under global value chains: Trends, characteristics, and paths.

With the accelerated expansion of global value chains (GVCs), China occupies an increasingly important position in the global production division system, which has important impacts for its economy and environment. Comprehensively measuring the economic benefits and emissions costs of China's participation in GVCs, and striving to achieve a mutually beneficial state of GVC upgrade and low-carbon economic development, are critical issues for China. This study applies the accounting framework of value-added trade and embodied CO2 emission trade to measure the potential CO2 emissions cost of China's value-added gains through traditional trade, simple GVC, and complex GVC from 2000 to 2014. The findings are fourfold. (1) Compared with traditional trade, GVC-related activities require higher carbon emissions costs to obtain value added, which exacerbates China's economic-environmental imbalance. (2) Electricity, Metals, and Non-metallic mineral industries are the primary sectors of embodied CO2 emissions exports, and they bear heavy emissions pressure while obtaining limited value added. (3) China's embodied CO2 trade and value-added trade with developing countries through GVCs are rising, whereas the trade with developed countries reveals a downward trend. (4) The characteristics of China's industrial paths under different trade routes vary considerably. CO2 emissions in the industrial path of GVC-related activities are more hidden, and comprehensive management must be carried out throughout the entire industrial chain from production to consumption. This study proposes policy recommendations for the coordinated development of economic and environmental relations, such as reducing the carbon intensity of key industries, strengthening trade cooperation with emerging economies, and enhancing China's position in GVCs.

Exploring spatial characteristics of city-level CO2 emissions in China and their influencing factors from global and local perspectives.

In China, cities are the basic units for implementing CO2 abatement policies. However, few studies have comprehensively explored the spatial characteristics of CO2 emissions (CEs) and their influencing factors at the city level from different perspectives. After collecting spatial data from 280 Chinese prefecture-level cities for 2005, 2012, and 2015, this work firstly uncovered the overall and local spatial characteristics of CEs by adopting spatial autocorrelation analysis. Then, five influencing factors, including the total resident population (POP), per capita GDP (PCGDP), energy intensity (EI), the proportion of secondary industry (SI), and climate factor-heating degree days (HDD), were examined using global and local regression models. The analyses revealed that (1) CEs presented spatial agglomeration features from global and local perspectives, indicating spatial association between neighboring cities; and (2) POP, PCGDP, EI, and HDD had statistically significant spatial correlations with CEs, and their effect sizes were as follows: PCGDP > POP > EI > HDD. More importantly, the impacts of these influencing factors on CEs varied across cities, exhibiting obvious spatial heterogeneity. According to these findings, local governments should strengthen coordination and cooperation with their surrounding cities to promote regional synergistic action on emission reduction. In addition, policymakers should also design differentiated abatement policies based on regional characteristics and differences instead of applying similar policies to all cities.

Evolutionary path and driving forces of inter-industry transfer of CO2 emissions in China: Evidence from structural path and decomposition analysis.

Carbon dioxide (CO2) emissions are currently a hot topic of global concern. It is of great significance for reducing CO2 emissions to fully understand the transfer pattern of CO2 emissions among industries and the key factors affecting CO2 emissions. This paper uses the structural path analysis model to explore deeply the main paths of inter-industry transfer of CO2 emissions in China from 2002 to 2017 and applies the structural path decomposition model to analyze the main factors affecting CO2 emissions in specific paths from the perspectives of CO2 emission intensity, intermediate product input structure, final demand structure, per capita final demand, and population size. The results show that: (1) China's CO2 emissions increased from 3500.41 million tons (Mt) in 2002 to 9475.66Mt in 2017, with an average annual growth rate of 6.86%. The growth rate of China's CO2 emissions slowed down after 2012. (2) Non-metallic mineral industry\electricity industry\metal products industry→(intermediate sector)→investment demand and electricity industry→(intermediate sector)→consumption demand are two types of key paths that affect China's CO2 emissions, and these paths remain basically unchanged during the study period. (3) The CO2 emission intensity effect is the main factor in restraining the growth of emissions, and the per capita final demand effect and intermediate product structure effect are the main promoting factors. The effect of driving factors on different industrial paths is different, and the offsetting effect of the driving factor in different paths may lead to the insignificant effect of this factor in the overall decomposition. To effectively reduce CO2 emissions, China should focus on specific industrial paths and implement upstream and downstream comprehensive governance to achieve a low-carbon industrial chain throughout the whole process.

Dynamic features and driving forces of indirect CO2 emissions from Chinese household: A comparative and mitigation strategies analysis.

Controlling CO2 emissions (CEs) is an important measure to mitigate global climate change. In recent years, the research on household consumption and its environmental impact has become a research hotspot in the field of sustainable development. Taking 2000-2014 as the research period, this paper studies the indirect CO2 emissions of household consumption (ICEs-HC) in China by using the Multi-region Input-Output model. Then the structural decomposition analysis method is used to analyze the driving factors of ICEs-HC. The results show that: (1) During the study period, ICEs-HC in China showed an increasing trend. The total ICEs-HC increased by 1.90 times, and the per capita ICEs-HC increased by 1.76 times. (2) ICEs-HC in China are concentrated mainly in Commercial and Public Services (CPS), Electricity, Gas, Steam and Air Conditioning Supply (EGSA), and Manufacture of Food and Tobacco (MFT), which accounted for 26.63%, 17.69% and 13.52%, respectively, of the total emissions in 2014. (3) China has been in the position of net outflow of ICEs-HC. (4) The growth of per capita household consumption is the main factor promoting the growth of ICEs-HC in China, and the reduction of carbon intensity in various countries is the main factor in restraining ICEs-HC in China. This study shows that ICEs-HC in China are likely to rise, and the government should not only constantly improve the level of household consumption, but also actively adjust the industrial structure and optimize the consumption structure to alleviate CEs effectively.

China's provincial CO2 emissions and interprovincial transfer caused by investment demand.

Based on the China's 1997, 2002, 2007, and 2012 multiregional input-output model, this study calculates China's provincial CO2 emissions from investment demand and interprovincial transfer of CO2 emissions caused by investment demand. The findings of this study are as follows: (1) From 1997 to 2012, the CO2 emissions from China's investment demand have seen rapid growth-the CO2 emissions from investment demand has increased by 4.52 times, and the per capita CO2 emissions caused by investment demand has increased by 4.13 times. Investment demand is an important driver of growth of China's CO2 emissions. The proportion of CO2 emissions from investment demand in CO2 emissions from China's three final demands rose from 37.72% in 1997 to 50.68% in 2012. (2) The CO2 emissions from investment demand are relatively large in provinces which have large-scale industries. Affected by investment-driven economic growth, CO2 emissions from investment demand in central, western, and northeastern provinces have increased more rapidly. (3) Large amounts of CO2 are emitted in the less-developed central and western provinces to meet the investment demand of the developed eastern provinces. As China's economy enters the "new normal," economic growth is shifting from investment-driven to consumption-driven, and the growth of CO2 emissions from investment demand will slow down.

Correction to: China's provincial CO2 emissions and interprovincial transfer caused by investment demand.

The original publication of this paper contains a mistake. The correct image of figure 4 is shown in this paper. The original article has been corrected.

Structural Changes in Provincial Emission Transfers within China.

Chinese provinces ultimately implement China's national climate policies. In the 2000s, there were unbalanced emission transfers (emissions produced in one region but consumed in other regions) between China's well- and less-developed regions, mainly related to demand in the well-developed eastern provinces. In the past decade, the plateau in China's exported emissions and changes in its industrial structure suggest that the features of the provincial emission transfers could have changed. We construct a Chinese provincial multiyear, multisector model (multi-regional input-output model) to investigate the structural changes in China's provincial emission transfers from 2002 to 2012. We find that from 2007 to 2012, the international-export-associated emission transfers driven by eastern provinces decreased by 17% after the 262% increase in 2002-07, while investment dominated 99% of the increase in emission transfers. At the sector level, emissions caused by construction in the east and west, and technology-intensive manufacturing in the center that largely related to investment were the major components of the increasing emission transfers in 2007-12, accounting for 23%, 21%, and 10% of the increase, respectively. Our findings indicate that attention should be given to committed emissions from investment and the interaction between non-uniform provincial climate policies and economic relationships between provinces.

Study on embodied CO2 transfer between the Jing-Jin-Ji region and other regions in China: a quantification using an interregional input-output model.

Jing-Jin-Ji region (i.e., Beijing, Tianjin, and Hebei) is China's key development region, but it is also the leading and most serious air pollution region in China. High fossil fuel consumption is the major source of both carbon dioxide (CO2) emissions and air pollutants. Therefore, it is important to reveal the source of CO2 emissions to control the air pollution in the Jing-Jin-Ji region. In this study, an interregional input-output model was applied to quantitatively estimate the embodied CO2 transfer between Jing-Jin-Ji region and other region in China using China's interregional input-output data in 2010. The results indicated that there was a significant difference in the production-based CO2 emissions in China, and furthermore, the Jing-Jin-Ji region and its surrounding regions were the main regions of the production-based CO2 emissions in China. Hebei Province exported a large amount of embodied CO2 to meet the investment, consumption, and export demands of Beijing and Tianjin. The Jing-Jin-Ji regions exported a great deal of embodied CO2 to the coastal provinces of southeast China and imported it from neighboring provinces.

Dynamic Economic Resilience and Economic Recovery from Disasters: A Quantitative Assessment.

This article analyzes the role of dynamic economic resilience in relation to recovery from disasters in general and illustrates its potential to reduce disaster losses in a case study of the Wenchuan earthquake of 2008. We first offer operational definitions of the concept linked to policies to promote increased levels and speed of investment in repair and reconstruction to implement this resilience. We then develop a dynamic computable general equilibrium (CGE) model that incorporates major features of investment and traces the time-path of the economy as it recovers with and without dynamic economic resilience. The results indicate that resilience strategies could have significantly reduced GDP losses from the Wenchuan earthquake by 47.4% during 2008-2011 by accelerating the pace of recovery and could have further reduced losses slightly by shortening the recovery by one year. The results can be generalized to conclude that shortening the recovery period is not nearly as effective as increasing reconstruction investment levels and steepening the time-path of recovery. This is an important distinction that should be made in the typically vague and singular reference to increasing the speed of recovery in many definitions of dynamic resilience.

Multiregional Input-Output Analysis of Spatial-Temporal Evolution Driving Force for Carbon Emissions Embodied in Interprovincial Trade and Optimization Policies: Case Study of Northeast Industrial District in China.

In the counties with rapid economy and carbon emissions (CEs) growth, CEs embodied in interprovincial trade (CEs-PT) significantly impacts the CEs amount and structure and represents a key issue to consider in CEs reduction policies formulation. This study applied EEBT and two-stage SDA model to analyze the characteristics and driving force of spatial-temporal evolution for net CEs-PT outflow in the Northeast Industrial District of China (NID). We found that, during 1997-2007, the net CEs-PT flowed out from NID to 16 south and east provinces, then to 23 provinces all over China, and its amount has increased 216.798Mt (by 211.67% per year). The main driving forces are technology and demand (further decomposed into structure and scale matrix); the contribution are 71.6418 Mt and 145.1562 Mt. Then, we constructed coupling relationship model and took the top three industries with the greatest net CEs-PT outflow (farming, forestry, animal husbandry and fisheries, electricity and heat production and supply, petroleum processing, coking, and nuclear fuel processing) as examples, adjusted the interprovincial trade constructions, scales, and objects, to reduce the CEs-PT with lower costs, greater effect, and more equitability. The achievement could provide reference for formulating CEs reduction policies for similar areas in the world characterized by rapid growth of economy and CEs.

Interprovincial transfer of embodied energy between the Jing-Jin-Ji area and other provinces in China: A quantification using interprovincial input-output model.

Commodity trade between regions implies a large amount of energy transfer. As an important economic growth pole of China, the Jing-Jin-Ji area (Beijing-Tianjin-Hebei) is also one of the areas with the largest energy consumption in China. Moreover, the primary energy consumer goods in this area are fossil fuels, such as coal. This has led to serious air pollution in the area. Therefore, the reduction of energy consumption under the premise of maintaining sustained economic growth is an important task of the Jing-Jin-Ji area. In this study, an interprovincial input-output model was applied to quantitatively estimate the embodied energy transfer between Jing-Jin-Ji area and other provinces in China. The results indicated that the Metal and nonmetal mineral processing industry and the Electrical, gas and water industry in the Jing-Jin-Ji area exported a large amount of embodied energy to the Yangtze River Delta and the Pearl River Delta. However, the embodied energy export of the Jing-Jin-Ji area mainly exported by Hebei province. Beijing and Tianjin even have some net import of embodied energy. The embodied energy transfer between Tianjin, Hebei and other provinces was mainly driven by investment, while the main media of embodied energy transfer between Beijing and other provinces was consumption. Therefore, we suggest that the Jing-Jin-Ji area should further increase the degree of dependence on other provinces' energy-intensive products and reduce the export of energy-intensive products. In addition, there should be difference in the energy and industrial policies among Beijing, Tianjin and Hebei, and the problems of high energy consumption and high proportion of heavy industry in Hebei should be first resolved.

Estimation of the contribution of exports to the provincial economy: an analysis based on China's multi-regional input-output tables.

This paper developed an estimation model for the contribution of exports to a country's regional economy based on the Chenery-Moses model and conducted an empirical analysis using China's multi-regional input-output tables for 1997, 2002, and 2007. The results indicated that China's national exports make significantly different contributions to the provincial economy in various regions, with the greatest contribution being observed in the eastern region and the smallest in the central region. The provinces are also subjected to significantly different export spillover effects. The boosting effect for the eastern provinces is primarily generated from local exports, whereas the western provinces primarily benefit from the export spillover effect from the eastern provinces. The eastern provinces, such as Guangdong, Zhejiang, Jiangsu, and Shanghai, are the primary sources of export spillover effects, and Guangdong is the largest source of export spillover effects for almost all of the provinces in China.