Toward a low carbon path: Do E-commerce reduce CO2 emissions? Evidence from China.

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality.

Transportation carbon emission reduction potential and mitigation strategy in China.

Effectively reducing transportation carbon emissions is greatly significant to achieve the carbon peaking and neutral goals of China. On the basis of considering regional technology heterogeneity, we employ the parametric meta-frontier approach to analyze the carbon emission performance and reduction potential of the transportation sector in China. Then, we further decompose the emission reduction potential's contributors into removing management inefficiencies and filling technology gaps. The estimated potential carbon emission reductions from transportation sector in China are 12.3 million tons, accounting for 8.4 % of the annual transportation carbon emissions. Specifically, the eastern regions, especially Shandong, Shanghai, and Liaoning have the greatest carbon emission reduction potential; while Qinghai, Jiangxi, and Ningxia have the smallest potential. As the major contributors to the potential emission reductions, filling technology gaps and removing management inefficiencies account for 57.5 % and 42.5 % of the total potential, respectively. Moreover, removing management inefficiencies dominate for the eastern region and filling technology gaps for the central and western regions. Finally, we provide provincial-specific emission mitigation strategies based on the identification of the reduction potential and its contributors. Our policy implications help decision-makers to facilitate the low-carbon development of transportation sector.

Exploring key sectors of CO2 emissions and driving factors to spatiotemporal evolution in China from multiple perspectives.

Identifying CO2 emission from different perspectives is necessary for developing the effective mitigation policies for China. Previous studies mainly focus on exploring important sectors from production and consumption sides, while the perspective of betweenness has been neglected. For narrowing the gap, a new perspective for accounting the critical transmission sectors is discussed. In this study, we calculated and compared the CO2 emissions of production-based, consumption-based, and betweenness-based from 2012 to 2017 based on the multi-regional input-output (MRIO) model. A structural decomposition analysis (SDA) is conducted to uncover the driving forces of CO2 emissions change from three accounting principles. The Findings are as follows: (1) the heavy industry sector (559.26 Mt) in Shandong and Jiangsu (471.97 Mt), Power in Guangdong (83.77 Mt) and Beijing (199.24 Mt), Equipment in Jiangsu (213.88 Mt) are identified as the key transmission sectors; (2) the emission intensity effect and the final demand product structure effect contribute to CO2 emission decrease in China, which are largely offset by the structure effect of final demand source and the final demand scale effect. Based on this, we propose some typical policy implications, such as paying close attention to the production efficiency of the key transmission sectors, optimizing the intermediate product input structure and increasing investment in the technology level, and then reducing the intensity of carbon emission.

Exploring the convergence patterns of PM2.5 in Chinese cities.

Economic development and ongoing urbanization are usually accompanied by severe haze pollution. Revealing the spatial and temporal evolution of haze pollution can provide a powerful tool for formulating sustainable development policies. Previous studies mostly discuss the differences in the level of PM2.5 among regions, but have paid little attention to the change rules of such differences and their clustering patterns over long periods. Therefore, from the perspective of club convergence, this study employs the log t regression test and club clustering algorithm proposed by Phillips and Sul (Econometrica 75(6):1771-1855, 2007. 10.1111/j.1468-0262.2007.00811.x) to empirically examine the convergence characteristics of PM2.5 concentrations in Chinese cities from 1998 to 2016. This study found that there was no evidence of full panel convergence, but supported one divergent group and eleven convergence clubs with large differences in mean PM2.5 concentrations and growth rates. The geographical distribution of these clubs showed significant spatial dependence. In addition, certain meteorological and socio-economic factors predominantly determined the convergence club for each city.

Spatial-temporal evolution of the allometric growth between economic scale and carbon emissions in China's cities and its driving mechanism.

Exploring the relationship between economic development and carbon emissions is a hot issue of concern to academia. Taking Chinese cities as the research object, this study constructed an allometric growth model of economic scale and carbon emissions to analyze the spatial-temporal evolution of their allometric growth from 2000 to 2017. Additionally, the geographical detector model was used to reveal the driving mechanism of allometric growth. The findings were as follows. (1) The spatial-temporal patterns of economic scale and carbon emissions were dominated by hot spots. Additionally, their size distribution was in an equilibrium stage. (2) The gap between the economic growth rate of Chinese cities and the growth rate of carbon emissions grew, reflecting the remarkable achievements in carbon emission reduction in Chinese cities as a whole. The scaling exponent declined from east to the west during 2000-2008, but showed the opposite trend during 2009-2017. The proportion of cities with negative allometric growth in the sample cities increased from 76.49 to 97.86%. (3) The influence of city investment intensity, energy utilization efficiency, technological development level, social consumption level, fiscal investment level and economic development level on allometric growth gradually decreases. These factors were also the main factors affecting the spatial-temporal heterogeneity of allometric growth. (4) The impact of various factors had a synergetic enhancement effect. These factors can be classified as economic factors, environmental factors and a combination of them. Under the nonlinear coupling of multiple factors, a spatially differentiated pattern of allometric growth was formed.

Technological roadmap towards optimal decarbonization development of China's iron and steel industry.

China's iron and steel (IS) industry contributes approximately 16 % of the nation's total CO2 emissions. This study evaluates the environmental impact of each step in the production process based on the life cycle assessment method. It then explores potential deep decarbonisation pathways, developing an integrated dynamic model to meet the carbon neutrality target. The results reveal three primary findings. (1) In 2020, the blast furnace-basic oxygen furnace contributed significantly to the global warming potential -1.77 E-8 kg CO2 equivalents per year (eq/yr) higher than the electric arc furnace-and the blast furnace process makes the largest contribution in ironmaking (8.9E-9 kg CO2 eq/yr). (2) Converter negative energy steelmaking technology has the highest energy savings at 39.07 million tons of coal equivalent (Mtce) and an emissions-reduction potential of 72.01 Mt. Its mitigation cost is 69 CNY/t CO2, followed by thick-layer sintering (30.21 Mtce, 61.21 Mt. and 70 CNY/t CO2) and the application of dry vacuum system for molten steel degassing circulation (26.17 Mtce, 56.03 Mt. and 102 CNY/t CO2). (3) Technological improvement could significantly impact the IS industry, reducing CO2 emissions through production structure improvement, technological development and ultra-low emissions technology, from 789 Mt. in a business-as-usual scenario to 516 Mt., 261 Mt. and 157 Mt. in 2060, respectively.

Sustainable Export Innovation Behavior of Firms Under Fiscal Incentive.

The fiscal imbalance between the central and local governments under fiscal centralization may motivate local governments to pass tax burdens on firms. The causal identification of the tax system reform and the sustainable export innovation behavior of firms are of great significance. This study uses the income tax sharing policy of China to examine the impact of fiscal centralization on the sustainable export innovation behavior of firms. We find that this tax reform has significantly inhibited the increase of the export value-added rate of firms, and has an increasing trend with the share ratio between the Central Government and the local government. Moreover, this effect mainly comes from the crowding-out effect of imported intermediate goods on domestic intermediate goods. The tests show that the above conclusions are consistent with the general logic of local governments. When they face greater downward fiscal pressure, they will further pass the tax burden on local firms and force the firms to promote their export performance to expand the tax base. This short-sighted behavior of replacing "quality improvement" with "quantity increase" is an important factor that affects the sustainable export innovation behavior of firms and the climb in the global value chain.

The impacts of the COVID-19 pandemic on China's green bond market.

The paper applies the event study method and econometric models to investigate the impacts of COVID-19 on China's green bond market for the first time. We find that (1) the COVID-19 pandemic has significant impacts on China's green bond market and increases the cumulative abnormal return (CAR) of the green bonds greatly. After the pandemic is relieved, the CAR drops significantly; (2) the improving of bond issuers' governance capacity, the weakening of information asymmetry and the reinforcing of debt-paying ability can effectively mitigate the negative impacts and positively promote the recovery of bond issuers after the pandemic; (3) the impacts of bond issuers' governance capacity, information asymmetry and debt-paying ability on the CAR of green bonds are significantly heterogeneous before and after the pandemic due to their property rights and whether they are listed or not.

Assessing changes and driving factors of energy consumption in China over 2000-2014: a perspective of final demand.

As the economy enters the new normal in China, more and more intellectuals are concerned about the energy consumption in the economic green transformation and development process; this article computes the energy consumption embodied in various final demand types by the utilization of the environmentally extended input-output (EEIO) model during 2000-2014. Then, the structural decomposition analysis is adopted for exploring energy consumption changes' driving factors considering various final demand categories. Furthermore, the decoupling between economic growth and energy consumption embodied in various final demand categories is revealed by the application of the Tapio model in China. The results indicate as below: (1) the energy consumption embodied in various final demand categories increased significantly during the study period; (2) the gross fixed capital formation (GFCF) was most conducive to the growth of energy consumption, while the construction department emerged as the greatest energy user in GFCF; (3) coal and oil were two main energy sources consumed regardless of any final demand categories; (4) in the three drivers, the scale effect had a primary contribution to increasing energy consumption. The intensity effect made a crucial contribution to mitigating energy consumption. The structural effect had a mild contribution to the energy consumption changes; (5) the five final demand categories were roughly characterized by the weak decoupling over the period 2000-2014. GFCF determined the decoupling index between economy growth and energy consumption largely. Finally, this article put forward implied policies concerning the reduction of energy utilization in China.

Will income inequality influence the abatement effect of renewable energy technological innovation on carbon dioxide emissions?

Environmental pollution and income inequality have become two salient issues in China. To achieve a green economic transformation, China urgently needs to develop renewable energy technologies to reduce carbon dioxide (CO2) emissions. However, the relationship among income inequality, renewable energy technological innovation (RETI) and CO2 emissions has not received sufficient attention in the current literature. Based on Chinese provincial panel data from 2000 to 2015, this paper adopts a panel fixed effect regression model and a panel threshold model to perform an analysis on the nonlinear relationship among these factors. The results show that (1) RETI is conducive to reducing per capita CO2 emissions (PCE). However, with an increase in income inequality, the abatement effect of RETI on per capita CO2 emissions will be hindered, and RETI will even positively contribute to PCE. (2) The panel threshold model shows that the impact of RETI on PCE has a significant single-threshold effect with regard to income inequality. When income inequality is lower than the threshold value, the impact of RETI on PCE is not significant. However, above the threshold value, that is, within the interval of higher income inequality, an increase in RETI will positively contribute to PCE. Finally, from the perspectives of income inequality and RETI, relevant policy implications are put forward for achieving the transformation of a low-carbon economy.

Analysis of the spatial association network structure of China's transportation carbon emissions and its driving factors.

Using the social network analysis method, this paper explores the characteristics of the spatial association network structure of China's provincial transportation carbon emissions from 2005 to 2015 and its driving factors. The results are as follows: (1) The spatial association of China's provincial transportation carbon emissions exhibits an intuitive network structure. The degree of closeness which were 0.2253 and 0.2333 in 2005 and 2015 respectively shows an increasing trend on the whole. However, it hit the bottom in 2011, reaching a minimum of 0.2230, which is the "low closeness degree inflection point". (2) The spatial association network presents a significant "core-edge" distribution pattern. Specifically, in the central and eastern regions of China, Henan and Jiangsu have degrees of up to 58.621 and 44.828, which are at the network center. However, some remote regions, like Jilin and Hainan, have degrees of less than 20.000, which are marginalized. (3) The geographical adjacency, the expansion of the difference in R&D investment, and the narrowing of the difference in economic development promote the formation of the interprovincial spatial association. Therefore, in the process of controlling carbon emissions from transportation, the government should focus on the provinces at the network center and pay attention to the impact of the R&D investment on the spatial association of transportation carbon emissions.

Decoupling and decomposition analysis of transportation carbon emissions at the provincial level in China: perspective from the 11th and 12th Five-Year Plan periods.

Based on the Tapio decoupling model, this paper calculates the decoupling indexes of the transportation output and the transportation carbon emissions of China's 30 provinces and municipalities from 2006 to 2015. The research period (2006-2015) is divided into the 11th Five-Year Plan period (FYP) (2006-2010) and the 12th FYP period (2011-2015). On this basis, we conduct a comparative analysis to describe the spatial-temporal evolution of the decoupling states of transportation output and transportation carbon emissions. Furthermore, in order to deeply analyze the reasons for the evolution of the decoupling states during the 12th FYP period compared with the 11th FYP period, the LMDI decomposition method is used to decompose and compare the factors affecting the transportation carbon emissions in the two periods. The results show the following: (1) from the national point of view, the decoupling relationship between transportation output and transportation carbon emissions improved gradually, with small fluctuations from 2006 to 2015; (2) from the provincial point of view, their decoupling states mainly were expansive negative decoupling and weak decoupling, and the spatial evolution of the two decoupling states is significantly different; (3) the reductions in the transportation energy intensity and transportation intensity were the main factors inhibiting the increase of transportation carbon emissions in the 11th and 12th FYP periods, respectively. The growth of per-capita wealth was the decisive factor driving the increase in transportation carbon emissions in the two periods; (4) in contrast to the causes of decreases in the carbon emission variations in the 11th FYP period, in the 12th FYP period, the significant reduction in transportation intensity is the main reason causing the significant decrease of carbon emission variations. However, the transportation energy intensity and the transportation intensity fail to reduce simultaneously in the two periods.