Impact of Express Delivery Industry’s Development on Transportation Sector’s Carbon Emissions: An Empirical Analysis from China

Elucidating the complex mechanism between urbanization, economic growth, carbon dioxide emissions is fundamental necessary to inform effective strategies on energy saving and emission reduction in China. Based on a balanced panel data of 31 provinces in China over the period 1997-2010, this study empirically examines the relationships among urbanization, economic growth and carbon dioxide (CO2) emissions at the national and regional levels using panel cointegration and vector error correction model and Granger causality tests. Results showed that urbanization, economic growth and CO2 emissions are integrated of order one. Urbanization contributes to economic growth, both of which increase CO2 emissions in China and its eastern, central and western regions. The impact of urbanization on CO2 emissions in the western region was larger than that in the eastern and central regions. But economic growth had a larger impact on CO2 emissions in the eastern region than that in the central and western regions. Panel causality analysis revealed a bidirectional long-run causal relationship among urbanization, economic growth and CO2 emissions, indicating that in the long run, urbanization does have a causal effect on economic growth in China, both of which have causal effect on CO2 emissions. At the regional level, we also found a bidirectional long-run causality between land urbanization and economic growth in eastern and central China. These results demonstrated that it might be difficult for China to pursue carbon emissions reduction policy and to control urban expansion without impeding economic growth in the long run. In the short-run, we observed a unidirectional causation running from land urbanization to CO2 emissions and from economic growth to CO2 emissions in the eastern and central regions. Further investigations revealed an inverted N-shaped relationship between CO2 emissions and economic growth in China, not supporting the environmental Kuznets curve (EKC) hypothesis. Our empirical findings have an important reference value for policy-makers in formulating effective energy saving and emission reduction strategies for China.

This article focuses on the spatiotemporal evolution characteristics of the efficiency of the express delivery industry in 31 provinces in China from 2011 to 2019. Since the express delivery business contributes significantly to the improvement of industrial structure and economic competitiveness, the temporal and spatial characteristics of its efficiency are crucial. In this paper, a three-stage SBM model is adopted to analyze the efficiency. The following are the findings: First, the express delivery industry is significantly affected by the external environment and also by random factors. The optimization of the industrial structure will reduce the input redundancy, and the improvement of the Internet level will lead to input redundancy. Second, China's eastern, central, and western regions have the same overall efficiency change trend in the express delivery industry, with the highest in the central region, followed by the eastern region, and the lowest in the western region. Third, the technical efficiency of the express delivery industry is mainly affected by its scale efficiency. Our research results provide an empirical basis for government policies and social-related investments.

China’s transport industry has made rapid progress, which has led to a great amount of carbon emissions. However, it is still unclear how carbon emissions from the transport sector are punctuated by shifts in underlying factors. This paper aims to examine the process of China’s carbon emissions from the transport sector as well as its major driving forces at the provincial level during the period of 2000 to 2015. We first estimate the carbon emissions from the transport sector at the provincial level based on the fuel and electricity consumption using a top-down method. We find that the carbon emission per capita is steadily increasing across the country, especially in the provinces of Chongqing and Inner Mongolia. However, the carbon emission intensity is decreasing in most provinces, except in Yunnan, Qinghai, Chongqing, Zhejiang, Heilongjiang, Jilin, Inner Mongolia, Henan and Anhui. We then quantify the effect of socioeconomic factors and their regional variations on carbon emissions using a panel model. The results show that the development of secondary industry is the most significant variable for carbon intensity at both the national and regional levels, while the effects of the other variables vary across regions. Among these factors, population density is the main factor of the increasing carbon emissions per capita from the transport sector for both the whole country and the western region, whereas the consumption level per capita of residents and the development of tertiary industry are the primary drivers of per capita carbon emissions for the eastern and central regions.

Effects of rural–urban development transformation on energy consumption and CO2 emissions: A regional analysis in China

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

Does the development of delivery industry increase the production of municipal solid waste?—An empirical study of China

Accurately assessing the progress of carbon emissions peak actions at the national and regional levels is a crucial foundation for achieving China’s carbon emissions peak target before 2030. This study first examines the relationship between carbon emissions peak and carbon emissions decoupling, and establishes their correspondence numerically by employing the Tapio decoupling model. Second, using provincial panel data from 2000 to 2019, it investigates the progress of the carbon emissions peak in China overall and in the Eastern, Central, and Western regions. The study finds that at the national level, China’s overall CO2 emissions have entered a near-peak plateau phase, where the growth rate of carbon emissions has significantly slowed and is much lower than GDP growth. However, an unstable rebound trend persists under the influence of macroeconomic policies. Regionally, the Eastern region has the most advanced progress toward the carbon emissions peak, followed by the Central region, with the Western region lagging. Moreover, the gaps among the three regions are gradually widening.

Differences in regional emissions in China's transport sector: Determinants and reduction strategies

Agricultural land, as an important carbon source, has produced about 20% of carbon dioxide globally. The calculation and spatial-temporal distribution of carbon emissions resulting from agricultural land utilization (ALU) has attracted a great deal of attention from scholars. Most of the existing literature widely agrees that China’s carbon emissions from ALU showed significant regional discrepancies, but rarely pays attention to the evolutionary characteristics of the discrepancies. This study calculated the total carbon emissions from ALU based on six kinds of carbon emissions sources in the 31 provinces of mainland China, which showed obviously different characteristics in terms of their abundances of agricultural land resources, relative scarcities of production factors, levels of science and technology and economic prosperity. We then analyzed the evolutionary process and characteristics of regional discrepancies in carbon emissions from ALU at the national level and regional level with the method of kernel density estimation. The key results demonstrated the following: (1) The carbon emissions from ALU in the whole country and the eastern, central and western regions of China have increased sharply during the study period. From 2000 to 2015, the carbon emissions from ALU in the whole of China, the eastern region, central region, and western region were increased by 2626.11 (104 tons), 441.32 (104 tons), 1054.45 (104 tons), and 1130.3 (104 tons), respectively, with an average annual growth rate of 2.75%, 1.29%, 3%, and 4.35%, respectively; (2) The scale of carbon emissions from ALU showed significant spatial disparities at the regional and inter-provincial levels. From 2000 to 2015, the central region had the highest carbon emissions from ALU, while the eastern and western regions had the second and third highest carbon emissions; (3) The distribution curves of carbon emissions from ALU in the whole country and each region all moved in the right direction gradually during the study period, and the width of the curves increased, indicating the regional discrepancies of carbon emissions from ALU was expanding at different spatial scales. Distribution curves of carbon emissions from ALU in the eastern, central and western regions all showed a “multi-polar” differentiation phenomenon in 2000, while presented a “tri-polar”, “bipolar” and “multi-polar” division in 2015, respectively.

The transportation sector has significantly contributed to greenhouse gas and air pollutant emissions. Consequently, there is an urgent need to investigate strategies to synergize the reduction in CO2 and pollutant emissions in this sector. Using panel data from 30 provinces in China over the period from 2005 to 2018, this study employs spatial econometric models and mediation effect models to investigate the synergistic effects of carbon markets and environmental regulations on carbon reduction and pollution control in the transportation sector, along with the underlying transmission mechanisms. The results are as follows: (1) Carbon markets can achieve synergistic reduction effects in both CO2 emissions and pollutant emissions, whereas environmental regulations can reduce pollutant emissions alone in the transportation sector. (2) The synergistic reduction effects of carbon markets and environmental regulations in the transportation sector exhibit regional heterogeneity. The central region can realize synergistic reductions, while the western and eastern regions may experience an increase in CO2 and pollutant emissions and cross-regional transfers. (3) Carbon markets can achieve synergistic reduction effects in the transportation sector by influencing the industrial structure at the provincial level, transportation supply and demand at the sectoral level, and green willingness at the individual level.

Studies on the CO2 emissions from the transportation sector in China are increasing, but their findings are inconclusive. The main reason is that the spatial correlation of CO2 emissions from the regional transportation sector has been ignored in examinations of the driving factors of CO2 emissions from this sector. In this paper, new emission factors are adopted to calculate the CO2 emission levels from the transportation sector in Chinese provinces. By fully considering the spatial correlation of regional CO2 emissions and based on a two-way Durbin model incorporating both spatial and temporal fixed effects, the driving factors of CO2 emissions from the transportation sector in China are studied. The CO2 and spatial regression results for the transportation sector in China suggest the following: 1) Most of the regions with the highest CO2 emissions from the Chinese transportation sector are located on the east coast; they have gradually expanded over time to include the central and western regions. 2) The CO2 emissions from the transportation sector are higher in South China than in North China, and the regions with higher CO2 emissions have gradually shifted from north to south. 3) Transportation activity intensity, urbanization level, technological level, industrial structure and per capita GDP greatly impact CO2 emissions from the transportation sector in each province of China. Among these factors, transportation activity intensity, urbanization level, and per capita GDP exert not only direct effects but also indirect effects, whereas technological level and industrial structure exert only direct effects.

Sectoral CO2, CH4, N2O and SO2 emissions from fossil fuel consumption in Nagpur City of Central India

Impact of FDI and R&D on China's industrial CO2 emissions reduction and trend prediction

Facing the growing problem of carbon emission pollution, the scientific and reasonable division of environmental management power between governments is the premise and institutional foundation for realizing China’s carbon emission reduction target in 2030. In this article, we directly assess the degree of environmental decentralization according to the allocation of environmental managers among different levels of government. By incorporating fiscal decentralization indicators, the provincial panel data and dynamic spatial econometric model are used to empirically test the impact of environmental decentralization on carbon emissions from a spatial perspective. The results show that (1) China’s provincial carbon emissions have significant inertia dependence and spatial path dependence. The increase (decrease) of provincial carbon emissions will lead to the increase (decrease) of carbon emissions in neighboring regions. (2) At the national level, environmental decentralization, environmental administrative decentralization, and environmental monitoring decentralization significantly reduce China’s carbon emissions, while environmental supervision decentralization and fiscal decentralization significantly increase carbon emissions. Similarly, the interaction of environmental decentralization and its decomposition indicators and fiscal decentralization also significantly promotes carbon emissions, and the impact is related to the types of environmental management decentralization. (3) The carbon emission effects of environmental decentralization in different regions are heterogeneous. The inhibition effect of environmental decentralization, environmental administrative decentralization, and environmental monitoring decentralization on carbon emissions in the western region is significantly greater than that in the eastern and central regions, but the inhibitory effect of the interaction of environmental decentralization and its decomposition index and fiscal decentralization on carbon emissions in the eastern region was significantly stronger than that in the central and western regions. The above results provide theoretical support for China to construct a differentiated carbon emission environmental management system from two aspects of regional differences and environmental management power categories.

Environmental regulation is an important tool to reduce CO2 emissions. To investigate the relationship between heterogeneous environmental regulations and CO2 emissions of China's textile industry (CTI), this paper uses the threshold model and panel model to study the impacts of command-based, market-based and public-based environmental regulations (CER, MER and PER) on the total carbon emissions and carbon emission intensity of CTI from 2004 to 2019. Then it further explores their regional heterogeneity. The results show that: at the national level, CER has a forced emission reduction effect and a green paradox effect on CTI’s total carbon emissions and carbon emission intensity, respectively. And MER shows a forced emission reduction effect on carbon emission intensity. But the coefficients of PER are not significant. At the regional level, the result verifies a U-shaped relationship between CER and CO2 emissions in the eastern textile industry. And CER shows a forced emission reduction effect in the central and western regions. The impact of MER on the carbon emission intensity of the eastern textile industry is N-shaped, which means MER can lower carbon emission intensity only within a certain range. And its impacts on the central and western regions are also the forced emission reduction effect. There is an inverted U-shaped relationship between PER and the total carbon emission in the eastern textile industry. While PER has always had a green paradox effect on carbon emission intensity in the eastern region. Other coefficients are not significant. Finally, this paper puts forward the policy suggestions to mitigate the CO2 emissions of CTI.