Accounting carbon emission changes under regional industrial transfer in an urban agglomeration in China's Pearl River Delta

On the background of climate change, studying tourism eco-efficiency of cities is of great significance to promote the green development of tourism. Based on the panel data of the three major urban agglomerations in China’s Yangtze River Delta, Pearl River Delta, and Beijing–Tianjin–Hebei region from 2008 to 2017, this paper constructed an evaluation index system and measured the tourism eco-efficiency of 63 cities by using a hybrid distance model called Super-EBM (epsilon-based measure). We compared the spatial and temporal evolution characteristics of tourism eco-efficiency in the three urban agglomerations. Furthermore, the internal factors influencing tourism eco-efficiency were explored through input–output redundancy, and the external factors were analyzed by a panel regression model. The results indicate that the tourism eco-efficiency of the three urban agglomerations in China generally shows a decreasing-rising-declining trend. Among them, the Yangtze River Delta has the highest eco-efficiency, followed by the Pearl River Delta, and the lowest in the Beijing–Tianjin–Hebei region. Moreover, there is a certain gap within each urban agglomeration. The redundancy input of labor and capital is the main internal cause of low eco-efficiency. Among the external factors, the status of the tourism industry and the level of urbanization have a positive effect on eco-efficiency, while the level of tourism development, technological innovation and investment have a negative impact on it. In the future, we must attach great importance to the development quality and overall benefit value of the tourism industry so as to achieve green and balanced development of the three major urban agglomerations in eastern China. Based on the above conclusions, this paper puts forward targeted policy implications to improve the tourism eco-efficiency of cities.

Urban agglomerations in China have become the strategic core of national economic development and the main component of the new type of urbanization. However, they are threatened by a series of eco-environmental problems and challenges, including the severe overexploitation of natural resources. Eco-efficiency, which is defined as accomplishing the greatest possible economic benefit with the least possible resource input and damage to the environment, is used as an indicator to quantify the sustainability of urban agglomerations. In this work, a traditional data envelopment analysis (DEA) model with a slack-based measurement (SBM) model of undesirable outputs, was used to assess and compare the economic efficiency and eco-efficiency of four major urban agglomerations in eastern China (UAECs) in 2005, 2011, and 2014. The spatio-temporal characteristics of the evolution of urban agglomerations were analyzed. Based on the results of a slack analysis, suggestions for improving the eco-efficiency of the four UAECs are provided. The overall economic efficiency of urban agglomerations located in the Shandong Peninsula, Yangtze River Delta, and Pearl River Delta displayed a V-shaped pattern (decreased and then increased). In contrast, the overall economic efficiency of the Beijing-Tianjin-Hebei urban agglomeration declined during the study period. The Beijing-Tianjin-Hebei urban agglomeration had a considerable loss of economic efficiency due to pollution, whereas the Shandong Peninsula urban agglomeration was less impacted. Overall, the eco-environmental efficiency of the four UAECs declined from 2005 to 2011 and then increased from 2011 to 2014. In addition, the urban eco-efficiency in the four coastal UAECs was characterized by different evolution patterns. The eco-efficiency was higher in the peri-urban areas of the core cities, riverside areas, and seaside areas and lower in the inland cities. The core cities of the Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta urban agglomerations were characterized by high resource consumption, economic benefit output, and eco-efficiency. In most of cities in the urban agglomerations, the emission of pollutants declined, leading to a reduction of pollutants and mitigation of environmental problems. In addition, a differential analysis, from the perspective of urban agglomeration, was performed, and concrete suggestions for improvement are proposed.

China has clearly put forward the strategic goals of reaching the “Carbon Emission Peak” by 2030, and achieving “Carbon Neutrality” by 2060. To achieve these goals, it is necessary to precisely understand the spatial distribution characteristics of historical carbon emissions in different regions. This paper has selected a representative national-level urban agglomeration in China, the Harbin–Changchun urban agglomeration, to study the temporal and spatial distribution characteristics of carbon emissions in its counties. This paper has constructed global and local Moran’s I indexes for the 103 counties in this urban agglomeration by using the carbon emission values reflected by night light data from 1997 to 2017 to perform global and local autocorrelation analysis on a spatial level. The results show that: (1) the main characteristic of carbon emission clustering in the Harbin–Changchun urban agglomeration is similar clustering; (2) the changes in carbon emissions of the Harbin–Changchun urban agglomeration have a strong correlation with relevant policies. For example, due to the impact of the “Twelfth Five-Year Plan” policies, in 2013, the global county-level Moran’s I index of the carbon emissions in the Harbin–Changchun urban agglomeration decreased by 0.0598; (3) the areas where high carbon emission values cluster together (“High–High Cluster”) and low carbon emission values cluster together (“Low–Low Cluster”) in the Harbin–Changchun urban agglomeration are highly concentrated, and the clusters are closely related to the development level of different regions.

An empirical study on the dynamic effect of regional industrial carbon transfer in China

Spatiotemporal evolutionary characteristics and driving forces of carbon emissions in three Chinese urban agglomerations

As an important means of reducing carbon emissions, environmental regulation and green technology innovation have become a top research topic in academia in recent years. Existing studies have investigated the phenomenon of green technology innovation responses to carbon emissions, but there is less existing literature explaining this phenomenon from a spatial perspective and exploring the effect of the joint mechanism of carbon emissions and environmental regulation on green technology innovation. Based on the spatial econometric model, this study used the panel data of 41 cities in the Yangtze River Delta urban agglomeration from 2010 to 2019, to measure the impact of environmental regulation and carbon emissions on green technology innovation from the perspective of spatial interaction. The findings are as follows: green technology innovation in the Yangtze River Delta urban agglomeration shows a trend of “high in the east and low in the west” and has spatial autocorrelation; green technology innovation responds positively to changes in environmental regulations and carbon emissions and, by decomposing the spatial effects, it can be observed that there is a spatial spillover effect of environmental regulations and carbon emissions on green technology innovation in the surrounding areas; there is a substitution effect between environmental regulations and carbon emissions. This paper combines the above results and proposes the corresponding policy recommendations.

The implementation of carbon peaking and carbon neutrality is an essential measure to reduce greenhouse gas emissions and actively respond to climate change. The net carbon sink efficiency (NCSE), as an effective tool to measure the carbon budget capacity, is important in guiding the carbon emission reduction among cities and the maintenance of sustainable economic development. In this paper, NCSE values are used as a measure of the carbon budget capacity to measure the spatiotemporal evolution of the carbon neutral capacity of three major urban agglomerations (UAs) in China during 2007–2019. The clustering characteristics of the NCSE of these three major UAs, and various influencing factors such as carbon emissions, are analyzed using a spatiotemporal cube model and spatial and temporal series clustering. The results reveal the following. (1) From the overall perspective, the carbon emissions of the three major UAs mostly exhibited a fluctuating increasing trend and a general deficit during the study period. Moreover, the carbon sequestration showed a slightly decreasing trend, but not much fluctuation in general. (2) From the perspective of UAs, the cities in the Beijing–Tianjin–Hebei UA are dominated by low–low clustering in space and time; this clustering pattern is mainly concentrated in Beijing, Xingtai, Handan, and Langfang. The NCSE values in the Yangtze River Delta UA centered on Shanghai, Nanjing, and the surrounding cities exhibited high–high clustering in 2019, while Changzhou, Ningbo, and the surrounding cities exhibited low–high clustering. The NCSE values of the remaining cities in the Pearl River Delta UA, namely Guangzhou, Shenzhen, and Zhuhai, exhibited multi-cluster patterns that were not spatially and temporally significant, and the spatiotemporal clusters were found to be scattered. (3) In terms of the influencing factors, the NCSE of the Beijing–Tianjin–Hebei UA was found to be significantly influenced by the industrial structure and GDP per capita, that of the Yangtze River Delta UA was found to be significantly influenced by the industrial structure, and that of the Pearl River Delta UA was found to be significantly influenced by the population density and technology level. These findings can provide a reference and suggestions for the governments of different UAs to formulate differentiated carbon-neutral policies.

Spatial structure and carbon emission of urban agglomerations: Spatiotemporal characteristics and driving forces

In recent decades, efficiency and intensification have emerged as hot topics within urban industrial land use (UILU) studies in China. However, the measurement and analysis of UILU efficiency and intensification are not accurate and in-depth enough. The study of UILU efficiency loss and intensification potential and their relationship is still lacking, and the application of parametric methods with clearer causal mechanisms is insufficient. This paper argued that the intensification potential of UILU could be defined as the amount of saved land or output growth resulting from reduced efficiency loss of UILU. Accordingly, we constructed quantitative models for measuring and evaluating the intensification potential of UILU, using the stochastic frontier analysis (SFA) method to calculate efficiency loss in three major urban agglomerations (38 cities) in China. Our results revealed a large scale and an expanding trend in the efficiency loss and intensification potential of UILU in three major urban agglomerations in China. From 2003 to 2016, the annual efficiency loss of UILU was 31.56%, the annual land-saving potential was 979.98 km2, and the annual output growth potential was 8775.23 billion Yuan (referring to the constant price for 2003). It is, therefore, imperative to formulate and implement better policies and measures to promote further intensification and to reduce inefficiency, especially in the Yangtze and Pearl River Deltas and prioritizing a few key cities, such as Dongguan, Shenzhen, and Shanghai.

Regional industrial transfer in the Jingjinji urban agglomeration, China: An analysis based on a new “transferring area-undertaking area-dynamic process” model

A multi-level characteristic analysis of urban agglomeration energy-related carbon emission: A case study of the Pearl River Delta

The energy-related carbon emissions of China’s manufacturing increased rapidly, from 36988.97 × 104 tC in 1996 to 74923.45 × 104 tC in 2012. To explore the factors to the change of the energy-related carbon emissions from manufacturing sector and the decoupling relationship between energy-related carbon emissions and economic growth, the empirical research was carried out based on the LMDI method and Tapio decoupling model. We found that the production scale contributed the most to the increase of the total carbon emissions, while the energy intensity was the most inhibiting factor. And the effects of the intrastructure and fuel mix on the change of carbon emissions were relatively weak. At a disaggregative level within manufacturing sector, EI subsector had a greater impact on the change of the total carbon emissions, with much more potentiality of energy conservation and emission reduction. Weak decoupling of manufacturing sector carbon emissions from GDP could be observed in the manufacturing sector and EI subsector, while strong decoupling state appeared in NEI subsector. Several advices were put forward, such as adjusting the fuel structure and optimizing the intrastructure and continuing to improve the energy intensity to realize the manufacturing sustainable development in low carbon pattern.

Comparison of urban growth patterns and changes between three urban agglomerations in China and three metropolises in the USA from 1995 to 2015

Land-use change, particularly urban expansion, can greatly affect the carbon balance, both from the aspects of terrestrial ecosystems and anthropogenic carbon emissions. Coastal China is a typical region of rapid urban expansion, and obvious spatial heterogeneity exists from the north to south. However, the different urban change characteristics and the effect on carbon balance remain undetermined. By unifying the spatial-temporal resolution of carbon source and sink data, we effectively compared the carbon budgets of three coastal urban agglomerations in China. The results show that all of the three urban agglomerations have undergone an obvious urban expansion process, with the built-up area increasing from 1.03 × 104 km2 in 2000 to 3.06 × 104 km2 in 2013. For Beijing–Tianjin–Hebei (BTH), the built-up area gradually expanded. The built-up area in the Yangtze River Delta (YRD) gradually changed before 2007 but rapidly grew thereafter. The built-up expansion of the Pearl River Delta (PRD) passed through three growing stages and showed the largest mean patch size. Carbon emission spatial patterns in the three urban agglomerations are consistent with their economic development, from which the net ecosystem production (NEP) spatial patterns are very different. Compared to carbon emissions, NEP has a carbon sink effect and can absorb some carbon emissions, but the amounts were all much lower than the carbon emissions in the three urban agglomerations. The carbon sink effect in the Yangtze River Delta is the most obvious, with the Pearl River Delta following, and the lowest effect is in Beijing–Tianjin–Hebei. Finally, a scientific basis for policy-making is provided for viable CO2 emission mitigation policies.

The confrontation and symbiosis of green and development: Coupling coordination analysis between carbon emissions and spatial development in urban agglomerations of China