Spatiotemporal heterogeneity and decoupling decomposition of industrial carbon emissions in the Yangtze River Delta urban agglomeration of China.

The objective of this study is to identify the spatiotemporal change law and the leading factors of industrial carbon emission decoupling. Based on the industrial carbon emission level of the Yangtze River Delta urban agglomeration (YRDUA) from 2006 to 2020, the spatiotemporal heterogeneity was explored with the help of the spatial Markov chain, the Tapio decoupling model was used to analyze its decoupling state from the industrial economy, and its driving factors were decomposed using the Kaya identity and logarithmic mean Divisia index (LMDI) model. The results show that (1) in 51.9% of the YRDUA's cities, the industrial carbon emission situation was stable, the emission reduction observation area (medium carbon) occupied a dominant position, and the emission reduction key area (relatively high carbon) gradually decreased. (2) Industrial carbon emissions had spatial overflow and path dependency characteristics, and the probability of carbon emission type transfer maintaining the original state reached 80.0%. From 2006 to 2011, the average probability of the downward migration of high-carbon cities was 5.0%. From 2011 to 2020, the average probability of the upward transfer of low-carbon cities was 9.4%. (3) The negative decoupling rate of carbon emissions in the YRDUA experienced a transition from 3.7% to 44.4% and then back to 7.4%, showing spatial imbalance. Unsatisfactory decoupling cities were concentrated along the Yangtze River and in coastal areas. (4) The promoting efficiency of energy intensity, carbon emission coefficient, and employment structure was gradually strengthened, and the carbon-increasing effect of labor input was gradually weakened. (5) The decoupling mode of heavy difficult cities is dominated by the three-factor balanced type, which is jointly affected by industrial production, labor input, and carbon emission coefficient. The findings in this study can provide inspiration for industrial carbon emission reduction in megalopolises.

Spatiotemporal pattern of regional carbon emissions and its influencing factors in the Yangtze River Delta urban agglomeration of China.

Urbanization is a critical factor affecting regional carbon emissions. Clarifying the linkage between urbanization and carbon emissions can provide a decision-making reference to realize China's goal of carbon neutrality. This article examines the spatiotemporal patterns of urbanization and carbon emissions in the Yangtze River Delta urban agglomeration from 2008 to 2018. A complete set of variables is considered to construct relevant land and ecological urbanization variables, and the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and spatial Durbin model (SDM) are adopted to explore the impact of various driving factors on carbon emissions. The results indicate that (1) during the study period, the carbon emissions in the Yangtze River Delta urban agglomeration exhibited a fluctuating increase and that the incremental carbon emissions followed a downward trend. (2) Carbon emissions exhibited a positive spatial correlation. Cold- and hotspot areas indicated a three-gradient pattern from west to east, and a concentric circle radiation pattern occurred with Shanghai as the core. Carbon emissions were spatially imbalanced, but the centre of gravity slightly fluctuated, with a total migration distance of 38.48 km, indicating a migration trend towards the southeast. (3) Regarding the two considered dimensions of urbanization, all driving factors except urbanization played a role in carbon emission enhancement. Consequently, for every 1% increase in economic factors, the carbon emissions correspondingly increased by 0.43-0.57%. Hence, economic factors are the most important factors promoting increased carbon emissions. In the ecological urbanization dimension, urbanization caused a non-significant decrease in carbon emissions, while there was no spillover effect on carbon emissions in neighbouring areas. Accordingly, carbon emission reduction efforts should promote the transformation of urbanization from a land-driven process to an ecologically driven process and realize the synergies among carbon emission reductions, urban development, and land use.

Spatial spillover effects of urbanization on carbon emissions in the Yangtze River Delta urban agglomeration, China.

To achieve a win-win situation for both urbanization and carbon emissions reduction from a spatiotemporal perspective, we need to identify the salient links between urbanization and carbon emissions in different dimensions. Using 2008-2018 panel data on the Yangtze River Delta urban agglomeration, this paper constructs a Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model based on four dimensions of urbanization: population, economy, land, and ecology. Additionally, it uses a whole group of variables for reference, constructs a Spatial Durbin model (SDM) to estimate the spatial effect, and empirically investigates the spatial dependence of carbon emissions and the influence of various driving factors. The results show that (1) in the temporal dimension, the historical carbon emissions of the study area continue to increase. However, the extent to which they are doing so is slowing, the number of low carbon emissions areas has significantly decreased, the number of medium carbon emissions areas have significantly increased, the number of high and relatively high carbon emissions areas are relatively stable, and energy intensity continues to decline. (2) In the spatial dimension, Shanghai, Suzhou, and their surrounding cities have always been carbon emissions hotspots, high and relatively high carbon emissions areas are mainly concentrated in these cities. Low carbon emissions areas and cold spots are mainly distributed in Anhui Province. Medium carbon emissions areas show a great spatial and temporal evolution and are distributed in all provinces. (3) In the four dimensions of urbanization, per capita GDP will not only affect regional carbon emissions but also have a spatial spillover effect. For every 1% increase in the economic factors, carbon emissions in neighboring regions will increase by 0.38-0.43%. Population, economic, and technological factors have significant positive effects on carbon emissions, and economic factor is the most important factor. (4) In different dimensions of urbanization, there are obvious heterogeneities in the impacts of different factors on carbon emissions. Among them, the elasticity coefficient of per capita GDP and energy intensity is the smallest among the dimension of land urbanization, and the elasticity coefficient of the total population is the smallest among the dimension of population urbanization. Therefore, when formulating carbon emissions reduction policies, it is necessary to fully consider the spatial spillover effects, determine the optimal population size threshold, advocate for a low-carbon lifestyle, promote clean technology, and realize information exchange and policy interaction across regions from the perspective of holistic governance.

Impact of changes in labor resources and transfers of land use rights on agricultural non-point source pollution in Jiangsu Province, China.

This study systematically explores the likely mechanisms driving the effect of the transfer of agricultural land use rights (ALURs) on agricultural non-point source pollution (ANSP) in the context of changing agricultural labor resources. It quantitatively estimates the direction and degree of this influence from a microeconomic perspective using data from rural households. The results reveal that economies of scale caused by ALURs transfers contribute to reducing both the ANSP and marginal costs of inputs. Changes in agricultural labor resources lead to reductions in agricultural labor supply and negatively impact on ANSP. Encouraging farmers to participate in ALURs transfers, therefore, helps to reduce ANSP. The government and related departments should implement policies that support farmers who decide to rent an entire village's land or the adjacent land to achieve economies of scale. Accelerating the development of small farm machinery that is suitable for smaller farm plots and the elderly can serve to reduce the use of chemical fertilizer and promote green production and sustainable agricultural development.

Ecological risk assessment of land use change in the Poyang Lake Eco-economic Zone, China.

Land use/land cover change has been attracting increasing attention in the field of global environmental change research because of its role in the social and ecological environment. To explore the ecological risk characteristics of land use change in the Poyang Lake Eco-economic Zone of China, an eco-risk index was established in this study by the combination of a landscape disturbance index with a landscape fragmentation index. Spatial distribution and gradient difference of land use eco-risk are analyzed by using the methods of spatial autocorrelation and semivariance. Results show that ecological risk in the study area has a positive correlation, and there is a decreasing trend with the increase of grain size both in 1995 and 2005. Because the area of high eco-risk value increased from 1995 to 2005, eco-environment quality declined slightly in the study area. There are distinct spatial changes in the concentrated areas with high land use eco-risk values from 1995 to 2005. The step length of spatial separation of land use eco-risk is comparatively long - 58 km in 1995 and 11 km in 2005 - respectively. There are still nonstructural factors affecting the quality of the regional ecological environment at some small-scales. Our research results can provide some useful information for land eco-management, eco-environmental harnessing and restoration. In the future, some measures should be put forward in the regions with high eco-risk value, which include strengthening land use management, avoiding unreasonable types of land use and reducing the degree of fragmentation and separation.

Exploring the mechanisms of ecological land change based on the spatial autoregressive model: a case study of the Poyang Lake Eco-Economic Zone, China.

Ecological land is one of the key resources and conditions for the survival of humans because it can provide ecosystem services and is particularly important to public health and safety. It is extremely valuable for effective ecological management to explore the evolution mechanisms of ecological land. Based on spatial statistical analyses, we explored the spatial disparities and primary potential drivers of ecological land change in the Poyang Lake Eco-economic Zone of China. The results demonstrated that the global Moran's I value is 0.1646 during the 1990 to 2005 time period and indicated significant positive spatial correlation (p < 0.05). The results also imply that the clustering trend of ecological land changes weakened in the study area. Some potential driving forces were identified by applying the spatial autoregressive model in this study. The results demonstrated that the higher economic development level and industrialization rate were the main drivers for the faster change of ecological land in the study area. This study also tested the superiority of the spatial autoregressive model to study the mechanisms of ecological land change by comparing it with the traditional linear regressive model.

[Dynamic changes of ecosystem service value in Pinggu District of Beijing].

Based on the land use/cover data of 1995 and 2004, and by using ecosystem service value per unit area of different terrestrial ecosystem types in China, the dynamic changes of ecosystem service value in Pinggu District of Beijing were analyzed. The results showed that the total ecosystem service value of Pinggu District was decreased from 3.291 x 10(9) yuan in 1995 to 3.044 x 10(9) yuan in 2004, with a change rate of -7.50%. The decrease in the areas of farmland and waters was the primary cause of the loss in ecosystem service function. Aquatic ecosystem had the highest ecological service value per unit area, while forest ecosystem gave the greatest contribution to the total ecosystem service value. The dynamic changes of the ecological service value revealed the conspicuously irrationality of land use structure in the District. The area proportions of forestland, farmland, and waters should be increased, and the conversion from farmland to constructive land should be controlled strictly. As the emergency water source and eco-conservation division of Beijing City, Pinggu District should improve its eco-environment protection and economic development to support the ecological and drinking water source securities of the Capital Beijing.