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.

Spatiotemporal dynamics of ecological security in a typical conservation region of southern China based on catastrophe theory and GIS.

Ecological security assessment can effectively reflect the ecological status of a region and reveal its level of sustainable development. In this paper, an ecological security-oriented evaluation system was constructed, and the ecological security level of the Dongjiangyuan region from 2000 to 2020 was evaluated based on catastrophe theory and GIS. The results were as follows: (1) As shown in the land use and cover maps, by 2020, the forestland area had decreased the most, and the artificial surface area had increased the most. (2) The ecological security index of the Dongjiangyuan region showed a low trend in the artificial surface area and its surrounding areas. The quite low values of the ecological security index in 2000 and 2010 were improved in 2020 due to the increase in ecological services capacity. The increased vegetation cover from 2000 to 2020 promoted the improved ecological service capacity. (3) The rapid urbanization process in the Dongjiangyuan region resulted in a lower ecological sensitivity index value. Notably, the ecological sensitivity index of the study area had a slightly decreasing trend. (4) The spatial autocorrelation showed that the proportion of hot and cold spots from 2000 to 2020 decreased by 2.96% and 6.91%, respectively. This study can provide a scientific basis and decision-making guidance for ecological management in the Dongjiangyuan region in the future.

Spatiotemporal dynamics and decoupling mechanism of economic growth and carbon emissions in an urban agglomeration of China.

Carbon emissions and economic growth are two contradictions in urban development, and their decoupling is related to the sustainable development of cities. This paper took urban agglomeration in the middle reaches of the Yangtze River (UAMRYR), China, as the study area. The Kaya model, the Tapio decoupling model, and the Logarithmic Mean Divisia Index (LMDI) model were adopted to analyze the spatiotemporal differentiation of carbon emissions, the decoupling of economic activities, and driving factors. The results indicate that (1) carbon emissions increased by 66% in the study period, but the growth momentum was curbed after 2015. Low level and medium level areas continue to decrease, and relatively high level area gradually become dominant. (2) Spatially, carbon emissions are in a pattern of middle-hot and east-cold. Jiangxi is in the sub-cold and coldspot area, while the hotspot area is driven by the transformation from Wuhan's single-core to Wuhan and Changsha's dual-core. (3) Since 2010, most cities have been in a good decoupling state, and weak decoupling cities have risen from 35.5% in the initial period to 87.1% in 2010-2011, but the decoupling situation of industrial cities with more high-energy-consuming industries still rebounded slightly. (4) The economic level and energy intensity effect had the most significant impact on the economic decoupling of carbon emissions, whose absolute contribution rates were greater than 35%. Urbanization and economic level both play a positive role in promoting carbon emissions, and the energy intensity plays a negative role in retarding carbon emissions. The population effect was mainly manifested in carbon increase from 2006 to 2011, and 45.2% of the cities from 2011 to 2017 turned into carbon suppression. Finally, we suggest that decoupling carbon emissions from economic growth requires developing green urbanization and a decarbonized economy, optimizing the structure of energy consumption and guiding rational population flow.

Intrinsic mechanisms and spatial effects of multidimensional urbanization and carbon emissions.

Existing studies on urbanization and carbon emissions are mostly based on a single pathway and lack the support of a theoretical framework. This study innovatively integrates Grossman's perspective of environmental effects analysis to develop a new framework to interpret the mechanism of multidimensional urbanization (MU) and carbon emissions (CEs). We first explored the spatial effects of MUs and CEs in the Yangtze River Delta urban agglomeration (YRDUA) and then introduced the "population-land-economic" urbanization variables into the S-STIRPAT model to determine the impact mechanisms of each factor on CEs under different urbanization dimensions. The results show that the spatiotemporal development patterns of MUs and CEs overlap to some extent. The Shanghai-Nanjing line is a high-value area of urbanization with different dimensions, as some edge cities are in low-value areas. However, there are local differences in the different dimensions of urbanization, e.g., population urbanization in the southern area is in a high-value area. CEs show a core-edge structure of "high in the center and low in the north and south". All factors, except for population urbanization, affect CEs locally, and their spillover effects are all positive, except for energy intensity, which has a negative influence on CEs in neighboring regions. Land urbanization has the largest positive impact on CEs, with a total effect coefficient of 0.409; economic urbanization has a coefficient of 0.195, and population urbanization has a coefficient of only 0.070. The findings can help to maximize urbanization growth while minimizing harmful environmental externalities.

Impact of the intensive use of urban construction land on carbon emission efficiency: evidence from the urban agglomeration in the middle reaches of the Yangtze River.

Urban construction land, as the main carrier of socioeconomic activities, is also a land type that is associated with large carbon emissions. This study uses statistical data of the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR) from 2006 to 2020 to examine the mechanism of the intensive use of urban construction land (IUUCL) on carbon emission efficiency (CEE) from the perspective of urban land resource utilization. The study shows that the capital-intensive and technology-intensive use of urban construction land can significantly increase CEE, while increased labor and energy intensification inhibits CEE. In addition, there is regional heterogeneity in the effect of the IUUCL on CEE. The external control factor industrial structure has the most obvious inhibiting effect on the CEE of the Wuhan urban circle, the intensive use of energy has become the crucial constraint on the carbon emission reduction of the city cluster around Poyang Lake, and the intensive use of science and technology is the key factor in realizing the green and low-carbon development of the Chang-Zhu-Tan city cluster. This study innovatively constructs a theoretical framework of IUUCL versus CEE and conducts a heterogeneous study on the CEE of intensive use of construction land from the perspective of urban agglomerations. By providing a better understanding of the intrinsic influence mechanism of both these processes, this study provides a new perspective for reducing carbon emissions.

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 change in ecological quality and its influencing factors in the Dongjiangyuan region, China.

It is of great significance for regional ecological protection and sustainable development to quickly and effectively assess and monitor regional ecological quality and identify the factors that affect ecological quality. This paper constructs the Remote Sensing Ecological Index (RSEI) based on the Google Earth Engine (GEE) platform to analyze the spatial and temporal evolution of ecological quality in the Dongjiangyuan region from 2000 to 2020. An ecological quality trend analysis was conducted through the Theil-Sen median and Mann-Kendall tests, and the influencing factors were analyzed by using a geographically weighted regression (GWR) model. The results show that (1) the RSEI distribution can be divided into the spatiotemporal characteristics of "three highs and two lows," and the proportion of good and excellent RSEIs reached 70.78% in 2020. (2) The area with improved ecological quality covered 17.26% of the study area, while the area of degradation spanned 6.81%. The area with improved ecological quality was larger than that with degraded ecological quality because of the implementation of ecological restoration measures. (3) The global Moran's I index gradually decreased from 0.638 in 2000 to 0.478 in 2020, showing that the spatial aggregation of the RSEI became fragmented in the central and northern regions. (4) Both slope and distance from roads had positive effects on the RSEI, while population density and night-time light had negative effects on the RSEI. Precipitation and temperature had negative effects in most areas, especially in the southeastern study area. The long-term spatiotemporal assessment of ecological quality can not only help the construction and sustainable development of the region but also have reference significance for regional ecological management in China.

Nudging Strategies for Arable Land Protection Behavior in China.

Arable land protection is critical to the sustainable development of agriculture in China and acceleration of the realization of the trinity protection goal of the quantity, quality, and ecology of arable land. As a new program of behavioral science to promote social development, nudge has gradually gained the favor of researchers and policy makers due to its unique advantages of small cost and substantial effect. However, current research and practical exploration of arable land protection behavior intervention based on the idea of nudging are still lacking. Implicit nudging strategies directly target the heuristic and analytic systems of arable land protection behavior of each stakeholder and possess more advantages than traditional intervention strategies. Therefore, this article designs six arable land protection behavior nudging strategies from the perspectives of cognition and motivation to realize the theoretical discussion of "generating medium-scale returns with nano-level investment". The nudging strategies of the cognitive perspective include default options, framing effects, and descriptive norms, while those of the motivation perspective aim to stimulate home and country, and heritage and benefit motives to promote arable land protection behavior of various stakeholders. The utility of nudge to arable land protection behavior may be controversial in practice. Therefore, the implementation in China should be based on the division of farmers, the number of options should be appropriate, and the external environment of arable land protection behavior should be fully considered.

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.

Assessing Changes in Ecosystem Service Values in Response to Land Cover Dynamics in Jiangxi Province, China.

This paper examines the ecosystem service values of Jiangxi province, China using the benefit transfer approach. The land cover dynamics results show that cropland and forest are the main land cover types in Jiangxi province. Urban land drastically increased after 2000, expanding from 846.54 km2 in 2000 to 2317.48 km2 in 2015. Forest and water obviously decreased across the study periods. Consequently, the total ecosystem service values decreased from 37.91 × 1010 Yuan in 1995 to 35.27 × 1010 Yuan in 2015. The values showed a declining trend, especially during the 1995-2000 period. The largest declines in ecosystem service values were caused by decreases in forest and water cover. Regulating services experienced the largest declines in ecosystem services value. Moreover, water supply showed the largest decline in ecosystem service value between 1995 and 2015. Not surprisingly, food production increased in the whole period, especially in the 1995-2000 period. Forest and cropland played the most important roles in the total ecosystem service values of Jiangxi province. We then discussed the relationship among ecosystem services based on the ecosystem service trade-off degree. The results show that the dominant relationship among ecosystem services in Jiangxi province was synergy; thus synergy mostly occurred in all ecosystem services except for food production from 1995 to 2015. However, during the 1995-2000 period, trade-offs mainly existed in both food production and waste treatment. The proportion of synergy greatly increased in the 2000-2015 period, and the synergistic relationship between waste treatment and other ecosystem services increased. However, the trade-off relationship between food production and other ecosystem services still has not improved, which should be concerned in the future. Changes in the percentage share of cropland showed a declining trend; thus, the potential risk of cropland loss should be monitored.