Urban agglomeration worsens spatial disparities in climate adaptation

Spatiotemporal dynamic relationships and simulation of urban spatial form changes and land surface temperature: a case study in Chengdu, China

Exploring the spatiotemporal dynamic evolution of local climate zones (LCZ) associated with changes in land surface temperature (LST) can help urban planners deeply understand urban climate. Firstly, we monitored the evolution of 3D urban spatial form in Chengdu City, Sichuan Province, China from 2010 to 2020, used the ordinary least squares model to fit the dynamic correlation (DR) between the changes in urban spatial patterns and changes in LST, and revealed the changes of urban spatial patterns closely related to the rise in LST. Secondly, the spatiotemporal patterns of LST were examined by the integration of the Space-Time Cube model and emerging hotspot analysis. Finally, a prediction model based on curve fitting and random forest was integrated to simulate the LST of study area in 2025. Results show the following: the evolution of the urban spatial form consists of three stages: initial incremental expansion, midterm incremental expansion and stock renewal, and late stock renewal and ecological transformation. The influence of the built environment on the rise of LST is greater than that of the natural environment, and the building density has a greater effect than the building height. The overall LST shows a warming trend, and the seven identified LST spatiotemporal patterns are dominated by oscillating and new hotspots patterns, accounting for 51.99 and 11.44% of the study area, respectively. The DR between urban spatial form and LST varies across different time periods and built environment types, whereas the natural environment is always positively correlated with LST. The thermal environment of the city will warm up in the future, and the area affected by the heat island will shift to the central of the city.

From global to national: The role of urban agglomerations in China's new development paradigm

Urban agglomerations (UAs), which serve as pivotal hubs for economic and innovative convergence, play a crucial role in enhancing internal circulation and strengthening external linkages. This study utilizes the China city-level multi-regional input-output tables, incorporating the Dagum Gini coefficient and kernel density estimation methods, to perform a thorough quantitative analysis. Disparities within the national and global value chains ("dual value chains") of Chinese UAs from 2012 to 2017 were assessed. Additionally, the logarithmic mean Divisia index (LMDI) method was applied to disaggregate the drivers of both national and global intermediate inputs (NII and GII). The study's key findings include the following: (1) The national value chain (NVC) within UAs exhibits robust growth, contrasting with the decline in the global value chain (GVC). (2) The inter-UA disparity contribution rate significantly surpasses the combined rates of intra-UA contribution and super-variation density. (3) Distinct evolutionary peak trends are discerned among various UAs within the "dual value chains", highlighting diverse spatial polarization characteristics and expansiveness. (4) The growth of the NVC has transitioned from a negative to a positive impact on NII, while the decline in GVC has substantially counteracted GII growth. Economic and demographic factors notably drive positive improvements in both NII and GII, whereas the efficiency of outflows presents a negative driving effect. Based on these findings, this study offers strategic recommendations to facilitate the effective integration of UAs into the new development paradigm, thereby providing a scientific basis for related decision-making processes.

Impacts of renewable energy on climate vulnerability: A global perspective for energy transition in a climate adaptation framework

The transition to renewable energy can disproportionately impact the effectiveness of climate change adaptation, due to regional heterogeneity. Many countries attempt to promote renewable energy to reduce the impact of climate change, but the impacts of national energy policy in the climate vulnerability framework remain little understood. Here, we exploit variations in renewable energy uses to test the effectiveness of climate adaptation policy across the dimensions of climate impact and vulnerability. Using the Fuzzy Analytic Hierarchy Process and panel data regression, we analyze the spatiotemporal correlation between renewable energy transition and climate vulnerability across the world. We find that while renewable energy increases proportionally with climate exposure and sensitivity, many countries exhibit discrepancies between the variation in renewable energy transition and climate vulnerability. The promotion of renewable energy funnels into nations with a higher level of adaptive capacity while bypassing more vulnerable countries. The results signify that existing renewable energy policies can exacerbate climate inequality and undermine the benefits of the transition to renewable energy by neglecting the spatial heterogeneity in climate vulnerability. Our findings provide empirical evidence for the ways in which renewable energy policy can generate spatial inequalities in climate adaptation.

Sustainable urban system structure evaluation in sparsely populated areas: case study of the Qinghai-Tibet Plateau in China

Urbanization in sparsely populated areas is critical for sustainability. The Qinghai-Tibet Plateau is a typical example of an ecologically fragile region that plays a crucial role in China’s ecological safety and water resource protection. We use a social network analysis to illustrate the structure of the urban system on the plateau and find that the agglomeration and diffusion capabilities of the core nodes are weak, which presents an obstacle to the sustainable development of the urban system. Nevertheless, we find that the intermediate nodes—which serve multiple integration functions for the various cultures, ethnic groups, and religions in the region—are core nodes that divide the dispersed cities and towns into four subgroups that function as small worlds (The cities and towns within one subgroup connect closely and each subgroup is organized independently somehow from others). Based on this finding, we suggest implementing a “double-layer” urban system to promote the sustainable urban development of the Qinghai-Tibet Plateau. This “double-layer” system breaks the usual urbanization trend, in which cities grow in size and their distribution becomes more concentrated; instead it provides a feasible way to maintain urban sustainability in a sparsely populated area.