Amid the escalating global climatic challenges, hydrological risks significantly influence human settlement patterns, underscoring the imperative for an in-depth comprehension of hydrological change’s ramifications on human migration. However, predominant research has been circumscribed to the national level. The study delves into the nonlinear effects of hydrological risks on migration dynamics in 46,776 global subnational units. Meanwhile, leveraging remote sensing, we procured globally consistent metrics of hydrological intrusion exposure, offering a holistic risk assessment encompassing hazard, exposure, and vulnerability dimensions, thus complementing previous work. Here, we show that exposure is the primary migration driver, surpassing socioeconomic factors. Surrounding disparities further intensified exposure’s impact. Vulnerable groups, especially the economically disadvantaged and elderly, tend to remain in high-risk areas, with the former predominantly migrating within proximate vicinities. The nonlinear analysis delineates an S-shaped trajectory for hydrological exposure, transitioning from resistance to migration and culminating in entrapment, revealing dependence on settlement resilience and adaptability.

Much of the research on climate change has focused on carbon reduction in cities or countries. However, more attention needs to be paid to how to achieve carbon neutrality in the urban design and planning stage, and the lack of quantitative analysis of carbon related to urban space makes it difficult to locate urban space and provide direct guidance for urban planning and design. This study proposed three optimization paths to achieve carbon neutrality in multi-scale urban building clusters. Firstly, we reconstructed the quantitative calculation system of urban building communities with the goal of carbon neutrality; secondly, we screened the carbon source reduction and carbon sink interventions that are suitable for multi-scale urban building communities; finally, we constructed a carbon emission and carbon sink calculation system of planning and design schemes based on the layout of relevant elements of planning and design schemes with a grid cell of 100 × 100 m. In practice, there was a gap of about 115,000 tons of CO₂ from the carbon-neutral target and 26% of carbon emission was distributed in the Xiajiabian Station TOD. In this study, nine types of carbon reduction measures were adopted to achieve carbon neutrality in the region, among which the highest carbon reduction was achieved by biomass energy measures, accounting for 29% of the total carbon reduction of 33,745.27 T. The objective of this study is to accurately and quantitatively assess the carbon targets of urban spaces at different scales and adopt effective measures to achieve carbon neutrality.

Public space is a crucial forum for public interaction and diverse activities among urban residents. Understanding how people interact with and perceive these spaces is essential for public placemaking. With billions of users engaging in social media expression and generating millions of data points every second, Social Media Big Data (SMBD) offers an invaluable lens for evaluating public spaces over time, surpassing traditional methods like surveys and questionnaires. This research introduces a comprehensive analytical framework that integrates SMBD with placemaking practices, specifically applied to the city of Xiamen, China. The result shows the social sentiment, vibrancy heatmaps, leisure activities, visitor behaviors, and preferred visual elements of Xiamen, offering urban designers valuable insights into the dynamic nature of citizen experiences. The findings underscore the potential of SMBD to inform and enhance public space design, providing a holistic approach to creating more inclusive, vibrant, and functional urban environments.

Concurrent meteorological extremes (CMEs) represent a class of pernicious climatic events characterized by the coexistence of two extreme weather phenomena. Specifically, the juxtaposition of Urban Extreme Rainfall (UER) and Urban Extreme Heat (UEH) can precipitate disproportionately deleterious impacts on both ecological systems and human well-being. In this investigation, we embarked on a meticulous risk appraisal of CMEs within China’s Greater Bay Area (GBA), harnessing the predictive capabilities of three shared socioeconomic pathways (SSPs) namely, SSP1-2.6, SSP3-7.0, and SSP5-8.5, in conjunction with the EC-Earth3-Veg-LR model from the CMIP6 suite. The findings evidence a pronounced augmentation in CME occurrences, most notably under the SSP1-2.6 trajectory. Intriguingly, the SSP5-8.5 pathway, typified by elevated levels of greenhouse gas effluents, prognosticated the most intense CMEs, albeit with a temperate surge upon occurrence. Additionally, an ascendant trend in the ratio of CMEs to the aggregate of UER and UEH portends an escalating susceptibility to these combined events in ensuing decades. A sensitivity analysis accentuated the pivotal interplay between UER and UEH as a catalyst for the proliferation of CMEs, modulated by alterations in their respective marginal distributions. Such revelations accentuate the imperative of assimilating intricate interdependencies among climatic anomalies into evaluative paradigms for devising efficacious climate change countermeasures. The risk assessment paradigm proffered herein furnishes a formidable instrument for gauging the calamitous potential of CMEs in a dynamically shifting climate, thereby refining the precision of prospective risk estimations.