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Continued urban expansion (UE) has long been regarded as a huge challenge for climate change mitigation. However, much less is known about how UE affects carbon emissions (CEs), especially in the urban agglomerations of the Yellow River Basin (UAYRB), China. In this regard, this study introduced kernel density analysis, the Gini coefficient, and Markov chains to reveal the UE patterns and carbon emissions intensity (CEI) in the UAYRB at the county level, and explored the spatial heterogeneity of the impact of UE on CEI with the geographically and temporally weighted regression model. The results show that both CEI and UE in the UAYRB showed a steady growing trend during the study period. The kernel density of CEI and UE revealed that CEI in the UAYRB was weakening, while the UE rate continuously slowed down. The Gini coefficients of both CEI and UE in the UAYRB region were at high levels, indicating obvious spatial imbalance. The Markov transfer probability matrix for CEI with a time span of five years showed that CEI growth will still occur over the next five years, while that of UE was more obvious. Meanwhile, counties with a regression coefficient of UE on CEI higher than 0 covered the majority, and the distribution pattern remained quite stable. The regression coefficients of different urban landscape metrics on CEI in the UAYRB varied greatly; except for the landscape shape index, the regression coefficients of the aggregation index, interspersion and juxtaposition index, and patch density overall remained positive. These findings can advance the policy enlightenment of the high-quality development of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

In recent years, global climate change and human alterations to land use have led to a decrease in ecosystem services, making ecosystems more vulnerable. However, unlike the well-established risk assessment frameworks used in natural disaster research, the concept of ecological risks arising from changes in land use is still in its early stages, with its nuances and assessment methodologies yet to be clearly defined. This study proposes a new framework for assessing ecological risks resulting from changes in land use in the Tarim River Basin. The framework employs a coupled PLUS and Invest model to evaluate the ecological risks of land use change under three development scenarios projected for the Tarim River Basin in Xinjiang by 2035. The findings indicate that: (1) Between 2000 and 2020, the predominant land use types in the Tarim River Basin in Xinjiang were primarily unused land, followed by grassland and cropland. Conversely, grassland, water, and construction land were relatively less prevalent. During this period, the area of unused land and cultivated land increased, while grassland, forest land, and water exhibited a declining trend. Moving forward, under the three scenarios from 2020 to 2035, land use changes in the study area are characterized by the expansion of cropland and unused land, coupled with a significant decrease in grassland area, while other land categories demonstrate minor fluctuations. (2) From 2020 to 2035, across various scenarios, the total ecosystem service within the study area demonstrates an overall increasing trend in both the northern and southern marginal zones. Specifically, under the baseline scenario, the total amount of ecosystem services in the study area decreased by 15.247% compared to 2020. Similarly, under the economic development scenario, this decrease amounted to 13.358% compared to 2020. Conversely, under the ecological protection scenario, the decrease reached 19.852% compared to 2020. (3) The structure of ecological risk levels from 2020 to 2035, across multiple scenarios, demonstrates a consistent pattern, characterized by a predominant proportion of moderate risk. Conversely, other risk levels occupy relatively smaller proportions of the area. [ABSTRACT FROM AUTHOR]

The intensification of the regional water cycle resulting from climate change, coupled with the influence of human activities, has brought about alterations in the frequency, scale, and intensity of droughts. In this study, based on hydrological big data and the standardized runoff drought index (SRI), the multi-scale spatiotemporal evolution of hydrological drought in China from 1948 to 2014 was analyzed using the run-length theory and gravity center model. Meanwhile, the hydrological drought hazard index was constructed to analyze the distribution of the hazard levels of drought in China. The results showed that, during 1948~2014, there was an opposite spatial distribution between the average intensity and the average coverage–duration–frequency of drought in the Yellow River Basin, Haihe River Basin and southeastern river basins. The drought situation in most river basins in China has shown an aggravating trend, among which the southeastern river basins, Haihe River Basin, Songliao River Basin and Pearl River Basin have generally shown an aggravating trend. The drought situation in China was severe in the 1950s and 1960s, gradually reduced in the 1970s, 1980s, and 1990s, and the drought situation was the mildest in the 1990s. After entering the 21st century, the drought situation began to worsen sharply. Meanwhile, from 1948 to 2014, the hazard level of drought generally presented a pattern of high in the west and north, and low in the east and south. The hazard levels of drought in the northwest and northeast were generally higher, and those in the southwest and southeast regions were generally lower. In general, the hazard levels of drought were relatively high in most areas of China. [ABSTRACT FROM AUTHOR]