Under global warming, compound heat and drought days (CHDDs) pose significant threats to both human health and agricultural production. This study systematically investigated CHDDs and the population and major crops exposed to the events across China from 1961 to 2022, using daily-scale temperature and standardized precipitation evapotranspiration index (SPEI). By integrating conventional percentile thresholds and crop-specific physiological stress temperatures for major crops, we employed a 3D visualization framework to quantify the co-occurrence patterns of extreme heat, drought, and CHDDs. The analysis revealed significant decadal changes: a sudden increase in CHDDs was observed in the late 1990s in eastern regions, while western China has shown a consistent upward trend since the 1980s. The highest exposure levels were concentrated in eastern China, where dense populations and extensive crop cultivation have driven a significant rise in both population and crop exposure since the 1990s, particularly for maize and rice. Pronounced regional disparities were evident in the characteristics of CHDDs: while drought days were more frequent in the northwest, southeastern China experienced the highest frequency and fastest growth rate of CHDDs. As a result, southeastern China has experienced the most significant increases in population exposure and the exposure of maize and rice crops. Meanwhile, the northwest arid region has seen rapid growth in population exposure and the exposure of maize and wheat crops, while Northeast China has shown a notable rise in maize exposure. These findings highlight the need for region-specific adaptation strategies to protect China’s food security and public health in a warming climate.

The Hindu Kush Himalaya (HKH) region is one of the regions in the global cryosphere characterized by localized positive anomalies, where the mass and extent of some glaciers have increased rather than declined. To explore whether the snow cover in this region exhibits localized positive snow water equivalent (SWE) anomalies and whether such anomalies may persist under global warming, ERA5-derived reanalysis data (1979–2024) were integrated with a random forest model that incorporates key climatic variables, including temperature, downward shortwave radiation, wind speed, relative humidity, and precipitation-derived snowfall. In addition, multi-scenario simulations from five CMIP6 climate models were used to investigate the spatiotemporal changes and future trends in SWE in the HKH region under 1.5–5.0 °C global warming levels. The results show that a localized SWE-positive anomalous area, identified by combining positive SWE trends with a Local Moran's I spatial correlation constraint, covered approximately 5.5 × 104 km2 in the northeastern Western Himalayas, the northern Eastern Himalayas, and parts of the Karakoram, where annual SWE increased weakly, in contrast to the significant decline (p < 0.05) observed in the whole region. The annual positive SWE signal was mainly associated with persistently lower mean temperature (nearly 10 °C colder than the non-anomalous area), abundant snowfall, and reduced downward shortwave radiation. Under 1.5–5.0 °C global warming, these positive SWE anomalies are projected to persist in high-elevation areas, with mean SWE remaining generally below the baseline (1995–2014) and showing only slight future variation, while the mean elevation of areas retaining positive SWE anomalies shifts slightly upward to about 5030–5040 m. These results highlight the persistence of localized SWE-positive anomalies within the HKH cryosphere.

ABSTRACT Drought poses a significant threat to agriculture in the transboundary Indus River Basin (IRB), which supports over 300 million people through direct and indirect dependence on agriculture. With limited cropland and growing climatic stress, the basin faces an increasing risk to food security. Yet, comprehensive assessments of cropland exposure to drought under a changing climate and socioeconomic conditions remain lacking. This study evaluates present and future cropland exposure to drought across the IRB using cropland data from the Land‐Use Harmonisation dataset (LUH2) and bias‐corrected output from seven CMIP6 global climate models, validated against ERA5 reanalysis data. We examined a baseline period (1995–2014) and three future time slices (2021–2040, 2041–2060 and 2081–2100) under seven Shared Socioeconomic Pathways (SSP1‐1.9 to SSP5‐8.5). Drought characteristics are quantified using the Standard Precipitation Evapotranspiration Index (SPEI) combined with run theory, incorporating CO 2 emissions. Results indicate that drought frequency is increasing in the future across the emission scenarios relative to the baseline. Cropland exposure displays pronounced spatial heterogeneity and a clear dynamic evolution over time, with the highest concentrations in the central IRB, particularly the Indo‐Pak Punjab and riparian corridors. By 2081–2100, annual cumulative exposed cropland area expands from 1875.3 to 2886.5 km 2 , representing an increase of 71.8%–88.1% relative to the baseline. Furthermore, attribution analysis shows that climate change dominates the increase in exposure through 2060, whereas cropland emerges as the primary driver by 2081–2100. These findings underscore the need for dual‐track drought risk‐management: climate‐focused adaptation for near‐term and integrated land‐use planning for long‐term resilience to safeguard food security in the IRB.

Renewable-dominated Power System (RDPS) is emerging as critical trend to achieve CO2 emission reduction, and the COP28 climate summit has set a global goal to triple its capacity to at least 11,000 GW by 2030. However, this system is heavily reliant on weather and climate conditions. While the inclusion of the storage in the RDPS can alleviate the impact of the volatility and intermittency, the new source-grid-load-storage system creates more risks resulting from increasing complexity of interconnections. These include heightened variability in renewable energy generation under extreme weather, growing instability in transmission infrastructure due to climate-induced stress, performance degradation of storage systems under temperature extremes, and limited flexibility in demand response during climate-driven load surges. Critically, these risks are not isolated but often interdependent, as climate-triggered disruptions in one part of the system can cascade across interconnected components and amplify local failures into large-scale outages. In this perspective, we assess the risks for the system across source, grid, load, and storage from the dimensions of hazard, exposure and vulnerability, highlight the emerging cascading risks driven by climate variability and extremes, and call for an urgent expansion of climate risk assessment frameworks to ensure the resilience and reliability of future power systems.

Compound heat-humidity extremes (CTHEs) pose escalating threats to human health, particularly for vulnerable populations (children and elderly) with limited physiological adaptability. This study reveals the expansion of CTHE-active seasons across eastern China from 1961 to 2022. Southern China (SC) and the Yangtze-Huaihe region (YH) exhibit earlier onsets and delayed terminations, prolonging hazardous CTHE seasons by one month post2015 in SC. The prolonged CTHE-active seasons, coupled with population growth, have driven sharp increases in exposure across eastern China, with annual CTHE and hazardous CTHE exposure increasing by 106 million and 78 million person-days since the 2000s. Vulnerable groups constitute 39 % of total exposure, with 11 % (CTHEs) and 34 % (hazardous CTHEs) attributable to season prolongation. Mechanistically, an intensified and westward-extended western North Pacific subtropical high enhances diabatic heating and moisture advection, driving prolonged CTHE-active seasons in SC and YH. These findings quantify climate-demographic synergies in heat-health risks, providing a scientific basis for climate-resilient health strategies targeting age-sensitive populations in eastern China's warming and humidifying hotspots.

As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O 3 air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.

The core mission of COP30 was to turn existing climate promises into concrete action.

ABSTRACT Previous studies addressing climate change impacts on discharge typically focused on limited periods, beginning with the earliest available observed data. This study extends the timeline to 1850–2023 using global climate models containing scenarios of both historical simulations (under climate change) and pre-industrial control (piControl, with greenhouse gases, aerosols, ozone, and solar irradiance fixed at 1850 levels) to drive hydrological models. Key findings include: (1) Basin average annual mean temperature has increased and precipitation has decreased from 1850 to 2023. With more pronounced climate change impacts in the late 20th and early 21st centuries, discharge in historical simulations decreased by up to 7% relative to piControl over the same period after 1970. (2) Climate change has increased discharge from March to May but decreased it in other months, particularly October, where historical simulations showed as much as a 25% decrease compared to piControl in recent decades. (3) Extreme high and low flows have decreased due to climate change, with decreases of up to 8 and 6%, respectively, after 2000, when compared to piControl. This study underscores the growing climate change impact on discharge, providing insights for disaster risk management and water resource planning in the Upper Yellow River (UYR).

The urbanization process of metropolises in China has accelerated in recent years, with the number of urban residents increasing by 21 % per decade (21 %/10a) and the per capita gross domestic product (per capita GDP) increasing by 120 % per decade (120 %/10a) from 2000 to 2019. In parallel with this rapid economic development, carbon emissions have greatly increased, rising by 141 % in 20 years. Understanding the carbon emission trend and its influencing factors is necessary to find plausible pathways for decarbonization. Using data from the Carbon Emission Accounts and Datasets (CEADs), this study analyses the spatiotemporal variations in urban carbon emissions from 2000 to 2019 via the ridge regression method, and the STIRPAT model is adopted, with provincial capitals in China as an example. The cities are classified into three stages of development (i.e., developed, developing and least developed cities) according to per capita GDP to explore the discrepancy in carbon emissions and influencing factors across different types of cities. (1) Urban carbon emissions show a fluctuating upwards trend for the overall sample, with yearly growth rates of 8 % per annum (8 %/a) for 2000-2009 and 2 % per annum (2 %/a) for 2010-2019. (2) For developed cities, affluence is the most significant influencing factor, followed by urbanization rate and energy intensity. In developing cities, carbon emissions initially increased rapidly and then presented a decelerating growth rate, with the main influencing factors being affluence, energy structure and industry structure. In the least developed cities, carbon emissions present a persistent increasing trend and are influenced mainly by affluence, energy structure and urbanization rate. (3) To coordinate economic benefits and carbon emissions, developed cities need to focus on reducing energy consumption, whereas developing cities need to accelerate energy and industrial transformation. For the least developed cities, strong emission reduction efforts may start later for socioeconomic reasons.

Rapid socioeconomic development has continuously driven urban land expansion at the expense of other land types, leading to significant changes in land use and environment. However, existing studies still lack fine-resolution, long-term projections of urban land. Using seven periods of land use data from 1990 to 2020, this study projects urban land in the Yangtze River Delta (YRD) region under the framework of Shared Socioeconomic Pathways (SSPs). A multiple linear regression model and the land use change scenario simulation model (GeoSOS-FLUS) were employed to make projection at a high spatial resolution of 1 km. The findings are as follows: (1) From 1990 to 2020, the rate of urban land expansion in the study area showed a pattern of initial acceleration followed by deceleration, with the average annual expansion rate decreasing from 1.36 × 103 km2 to 0.24 × 103 km2. The center of gravity shifted toward the southeast. (2) Future urban land expansion is projected to increase by 14 × 103 km2 (SSP3) to 48 × 103 km2 (SSP5). The northern and central parts of the region will experience more significant growth, and the center of gravity is projected to shifting northwest. (3) Under SSP2 and SSP5, the urban land will increase continuously. The findings can offer a valuable insight for regional planning and sustainable development.

This study explores the combined impacts of climate and land use changes on the discharge of the Upper Yellow River Basin (UYR), an area of significant water conservation, employing Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models and land use statistics. Discharge projections were conducted by hydrological models for the near-term (2021-2040), mid-term (2041-2060) and long-term (2081-2100) under seven shared socioeconomic pathways (SSPs). The study's key findings are as follows: (1) temperature and precipitation are projected to increase under all SSPs, with greater rates under higher radiative forcing scenarios. Barren land is expected to undergo the most significant changes in land use, followed by grassland and forest, with the largest variations occurring in the long term. (2) The combined impacts of climate and land use changes lead to an overall increase in annual and seasonal discharge, with the most pronounced increases in spring. Under SSP5-8.5, spring discharge is projected to increase by up to 90.19% in the long term. Changes in discharge extremes also suggest an increasing likelihood of floods and droughts. (3) Land use changes play a crucial role in discharge estimation. Neglecting land use dynamics leads to significant overestimation of summer discharge, exceeding 4000 km3/y under all SSPs across different time periods. This study provides more reliable scenarios for future discharge changes in the UYR and emphasises the crucial role of land use in discharge projections.

The response of global dryness and vegetation to CO2 removal experiments, especially for net- negative emission is immature. Here we conducted a thorough investigation to identify hysteresis and reversibility in global dryness, as well as the vegetation productivity’s response to dry and wet episodes, considering their asymmetrical nature. The asymmetry index (AI) includes two important aspects such as positive AI indicates a dominant increase of vegetation productivity during wet episodes compared to the decline in dry episodes and negative AI implies a larger reduction of productivity in dry years compared to an increase in wet years. Aggregate results from various drought indices and vegetation productivity reveal a dominant dryness in the CO2 decrease phase. Global dryness shows strong hysteresis and irreversible behavior over half of the global land with significant regional disparity. Irreversible changes in dryness are concentrated in specific areas, i.e., hotspots, covering over 14% of the global land, particularly pronounced in Northern Africa, Southwest Russia, and Central America. Moreover, a wider spread of negative asymmetry indicates a significant decrease in vegetation productivity caused by dryness. Importantly, the potential evapotranspiration is projected to be the primary driver of global dryness as well as vegetation asymmetry. Our findings suggest only CO2 alleviation is not enough to cope with drought rather implementing advanced water management strategies is a must to mitigate the impact of drought effectively.

A warming climate is driving an increase in the frequency and intensity of extreme weather events, including heatwaves, droughts, and heavy rainfall. These events are increasingly occurring in rapid succession or simultaneously, creating compound effects that amplify their overall impact. Among these, Drought-Wet Abrupt Alternation events (DWAA) - rapid transitions between drought conditions and extreme wet periods (characterized by heavy precipitation) - are becoming more frequent. Northern China, spanning multiple climate subregions and strongly influenced by various monsoon systems, serves as a typical example of such events. Using 40 years of historical meteorological data (1980-2020), we examined the spatiotemporal patterns of DWAA across Northern China and identified the North China Plain and the Loess Plateau as primary hotspots. In comparison, drought-to-wet transitions (DTW) posed a higher risk level to Northern China than wet-to-drought transitions (WTD), characterized by generally more intense transition magnitudes and a more pronounced increasing trend in frequency over the past 40 years. Crucially, the Loess Plateau and northern North China Plain emerged as areas most severely affected, identified as high-frequency zones (recording eight or more events per decade) and high-risk areas for both DTW and WTD. Over 50 % of DTW occurred in summer, while nearly 80 % of WTD took place in summer and autumn-periods crucial for both agricultural productivity and ecosystem health. This seasonal concentration is driven by climate warming, which has intensified the concentration of precipitation and, in turn, heightened the severity of dry-wet transitions. Our research underscores the urgent need for improved disaster risk management, water resource planning, and climate adaptation strategies in these vulnerable regions.

Drought is expected to intensify with rising CO _2 , but its behavior under CO _2 mitigation, remains uncertain. The response of the climate system to CO _2 variation exhibits hysteresis and irreversibility, highlighting the difficulty of recovery and the potential for long-lasting impacts. We investigated the hysteresis and reversibility of global drought and the associated underlying drivers. The Community Earth System Model 2 was used to simulate CO _2 changes: linear increases, decreases (i.e. net negative), and restoration to the initial level. This paper incorporates three well-established indices based on atmospheric, meteorological and soil moisture data to reflect drought. Here, we show that drought is dominant during the CO _2 decrease phase, leading to strong hysteresis with irreversible behavior over more than half of the global land cover. The robust irreversible changes in drought are concentrated in specific areas, i.e. hotspots, covering over 11% of the global land and are particularly pronounced in Northern Africa, Southwest Russia, and Central America. A decrease in precipitation drives drought during the CO _2 increase phase, while an enhanced vapor pressure deficit (VPD) exacerbates it during the CO _2 decrease phase. This increased VPD exacerbates drought hysteresis by raising potential evapotranspiration. Our findings suggest that only CO _2 reduction is not enough to effectively mitigate drought impacts, rather advanced water management strategies are essential.

The COP29 held in Baku (Azerbaijan) from 11 to 24 November 2024 passed a new climate finance goal, aiming to support the developing countries to address the climate challenges.

The Indus River Basin is one of the most densely populated transboundary river basins in the world and is the region with the most serious water disputes. Given the current population's rapid growth, inclusive and high-resolution datasets are urgently needed to assess how this growth will affect the distribution of resources and the sustainability of the environment. Here we present a population gridded dataset for the Indus River Basin with a resolution of 2.5 arc-minutes (~5 km). Based on the historical population distribution and the provincial (state) demographic parameters of the four countries, Afghanistan, China, India, and Pakistan, we projected the population size and structure (age, sex) changes under the Shared Socioeconomic Pathways (SSP1-5) for the period of 2020-2100 on each grid in the Indus River Basin. The dataset was well verified by comparing it with the observed population gridded dataset in 62,140 grids in the basin. The dataset can be useful sources for further research in resource management, sustainable development initiatives, and assessment of climate change impact.

Spatial planning, recognized as a systematic policy instrument for regional development and governance, plays a crucial role in achieving carbon peak and carbon neutrality. This study establishes a framework for carbon sources/sinks estimation and carbon compensation optimization and conducts empirical research in a representative coal resource-based city. We analyzed the spatial–temporal distribution characteristics of net carbon emissions in Huaibei from 2006 to 2020 using a spatial correlation model and an improved Carnegie–Ames–Stanford approach (CASA). Then, we applied the normalized revealed comparative advantage (NRCA) index and the SOM-K-means clustering model to categorize the carbon pattern into payment, balance, and compensation areas. These areas were further integrated with the “Three-zones and Three-lines” to reclassify nine spatial partition optimization types. Finally, we proposed a targeted emission reduction and sink enhancement optimization scheme. We found that urban carbon emissions and carbon sinks exhibit a significant mismatch, with the net carbon emission intensity reaching 166.76–383.27 t·hm−2 from 2006 to 2020, showing a rapid increase followed by stabilization. The high-value area, centered in Xiangshan District, exhibits a circularly decreasing spatial characteristic, gradually extending to the central city of Suixi County. In the optimized payment area, the level of the carbon emission contributive coefficient surpasses the ecological support coefficient (3.92 < ECC < 6.04, 2.09 < ESC < 3.58). The optimized space in the balance area type is primarily situated in mining subsidence areas, leading to a lower overall level (0.42 < ECC < 0.57, 0.49 < ESC < 1.13). The optimized space in the compensation area type (2.24 < ECC < 3.25, 4.59 < ESC < 5.69) requires economic or non-economic compensation from the payment area. The study combines the “Three-zones and Three-lines” with the results of carbon compensation to formulate an urban emission reduction and sink enhancement program, which not only helps to consolidate the theory of low-carbon cities but also effectively promotes the realization of the regional carbon peak goal.

The COP29 held in Baku (Azerbaijan) from 11 to 24 November 2024 passed a new climate finance goal, aiming to support the developing countries to address the climate challenges.