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Due to a series of human activities like deforestation and land degradation, the concentration of greenhouse gases has risen significantly. Forest vegetation is an important part of forest ecosystems with high carbon sequestration potential. Estimates of the carbon sequestration rate of forest vegetation in various provinces and districts are helpful to the regional and global Carbon cycle. How to build an effective carbon sequestration potential model and reveal the spatiotemporal evolution trend and driving factors of carbon sequestration potential is an urgent challenge to be solved in carbon cycle simulation and prediction research. This study characterized the carbon sequestration status of forest vegetation using the modified CASA (Carnegie-Ames Stanford Approach) model and estimated the carbon sequestration potential from 2010 to 2060 using the FCS (Forest Carbon Sequestration) model combined with forest age and biomass under the four future Shared Socioeconomic Pathways (SSP) scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, then proposes natural, social, and economic perspectives. This study found that the average NPP of the forest vegetation in Chongqing from 2000 to 2020 was 797.95 g C/m2, and the carbon storage by 2060 was 269.94 Tg C. The carbon sequestration rate varied between <0.01 Tg C/a and 0.20 Tg C/a in various districts and counties. Over time, forest growth gradually slowed, and carbon sequestration rates also decreased. Under the four future climate scenarios, the SSP5-8.5 pathway had the highest carbon sequestration rate. Natural factors had the greatest influence on changes in carbon sequestration rate. This result provides data support and scientific reference for the planning and control of forests and the enhancement of carbon sequestration capacity in Chongqing. [ABSTRACT FROM AUTHOR]

At first glance, assessing future landslide‐exposed population appears to be a straightforward task if landslide hazard estimates, climate change, and population projections are available. However, the intersection of landslide hazard with socioeconomic elements may result in significant variation of estimated landslide exposure due to considerable variations in population projections. This study aims to investigate the effects of different sources of population data on the evaluation of landslide‐exposed population in China under four Shared Socioeconomic Pathways (SSPs) scenarios. We utilize multiple global climate models (GCMs) from Coupled Model Intercomparison Project Phase 6 and six high‐resolution spatially explicit static and dynamic population data sets to drive available landslide models. The results indicate an overall rise in landslide hazard projections, with an increase in the potential impact area of 0.4%–2.7% and an increase in the landslide frequency of 4.7%–20.1%, depending on the SSPs scenarios and future periods. However, the likely changes in future landslide exposed population, as modeled by incorporating population data from different sources with landslide hazard, yield divergent outcomes depending on the population data source. Thus, some of the projections depict an increase in future landslide exposure, while others show a clear decrease. The nationwide divergence ranged from −64% to +48%. These divergent findings were mainly attributed to differences in population data and a lesser extent to variations in GCMs. The present findings highlight the need to pay closer attention to the dynamic evolution of the elements at risk and the associated data uncertainties. Plain Language Summary: As climate change continues, extreme rainfall is expected to become more frequent and intense. This can lead to changes in landslide risks and how population is exposed to them. While previous studies have mainly focused on how the landslide likelihood may change in time, few have paid attention to how dynamic socioeconomic factors play a role in determining landslide risk. In this study, we used multiple global climate models and different population data sets to investigate how different sources of population information can affect estimates of future landslide risks in China. Overall, we found that landslide hazard is likely to increase in the future. However, when we incorporated different population data into our models, we found divergent results in terms of the number of people exposed to these phenomena. Depending on the population data used, the estimates ranged from a decrease of about 64% to an increase of 48%. These different outcomes were mainly due to variations in population data we used, although climate models also had an impact. These conflicting estimates highlight the need to consider changes in elements at risk when assessing disaster risks and developing targeted measures to adapt to and mitigate the effects of climate change. Key Points: Future landslide exposure is assessed by combining landslide model with spatially explicit population and global climate model dataPotential impact areas and frequency of landslides in China under climate change are projected to increase by 0.4%–2.7% and 4.7%–20.1%, respectivelyVarying sourced population projections may induce divergent signals (−64% to +48%) of landslide‐exposed population under climate change [ABSTRACT FROM AUTHOR]

Based on the 1-km resolution long time series temperature data set, the spatial and temporal patterns of the magnitude and trend of the four-season mean temperature changes in the historical period (2001-2020), and in the future period (2021-2100) under the low forcing scenario (SSP119), medium forcing scenario (SSP245) and high forcing scenario (SSP585) are analyzed using the distance level method, Mann-Kendall trend test method and Sen's slope estimation method, with a view to providing a basis for developing detailed regional adaptation strategies in the context of climate warming. The results show that: (1) compared with the historical period, the average temperature of the four seasons in the future will increase in general under the three scenarios, and the area with the largest increase in summer is 66.70% under SSP119, 37.37% and 99.06% under SSP245 and SSP585, respectively. At the same time, the overall variation range of seasonal mean temperature under the three SSP scenarios is significantly different, which is moderated under SSP119, followed by SSP245, and the largest increase range under SSP585. (2) In the historical period, compared with other seasons, the significant rise in mean temperature in spring had the fastest rate (0.68±0.24°C⋅10y-1) and the largest area share (14.44%), mainly distributed in North China, Yunnan, Guizhou, Jiangsu and Zhejiang provinces. (3) In the future period, the regional seasonal mean temperature in China shows an overall rising trend with significant spatial differences; among them, under the SSP119 scenario, the regions with significantly rising mean temperature in spring and winter are mainly concentrated in southern China and the local area of the Qinghai-Tibet Plateau, accounting for 29.03% and 25.58% of the area, respectively; under the SSP245 and SSP585 scenarios, the seasonal mean temperature in all regions of China shows a significant upward trend; under the SSP585 scenario, the seasonal mean temperature in the north increases at a faster rate than that in the south, and the national region has the fastest significant rate of increase in winter (0.66±0.09°C⋅10y-1). [ABSTRACT FROM AUTHOR]

This study presents an analysis of the changes in extreme temperatures over major river basins in China under different shared socioeconomic pathway (SSP) scenarios based on a set of dynamical downscaling over CORDEX East Asia, performed with the regional climate model RegCM4 at a resolution of 25 km, driven by the global climate model FGOALS‐g3. The results indicated that the dynamical downscaling tended to reduce the warm (cold) biases of the present‐day daily maximum (TXx) and minimum temperatures (TNn) simulated by FGOALS‐g3. Under the SSP scenarios, substantial increases in TXx and TNn and the number of warm days and warm nights throughout China were projected by both models. The average increase in TXx in most of the river basins ranged from 1 to 2°C under the SSP1‐2.6 scenario, from 2 to 3°C under the SSP2‐4.5 scenario, and from 3 to 5°C under the SSP5‐8.5 scenario. Reductions in the number of cold days and cold nights were projected across China, but these reductions were smaller than the increases in the number of warm days and warm nights. The interregional variability in the increases in TXx and TNn was more pronounced in the SSP5‐8.5 scenario and the RegCM4 model than in the other SSP scenarios and the FGOALS‐g3 model, respectively. Larger percentages of the land area and population of China would be affected by greater increases in extreme high temperatures and TNn. Under the SSP2‐4.5 (SSP1‐2.6) scenario, 20–65% (50–95%) of the impacts of extreme temperatures under the SSP5‐8.5 scenario could be avoided across most regions in China. The avoided impacts of warm days and warm nights were greater than those of the other extreme temperature indices. More of the impacts of extreme temperatures could be avoided in the Huai River basin, Yellow River basin, Hai River basin, and Northwest Interior River basin than in the other river basins in China. [ABSTRACT FROM AUTHOR]

To connect a wide range of research communities including climate change mitigation and adaptation activities, the Intergovernmental Panel on Climate Change (IPCC) 6th assessment report (AR6) employs the Shared Socioeconomic Pathway (SSP) scenarios. The CORDEX East Asia calls for a dynamical downscaling of climate change projections under the new SSP scenarios. In this study, the state-of-the-art regional climate model RegCM4 with a horizontal resolution of 25 km was used to dynamically downscale future climate changes, which were derived from the global climate model FGOALS-g3, under multiple SSP scenarios over the CORDEX East Asia Phase II domain. Compared to the driving global model FGOALS-g3, the downscaling exhibited added value in the simulation of present-day mean and extreme rainfall over China in terms of both spatial pattern correlation and biases. The largest improvements were found over the Pearl River Basin and the Yangtze River Basin. For the period of 2081–2100 under the SSP2-4.5 scenario, the areas in China with increases in the projected mean and extreme rainfall generally overlapped with the areas with substantial climatological mean and extreme rainfall in both RegCM4 and FGOALS-g3, which highlights the importance of simulated climatology in projecting future rainfall changes. The moisture budget analyses indicated that the projected increases in summer mean rainfall were mainly attributed to thermodynamic processes associated with the increased moisture. The mean and extreme rainfall was most sensitive to the increased emission scenarios in the Northwest Interior River Basin and least sensitive in southern China. From SSP1-2.6 to SSP5-8.5, larger fractions of land area and population would be affected by greater increased and more intense rainfall. If the emissions were reduced from SSP5-8.5 to SSP1-2.6, over 80% of the impacts would be avoided over most regions in China. [ABSTRACT FROM AUTHOR]

• We firstly applied the high forest thematic resolution land use to assess species distribution; • Firmiana danxiaensis was selected, as it is a rare tree species that is endemic to China; • Both future climate and land use change data are projections for the SSPs scenarios. The distribution of species is mostly influenced by climate synergistic effects and land use. The prediction of endangered species is dependent on fine-scale environmental features, especially in forests. The capture of fine-scale suitable habitats is bounded by low spatial resolution and coarse categorization. In this study, we improved the land use information and forest spatial detail through high forest thematic resolution land use data. To understand the relative influence of environmental factors, suitable habitat models for Chinese endangered tree species (Firmiana danxiaensis) under three climate and high forest thematic resolution land use conditions was constructed. We also assess F. danxiaensis 's response to climate and land use, and differential performance in land use on the suitable habitat. The area of suitable habitat for F. danxiaensis grows slowly under the SSP1-2.6 (shared social pathway scenario) scenario, decreases by 21.33% from the present to 2090 under the SSP2-4.5 scenario, and expands significantly under the SSP5-8.5 scenario. We conclude that high forest thematic resolution land use is beneficial in capturing species' requirements for specific habitats and especially necessary in predicting endangered species. At the same time, the distribution of suitable habitats for species is primarily driven by climate, and limited their development by land use. The study shows that the synthetic effects of climate and land use change on F. danxiaensis are positive, with a marked trend toward the northeast. As a consequence, some endangered species are able to benefit from future SSPs scenarios, in particular they respond more strongly to the SSP5-8.5 scenario than to the other scenarios. Assessing the role of changes in the climate and high forest thematic resolution land use on F. danxiaensis will help promote sustainable land use management and contribute to the conservation policy for Chinese endangered species. [ABSTRACT FROM AUTHOR]

Electrifying the transport sector is crucial for reducing CO 2 emissions and achieving Paris Agreement targets. This largely depends on rapid decarbonization in power plants; however, we often overlook the trade-offs between reduced transportation emissions and additional energy-supply sector emissions induced by electrification. Here, we developed a framework for China's transport sector, including analyzing driving factors of historical CO 2 emissions, collecting energy-related parameters of numerous vehicles based on the field- investigation, and assessing the energy-environment impacts of electrification policies with national heterogeneity. We find holistic electrification in China's transport sector will cause substantial cumulative CO 2 emission reduction (2025-2075), equivalent to 19.8-42% of global annual emissions, but with a 2.2-16.1 GtCO 2 net increase considering the additional emissions in energy-supply sectors. It also leads to a 5.1- to 6.7-fold increase in electricity demand, and the resulting CO 2 emissions far surpass the emission reduction achieved. Only under 2 and 1.5 °C scenarios, forcing further decarbonization in the energy supply sectors, will the holistic electrification of transportation have a robust mitigation effect, -2.5 to -7.0 Gt and -6.4 to -11.3 Gt net-negative emissions, respectively. Therefore, we conclude that electrifying the transport sector cannot be a one-size-fits-all policy, requiring synergistically decarbonization efforts in the energy-supply sectors.

[Display omitted] • An ensemble of fifteen members combined by five bias-corrected GCMs and three empirical models were included. • Ensemble means of basin-wide rainfall erosivity would increase by 2.5%-31.0%. • Adverse impact of climate change on soil erosion might be minor in certain seasons and regions. Climate change is a driver of soil erosion, but the future projections of seasonal rainfall erosivity variability and spatial distribution over the Lancang-Mekong River Basin (LMRB) are still not well understood. Based on the bias-corrected precipitation data from five General Circulation Models (GCMs) in the sixth phase of the Coupled Model Intercomparison Project (CMIP6), the impacts of future climate change on the seasonal rainfall erosivity over the LMRB were assessed using three widely applied empirical daily rainfall erosivity models under three combined scenarios of the Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-RCP2.6, SSP3- RCP7.0 and SSP5- RCP8.5). The results show that rainfall erosivity would generally increase in the near term (2030–2060) and far term (2070–2100), and more ensemble members agree with the increase in rainfall erosivity, especially under the high emission scenarios in the far term. In the near term, the ensemble mean of basin-wide rainfall erosivity would increase by 2.5%-8.7% compared to the baseline period (1980–2010), while in the far term, the ensemble mean would increase by 12.2%-31.0%. Seasonal variations in rainfall erosivity show that summer rainfall erosivity from June to August accounts for more than two-thirds of the total annual rainfall erosivity. Although the projected basin-wide average summer rainfall erosivity would increase, the mid-southern basin in Thailand and southern Lao PDR would experience a decrease. For rainfall erosivity from March to May, large areas except for the mountainous part of China would also experience a decrease in seasonal rainfall erosivity. The projected changes in rainfall erosivity can contribute to a better understanding of soil erosion risk under climate change across the LMRB. [ABSTRACT FROM AUTHOR]

Projecting future air pollution and related health burdens remains challenging because of the complex interactions among future emissions, population, and climate change. In this study, we estimated the premature deaths attributed to ambient fine particulate matter (PM 2.5) and ozone (O 3) from 2015 to 2100 under four socioeconomic climate scenarios based on an age-stratified assessment method. We found that PM 2.5 will decrease in all shared socioeconomic pathway (SSP) scenarios and O 3 will decrease in the SSP1-2.6 and SSP2-4.5 scenarios, contributing to a decrease in premature mortality together with the declining total population in China. However, the benefits of a decline in population size and PM 2.5 and O 3 concentrations over time will be largely offset by population aging, and premature death caused by PM 2.5 and O 3 will continue to rise till 2060–2080. This impact was greater for the O 3 -related deaths than those for PM 2.5. Our study highlights the importance of future prevention strategies that must jointly improve air quality and susceptibility to aging. [ABSTRACT FROM AUTHOR]

Climate change can alter the frequency and intensity of extreme rainfall across the globe, leading to changes in hazards posed by rainfall-induced landslides. In recent decades, China suffered great human and economic losses due to rainfall-induced landslides. However, how the landslide hazard situation will evolve in the future is still unclear, also because of sparse comprehensive evaluations of potential changes in landslide susceptibility and landslide occurrence frequency under climate change. This study builds upon observed and modelled rainfall data from 24 bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs), a statistical landslide susceptibility model, and empirical rainfall thresholds for landslide initiation, to evaluate changes in landslide susceptibility and landslide occurrence frequency at national-scale. Based on four Shared Socioeconomic Pathways (SSP) scenarios, changes in the rainfall regime are projected and used to evaluate subsequent alterations in landslide susceptibility and in the frequency of rainfall events exceeding empirical rainfall thresholds. In general, the results indicate that the extend of landslide susceptible terrain and the frequency of landslide-triggering rainfall will increase under climate change. Nevertheless, a closer inspection provides a spatially heterogeneous picture on how these landslide occurrence indicators may evolve across China. Until the late 21st century (2080-2099) and depending on the SSP scenarios, the mean annual precipitation is projected to increase by 13.4 % to 28.6 %, inducing an 1.3 % to 2.7 % increase in the modelled areal extent of moderately to very highly susceptible terrain. Different SSP scenarios were associated with an increase in the frequency of landslide-triggering rainfall events by 10.3 % to 19.8 % with respect to historical baseline. Spatially, the southeastern Tibetan Plateau and the Tianshan Mountains in Northwestern Basins are projected to experience the largest increase in landslide susceptibility and frequency of landslide-triggering rainfall, especially under the high emission scenarios. Adaptation and mitigation methods should be prioritized for these future landslide hotspots. This work provides a better understanding of potential impacts of climate change on landslide hazard across China and represents a first step towards national-scale quantitative landslide exposure and risk assessment under climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Understanding historical and future drought patterns is crucial to acclimation and the mitigation of drought. The negative impact of China's droughts on the social economy has attracted attention; however, there is still no comprehensive or long-term monitoring pattern for future droughts. Here we evaluated the precipitation and temperature simulation capability of Coupled Model Intercomparison Project Phase 6 (CMIP6) and evaluated the temporal and spatial pattern of droughts during 1961–2099 across China. The results show that the multi-model ensemble mean (MME) is more representative of the observed precipitation and temperatures across China than the single climate model. China experienced an overall drying trend in the historical period. After 1991, the drought frequency (DF), drought duration (DD), and drought intensity (DI) in the northwest of the Inland River Basin and in the Yangtze River Basin increased significantly. Compared with the historical period, China will suffer more frequent drought events, although the DD and DI will be weakened under SSP1-2.6 and SSP2-4.5, while China will experience longer DD and more serious drought events under SSP3-7.0 and SSP5-8.5. The Hai River Basin and Huai River Basin are expected to have more serious drought trends in summer. Compared with historical periods, the drought trend will increase by 2.9–5.7 times and 1.1–4.2 times, respectively. The results can be used for decision making regarding future drought control. [ABSTRACT FROM AUTHOR]

Global protected areas are the key factor in maintaining biodiversity and ecosystem services. However, few studies use human activity pressure to assess the effectiveness of protected areas. This study constructed a human activity pressure index to assess the effectiveness of China's protected areas, and predicted the change trend in 2050 under the SSP scenarios. The results are as follows: (1) From 2000 to 2020, the pressure of human activities in 75.15% of China's protected areas is on the rise, accounting for 37.98% of the total area of the reserves. (2) China's protected areas can relieve the pressure of human activities by 1.37%, and there are regional differences in the effectiveness. (3) Under the SSP scenarios, the protected areas can alleviate the effect of the pressure of the population well. These results can provide a systematic and scientific reference for the planning, construction, evaluation and management of global protected areas.

This study investigates changes in fine particulate matter (PM 2.5 ) concentration and air-quality index (AQI) in Asia using nine different Coupled Model Inter-Comparison Project 6 (CMIP6) climate model ensembles from historical and future scenarios under shared socioeconomic pathways (SSPs). The results indicated that the estimated present-day PM 2.5 concentrations were comparable to satellite-derived data. Overall, the PM 2.5 concentrations of the analyzed regions exceeded the WHO air-quality guidelines, particularly in East Asia and South Asia. In future SSP scenarios that consider the implementation of significant air-quality controls (SSP1-2.6, SSP5-8.5) and medium air-quality controls (SSP2-4.5), the annual PM 2.5 levels were predicted to substantially reduce (by 46% to around 66% of the present-day levels) in East Asia, resulting in a significant improvement in the AQI values in the mid-future. Conversely, weak air pollution controls considered in the SSP3-7.0 scenario resulted in poor AQI values in China and India. Moreover, a predicted increase in the percentage of aged populations (>65 years) in these regions, coupled with high AQI values, may increase the risk of premature deaths in the future. This study also examined the regional impact of PM 2.5 mitigations on downward shortwave energy and surface air temperature. Our results revealed that, although significant air pollution controls can reduce long-term exposure to PM 2.5 , it may also contribute to the warming of near- and mid-future climates.