Since the launch of China’s Fengyun-3 meteorological satellite in 2008, its microwave radiometer temperature observation data has been widely used in numerical weather forecasting and disaster monitoring, but its application in the climate change research remains notably insufficient. In particular, its stability has not been quantitatively evaluated, which is crucial for climate change studies. To fill this gap, in accordance with the basic climate variable observation requirements defined by the Global Climate Observing Systems (GCOS), the stability for Fengyun-3D/MWTS-II operational temperature observations has been quantitatively evaluated through anomaly and difference trend analysis, taking the homogenized temperature climate dataset from NOAA satellites as a reference. During the evaluation, the effects of diurnal sampling errors (i.e., diurnal drift) caused by orbital drift on temperature observations in different global regions (ocean and land) and across different channels were considered. The following conclusions were drawn: (1) For the mid-tropospheric channel 4 over the ocean, upper tropospheric channel 6, and lower stratospheric channel 9, the effects of diurnal drift are minimal, and their stability meets the requirements for climate change research. The temperature trend of channel 4 over land is largely influenced by diurnal drift errors. (2) The upper tropospheric channel 7 and lower stratospheric channel 8 exhibit small diurnal drift effects but have significant calibration drift errors. (3) The temperatures from the stratospheric mid-to-upper layers (channels 10-13) are all affected by diurnal drift errors, making it difficult to determine if there is a calibration drift error. Therefore, diurnal drift errors need to be corrected before stability evaluation. The stability evaluation aids in the selection of high-confidence satellite observations for climate change research, provides key evidence for correcting diurnal drift and calibration drift errors, and lays a scientific foundation for constructing a homogenized temperature climate dataset from Fengyun satellites. This study will advance the application of Fengyun-3D observations in climate change research.
Sunshine duration is an important indicator for monitoring solar energy resources and plays a key role in climate change and renewable energy assessment. To explore the spatiotemporal variation characteristics of solar drought events in China under the background of global warming, this study is based on daily sunshine duration data from 2242 meteorological stations covering China from 1981 to 2020. It employs methods such as the Sen’s slope method and the Mann-Kendall non-parametric test, the Mann-Kendall mutation test, wavelet analysis, and K-means clustering for systematic analysis. The findings reveal that the number of no-sunshine days, the number of low-sunshine days, the frequency of consecutive no-sunshine days, and the maximum no-sunshine duration all show a significant upward trend. The mutation test indicates that this trend has significantly strengthened after 2000. Solar drought events have a main cycle of 2-6 years, with significant periodic variations in different periods. They show a significant increasing trend from the North China Plain to the middle and lower reaches of the Yangtze River. The proportion of stations with a significant increase in frequency of no-sunshine days, low-sunshine days, consecutive no-sunshine days, and consecutive low-sunshine days all reaches more than 22%. Although the proportion of stations with a significant increase in the maximum no-sunshine duration and the maximum low-sunshine duration is relatively low, their spatial aggregation has been enhanced. The regions with solar drought events in China are mainly concentrated in the Sichuan Basin and the eastern part of the Yunnan-Guizhou Plateau (extreme solar drought area), the middle and lower reaches of the Yangtze River (severe solar drought area), and the North China Plain (moderate solar drought area), presenting an overall spatial differentiation pattern of “low in the west and high in the east, low in the north and high in the south”. This study can provide a scientific basis for the prediction and response to solar drought events in China under the background of climate change.
This study conducted climate data calibration, natural runoff reconstruction, and vegetation water requirement simulation. And a stochastic multi-objective water rights trading decision-making model was developed under multiple climate change scenarios to quantitatively assess effectiveness of cross-sectorial water rights trading on water management system in the Dagu River basin under climate change conditions in the future (2026—2055). The results are as follows: (1) Annual average natural runoff, water demand per unit of production scale in planting industry, and water demand per unit area of wetlands are the highest under SSP1-2.6 scenario and the lowest under SSP5-8.5 scenario. (2) Under multiple climate change scenarios, water rights trading mechanism is more effective than non-trading mechanism in alleviating water scarcity issues in river basins. From perspective of entire basin, water rights trading mechanism shows the most significant effect on alleviating water shortage under SSP5-8.5 scenario, with water deficit decreasing by 7.05%-14.59% compared with non-trading system. From the industry perspective, trading mechanism results in the greatest reduction in water scarcity for enterprises, followed by agriculture, fisheries, and livestock industry. Regarding regions, water deficit decreases in all four counties within the basin, with the most significant reduction in Laixi, where the average water deficit decreases by 6.90%-10.91% under multiple climate change scenarios. Meanwhile, 71% of river sections experienced a reduction in water shortage, while 29% saw an increase. (3) Under multiple climate change scenarios, water rights trading increases total water supply, system benefits, and efficiency of system by 0.72%-0.90%, 10.26%-11.05%, and 9.48%-10.06%, respectively. Under SSP5-8.5 scenario, the trading mechanism brings about the most significant increase in total water supply, system benefits, and system efficiency.
Based on CMIP6 climate model data and the MaxEnt model, this study systematically evaluates the evolution of suitable cultivation areas for single-cropping rice in the Jianghuai region during the climatic baseline period (1985-2014) and the future (2026-2100) under different scenarios, by coupling environmental factors such as soil, topography, and human activities. The results are as follows. (1) Through the “dual-index” mechanism combining collinearity testing and Jackknife method, 9 dominant factors were screened from 14 potential environmental factors, with a cumulative contribution rate of 94.4%. Model validation shows that the prediction accuracy of the optimized MaxEnt model was significantly improved (AUC=0.923), which is superior to the prediction accuracy reported in similar studies (e.g., 0.85-0.90). (2) The mean temperature during the entire growth period of single-cropping rice in the Jianghuai region shows a significant upward trend in the future, with the maximum warming rate under the SSP5-8.5 scenario (0.50℃/(10 a)). Precipitation generally shows an increasing trend, which is higher in the central and northern Jianghuai region than that in the south. (3) During the climatic baseline period, high-suitability areas are concentrated in the Yangtze River Delta and along-river plains, accounting for 21.7% of the total area, characterized by high proportion of paddy soil and superior hydrothermal conditions; medium-suitability areas are mainly located in the plains south of the Huaihe river, accounting for 26.2%; low-suitability areas are distributed in the Huaibei plain, accounting for 35.1%; non-suitability areas include the Dabie mountains and southern Anhui mountains, northwestern drylands, and urbanized areas, accounting for 17.1%. (4) In the future, the suitable areas show a trend of “eastern contraction and northern expansion”. In future periods, under the SSP5-8.5 scenario, the area of high-suitability areas will decrease by 3.8 percentage points, and that of low-suitability areas will increase by 6.6 percentage points. This evolution is mainly driven by the “double-edged sword” effect of climate warming: on one hand, northern Anhui (north of 32°N) becomes the main expansion area due to the increase of ≥10℃ accumulated temperature by 300-450℃·d and the extension of the growth period by 12-18 days; on the other hand, southern Jiangsu (south of 32°N) shows significant contraction under the stress of increased high-temperature days to 35-45 days, especially the probability of extreme high temperature during the critical growth stages (booting-heading stage) of rice increases by a factor of 3-5. It is proposed to enhance climate resilience through the breeding heat-tolerant varieties and optimizing planting layouts, providing a scientific basis for formulating regional agricultural adaptation strategies.
The Tibetan Plateau (TP) experienced a record-breaking concurrence of heatwave and drought in 2022. However, the impact of this compound hot-dry extreme event on vegetation growth and its underlying mechanisms remain unclear. Based on climate data and remote-sensing derived vegetation index during 2000—2022, changes in vegetation growth in response to this event were analyzed and the potential driving mechanisms were clarified. The compound hot-dry extreme event in 2022 significantly suppressed vegetation growth over the TP, with the growing season Normalized Difference Vegetation Index (NDVI) declined by 28% compared to the previous year. About 6% of the study area experienced severe suppression, ranking the third highest during the study period. Regions with remarkable NDVI decline were primarily located in the southern and northeastern parts of TP. Further analysis indicated that the unusually high temperatures and sufficient precipitation during April-May 2022 led to earlier spring phenology and accelerated soil moisture depletion. The subsequent summer drought and elevated temperatures further intensified soil moisture deficits through land-atmosphere feedbacks. Additionally, daily maximum temperatures during July-August notably surpassed the temperature optima for plant growth for over 90% of the study area. Collectively, these compound heat and drought stresses significantly suppressed vegetation growth in 2022. This research provides critical insights into the local ecological responses to climate change.
Climate change is promoting the global energy system to transition to renewable energy, but it brings new challenges along with the increase in emissions in the upstream and downstream of its industrial chain. From a global industry chains perspective, this study systematically investigated the dynamics and driving mechanisms of embodied carbon emissions in the renewable energy power generation sector using multi-regional input-output model (MRIO) and structural decomposition analysis (SDA), with a focus on the impact of trade linkages among key countries. Furthermore, the impact of uncertain information on accounting outcomes was examined. The results are as follows. (1) From 2016 to 2022, the global net transfer of CO2 in the renewable energy power generation sectors decreased by 2.49%. (2) Overall demand growth was the predominant factor driving the increase in embodied carbon emissions, the optimization effect of production structure played a significant role in reducing carbon emissions. (3) The carbon emission intensity effect of wind and solar thermal power generation sectors initially decreased before increasing, reflecting the intricate interplay between technological advancement and scale expansion. (4) Renewable energy power products in the upstream production stages of China, the United States, Germany, Mexico, and other countries saw significant increases. Notably, Germany, as an exporter, experienced a 70% rise in embodied carbon emissions within the renewable energy sector due to its exported products, underscoring the critical role of international trade in energy transition and carbon reduction. This study offers new insights into the complex role of renewable energy in the global energy transition and provides a scientific foundation for formulating precise emission reduction strategies.
The impact of methane emissions on global warming has attracted widespread attention worldwide. As a significant source of global methane emissions, the BRICS countries play a crucial role in global climate governance through their emission reduction efforts. Based on the EDGAR database, a quantitative analysis of methane emission characteristics in BRICS countries from 1970 to 2023 was conducted, the Tapio decoupling model was employed to examine the decoupling relationship between methane emissions and economic development, and future cooperation suggestions in methane management among BRICS countries by combining existing policies were proposed in this study. The results show that the BRICS countries have contributed over one-third to global methane emissions, showing an upward trend with an average annual growth rate in the past decade exceeding the global average. Overall, BRICS countries demonstrate weak decoupling between methane emissions and economic growth, indicating synchronized growth with faster economic expansion. However, Brazil and Russia have not shown a decoupling trend, where economic development still closely linked to methane emissions. Regarding emission structure, BRICS methane emissions primarily originated from energy activities (29.5%), agricultural activities (47.0%), waste management (20.3%), and other sectors (3.2%) in 2023. From 1970 to 2023, methane emission intensity in all BRICS countries showed declining trends, with China achieving the fastest reduction rate, while India maintained the lowest per capita emissions. Although BRICS members have not established specific mandatory methane reduction targets, their recent strengthened cooperation in climate change presents opportunities. To fully leverage the BRICS cooperation mechanism and amplify climate, environmental, and economic benefits of methane mitigation, systematic collaboration was proposed through establishing a methane reduction working group, enhancing policy coordination, promoting technology sharing, and expanding financial support, thereby advancing global methane governance.
Data were collected on more than 15.822 million flight movements at 271 civil aviation airports in China from 2022 to 2024. Based on the flight-by-flight, multi-stage carbon dioxide (CO2) emission accounting method recommended by the International Civil Aviation Organization (ICAO), a high spatiotemporal resolution carbon emission inventory for China’s civil aviation was constructed, systematically revealing the spatiotemporal evolution characteristics of carbon emissions from airports and flight routes. The results show that the CO2 emissions of China’s civil aviation were 56.467 million tons, 108.261 million tons, and 134.381 million tons in 2022, 2023, and 2024, respectively. Following the lifting of COVID-19 lockdown policies, China’s civil aviation carbon emissions surged by 91.7% year-on-year in 2023, significantly outpacing the average growth rate of global aviation carbon emissions over the same period. Nationwide, 84.5% of airports (218 airports) experienced an increase in carbon emissions, and all 16 core flight routes with annual CO2 emissions exceeding 300 thousand tons saw an increase of more than 130%. In 2024, the growth rate of aviation carbon emissions declined to 24.1%, yet 60.9% of airports (157 airports) still recorded an increase in emissions. Based on the emission inventory, a benchmark-based aviation allowance allocation method was proposed under an intensity management framework, defining airlines as compliance entities and using aircraft CO2 emissions per unit distance as the benchmark indicator. Under three scenarios of lenient, balanced, and strict regulation, the benchmark values for aviation allowance allocation in 2024 are set at 21.645, 20.844 and 19.927 t CO2/km, respectively. Under this framework, Air China, Hainan Airlines, and Shandong Airlines have relatively high allowance deficits, whereas Tianjin Airlines, Sichuan Airlines, and Shenzhen Airlines have relatively high allowance surpluses. This method effectively incentivizes low-emission-intensity airlines while constraining high-emission-intensity airlines without restricting the development of the aviation industry. Furthermore, it is highly compatible with the existing benchmark-based approach in China’s national carbon market, providing a reference for the design of aviation allowance allocation methods when the aviation sector is incorporated into the national carbon market.
Based on the CMIP6 dataset, the changes in China’s offshore photovoltaic power potential (PVP) were projected in the near-future (2021-2060) and far-future (2061-2100) compared to the historical period (1975-2014) under two typical scenarios, SSP1-2.6 and SSP5-8.5, and the potential impacts of climate change on future PVP were analyzed. The results are as followed. In the near-future period, the PVP potential under both scenarios shows a pattern of increasing in the northern part of the study area and decreasing in the southern part. The maximum increase in PVP under the SSP1-2.6 scenario is projected to increase by more than 3%, which is about 1.8 times higher than that under the SSP5-8.5 scenario. In the far-future period, the PVP shows an increase in almost the entire study area under the SSP1-2.6 scenario. In terms of monthly changes, PVP will increase throughout the year under the SSP1-2.6 scenario for both the near- and far- future, with the largest increases occurring in February 2.18% and 4.20%, respectively. Under the SSP5-8.5 scenario, both periods show negative changes in PVP from June to September, with the most significant decrease in August. The effect of surface downwelling shortwave radiation on PVP changes is greater than that of temperature and is the main cause of PVP changes. The results of the study provide an important reference for offshore solar energy development and utilization as well as energy planning and management.
Green Electricity Certificate (GEC) offers new economic incentives for rooftop photovoltaic (PV) projects, significantly enhancing investment attractiveness. Additionally, the inclusion of traded GEC electricity volumes in the government energy-saving evaluation metrics motivates local governments to advance renewable energy development. This study selected 100 cities across 9 provinces, integrating local meteorological conditions, rooftop area, electricity consumption load, and PV policies, to conduct simulation modeling and cost-benefit analysis for both commercial and residential buildings. The results indicate that GEC significantly improves the economic viability of rooftop PV projects, with 20% of cities transitioning from non-economical to economical status. The average net present value (NPV) across all cities increases by CNY 215 million, while the internal rate of return (IRR) and dynamic payback period (DPBP) also show improvements. Notably, residential buildings, due to their lower self-consumption rates and higher grid-fed electricity participating in GEC trading, experience more substantial revenue increases. From a regional perspective, economically underdeveloped areas, characterized by lower self-consumption rates, benefit more from GEC revenues, demonstrating that GEC can help narrow the economic disparity in rooftop PV adoption among cities and promote balanced regional renewable energy development. Additionally, local consumption of rooftop PV could contribute a median of 58.75% (1.25%-264.23%) of the non-hydro renewable energy consumption targets, highlighting the critical role of rooftop PV in achieving local renewable energy goals. Sensitivity analysis indicates that cities with lower self-consumption rates are more affected by GEC price fluctuations. This study provides a scientific basis for optimizing distributed PV deployment and achieving renewable energy consumption targets at the provincial level.