In the digital era,the development of the digital economy has gained significant practical importance for enhancing reductions in carbon dioxide(CO_(2))emissions.However,existing studies must clarify the key“hidden”...In the digital era,the development of the digital economy has gained significant practical importance for enhancing reductions in carbon dioxide(CO_(2))emissions.However,existing studies must clarify the key“hidden”mechanisms driving actual changes in CO_(2)emissions.Although both the digital economy and CO_(2)emissions are widely researched topics,previous literature has rarely provided an explicit examination of their underlying mechanisms.This study conducts a detailed literature review and finds that the digital economy affects CO_(2)emissions through four main channels:technical,structural,resource allocation,and spatial spillover.However,these channels should not be examined independently due to their interactive effects.Moreover,each of these four channels can be further subdivided,making it essential to explore the subpaths and interconnections among them.By offering a more nuanced understanding of how the digital economy contributes to CO_(2)emissions reduction,this study provides valuable insights that can inform strategic policy development.展开更多
High-efficiency hydrogen production through photoelectrochemical(PEC)water splitting has emerged as a promising solution to address current global energy challenges.Ⅲ-nitride semiconductor photoelectrodes with nanost...High-efficiency hydrogen production through photoelectrochemical(PEC)water splitting has emerged as a promising solution to address current global energy challenges.Ⅲ-nitride semiconductor photoelectrodes with nanostructures have demonstrated great potential in the near future due to their high light absorption,tunable direct band gap,and strong physicochemical stability.However,several issues,including surface trapping centers,surface Fermi level pinning,and surface band bending,need to be addressed.In this work,enhanced photovoltaic properties have been achieved using gallium nitride(GaN)nanowires(NWs)photoelectrodes by adopting an alkaline solution surface treatment method to reduce the surface states.It was found that surface oxides on NWs can be removed by an alkaline solution treatment without changing the surface morphology through X-ray photoelectron spectroscopy(XPS),scanning electron microscopy(SEM)and other characterization methods.These findings provide new insights to the development of high-efficiency photoelectrodes for new energy source applications.展开更多
To meet the demands for seamless medium-and short-range weather forecasting during the Beijing Winter Olympics(2022),the Winter Olympics research team at the Earth System Modeling and Prediction Centre(CEMC)of the Chi...To meet the demands for seamless medium-and short-range weather forecasting during the Beijing Winter Olympics(2022),the Winter Olympics research team at the Earth System Modeling and Prediction Centre(CEMC)of the China Meteorological Administration(CMA)developed an integrated global and regional numerical weather prediction(NWP)model system.In support of the Winter Olympics,the system focuses on key short-and medium-range deterministic and ensemble forecast technologies for complex terrain.By introducing a three-dimensional reference atmosphere and a predictor-corrector iterative algorithm into the regional model's dynamical framework,the team enhanced the spatial accuracy and temporal integration stability of the high-resolution regional model.The team also developed data assimilation techniques for dense surface automatic weather stations and high spatiotemporal resolution imagery from China's Fengyun satellites,improving the monitoring and application capability of unconventional observations for the Winter Olympics.Furthermore,they established a3 km high-resolution regional ensemble prediction system by advancing multiscale hybrid initial perturbation techniques and stochastic perturbation methods for physical processes with spatiotemporal correlations,suitable for complex terrain.To enhance deterministic and probabilistic forecasts at grid and station scales over complex terrain,the team studied bias correction techniques across different resolutions and developed methods for rapidly and effectively extracting key forecast information from large volumes of model output.In particular,machine learning-based approaches were employed to process and fuse massive forecast products containing probabilistic information.These efforts led to the development of a seamless Winter Olympics meteorological forecasting system covering a lead time of 0–15 days and the entire competition zone,featuring forecast updates every hour within 24 h,every 3 h within 24–72 h,and every 12 h within 72–360 h.These products were applied comprehensively in real-time operations during the winter training,test events,and the Olympic and Paralympic Games,representing the highest level of China's independently developed NWP systems in meteorological support for major events.The integrated technological achievements have since been incorporated into the national operational NWP system,and they continue to play a vital role in daily forecasting services,disaster prevention and mitigation,and support for major events.展开更多
Abundant probability information from ensemble forecasting has been used to forecast extreme weather such as extremely high/low temperatures.In this study,leveraging the Convection Permitting Ensemble Forecasting Syst...Abundant probability information from ensemble forecasting has been used to forecast extreme weather such as extremely high/low temperatures.In this study,leveraging the Convection Permitting Ensemble Forecasting System(CPEFS)of North China rather than coarse-resolution global ensemble forecast systems as in previous studies,based on the Anderson-Darling(A-D)test principle,we built an Extreme Weather Forecast Index(EFI)for temperature to forecast extreme temperature events over North China.Using the CPEFS's 3-yr historical forecast data,a cumulative distribution function(CDF)for temperature in North China was constructed,establishing a refined model climate capable of identifying extreme temperatures with geographical specific features.The temperature EFI was formulated to reflect differences between the ensemble forecast CDF and the model climate CDF,which can be used to forecast extreme temperatures.We conducted simulation experiments for extremely high(low)temperatures in summer(winter)2023.The results demonstrate that the EFI warning signals for extreme temperature aligned reasonably with the automatic station observations.It is found that the optimal EFI thresholds are 0.7 or 0.8(-0.8)for extremely high(low)temperatures.When applying the EFI thresholds to the extreme temperature events in China in 2023,EFI showed a strong skill at the 2-day lead time.However,the forecast accuracy decreased as the forecast lead time extended.Comparison between global ensemble-based EFI and CPEFS-based EFI reveals that high-resolution ensemble-based EFI products could in general achieve a better performance,providing strong warning signals and more refined geographical distributions.展开更多
Summary What is already known about this topic?Long-term temperature variability(TV)has been examined to be associated with cardiovascular disease(CVD).TV-related dyslipidemia helps us understand the mechanism of how ...Summary What is already known about this topic?Long-term temperature variability(TV)has been examined to be associated with cardiovascular disease(CVD).TV-related dyslipidemia helps us understand the mechanism of how climate change affects CVD.What is added by this report?Based on the China Health and Retirement Longitudinal Study(CHARLS)from 2011 to 2018,this study estimated the long-term effect of TV on dyslipidemia in middle-aged and elderly adults.展开更多
This paper describes a fire forecast system—Weather Research and Forecasting-Fire(WRF-Fire)—that is employed to simulate a real wildfire case in Xichang,Sichuan Province,Southwest China on 30 March 2020 at a 100-m r...This paper describes a fire forecast system—Weather Research and Forecasting-Fire(WRF-Fire)—that is employed to simulate a real wildfire case in Xichang,Sichuan Province,Southwest China on 30 March 2020 at a 100-m resolution over the fire area,in order to provide a fine representation of the terrain and fuel heterogeneities and explicitly resolve the atmospheric turbulence.Four sensitivity experiments were conducted to analyze the impacts of atmospheric model grid spacing and fire–atmosphere interaction on simulated meteorological fields and fire behavior.The results indicate that finer horizontal grid spacing in the atmospheric model improves the accuracy of wind,temperature,and moisture simulations in the near surface layer.Especially,it can better describe local wind field characteristics,capture microscale wind speed fluctuations,and produce more significant effect from fire–atmosphere interaction.The mass and energy released by the fire model and its feedback to the atmospheric model exhibit enhanced heterogeneous characteristics.The simulated fire area aligns well with the observation,with KAPPA coefficient(KC)of 0.56–0.59 and spatial correlation coefficient(SC) of 0.52–0.59.For this real case,the influence of heterogeneous land surface on the fire behavior is much greater than the atmosphere–fire interaction.The study suggests that WRFFire holds high potential as a real wildfire simulation tool,offering a new and feasible approach for fire prediction.展开更多
基金financial support from the National Natural Science Foundation of China[Grant No.72274159].
文摘In the digital era,the development of the digital economy has gained significant practical importance for enhancing reductions in carbon dioxide(CO_(2))emissions.However,existing studies must clarify the key“hidden”mechanisms driving actual changes in CO_(2)emissions.Although both the digital economy and CO_(2)emissions are widely researched topics,previous literature has rarely provided an explicit examination of their underlying mechanisms.This study conducts a detailed literature review and finds that the digital economy affects CO_(2)emissions through four main channels:technical,structural,resource allocation,and spatial spillover.However,these channels should not be examined independently due to their interactive effects.Moreover,each of these four channels can be further subdivided,making it essential to explore the subpaths and interconnections among them.By offering a more nuanced understanding of how the digital economy contributes to CO_(2)emissions reduction,this study provides valuable insights that can inform strategic policy development.
基金funded by the National Key R&D Program of China(No.2021YFB3601600)Innovation Support Programme(Soft Science Research)Project Achievements of Jiangsu Province(No.BK20231514)+3 种基金the National Nature Science Foundation of China(Nos.61974062,62004104)the Leading-edge Technology Program of Jiangsu Natural Science Foundation(No.BE2021008–2)The Fundamental Research Foundation for the Central UniversitiesCollaborative Innovation Center of Solid-State Lighting and Energy-Saving Electronics。
文摘High-efficiency hydrogen production through photoelectrochemical(PEC)water splitting has emerged as a promising solution to address current global energy challenges.Ⅲ-nitride semiconductor photoelectrodes with nanostructures have demonstrated great potential in the near future due to their high light absorption,tunable direct band gap,and strong physicochemical stability.However,several issues,including surface trapping centers,surface Fermi level pinning,and surface band bending,need to be addressed.In this work,enhanced photovoltaic properties have been achieved using gallium nitride(GaN)nanowires(NWs)photoelectrodes by adopting an alkaline solution surface treatment method to reduce the surface states.It was found that surface oxides on NWs can be removed by an alkaline solution treatment without changing the surface morphology through X-ray photoelectron spectroscopy(XPS),scanning electron microscopy(SEM)and other characterization methods.These findings provide new insights to the development of high-efficiency photoelectrodes for new energy source applications.
基金supported by the National Natural Science Foundation of China(NSFC)Major Program(Grant No.42090032)NSFC Projects(Grant Nos.42475169,42175012)the Science and Technology Winter Olympics Special Subject(Grant No.2018YFF0300103)。
文摘To meet the demands for seamless medium-and short-range weather forecasting during the Beijing Winter Olympics(2022),the Winter Olympics research team at the Earth System Modeling and Prediction Centre(CEMC)of the China Meteorological Administration(CMA)developed an integrated global and regional numerical weather prediction(NWP)model system.In support of the Winter Olympics,the system focuses on key short-and medium-range deterministic and ensemble forecast technologies for complex terrain.By introducing a three-dimensional reference atmosphere and a predictor-corrector iterative algorithm into the regional model's dynamical framework,the team enhanced the spatial accuracy and temporal integration stability of the high-resolution regional model.The team also developed data assimilation techniques for dense surface automatic weather stations and high spatiotemporal resolution imagery from China's Fengyun satellites,improving the monitoring and application capability of unconventional observations for the Winter Olympics.Furthermore,they established a3 km high-resolution regional ensemble prediction system by advancing multiscale hybrid initial perturbation techniques and stochastic perturbation methods for physical processes with spatiotemporal correlations,suitable for complex terrain.To enhance deterministic and probabilistic forecasts at grid and station scales over complex terrain,the team studied bias correction techniques across different resolutions and developed methods for rapidly and effectively extracting key forecast information from large volumes of model output.In particular,machine learning-based approaches were employed to process and fuse massive forecast products containing probabilistic information.These efforts led to the development of a seamless Winter Olympics meteorological forecasting system covering a lead time of 0–15 days and the entire competition zone,featuring forecast updates every hour within 24 h,every 3 h within 24–72 h,and every 12 h within 72–360 h.These products were applied comprehensively in real-time operations during the winter training,test events,and the Olympic and Paralympic Games,representing the highest level of China's independently developed NWP systems in meteorological support for major events.The integrated technological achievements have since been incorporated into the national operational NWP system,and they continue to play a vital role in daily forecasting services,disaster prevention and mitigation,and support for major events.
基金Supported by the National Natural Science Foundation of China(U2242213)。
文摘Abundant probability information from ensemble forecasting has been used to forecast extreme weather such as extremely high/low temperatures.In this study,leveraging the Convection Permitting Ensemble Forecasting System(CPEFS)of North China rather than coarse-resolution global ensemble forecast systems as in previous studies,based on the Anderson-Darling(A-D)test principle,we built an Extreme Weather Forecast Index(EFI)for temperature to forecast extreme temperature events over North China.Using the CPEFS's 3-yr historical forecast data,a cumulative distribution function(CDF)for temperature in North China was constructed,establishing a refined model climate capable of identifying extreme temperatures with geographical specific features.The temperature EFI was formulated to reflect differences between the ensemble forecast CDF and the model climate CDF,which can be used to forecast extreme temperatures.We conducted simulation experiments for extremely high(low)temperatures in summer(winter)2023.The results demonstrate that the EFI warning signals for extreme temperature aligned reasonably with the automatic station observations.It is found that the optimal EFI thresholds are 0.7 or 0.8(-0.8)for extremely high(low)temperatures.When applying the EFI thresholds to the extreme temperature events in China in 2023,EFI showed a strong skill at the 2-day lead time.However,the forecast accuracy decreased as the forecast lead time extended.Comparison between global ensemble-based EFI and CPEFS-based EFI reveals that high-resolution ensemble-based EFI products could in general achieve a better performance,providing strong warning signals and more refined geographical distributions.
基金Supported by from National Natural Science Foundation Project of China(81872590 and 41761144056).
文摘Summary What is already known about this topic?Long-term temperature variability(TV)has been examined to be associated with cardiovascular disease(CVD).TV-related dyslipidemia helps us understand the mechanism of how climate change affects CVD.What is added by this report?Based on the China Health and Retirement Longitudinal Study(CHARLS)from 2011 to 2018,this study estimated the long-term effect of TV on dyslipidemia in middle-aged and elderly adults.
基金Supported by the National Key Research and Development Program of China (2022YFC3004105)National Natural Science Foundation of China (42275201)。
文摘This paper describes a fire forecast system—Weather Research and Forecasting-Fire(WRF-Fire)—that is employed to simulate a real wildfire case in Xichang,Sichuan Province,Southwest China on 30 March 2020 at a 100-m resolution over the fire area,in order to provide a fine representation of the terrain and fuel heterogeneities and explicitly resolve the atmospheric turbulence.Four sensitivity experiments were conducted to analyze the impacts of atmospheric model grid spacing and fire–atmosphere interaction on simulated meteorological fields and fire behavior.The results indicate that finer horizontal grid spacing in the atmospheric model improves the accuracy of wind,temperature,and moisture simulations in the near surface layer.Especially,it can better describe local wind field characteristics,capture microscale wind speed fluctuations,and produce more significant effect from fire–atmosphere interaction.The mass and energy released by the fire model and its feedback to the atmospheric model exhibit enhanced heterogeneous characteristics.The simulated fire area aligns well with the observation,with KAPPA coefficient(KC)of 0.56–0.59 and spatial correlation coefficient(SC) of 0.52–0.59.For this real case,the influence of heterogeneous land surface on the fire behavior is much greater than the atmosphere–fire interaction.The study suggests that WRFFire holds high potential as a real wildfire simulation tool,offering a new and feasible approach for fire prediction.
