On-Chip Micro Temperature Controllers Based on Freestanding Thermoelectric Nano Films for Low-Power Electronics

Multidimensional integration and multifunctional com-ponent assembly have been greatly explored in recent years to extend Moore’s Law of modern microelectronics.However,this inevitably exac-erbates the inhomogeneity of temperature distribution in microsystems,making precise temperature control for electronic components extremely challenging.Herein,we report an on-chip micro temperature controller including a pair of thermoelectric legs with a total area of 50×50μm^(2),which are fabricated from dense and flat freestanding Bi2Te3-based ther-moelectric nano films deposited on a newly developed nano graphene oxide membrane substrate.Its tunable equivalent thermal resistance is controlled by electrical currents to achieve energy-efficient temperature control for low-power electronics.A large cooling temperature difference of 44.5 K at 380 K is achieved with a power consumption of only 445μW,resulting in an ultrahigh temperature control capability over 100 K mW^(-1).Moreover,an ultra-fast cooling rate exceeding 2000 K s^(-1) and excellent reliability of up to 1 million cycles are observed.Our proposed on-chip temperature controller is expected to enable further miniaturization and multifunctional integration on a single chip for microelectronics.

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

Record-breaking High-temperature Outlook for 2023: An Assessment Based on the China Global Merged Temperature(CMST) Dataset

According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since the period of instrumental observation began, being only slightly lower than the values recorded in 2016 and 2020, and historically record-breaking GMST emerged from May to July 2023. Further analysis also indicates that if the surface temperature in the last five months of 2023 approaches the average level of the past five years, the annual average surface temperature anomaly in 2023 of approximately 1.26°C will break the previous highest surface temperature, which was recorded in 2016of approximately 1.25°C(both values relative to the global pre-industrialization period, i.e., the average value from 1850 to1900). With El Ni?o triggering a record-breaking hottest July, record-breaking average annual temperatures will most likely become a reality in 2023.

Effect of sample temperature on femtosecond laser ablation of copper

We conduct an experimental study supported by theoretical analysis of single laser ablating copper to investigate the interactions between laser and material at different sample temperatures,and predict the changes of ablation morphology and lattice temperature.For investigating the effect of sample temperature on femtosecond laser processing,we conduct experiments on and simulate the thermal behavior of femtosecond laser irradiating copper by using a two-temperature model.The simulation results show that both electron peak temperature and the relaxation time needed to reach equilibrium increase as initial sample temperature rises.When the sample temperature rises from 300 K to 600 K,the maximum lattice temperature of the copper surface increases by about 6500 K under femtosecond laser irradiation,and the ablation depth increases by 20%.The simulated ablation depths follow the same general trend as the experimental values.This work provides some theoretical basis and technical support for developing femtosecond laser processing in the field of metal materials.

Temperature inversion enables superior stability for low-temperature Zn-ion batteries

It is challenging for aqueous Zn-ion batteries(ZIBs)to achieve comparable low-temperature(low-T)performance due to the easy-frozen electrolyte and severe Zn dendrites.Herein,an aqueous electrolyte with a low freezing point and high ionic conductivity is proposed.Combined with molecular dynamics simulation and multi-scale interface analysis(time of flight secondary ion mass spectrometry threedimensional mapping and in-situ electrochemical impedance spectroscopy method),the temperature independence of the V_(2)O_(5)cathode and Zn anode is observed to be opposite.Surprisingly,dominated by the solvent structure of the designed electrolyte at low temperatures,vanadium dissolution/shuttle is significantly inhibited,and the zinc dendrites caused by this electrochemical crosstalk are greatly relieved,thus showing an abnormal temperature inversion effect.Through the disclosure and improvement of the above phenomena,the designed Zn||V_(2)O_(5)full cell delivers superior low-T performance,maintaining almost 99%capacity retention after 9500 cycles(working more than 2500 h)at-20°C.This work proposes a kind of electrolyte suitable for low-T ZIBs and reveals the inverse temperature dependence of the Zn anode,which might offer a novel perspective for the investigation of low-T aqueous battery systems.

The Effects of Thickness and Location of PCMon the Building’s Passive Temperature-Control–A Numerical Study

Building energy consumption and building carbon emissions both account for more than 20%of their total national values in China.Building employing phase change material(PCM)for passive temperature control shows a promising prospect in meeting the comfort demand and reducing energy consumption simultaneously.However,there is a lack of more detailed research on the interaction between the location and thickness of PCM and indoor natural convection,as well as indoor temperature distribution.In this study,the numerical model of a passive temperature-controlled building integrating the developed PCM module is established with the help of ANSYS.In which,the actual weather condition of Beijing city is set as the boundary conditions and the indoor natural convection is simulated with the consideration of radiation model.The effects of PCM’s thickness and location on the internal temperature field are analyzed and discussed.The results show that the room could maintain within the human comfort temperature range with the longest ratio of 94.10%and the shortest ratio of 51.04%as integrating PCM.In comparison,the value is only 26.70%without PCM.The room’s maximum temperature fluctuation can also be improved;it could be lowered by 64.4%compared to the normal condition.When the quantity of PCM is sufficient,further increasing the PCM amount results in a temperature fluctuation reduction of less than 0.1°C and does not increase the comfort time.Placing PCM on the wall induces an apparent variation in indoor temperature along the vertical direction.Conversely,placing PCM on the roof can lead to a heat transfer rate difference of up to seven times.The optimal placement of PCM depends on the difference between the environmental and phase change temperatures.If the difference is positive,placing PCM on the roof is more effective;conversely,the opposite holds.According to the results over the entire cycle,PCM application on vertical walls yields better performance.The significant difference in natural convection caused by the same thickness of PCM but different application positions,coupled with the influence of air movement on the melting and solidification of PCM,further impacts indoor temperature fluctuations and comfort.This study can provide guidance for the application location and thickness of PCM,especially for scenarios where temperature regulation is required at a specific time.

Assessment of the Spatio-Temporal Trends of Annual Extreme Temperature Indices over Tanzania during the Period of 1982-2022

Extreme weather and climatic phenomena, such as heatwaves, cold waves, floods and droughts, are expected to become more common and have a significant impact on ecosystems, biodiversity, and society. Devastating disasters are mostly caused by record-breaking extreme events, which are becoming more frequent throughout the world, including Tanzania. A clear global signal of an increase in warm days and nights and a decrease in cold days and nights has been observed. The present study assessed the trends of annual extreme temperature indices during the period of 1982 to 2022 from 29 meteorological stations in which the daily minimum and maximum data were obtained from NASA/POWER. The Mann-Kendall and Sen slope estimator were employed for trend analysis calculation over the study area. The analyzed data have indicated for the most parts, the country has an increase in warm days and nights, extreme warm days and nights and a decrease in cold days and nights, extreme cold days and nights. It has been disclosed that the number of warm nights and days is on the rise, with the number of warm nights trending significantly faster than the number of warm days. The percentile-based extreme temperature indices exhibited more noticeable changes than the absolute extreme temperature indices. Specifically, 66% and 97% of stations demonstrated positive increasing trends in warm days (TX90p) and nights (TN90p), respectively. Conversely, the cold indices demonstrated 41% and 97% negative decreasing trends in TX10p and TN10p, respectively. The results are seemingly consistent with the observed temperature extreme trends in various parts of the world as indicated in IPCC reports.

Temperature-Based Fan Speed Optimization Strategy

As energy efficiency and indoor comfort increasingly become key standards in modern residential and office environments,research on intelligent fan speed control systems has become particularly important.This study aims to develop a temperature-feedback-based fan speed optimization strategy to achieve higher energy efficiency and user comfort.Firstly,by analyzing existing fan speed control technologies,their main limitations are identified,such as the inability to achieve smooth speed transitions.To address this issue,a BP-PID speed control algorithm is designed,which dynamically adjusts fan speed based on indoor temperature changes.Experimental validation demonstrates that the designed system can achieve smooth speed transitions compared to traditional fan systems while maintaining stable indoor temperatures.Furthermore,the real-time responsiveness of the system is crucial for enhancing user comfort.Our research not only demonstrates the feasibility of temperature-based fan speed optimization strategies in both theory and practice but also provides valuable insights for energy management in future smart home environments.Ultimately,this research outcome will facilitate the development of smart home systems and have a positive impact on environmental sustainability.

Study on Temperature Disaster Indicators of Passion Fruit in Southwest Fujian, China

In China, meteorological forecasting relies on meteorological data obtained from regional and national stations. However, there were discrepancies between the data collected from the meteorological station at the passion fruit growing base and the data from regional and national stations. Consequently, the high and low temperature disaster indicators determined by the meteorological station at the passion fruit growing base cannot be applied to meteorological forecasting. To address this issue and facilitate the monitoring and early warning of high and low temperature disasters in passion fruit cultivation in Fujian, China, we used multi-source hourly temperature data (including the data from meteorological observation stations in passion fruit growing bases, the nearest regional stations, and national surface conventional meteorological observation stations) in three cities in southwestern Fujian (Longyan, Sanming, and Zhangzhou) spanning the years 2020 to 2022. By employing comprehensive statistical analysis methods (0.5 interval division and Cumulative frequency), we identified that passion fruit in southwestern Fujian was susceptible to high temperature disasters during the blooming-fruiting period, as well as low temperature disasters during the sprouting period. Consequently, we developed high and low temperature disaster indicators based on data from regional and national stations for different phenological periods of passion fruit in this region.

Development of a RBFNN prediction model for carrot quality based on meteorological temperatures at vegetable stations

To evaluate and predict the quality of carrots during logistics process in North China under extreme temperature conditions,quality indicator changes of carrots were investigated,and temperature-coupled quality prediction models were developed.Seven temperatures were selected from meteorological temperature data by cluster analysis to simulate the changes in extreme temperatures during the short-term transportation of carrots.No carrots rotted during the 48h storage period.Under both isothermal and nonisothermal conditions,weight loss andΔE increased while the firmness and sensory evaluation(SE)decreased.The RBFNN performed better than the Arrhenius model in predicting weight loss andΔE,with R^(2)>0.97,MSE<0.009 and relative errors within±18%.The results of the predictive confidence level and standardized residual indicated the good performance of the RBFNN model.The temperature-coupled prediction models of RBFNN were promising candidates for predicting the quality of vegetable products and therefore reducing economic loss of vegetable industry.

Competitive oxidation behavior of Ni-based superalloy GH4738 at extreme temperature

A high thrust-to-weight ratio poses challenges to the high-temperature performance of Ni-based superalloys. The oxidation behavior of GH4738 at extreme temperatures has been investigated by isothermal and non-isothermal experiments. As a result of the competitive diffusion of alloying elements, the oxide scale included an outermost porous oxide layer (OOL), an inner relatively dense oxide layer (IOL), and an internal oxide zone (IOZ), depending on the temperature and time. A high temperature led to the formation of large voids at the IOL/IOZ interface. At 1200℃, the continuity of the Cr-rich oxide layer in the IOL was destroyed, and thus, spallation occurred. Extension of oxidation time contributed to the size of Al-rich oxide particles with the increase in the IOZ. Based on this finding,the oxidation kinetics of GH4738 was discussed, and the corresponding oxidation behavior at 900-1100℃ was predicted.

A bHLH transcription factor,CsSPT,regulates high-temperature resistance in cucumber

High-temperature stress threatens the growth and yield of crops. Basic helix-loop-helix(bHLH) transcription factors(TFs) have been shown to play important roles in regulating high-temperature resistance in plants. However, the bHLH TFs responsible for high-temperature tolerance in cucumbers have not been identified. We used transcriptome profiling to screen the high temperature-responsive candidate bHLH TFs in cucumber. Here, we found that the expression of 75 CsbHLH genes was altered under high-temperature stress. The expression of the CsSPT gene was induced by high temperatures in TT(Thermotolerant) cucumber plants. However, the Csspt mutant plants obtained by the CRISPR-Cas9 system showed severe thermosensitive symptoms, including wilted leaves with brown margins and reduced root density and cell activity.The Csspt mutant plants also exhibited elevated H_(2)O_(2) levels and down-regulated photosystem-related genes under normal conditions.Furthermore, there were high relative electrolytic leakage(REC), malondialdehyde(MDA), glutathione(GSH), and superoxide radical(O_(2)^(·-)) levels in the Csspt mutant plants, with decreased Proline content after the high-temperature treatment. Transcriptome analysis showed that the photosystem and chloroplast activities in Csspt mutant plants were extremely disrupted by the high-temperature stress compared with wildtype(WT) plants. Moreover, the plant hormone signal transduction, as well as MAPK and calcium signaling pathways were activated in Csspt mutant plants under high-temperature stress. The HSF and HSP family genes shared the same upregulated expression patterns in Csspt and WT plants under high-temperature conditions. However, most bHLH, NAC, and bZIP family genes were significantly down-regulated by heat in Csspt mutant plants. Thus, these results demonstrated that CsSPT regulated the high-temperature response by recruiting photosynthesis components, signaling pathway molecules, and transcription factors. Our results provide important insights into the heat response mechanism of CsSPT in cucumber and its potential as a target for breeding heat-resistant crops.

Machine learning-assisted efficient design of Cu-based shape memory alloy with specific phase transition temperature

The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical significance.In this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored data.Component modeling and feature modeling were used to predict the phase transition temperature of the shape memory alloys.The experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)model.The results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition temperature.On this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between atoms.This work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.

Low-energy-consumption temperature swing system for CO_(2) capture by combining passive radiative cooling and solar heating

Temperature-swing adsorption(TSA)is an effective technique for CO_(2) capture,but the temperature swing procedure is energy-intensive.Herein,we report a low-energy-consumption system by combining passive radiative cooling and solar heating for the uptake of CO_(2) on commercial activated carbons(CACs).During adsorption,the adsorbents are coated with a layer of hierarchically porous poly(vinylidene fluoride-co-hexafluoropropene)[P(VdF-HFP)HP],which cools the adsorbents to a low temperature under sunlight through radiative cooling.For desorption,CACs with broad absorption of the solar spectrum are exposed to light irradiation for heating.The heating and cooling processes are completely driven by solar energy.Adsorption tests under mimicked sunlight using the CACs show that the performance of this system is comparable to that of the traditional ones.Furthermore,under real sunlight irradiation,the adsorption capacity of the CACs can be well maintained after multiple cycles.The present work may inspire the development of new temperature swing procedures with little energy consumption.

Photoperiod Mediates the Effects of Temperature and Light Intensity on the Proliferation of Ulva prolifera

In order to study the complex effects of photoperiod,temperature,and light intensity on the spore maturation and release number of Ulva prolifera,we cultured thalli segment(2–3 mm)under three different photoperiods(L:D=12:12,14:10 and 10:14),temperature(15℃(LT),25℃(MT)and 30℃(HT))and light intensity(100,200 and 400μmol m^(−2)s^(−1),noted as LL,ML and HL,respectively)conditions.Then the maturation time,spore release number and chlorophyll fluorescence were analyzed.The results suggested that:1)The spore maturation time was accelerated by higher temperature or higher light intensity from 62 h to 36 h,and changes in day length accelerated the spore maturation to a certain extent as compared with 12:12 light/dark cycle;2)Higher light intensity significantly decreased the chlorophyll fluorescence(Fv′/Fm′,NPQ,rETRmax andα)of the mature reproductive segment under 30℃with 12:12 light/dark cycle.But when in the other photoperiods(10:14 and 14:10 conditions),the inhibitory effects of high light intensity were alleviated significantly;3)The optimum condition for the spore maturation and release was 12:12 light/dark cycle,25℃,400μmol m^(−2)s^(−1),with both shorter and longer photoperiod reducing the spore release number;4)Higher light intensity significantly increased the spore release number under 25℃,but these effects were alleviated by 30℃treatment.This study is the first attempt to elucidate the coincidence effects of photoperiod,temperature and light intensity on the reproduction of Ulva,which would help to reveal the mechanism of the rapid proliferation of green tide.

Alkyl dimethyl betaine activates the low-temperature collection capacity of sodium oleate for scheelite

The impact of alkyl dimethyl betaine (ADB) on the collection capacity of sodium oleate (NaOl) at low temperatures was evaluated using flotation tests at various scales. The low-temperature synergistic mechanism of ADB and NaOl was explored by infrared spectroscopy, X-ray photoelectron spectroscopy, surface tension measurement, foam performance test, and flotation reagent size measurement.The flotation tests revealed that the collector mixed with octadecyl dimethyl betaine (ODB) and NaOl in a mass ratio of 4:96 exhibited the highest collection capacity. The combined collector could increase the scheelite recovery by 3.48% at low temperatures of 8–12℃. This is particularly relevant in the Luanchuan area, which has the largest scheelite concentrate output in China. The results confirmed that ODB enhanced the collection capability of NaOl by improving the dispersion and foaming performance. Betaine can be introduced as an additive to NaOl to improve the recovery of scheelite at low temperatures.

Dietary fat supplementation relieves cold temperature-induced energy stress through AMPK-mediated mitochondrial homeostasis in pigs

Background Cold stress has negative effects on the growth and health of mammals, and has become a factor restricting livestock development at high latitudes and on plateaus. The gut-liver axis is central to energy metabolism, and the mechanisms by which it regulates host energy metabolism at cold temperatures have rarely been illustrated. In this study, we evaluated the status of glycolipid metabolism and oxidative stress in pigs based on the gut-liver axis and propose that AMP-activated protein kinase(AMPK) is a key target for alleviating energy stress at cold temperatures by dietary fat supplementation.Results Dietary fat supplementation alleviated the negative effects of cold temperatures on growth performance and digestive enzymes, while hormonal homeostasis was also restored. Moreover, cold temperature exposure increased glucose transport in the jejunum. In contrast, we observed abnormalities in lipid metabolism, which was characterized by the accumulation of bile acids in the ileum and plasma. In addition, the results of the ileal metabolomic analysis were consistent with the energy metabolism measurements in the jejunum, and dietary fat supplementation increased the activity of the mitochondrial respiratory chain and lipid metabolism. As the central nexus of energy metabolism, the state of glycolipid metabolism and oxidative stress in the liver are inconsistent with that in the small intestine. Specifically, we found that cold temperature exposure increased glucose transport in the liver, which fully validates the idea that hormones can act on the liver to regulate glucose output. Additionally, dietary fat supplementation inhibited glucose transport and glycolysis, but increased gluconeogenesis, bile acid cycling, and lipid metabolism. Sustained activation of AMPK, which an energy receptor and regulator, leads to oxidative stress and apoptosis in the liver;dietary fat supplementation alleviates energy stress by reducing AMPK phosphorylation.Conclusions Cold stress reduced the growth performance and aggravated glycolipid metabolism disorders and oxidative stress damage in pigs. Dietary fat supplementation improved growth performance and alleviated cold temperature-induced energy stress through AMPK-mediated mitochondrial homeostasis. In this study, we high-light the importance of AMPK in dietary fat supplementation-mediated alleviation of host energy stress in response to environmental changes.

Timing effect of high temperature exposure on the plasticity of internode and plant architecture in maize

The occurrence of high temperature(HT)in crop production is becoming more frequent and unpredictable with global warming,severely threatening food security.The state of an organ’s growth and development is largely determined by the temperature conditions it is exposed to over time.Maize is the main cereal crop,and its stem growth and plant architecture are closely related to lodging resistance,and especially sensitive to temperature.However,systematic research on the timing effect of HT on the sequentially developing internode and stem is currently lacking.To identify the timing effect of HT on the morphology and plasticity of the stem in maize,two hybrids(Zhengdan 958(ZD958),Xianyu 335(XY335))characterized by distinct morphological traits in the stem were exposed to a 7-day HT treatment from the V6 to V17 stages(Vn presents the vegetative stage with n leaves fully expanded)in 2019-2020.The results demonstrated that exposure to HT during V6-V12 accelerated the rapid elongation of stems.For instance,HT occurring at V7 and V12 specifically promoted the lengths and weights of the 3rd-5th and 9th-11th internodes,respectively.Meanwhile,HT slowed the growth of internodes adjacent to the promoted internodes.Interestingly,compared with control,the plant height was significantly increased soon after HT treatment,but the promotion effect became narrower at the subsequent flowering stage,demonstrating a self-adjusting mechanism in the maize plant in response to HT.Importantly,HT altered the plant architectures,including a rising of the ear position and increase in the ear position coefficient.XY335 exhibited greater sensitivity in stem development than ZD958 under HT treatment.These findings improve our systematic understanding of the plasticity of internode and plant architecture in response to the timing of HT exposure.

Diphylleia Grayi-Inspired Intelligent Temperature-Responsive Transparent Nanofiber Membranes

Nanofiber membranes(NFMs) have become attractive candidates for next-generation flexible transparent materials due to their exceptional flexibility and breathability. However, improving the transmittance of NFMs is a great challenge due to the enormous reflection and incredibly poor transmission generated by the nanofiber-air interface. In this research, we report a general strategy for the preparation of flexible temperature-responsive transparent(TRT) membranes,which achieves a rapid transformation of NFMs from opaque to highly transparent under a narrow temperature window. In this process, the phase change material eicosane is coated on the surface of the polyurethane nanofibers by electrospray technology. When the temperature rises to 37 ℃, eicosane rapidly completes the phase transition and establishes the light transmission path between the nanofibers, preventing light loss from reflection at the nanofiber-air interface. The resulting TRT membrane exhibits high transmittance(> 90%), and fast response(5 s). This study achieves the first TRT transition of NFMs, offering a general strategy for building highly transparent nanofiber materials, shaping the future of next-generation intelligent temperature monitoring, anti-counterfeiting measures, and other high-performance devices.

Evaluation and Projection of Population Exposure to Temperature Extremes over the Beijing−Tianjin−Hebei Region Using a High-Resolution Regional Climate Model RegCM4 Ensemble

Temperature extremes over rapidly urbanizing regions with high population densities have been scrutinized due to their severe impacts on human safety and economics.First of all,the performance of the regional climate model RegCM4 with a hydrostatic or non-hydrostatic dynamic core in simulating seasonal temperature and temperature extremes was evaluated over the historical period of 1991–99 at a 12-km spatial resolution over China and a 3-km resolution over the Beijing−Tianjin−Hebei(JJJ)region,a typical urban agglomeration of China.Simulations of spatial distributions of temperature extremes over the JJJ region using RegCM4 with hydrostatic and non-hydrostatic cores showed high spatial correlations of more than 0.8 with the observations.Under a warming climate,temperature extremes of annual maximum daily temperature(TXx)and summer days(SU)in China and the JJJ region showed obvious increases by the end of the 21st century while there was a general reduction in frost days(FD).The ensemble of RegCM4 with different land surface components was used to examine population exposure to temperature extremes over the JJJ region.Population exposure to temperature extremes was found to decrease in 2091−99 relative to 1991−99 over the majority of the JJJ region due to the joint impacts of increases in temperature extremes over the JJJ and population decreases over the JJJ region,except for downtown areas.Furthermore,changes in population exposure to temperature extremes were mainly dominated by future population changes.Finally,we quantified changes in exposure to temperature extremes with temperature increase over the JJJ region.This study helps to provide relevant policies to respond future climate risks over the JJJ region.