Factors Influencing the Spatial Variability of Air Temperature Urban Heat Island Intensity in Chinese Cities

Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.

Surface air temperature change in the Wuyi Mountains,southeast China

Detecting changes in surface air temperature in mid-and low-altitude mountainous regions is essential for a comprehensive understanding of warming trend with altitude.We use daily surface air temperature data from 64 meteorological stations in Wuyi Mountains and its adjacent regions to analyze the spatio-temporal patterns of temperature change.The results show that Wuyi Mountains have experienced significant warming from 1961 to 2018.The warming trend of the mean temperature is 0.20℃/decade,the maximum temperature is 0.17℃/decade,and the minimum temperature is 0.26℃/decade.In 1961-1990,more than 63%of the stations showed a decreasing trend in annual mean temperature,mainly because the maximum temperature decreased during this period.However,in 1971-2000,1981-2010 and 1991-2018,the maximum,minimum and mean temperatures increased.The fastest increasing trend of mean temperature occurred in the southeastern coastal plains,the quickest increasing trend of maximum temperature occurred in the northwestern mountainous region,and the increase of minimum temperature occurred faster in the southeastern coastal and northwestern mountainous regions than that in the central area.Meanwhile,this study suggests that elevation does not affect warming in the Wuyi Mountains.These results are beneficial for understanding climate change in humid subtropical middle and low mountains.

Spatial Variation in CO_(2) Concentration Improves the Simulated Surface Air Temperature Increase in the Northern Hemisphere

The increasing concentration of atmospheric CO_(2) since the Industrial Revolution has affected surface air temperature.However,the impact of the spatial distribution of atmospheric CO_(2) concentration on surface air temperature biases remains highly unclear.By incorporating the spatial distribution of satellite-derived atmospheric CO_(2) concentration in the Beijing Normal University Earth System Model,this study investigated the increase in surface air temperature since the Industrial Revolution in the Northern Hemisphere(NH) under historical conditions from 1976-2005.In comparison with the increase in surface temperature simulated using a uniform distribution of CO_(2),simulation with a nonuniform distribution of CO_(2)produced better agreement with the Climatic Research Unit(CRU) data in the NH under the historical condition relative to the baseline over the period 1901-30.Hemispheric June-July-August(JJA) surface air temperature increased by 1.28℃ ±0.29℃ in simulations with a uniform distribution of CO_(2),by 1.00℃±0.24℃ in simulations with a non-uniform distribution of CO_(2),and by 0.24℃ in the CRU data.The decrease in downward shortwave radiation in the non-uniform CO_(2) simulation was primarily attributable to reduced warming in Eurasia,combined with feedbacks resulting from increased leaf area index(LAI) and latent heat fluxes.These effects were more pronounced in the non-uniform CO_(2)simulation compared to the uniform CO_(2) simulation.Results indicate that consideration of the spatial distribution of CO_(2)concentration can reduce the overestimated increase in surface air temperature simulated by Earth system models.

Influence of the Atlantic Multidecadal Oscillation and Interdecadal Pacific Oscillation on Antarctic surface air temperature during 1900 to 2015

The importance of the Atlantic Multidecadal Oscillation(AMO)and Interdecadal Pacific Oscillation(IPO)in influencing zonally asymmetric changes in Antarctic surface air temperature(SAT)has been established.However,previous studies have primarily concentrated on examining the combined impact of the contrasting phases of the AMO and IPO,which have been dominant since the advent of satellite observations in 1979.This study utilizes long-term reanalysis data to investigate the impact of four combinations of+AMO+IPO,–AMO–IPO,+AMO–IPO,and–AMO+IPO on Antarctic SAT over the past 115 years.The+AMO phase is characterized by a spatial mean temperature amplitude of up to 0.5℃over the North Atlantic Ocean,accompanied by positive sea surface temperature(SST)anomalies in the tropical eastern Pacific and negative SST anomalies in the extratropical-mid-latitude western Pacific,which are indicative of the+IPO phase.The Antarctic SAT exhibits contrasting spatial patterns during the+AMO+IPO and+AMO–IPO periods.However,during the–AMO+IPO period,apart from the Antarctic Peninsula and the vicinity of the Weddell Sea,the entire Antarctic region experiences a warming trend.The most pronounced signal in the SAT anomalies is observed during the austral autumn,whereas the combination of–AMO and–IPO exhibits the smallest magnitude across all the combinations.The wavetrain excited by the SST anomalies associated with the AMO and IPO induces upper-level and surface atmospheric circulation anomalies,which alter the SAT anomalies.Furthermore,downward longwave radiation anomalies related to anomalous cloud cover play a crucial role.In the future,if the phases of AMO and IPO were to reverse(AMO transitioning to a negative phase and IPO transitioning to a positive phase),Antarctica could potentially face more pronounced warming and accelerated melting compared to the current observations.

Response of Rice Cultivars to Elevated Air Temperature and Soil Amendments: Implications towards Climate Change Adaptations and Mitigating Global Warming Potentials

Global mean surface air temperature is expected to increase 1.1˚C - 6.4˚C by the end of 21st century which may affect rice productivity and methane emissions in the future climate. This experiment was conducted to investigate the response of rice cultivars to elevated air temperature (+1.5˚C higher than ambient) and soil amendments in regards to rice yield, yield scaled methane emissions and global warming potentials. The experimental findings revealed that replacement of inorganic fertilizers (20% - 40% of recommended NPKS) with Vermicompost, Azolla biofertilizer, enriched sugarcane pressmud, rice husk biochar and silicate fertilization increased rice yield 13.0% - 23.0%, and 11.0% - 19.0% during wet aman and dry boro season, respectively. However, seasonal cumulative CH4 fluxes were decreased by 9.0% - 25.0% and 5.0% - 19.0% during rainfed wet aman and irrigated dry boro rice cultivation, respectively with selected soil amendments. The maximum reduction in seasonal cumulative CH4 flux (19.0% - 25.0%) was recorded with silicate fertilization and azolla biofertilizer amendments (9.0% - 13.0%), whereas maximum grain yield increment 10.0 % - 14.0% was found with Vermicompost and Sugarcane pressmud amendments compared to chemical fertilization (100% NPKS) treated soils at ambient air temperature. However, rice grain yield decreased drastically 43.0% - 50.0% at elevated air temperature (3˚C higher than ambient air temperature), eventhough accelerated the total cumulative CH4 flux as well as GWPs in all treatments. Maximum seasonal mean GWPs were calculated at 391.0 kg CO2 eq·ha−1 in rice husk biochar followed by sugarcane pressmud (mean GWP 387.0 kg CO2 eq·ha−1), while least GWPs were calculated at 285 - 305 kg CO2 eq·ha−1 with silicate fertilizer and Azolla biofertilizer amendments. Rice cultivar BRRI dhan 87 revealed comparatively higher seasonal cumulative CH4 fluxes, yield scaled CH4 flux and GWPs than BRRI dhan 71 during wet aman rice growing season;while BRRI dhan 89 showed higher cumulative CH4 flux and GWPs than BINA dhan 10 during irrigated boro rice cultivation. Conclusively, inorganic fertilizers may be partially (20% - 40% of the recommended NPKS) replaced with Vermicompost, azolla biofertilizer, silicate fertilizer and enriched sugarcane pressmud compost for sustainable rice production and decreasing GWPs under elevated air temperature condition.

Effects of temperature, particle size, and air humidity on sensibility of typical high-energetic explosives

The production and utilization of high-energetic explosives often pose a range of safety hazards,with sensitivity being a key factor in evaluating these risks.To investigate how temperature,particle size,and air humidity affect the responsiveness of commonly used high-energetic explosives,a series of BAM(Bundesanstalt für Materialforschung und-prüfung)impact and friction sensitivity tests were carried out to determine the critical impact energy and critical load pressure of four representative high-energetic explosives(RDX,HMX,PETN and CL-20)under different temperatures,particle sizes,and air humidity conditions.The experimental findings facilitated an examination of temperature and particle size affecting the sensitivity of high-energetic explosives,along with an assessment of the influence of air humidity on sensitivity testing.The results clearly indicate that high-energetic explosives display a substantial decline in critical reaction energy when subjected to micrometre-sized particles and an air humidity level of 45%at a temperature of 90℃.Furthermore,it was noted that the critical reaction energy of high-energetic explosives diminishes with an increase in temperature within 25℃−90℃.In the same vein,as the particle sizes of high-energetic explosives increase,so does the critical reaction energy for micrometre-sized particles.High air humidity significantly affects the sensitivity testing of high-energetic explosives,emphasizing the importance of refraining from conducting sensitivity tests in such conditions.

Urban Surroundings Influence on Air Temperature in a Small Urban Area of Curitiba-Brazil

The formation of urban climates constitutes a distinctive system intrinsically linked to the urban environment. This study aims to delve into the impact of the urban environment on climatic variables. The Urban Weather Generator (UWG) algorithm was employed to generate climatic data, facilitating the creation of an epw climate file that corresponds to the urban characteristics surrounding the Centro Politécnico campus at the Federal University of Paraná (UFPR). Comprehensive analyses encompassing land use, occupancy patterns, albedo, surface absorption, anthropogenic heat, and architectural attributes were conducted. A comparative assessment between the UWG-derived air temperature values and meteorological station data revealed that the UWG effectively characterizes the air temperature patterns around the UFPR campus. The anticipated air temperature values consistently surpass the original dataset (SWERA), which was utilized as input, primarily during the hours from 3 p.m. to 7 a.m., showcasing the unmistakable urban heat island phenomenon.

Calculation of Mass Concrete Temperature and Creep Stress under the Influence of Local Air Heat Transfer

Temperature-induced cracking during the construction of mass concrete is a significant concern.Numerical simulations of concrete temperature have primarily assumed that the concrete is placed in an open environment.The problem of heat transfer between the air and concrete has been simplified to the concrete’s heat dissipation boundary.However,in the case of tubular concrete structures,where air inlet and outlet are relatively limited,the internal air temperature does not dissipate promptly to the external environment as it rises.To accurately simulate the temperature and creep stress in tubular concrete structures with enclosed air spaces during construction,we establish an air–concrete coupled heat transfer model according to the principles of conjugate heat transfer,and the accuracy of the model is verified through experiments.Furthermore,we conduct a case study to analyze the impact of airflow within the ship lock corridor on concrete temperature and creep stress.The results demonstrate that enhancing airflow within the corridor can significantly reduce the maximum concrete temperature.Compared with cases in which airflow within the corridor is neglected,the maximum concrete temperature and maximum tensile stress can be reduced by 12.5℃ and 0.7 MPa,respectively,under a wind speed of 4 m/s.The results of the traditional calculation method are relatively close to those obtained at a wind speed of 1 m/s.However,the temperature reduction process in the traditional method is faster,and the method yields greater tensile stress values for the corridor location.

Decadal prediction skill for Eurasian surface air temperature in CMIP6 models

评估CMIP6年代际预测试验对季节平均SAT的预测技巧的结果表明:模式不能有效预测冬季和秋季SAT的年代际变率.IPSL-CM6A-LR和多模式集合平均对于春季SAT展现了预测技巧,其中对于变率的预测技巧好于振幅的结果.基于蒙古和我国华北地区的显著预测技巧,模式对于夏季SAT表现出最佳的预测水平.与外部强迫相比,模式对于SAT的预测技巧可能来自初始化.模式中的一个明显系统性误差值得注意,即模式中冬季SAT的变率可以持续到其他季节,而在观测中其他季节的SAT变化与冬季SAT相对独立.

Intermolecular Acid-Base-Pairs Containing Poly(p-Terphenyl-co-lsatin Piperidinium)for High Temperature Proton Exchange Membrane Fuel Cells

How to optimize and regulate the distribution of phosphoric acid in matrix,and pursuing the improved electrochemical performance and service lifetime of high temperature proton exchange membrane(HT-PEMs)fuel cell are significant challenges.Herein,bifunctional poly(p-terphenyl-co-isatin piperidinium)copolymer with tethered phosphonic acid(t-PA)and intrinsic tertiary amine base groups are firstly prepared and investigated as HT-PEMs.The distinctive architecture of the copolymer provides a well-designed platform for rapid proton transport.Protons not only transports through the hydrogen bond network formed by the adsorbed free phosphoric acid(f-PA)anchored by the tertiary amine base groups,but also rely upon the proton channel constructed by the ionic cluster formed by the t-PA aggregation.Thorough the design of the structure,the bifunctional copolymers with lower PA uptake level(<100%)display prominent proton conductivities and peak power densities(99 mS cm^(-1),812 mW cm^(-2)at 160℃),along with lower PA leaching and higher voltage stability,which is a top leading result in disclosed literature.The results demonstrate that the design of intermolecular acid-base-pairs can improve the proton conductivity without sacrificing the intrinsic chemical stability or mechanical property of the thin membrane,realizing win-win demands between the mechanical robustness and electrochemical properties of HT-PEMs.

Estimating Monthly Surface Air Temperature Using MODIS LST Data and an Artificial Neural Network in the Loess Plateau, China

Air temperature(Ta)datasets with high spatial and temporal resolutions are needed in a wide range of applications,such as hydrology,ecology,agriculture,and climate change studies.Nonetheless,the density of weather station networks is insufficient,especially in sparsely populated regions,greatly limiting the accuracy of estimates of spatially distributed Ta.Due to their continuous spatial coverage,remotely sensed land surface temperature(LST)data provide the possibility of exploring spatial estimates of Ta.However,because of the complex interaction of land and climate,retrieval of Ta from the LST is still far from straightforward.The estimation accuracy varies greatly depending on the model,particularly for maximum Ta.This study estimated monthly average daily minimum temperature(Tmin),average daily maximum temperature(Tmax)and average daily mean temperature(Tmean)over the Loess Plateau in China based on Moderate Resolution Imaging Spectroradiometer(MODIS)LST data(MYD11A2)and some auxiliary data using an artificial neural network(ANN)model.The data from 2003 to 2010 were used to train the ANN models,while 2011 to 2012 weather station temperatures were used to test the trained model.The results showed that the nighttime LST and mean LST provide good estimates of Tmin and Tmean,with root mean square errors(RMSEs)of 1.04℃ and 1.01℃,respectively.Moreover,the best RMSE of Tmax estimation was 1.27℃.Compared with the other two published Ta gridded datasets,the produced 1 km×1 km dataset accurately captured both the temporal and spatial patterns of Ta.The RMSE of Tmin estimation was more sensitive to elevation,while that of Tmax was more sensitive to month.Except for land cover type as the input variable,which reduced the RMSE by approximately 0.01℃,the other vegetation-related variables did not improve the performance of the model.The results of this study indicated that ANN,a type of machine learning method,is effective for long-term and large-scale Ta estimation.

Absorptive root-multidimension strategy links air temperature and species distribution in a montane forest

Background: Air temperature affects absorptive root traits, which are closely related to species distribution.However, it is still unclear how air temperature regulates species distribution through changes in absorptive root traits. Seven functional traits of the absorptive roots of 240 individuals of 52 species, soil properties and air temperature were measured along an elevational gradient on Mt. Fanjingshan, Tongren City, Guizhou, and then the direct and indirect effects of these controls on species distribution were detected.Results: Absorptive roots adapted to air temperature with two strategies. The first strategy was positively associated with the specific root area(SRA) and specific root length(SRL) and was negatively associated with the root tissue density(RTD), representing the classic root economics spectrum(RES). The second strategy was represented by the trade-off between root diameter, mycorrhizal fungi colonization(MF) and SRL, representing the collaboration gradient with “do it yourself” resource uptake ranging from “outsourcing” to mycorrhizal resource uptake. Air temperature regulated species distribution in six ways: directly reducing species importance value;indirectly increasing the species importance value by reducing soil nitrogen content or increasing soil pH by reducing soil moisture inducing absorptive roots to change from “do it yourself” resource absorption to “outsourcing” resource absorption;indirectly decreasing the species importance value by decreasing soil moisture to change from“outsourcing”resource absorption to “do it yourself” resource absorption;indirectly increasing the species importance value with increasing soil pH by reducing soil moisture resulting in absorptive root traits turning into nutrient foraging traits;and indirectly decreasing the species importance value by promoting absorptive root traits to nutrient conservation traits.Conclusions: Absorptive root traits play a crucial role in the regulation of species distribution through multiapproaches of air temperature.

具有时滞效应的air2stream河流水温模型及应用研究

高精度河流水温模型对于深入了解水温的时空变化特征和河流生态修复具有重要意义。基于数据驱动的air2stream模型在保证预测精度的同时,避免了计算的复杂性,已成为河流水温模拟常用的模型。由于水的热惯性及水文条件等的影响,河流水温变化往往显著滞后于气温变化,而air2stream原模型并未考虑滞后效应,导致该模型在流量未知情况下实际精度偏低。为解决该问题,采用气温-水温皮尔逊相关系数计算时滞天数,构建具有时滞的air2stream新模型,进一步根据长江中下游地区两个监测站的多年实测数据验证新模型的有效性和稳定性。结果表明:新模型在不引进额外观测数据的条件下具有更高精度且性能更稳定。相比原模型,在两个监测站新模型的均方根误差分别降低约4.29%和5.85%。新模型具有精度高、水文要素需求少的特点,可为长江中下游的水环境影响评价和生态保护提供依据。

基于Aqua卫星AIRS数据的南大洋大气逆温和逆湿特性研究

南大洋大气普遍存在着逆温和逆湿现象,其分布和变化对海-冰-气之间的物质和通量交换具有重要影响。利用Aqua卫星上搭载的大气红外探测器(AIRS)观测数据,提取了南大洋大气的逆温和逆湿特性,并研究了其时空分布与变化特征。此外,以全球无线电探空数据集的探测结果为参考值,分析了AIRS在进行大气逆温和逆湿探测过程中受到云量影响的特征。结果表明,AIRS估计的逆温特性受云量的影响较小,在多云条件下AIRS也可精确地估计逆温特性。利用AIRS最新的第7版(V7)数据产品对2004-2020年南大洋大气逆温和逆湿的频率(强度)进行研究,发现秋冬季比春夏季高(强),在龙尼冰架、罗斯冰架和南极半岛附近的海域的大气出现逆温和逆湿现象较其他区域更频繁,且强度更强。

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.

Using satellite-derived land surface temperatures to clarify the spatiotemporal warming trends of the Alborz Mountains in northern Iran

The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects the ecosystem of this area.This study investigated the spatiotemporal changes and trends of the nighttime LST in the western region of the Central Alborz Mountains at elevations of 1500-4000 m above sea level.MODIS data were extracted for the period of 2000-2021,and the Mann-Kendall nonparametric test was applied to evaluating the changes in the LST.The results indicated a significant increasing trend for the monthly average LST in May-August along the southern aspect.Both the northern and southern aspects showed decreasing trends for the monthly average LST in October,November,and March and an increasing trend in other months.At all elevations,the average decadal change in the monthly average LST was more severe along the southern aspect(0.60°C)than along the northern aspect(0.37°C).The LST difference between the northern and southern aspects decreased in the cold months but increased in the hot months.At the same elevation,the difference in the lapse rate between the northern and southern aspects was greater in the hot months than in the cold months.With increasing elevation,the lapse rate between the northern and southern aspects disappeared.Climate change was concluded to greatly decrease the difference in LST at different elevations for April-July.

Changes in snow cover extent in the Central Taurus Mountains from 1981 to 2021 in relation to temperature, precipitation, and atmospheric teleconnections

The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central Taurus Mountains(Bolkar, Aladaglar, Tahtali and Binboga Mountains) from 1981 to 2021. Linear trends of snow cover season(November to April) over the last 41 years showed decreases in SCE primarily at lower elevations. The downward trend in SCE was found to be more pronounced and statistically significant for only November and March. SCE in the Central Taurus Mountains has declined about-6.3% per decade for 2500-3000 m in November and about-6.0% per decade for 1000-1500 m and 3000+ m in March over the last 41 years. The loss of SCE has become evident since the 2000s, and the lowest negative anomalies in SCE have been observed in 2014, 2001, and 2007 in the last 41 years, which are consistent with an increase in air temperature and decreased precipitation. SCE was correlated with both mean temperature and precipitation, with temperature having a greater relative importance at all elevated gradients. Results showed that there is a strong linear relationship between SCE and the mean air temperature(r =-0.80) and precipitation(r = 0.44) for all elevated gradients during the snow season. The Arctic Oscillation(AO), the North Atlantic Oscillation(NAO), and the Mediterranean Oscillation(MO) winter indices were used to explain the year-to-year variability in SCE over the Central Taurus Mountains. The results showed that the inter-annual variability observed in the winter SCE on the Central Taurus Mountains was positively correlated with the phases of the winter AO, NAO and MO, especially below 2000 m elevation.

Low ambient temperature and air pollution are associated with hospitalization incidence of coronary artery disease:Insights from a cross-sectional study in Northeast China

Background:Previous studies have established a link between fluctuations in climate and increased mortality due to coronary artery disease(CAD).However,there remains a need to explore and clarify the evidence for associations between meteorological changes and hospitalization incidences related to CAD and its subtypes,especially in cold regions.This study aimed to systematically investigate the relationship between exposure to meteorological changes,air pollutants,and hospitalization for CAD in cold regions.Methods:We conducted a cross-sectional study using hospitalization records of 86,483 CAD patients between January 1,2009,and December 31,2019.Poisson regression analysis,based on generalized additive models,was applied to estimating the influence of hospitalization for CAD.Results:Significant associations were found between low ambient temperature[-10℃,RR=1.65;95%CI:(1.28-2.13)]and the incidence of hospitalization for CAD within a lag of 0-14 days.Furthermore,O_(3)[95.50μg/m^(3),RR=12;95%CI:(1.03-1.21)]and NO_(2)[48.70μg/m^(3),RR=1.0895%CI:(1.01-1.15)]levels were identified as primary air pollutants affecting the incidence of CAD,ST-segment-elevation myocardial infarction(STEMI),and non-STEMI(NSTEMI)within the same lag period.Furthermore,O_(3)[95.50μg/m^(3),RR=1.12;95%CI:(1.03-1.21)]and NO_(2)[48.70μg/m^(3),RR=1.0895%CI:(1.01-1.15)]levels were identified as primary air pollutants affecting the incidence of CAD,ST-segment-elevation myocardial infarction(STEMI),and non-STEMI(NSTEMI)within the same lag period.The effect curve of CAD hospitalization incidence significantly increased at lag days 2 and 4 when NO_(2)and O_(3)concentrations were higher,with a pronounced effect at 7 days,dissipating by lag 14 days.No significant associations were observed between exposure to PM,SO_(2),air pressure,humidity,or wind speed and hospitalization incidences due to CAD and its subtypes.Conclusion:Our findings suggest a positive correlation between short-term exposure to low ambient temperatures or air pollutants(O_(3)and NO_(2))and hospitalizations for CAD,STEMI,and NSTEMI.These results could aid the development of effective preparedness strategies for frequent extreme weather events and support clinical and public health practices aimed at reducing the disease burden associated with current and future abnormal weather events.

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.