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Background: Physical activity (PA) is an important contributor to one's physical and mental health both acutely and across the lifespan. Much research has done on the ambient environment's impact on PA; however, these studies have used absolute values of atmospheric measures such as temperature and humidity, which vary spatiotemporally and make comparisons between studies which differ in location or time of year difficult to square with one another. Methods: Here, we employ the Global Weather Type Classification, Version 2, to determine the combined impact of temperature and humidity on PA in a sample of insufficiently active young adults. We conducted secondary analyses of data from a single-group behavioral intervention trial that varied the number of digital messages sent daily. Young adults (n = 81) wore Fitbit Versa smartwatches for a 6-month period sometime between April 2019 and July 2020, and location was tracked using a custom smartphone application. Results: Mixed linear models indicated that, across 8179 person-days, PA was significantly lower on days with humid conditions and significantly higher on warm dry days, though the latter relationship was no longer significant when controlling for timing in relation to the COVID-19 pandemic declaration. Demographic factors did not affect the relationship between weather and PA. Conclusions: Results are a first step in providing additional guidance for encouraging PA in insufficiently active individuals given forecasted daily weather conditions. Future work should examine seasonal variability in the weather type–PA relationship without the influence of a world-altering event influencing results. [ABSTRACT FROM AUTHOR]

The giant impact between proto-Earth and a Mars-sized planet called Theia resulted in the formation of the Earth–Moon system, and the silicate mantles of the initial bodies may have partly been vaporized. Here, we develop a machine learning potential for MgSiO3 based on the data from first-principles calculations to estimate its critical point. The variations in pressure along different isotherms yield the position of the critical point of MgSiO3 at 0.54 g cm−3 and 6750 ± 250 K, which agrees with the previous theoretical estimation. We also simulate the MgSiO3 melt under a spectrum of critical conditions to understand the changes in coordination environment with density and temperature. The fourfold Si–O coordination hardly changes with increasing density at 3000 K. However, with increasing temperature, the dominance of four-coordinated Si–O diminishes rapidly as density decreases. Regarding Mg–O coordination, the overall trend, which varies with temperature and density, remains largely consistent with Si–O but with a greater diversity in the types of coordination due to more bond breaking events. Our work opens a new avenue by employing machine learning methods to estimate the critical point of silicates. [ABSTRACT FROM AUTHOR]

SiC fibers are widely used in composites exposed to high temperature oxidizing environments. The present study compares the oxidation behavior of SiC fibers and the associated changes in tensile strength upon their exposure to dry air and steam for up to 50 hours at temperatures from 950°C to 1350°C. In both cases, the scale thickness and oxide microstructure were analyzed by scanning electron microscopy. When the SiC fibers were oxidized in air, a crack-free amorphous oxide layer formed at temperatures up to 1200°C, whereas a cracked, crystallized oxide layer was found at 1350°C. By contrast under steam environment, a crystalline oxide forms at 950°C for oxidation times longer than 30 h. In both environments, the fiber strength decreased with increasing exposure time and temperature, the degradation being faster after oxidation in steam compared to dry air. This appears to relate to residual stress in the oxide scale and a reduction in the cross section of the load-bearing unoxidized SiC. An increase in defect size may also contribute to the loss of strength. The oxide scale follows parabolic growth kinetics in both dry air and in steam from 950°C to 1350°C, except at 1350°C for over 30 hours. The oxidation rate in steam is faster than that in dry air, with activation energies of 79.8±1.4 kJ/mol in steam and 153.6±3.4 kJ/mol in dry air, respectively. This work is relevant to the application of SiC fibers and SiC fiber reinforced composites in air and steam environments at high temperature. [ABSTRACT FROM AUTHOR]

The summer of 2022 has been the so far hottest summer on record in Central Europe. High temperatures negatively affect the physiology of plants and cause considerable thermal stress in particular on the leaf level. The assessment of the temperature-dependent decline of the quantum use efficiency of the photosystem II (Fv/Fm) has gained much popularity to quantify the leaf-level sensitivity to thermal stress. An open question is whether leaves heat to those in vitro estimated threshold temperatures on hot days or if plants can avoid heat stress through transpirational cooling. Therefore, leaf temperatures were monitored on a non-native Austrian oak (Quercus cerris) during a heatwave in July 2022 and compared to observed air temperature and leaf thermal traits assessed with a chlorophyll fluorometer. The highest air temperature recorded during the heatwave was 42.5 °C and surpassed the breaking point temperature (temperature at 5% decline of Fv/Fm; T5) by 0.3 °C, but was 6.1 °C lower than T50 (temperature at 50% decline of Fv/Fm). However, during the hottest day, the maximum leaf temperature was significantly below the air temperature. Even the directly illuminated leaf facing south reached a maximum temperature of only 38.7 °C but reached 39.8 °C on the second hottest day when the air temperature went up to 39.6 °C. All leaves showed a certain degree of homeothermy as the slope between leaf temperature and air temperature was 0.83 (P < 0.05). In conclusion, Austrian oak can buffer thermal stress during heatwaves to a certain degree, however, leaf temperatures are only marginally below critical threshold temperatures. [ABSTRACT FROM AUTHOR]

Non-ionic hydrophobic eutectic solvents have emerged as a new class of eutectic solvents. They are prepared by mixing two non-ionic components. They have gained significant interest compared to their counterpart ionic hydrophobic eutectic solvents and hydrophobic ionic liquids due to the availability of a wide array of non-ionic substances that can be used to prepare these solvents. Understanding the distinct physical characteristics of these solvents is crucial to their practical application within process industries and associated fields. The present work reports the development of a density model for these solvents based on the conductor-like screening model (COSMO), a dielectric continuum solvation model. For this purpose, a comprehensive literature search was carried out, and 485 density points of 37 different hydrophobic non-ionic eutectic solvents were collected. COSMO volume, one of the outputs of the COSMO calculations, was correlated with the experimental molar volume for the model development. Two different models were developed, one at 298.15 K and another a general model that can predict the density over a wide temperature range at atmospheric pressure. The developed model only requires the molar ratio and COSMO volumes of the components forming the eutectic solvents to predict the density. The proposed general model performed better than most other models and was comparable with the best one reported in the literature, with an average relative deviation percent (ARD%) of 1.34%. [ABSTRACT FROM AUTHOR]

Heat exchangers require periodic maintenance. Offline cleaning scheduled shutdowns are usually needed to restore the exchanger effectiveness, drastically reduced when fouling accumulation occurs. An online real-time alternative for monitoring the effectiveness of exchanger (during a period of eleven months of continuous operation) and an adapted version of the ε-NTU method to calculate its effectiveness are discussed. The experimental difficulties of measuring the mass flow rate and the hot air temperature at the exit of the exchanger is examined. Detailed analysis confirmed that the outlet temperature of the hot fluid could introduce errors of up to 30% in the calculation of the exchanger effectiveness. A skillful treatment of the energy balance is proposed to address the issue. The associated uncertainties are estimated by two independent approaches, the so-called classic method, i.e., the Guide to the Expression of Uncertainty in Measurement and the Monte Carlo method. Both confirmed that measurements of the air outlet temperature accounts for more than 50% of the uncertainty associated with the calculation of the exchanger effectiveness. It is suggested that the conventional method (based on measurements of the outlet air temperature) is not suitable for traditional everyday practices to monitor the effectiveness of the heat exchangers of hydrogenerators. [ABSTRACT FROM AUTHOR]

Low-temperature storage is an important way to maintain the quality of foodstuffs. Meanwhile, the massive power consumption and high operating costs of maintaining low temperatures are the main constraints for applying low-temperature storage applications. Utilizing phase change material (PCM) for low-temperature storage, which can postpone alleviate the electricity requirement, is a workable alternative. In the present study, numerical investigations are conducted to analyze the thermal, economic, and preservation performances in apple refrigerated warehouses (RWHs) with and without on-shelf PCM. The results show that employing on-shelf PCM can reduce the operating cost of the RWH by about 34.1 % without deteriorating apple preservation performance in that the maximal difference in firmness reduction of apple is only about 6.57 %. In addition, the maximum air temperature in the pallet region of the RWH with on-shelf PCM varies from -1 °C to 2.9 °C, which is about 1.1 °C lower than that without on-shelf PCM during the storage process. Meanwhile, the maximum temperature rise rate of apple can be reduced from 0.58 °C/h to 0.21 °C/h with on-shelf PCM. However, the temperature of the apple on the edge of the pallet in the RWH with on-shelf PCM is higher than that in the RWH without on-shelf PCM in the last 6 h of daily storage. [ABSTRACT FROM AUTHOR]

Recently, numerous studies have highlighted that the climate worldwide is changing rapidly due to increased greenhouse gas (GHG) emissions. The average ambient temperatures across Canada are rising approximately twice as fast as the rest of the world. The projected change in climate may increase the air and surface temperature indices, thus affecting the duration of spring load restrictions (SLRs) on roads, which may potentially impact the trucking industry and economy. Therefore, the best practices must be adjusted when identifying the optimal SLR periods that consider climate change. In Ontario, Canada, the SLR periods are imposed based on subsurface temperature data that is obtained from the road weather information system (RWIS) and spring load adjustment (SLA) stations in conjunction with visual observations. In this study, different methods of determining SLR periods were investigated. Then, new models were developed to correlate the surface cumulative thawing index (CTI) and thawing depth (TD) of a site. These models were developed utilizing atmospheric, surface, and subsurface data that was collected from different SLA and RWIS weather stations at various locations across Ontario, Canada. Finally, the developed models were utilized to predict the SLR periods for future scenarios using data from different global circulation models (GCM) and representative concentration pathways (RCPs). This study concludes that the SLR periods are expected to shrink across Ontario, Canada, by 2100. The results of this study might help different road authorities and trucking agencies maximize the life of the road structure and minimize the economic hardships that are faced during SLR periods. [ABSTRACT FROM AUTHOR]

Direct air capture (DAC) is a negative emission technology for removing CO2 from the atmosphere to maintain the CO2 level within a reasonable range so as to address greenhouse effects. In this study, the operational optimization of lab‐scale DAC has been investigated using a crossflow air‐liquid contactor loaded with a three dimensionally printed Gyroid packing structure and a potassium sarcosinate solvent. The effects of various parameters, including feed air flow rate, liquid solvent flow rate, contactor geometry, and ambient temperature, are examined. The results demonstrate that the Gyroid packing design achieves comparable CO2 capture performance to conventional packed beds but with a significantly lower pressure drop of up to 77.8%, suggesting its potential as an efficient and cost‐effective solution for gas–liquid contactors in DAC. Additionally, the study explores the climate impact on CO2 capture performance and finds that as the air temperature increases from 35 to 95°F at a fixed relative humidity of 80%, the CO2 capture rate increased from 23.2% to 46.8% with better stability. The research highlights the importance of optimizing contactor design and operational conditions to improve the CO2 capture rate and feasibility of DAC systems as a negative emission technology for addressing greenhouse effects. [ABSTRACT FROM AUTHOR]

In this paper, we have proposed a nonlinear mathematical model to study the dynamics of atmospheric carbon dioxide $({\rm{CO}}{{\kern 1pt} _{\rm{2}}})$(CO2) and atmospheric temperature due to energy sectors. Energy sector is a major contributor of atmospheric carbon dioxide. We have studied the effects of energy consumption and human population on ${\rm{CO}}{{\kern 1pt} _{\rm{2}}}$CO2 level and temperature. Burning of fossil fuels results in an increase of ${\rm{CO}}{{\kern 1pt} _{\rm{2}}}$CO2 level and temperature. To curb the ${\rm{CO}}{{\kern 1pt} _{\rm{2}}}$CO2 level and temperature, efficient mitigation options are required. Mitigation options, which reduce emission rate of ${\rm{CO}}{{\kern 1pt} _{\rm{2}}}$CO2, energy consumption rate and rate of increase in temperature, are considered in this model. By taking the efficiencies of mitigation options as control variables, the optimality system is derived. Numerical simulations are carried out to validate our analytical findings. The optimal profiles of control variables are plotted for different values of emission rate of ${\rm{CO}}{{\kern 1pt} _{\rm{2}}}$CO2, energy consumption rate and rate of increase in temperature. Maximum efficiencies of mitigation options are also plotted against to reduce emission rate of ${\rm{CO}}{{\kern 1pt} _{\rm{2}}}$CO2, energy consumption rate and rate of increase in temperature. It is found that mitigation cost of implementation of mitigation options can be minimized by implementing more efficient mitigation options. [ABSTRACT FROM AUTHOR]

An accurate determination of minimum ignition energy (MIE) is essential for assessing electrostatic hazards and characterising potential for occurrence of combustion in flammable mixtures. This is of utmost importance for hydrogen-air mixtures characterised by a MIE equal to 0.017 mJ, whereas conventional flammable gases are characterised by MIE typically higher than 0.1 mJ. The study aims at developing and validating a CFD three-dimensional model capable to simulate complex unsteady physical and chemical phenomena underlying capacitive discharge spark. The model accounts for the experimental apparatus details, including the effect of electrodes' gap and associated heat losses. The numerical approach accurately reproduced the experimental measurements of MIE for mixtures of hydrogen with air at initial temperature ranging from ambient (T = 288 K) to cryogenic (T = 123 K). Hydrogen concentration in air was included in the range 10–55% for tests at T = 288 K, and 20–60% for tests at T = 173 K and 123 K respectively. Simulations assess the impact of experimental characteristics and design, such as the electrodes' dimension, and numerical features on process dynamics, growth of the flame kernel and MIE predictions. • Development of a CFD 3D model simulating the phenomena underlying a discharge spark. • Inclusion of effect of conductive and radiative heat losses on the MIE predictions. • Validation against tests on H 2 -air mixtures at ambient and cryogenic temperatures. • Simulations provide insights into the process dynamics and flame kernel development. [ABSTRACT FROM AUTHOR]

This study explores aerosol direct, indirect, and feedback effects on meteorology and fine particulate matter during heat waves of August 2022 over eastern China by using an online coupled regional climate–chemistry–aerosol model. In this period, aerosols exerted mean direct (DRE) and indirect (IRE) radiative effects of −3.9 Wm−2 and −2.4 Wm−2 at TOA, which totally caused a decrease in average surface air temperature by 0.3 °C over east China, accompanied by decreases in PBLH (planetary boundary layer height) and precipitation and an increase in PM2.5 concentration. With the anthropogenic emission reduction from 2013 to 2022, DRE apparently decreased while IRE changed little, leading to a decrease in total aerosol radiative effect (TRE) by 27% at TOA. The weakened TRE resulted in increases in surface air temperature and precipitation by 0.14 °C and 2.7 mm, respectively, on average over east China, with the maximum warming exceeding 0.5 °C in BTH (Beijing–Tianjin–Hebei province). This study highlights a warming trend due to weakened TRE, which may exacerbate heat wave, and an increasing importance of aerosol IRE relative to DRE due to weak sensitivity of cloud properties to aerosol change during the emission reduction. [ABSTRACT FROM AUTHOR]

Climate change and extreme weather events are threatening agricultural production worldwide. The anticipated increase in atmospheric temperature may reduce the potential yield of cultivated crops. Agroforestry is regarded as a climate-resilient system that is profitable, sustainable, and adaptable, and has strong potential to sequester atmospheric carbon. Agroforestry practices enhance agroecosystems' resilience against adverse weather conditions via moderating extreme temperature fluctuations, provisioning buffers during heavy rainfall events, mitigating drought periods, and safeguarding land resources from cyclones and tsunamis-type events. Therefore, it was essential to comprehensively analyze and discuss the role of agroforestry in providing resilience during extreme weather situations. We hypothesized that integrating trees in to the agro-ecosystems could increase the resilience of crops against extreme weather events. The available literature showed that the over-story tree shade moderates the severe temperature (2-4°C) effects on understory crops, particularly in the wheat and coffee-based agroforestry as well as in the forage and livestock-based silvipasture systems. Studies have shown that intense rainstorms can harm agricultural production (40-70%) and cause waterlogging. The farmlands with agroforestry have been reported to be more resilient to heavy rainfall because of the decrease in runoff (20-50%) and increase in soil water infiltration. Studies have also suggested that drought-induced low rainfall damages many crops, but integrating trees can improve microclimate and maintain crop yield by providing shade, windshield, and prolonged soil moisture retention. The meta-analysis revealed that tree shelterbelts could mitigate the effects of high water and wind speeds associated with cyclones and tsunamis by creating a vegetation bio-shield along the coastlines. In general, existing literature indicates that implementing and designing agroforestry practices increases resilience of agronomic crops to extreme weather conditions increasing crop yield by 5-15%. Moreover, despite its widely recognized advantages in terms of resilience to extreme weather, the systematic documentation of agroforestry advantages is currently insufficient on a global scale. Consequently, we provide a synthesis of the existing data and its analysis to draw reasonable conclusions that can aid in the development of suitable strategies to achieve the worldwide goal of adapting to and mitigating the adverse impacts of climate change. [ABSTRACT FROM AUTHOR]

Under global warming, heatwaves (HWs) are exerting increasing impacts on human life. In order to explore the thermal sensation of HWs under the combined influence of air temperature, humidity, radiation and wind speed, this study utilized the hourly Universal Thermal Climate Index (UTCI) data from the ECMWF Reanalysis v5 (ERA5) to define daytime, night‐time and compound HWs, and then comparatively analysed their occurrences in China during 1981–2020. Results revealed that daytime HWs affect the majority of regions in China with the exception of the Tibetan Plateau, while both night‐time and compound HWs mainly strike the Yangtze River Basin and the Guangdong–Guangxi region in southeastern China. Additionally, it is noteworthy that a substantial portion of regions experiencing night‐time HWs also encounter compound HWs. The frequency and intensity of all three types of HWs show increasing trends generally in regions where HWs occur. The spatial coverage of HWs grows at rates of 8.05%/10a, 2.11%/10a and 1.62%/10a for the daytime, night‐time and compound types, respectively. For each summer month, the spatial coverage of daytime HWs notably surpasses that of night‐time and compound HWs. Further classifying HWs with intensity, it is found that the spatial coverage of both moderate and severe HW events exhibits discernible rising trends across all three types of HWs. Furthermore, regions with higher HW frequencies are more likely to experience severe HWs as well as record‐breaking ones. Additionally, the spatial coverage of daytime, night‐time and compound record‐breaking HWs is expanding. [ABSTRACT FROM AUTHOR]

Snow is particularly impacted by climate change and therefore there is an urgent need to understand the temporal and spatial variability of depth of snowfall (HN) trends. However, the analysis of historical HN observations on large‐scale areas is often impeded by lack of continuous long‐term time series availability. This study investigates HN trends using observed time series spanning the period 1920–2020 from 46 sites in the Alps at different elevations. To discern patterns and variations in HN over the years, our analysis focuses also on key parameters such as precipitation (P), mean air temperature (TMEAN), and large‐scale synoptic descriptors, that is, the North Atlantic Oscillation (NAO), Arctic Oscillation (AO) and Atlantic Multidecadal Oscillation (AMO) indices. Our findings reveal that in the last 100 years and below 2000 m a.s.l., despite a slight increase in winter precipitation, there was a decrease in HN over the Alps, especially for southern and low‐elevation sites. The South‐West and South‐East regions experienced an average loss of 4.9 and 3.8%/decade, respectively. A smaller relative loss was found in the Northern region (2.3%/decade). The negative HN trends can be mainly explained by an increase of TMEAN by 0.15°C/decade. Most of the decrease in HN occurred mainly between 1980 and 2020, as a result of a more pronounced increase in TMEAN. This is also confirmed by the change of the running correlation between HN and TMEAN, NAO, AO over time, which until 1980 were not correlated at all, while the correlation increased in later years. This suggests that in more recent years favourable combinations of temperature, precipitation, and atmospheric pattern have become more crucial for snowfall to occur. On the other hand, no correlation was found with the AMO index. [ABSTRACT FROM AUTHOR]

In July and August 2022, the Yangtze River basin (YRB) experienced its hottest summer since 1961. The SINTEX‐F2 seasonal prediction system initialized in early May predicted the hotter‐than‐normal summer due to its successful prediction of central Pacific La Niña, negative Indian Ocean Dipole and the resultant warming in the tropical West Pacific‐East Indian Ocean (TWP_EIO). The common SST forcing explains only about 26% to the heatwave strength, while the internal variations in the anomalous warming in the TWP_EIO and Europe, surplus precipitation in Pakistan, and local land‐air interaction account for approximately 65%, based on the analysis of 108 ensemble members. These factors have collectively increased the maximum temperature over the YRB through the enhancement and westward expansion of western North Pacific subtropical high. Our findings quantify the relative contributions of external forcing and internal variations to the unprecedented hot event, offering insights into its forming mechanism and potential predictability. Plain Language Summary: A record‐breaking heatwave event occurred in the YRB in July and August 2022, posing significant risks on human health, power supply, and social economic activities. Recognizing the importance of such an event, our study aims to identify key factors influencing its prediction using the SINTEX‐F2 system. The central Pacific La Niña, negative Indian Ocean Dipole and the resultant warming in the TWP_EIO provide the dominant predictability, but accounts only about 26% of the heatwave strength. However, internal variations in the anomalous warming in the TWP_EIO and Europe, surplus precipitation in Pakistan, and local land‐air interaction collectively explain about 65%. Our results suggest the necessity of large‐ensemble prediction in capturing this kind of unprecedented extreme event. Key Points: The SINTEX‐F2 initialized on 2022 early May captures the warmer‐than‐normal air temperatures in Yangtze River basinThe model successfully predicts co‐occurrences of CP La Niña and negative IOD in 2022However, the direct SST forcing contributes only 26% to the 2022 extreme event in Yangtze River basin [ABSTRACT FROM AUTHOR]

The impact of land variables on temperature forecasts in atmospheric cycling is often underestimated or overlooked. This oversight primarily occurs due to the abundance of meteorological measurements available for assimilation and partly because soil states are assumed to be quickly reset by atmospheric forcing, such as precipitation, justifying no spin‐ups or no updates of soil states during cycling. In this study, by updating soil moisture every 6 hr using different analysis data sets for May 2019, considerable discrepancies were found, highlighting large uncertainties in soil moisture analysis. Different soil moisture analyses produced systematically different temperature forecasts, with errors growing over cycles to be comparable to a typical error magnitude of 2‐m temperature observations (∼2°K). This study demonstrates that temperature forecasts are significantly influenced by whether and how soil moisture is updated, not only near the surface but also up to the low‐mid troposphere and throughout the cycles. Plain Language Summary: This study examines the impact of soil moisture on temperature forecasts in the context of atmospheric cycling. During the 6‐hr cycling for May 2019 over the CONUS domain, updating soil moisture systematically affects temperature forecast bias (>±1°K) in the low‐mid troposphere throughout the cycles. We also observe significant uncertainties across state‐of‐the‐art soil moisture analysis data sets, highlighting the challenges of land data assimilation. Key Points: Temperature forecast errors are significantly affected by whether or how soil moisture is updated in atmospheric cyclingLarge uncertainties are found across different soil moisture analysis data setsUpdating soil moisture alone can mitigate temperature forecast bias in the low‐mid troposphere, systematically improving forecast accuracy [ABSTRACT FROM AUTHOR]

The mechanisms by which clouds impact the variability of the mid‐latitude atmosphere are poorly understood. We use an idealized, dry atmospheric model to investigate the relationship between Atmospheric Cloud Radiative Effects (ACRE) and annular mode persistence. We force the model with time‐varying diabatic heating that mimics the observed ACRE response to the Southern Annular Mode (SAM). Realistic ACRE forcing reduces annular mode persistence by 5 days (−16%), which we attribute to a weakening of low‐frequency eddy forcing via modified low‐level temperature gradients, though this effect is partly compensated by reduced frictional damping due to zonal wind anomalies becoming more top‐heavy. The persistence changes are nonlinear with respect to the amplitude of ACRE forcing, reflecting nonlinearities in the response of the eddy forcing. These results highlight the ACRE's impact on low‐frequency eddy forcing as the dominant cause of changes in annular mode persistence. Plain Language Summary: In this study, we conduct novel modeling experiments aimed at understanding how clouds affect the unforced variability of jet streams—concentrated bands of eastward wind in the mid‐latitude atmosphere. We focus on direct heating and cooling of the atmosphere by clouds, called Atmospheric Cloud Radiative Effects (ACRE), and how these impact the annular mode—the most significant type of jet stream variability, which consists of north‐south shifts of the jet's position. Using a simplified atmospheric model, we investigate how the persistence and structure of the annular mode are impacted by heatings and coolings that mimic the observed ACRE response to the Southern Hemisphere Annular Mode (SAM). We find that the ACRE reduces the persistence of the annular mode (i.e., deviations of the jet stream from its mean position tend to persist for less time), which we attribute to a weakening of the feedback mechanism by which atmospheric waves strengthen the jet where it is already strongest. We identify some compensating effects, but, overall, our results highlight that ACRE impacts jet streams via low‐altitude temperature gradients and atmospheric wave generation. Key Points: The response of Atmospheric Cloud Radiative Effects (ACRE) to the Southern Annular Mode (SAM) reduces SAM's persistenceThe decrease in SAM's persistence is attributed to weakened low‐frequency eddy forcing via disruption of low‐level temperature gradientsThe change in persistence is nonlinear with respect to the amplitude of ACRE forcing [ABSTRACT FROM AUTHOR]

Antarctic warm extremes impact the cryosphere, with very warm extremes driving surface melt on ice shelves. Here, we analyze temperatures exceeding the 90th percentile and the associated circulation patterns and radiation anomalies. ERA5 reanalysis data show positive geopotential height anomalies related to the occurrence of warm extremes. The highest temperature during warm extremes appears on the western periphery of high‐pressure systems, consistent with anticyclonic advection. Temperature anomalies during warm extremes are strongest in winter due to the transport of warm and moist air and a strong meridional temperature gradient. In summer, the weak meridional gradients of top‐of‐atmosphere downward solar radiation flux and surface air temperature contribute to weak temperature anomalies. Warm extremes are associated with positive longwave radiation anomalies in all seasons, but with negative shortwave radiation anomalies at the surface except during polar night. These relationships are verified by station observations. Our results confirm that Antarctic warm extremes are mostly driven by meridional advection of warm air, and suggest that these warm air masses are predominantly moist and cloudy. Plain Language Summary: Changes in Antarctic climate will alter the amount of water stored in the kilometer‐thick Antarctic ice cover, and thereby global sea level. So far, only some regions of the continent have experienced substantial warming under climate change, while others remain largely unaffected. In this study, we analyze the relatively warmest Antarctic temperatures in each place and season. We find that these warm extremes depart more strongly from seasonal mean temperatures in winter than in summer. Warm extremes are often a consequence of warmer air being transported from further North and coincide with moist, probably cloudy air that emits more infrared radiation to the surface than dry, cold air. Key Points: Warm extremes accompanied by high‐pressure systems are driven by advectionWinter experiences strongest temperature anomalies during warm extremesLongwave radiation anomalies during warm extremes are positive and contribute to warm extremes, shortwave radiation anomalies are negative [ABSTRACT FROM AUTHOR]

In this study, the Atmospheric Infrared Sounder (AIRS) Observations for Model Intercomparison Projects (Obs4MIPs) V2.1 tropospheric air temperature, specific humidity, and relative humidity data are utilized to evaluate the global tropospheric temperature and humidity simulations in the fully coupled global climate models from the Coupled Model Intercomparison Project phases 3, 5, and 6 (CMIP3, CMIP5, and CMIP6), and possible simulation improvement in CMIP6 models in comparison to CMIP3 and CMIP5 models. Our analyses indicate that all three phases of CMIP models share similar tropospheric air temperature, specific humidity, and relative humidity biases in their multi‐model ensemble means relative to AIRS. Cold biases up to 4 K and positive relative humidity biases up to 20% are found in the free troposphere almost globally with maxima over the mid‐latitude storm tracks. Warm biases up to 2 K are seen over the Southern Ocean in the lower troposphere. Positive specific and relative humidity biases exist over the off‐equatorial oceans while negative specific and relative humidity biases are seen near the equator in the tropical free troposphere, which are related to the double‐intertropical convergence zone bias in the models. Both the air temperature and specific humidity biases are important to the relative humidity biases except in the tropical free troposphere where the specific humidity biases dominate. The tropospheric air temperature, specific humidity, and relative humidity biases are reduced from CMIP3 to CMIP5 and to CMIP6 at almost all pressure levels except at 300 hPa for specific humidity and in the boundary layer for relative humidity. Plain Language Summary: In this study, we use the Atmospheric Infrared Sounder (AIRS) data to assess how well the fully coupled global climate models simulate temperature and humidity in the troposphere. We focus on the climate models from the recent three phases of Coupled Model Intercomparison Project (CMIP3, CMIP5, and CMIP6) and investigate if there is any bias reduction in the recent CMIP6 models compared to the earlier CMIP3 and CMIP5 models. To conduct our evaluation, we compare the CMIP model ensemble averages with the AIRS data and find that all three phases of CMIP models exhibit similar biases in tropospheric temperature and humidity. For example, cold biases up to 4 K and positive relative humidity biases up to 20% are seen in the free troposphere over most regions, with the maximum biases over the midlatitudes. Positive specific and relative humidity biases are found over the off‐equatorial oceans while negative specific and relative humidity biases are seen near the equator in the tropical free troposphere. We also note a possible temperature and humidity bias reduction from the CMIP3 models to the CMIP5 models and then to the CMIP6 models at most pressure levels. Key Points: CMIP Phase 3, 5 and 6 climate models share similar tropospheric air temperature, specific and relative humidity biases relative to Atmospheric Infrared SounderCold biases and positive relative humidity biases are prevalent in free troposphere almost globally with maxima over the mid‐latitude oceansDouble‐intertropical convergence zone bias‐related specific and relative humidity biases are evident in tropical free troposphere: positive (negative) off (near) the equator [ABSTRACT FROM AUTHOR]

The impacts of falling ice radiative effects (FIREs) on land‐atmosphere feedback processes were examined, with a focus on the fidelity of land surface properties and their variability as inferred by global climate models (GCMs). We conducted a pair of sensitivity experiments using the National Center for Atmospheric Research (NCAR) Community Earth System Model Version 1 (CESM1) in fully coupled modes with FIREs turned on and off. This allowed us to investigate the seasonal response of land surface properties to changes in radiation fluxes and land surface temperature (LST) associated with FIREs across global land areas. Our findings indicate that during boreal winter, excluding FIREs results in less surface downward longwave and net flux (∼5–15 Wm−2), leading to a colder land surface (∼2–4 K) and air temperatures (∼1–4 K) at mid‐ and high latitudes. Consequently, the surface frozen soil layer and snow cover persist through spring, delaying snowmelt and thawing until summer. This delay reduces liquid soil moisture, thereby suppressing vegetation productivity in subsequent seasons. Conversely, tropical regions, exhibit contrasting responses, with a warmer land surface (∼0.5 K) and warmer air temperatures (∼0.1–0.5 K) due to increased surface downward shortwave and net flux (∼2–10 Wm−2). This enhancement in radiation fosters increased vegetation productivity throughout the seasonal cycle. These findings illustrate a local response of land surface properties to changes in the surface energy balance and LST, highlighting the significant role that FIREs play in land surface modeling within GCMs. Plain Language Summary: We explored the seasonal response of land surface properties to changes in radiation fluxes and land surface temperature across global land areas using the CESM1‐CAM5 coupled model with falling ice radiative effects (FIREs) both turned on and off. During boreal winter, excluding FIREs reduces surface downward longwave and net flux, resulting in a colder land surface and colder air temperatures at mid‐ and high latitudes. These cold conditions lead to the persistence of the surface frozen soil layer and snow cover through spring, delaying snowmelt and thawing until summer, which in turn reduces liquid soil moisture and suppresses vegetation growth in subsequent seasons. In contrast, tropical regions exhibit a warmer land surface and air temperatures due to increased downward shortwave and net flux, promoting vegetation growth throughout the year. Key Points: Most Coupled Model Intercomparison Project Phase 5 models did not consider falling ice radiative effects (FIREs)Excluding FIREs results in cold air, prolonging frozen soil and snow cover, which suppress vegetation growth at mid‐ to high latitudesExcluding FIREs leads to warmer air temperatures and promotes enhanced vegetation growth in tropical latitudes [ABSTRACT FROM AUTHOR]

Accurate air temperatures underpin environmental research. Most professional meteorological air temperature measurements still expose thermometers within traditional, naturally ventilated screens. Their representation of true air temperature depends on screen airflow, and therefore local winds. Accuracies of daily maximum (Tmax) and minimum (Tmin) air temperatures are assessed by comparison between a naturally ventilated large conventional screen and a co‐located aspirated reference screen. In over 1200 days' data, the naturally ventilated Tmin and Tmax both showed small (median < 0.06°C) cold bias, but, in 1% of cases, warm Tmax bias and cold Tmin bias >|1°C|. The Tmin cold bias is associated with calm clear nights, and the Tmax warm bias events with calm winter days at low sun angles, allowing solar heating of the screen. The prevalence of poor natural ventilation, potentially affecting Tmin and Tmax, is estimated across European sites. Poor ventilation occurred at Tmin for 12% of values, and at Tmax for 4%. Climatological averaging will reduce these effects, but, without corroborating wind data, statistical changes in Tmin or Tmax, including identifying “Tropical Nights” (Tmin > 20°C) or occurrences of winter extremes, may have limited value. Wider adoption of aspirated thermometer screens, with an initial overlap period, will largely eliminate these effects. [ABSTRACT FROM AUTHOR]

Summer drought over northern Asia (NA) seriously threatens the local fragile ecological environment and social economy development. In this study, using the standardized precipitation evapotranspiration index (SPEI), we first identify the dominant modes of interannual variability in summer drought condition over NA and then explore the atmospheric patterns responsible for the formation of the modes. The results show that the first empirical orthogonal function (EOF1) mode of summer SPEI over NA exhibits a meridional dipole pattern, which is influenced primarily by the polar–Eurasian teleconnection (POL) and circumglobal teleconnection (CGT) patterns. Under the influence of negative POL and positive CGT patterns, there is an anomalous anticyclone (cyclone) over northwestern Siberia (Lake Baikal to Northeast China). Such atmospheric circulations lead to meridional dipole patterns in air temperature, moisture condition, vertical motion, and cloud cover over NA, favoring decreased (increased) precipitation and increased (decreased) potential evapotranspiration over northern (southern) NA, finally contributing to the formation of EOF1. The second EOF (EOF2) shows an approximate zonal dipole pattern, which is influenced by the British–Baikal Corridor (BBC) and Scandinavia (SCA) teleconnection patterns. The positive BBC and SCA patterns can lead to an anomalous anticyclone over the Ural Mountains and a cyclone over Lake Baikal. Such atmospheric circulations result in a zonal dipole pattern in precipitation and potential evapotranspiration over NA through changing the local moisture condition, air temperature, and radiation, consequently favoring the formation of EOF2. Fitting analysis indicates that the aforementioned atmospheric factors can explain 76% (55%) of the interannual variability of EOF1 (EOF2). [ABSTRACT FROM AUTHOR]

In order to accurately and easily predict the variation of the average temperature of the concrete rectangular hollow pier. Firstly, the temperature distribution of the concrete rectangular hollow pier of Changjiahe Special Bridge was observed for 212 days. Then, based on the observation data, the functional relationship between the average concrete hollow pier temperature and the outside air temperature, and the air temperature inside the hollow pier was studied. Finally, based on this functional relationship, a prediction model for the range of variation of the mean temperature of the hollow pier was given and verified. The results of the study show that: the change of external shade temperature can be regarded as the superposition of different cyclic changes and random changes; the change rule of the average temperature of the concrete hollow pier is the same as that of the air temperature, both presenting day-by-day cyclic and step changes; the linear correlation coefficients between the daily maximum and daily minimum average hollow pier temperature and the daily average air temperature are R = 0.980 and R = 0.973, respectively; the daily average air temperature, the daily average air temperature inside the pier and daily average hollow pier temperature are R = 0.980, R = 0.998; the daily variation of the average hollow pier temperature and the daily variation of the air temperature are approximately linear, with a correlation coefficient of R = 0.899; assuming that the average temperature of the concrete hollow pier is a folding change, based on the above relationship, a method of predicting the time-by-time average temperature of the concrete hollow piers is proposed, as well as two methods of predicting the average temperature of the test piers. Average temperature change range method. Comparing the predicted values with the measured values, it is found that the predicted values are in good agreement with the measured values. [ABSTRACT FROM AUTHOR]

Single atom catalysts (SACs) exhibit the flexible coordination structure of the active site and high utilization of active atoms, making them promising candidates for nitrogen reduction reaction (NRR) under ambient conditions. By the aid of first‐principles calculations based on DFT, we have systematically explored the NRR catalytic behavior of thirteen 4d‐ and 5d‐transition metal atoms anchored on 2D porous graphite carbon nitride C5 ${_5 }$ N2 ${_2 }$. With high selectivity and outstanding activity, Zr, Nb, Mo, Ta, W and Re‐doped C5 ${_5 }$ N2 ${_2 }$ are identified as potential nominees for NRR. Particularly, Mo@C5 ${_5 }$ N2 ${_2 }$ possesses an impressive low limiting potential of −0.39 V (corresponding to a very low temperature and atmospheric pressure), featuring the potential determining step involving *N−N transitions to *N−NH via the distal path. The catalytic performance of TM@C5 ${_5 }$ N2 ${_2 }$ can be well characterized by the adsorption strength of intermediate *N2 ${_2 }$ H. Moreover, there exists a volcanic relationship between the catalytic property UL ${_{\rm{L}} }$ and the structure descriptor Ψ ${{{\Psi }}}$ , which validates the robustness and universality of Ψ ${{{\Psi }}}$ , combined with our previous study. This work sheds light on the design of SACs with eminent NRR performance. [ABSTRACT FROM AUTHOR]

Climate change poses a substantial threat to agricultural sustainability globally. Agriculture is a vital component of the gross domestic production of developing countries. The multifaceted impacts of climate change on agriculture, highlighting how extreme weather events such as water stress, heatwaves, erratic rainfall, storms, floods, and emerging pest infestations are disrupting agricultural productivity. The socioeconomic status of farmers is particularly vulnerable to climatic extremes with future projections indicating significant increment in ambient air temperatures and unpredictable, intense rainfall patterns. Agriculture has historically relied on the extensive use of synthetic fertilizers, herbicides, and insecticides, combined with advancements in irrigation and biotechnological approaches to boost productivity. It encompasses a range of practices designed to enhance the resilience of agricultural systems, improve productivity, and reduce greenhouse gas emissions. By adopting climate‐smart practices, farmers can better adapt to changing climatic conditions, thereby ensuring more sustainable and secure food production. Furthermore, it identifies key areas for future research, focusing on the development of innovative adaptation and mitigation strategies. These strategies are essential for minimizing the detrimental impacts of climate change on agriculture and for promoting the long‐term sustainability of food systems. This article underscores the importance of interdisciplinary approaches and the integration of advanced technologies to address the challenges posed by climate change. By fostering a deeper understanding of these issues to inform policymakers, researchers, and practitioners about effective strategies to safeguard agricultural productivity and food security in the face of changing climate. [ABSTRACT FROM AUTHOR]

Impaired thermoregulatory function is a clinical feature of many health conditions that affect triathletes using wheelchairs and consequently, individual athlete performances may fluctuate according to environmental temperature. We aimed to determine the effect of 1) water temperature on wheelchair triathlon swim time and 2) air temperature on handcycle and wheelchair run (push) time. Published race records from 2017 to 2023 (n = 49 events) were extracted from the World Triathlon website. Bayesian negative binomial regression was used to separately model the nonlinear relationships between water temperature and swim time, and air temperature and handcycle and push time. Age, sex, sport class, whether wetsuits were worn (swim model), and swim time (handcycle and push model) were included as fixed effects. Over the observed water temperature range of 15.7–30.5°C, male swim time (mm:ss) improved from 14:13 (95% credible interval [CrI] = 12:27, 16:09) to 12:35 (95% CrI = 11:00, 14:19). Female swim time improved from 15:33 (95% CrI = 13:24, 17:55) to 12:46 (95% CrI = 11:03, 14:38). It was unclear whether handcycle and push time slowed over the observed air temperature range of 14–33°C. Warmer water temperatures, up to 30.5°C, were associated with faster swim times. It was unclear whether combined handcycle and push time slowed with increases in air temperature, up to 33°C. The integration of information on athlete impairment type and severity with performance data is needed to better understand the extent to which individual athlete performances fluctuate across environmental conditions. [ABSTRACT FROM AUTHOR]

Summers with extremely high vapor pressure deficit contribute to crop losses, ecosystem damages, and wildfires. Here, we identify very rare summer vapor pressure deficit extremes globally in reanalysis data and climate model simulations, and quantify the contributions of temperature and atmospheric moisture anomalies to their intensity. The simulations agree with reanalysis data regarding these physical characteristics of historic vapor pressure deficit extremes, and show a +33/+28% increase in their intensity in the northern/southern mid-latitudes over this century. About half of this drastic increase in the magnitude of extreme vapor pressure deficit anomalies is due to climate warming, since this quantity depends exponentially on temperature. Further contributing factors are increasing temperature variability (e.g., in Europe) and the expansion of soil moisture-limited regions. This study shows that to avoid amplified impacts of future vapor pressure deficit extremes, ecosystems and crops must become more resilient not only to an increasing mean vapor pressure deficit, but additionally also to larger seasonal anomalies of this quantity. Global climate simulations are analyzed to identify extreme summer temperature and humidity conditions that are harmful to crops and ecosystems, and it is shown that climate change leads to a drastic intensification of such events in extratropical regions. [ABSTRACT FROM AUTHOR]

The unprecedented growth in population and swift industrial advancements exert considerable strains on the ecosystem, particularly within medium-sized and large urban landscapes. The critical investigation into the intricate links between current and prospective land utilization, as well as the ecosystem service value (ESV), holds considerable empirical relevance for the calibration of land usage frameworks, thereby contributing to the sustainable evolution of extensive urban zones. Utilizing GlobeLand 30 data, the present research probes into the pattern of land transformation and the spatial-temporal dispersal of ESV in Henan's Yellow River vicinity over a span from 2000 to 2020. For the enhancement of land usage alignment, a Markov-PLUS fusion model was devised to gauge three disparate ESV transition scenarios slated for 2030, namely, natural development scenario (NDS), cropland protection scenario (CPS), and ecological protection scenario (EPS). The principal determinants of land transformation within the 2000-2020 period were recognized as elevation, populace concentration, and atmospheric temperature. Amid the rapid accretion of construction land engulfing substantial cropland and grassland areas, there was an ESV diminution to the tune of 1.432 billion RMB between 2000 and 2020. The ESV's high-value regions were discerned within relatively undisturbed ecosystem zones, with the lower-value sections identified in cropland and constructed areas, where human interventions exerted pronounced effects on the ecosystem. In accordance with the 2030 land usage simulations and analyses, in contrast to alternative scenarios, the EPS exhibited the least fluctuation in land type alterations in 2030, demonstrated the most pronounced escalation in cold spot concentration, and reached a peak agglomeration level. This underscores that the EPS not only offers a refinement in land utilization configuration but also mediates the equilibrium between economic and ecological considerations. The insights derived from this investigation afford innovative evaluative methods for spatial planning, ecological recompense, and sustainable land exploitation within largeand medium-scale urban domains. [ABSTRACT FROM AUTHOR]

The current study is to develop surface-modified peanut shell granules by incorporating activated carbon to enhance the removal efficiency of Orange G dye (OGD) through adsorption. Activated carbon was prepared from Arachis hypogaea shell (Peanut shell) using a chemical activation method. Ultrasonic Activated Peanut Shell Powder (UAPSP) was characterised using FT-IR and SEM analysis to identify functional groups and assess surface morphology. To determine the optimal conditions, a batch adsorption study was conducted. The results indicated a maximum removal efficiency of 99.5% and a maximum adsorption capacity of 298.36 mg/g under the following parameters: pH 5, temperature 303 K, interaction period of 60 min, a dosage of 0.5 g/L for an OGD concentration of 10 mg/L. The adsorption mechanism in the current system was evaluated using the Langmuir, Freundlich, Sips, Temkin, and D-R isotherms models. Among these, the Langmuir isotherm exhibited the best fit with an R2 value of 0.997. UAPSP demonstrated a monolayer adsorption capacity of 1.9 mg/g for OGD removal. The pseudo-second-order kinetic model provided the most effective fit with an R2 value of 0.998. Thermodynamic studies revealed that the adsorption process was spontaneous and exothermic, as evidenced by the negative values of ΔG° (−1.497) and ΔS° (16.4052) at 303 K. Additionally, the mean free energy value (E) in the D-R isotherm increased to 10.58 KJ/mol with a temperature rise from 303 K to 343 K. The characterisation results confirmed that UAPSP is an effective, cost-free, and commercial alternative adsorbent for the removal of hazardous dyes from wastewater. [ABSTRACT FROM AUTHOR]

In this study, we report observations of propagating radial carpet beams (RCBs) through a turbulent atmosphere at ground level with a 120 m path length. RCBs are a class of nondiffracting, accelerating, self-healing, and self-amplifying beams, and generated in the diffraction of a plane wave from amplitude/phase radial gratings having different spoke numbers. Observations were made at different times of the day. The intensity profile of an RCB becomes complicated when the number of grating spokes used to generate the beam is large, and includes high intensity spots, called main intensity spots (MISs), which are symmetrically placed at the central area around the beam axis and whose number is equal to (twice) the number of spokes of the amplitude (phase) grating used to generate the beam. With the aid of a telescope and a CCD camera, successive frames of the intensity pattern of the RCBs having different levels of structural complexity are recorded at the end of the path. For the data recorded at different times of the day, we calculate the variance of displacements of MISs along the radial direction. We observe that displacements of the MISs increase with increasing mean temperature of the air; on the other hand, as the complexity of the beam intensity pattern increases, the displacements of the MISs decrease. In order to compare the resilience of different RCBs and a well-known structured beam against atmospheric turbulence, we investigate deformation of the intensity profiles of a Laguerre–Gaussian (LG) beam having a topological charge 20 and different RCBs at the end of the path. It is shown that under the same turbulence condition, highly complex RCBs are more resilient to the destructive effects of the atmospheric turbulence. In particular, for the RCBs generated with gratings having 30 spokes and more, the number of MISs of the received intensity patterns is changed by less than 1% even when the turbulence strength is high. But for the LG beam, its intensity ring is clearly broken in different places, which makes it impossible to follow its maximum intensity in the radial direction [ABSTRACT FROM AUTHOR]

Understanding the genotype-by-environment interaction (GEI) and considering it in the selection process is a sine qua non condition for the expansion of Brazilian eucalyptus silviculture. This study's objective is to select high-performance and stable eucalyptus clones based on a novel selection index that considers the Factor Analytic Selection Tools (FAST) and the clone's reliability. The investigation explores the nuances interplay of GEI and extends its insights by scrutinizing the relationship between latent factors and real environmental features. The analysis, conducted across seven trials in five Brazilian states involving 78 clones, employs FAST. The clonal selection was performed using an extended FAST index weighted by the clone's reliability. Further insights about GEI emerge from the integration of factor loadings with 25 environmental features through a principal component analysis. Ten clones, distinguished by high performance, stability, and reliability, have been selected across the target population of environments. The environmental features most closely associated with factor loadings, encompassing air temperature, radiation, and soil characteristics, emerge as pivotal drivers of GEI within this dataset. This study contributes insights to eucalyptus breeders, equipping them to enhance decision-making by harnessing a holistic understanding-from the genotypes under evaluation to the diverse environments anticipated in commercial plantations. [ABSTRACT FROM AUTHOR]

This decade‐long study from the INTERCONF programme addresses the data gap on ocean dynamics in the Southern Hemisphere. Focusing on the Brazil‐Malvinas Confluence (BMC), we investigated the effect of temperature differences between the warm Brazil Current (BC) and the cold Malvinas Current (MC) on water vapour in the marine atmospheric boundary layer (MABL). Our results show a clear distinction: warmer BMC waters have 32% more water vapour (2 kg·m−2 on average) compared to the MC. This highlights the direct link between ocean temperatures and atmospheric processes. Analysis of radiosonde data alongside satellite measurements showed better agreement over cooler waters with lower water vapour, leading to lower variability. This suggests less atmospheric turbulence and improved data compatibility, especially for satellite retrievals such as AIRS. Comparisons between reanalysis data (CFSR), satellite sounders (AIRS) and radiosondes (RS) showed consistent air temperature profiles, with average errors within the 10% threshold for satellite measurements. While capturing humidity variations remains a challenge, especially at high concentrations (indicated by higher mean squared error values), our study highlights the reliability of satellite data, particularly over the cold BMC region. This research highlights the importance of studying the interactions between ocean fronts and atmospheric phenomena for a complete picture of Southern Hemisphere ocean dynamics. It offers valuable insights for scientists across disciplines, providing a broad perspective on the results and their significance in different contexts. [ABSTRACT FROM AUTHOR]

Color centers in wide band-gap semiconductors, which have superior quantum properties even at room temperature and atmospheric pressure, have been actively applied to quantum sensing devices. Characterizing the quantum properties of the color centers in the semiconductor materials and ensuring that these properties are uniform over a wide area are key issues for developing quantum sensing devices based on color centers. In this article, we have developed an optics design protocol optimized for evaluating the quantum properties of color centers and have used this design approach to develop a new microscopy system called columnar excitation fluorescence microscope (CEFM). The essence of this system is to maximize the amount of fluorescence detection of polarized color centers, which is achieved by large-volume and uniform laser excitation along the sample thickness with sufficient laser power density. This laser excitation technique prevents undesirable transitions to undesirable charge states and undesirable light, such as unpolarized color center fluorescence, while significantly increasing the color center fluorescence. This feature enables fast measurements with a high signal-to-noise ratio, making it possible to evaluate the spatial distribution of quantum properties across an entire mm-size sample without using a darkroom, which is difficult with typical confocal microscope systems. [ABSTRACT FROM AUTHOR]

The space-borne Integrated Path Differential Absorption (IPDA) lidar can measure the global distribution of CO2. Here, we simulate measurements on the R16 absorption line employing a 1572 nm electro-optic dual-comb interferometer. We introduce a comprehensive modeling and retrieval framework to assess the lidar's capability in measuring the column-averaged of CO2 in the atmosphere. The assessment combines data simulation with linearization error analysis to solve the nonlinearity in retrieval. Our findings suggest that positioning any sampling wavelength at the absorption peak will significantly increase the random error by about 30%. The lidar can operate with an optimal wavelength strategy where the wavelength bias has virtually no effect, but it must still account for the effects of atmospheric temperature and pressure. We performed a comprehensive global evaluation using geophysical data, comparing results across 3 to 17 wavelengths. Distributing 20 W launched power over 11 wavelengths enables measurement with an error below 0.9 ppm over most of the Earth's surface. [ABSTRACT FROM AUTHOR]

Spatial proxies, such as coordinates and distance fields, are often added as predictors in random forest (RF) models without any modifications being made to the algorithm to account for residual autocorrelation and improve predictions. However, their suitability under different predictive conditions encountered in environmental applications has not yet been assessed. We investigate (1) the suitability of spatial proxies depending on the modelling objective (interpolation vs. extrapolation), the strength of the residual spatial autocorrelation, and the sampling pattern; (2) which validation methods can be used as a model selection tool to empirically assess the suitability of spatial proxies; and (3) the effect of using spatial proxies in real-world environmental applications. We designed a simulation study to assess the suitability of RF regression models using three different types of spatial proxies: coordinates, Euclidean distance fields (EDFs), and random forest spatial prediction (RFsp). We also tested the ability of probability sampling test points, random k -fold cross-validation (CV), and k -fold nearest neighbour distance matching (kNNDM) CV to reflect the true prediction performance and correctly rank models. As real-world case studies, we modelled annual average air temperature and fine particulate air pollution for continental Spain. In the simulation study, we found that RFs with spatial proxies were poorly suited for spatial extrapolation to new areas due to significant feature extrapolation. For spatial interpolation, proxies were beneficial when both strong residual autocorrelation and regularly or randomly distributed training samples were present. In all other cases, proxies were neutral or counterproductive. Random k -fold cross-validation generally favoured models with spatial proxies even when it was not appropriate, whereas probability test samples and kNNDM CV correctly ranked models. In the case studies, air temperature stations were well spread within the prediction area, and measurements exhibited strong spatial autocorrelation, leading to an effective use of spatial proxies. Air pollution stations were clustered and autocorrelation was weaker and thus spatial proxies were not beneficial. As the benefits of spatial proxies are not universal, we recommend using spatial exploratory and validation analyses to determine their suitability, as well as considering alternative inherently spatial modelling approaches. [ABSTRACT FROM AUTHOR]

We assess the temperature stability requirements of unseeded Nd:YAG lasers in lidar systems for atmospheric temperature profiling through the rotational Raman technique. Taking as a reference a system using a seeded laser assumed to emit pulses of negligible spectral width and free of wavelength drifts, we estimate first the effect of the pulse spectral widening of the unseeded laser on the output of the interference filters, and then we derive the limits of the allowable wavelength drift for a given bias in the temperature measurement that would add to the noise-induced uncertainty. Finally, using spectroscopic data, we relate the allowable wavelength drift to allowable temperature variations in the YAG rod. We find that, in order to keep the bias affecting atmospheric temperature measurements smaller than 1 K, the Nd:YAG rod temperature should also be kept within a variation range of 1 K. [ABSTRACT FROM AUTHOR]

Purpose: The rising frequency of extreme heat events poses an escalating threat of heat-related illnesses and fatalities, placing an additional strain on global healthcare systems. Whether the risk of heat-related issues is sex specific, particularly among the elderly, remains uncertain. Methods: 16 men and 15 women of similar age (69 ± 5 years) were exposed to an air temperature of 39.1 ± 0.3 °C and a relative humidity (RH) of 25.1 ± 1.9%, during 20 min of seated rest and at least 40 min of low-intensity (10 W) cycling exercise. RH was gradually increased by 2% every 5 min starting at minute 30. We measured sweat rate, heart rate, thermal sensation, and the rise in gastrointestinal temperature (Tgi) and skin temperature (Tsk). Results: Tgi consistently increased from minute 30 to 60, with no significant difference between females and males (0.012 ± 0.004 °C/min vs. 0.011 ± 0.005 °C/min; p = 0.64). Similarly, Tsk increase did not differ between females and males (0.044 ± 0.007 °C/min vs. 0.038 ± 0.011 °C/min; p = 0.07). Females exhibited lower sweat rates than males (0.29 ± 0.06 vs. 0.45 ± 0.14 mg/m2/min; p < 0.001) in particular at relative humidities exceeding 30%. No sex differences in heart rate and thermal sensation were observed. Conclusion: Elderly females exhibit significantly lower sweat rates than their male counterparts during low-intensity exercise at ambient temperatures of 39 °C when humidity exceeds 30%. However, both elderly males and females demonstrate a comparable rise in core temperature, skin temperature, and mean body temperature, indicating similar health-related risks associated with heat exposure. [ABSTRACT FROM AUTHOR]

This project evaluates the impact of interior insulation on external walls in three Swedish heritage buildings. Field measurements and hygrothermal simulations were conducted to assess available solutions. Measurements of temperature and relative humidity were taken both indoors and outdoors, as well as on the exterior and interior surfaces of the walls. The accuracy of simulation standards for indoor air temperature and relative humidity was evaluated, and the findings indicate that current simulation standards can serve as reliable alternatives when on-site measurements are not feasible. Validated models were used to analyze the impact of 13 different interior insulation solutions, including vapor-tight and open options, some of which were capillary active. The results highlight that the risk of moisture damage depends on the design of the existing external wall and indicate the importance of hydrophobic treatment in mitigating risks. Thinner amounts of interior insulation can significantly reduce transmission losses without compromising moisture performance. Overall, all the assessed external walls can be safely insulated from the interior, although hydrophobic treatment is recommended for optimal results. This research provides practical insights for decision-making in simulation approaches and optimizing insulation strategies to enhance the performance and durability of external walls in building projects. [ABSTRACT FROM AUTHOR]

The growth cycle of tellurium zinc cadmium crystals is long and the growth system is complex. When using vertical Bridgman or vertical gradient freezing methods to grow tellurium zinc cadmium (CdZnTe) crystal materials, the growth process is often difficult to observe intuitively, and there is no corresponding means to detect the temperature field inside the crystals, which brings inconvenience to improve the crystal growth process. In this paper, numerical simulation software is used to analyze the influences of furnace air convection on the temperature field of CdZnTe crystal growth. By opening holes at the top and bottom of furnace, gas exchanging occurs between the inside and outside of the furnace, thereby regulates the convection behaviors. Before opening holes, the convection rate is slow (only 10-5 m/s), forming stable convection cells; after opening holes, the convection rate significantly increases (0.25 - 0.90 m/s), and the convection state changes to laminar flow. Through controlling the aperture size (20 - 40 mm) in the model, the laminar flow rate can be effectively regulated. At the same temperature setting, when the flow rate increases from 0.25 m/s to 0.90 m/s, the temperature gradient will increase from 0.5 K/mm to 1.1 K/mm. Furthermore, experimental work is applied on real furnace, the change of temperature filed before and after opening holes were studied. The experimental results of temperature gradient is accord with the simulating results. It is also found that under laminar flow state, increasing convection rate may improve the stability of temperature field. The increase of temperature gradient and the improvement of stability in the temperature field will be beneficial for the preparation of high-quality CdZnTe crystals. [ABSTRACT FROM AUTHOR]

Research on rainfall is critically important due to its significant impact on climate change and natural disasters in Indonesia. Various factors influence rainfall variability. Consequently, when examining spatial aspects, it is likely that spatial dependency exists not only in the response variable but also in the exogenous variables. Hence, a model that accounts for spatial dependencies between these variables is required. The integration of the Spatial Durbin Model (SDM) with Casetti's expansion approach can be utilized to predict spatial patterns of rainfall influenced by exogenous variables. By incorporating spatial effects and relevant independent variables, this model can provide more precise estimates of rainfall distribution across different regions. This modeling technique is particularly effective for accurate rainfall prediction, considering exogenous factors such as air temperature, humidity, solar irradiation, and surface pressure. The SDM with Casetti's expansion approach was employed to predict rainfall patterns in the Java Island region, utilizing data from the National Aeronautics and Space Administration's Prediction of Worldwide Energy Resources (NASA POWER) big data website. The application of this model in the context of rainfall prediction highlights its importance in enhancing the understanding of weather dynamics and aiding disaster risk mitigation in Java Island, a highly populated region characterized by a Monsoon rainfall pattern. The rainfall prediction follows a Knowledge Discovery in Databases (KDD) methodology. The results of this study are expected to be valuable to relevant agencies, such as the Meteorology, Climatology, and Geophysics Agency (BMKG), and agribusiness companies, improving agricultural planning and planting seasons. Additionally, the general public can benefit from more accurate climate information, particularly regarding rainfall. The computational framework is developed within an RShiny web application, and the performance of the proposed technique is measured by the Mean Absolute Percentage Error (MAPE), achieving a very accurate prediction rate of 2.78%. [ABSTRACT FROM AUTHOR]

Climate change is a global problem facing all aspects of the agricultural sector. Heat stress due to increasing atmospheric temperature is one of the most common climate change impacts on agriculture. Heat stress has direct effects on crop production, along with indirect effects through associated problems such as drought, salinity, and pathogenic stresses. Approaches reported to be effective to mitigate heat stress include nano-management. Nano-agrochemicals such as nanofertilizers and nanopesticides are emerging approaches that have shown promise against heat stress, particularly biogenic nano-sources. Nanomaterials are favorable for crop production due to their low toxicity and eco-friendly action. This review focuses on the different stresses associated with heat stress and their impacts on crop production. Nano-management of crops under heat stress, including the application of biogenic nanofertilizers and nanopesticides, are discussed. The potential and limitations of these biogenic nano-agrochemicals are reviewed. Potential nanotoxicity problems need more investigation at the local, national, and global levels, as well as additional studies into biogenic nano-agrochemicals and their effects on soil, plant, and microbial properties and processes. [ABSTRACT FROM AUTHOR]

Simple Summary: The use of single-box housing for domestic horses is a matter of concern due to its potential negative effects on their social interaction and movement. Horses in tropical regions may also face challenges due to heat and humidity fluctuations affecting their thermal comfort and heat dissipation. This study sought to explore the stress responses in horses housed in different stable designs in a tropical savanna region, as little research has considered this topic. The results reveal correlations across stable designs between internal humidity, air temperature, ammonia levels, and heart rate variability (HRV) modulation in horses. We also observed distinct stress responses in horses in different stable designs. These findings suggest that daily changes in the internal environment, as well as stable design, play crucial roles in affecting horses' stress responses and overall well-being in tropical savanna regions. These results have important welfare implications for the management of horse housing in such environments. Single-confinement housing can pose welfare risks to domestic horses. This study investigated horses' stress responses when confined to single stalls in different stable designs in a tropical savanna region to address a gap in the literature. In total, 23 horses were assigned to a stable with a central corridor and solid external walls (A) (N = 8), a stable with one side corridor and solid external walls (B) (N = 6), or a stable with a central corridor and no solid external walls (C) (N = 9). Air velocity, relative humidity, air temperature, and noxious gases were measured inside the stables, and the heart rate and HRV of the horses were also determined. The relative humidity was lower in stable C than in stable A (p < 0.05), while the air temperature was higher in stable C than in stable B (p < 0.05) during the day. The airflow and ammonia levels were higher in stable C than in stables B and A (p < 0.01–0.0001). Overall, horses' HRV in stable A was lower than in those in stables B and C (p < 0.05–0.01). Horses in stable A tended to experience more stress than those in other stables. [ABSTRACT FROM AUTHOR]

The cyclic oxidation behavior of an additive manufactured CoCrMo alloy with 0.14 wt.% C was investigated at 914 °C for 32 cycles, each lasting 10 h, resulting in a total exposure time of 320 h. The oxidation rate was assessed for mass gain after finishing each 40 h oxidation cycle. It was experimentally determined that the oxidative process at 914 °C of this CoCrMo alloy follows a parabolic law, with the process being fast at the beginning and slowing down after the first 40 h. The microstructural analysis revealed that in the as-printed state, the phases developed were primarily the γ matrix and minor traces of ε phase. The oxidative process ensured an increase in the ε phase and precipitation of carbides which produced a 12% increase in the material's hardness after the first 40 h of exposure at 914 °C. The oxidation process led to the development of an oxide scale comprising a dense Cr2O3 layer and a porous layer of CoCr2O4 spinel, the latter spalling after the 240 h of exposure. Despite this spallation, the oxide scale continued to develop in the presence of O, Cr, and Co. The experimental analysis provided valuable insights regarding the material's behavior under prolonged exposure at high temperature in air, demonstrating its suitability as a candidate for additive manufactured mandrels used for bending metallic pipe fitting elbows. [ABSTRACT FROM AUTHOR]

Improving the performance of drop-in hydrocarbon refrigerants for the increasing in-flow of conventional refrigerators to Nigeria is a necessary sustainable strategy. This experimental study investigates the enhancement limits of a liquid-line magnetic field, CNT nano-lubricant, and a combination of both on an R134a domestic refrigerator with 40–70 g each of R600a refrigerants. The study compares the performance of R600a refrigerant without enhancements (pure) and with two pairs of 3000 Gauss liquid-line mounted O-ring permanent magnets (Mag), 0.2 g L−1 concentration of CNT nano-lubricant (Nano), and both liquid-line magnet and CNT nano-lubricant (Mag-Nano). Test parameters include evaporator air temperature, discharge pressure, power consumption, coefficient of performance (COP), and total equivalent warming impact (TEWI). The results show that enhancement methods led to higher COP in the range of 16.64–42.38%. At the same time, evaporator air temperature, discharge pressure, power consumption, and TEWI were lower by 9.76% to 20.96%, 17.75% to 34.26%, 5.22% to 13.42%, and 5.88% to 10.86%, respectively. In conclusion, the proposed enhancement techniques in the refrigeration system provide normal, safe, and efficient operation. [ABSTRACT FROM AUTHOR]