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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]

The applicability and accuracy of high‐resolution Real‐Time Meso‐scale Analysis (RTMA) system is assessed over India for the first time. The RTMA is a high‐spatial (2.5 km) and temporal resolution analysis system for near‐surface weather conditions. It is used to simulate near‐surface air temperature over India during the Heatwave (HW) period 12th to 20th April 2023. The verification analysis of temperature using the GLDAS gridded temperature shows reasonable improvement in the analysis from RTMA by capturing regional features compared to first‐guess. The spatial and temporal verification using the IMD station observations also confirms the value addition of RTMA in capturing the locations of recorded highest Tmax and their daily variations. The location‐specific heat stress analysis of RTMA shows high skill over many locations during HW days. Heat stress regions have been accurately brought out in the RTMA. Hence, the RTMA can be used for now‐casting and severe weather monitoring. Plain Language Summary: Heat wave (HW) alert systems require accurate high‐resolution surface weather data for better adaption strategies. Real‐Time Meso‐scale Analysis (RTMA) system configured to generate surface weather parameters at a high‐spatial (2.5 km) and temporal (3 hrs) resolution at National Center for Medium Range Weather Forecasting (NCMRWF) for the very first time in India. We verified its performance in representing the HW conditions and extreme temperatures over the Indian region relative to India Meteorological Department (IMD) observations/Global Land Data Assimilation System (GLDAS) during the HW period of 12th to 20th April 2023. Our results indicate significant improvement in the spatial and temporal variations of daily maximum temperature simulated by RTMA system. We have noted lower absolute mean errors of ∼ 0.02 for the RTMA in predicting the Tmax over the HW affected regions of Bihar, Odisha, West Bengal, and East Uttar Pradesh when compared to the GFS model. These improvements have led to the better identification of the locations of higher heat risk through the computation of the Heat Index and highlight the applicability of RTMA. Overall this study clearly brings out the usability of RTMA final analysis fields for now‐casting and severe weather monitoring. Key Points: It is a first‐of‐its‐kind study to understand the applicability and accuracy of high‐resolution RTMA over India by analyzing heatwaveRTMA temperature analysis shows higher skill over the heatwave regions and locations as compared to the background fields and observationsThe study suggested that the RTMA final analysis fields are highly useable for severe weather monitoring and impact‐based weather forecasts [ABSTRACT FROM AUTHOR]

Wet and cold biases on the Tibetan Plateau (TP) commonly exist in global and regional climate simulations. Previous studies have explored the possible causes of wet and cold biases and contributed to reducing these biases. However, the connection between wet and cold biases remains insufficiently addressed. Our research indicates that the TP wet bias converts into positive snow amount bias not continually but efficiently and concentratedly, under the control of snow phenology in different regions. Furthermore, the complex relationship between snow amount, snow coverage and surface albedo restricts the transformation of snow amount to surface albedo bias, and thus to cold bias. Our research highlights the spatio‐temporally divergent transformation of wet to cold bias on the TP during snow season, providing a novel perspective to understand the intrinsic connection between wet and cold biases and improve climate simulations on the TP. Plain Language Summary: Due to the harsh environment, observational data are limited on the Tibetan Plateau (TP), so climate model is one of necessary tools for climate researches. However, both global and regional climate models generally overestimate precipitation (wet bias) and underestimate near surface air temperature (cold bias) on the TP. Previous studies have pointed out the possible causes of the wet and cold biases, and partly reduced these biases, leaving the connection between these biases unaddressed. Our study finds that the conversion of wet to cold bias during snow season is divergent in different areas of the TP. Under the control of snow duration in different areas, the wet bias efficiently and concentratedly transforms into larger snow amount. Furthermore, the complex relationship between snow amount, snow coverage and surface albedo restricts the transformation of snow amount to surface albedo bias, and thus to cold bias. We reveal the spatio‐temporally divergent transformation of wet to cold bias on the TP during snow season, and these conclusions will contribute to a better improvement of snow and climate modeling on the TP. Key Points: WRF simulations significantly overestimate snow amount and delay snow phenology on the Tibetan Plateau (TP)Snowfall bias is not always transformable into snow amount bias, depending on snow phenologyComplex relationship between snow amount and surface albedo restricts the transformation of wet to cold bias on the TP [ABSTRACT FROM AUTHOR]

Summary: Current estimates of temperature effects on plants mostly rely on air temperature, although it can significantly deviate from leaf temperature (Tleaf). To address this, some studies have used canopy temperature (Tcan). However, Tcan fails to capture the fine‐scale variation in Tleaf among leaves and species in diverse canopies.We used infrared radiometers to study Tleaf and Tcan and how they deviate from air temperature (ΔTleaf and ΔTcan) in multispecies tropical tree plantations at three sites along an elevation and temperature gradient in Rwanda.Our results showed high Tleaf (up to c. 50°C) and ΔTleaf (on average 8–10°C and up to c. 20°C) of sun‐exposed leaves during 10:00 h–15:00 h, being close to or exceeding photosynthetic heat tolerance thresholds. These values greatly exceeded simultaneously measured values of Tcan and ΔTcan, respectively, leading to strongly overestimated leaf thermal safety margins if basing those on Tcan data. Stomatal conductance and leaf size affected Tleaf and Tcan in line with their expected influences on leaf energy balance.Our findings highlight the importance of leaf traits for leaf thermoregulation and show that monitoring Tcan is not enough to capture the peak temperatures and heat stress experienced by individual leaves of different species in tropical forest canopies. [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]

Dry‐ and wet‐bulb temperature (Td and Tw) are usually to define heatwaves (HWs) which have been enhanced under anthropogenic climate change (ACC) and urbanization. However, responses of various types of HWs (i.e., dry HWs, only high Td; humid HWs, only high Tw; hybrid HWs, both high Td and Tw; total HWs, high Td or Tw), to ACC and urbanization remain unknown. In this study, both observations and simulations show significantly increasing occurrence probability of total HWs over China during 1971–2020, whereas this increase is mainly reflected in hybrid HWs, followed by dry HWs and humid HWs. 68.2%–93.0% of the observed increases in the above four types of HWs can be attributed to ACC; on the other hand, urbanization tends to suppress humid HWs but enhance dry HWs, as a result of contributing to the increase of hybrid HWs by 10.9%. Under future ACC, total HWs are projected to be more frequent as expected, which is mainly sourced from the increasing hybrid HWs because dry/humid HWs are projected to be steady/downward. As a consequence, urban population exposure to ACC‐induced total HWs would remarkably increase to 83.55 billion person‐days by the 2090s, 89.5% of which can be attributed to hybrid HWs. Urbanization would amplify this population exposure of ACC‐induced hybrid HWs from 74.79 billion person‐days to 110.9 billion person‐days. Our results underscore the importance of improving understanding of hybrid HWs in urban areas and developing targeted adaptation planning on a warmer planet. Plain Language Summary: Under global warming and urbanization, increases in heatwaves (HWs) characterized by air temperature and humidity, have profound adverse effects on human health and socio‐economic well‐being. In this study, HWs are divided into four types: humid HWs (dominated by high air humidity), dry HWs (dominated by high air temperature), hybrid HWs (both high temperature and high humid), and total HWs (encompassing all the three above types), to investigate changes in HWs under different temperature and humidity conditions and their responses to anthropogenic climate change (ACC) and urbanization. Both observations and simulations show that occurrence probability of the four types of HWs increased over China in recent decades, of which ACC contributes to 68.2%–93.0% of intensification of HWs. The increasing occurrence probability of total HWs is mainly reflected in hybrid HWs, followed by dry HWs and humid HWs. Urbanization tends to inhibit (promote) rise in humid HWs (dry HWs), resulting in an increase in hybrid HWs. Under urban expansion and global warming, urban population in China will be more exposed to extremes of humid and hot conditions (hybrid and total HWs), especially in densely populated and rapidly urbanizing areas. Key Points: Historical increasing likelihood of total heatwaves (HWs) over China is dominated by that of hybrid HWsUrbanization tends to suppress (enhance) humid (dry) HWs and hence increase likelihood of hybrid HWs under anthropogenic climate changeFuture anthropogenic warming and urban expansion jointly lead to remarkable increase of urban population exposure to hybrid HWs [ABSTRACT FROM AUTHOR]

The atmospheric activity on Kalimantan Island (KI) is important for regulating regional weather and climate. This study investigates the effect of autumn soil moisture over KI on following winter precipitation over southern China (SC) during 1968–2014. The results show that the autumn soil moisture over the KI has a significant negative correlation with subsequent winter precipitation over SC. The correlation remains statistically significant when using partial correlation to filter out the concurrent influences of El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) signals. The soil moisture anomalies over KI, which initiate in the autumn and persist into the winter, lead to changes in local thermal conditions and atmospheric temperature. Negative soil moisture anomalies over KI will result in positive heating anomalies of the atmosphere above the land surface. This atmospheric heating causes ascending motion, which creates a semi‐closed vertical circulation from KI to the tropical northwest Pacific. This vertical circulation would strengthen the northwest Pacific anticyclone and weaken the East Asian winter monsoon (EAWM). Consequently, southwesterly water vapour flux prevails in the SC as well as the South China Sea (SCS), facilitating the transportation of more water vapour into the SC. Simultaneously, water vapour convergence in the SC. Collectively, these contribute to an addition of precipitation over SC. [ABSTRACT FROM AUTHOR]

Due to their significant influence on large‐scale atmospheric circulation and climate anomalies, the variability of Arctic sea ice and Eurasian snow cover during late autumn and their combined effects have garnered increasing attention. This study aims to investigate the physical mechanism underlying the covariation among the Barents‐Kara Seas (BKS) sea ice concentration (SIC), Eurasian snow cover extent (SCE) and the ensuing winter Eurasian surface air temperature (SAT). The statistics results of singular value decomposition suggest a significant linkage between the decreased BKS SIC, zonal “negative–positive” dipole SCE anomalies over Eurasia in November and cold Eurasian SAT in January–February (JF). Observational diagnosis analyses about the meridional moisture, heat transport and surface heat flux demonstrate that subpolar Eurasian anticyclonic circulation plays a crucial role in connecting the predominant modes of SIC and SCE. Furthermore, the BKS SIC and Eurasian SCE anomalies can jointly excite upward‐propagating planetary waves into the stratosphere, while simultaneously reducing the subpolar meridional temperature gradient. This results in westerly wind deceleration and favours the continuous planetary wave propagation. Consequently, the stratospheric polar vortex is significantly weakened, along with negative Northern Annular Mode anomalies propagating downward from the stratosphere to troposphere. Negative‐phase Arctic Oscillation anomalies correspondingly develop during JF, resulting in widespread cold anomalies over the Eurasian continent. These results are further confirmed by numerical sensitivity experiments from the Community Atmosphere Model forced by the above mentioned SIC and SCE anomalies. The empirical hindcast model analyses further suggest that the prediction skill of JF Eurasian SAT is enhanced when both the November BKS SIC and Eurasian SCE signals are considered. [ABSTRACT FROM AUTHOR]

ABSTRACT Freezing air temperatures kill most leaves, yet the leaves of some species can survive these events. Tracking the temporal and spatial dynamics of freezing remains an impediment to characterizing frost tolerance. Here we deploye time‐lapse imaging and image subtraction analysis, coupled with fine wire thermocouples, to discern the in situ spatial dynamics of freezing and thawing. Our method of analysis of pixel brightness reveals that ice formation in leaves exposed to natural frosts initiates in mesophyll before spreading to veins, and that while ex situ xylem sap freezes near 0°C, in situ xylem sap has a freezing point of −2°C in our model freezing‐resistant species of Lonicera. Photosynthetic rates in leaves that have been exposed to a rapid freeze or thaw do not recover, but leaves exposed to a slow, natural freezing and thawing to −10°C do recover. Using this method, we are able to quantify the spatial formation and timing of freezing events in leaves, and suggest that in situ and ex situ freezing points for xylem sap can differ by more than 4°C depending on the rate of temperature decline. [ABSTRACT FROM AUTHOR]

Most C–H bond activations of natural gas alkanes rely on transition metal complexes. Activations by using main-group systems have been reported but required heating or photo-irradiation under high atmospheric pressure with rather low regioselectivity. Here we report that Lewis acid-carbene adducts facilely undergo oxidative additions to C–H bonds of ethane, propane and n-butane with high selectivity under room temperature and atmospheric pressure. The Lewis acids can be moved by the addition of a base and the carbene-derived products can be easily converted into aldehydes. This work offers a route for main-group element compounds to selectively functionalise C–H bonds of natural gas alkanes and other small molecules. Activation of natural gas alkanes using main-group systems typically requires heating or photo-irradiation under high atmospheric pressure with low regioselectivity. Here the authors report Lewis acid-carbene adduct activation of C–H bonds in ethane, propane and n-butane under one atmospheric pressure and at room temperature with high selectivity. [ABSTRACT FROM AUTHOR]

Changes in the soil freeze–thaw status will inevitably affect the thermal conditions and properties of the Tibetan Plateau (TP), thereby affecting its upper atmosphere, and further afield in East Asia and even globally. In this study, using the soil temperature simulated by the Community Land Model Version 5.0 (CLM5.0), the timing and duration of the soil freeze–thaw status were divided into freeze start‐date, freeze end‐date and freeze duration. Then, using linear trend estimation, correlation analysis and other methods, the changes in the spatiotemporal distribution of the timing and duration of the soil freeze–thaw status from 1979 to 2018 over the TP were analysed, and the relationships between them and surface temperature, altitude and latitude were analysed. The results obtained were as follows: (1) The soil temperature simulated by CLM5.0 can reasonably reproduce the seasonal changes in multilayer soil temperature, and correlated well with observations. Simulated by CLM5.0 of the time and duration of the soil freeze–thaw status also correlated well with observations. (2) The spatial distribution of the soil freeze–thaw status is characterized by a trend of delayed freezing, advanced thawing and shortened freeze duration from northwest to southeast over the TP. From 1979 to 2018, the freeze start‐date postponed by 7.3 days and became delayed at a rate of 1.9 days per decade, while the freeze end‐date advanced by 6.4 days at a rate of 1.7 days per decade, and the freeze duration shortened by 13.7 days at a rate of 3.6 days per decade. The timing and duration of the soil freeze–thaw status vary across different regions of the TP. The freeze start‐date in all areas of the TP has been delayed in the past 39 years. Except for the subcold zone and arid regions of the TP, the freeze end‐date has occurred earlier and the freeze duration has shortened, with the most significant changes in the subcold zone and humid regions, while the freeze end‐date has advanced at a rate of 3.6 days per decade and the freeze duration has shortened at a rate of 6.3 days per decade. (3) The timing and duration of the soil freeze–thaw status are significantly correlated with surface air temperature, elevation and latitude, exceeding the 99% confidence level. The correlation between the timing and duration of the soil freeze–thaw status and surface temperature is strongest, followed by altitude, and correlation with latitude is weaker. The correlation between surface air temperature and the timing and duration of the soil freeze–thaw status in the western TP is stronger than that in the eastern TP. The rate of change in the soil freeze–thaw status increases with altitude to 3000 m above sea level, while this rate decreases with elevation above 3000 m. The rate of change in the soil freeze–thaw status is greatest at 29°N, while the rate of delay in the freeze start‐date is minimal at 33°N and the rates of advancement in the freeze end‐date and shortening of the freeze duration are minimal at 35°N. [ABSTRACT FROM AUTHOR]

Introduction: Amidst escalating global temperatures, increasing climate change, and rapid urbanization, addressing urban heat islands and improving outdoor thermal comfort is paramount for sustainable urban development. Green walls offer a promising strategy by effectively lowering ambient air temperatures in urban environments. While previous studies have explored their impact in various climates, their effectiveness in humid climates remains underexplored. Methods: This research investigates the cooling effect of a green wall during summer in a humid climate, employing two approaches: Field Measurement-Based Analysis (SC 1: FMA) and Deep Learning Model (SC 2: DLM). In SC 1: FMA, experiments utilized data loggers at varying distances from the green wall to capture real-time conditions. SC 2: DLM utilized a deep learning model to predict the green wall's performance over time. Results: Results indicate a significant reduction in air temperature, with a 1.5°C (6%) decrease compared to real-time conditions. Long-term analysis identified specific distances (A, B, C, and D) contributing to temperature reductions ranging from 1.5°C to 2.5°C, highlighting optimal distances for green wall efficacy. Discussion: This study contributes novel insights by determining effective distances for green wall systems to mitigate ambient temperatures, addressing a critical gap in current literature. The integration of a deep learning model enhances analytical precision and forecasts future outcomes. Despite limitations related to a single case study and limited timeframe, this research offers practical benefits in urban heat island mitigation, enhancing outdoor comfort, and fostering sustainable and climate-resilient urban environments. [ABSTRACT FROM AUTHOR]

A large input delay, parametric uncertainties, matched disturbances and mismatched disturbances exist extensively in variable air volume air-conditioning systems, which can deteriorate the control performance of the room temperature and even destabilize the system. To address this problem, an adaptive-gain command filter control framework for the room temperature of variable air volume air-conditioning systems is exploited. Through skillfully designing an auxiliary system, both the filtered error and the input delay can be compensated concurrently, which can attenuate the effect of the filtered error and the input delay on the control performance of the room temperature. Then, a smooth nonlinear term with an adjusted gain is introduced into the control framework to compensate for parametric uncertainties, matched disturbances and mismatched disturbances, which relieves the conservatism of the controller gain selection. With the help of the Lyapunov theory, both the boundedness of all the system signals and the asymptotic tracking performance for the room temperature can be assured with the presented controller. Finally, the contrastive simulation results demonstrate the validity of the developed method. [ABSTRACT FROM AUTHOR]

Even though the streamer process can be identified in nanoseconds and microseconds through experimental measurements, the breakdown time of air discharge is still unknown. The instability of electrons is suspected to be an attachment-instability phenomenon of the channel conductivity. We investigated breakdown time across milliseconds to better understand how the oxygen excitations of the 200–400 nm range influence a high-conductivity channel even with a weaker applied voltage. Experiments were performed with positive impulse voltages ranging from +42 to +75 kV in the step of +6 kV at a 3 cm gap between needle-to-plane electrodes in a horizontal configuration. A spectrometer with an integration time of 70 ms was used to capture the spectra during voltage discharge. The shortest breakdown time was found at +60 kV with 77 ns compared to +66, +72, and +75 kV. We conclude that the shorter breakdown time at +60 kV is primarily due to the oxygen-excited state in O IV at 262.999 nm. This state helps maintain electron flow by preventing electron loss, with a decay time of 2.5 µs, while releasing Joule heat at a temperature of 26,003 K, which optimizes conductivity. This process occurs before the recombination of the O I line at 777.417 nm, which has a significantly shorter decay time of 27 ns. [ABSTRACT FROM AUTHOR]

The hydration heat generated during the concreting of cast-in-place piles causes thermal disturbance to the surrounding permafrost, leading to its thawing. This further affects the stability of the pile foundation and degrades the construction progress. To explore the influence mechanisms of the concrete hydration heat on the permafrost temperature field around the pile, as well as that of different construction seasons on the pile-side boundary conditions and permafrost temperature field, monitoring results of on-site tests and numerical simulation were used to analyze the distribution law of the pile soil temperature field in space and time, and the pile-side boundary conditions and permafrost temperature field during construction seasons. The results show that the temperature trend of the pile foundation can be divided into three stages: a rapid rise phase (0∼2 d), a rapid decline phase (2∼10 d), and a slow decline and stabilization phase (10∼90 d). As the radial distance from the pile center decreases, there occur a corresponding acceleration in temperature increase and an elevated maximum temperature rise (MTR). The influence range of the molding temperature and the hydration heat is about 1∼2 times the pile diameter and less than 1.5 m in the depth direction. Compared to the atmospheric temperature, there is a lag in the change in the permafrost temperature caused by accumulation of ground temperature, and the significant difference between the two leads to an increased rate of heat exchange at the boundary condition. Conducting drilling operation and cast-in-place pile construction in the cold seasons is conducive to reducing the thermal disturbance to the permafrost around the pile in permafrost areas. [ABSTRACT FROM AUTHOR]

Simple Summary: Low-pressure systems frequently occur during the summer in coastal areas and can be detrimental to commercial poultry houses. The effects of air temperature and humidity vary across different periods. Throughout the generation of low-pressure systems, landfall, and disappearance, air temperature and humidity changes can interfere with the housing environment. However, farmers often overlook the impact of low-pressure systems on large-scale poultry houses, which may impair the production of laying hens. This study investigated the effects of the different low-pressure systems on the housing environment and egg production in large-scale poultry houses in China. The results indicated that a single low-pressure system reduced the laying performance, whereas a sustained low-pressure system mitigated the impact on egg production. This study aimed to determine the effect of low-pressure systems on the environment and the laying performance of large-scale poultry houses during the summer and to provide a basis for farmers to adjust their environmental control strategies under extreme weather conditions. Low-pressure systems (LPSs) are among the most critical weather systems, producing excessive precipitation that causes air temperatures to drop and rise considerably. Acute temperature changes directly affect poultry feed intake (FI) and laying performance. To explore the effects of LPSs on hens, the parameters of air temperature, relative humidity, egg production, and feed utilization efficiency were evaluated during different LPSs in three houses. Results indicated that about 2.8 ± 0.7 d, 2.4 ± 0.5 d, and 2.4 ± 0.5 d before the LPS landfall in houses 1, 2, and 3, respectively, the indoor air temperature started to decrease, with the average decreases being 1.7 °C ± 0.4 °C, 2.4 °C ± 0.6 °C, and 1.8 °C ± 0.4 °C, respectively. Significant differences were observed between different LPSs for reducing indoor air temperature (p < 0.05) in the three houses. In house 1, the egg production rates (EPRs) were decreased by 6.6% and 1.1% when LPSs 1 and 2 landed. The average egg weight (AEW) and FI during the LPS landfall were significantly higher than those before the LPS landfall (p < 0.01). Under successive LPSs landfall in the three houses, the EPRs initially reduced by 3.9%, 4.0%, and 0.5%, respectively, but the second LPS event increased the EPRs by 1.8%, 5.3%, and 1.0%, respectively. Furthermore, the LPS landfall increased the feed conversion ratio (FCRe) in the three houses, all above 2.00. In conclusion, LPSs can reduce heat stress, lower the EPRs, and lead to higher FI, FCRe, and AEW. [ABSTRACT FROM AUTHOR]

Stem water content serves as a pivotal parameter that reflects the plant vitality and maintains their internal water balance. Given the insufficient comprehension regarding the stem water content characteristics and its influencing factors during different stages of the overwintering period, the study focused on Acer truncatum Bunge and developed an Internet of Things (IoT)-based ecological information monitoring system. The system incorporated a proprietary stem water content sensor, allowing non-invasive, in-situ and real time acquisition of stem water content while monitoring diverse environmental parameters. We conducted a detailed elucidation of stem water content variation characteristics and their responses to diverse environmental factors. The results showed: (1) During the overwintering period, stem water content exhibited diurnal variations characterized by " daytime ascent and nighttime descent" across the three stages, exhibiting differences in the moment when the stem water content reaches extremal values and daily fluctuations ranges. Stem water content exhibited minimal fluctuations during deciduous and bud-breaking stages but experienced significant freezing-thawing alternations during the dormant stage, leading to an increased daily fluctuation range. (2) The Pearson correlation coefficients between environmental parameters and stem water content varied dynamically across stages. Path analysis revealed that during the deciduous stage, stem temperature and saturation vapor pressure deficit were dominant factors influencing stem water content; during dormant stage, air temperature and saturation vapor pressure deficit directly impacted stem water content; during the bud-breaking stage, the primary parameters affecting stem water content were saturation vapor pressure deficit and stem temperature. The study provides valuable insights into unveiling the water transport patterns within tree stems tissue and their environmental adaptation mechanisms during the overwintering period, aiding in the scientific development of winter management strategies to protect trees from severe cold and freezing damage, while fostering healthy growth in the subsequent year. [ABSTRACT FROM AUTHOR]

Drought is one of the most serious natural disasters with the widest distribution, the highest frequency, and the greatest economic losses in the world. A grave threat has been posed to agricultural production, food security, and socioeconomic development. It is of great significance to timely and accurately monitor the drought at the regional scale. In this study, the NDVI-LST feature space was constructed using the MOD11A2 surface temperature 8-d synthetic product and MOD13A1 vegetation index 16-d synthetic product. The data was collected from the land surface temperature (LST) and normalized difference vegetation index (NDVI). Temperature vegetation dryness index (TVDI) was captured from the Guanzhong areas in a 20-year time series from 2001 to 2020. The spatial and temporal distribution of drought was analyzed to determine the causes and future trends of natural disasters. The results show that: 1) It was feasible to carry out drought monitoring on a regional scale using the TVDI remote sensing index. The average TVDI was 0.57 over the past 20 years. The drought type was in a normal state in general. The highest annual average TVDI was found in 2013 and the lowest in 2006. The average TVDI value fluctuated greatly during the 20-year period. Drought also shared strong regional characteristics, indicating a spatial distribution pattern of wet in the southwest, dry in the center and northeast, and normal in the north. 2) The spatial and temporal trends of drought showed that 82.00% of the areas had relatively stable droughts, and only 8.05% of the areas were with improved droughts. As such, there was a relatively small variation in the drought condition; Combined with the Hurst index, the future trend of drought was characterized by a relatively small amount of change. There was an anti-sustainable trend of drought in the future; Combined Hurst index and TVDI trend, 7.71% of the study area was continuously wet in the future, and 36.24% of the area was changed from drought to wet. 3) The TVDI value was positively correlated with the air temperature, while negatively correlated with the precipitation. There was a similar spatial distribution pattern of the 20-year average TVDI and the annual average air temperature. The air temperature and precipitation shared a similar distribution in the spatial pattern. The degree of drought depended mainly on the air temperature and precipitation. Meanwhile, the degree of aridity was negatively correlated with both elevation and slope. The arid and more arid types were mainly distributed in the central plains with low elevations and small slopes. While the moist and more moist types occupied a larger area in the mountainous areas south of the Qinling Mountains with high elevation. The TVDI values varied with months in the different land use types in the study area. The cropland and construction land presented the highest TVDI values, with the annual mean values of 0.76 and 0.75, respectively, whereas, the woodland was the smallest TVDI value, with an annual mean value of 0.45. Therefore, the woodland and grassland cover can be expected to positively mitigate the drought. The TVDI can be used to quantify the drought conditions from the regional scale. Remote sensing drought monitoring can also provide a theoretical foundation and scientific basis for the formulation of drought countermeasures in Guanzhong areas. [ABSTRACT FROM AUTHOR]

In recent decades, the annual mean temperature has increased, with unusual alternations of hot and cold years. In addition, the changes in temporal precipitation patterns are caused by complex interactions between temperature change, the global water cycle, and other components of the Earth's systems. To construct a statistical model of these temporal patterns in terms of temperature and precipitation, we propose a logistic mixture of spatial multivariate penalized regression splines for temporal profiles and apply this model to the contiguous United States climate data over 123 years (1900 to 2022) at 252 weather stations. The results reveal that the proposed model identifies climatologically meaningful clusters of weather stations in the contiguous United States with two important meteorological variables, temperature and precipitation, identifying the climate change patterns of each climate zone. The surface air temperature increased in the Northeast and West (Mountain and Pacific) regions, where the climate is affected by the continental Arctic air. A notable increment of precipitation also occurred in the Northeast. In contrast, the South region, where the climate is affected by the tropical Atlantic Ocean, is more stable than other regions in terms of year-to-year variations in temperature and precipitation. [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]

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]

A new composite material, named TSC/AXAD-2, was developed by incorporating a bis-thiosemicarbazone derivative (TSC) into Amberlite XAD-2 to extract Pb2+ ions from wastewater. The new composite was characterized using XPS, TGA, FTIR, BET, EDX, 1H-NMR, 13C-NMR, and GC-MS analyses. The sorption parameters, such as pH value of media, equilibrium time, initial Pb2+ ion concentration, composite dose, temperature, and eluting agents, were methodically optimized. The utmost adsorption capacity is 45.3 mg.g−1; it was achieved at pH value of of 5.5, 15 min of agitation, room temperature, and initial concentration of 200 mg.L−1 Pb2+ ions. The isotherm studies revealed that the adsorption process closely matches the Langmuir model, with a theoretical retention capacity of 46.12 mg.g−1. Furthermore, kinetic modeling using the pseudo-first-order accurately depicted the adsorption of Pb2+ ions. The thermodynamic study suggested that the adsorption process is exothermic, spontaneous, and more favorable at lower temperatures. The desorption of Pb2+ ions from the loaded composite was conducted with 1.0 M of either HCl or HNO3. The TSC/AXAD-2 composite successfully met WHO and FAO guidelines for removal of Pb2+ ions from wastewater before its discharge into the marine environment. [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]

Increasing summer temperatures and higher probabilities of extreme heat events have led to concerns about tree damage and mortality. However, insufficient attention has been given to conditions leading to heat-related regeneration failures in temperate forests. To address this, managers need to understand how microclimate varies under a range of overstory conditions. We measured air temperatures at 2 cm above-ground underneath a gradient of canopy cover on south-facing slopes in recently thinned Douglas-fir stands in western Oregon, USA. To expand the ecological relevance of these data to impacts on regeneration, we created the stress degree hours (SDH) metric, representing the amount of time—and by how much—temperatures exceeded biologically relevant stress thresholds. Overall, for every 10% increase in canopy cover, maximum temperatures at 2 cm were 1.3 °C lower, the odds of temperatures exceeding stress thresholds for conifer regeneration declined by a multiplicative factor of 0.26, and the total of SDH decreased by 40%. These reductions are large enough to be worthy of attention when managing for tree regeneration. However, data collected during the Pacific Northwest Heat Dome in June 2021 indicate that with various climate change scenarios and heatwave occurrences, temperatures will be unfavorable for regeneration regardless of overstory cover. [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]

In recent years, extreme climate events have shown to be occurring more frequently. As a highly populated area in central China, the Jialing River Basin (JRB) should be more deeply explored for its patterns and associations with climatic factors. In this study, based on the daily precipitation and atmospheric temperature datasets from 29 meteorological stations in JRB and its vicinity from 1960 to 2020, 10 extreme indices (6 extreme precipitation indices and 4 extreme temperature indices) were calculated. The spatial and temporal variations of extreme precipitation and atmospheric temperature were analyzed using Mann–Kendall analysis, to explore the correlation between the atmospheric circulation patterns and extreme indices from linear and nonlinear perspectives via Pearson correlation analysis and wavelet coherence analysis (WTC), respectively. Results revealed that among the six selected extreme precipitation indices, the Continuous Dry Days (CDD) and Continuous Wetness Days (CWD) showed a decreasing trend, and the extreme precipitation tended to be shorter in calendar time, while the other four extreme precipitation indices showed an increasing trend, and the intensity of precipitation and rainfall in the JRB were frequent. As for the four extreme temperature indices, except for TN10p, which showed a significant decreasing trend, the other three indices showed a significant increasing trend, and the number of low-temperature days in JRB decreased significantly, the duration of high temperature increased, and the basin was warming continuously. Spatially, the spatial variation of extreme precipitation indices is more obvious, with decreasing stations mostly located in the western and northern regions, and increasing stations mostly located in the southern and northeastern regions, which makes the precipitation more regionalized. Linearly, most of the stations in the extreme atmospheric temperature index, except TN10p, show an increasing trend and the significance is more obvious. Except for the Southern Oscillation Index (SOI), other atmospheric circulation patterns have linear correlations with the extreme indices, and the Arctic Oscillation (AO) has the strongest significance with the CDD. Nonlinearly, NINO3.4, Pacific Decadal Oscillation (PDO), and SOI are not the main circulation patterns dominating the changes of TN90p, and average daily precipitation intensity (SDII), maximum daily precipitation amount (RX1day), and maximum precipitation in 5 days (Rx5day) were most clearly associated with atmospheric circulation patterns. This also confirms that atmospheric circulation patterns and climate tend not to have a single linear relationship, but are governed by more complex response mechanisms. This study aims to help the relevant decision-making authorities to cope with the more frequent extreme climate events in JRB, and also provides a reference for predicting flood, drought and waterlogging risks. [ABSTRACT FROM AUTHOR]

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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]

AbstractThe performance capability of granular activated carbon (GAC) adsorption in terms of disinfection by-product (DBPs) removal was investigated with synthetic water containing 1) trihalomethanes (THMs), 2) haloacetronitriles (HANs), and 3) Mix-THMs & HANs. The initial 20 min of adsorption resulted in the maximum adsorption rate, with the total THMs, total HANs, and total Mix–THMs & HANs being 4.972, 2.071, and 6.460 µg/gGAC-min, respectively. GAC dosage affects the adsorption selectivity of THMs and HANs. Under a low GAC dosage, the selectivity of GAC adsorbs more bromo-THMs than chloro-THMs. The adsorption selectivity of THMs on GAC following bromoform > dibromochloromethane > bromodichloromethane > chloroform was investigated. As the GAC concentration increased, the selectivity of THM adsorption by GAC became comparable. Chloro-HAN, in contrast to THMs, has a higher adsorption selectivity than bromo-HAN. Trichloroacetonitrile was removed by GAC more rapidly than the other HAN species when the GAC dose was increased. The toxin of bromoform was primarily eliminated through GAC adsorption, caused by a greater removal rate than that of the other THMs. As an implemented measure, GAC is introduced to reduce THMs and HANs and the toxic contents associated with THMs and HANs. [ABSTRACT FROM AUTHOR]

AbstractThe current work is directed to study the synthesis of nanostructured polypyrrole (PPy) using an azo dye as a soft template. The as-prepared PPy was applied for the adsorption of methylene blue (MB) dye. The influence of the synthesis conditions on the morphology of the synthesized nanostructured PPy was examined. Different analytical tools were used for characterization of the synthesized nanostructured PPy. The surface area of the as-prepared nanostructured PPy was measured to be 30 m2 g−1 and hence it was applied for the adsorption of MB as a model of organic dyes. The influence of different parameters on the adsorption/removal of MB was investigated. It was found that the alkaline medium enhances the adsorption rate and the adsorption capacity. Upon increasing the system temperature, the adsorption capacity of nanostructured PPy toward MB dye increased. Different kinetic models were studied, and the current system was found to follow pseudo-second order as well as intraparticle diffusion kinetic models. The equilibrium data were examined by applying Langmuir, Freundlich, and Tempkin isotherms and the first model preferably described MB dye adsorption onto the nanostructured PPy. Reusability of the synthesized nanostructured PPy for the adsorption of MB dye was investigated for many cycles. [ABSTRACT FROM AUTHOR]

1. This study evaluated the effects of cyclic eggshell temperature between 10 and 14 d of embryogenesis on traits viz. the expression of MYOZ2, PPARγ and GPx7 in breast muscle, meat quality and incidence of white striping at slaughter age.2. Eggs were obtained from Cobb and Ross broiler breeders to investigate the response of breeds to eggshell temperature, which regulated air temperature. A total of 784 eggs were incubated at either the control eggshell temperature (37.8°C) from 0 to 18 d or exposed to cyclic high eggshell temperature (CHT) at 38.8°C for 6 h/d between 10 and 14 d of incubation. The temperature was 36.8°C between 18 and 21 d. Hatched chicks were reared under optimum rearing conditions. The birds were sampled at 19 d of incubation, at hatch and at 42 d post-hatch.3. There was no effect of eggshell temperature on yolk-free body weight and residual yolk sac weight. The CHT chicks had wider breasts on the day of hatching.4. At hatch and 42d post-hatch, PPARγ expression in Cobb-CHT was upregulated 4.78-fold and downregulated 3.28-fold, respectively, compared to the Cobb-control. At slaughter age, chickens from Ross-CHT had 1.98- and 2.33-fold upregulated PPARγ and GPX7 expressions, respectively, compared to Ross-control. The CHT increased GPx7 expression in the Cobb-CHT day-old chicks compared to the Cobb-control. On ED19, MYOZ2 expression was upregulated in Cobb and downregulated in Ross by CHT.5. The effects of breed and eggshell temperature on pH15, L*, a*, expressible juice and cooking loss were not significant. The CHT increased the incidence of severe white striping lesions in Ross chickens.6. It was concluded eggshell temperature modulated embryo development, incidence of white striping and expression of related genes differently in the two commercial breeds. [ABSTRACT FROM AUTHOR]

In recent decades, India has witnessed an increase in the intensity, frequency, and spread of extreme weather events. The widespread increase in extreme precipitation over the Western Coast of India is a matter of great concern. The factors contributing to such devastating extreme precipitation remain unclear due to the variability present in meteorological and oceanic variables and associated large‐scale circulations. Using reanalysis and observed datasets, we attempted to identify a combination of dynamic, thermodynamic, and cloud microphysics processes contributing to the anomalous precipitation from August 1 to 10, 2019 against its climatology. Our key findings highlight the crucial role of warm sea surface temperatures (anomaly >1.4°C), outgoing longwave radiation (anomaly <−50 W·m−2), and atmospheric temperature (anomaly over the ocean is >1.6°C) in enhancing the moisture‐holding capacity of the atmosphere by almost 10%. This elevated moisture, propelled by intensified low‐level winds (anomalies exceeding 4 m·s−1), leads to a shift from ocean to land. Notably, we observe that vertical updrafts (anomalies >−0.4 m·s−1) contribute to increased atmospheric instability and moisture convergence. The presence of an ample amount of cloud hydrometeors, with anomalies surpassing 2.5 × 10−4 kg·kg−1, establishes conditions conducive to sustained intense precipitation. Our findings deepen our understanding of the complex relationships between ocean and atmospheric dynamics, and wind patterns, and emphasize their pivotal influence on regional weather patterns and land surface hydrology. [ABSTRACT FROM AUTHOR]

This is the first journal article from the ASHRAE research project RP 1865, “Optimizing Supply Air Temperature Control for Dedicated Outdoor Air Systems,” focusing on the large-scale energy performance evaluation of the optimal control of dedicated outdoor air systems (DOAS). DOAS is a type of air handling system that is installed in buildings to ensure proper ventilation for the built environment. It is acknowledged that DOAS with proper operation strategies can provide sufficient ventilation and dehumidification while achieving energy efficiency. In this regard, there have been efforts to develop advanced control sequences (e.g., optimal control) for DOAS. Still, limited studies have demonstrated the effectiveness of such DOAS controls on a larger scale under varying climate zones with different DOAS configurations. To fill the research gap, this study aims to quantify the energy-saving potentials of applying an optimal supply air temperature (SAT) control strategy for DOAS considering diverse configurations of HVAC systems in various climate conditions across the United States. For this study, we first developed a total of 180 EnergyPlus models accommodating different types of buildings (i.e., detailed medium-sized office and primary school) and HVAC systems (i.e., DOAS types, DOAS sizes, and terminal units) under varying ASHRAE climate zones (i.e., 2A, 3B, 4A, 4C, 6A, and 6B). Next, genetic algorithm (GA)-based optimizations were conducted to determine the optimal DOAS SAT control that would minimize the energy cost of the entire HVAC system operation. Our study of comparing the optimal control to a typical rule-based control (i.e., outdoor air temperature-based reset control) revealed approximately 4–34% of energy cost saving potential by optimizing the DOAS SAT control sequence. [ABSTRACT FROM AUTHOR]

Summary Climate change not only leads to higher air temperatures but also increases the vapour pressure deficit (VPD) of the air. Understanding the direct effect of VPD on leaf gas exchange is crucial for precise modelling of stomatal functioning. We conducted combined leaf gas exchange and online isotope discrimination measurements on four common European tree species across a VPD range of 0.8–3.6 kPa, while maintaining constant temperatures without soil water limitation. In addition to applying the standard assumption of saturated vapour pressure inside leaves (ei), we inferred ei from oxygen isotope discrimination of CO2 and water vapour. ei desaturated progressively with increasing VPD, consistently across species, resulting in an intercellular relative humidity as low as 0.73 ± 0.11 at the highest tested VPD. Assuming saturation of ei overestimated the extent of reductions in stomatal conductance and CO2 mole fraction inside leaves in response to increasing VPD compared with calculations that accounted for unsaturation. In addition, a significant decrease in mesophyll conductance with increasing VPD only occurred when the unsaturation of ei was considered. We suggest that the possibility of unsaturated ei should not be overlooked in measurements related to leaf gas exchange and in stomatal models, especially at high VPD. [ABSTRACT FROM AUTHOR]

Midlatitude Europe (ME) emerges as a prominent heatwave hotspot with rapid increases in summer surface air temperature and heatwave days since 1979, surpassing the global land averages by approximately 2.6 and 2.3 times, respectively. The circulation analogs‐based dynamic adjustment reveals that approximately 38% and 35% of these trends result from shifts in zonal dipolar circulation patterns over the North Atlantic (NA) and Europe, crucial for the enhanced warming compared to the global land average. The circulation changes are associated with warming sea surface temperatures in the NA. This warming pattern resembles the Atlantic Multidecadal Variability and is predominantly induced by greenhouse gases. Moreover, the stronger air temperature response in ME to decreased aerosols amplifies warming, contributing to the rapid increase in heatwave frequency. These findings highlight a prominent influence of anthropogenic forcings on the swift surge of European heatwaves compared to global land, with a potential implication for adaptation strategies and risk management. Plain Language Summary: Midlatitude Europe is experiencing a significant increase in heatwaves, with summer temperatures and heatwave occurrences rising much faster than the global land averages since 1979. One of the key contributors to this rapid warming is the changes in zonal dipolar circulation patterns over the NA and Europe, which are linked to the warm sea surface temperatures in the NA. This warming pattern, resembling the Atlantic Multidecadal Variability, is largely caused by greenhouse gases and additionally influenced by reduced aerosols and natural forcing. Furthermore, the stronger response of air temperatures in midlatitude Europe to decreased aerosol emissions intensifies summer warming, contributing to a rapid increase in heatwave days. These findings highlight the significant impact of anthropogenic forcings on the observed surge of heatwaves in Europe compared to global land, with an important implication for developing strategies to adapt to these changing climate conditions and managing the associated risks. Key Points: Midlatitude Europe exhibits more rapid increases in summer heatwave frequency than the global land averages in recent decadesAtmospheric circulation changes contributing about one third of the observed warming trend, further intensify the rapid increases in summer heatwave frequencyLocal air temperature response to reduced aerosol emissions contributes about half of the enhanced warming compared to the global land average [ABSTRACT FROM AUTHOR]

Firefighters in such serious environments (i.e., hazardous flames and radiant heat, high air temperatures, hot chemicals and liquids) must wear fire protective clothing during fire extinguishing and rescue operations. Many studies in the field of fire protective clothing have been conducted to evaluate the protective, mechanical and comfort performance of fire protective clothing. A comprehensive review of the literature has been undertaken to provide a better understanding of single-layer and multilayer fire protective clothing with protective, mechanical and comfort performance. Factors affecting the durability of protective clothing in the light of their expected retirement age and a number of significant standards for laboratory and manikin testing are discussed. The comfort of wearing clothing is another aspect that needs special consideration when designing a multilayered fire protective suit. A number of emerging technologies have been outlined to address the various challenges of the present day. [ABSTRACT FROM AUTHOR]

Asparagus (Asparagus officinalis L.) is an important vegetable crop in southern Ontario, Canada, where winter air and soil temperatures below 0°C are common. Consequently, cultivars growing in this area must possess winterhardiness and freezing tolerance for survival. Asparagus acquires freezing tolerance in the fall through cold acclimation and loses freezing tolerance in the spring through deacclimation. To understand the molecular bases of these processes, transcriptomic analysis (RNA-Seq) was conducted on two cultivars, one adapted, 'Guelph Millennium' (GM), and one unadapted, 'UC157' (UC), to the winter conditions of southern Ontario. RNA extracted from bud and rhizome tissues, sampled on three dates during early spring and late fall, was subjected to sequencing. In the fall, the numbers of differentially expressed (DE) genes at the second and third harvests increased, relative to the first harvest, in dormant buds and rhizomes as freezing tolerance of cultivars increased, and the majority of DE genes were downregulated. In spring, freezing tolerance decreased as plants deacclimated and most genes DE at second and third harvests were upregulated in both cultivars. GM had lower LT50 (lethal temperature at which 50% of plants die) values and hence higher freezing tolerance than UC on specific sampling dates during both spring and fall, and expression patterns of specific genes were correlated with LT50 differences. Functional analysis revealed that these genes were involved in carbohydrate metabolic process, plant hormone signal transduction (auxin and gibberellin), proline metabolism, biosynthesis of secondary metabolites, circadian rhythm, and late embryogenesis abundant proteins and could be associated with cold acclimation and deacclimation processes. These findings will help researchers understand the molecular mechanisms of freezing tolerance in asparagus, leading to breeding and genetic strategies to improve the trait. [ABSTRACT FROM AUTHOR]

The increasing ocean warming due to climate change significantly threatens regional marine ecosystems by raising the frequency and severity of extreme temperature events. This study examines patterns and trends of maximum annual sea surface temperature (Tmax) in the Eastern China Seas from 1985 to 2022. The results show a significant warming trend in Tmax, exceeding the global average, with notable differences between southern and northern regions. The northern Tmax warming rate is faster, with occurrence times significantly advancing, while the southern Tmax warming rate is slower, with occurrence times significantly delayed. The southern Tmax and its timing are closely correlated with the annual maximum air temperature and its timing. In the north, Tmax timing is influenced by latent heat flux (QLH); a significant increase in August QLH inhibits the continued rise of SST, causing Tmax to advance. The study also highlights a significant increase in marine heatwaves at Tmax timing, with higher Tmax indicating a higher occurrence probability. By elucidating these Tmax trends and dynamics, our study enhances understanding of regional climate impacts, supporting targeted conservation efforts and adaptive ecosystem management strategies in the Eastern China Seas. [ABSTRACT FROM AUTHOR]

The influence of northern polar vortex in the stratosphere (SPV) in December‐January on Asia's surface air temperature (SAT) in February has been examined using reanalysis data sets and a barotropic model. An out‐of‐phase interannual linkage between the SPV in December‐January and SAT in February during 1979–2022 has been observed, that is, a strong (weak) SPV corresponds to a cooling (warming) over Asia. Approximately 25% of the SAT over Asia in February can be explained by the SPV in December‐January. This relationship between the SPV and SAT is independent of the Arctic Oscillation. The influence of the SPV on SAT over Asia cannot be solely explained by radiative processes, but is instead related to circulation anomalies in the troposphere. A stronger SPV tends to result in negative geopotential height anomalies with cyclonic circulation over Asia. The SPV‐related geopotential height over Asia is accompanied by a weakened teleconnection pattern between the North Atlantic and Asia, with three centers from the northeastern Atlantic‐eastern Europe‐Asia, and fewer stationary waves propagated from North Atlantic into Asia. These anomalous circulation patterns and anomalous northerly wind over Central Asia in February are beneficial to the colder air transportation from the higher latitudes to Asia, facilitating a surface cooling over Asia. Our results shed light on the interannual linkage between SPV and SAT over Asia, suggesting that the SPV in December‐January could be considered as a new predicator of SAT in February over Asia. Plain Language Summary: Scientists and the public have become increasingly aware of the significant influences of the stratosphere on tropospheric weather and climate. While numerous studies have focused on the crucial roles of stratospheric anomalies in shaping surface air temperature (SAT) anomalies over Europe and North America, relatively little attention has been given to understanding the potential impacts of stratospheric polar vortex over Arctic (SPV) on SAT over Asia. In this study, we found a robust and out‐of‐phase linkage between the SPV in December‐January and SAT in February over Asia during 1979–2022. A stronger SPV tends to induce an anomalous cyclonic circulation characterized by negative geopotential height, facilitating the transport of colder air from higher latitudes to Asia, thereby contributing a cooling effect on the surface. Our findings suggest that the December‐January SPV can serve as a predictor for SAT in February over Asia. Key Points: A strong (weak) SPV in December‐January tends to result in a cooling (warming) over Asia in February on interannual timescalesThe out‐of‐phase linkage between December‐January SPV and February surface air temperature (SAT) is independent of AO in FebruaryThe influence of SPV on Asia SAT is related to the tropospheric circulation anomalies via dynamic process, rather than radiative process [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]

Previous research has explored the impact of the Interdecadal Pacific Oscillation (IPO) and Atlantic Multidecadal Oscillation (AMO) on Antarctic surface air temperature (SAT) variability. However, a notable gap remains in our comprehension concerning the response of Antarctic SAT to the four phase combinations of IPO and AMO. In this study, we unveil unique patterns of Antarctic SAT anomalies during four distinct sub-periods based on the phases of IPO and AMO. Notably, Antarctic SAT anomalies exhibit a considerable seasonality, with the most pronounced (weakest) anomalies occurring during the austral winter (summer), a phenomenon consistent across all four sub-periods. These different anomalous SST patterns trigger varying convective rainfall patterns, consequently initiating distinct wavetrains that propagate into the Southern Ocean. These different wavetrains, in turn, induce variations in sea level pressure and surface wind fields, resulting in different Antarctic SAT anomalies primarily through mechanisms related to horizontal thermal advection and downward longwave radiation. Plain language summary: Understanding the variability in Antarctic surface air temperature (SAT) is crucial for unraveling the complex dynamics of the polar climate system and its broader implications for global climate patterns. Fewer studies highlighted the impacts of the four combinations of the phases of IPO and AMO on Antarctic SAT anomalies. In this study, we uncover distinct patterns of Antarctic SAT anomalies during four different periods based on the phases of IPO and AMO. We note that Antarctic SAT anomalies exhibit a considerable seasonality, with the most pronounced (weakest) anomalies occurring during the austral winter (summer), consistently across all four periods. The anomalous SST patterns during different periods trigger distinct wavetrains that propagate into the Southern Ocean, inducing variations in sea level pressure, surface wind fields, and Antarctic SAT anomalies. These findings bear substantial implications for the prediction of Antarctic seasonal SAT variations on interdecadal timescales. Key points: Antarctic SAT anomalies exhibit a considerable seasonality during the four combinations of the phases of the IPO and AMO. These different SST anomalies during the combinations trigger distinct wavetrains that propagate into the Southern Ocean. Different wavetrains induce anomalous sea level pressure and surface wind fields and Antarctic SAT through thermal advection and radiation. [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]

A study was conducted on the climatological characteristics of fog and mist at Pula Airport in the northeastern Adriatic, using statistical and machine learning approaches. The study utilized meteorological data from Pula Airport, along with satellite sea surface temperature (SST) data from two coastal areas west and east of the airport, to gain insights into the influence of sea temperature on fog formation. To identify weather patterns associated with the occurrence of fog and mist, wind and mean sea-level pressure (MSLP) data from the ERA5 reanalysis were analyzed using Growing Neural Gas (GNG), a machine learning method. A notable finding was a declining trend in the frequency of fog and mist at the airport, which can be linked to the results of the GNG analysis of the ERA5 data. This analysis showed a decrease in synoptic patterns favorable for fog and mist. Fog occurs mainly between October and March and is primarily associated with weak easterly and northeasterly winds. Additionally, fog is more likely to occur when the sea surface temperature is higher than the air temperature. Mist has similar characteristics to fog, although it is more likely to occur with easterly winds. [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]

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]