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Severe thunderstorms pose significant challenges to communities and infrastructure, with timely and accurate prediction increasingly difficult. This study compares a control run (CNTL) with a 3DVAR run by assimilating upper-air observational data, focusing on severe thunderstorm events in Bihar on 25th June, 2020, and West Bengal on 07th June, 2021. It assesses the impact of data assimilation on severe thunderstorm initiation and intensification, considering factors such as Convective Available Potential Energy (CAPE), Convective Inhibition (CIN), rainfall, wind, and relative humidity. Using 0.25° * 0.25° NCEP GDAS FNL data, the model was integrated for 48 h with eight 6-hourly assimilation cycles for 3DVAR for both cases. Bihar exhibited a CAPE of 1800 J/kg, while West Bengal recorded 5000 J/kg, indicating severe thunderstorm conditions. Model performance metrics, including Accuracy (ACC), Equitable Threat Score (ETS), Heidke Skill Score (HSS), Probability of Detection (POD), True Skill Statistic (TSS), Critical Success Index (CSI), and False Alarm Ratio (FAR) were utilised. Assimilating upper air observational data notably improved model-simulated results, rectifying issues such as overestimated rainfall by 20–40 mm in Bihar, correcting overestimations of 100 mm, and underestimating 80–100 mm in northern and southern parts of West Bengal. Additionally, 3DVAR reduced spatial and temporal lags in both cases. ACC approached 1 for Bihar rainfall, while FAR neared 0 for West Bengal CIN during event time in the 3DVAR run. Each model runs showed similar patterns during peak intervals, but the 3DVAR approach generally exhibited closer alignment with the observation, emphasising its effectiveness in enhancing severe thunderstorm prediction accuracy. [ABSTRACT FROM AUTHOR]

Background Evidence has shown that the incidence of bacillary dysentery (BD) is associated with climatic factors. However, the lagged effects of climatic factors on BD are still unclear, especially lacking research evidence from arid and semi-arid regions. Therefore, this study aims to add new insights into this research field. Methods Spatial autocorrelation, time series analysis and spatiotemporal scans were used to perform descriptive analyses of BD cases from 2009 to 2019. On the basis of monthly data from 2015 to 2019, multivariable distributed lag non-linear models were used to investigate the lagged effects of climatic factors on BD. Results The hot spots for BD incidence are gradually decreasing and becoming increasingly concentrated in the southern part of Gansu Province. The maximum cumulative relative risks for monthly average temperature, sunshine duration, average relative humidity and precipitation were 3.21, 1.64, 1.55 and 1.41, respectively. The lagged effects peaked either in the current month or with a 1-month lag, and the shape of the exposure–response curve changed with the increase in maximum lag time. After stratification by per capita gross domestic product, there were differences in the effects. Conclusions Climatic factors can influence the incidence of BD, with effects varying across different lag times. It is imperative to vigilantly track the disparities in the incidence of BD attributable to economic factors. [ABSTRACT FROM AUTHOR]

Copyright of Automobile Technology & Material is the property of Automobile Technology & Material Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study investigates the relationship between oxygen isotope ratios (δ18 O) in oak tree ring cellulose and past drought variability in Letea Forest, Romania. A δ18 O site chronology spanning 1803–2020 was compiled from seven individual time series. δ18 O values exhibited a significant negative correlation with moisture-related variables (cloud cover, relative humidity, and precipitation) and a positive correlation with temperature and sunshine duration. This confirms that δ18 O from tree rings can be a good proxy for moisture availability. The strongest correlation was found between δ18 O and the August Standardized Precipitation Evapotranspiration Index for an accumulation period of 9 months (SPEI9) for central and eastern Europe. This highlights SPEI9 as a superior indicator of drought compared to individual parameters like temperature or precipitation. Using a linear regression model, we reconstructed August SPEI9 variability for the past 200 years. The reconstruction captured interannual and decadal variations, with distinct wet and dry periods. Analysis of large-scale atmospheric circulation patterns revealed a link between high δ18 O values (indicating dry conditions) and a high-pressure system over the North Atlantic. Conversely, low δ18 O values (indicating wet conditions) corresponded to negative pressure anomalies over Europe. Moreover, extreme values of δ18 O are also associated with the prevalence of a hemispheric teleconnection pattern, namely wave number 4. This δ18 O chronology and the corresponding August SPEI9 reconstruction offer valuable tools for understanding past climate variability and its relationship with large-scale atmospheric and oceanic circulation patterns. [ABSTRACT FROM AUTHOR]

Aviation contributes to global emissions of carbon dioxide, aerosol particles, water vapor (WV), and other compounds. WV promotes the formation of condensation trails (contrails), which are known for their net warming effect on the climate. Contrail formation is often estimated using the Schmidt–Appleman criterion (SAc) together with meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 atmospheric reanalysis model. We compare ERA5 output of temperature and relative humidity in the upper troposphere and lower stratosphere with 5 years of In-service Aircraft for a Global Observing System (IAGOS) observations over the North Atlantic. Good agreement was found for the temperature fields, with a maximum bias of - 0.4 K (200 hPa level), while larger biases were found for relative humidity of up to - 5.5 % (250 hPa level). Using original ERA5 data, conditions prone to contrail formation occurred 50.3 % and 7.9 % of the time for non-persistent and persistent contrails, respectively, while 44.0 % and 12.1 % were flagged in the IAGOS data. We propose a multivariate quantile mapping (QM) correction to remove systematic biases by post-processing ERA5 temperature and relative humidity fields with respect to contrail formation. The QM correction was applied to post-process ERA5 data, reducing the temperature bias to less than 0.1 K and the relative humidity bias to less than - 1.5 %, resulting in 44 % and 10.9 % of the data points now being flagged for non-persistent and persistent contrail formation, respectively. Our bias correction generalizes well compared to the IAGOS observations. How it generalizes outside the IAGOS regions remains to be investigated. [ABSTRACT FROM AUTHOR]

Copyright of BIOAGRO is the property of Revista BIOAGRO and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the context of global warming and rapid urbanization, the frequency of simultaneous occurrence of extreme high temperature, ozone pollution, and particulate matter pollution has increased. However, independent and composite characterization of PM2.5, ozone, and extreme heat pollution events has not been systematically analyzed so far. This study combines meteorological and pollutant data with the GTWR model in an attempt to reveal the patterns of independent heat days (IHD), compound PM2.5-ozone pollution (CPOP), and composite heat-PM2.5-ozone pollution (CHPOP). In this study, we found that in July and August in South Korea, the frequency of CPOP events, the frequency of CHPOP events, and the composite proportion of CHPOP events all show an overall pattern of east-high and west-low; the atmospheric circulation patterns of the three extreme events have brought about more stagnation conditions, which may be related to cyclone activity; the occurrence of CPOP events is mainly accompanied by a continuous decrease in relative humidity and cloud cover, both IHD and CHPOP events occur with increasing temperatures, decreasing cloudiness, and anomalously high pressures; under the same events, excluding relative humidity, PM2.5 and ozone showed similar conditions with respect to the dependence on temperature, wind speed, barometric pressure, cloudiness, and nitrogen dioxide. This study identified the independent and composite characteristics of PM2.5, ozone, and extreme heat pollution events, which can enhance early prediction and pollution prevention of these extreme events. [ABSTRACT FROM AUTHOR]

Lemon fruits undergo various quality changes during postharvest storage that reduce fruit quality. This study aimed to examine the effects of chitosan (CHI) and salicylic acid (SA) based composite coatings on various postharvest quality attributes of lemons stored at 6–8 °C and 90–95% relative humidity. The prepared coatings were characterized using the Fourier transform infrared spectroscopy and rheology. Results indicated that chitosan coatings enriched with salicylic acid effectively maintained the physiochemical and antioxidant properties compared to uncoated fruits. Among all treatments, the combination of CHI 2.0% and SA 2.0 mM maintained the highest ascorbic acid (458 mg L−1), titratable acidity (5.23%), phenols (peel: 26.11 mg g−1; pulp: 17.72 mg g−1), flavonoids (peel: 2.49 mg g−1; pulp: 2.29 mg g−1), DPPH (peel: 42.66%; pulp: 34.91%) and OH radical scavenging activity (peel: 17.84%; pulp: 13.61%) by the end of storage. Additionally, fruits treated with CHI 2.0% + SA 2.0 mM exhibited reduced mass loss (5.28%). Overall, the study concludes that the CHI 2.0% + SA 2.0 mM combination showed promising results and can be used as an effective method for preserving the postharvest quality of lemon fruit. [ABSTRACT FROM AUTHOR]

Objective. Patients with inflammatory articular diseases, such as psoriatic arthritis (PsA), report weather changes in their symptoms. Our objective was to investigate the correlation between weather variation, disease activity (DA), and patient-reported outcomes (PROs) in patients with PsA. Methods. Hourly measurements of temperature, relative humidity, and pressure were obtained from 2015 to 2020 in Montreal (through Environment Canada) and were matched with DA and PROs of patients with PsA enrolled in Rhumadata. The differences in mean DA and PROs were examined between winter and summer. Pearson correlation coefficients were calculated between clinical profile and weather measurements. Results. Among patients with PsA, 2665 PROs were collected for a total of 858 patients. The Clinical Disease Activity Index (P = 0.001) and Simplified Disease Activity Index (P < 0.001) were lower in winter. In summer, positive correlations were found between humidity and symptoms (using patient global assessment, fatigue, pain, C-reactive protein, Bath Ankylosing Spondylitis Disease Activity Index, Bath Ankylosing Spondylitis Functional Index), whereas negative correlations between temperature and Health Assessment Questionnaire--Disability Index were reported. In winter, positive correlations were observed between temperature, fatigue, and pain. Conclusion. This is the first study to investigate weather variations through subjective and objective PROs matched with patients with PsA. Statistically significant differences in clinical profile were evident between winter and summer, as well as in their correlation with weather measurements. However, these distinctions lack clinical significance, suggesting a small impact on patients with PsA. [ABSTRACT FROM AUTHOR]

A graphene oxide (GO)-based humidity sensor is reported in this work wherein the influence of the substrate on its humidity-sensing properties is compared by depositing a GO film on two different substrates: glass and wearable fabric. While the GO film exhibits sensitivity to humidity for both substrates, its response varies from 35% for the glass substrate to 74% for wearable fabric at 60% relative humidity (RH), clearly indicating the superiority of the wearable fabric over glass. The sensors (on both substrates) show almost no sensitivity to several common volatile organic compounds (VOCs) and gases, suggesting their high selectivity towards humidity. In both cases, the sensor can detect humidity with high repeatability over several cycles and exhibits fast response and recovery times of 6 s/10 s and 7 s/12 s for glass and wearable fabric, respectively. The sensing mechanism is explained in terms of pre-adsorbed surface oxygen ions, as measured by the change in water signal upon exposure of the GO film to humidity using Fourier transform infrared (FTIR) spectroscopy. Thus, we demonstrate that the developed GO film on wearable fabric can act as a low-cost, flexible, and wearable humidity sensor with good sensitivity, reproducibility, and selectivity. [ABSTRACT FROM AUTHOR]

While urban heat islands (UHIs) have been thoroughly studied in cities worldwide, the specific risks and vulnerabilities related to urban heat in Ethiopia and Africa as a whole has given less attention. Urbanization often replaces green spaces with impervious surfaces, which diminishes natural cooling, precipitation, and water infiltration. This change can significantly affect land surface temperatures (LST) and contribute to UHI formation and its impacts. This study aimed to identify and assess the risk factors linked to UHIs, focusing on pinpointing the most vulnerable areas within cities using principal components explanatory factor analysis (HV-PC-EFA) and the urban heat vulnerability index (UHVI) model. The analysis utilized 19 composite indicators under well-established categories such as exposure, sensitivity, and adaptive capacity to assess potential risk zones. The results from the two models were compared, and their variations were examined. In the HV-PC-EFA model, indicators like urban density and roof type, along with adaptive factors such as vegetation cover, urban thermal field variances, and relative humidity, were not distinctly separated as individual components. This may cause discrepancies in the final outcomes, impacting the spatial distribution and extent of vulnerability. Despite observing some spatial variations in identifying risk areas, the study provides a broad perspective essential for developing evidence-based policies and strategies to enhance cities' resilience to high temperatures and promote sustainable environments. Given the challenges in modifying existing infrastructure, it is practical to regularly implement adaptive measures, such as preserving and restoring urban water bodies, planting trees, creating green public spaces, and raising public awareness about these risks. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to determine the impact of season, temperature and humidity on the severity of Raynaud phenomenon (RP) in systemic sclerosis. Methods: Data from the Australian Scleroderma Cohort Study were used to assess associations of patient‐reported worsened RP in the month preceding each study visit. Mean monthly weather data were obtained from the closest weather station to the patient's address. We evaluated the relationship between worsened RP and health‐related quality of life (HRQoL) measured using the Short Form 36 instrument. Results: Among 1,972 patients with systemic sclerosis, RP was a near‐universal finding, and worsened RP in the preceding month was reported in 26.7% of 9,175 visits. "Worsened RP" showed significant environmental variability. On multivariable analysis, worsened RP was associated with low mean maximum temperatures (odds ratio [OR] 0.91, 95% confidence interval [95% CI] 0.90–0.92, P < 0.001), high relative humidity (OR 1.05, 95% CI 1.04–1.05, P < 0.001) and lower mean daily evaporation (OR 0.77, 95% CI 0.73–0.81, P < 0.001). Worsened RP was strongly associated with telangiectasia, calcinosis, and digital ulceration, as well as demonstrating an association with anticentromere antibody and gastroesophageal reflux disease and a negative correlation with diffuse disease. Worsened RP was also strongly associated with worse HRQoL. Conclusion: Lower environmental temperature and higher relative humidity had significant associations with worsened RP in this systemic sclerosis cohort, suggesting an important role for dry warmth in managing this condition. [ABSTRACT FROM AUTHOR]

In the operation of the proton exchange membrane fuel cell (PEMFC) with dead-ended anode (DEA), the cathode relative humidity affects the accumulation state of water and nitrogen on the anode side, which in turn seriously affects the cell's working performance. In order to investigate the mechanism of the cathode relative humidity on the PEMFC performance, numerical simulation and segmented in-situ measurement methods were used in this study. The results of the study showed that the lower cathode relative humidity causes insufficient water content in the PEMFC. This can further lead to localized dehydration of the membrane, which causes degradation of the DEA-PEMFC performance. Moreover, the higher cathode relative humidity increases the water content on the cathode side of the PEMFC. This not only increases the membrane permeability to nitrogen but also accelerates the water concentration back-diffusion process. The water and nitrogen that penetrate into the anode side can occupy the gas transport channel and hinder hydrogen transport, resulting in the insufficient localized gas supply in the DEA-PEMFC. This finally results in lower transient voltages and significantly shorter stabilized operation times. Therefore, reasonable control of cathode relative humidity is required to ensure long-term efficient and stable operation of the DEA-PEMFC. [ABSTRACT FROM AUTHOR]

Introduction: Due to rising temperature extremes, workplaces are seeking new solutions, such as using personal cooling garments (PCG) to mitigate and manage workplace heat exposure. This systematic review sought to assess the physiological and perceptual effects of PCGs on workers in standard work clothing performing moderate‐to‐heavy intensity tasks in hot environments. Methods: A peer‐reviewed search strategy was conducted in MEDLINE, Embase, CINAHL, Scopus, Global Health, and Business Source Complete with no language or time limits. A meta‐analysis using a realist evaluation framework was then performed to evaluate the effectiveness of the PCGs. Results: Thirty‐three studies with 764 participants (98% male; average 21 ± 34 participants per study), conducted primarily in a laboratory setting (76%) were included. The studies were 193 ± 190 min in duration and consisted of a moderate‐to‐heavy work effort of 3.3 ± 1.0 METs in hot ambient conditions (temperature: 35.9 ± 3.3°C, 51.4 ± 12.1% relative humidity, wet bulb globe temperature [WBGT] 31.2 ± 2.6°C). The PCGs (n = 67) facilitated heat exchange through conduction (n = 39), evaporation (n = 4), convection (n = 2), radiation (n = 2), or hybrid combinations (n = 20). Conductive and hybrid PCGs offered the greatest thermoregulatory benefit, whereby core temperature (Tc) and heart rate (HR) reductions were consistently observed (Conductive: Tc: −0.3°C, HR: −12 bpm; Hybrid: Tc:−0.2°C, HR: −10 bpm), while PCGs directed at enhancing evaporative and radiative heat exchange had no or minimal effect on the physiological outcomes assessed (i.e., TC < 0.1°C, HR: < 0.7 bpm). Conclusion: While the PCGs had a positive overall effect, conductive options offered the most consistent benefit to workers. WBGT, clothing insulation, and duration of wear significantly affected some physiological and perceptual outcomes. [ABSTRACT FROM AUTHOR]

Systematic under-prediction of near-surface humidity and precipitation is a major issue in numerical weather prediction (NWP) within the complex terrain of Nepal Himalayas. Inaccurate initialization of weather models is a major cause of errors in weather prediction. Data Assimilation (DA) is essential for improving the initial conditions used in weather models, thus reducing uncertainties in weather forecasts. Though the global initial conditions driving the regional model undergo some DA, downscaling the coarser analysis for regional forecasting often leads to inaccurate forecasts. This study uses the Three-Dimensional Variational (3DVAR) DA to assimilate observations into a high-resolution regional weather model and systematically examines the improvement in the accuracy of near-surface weather variable predictions and the predictability of rainfall over the Central Nepal Himalayas during the pre-monsoon season, compared to forecast generated without DA. Three-day forecasts over the Kathmandu Valley were performed in seven DA experiments using different combinations of publicly available instrument data. The changes in initial conditions over an area after assimilation varied with the assimilated observations. Assimilating surface and upper-air weather observations, along with satellite radiance data in all the domains of the nested system produced a better forecast of humidity, temperature, rainfall, and cloud cover over the valley despite fewer observations in child-domains. The forecast successfully predicted the previously missing rainfall in the control simulation. The study demonstrated the significant positive impacts of 3DVAR-DA on the regional model forecast over the Himalayan region, even with a small domain and also beyond 24 h after assimilation of publicly available data. [ABSTRACT FROM AUTHOR]

Background: Pyrilla perpusilla (Walker) is an important pest of sugarcane ecosystem in the Tarai region of Uttarakhand state of India. The study focused on investigating the population dynamics of Pyrilla (sugarcane leaf hopper) and its parasitoids under the natural field conditions. Results: During the study, two important parasitoids, viz., Fulgoraecia Melanoleuca, a nymphal/adult parasitoid (Lepidoptera: Epipyropidae), and Cheiloneurus pyrillae, an egg parasitoid (Hymenoptera: Encyrtidae), were found associated with the sugarcane leaf hopper. The peak mean population of ecto-parasitoid, F. melanoleuca cocoon, was observed in November 2022–23 and 2023–24. The morning hour relative humidity showed a negative significant relation with the cocoon population. The maximum parasitization of nymphs and adults Pyrilla was found to be 46.7 and 46.0%, respectively, from September to October during 2022–23 and 2023–24 crop seasons, after that the declining trend in parasitization by F. melanoleuca was observed. An increasing trend was recorded in egg parasitization in July, when the maximum mean population density of Pyrilla egg batches (2.28 /leaf), nymphs (4.75/leaf) and adults (4.58/leaf) was found. Temperature and relative humidity had significant correlations with Pyrilla egg batches. Conclusion: Overall, the study outlines the presence of Pyrilla and its naturally occurring parasitoids in the sugarcane ecosystem, along with the effects of weather conditions on Pyrilla's population density and the parasitization rates of the parasitoids. The peak activity period of pest and its parasitoids was reported from September to November. Weather factors such as temperature ranging from 16 to 37.25 °C and relative humidity (62.7–93.8%) played a significant role in affecting their density and parasitization. [ABSTRACT FROM AUTHOR]

The inherent model uncertainty in precipitation projections is found to be more dominant over tropical regions thereby reducing the reliability of using them in climate change impact assessment studies. To address such issues, a subset of well performing global climate models (GCMs) can provide narrow range of possible future outcomes, which can be helpful in formulating mitigation and adaptation strategies that are more targeted and efficient. In this study, climate models are selected based on their performance in simulating relative humidity and vertical velocity since these variables play an important role in precipitation simulation and significantly contribute toward the intermodel spread. The models are evaluated by using various statistical performance measures and ranked using multi‐criteria decision‐making approaches. Finally, based on Jenks natural breaks optimization algorithm, subset of GCMs consisting of ACCESS1.0, ACCESS1.3 and INM‐CM4 models, are considered as the best possible subset for precipitation simulation over tropical land regions. Two observational precipitation datasets are further considered to investigate the effectiveness of the proposed framework. The proposed methodology is validated to be effective in identifying the best climate models since the resulting subset is capable of both capturing observed precipitation and minimizing the uncertainty in future projections. Hence, this methodology can be utilized further for performance evaluation of GCMs focusing different geography and climatic drivers. [ABSTRACT FROM AUTHOR]

Recent research highlights the influence of the Atlantic Niño on the likelihood of strong hurricanes forming in the tropical Atlantic. This phenomenon increases the risk of hurricanes impacting the Caribbean islands and the United States. A recent study identifies two distinct types of the Atlantic Niño, with warming concentrated in the central (CA) and eastern (EA) equatorial Atlantic, respectively. By analyzing observational and reanalysis data, we investigated how these two types of the Atlantic Niño affect hurricane activity. The findings reveal that the CA Niño enhances hurricane frequency south of 20°N, while the CA Niña promotes hurricanes north of 20°N. The CA Niño exerts a more significant influence on hurricanes than the EA Niño, primarily by affecting wind shear, relative vorticity, and vertical velocity. In contrast, the EA Niño mainly impacts relative humidity and African Easterly Waves. These insights could improve the accuracy of seasonal hurricane forecasts. Plain Language Summary: Recent research suggests that the Atlantic Niño increases the likelihood of strong hurricanes forming near the Cape Verde Islands, raising the risk of hurricanes impacting the Caribbean and the United States. A recent study identified two types of Atlantic Niño, which cause warming in the central and eastern equatorial Atlantic (CA and EA). By analyzing observational and reanalysis data, we found that the CA Niño influences hurricanes south of 20°N, while CA Niña affects hurricanes north of 20°N. The CA Niño has a greater impact on hurricanes than the EA Niño because it more strongly affects wind shear, relative vorticity, and vertical velocity—key factors in hurricane formation and intensification. In contrast, the EA Niño mainly influences relative humidity and African Easterly Waves. Understanding these effects could improve seasonal hurricane forecasts. Key Points: Central Atlantic Niño/Niña events have a greater impact on TC genesis and tracks compared to Eastern Atlantic Niño/Niña eventsCentral Atlantic Niño affects hurricanes south of 20°N in the North AtlanticCentral Atlantic Niño provides more favorable conditions for Atlantic hurricanes compared to Eastern Atlantic Niño [ABSTRACT FROM AUTHOR]

This study presents a novel approach for conducting all‐day retrieval of cloud macro‐physical properties (single‐layer cloud phase, cloud top height, and cloud base height for optical thickness less than 10) using the Advanced Geostationary Radiation Imager (AGRI) and the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the geostationary meteorological satellite Fengyun‐4A based on machine learning methods. Model accuracy was compared after integrating ECMWF Reanalysis v5 (ERA‐5) data, atmospheric temperature and moisture profiles, and GIIRS clear‐column radiance. Results demonstrate that integrating GIIRS clear‐column radiances can enhance the precision of cloud phase classification and the retrieval of cloud macro‐physical properties. This effectively replaces the role of atmospheric temperature and humidity profiles, which are typically required for thermal infrared remote sensing retrieval. Moreover, the issue of delayed acquisition of ERA‐5 atmospheric temperature and humidity profiles is mitigated, enabling near real‐time and all‐day retrieval of cloud macro‐physical properties. Plain Language Summary: This study introduces a new method for accurately determining the macro‐physical properties of clouds using satellite data and machine learning techniques. By combining observations from the Advanced Geostationary Radiation Imager (AGRI) and the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the geostationary meteorological satellite Fengyun‐4A, we improve the accuracy of cloud phase classification and retrieve information regarding cloud height. This new approach reduces reliance on traditional methods that require atmospheric temperature and humidity data, making it easier to obtain real‐time cloud information throughout the day. These findings have the potential to significantly enhance our ability to monitor and understand cloud behavior using satellite technology. This is the first time to combine the observations from both geostationary satellite imager (AGRI) and sounder (GIIRS) to retrieve the macro‐physical properties of clouds. Key Points: Combined use of AGRI and GIIRS observations significantly enhances the accuracy of all‐day retrieval of thin cloud macro‐physical propertiesGIIRS clear‐column radiance can replace ERA reanalysis data in thermal infrared retrieval algorithms, achieving similar or higher accuracyUsing GIIRS observations can avoid the issue of lagging atmospheric profile generation, thereby enabling near real‐time cloud retrieval [ABSTRACT FROM AUTHOR]

Convective cloud processes are sensitive to environmental conditions that vary on scales smaller than reanalysis data sets (sub‐reanalysis scales). Convective environment variability within areas representative of reanalysis data sets is quantified using large‐domain, high‐resolution (∆x = 100 m) simulations of convective cloud systems throughout the tropics and subtropics. Even after removing locations of resolved clouds and precipitation, convective environment parameters vary significantly on these scales. For example, for half of the simulated data, 500 hPa relative humidity varies by ∼30% within a typical reanalysis area. Surface winds, convective available potential energy, and middle‐tropospheric moisture are the most variable convective environment parameters for both continental and maritime regimes, while above‐surface temperature and winds are the least variable. While high‐resolution, sub‐reanalysis‐scale extrema are well‐correlated with the reanalysis‐area mean values, some of the most extreme convective environments can occur within regions with moderate reanalysis‐area mean values, particularly for continental regions. Plain Language Summary: Cloud development, processes, and properties are highly sensitive to their environments. Cloud‐resolving model simulations throughout the tropics and subtropics are used to estimate how much cloud environments vary within coarser reanalysis data sets (e.g., ERA5 Reanalysis) that are often used to study cloud environments and processes. These results show that cloud environments vary significantly within a 27 km by 27 km area (typical resolution of reanalysis data sets), and that this variability needs to be considered when using coarse data sets to understand cloud environments. The cloud environment parameters with the greatest small‐scale variability are surface winds, thermodynamic instability, and moisture in the middle‐tropospheric levels, and variability is larger over land regions than over ocean regions. Importantly, localized extrema can often occur within regions of moderate reanalysis‐scale values, further demonstrating that care needs to be taken when using reanalysis data to assess convective cloud environments. Key Points: Convective environment parameters vary significantly within a typical reanalysis data set area, impacting cloud processesNear‐surface winds, convective available potential energy and middle‐tropospheric moisture are the most variable convective environment parametersSub‐reanalysis‐dataset‐scale extrema in convective environments can occur in regions with moderate reanalysis data set mean values [ABSTRACT FROM AUTHOR]

ABSTRACT The effectiveness and safety of drugs may be compromised by the degradation of APIs during preparation processes or after they have been released to market. This study has investigated the degradation of 500‐mg Acetaminophen tablet (C8H9NO2) when stored under unfavorable conditions such as increased temperature and high levels of humidity. To quantify the amount of API, the Raman intensity variations of characteristic peaks of API and polyvinylpyrrolidone (PVP) (C6H9NO) are explored. By considering various sources of error in all experiments, the reliability of the extracted data set from Raman spectrums and the quality of results obtained using the utilized technique for predicting API is investigated at standard room temperature. The results demonstrate an acceptable precision in the range of pharmacopeia monograph. Then, the effect of temperature and humidity variations on the amount of API is investigated based on the related Raman spectra. The results show that the API's quantity starts to decrease after about 60 min at the temperature of 45°C ± 2°C and the relative humidity (RH) of 75% ± 2%. According to our results, when tablets are kept under the unfavorable conditions, the degradation pattern of API follows a logarithmic trend. [ABSTRACT FROM AUTHOR]

High temperatures facilitate the formation of stable, high‐crystallinity α‐FAPbI3 films but can lead to the volatilization of organic components in perovskites. Here, a 300 °C hot‐press‐assisted recrystallization strategy is reported to grow stable phase‐pure α‐FAPbI3 film without any dopants. High temperature can promote the transformation of δ‐FAPbI3 to α‐FAPbI3, and induces recrystallization to relieve strain. The applied pressure creates a confined space that effectively prevents the volatilization of organic components in perovskite. The α‐FAPbI3 film prepared by hot‐press at 300 °C achieves an average grain size of ≈3 µm (with grains up to 10 µm) and demonstrates excellent damp‐heat stability, showing no significant change after 20 s in deionized water. The result solar cell delivers a power conversion efficiency as high as 24.06% and retains >70% of their initial efficiency value after 1000 h at 85 °C and 85% relative humidity. [ABSTRACT FROM AUTHOR]

Organic molecules with tailorable chemical structures, high stability, and solution processability have great potential in the sensing field. Compared with p‐type organic small molecules (OSMs), the electron‐dominated n‐type analogs show superior conductivity when exposed to reducing gases, which can achieve outstanding sensor signal‐to‐noise ratios. However, inadequate humidity resistance at room temperature hinders the development of such molecules. Herein, an A‐D‐π‐D‐A molecular design strategy is proposed based on electron‐deficient B←N units, which results in effective intramolecular charge transport and sensitive responses by extending the π‐conjugation bridge. As a result, the ST‐2BP with A‐D‐π‐D‐A configuration shows a prominent sensitivity of 787 (Ra/Rg) in 20 ppm NH3 at room temperature and an almost initial and stable response under different relative humidity conditions, which is the highest among currently reported OSM sensors. Supported by theoretical calculations and in situ FTIR spectra, it is revealed that B←N units, which function as the active centers mediate the specific ammonia adsorption. This study provides a new understanding of the design of high‐performance room temperature gas sensing materials by decorating B←N units. [ABSTRACT FROM AUTHOR]

In this study, long-term and continuous monitoring of atmospheric radon concentration, temperature, air pressure, and humidity was conducted at China Jinping Underground Laboratory. The impacts of temperature, humidity, and air pressure on radon concentration in the experimental environment were specifically examined, along with the potential interactions among these factors. Moreover, Radon data were denoised using Singular Spectrum Analysis (SSA) to reveal factors that might influence changes in radon concentration. The possible mechanisms by which these environmental factors influence radon migration have also been explored. This research not only provides new insights into the behavior of radon in underground environments but also offers important references for formulating effective radon management and protective actions. [ABSTRACT FROM AUTHOR]

For successful operation of a fuel cell, its lifetime should be at least 40,000 h. Durability tests are usually limited by certain/standard conditions. On the other hand, operation of a proton exchange membrane fuel cell (PEMFC) under real, nonstandard conditions may lead to an irreversible reduction in the device efficiency and/or degradation of its components. This review deals with the PEMFC performance under a variety of nonstandard conditions, including low and high humidity, and low and high temperatures. Mechanisms of influence of operating conditions on the device performance are identified and analyzed. It is shown that operation of a PEMFC with standard components under nonstandard operating conditions leads to irreversible consequences and reduces the expected lifetime of the device. Nonstandard operating conditions have a significant impact on the components of proton exchange membrane fuel cells; Temperature and humidity of the reagents have reversible and irreversible effects on the electrocatalyst and proton exchange membrane; Consideration of degradation mechanisms is necessary in the design of stable fuel cells. [ABSTRACT FROM AUTHOR]

The Missouri River Basin, one of the primary agricultural regions in North America, is prone to large hydroclimatic variability and extreme events. The Great Plains low‐level jet (GPLLJ) is one of the major sources of moisture transport into this region, and concerns over moisture extremes already seen in the interior U.S. have been linked to changes in GPLLJ. However, the relationship between GPLLJ and precipitation in this region remains uncertain, with studies showing conflicting results that may be related to distinct types of jet events. Here, we use daily GPLLJ data to study connections between different types of jet events and precipitation, integrated water vapor transport, and synoptic conditions to better understand GPLLJ‐streamflow linkages. We assess GPLLJ conditions during historical flood events and potential future changes using CMIP6 projections. We find: (a) in May–September, GPLLJ is associated with 29%–46% of monthly precipitation and with increased precipitation intensity; (b) GPLLJ has a consistently positive impact on Missouri River streamflow over the warm season; (c) coupled jets have a larger impact on moisture transport than uncoupled jets, but streamflow impact is reduced, likely due to seasonal timing; (d) unusual jet conditions preceded historical warm‐season flood events; and (e) future projections indicate relatively small changes in GPLLJ meridional wind velocities along with large increases in moisture transport driven by humidity increases. Although future streamflow will be partially dependent on snowmelt from the upper basin, the projected intensification of warm‐season moisture transport to the Missouri River suggests possible increases in future flood risk. Plain Language Summary: Both floods and droughts are of concern in the Missouri River, which is relied upon for agriculture, fish and wildlife, transportation, and power generation. One of the river's main sources of water is the Great Plains low‐level jet—strong winds near Earth's surface that bring moisture from the Gulf of Mexico to the Missouri River basin during summer months. In this study, we examined how different configurations of jets affect rain, movement of moisture in the atmosphere, and streamflow in the Missouri River, as well as the conditions leading up to flood events. We found that more than a third of monthly rain totals are associated with a jet, and that jet occurrence coincides with higher streamflow in the Missouri River. Atmospheric moisture transport and the number of jets were unusually high in the weeks preceding the 1951, 1986, and 1993 flood events. Although drying associated with global warming has been projected for this region, our results suggest that flooding will remain a concern for the Missouri River due to increasing water vapor content and transport in the atmosphere. Key Points: The Great Plains low‐level jet (GPLLJ) has a clear and consistent impact on Missouri River streamflow and peak flows during the warm seasonGPLLJ is associated with 29%–46% of warm season precipitation and with increases in precipitation intensity and flood eventsModels project large increases in future moisture transport, a source of concern for precipitation‐driven flooding in the Missouri River [ABSTRACT FROM AUTHOR]

The flood that would result from the greatest depth of precipitation "meteorologically possible", or Probable Maximum Precipitation (PMP) is used in the design of dam spillways and other high‐risk structures. Historically, PMP has been estimated by scaling depth‐area‐duration relationships obtained from severe historical storms. Over the last decade, numerical weather prediction models have been used to instead simulate precipitation resulting from the addition of atmospheric moisture (called relative humidity maximization, or RHM). Despite the major improvement this represents, model‐based PMP relies on a key assumption, which this paper re‐evaluates in Oroville dam's Feather River watershed (California). Model‐based as well as earlier procedures assume that severe historical storms achieved maximum efficiency (moisture conversion to precipitation) and only maximize moisture. We examine the most severe storms found in the CESM2‐LE global climate model ensemble, which constitutes a very large artificial record (∼1,150 years) in comparison with the historical record, to understand the upper bounds of storm efficiency and precipitation. We downscale the 10 most severe CESM2‐LE storms (by precipitation totals), and identify key storm attributes (vertical motion, convection and convergence) that control precipitation efficiency. In comparison with historical storms, we find that CESM‐LE storms can have 30% higher efficiency and 32% higher precipitation, but produce only 8% higher PMP estimates, suggesting some convergence of model ensemble and historical storms in terms of PMP. The understanding of the controls on storm efficiency that our work provides leverages past work focused on moisture and supports the development of more reliable PMP storm amplification guidance. Plain Language Summary: The Probable Maximum Precipitation (PMP) is the largest amount of rainfall that could occur at a location. It is used to design dams that can safely handle the largest possible flood. The PMP is estimated by amplifying the storms that produced the most rainfall observed in the past. As there are issues with current methods to estimate PMP, new methods using atmospheric models are being developed. However, model‐based methods also assume that observed storms were efficient at converting atmospheric moisture to rainfall, and only their moisture needs to be amplified. This is questionable because few severe storms have been observed, meaning storms with more efficient moisture conversion, that could produce more precipitation, could occur. Focusing on Oroville dam's Feather River basin (California), we examine the CESM2‐LE data set, a long artificial weather record produced by a model and which differs from the actual record but is designed to have similar characteristics. We find that storms selected from this much larger sample produce only slightly larger PMP estimates than historical storms. Therefore, our findings do not challenge the validity of currently used PMP values obtained using historical storms. This result will be important for the development of reliable PMP estimation guidance. Key Points: Historical storms currently used in Probable Maximum Precipitation (PMP) estimation (both model‐based and earlier methods) may not have achieved maximum storm efficiencyA ∼1,150‐year artificial sample contains rare storms that are more severe than historical storms, but less severe than current PMP totalsPMP estimates produced by amplification of the ∼1,150‐year artificial sample storms are 8% larger than PMP based on historical storms [ABSTRACT FROM AUTHOR]

Low-cost sensors have revolutionized air quality monitoring, however, precision is questioned compared to reference instruments. Hence, the performance of two widely used PM2.5 Sensors, Purple Air (PA) and ATMOS, were evaluated over a 10-month period in the North Western-Indo Gangetic Plains (NW-IGP). In-field collocation with Beta Attenuation Monitor found low R2 values; 0.40 for ATMOS and 0.43 for PA. To calibrate and improve the accuracy of sensors, five Machine Learning (ML) models and an empirical relative humidity correction methodology were used separately for both sensors. Out of these, the Decision Tree outperformed others, and R2 values improved to 0.996 for ATMOS and 0.999 for PA. Root mean square error reduced from 34.6 µg/m3 to 0.731 µg/m3 for ATMOS and from 77.7 µg/m3 to 0.61 µg/m3 for PA, while using DT as a calibrating model. The study reveals the best-performing ML model for correcting PM2.5 sensor data, enhancing the accuracy of air quality monitoring systems. [ABSTRACT FROM AUTHOR]

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Heat waves (HW) are prolonged periods of excessively hot weather that can cause severe socioeconomic and environmental impacts. This study aims to evaluate the differences in stored heat and turbulent flux partitioning during a heat wave event in Mexico City, using observations from an eddy covariance tower during the period from 14 June to 21 June 2023. During this period, net radiation (Rn) and sensible heat flux (H) increased significantly, particularly from noon to evening, reflecting stable atmospheric conditions. The air temperature showed a noticeable increase in the afternoon and evening, whereas absolute humidity decreased. We found that during the heat wave, the Bowen ratio (β) increased by 80% during daylight hours and 65% over a full 24-hour period compared to the pre-heat wave period. This heat release at night prolonged warm conditions, intensifying heat stress. The partitioning of net radiation for latent heat (LE), sensible heat (H), and heat storage (ΔQs) showed significant changes; during the heat wave, 51% of Rn was allocated to H and 34% to ΔQs, compared to pre-heat wave values of 49% and 27%, respectively. This study introduces a new characterization of heat waves in terms of energy, emphasizing the significant shifts in energy flux partitioning and storage. The new characterization highlights the critical role of urban heat storage and its release in exacerbating heat stress during and after heat wave events. This approach provides a comprehensive understanding of the energy dynamics during heat waves, which is essential for developing effective mitigation strategies to combat the adverse effects of extreme heat in urban environments. [ABSTRACT FROM AUTHOR]

Improved knowledge on Proton Exchange Membrane Fuel Cell (PEMFC) behaviour in the Intermediate Temperature (IT: 80–120 °C) is needed. Here, ionic conductivity and H 2 permeability are analysed under H 2 /N 2 using electrochemical impedance spectroscopy, linear sweep voltammetry for three catalyst-coated membranes (CCMs): Nafion HP (reinforced), Nafion 211 (non-reinforced) and a reinforced commercial membrane (RCM, membrane thickness 13 μm). Multiple relative humidity (RH) levels and pressure configurations are analysed at IT. Results show that ionic conductivity and H 2 permeability increase with temperature and RH. However, lower crossover is measured above 100 °C and wet conditions due to low H 2 partial pressure. The highest crossover is measured with an overpressure on the H 2 side which, especially for RCM, suggests possible convection. The membrane reinforcement might reduce the permeability and it decreases the conductivity. Mass spectrometry confirmed that sprayed CCMs suffer from higher crossover than pristine membranes, although the membrane thickness is unchanged. [Display omitted] • Membrane conductivity increases with higher temperature and relative humidity (RH). • The mechanical reinforcement reduces the conductivity in the membrane. • Permeability increases with temperature and RH but is reduced by the reinforcement. • H 2 crossover is critical at low currents, i.e. idling conditions. • Klinkenberg effect on permeability of sprayed CCMs is observed. [ABSTRACT FROM AUTHOR]

The stable isotope composition of meteoric water has been widely used to understand hydrological processes worldwide. We present a unique dataset, with the isotopic composition (δ18O and δ2H) of meteoric waters, derived from a nationwide study in Cuba. It includes monthly composite and event-based precipitations, from January 2017 to December 2021 (N = 526 and N = 111 respectively). Monthly data showed minor seasonal trends (dry vs. rainy), with a notable influence of tropical cyclones. Event-based data demonstrated that precipitation associated with tropical cyclones exhibited lower isotopic compositions. The analysis of potential factors influencing the isotopic composition of precipitation showed a minor influence of the rainfall amount, but negligible influence of factors such are relative humidity, elevation, and air temperature. This data set can be used as a tool not only to understand hydrological processes at the country scale, but also to further improve and develop isotope-enabled modelling for assessing water balances and fluxes, understanding the impact of extreme events, and paleoreconstruction in the Intra-Americas Sea. [ABSTRACT FROM AUTHOR]

Although numerous studies have projected changes in freezing rain under future climate conditions, the internal variability of freezing rain remains poorly quantified. Here, we introduce a framework utilizing a novel machine‐learning algorithm to diagnose freezing rain in reanalysis and climate model simulations. By employing multivariate quantile mapping, we decompose the projected freezing rain trend into contributions from changes in temperature, relative humidity, and precipitation, which helps separate the forced response from internal climate variability. Our finding reveals a notable decrease in freezing rain occurrence in most areas. Despite a substantial temperature increase, internal variability overshadows climate forcing across a large portion of the eastern United States until about 2050. This insight has implications for practitioners, suggesting that the observed freezing rain frequency climatology continues to provide a relevant baseline for decision‐making in the near term. However, longer‐term design and adaptation plans should consider the projected changes in these regions. Plain Language Summary: Freezing rain is a hazardous type of winter precipitation that can lead to significant transportation delays and power outages. This study explores future changes in freezing rain by using a combination of machine‐learning and statistical methods. We find that freezing rain frequency is expected to decline as temperatures rise across much of the eastern United States. However, natural variations in freezing rain occurrence are more significant than the impact of climate change in the Northern Great Plains, a small portion of the Midwest, and the northeastern United States throughout the 21st century. Across other regions of the eastern United States, the projected decline in freezing rain frequency emerges from the background natural climate variability around 2050. This means that, in the near term, the potential impacts of freezing rain on travel and infrastructure will not be substantially different than those in the past. Key Points: Multivariate quantile mapping is used to separate the forced response of freezing rain from internal climate variabilityInternal variability dominates projected freezing rain changes in numerous regions despite a clear temperature increaseProperly accounting for internal variability is critical for risk assessments of future freezing rain events [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) pose a substantial threat to human life and property, with China being among the most affected countries. In this study, a significant increasing trend is detected for TC destructiveness, primarily measured by precipitation, and for TC‐induced damage, measured by direct economic losses (DELs), in the inland areas of East China. In contrast, a similar trend cannot be observed in the coastal regions. The rapid increase of TC‐induced damage in the inland areas of East China is directly related to an increase of the annual number of disastrous TCs, which is a result of the increased TC landfall frequency and the increased TC decay timescale after landfall. The increase in specific humidity, soil moisture, and the decrease in vertical wind shear in East China favor the survival of TCs inland. Our results highlight the significance of TC disaster prevention in the inland regions. Plain Language Summary: The damage induced by tropical cyclones (TCs) shows a long‐term increasing trend in mainland China. In general, the occurrence of TC disasters is more frequent in coastal areas than inland. However, inland areas lack resilience toward TC attacks, resulting in substantial damage when a TC reaches. This study focuses on the long‐term variations of TC destructiveness and the damage that results in inland areas, and a significant increasing trend has been observed, particularly in East China. The rapid increase of TC‐induced damage in the inland areas of East China is essentially due to the increased annual number of disastrous TCs in this region. Such an increase of the disastrous TC number is not only attributed to the increasing TC landfall frequency but also related to the increasing post‐landfall TC decay timescale. It is further demonstrated that the increase in specific humidity, soil moisture, and the decrease in vertical wind shear in East China favor the survival of TCs in inland areas. Our findings highlight the significance of TC disaster prevention in the inland areas. Key Points: A significant increasing trend is detected for TC destructiveness and its resulting damage in the inland areas of East ChinaThe increase of TC‐induced damage is primarily due to an increase in the annual number of disastrous TC eventsThe increase in disastrous TC events is related to an increase in TC landfall frequency and in decay timescale of TCs after landfall [ABSTRACT FROM AUTHOR]

Poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is a conductive polymer widely used in various microwave sensing components. Enhancing the efficiency of PEDOT:PSS‐based microwave structures relies on improving the polymer's conductivity, achievable by adding secondary solvents such as dimethyl sulfoxide (DMSO), which significantly boosts the electrical conductivity. However, the performance of DMSO‐doped PEDOT:PSS films in microwave regime requires investigations. Herein, patch resonators are fabricated using solution processing of aqueous dispersion of PEDOT:PSS doped with varying concentrations of DMSO from 0 to 8 wt.% to investigate their microwave behavior within the frequency range of 4.5–6.5 GHz. The PEDOT:PSS patch structures are implemented on a glass substrate and their resonant characteristics, including resonant frequency and amplitude, are studied in response to varying relative humidity (RH) levels ranging from 0% to 70%. The significant variations in the microwave responses are observed at the resonant amplitude, confirming the main impact of humidity on the conductivity of the films. According to the measured results, the 2 wt.% doped patch shows greater sensitivity to the changes to the RH in contrast to the 8 wt.% doped patches, where the response shows less sensitivity to the humidity variation. The results indicate that a lower percentage of DMSO enhances sensitivity to the humidity at the cost of increased electromagnetic loss in the resonant patch structures for humidity sensing applications. [ABSTRACT FROM AUTHOR]

Understanding boundary-layer atmospheric temperature and moisture is essential for advancing our knowledge of the Earth system. This study adopts a one-dimensional variational (1DVAR)-based technique to integrate spaceborne measurement and ground-based observations for improving the retrieval of low-level atmospheric profiles. The performance of the algorithm under different atmospheric and observational scenarios, such as surface-air and skin temperature differences (∆T), surface pressure (Ps), and satellite zenith angle, respectively, has been systematically evaluated using the Geosynchronous Interferometric Infrared Sounder (GIIRS) on board the Fengyun-4A satellite as an example. Through theoretical information analysis, using both simulated and actual data experiments, this study demonstrates that incorporating ground-based temperature and moisture observations significantly enhances retrieval accuracy with 1DVAR, particularly over elevated terrain. The new algorithm is more effective in low-level temperature retrievals when air temperatures are colder relative to surface-skin temperatures, and it also shows greater benefit for water-vapor retrievals when the temperature difference between the air and the skin is minimal. However, as the zenith angle increases to 55°, the accuracy of temperature retrievals deteriorates, although this is mitigated by the combination of surface-air temperature observations. Notably, the positive impact of surface observations extends to approximately 100–200 hPa above the surface, underscoring the importance of accurate ground-based measurements in conjunction with spaceborne data for atmospheric profiling. [ABSTRACT FROM AUTHOR]

Plants need to adapt to fluctuating atmospheric humidity and respond to both high and low humidity. Despite our substantial understanding of plant responses to low humidity, molecular mechanisms underlying the high humidity (HH) response are much less well understood. In this study, we investigated early responses to HH in Arabidopsis. Expression of CYP707A3, encoding an abscisic acid (ABA) 8'-hydroxylase, is induced by HH within 10 min, which leads to a decrease in foliar ABA level. We identified that the combined action of CAMTA3 and CAMTA2 transcription factors regulate this response. This regulation requires a calmodulin (CaM)-binding domain of CAMTA3. Transcriptomes of HH-regulated genes are enriched in those related to calcium signaling, including cyclic nucleotide-gated ion channels (CNGCs). Moreover, HH induces CNGC2-and CNGC4-mediated increases in cytosolic Ca2+ concentrations in leaves within a few minutes. We also found that CNGC2, CNGC4, and CAMTAs participate in HH-induced hyponastic movement of petioles. Taken together, our results indicate that CNGC2/CNGC4-Ca2+-CaM-CAMTA3/CAMTA2 acts as a primary regulatory module to trigger downstream HH responses. [ABSTRACT FROM AUTHOR]

Studies on radiosensitization of biological damage by O2 began about a century ago and it remains one of the most significant subjects in radiobiology. It has been related to increased production of oxygen radicals and other reactive metabolites, but only recently to the action of the numerous low-energy electrons (LEEs: 0–30 eV) produced by ionizing radiation. We provide the first complete set of G-values (yields of specific products per energy deposited) for all conformational damages induced to plasmid DNA by LEEs (GLEE (O2)) and 1.5 keV X-rays (GX(O2)) under oxygen at atmospheric pressure. The experiments are performed in a chamber, under humidity levels ranging from 2.5 to 33 water molecules/base. Photoelectrons from 0 to 30 eV are produced by X-rays incident on a tantalum substrate covered with DNA. Damage yields are measured by electrophoresis as a function of X-ray fluence. The oxygen enhancement ratio GLEE(O2)/GLEE(N2), which lies around 2 for potentially lethal cluster lesions, is similar to that found with cells. The average ratio, GLEE(O2)/GX(O2), of 12 for cluster lesions and crosslinks strongly suggest that DNA damages that harm cells are much more likely to be created by LEEs than any other initial species generated by X-rays in the presence of O2. [ABSTRACT FROM AUTHOR]

Recently, there is rapid development of thermochromic metal halide perovskite (MHPs) for smart window applications due to their competitive optical performance and cost‐effective synthesis. However, existing MHP smart windows predominantly feature 3D perovskite, which exhibits a deficiency in environmental stability, presenting persistent challenges for practical applications. This study introduces a novel and more durable 2D thermochromic perovskite, Tha2MAPbI4 (TMPI, Tha = thiourea, MA = methylamine), wherein Tha acts as a Lewis acid‐base adduct. TMPI demonstrates a reversible transition, achieving 83.7% luminous transmittance in the cold state and 35.2% in the hot state, thereby showcasing a substantial solar modulation ability of 24.7%. Further analysis of the crystal structure reveals that the thermochromic behavior of TMPI arises from a phase transition between 0D perovskite and 2D perovskite, induced by a dehydration‐hydration process. Notably, TMPI maintains thermochromic properties even after direct exposure to 75% relative humidity and 25 °C air for up to 28 days, a stark contrast to traditional 3D perovskites that lose their thermochromic capabilities within a few days under similar conditions. This research unveils TMPI as a thermochromic 2D perovskite that marks a significant advancement in environmental stability, indicating promising prospects for thermochromic smart windows. [ABSTRACT FROM AUTHOR]

AbstractOrder identification for models of big time series data presents computational challenges. Results from previous studies on big univariate time series suggest that methods based on kriging and optimization can reduce the computing time substantially while providing adequately plausible model orders. In today’s world, however, one must analyze multiple big time series simultaneously, such as multiple stocks or measuring humidity in various rooms of a house. This becomes a much bigger computational challenge to address, as one must take into account the cross-correlation between the individual time series. The goal of this paper is to detail a method to fit big multivariate time series. The results show that the proposed technique can substantially decrease computing time while still providing reasonably accurate model orders. [ABSTRACT FROM AUTHOR]

Owing to its extensive use and intrinsic toxicity, NH3 detection is very crucial. Moisture can cause significant interference in the performance of sensors, and detecting NH3 in high humidity is still a challenge. In this work, a humidity-activated NH3 sensor was prepared by urocanic acid (URA) modifying poly (ethylene glycol) diacrylate (PEGDA) via a thiol-ene click cross-linking reaction. The optimized sensor achieved a response of 70% to 50 ppm NH3 at 80% RH, with a response time of 105.6 s and a recovery time of 346.8 s. The sensor was improved for response and recovery speed. In addition, the prepared sensor showed excellent selectivity to NH3 in high-humidity environments, making it suitable for use in some areas with high humidity all the year round or in high-humidity areas such as the detection of respiratory gas. A detailed investigation of the humidity-activated NH3-sensing mechanism was conducted using complex impedance plot (CIP) measurements. [ABSTRACT FROM AUTHOR]

The aircraft smart skin (ASS) with structural health monitoring capabilities is a promising technology. It enables the real-time acquisition of the aircraft's structural health status and service environment, thereby improving the performance of the aircraft and ensuring the safety of its operation, which in turn reduces maintenance costs. In this paper, a miniaturized and ultra-low-power wireless multi-parameter monitoring system (WMPMS) for ASS is developed, which is capable of monitoring multiple parameters of an aircraft, including random impact events, vibration, temperature, humidity, and air pressure. The system adopts an all-digital monitoring method and a low-power operating mechanism, and it is integrated into a low-power hardware design. In addition, considering the airborne resources limitations, an energy self-supply module based on a thermoelectric generator (TEG) is developed to continuously power the system during flight. Based on the above design, the system has a size of only 45 mm × 50 mm × 30 mm and an average power consumption of just 7.59 mW. Through experimental validation, the system has excellent performance in multi-parameter monitoring and operating power consumption, and it can realize the self-supply of energy. [ABSTRACT FROM AUTHOR]

Lviv (Ukraine), a city of about 1 million inhabitants, is classified as a Western Forest-Steppe according to the forestry zonation. The mesoclimatic anomaly in the western forest-steppe with its humid mild climate is composed of the sum of microclimates formed by the thermal regime. As in every large city, Lviv has historically developed a distinctive microclimate influenced by many natural and anthropogenic factors, including global climate change, urban development, population growth, landscape fires, etc. This contributes to the development of a heat island effect, which is characterised primarily by an increase in air temperature and a decrease in air humidity and is a negative factor for the development of vegetation in the city's green zone. It was necessary to investigate the territory of the "dry island" -- the lower tier of the "heat island" -- to determine the level of vitality of the main woody plants located within these boundaries. As it could be observed, the "dry island" is located in the dense development of the central part of the city, where the temperature of the dead underlying surface (stone, asphalt, concrete) was in the range of 57-62 °C, the air temperature was 28.5-29.1 °C, and the humidity was 50.2--51.2%. Drought conditions affect the growth, development and reproductive capacity of woody plants. It has been established that the heat island should be reduced by urban greening in the horizontal and vertical ranges, and to maintain the physiological stability of tree plantations in the hot season, it is necessary to develop recommendations for the care of vegetation in the green zone of the city, depending on microclimatic indicators, especially air and soil temperatures, air and soil humidity. [ABSTRACT FROM AUTHOR]

The depth of convective clouds affects vertical transport of atmospheric constituents, influencing downstream weather and climate. Atmospheric controls on the maximum depth reached by moist convection are investigated with radar‐tracked convective cells tagged with sounding‐derived atmospheric parameters from a field campaign in central Argentina. Regression analyses show that narrow (<12‐km diameter) and wide (>16‐km diameter) cell depths respond to disparate factors, where cell areas are defined using composite reflectivity signatures. Undiluted lifted parcel indices including convective available potential energy (CAPE) and level of neutral buoyancy (LNB) are top predictors of wide cell maximum depth while mid‐tropospheric relative humidity is the top predictor of narrow cell maximum depth. Because narrow cells are more numerous than wide cells, the overall outcome of the full cell population does not strongly correlate with CAPE and LNB conditions. Tracked cells and atmospheric conditions in a simulation with 3‐km grid spacing covering the field campaign produce similar results to those observed. Narrow cells that are relatively deep have a cooler and moister mid‐troposphere with weaker free tropospheric subsidence, while relatively deep wide cells have much warmer and moister lower tropospheric conditions. These atmospheric differences are present 1 hr before cell initiation at both a fixed observing site and variable cell initiation locations. Simulated narrow cell maximum equivalent potential temperature decreases with height at a rate similar to the ambient vertical gradient, causing these cells to fall short of their LNB and supporting the view that entrainment‐driven dilution is a dominant control on their depth. Plain Language Summary: The depth that storms reach impacts where the heat, moisture, momentum, aerosols, and trace gases that they are transporting are deposited, but this depth is difficult to predict because most storms fall short of their theoretically maximum possible depth. The reason for this shortfall is that most storms are narrow, such that they are effectively diminished by mixing with surrounding drier air as the storm deepens. Thus, a dominant control on the depth of these clouds is the humidity of this surrounding air. However, wide storms are less vulnerable to destructive mixing with dry air. As a result, they more consistently reach depths that are well predicted by theory. These conclusions were reached via analysis of over a thousand storms over several months using field experiment measurements and a computer simulation. Key Points: Wide convective cell depth responds most to available instability, while narrow cell depth responds most to midlevel relative humidityEntrainment‐driven reduction of buoyancy decreases as cell width increases, causing disparate narrow and wide cell depth responsesA convection‐permitting simulation with 3‐km horizontal grid spacing generally reproduces observed relationships [ABSTRACT FROM AUTHOR]

As Arctic sea ice rapidly melts, trans‐Arctic shipping routes are emerging with significant economic value and potentially reshaping global shipping patterns. The safety of ships navigating along these routes will be severely threatened by low visibility caused by Arctic sea fog. Here, we utilize ship and coastal site observations spanning 1979–2023 to investigate the climatological features and mechanisms of Arctic sea fog from June to September. We find that the Northern Sea Route (NSR, along the Russian coast) experiences a mean fog frequency of 20.0%, significantly higher than the 11.5% fog frequency observed along the Northwest Passage (NWP, along the Canadian coast). Fog frequency shows null correlation with sea ice but a strong negative correlation (−0.80) with surface air temperature. The lower mean surface air temperature in the NSR region enhances relative humidity and atmospheric stability, which are conducive to fog formation and maintenance. We further reveal that fog formation mechanisms differ between the NSR and NWP. Along the NSR, fog is usually advection fog, associated with upper boundary layer warming and moistening; in contrast, along the NWP, fog is typically radiation fog linked to near‐surface cooling. Our study highlights the distinct fog frequency and dominant mechanisms along the different trans‐Arctic shipping routes, thereby establishing observed reference for the model validation of simulating Arctic sea fog. Plain Language Summary: The rapid retreat of Arctic sea ice, driven by climate change, has led to a gradual increase in the area of open water in the Arctic. Arctic shipping routes will soon be navigable in summer, allowing for a nearly one‐third reduction in distance from the Far East to western Europe, compared with traditional routes via the Suez Canal. In recent years, it has gradually been realized that the frequent occurrence of sea fog in the Arctic summer poses a threat to the safety and speed of Arctic shipping routes. Nevertheless, due to the sparsity of Arctic observations, the understanding of Arctic sea fog remains relatively preliminary. This paper uses multisource observation data to comprehensively investigate the climatological characteristics and formation mechanisms of Arctic sea fog, particularly highlighting their differences along the shipping routes. This work deepens our understanding of Arctic sea fog and provides a scientific observation guidance for enhancing the safety of Arctic navigation. Key Points: Fog frequency along the Northern Sea Route (NSR) is twice of that along the Northwest Passage, dominated by air temperature rather than sea iceFogs along the NSR are associated with warming and moistening at upper boundary layer, which are mostly advection fogFogs along the Northwest Passage are linked to near‐surface cooling, which are mostly radiation fog [ABSTRACT FROM AUTHOR]

Lily bulb rot disease has harmed edible lily in recent years, resulting in yield losses in China. As a results, both morphological and molecular techniques must be used to confirm the etiology of storage bulb rot disease on lily bulbs. Lily bulbs with indications of rot symptoms during storage were gathered in Lanzhou, Gansu Province, China. A strain was isolated and its morphologically characterized as a Schizophyllum commune specie. Pathogenicity tests further confirmed that the strain caused apparent S. commune symptoms on lily bulbs which were consistent with those seen in the field. The pathogenicity of S. commune to lily bulb was 100%, and morphological identification showed that the mycelia of the pathogen were white and villous, with septate, branched, and acicular bodies and obvious lock-shaped joints. The mycelia had uneven thickness, ranging from 1.03 to 3.06 μm, and turned gray-white at the later growth stage. Moreover, the pathogen formed a mycelial column on potato dextrose agar (PDA) medium, which formed a coral-like fruiting body primordium, which split, forming pileus for spore production. The spores were colorless and cylindrical, with an oblique tip and a size of 4.6–7.2 μm × 2.2–2.7 μm. The isolate was deduced as based on phylogenetic analysis with 2 genes (ribosomal DNA-ITS and LSU) as well as morphological characteristics and cultural features, the isolate was identified S. commune. Soluble starch, yeast extract, temperature of 30°C, pH 7, relative humidity of 100%, and complete dark were shown to be the optimum culture conditions for surface mycelium growth. In conclusion, this is the first report of S. commune causing bulb rot of edible lilies in China. The study provides a basis for more effective control strategies for lily bulb rot disease. [ABSTRACT FROM AUTHOR]

The aim of this study was to give insights on the effects of an industrially relevant kilning method, with a focus on lipase inactivation and oat-base production. Storage of non-kilned, dehulled oat kernels in either room temperature or at 37 °C for up to 64 days led to increasing lipase activity with time, despite a decrease in moisture content and water activity, demonstrating the importance of kilning before storage. It was shown that the temperature and relative humidity used during the kilning had a major impact on both protein solubility and lipase inactivation. Steaming with saturated steam at 90 °C for 30 min followed by drying at 100 °C for 30 min was found to be enough to inactivate all lipases but still leave a relatively high protein solubility (42% of the total soluble protein). In the sensory trial, the indication was that kilning was a vital step from a sensory quality perspective, giving a pleasant aroma to the final oat-base product. However, with kilning, the final protein content decreased; thus, these results are important for the development of future oat-base products, where quality, nutritional content, and taste need to be balanced. [ABSTRACT FROM AUTHOR]

Melanin is responsible, in Nature, for photoprotection, for this reason it is expected to be poorly photoreactive. However, the photo‐reactivity of melanin and related materials is well documented. Here we discuss some relevant recent examples to demonstrate that, indeed, the actual mechanism of interaction of melanin with light is complex and still not completely understood. Photochemical and photothermal processes are involved, giving a contribution that strongly depends on light wavelength and intensity. Moreover, some interesting experiments demonstrated that photochemical reactivity of melanin related compounds is likely to be indirect, in the sense that the effect of light is to increase the number of radical species rather than creating photoreactive excited state. These suggestions open‐up new perspectives in the interpretation of the role of melanin in photoprotection and in the design of new melanin based photoactive materials for energy conversion, environmental remediation, and nanomedicine. Further complication is given by the role of atmospheric oxygen and humidity in the photoinduced processes. Beside this complexity of behavior makes it difficult a systematic understanding of the interaction of melanin with light, it surely strongly contributes to make the properties of melanin and related materials unique. [ABSTRACT FROM AUTHOR]

AbstractHull compaction is an important waste management practice for volume reduction of hollow metallic hull waste generated in the back end of the nuclear fuel cycle. The hull waste should be totally dried of wash solution before high pressure compaction to avoid radiolysis and corrosion phenomena.[1] In the present work, the influence of various operating parameters (volumetric air flow rate, inlet air temperature, and quantity of hull waste) on the performance of a hull dryer unit has been investigated experimentally. It was observed that drying time exhibited an inverse relationship with both air flow rate and temperature. Furthermore, an increase in the mass of hull waste within the batching can led to improved dry air utilization efficiency. To enable a more comprehensive understanding of the drying process and accurate prediction of drying times, a mathematical model was formulated. A new methodology for estimating the specific surface area of randomly packed hull pieces has been presented. A comprehensive comparison of simulated data with measured exhaust air properties (mass absolute humidity, exit air temperature) and drying times was performed. The close agreement between model predictions and experimental results, with mean absolute percentage error ranging from 2.39923 to 25.21 established strong validation of the model, confirming its predictive capability. This validated model provides a robust foundation for designing future hull dryer units by enabling the calculation of optimal process parameters for various drying time requirements. The study shows that the direct contact hot air heating is a promising technique for drying of hull waste and can be accepted in fast reactor fuel cycle. [ABSTRACT FROM AUTHOR]

Liquid crystalline elastomers (LCEs) are considered as emerging functional materials that present potentials in fabrication of intelligent soft robots, biomimetic devices and photonic actuators. Here, a new functional liquid crystalline (LC) monomer with dynamic boronic ester group is designed and synthesized. This new molecule has a wide LC phase and polymerizable acrylic double bonds, which facilitates subsequent polymerization to prepare films. The prepared LCEs matrix is intrinsically self‐healable and self‐weldable. In addition, such material can be used as versatile matrix to be functionalized as diverse devices. By introducing the humidity responsive aggregation‐induced emission (AIE) molecules into the LCEs film, which exhibit bright fluorescence at low relative humidity (RH). Finally, copper sulfide (CuS) nanoparticles are doped into the LCEs film to achieve programmable thermal‐responsive deformations. This work provides valuable insight for the development of smart soft robots in actuating area. [ABSTRACT FROM AUTHOR]