Seasonal Temperature Changes Research Articles

Effect of seasonal changes in temperature on capture efficiency in the blue mussel, Mytilus edulis, fed seston and microplastics

AbstractSuspension‐feeding bivalve molluscs are dominant benthic fauna in many near‐shore environments, with phytoplankton often being their main prey type. Feeding, which involves hydrosol filtration and mucociliary processes to capture particles and process them for digestion, occurs at low Reynolds numbers. Changes in water temperature have been shown to affect feeding processes of bivalves as a result of altered physiological processes or temperature‐dependent changes in kinematic viscosity of water. Most studies, however, have focused on feeding rates and have manipulated temperature under laboratory conditions. In this study, experiments were conducted using ambient seawater and acclimatized blue mussels, Mytilus edulis, to examine particle capture efficiency over a 1‐year period. During this period, water temperature decreased from ~18°C to 5°C with a concomitant increase in viscosity of ~41%. The capture of a wide variety of bacteria and phytoeukaryotes (0.8–8 μm), as well as two sizes of polystyrene microspheres (1 and 6 μm), was quantified to calculate capture efficiency. Data demonstrate that temperature, and the concomitant change in water viscosity, had no significant effect on capture efficiency. Cyanobacteria were captured at significantly higher rates than other bacteria of similar size. These results suggest that the laterofrontal cirri of blue mussels act as paddles rather than sieves because capture efficiency was constant over a range of viscosities and Reynolds numbers. Additionally, the efficient capture of some bacteria and smaller phytoeukaryotes by the mussels suggests that these plankters could play a larger role in the diet of M. edulis than previously considered. The ecological impact of these findings, especially regarding differences in capture efficiency of different bacterial cells, warrants further study.

SARIMA Model-Based Maximum Temperature Forecasting in Bangladesh: A Data-Driven Evaluation from 1981 to 2024

Bangladesh is a tropical nation where there are notable seasonal temperature changes. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model is used in this study to forecast Bangladesh's maximum temperature from 2023 to 2042. The objective is to assess how rising temperatures can affect public health, energy consumption, and agriculture. Autocorrelation and partial autocorrelation analysis will be used to improve the model. Analysis was done using historical maximum temperature data spanning from 1981 to 2022. Forecasts were produced using the SARIMA model, whose parameters were chosen in accordance with plots of the autocorrelation function (ACF) and partial autocorrelation function (PACF). The model SARIMA (1,1,2)(0,0,1) is selected based on AIC. In order to account for forecast uncertainty, forecasts were created for the years 2023–2042. 95% prediction ranges were then calculated. Bangladesh's maximum temperatures are predicted by the SARIMA model to rise gradually, from roughly 33.75°C in 2023 to 34.17°C in 2042. With some degree of uncertainty, the 95% prediction intervals show a steady increasing trend between 33.53°C and 34.51°C. The anticipated increase in the highest temperatures has major consequences for Bangladesh. These results highlight how crucial it is to create adaptation plans and laws in order to lessen the effects of warming temperatures and increase resilience.

Initial monitoring of a six-story lightweight timber frame building under different environmental conditions

AbstractThis study presents a comprehensive investigation of the dynamic behavior of a six-story lightweight timber frame building through periodic and continuous ambient vibration tests. Seasonal changes in temperature and relative humidity can influence the dynamic response of timber buildings, by affecting stiffness, strength, and connection properties due to changes in moisture content. Systematic tests were performed from October 2022 until May 2024 to identify natural frequencies, damping ratios, and mode shapes of the building using five battery-driven data acquisition units equipped with 15 uni-axial accelerometers. Two different only-output frequency and time domain Operational Modal Analysis (OMA) methods were used to evaluate the dynamic properties of the building. Additionally, the building has been continuously monitored with temperature and humidity sensors since its construction. Results obtained from the periodic measurements highlighted the need for a permanent system to capture the transient changes in the modal parameters. A complementary permanent system to record the accelerations at the roof level was installed in May 2024. The modal parameters from in situ measurements were compared with those obtained from the Finite Element (FE) model of the structure. The FE model, calibrated through a multi-stage approach, incorporating non-structural elements, and varying imposed loads, showed good agreement with experimental data. Comparative analysis of the results obtained under different temperature and humidity conditions showed the effect of the environmental conditions on the building dynamics properties, for both periodic and permanent measurements. This study highlights the importance of continuous monitoring and detailed FE modeling in understanding the dynamic properties and long-term structural behavior under varying conditions. This information can be used to ensure that the building meets safety and performance requirements and to identify potential issues that may need to be addressed during the design and maintenance phases.

Monthly, Annual and Seasonal Changes in Temperature by Using Mann Kendall and Sen’s Slope Estimator in Karnataka, India

The mean annual minimum temperature during the period 1979-2019 has increased significantly in Eastern dry zone, Southern dry zone and Southern transition zone to a cumulative of total of 0.010°C, 0.013°C and 0.08 °C respectively while it has decreased significantly in Hilly zone with a magnitude of -0.032°C. The annual maximum temperature significantly increased in North eastern transition zone (0.018°C), North eastern dry zone (0.017°C), Northern dry zone (0.014°C), Central dry zone (0.010°C), Eastern dry zone (0.011°C), Southern dry zone (0.013°C), Southern transition zone (0.016°), Northern transition zone (0.016°C) and Coastal zone (0.018°C). The hilly zone experienced a decrease in annual maximum temperature by-0.055°C. Therefore, it is evidential that, Karnataka is getting raised over the years. Researchers should develop crop varieties that are insensitive to temperature changes and scientist should develop packages of practices which will reduce adverse effect of fluctuations in climate parameters on crop productivity.

Temperature-Induced Seasonal Dynamics of Brain Gangliosides in Rainbow Trout (Oncorhynchus mykiss Walbaum) and Common Carp (Cyprinus carpio L.).

This study aimed to determine the expression and distribution of gangliosides in specific regions of the brains of rainbow trout (Oncorhynchus mykiss Walbaum) and common carp (Cyprinus carpio L.) with regard to seasonal temperature changes. Seasonal changes in ganglioside expression and distribution within the species were expected. The natural ecosystems of these fishes differ significantly due to their distinct habitat preferences, geographic distributions, and environmental requirements. Based on the fact that the common carp is eurythermic and adapts to a wide range of temperatures, while the rainbow trout is stenothermic and thrives in a narrower temperature range, it was expected that these species would exhibit distinct patterns of ganglioside modification as part of their adaptive response to temperature fluctuations. Immunohistochemistry using specific antibodies for the major brain gangliosides (GM1, GD1a, GD1b, GT1b), along with the Svennerholm method for quantifying sialic acid bound to gangliosides, revealed that cold acclimatization led to an increase in polysialylated gangliosides in the common carp brain and an increase in trisialogangliosides in the rainbow trout brain. Immunohistochemical analysis also identified region-specific changes in ganglioside expression, suggesting specific functional roles in neuronal adaptation. These results supported the hypothesis that the composition and distribution of brain gangliosides change in response to seasonal thermal shifts as part of the adaptive response. The results underscore the importance of gangliosides in neuronal function and adaptation to environmental stimuli, with implications for understanding fish resilience to temperature changes. This study offers valuable insights into species' temperature adaptation, with implications for physiological and ecological management and improved aquaculture practices. Future research could expand the species scale, study molecular mechanisms and regulatory pathways in ganglioside metabolism, and examine ganglioside interactions with membrane proteins and lipids for a deeper understanding of thermal adaptation.

Spatiotemporal profiles and underlying mechanisms of the antibiotic resistome in two water-diversion lakes

Human-induced interventions have altered the local characteristics of the lake ecosystems through changes in hydraulic exchange, which in turn impacts the ecological processes of antibiotic resistance genes (ARGs) in the lakes. However, the current understanding of the spatiotemporal patterns and driving factors of ARGs in water-diversion lakes is still seriously insufficient. In the present study, we investigated antibiotic resistome in the main regulation and storage hubs, namely Nansi Lake and Dongping Lake, of the eastern part of the South-to-North Water Diversion project in Shandong Province (China) using a metagenomic-based approach. A total of 653 ARG subtypes belonging to 25 ARG types were detected with a total abundance of 0.125–0.390 copies/cell, with the dominance of bacitracin, multidrug, and macrolide-lincosamide streptogramin resistance genes. The ARG compositions were sensitive to seasonal variation and also interfered by artificial regulation structures along the way. Human pathogenic bacteria such as Acinetobacter calcoaceticus, Acinetobacter lwoffii, Klebsiella pneumoniae, along with the multidrug resistance genes they carried, were the focus of risk control in the two studied lakes, especially in summer. Plasmids were the key mobile genetic elements (MGEs) driving the horizontal gene transfer of ARGs, especially multidrug and sulfonamide resistance genes. The null model revealed that stochastic process was the main driver of ecological drift for ARGs in the lakes. The partial least squares structural equation model further determined that seasonal changes of pH and temperature drove a shift in the bacterial community, which in turn shaped the profile of ARGs by altering the composition of MGEs, antibacterial biocide- and metal-resistance genes (BMGs), and virulence factor genes (VFGs). Our results highlighted the importance of seasonal factors in determining the water transfer period. These findings can aid in a deeper understanding of the spatiotemporal variations of ARGs in lakes and their driving factors, offering a scientific basis for antibiotic resistance management.

The Yangtze River Delta experienced strong seasonality and regular summer upwelling during the warm mid-Holocene

The mid-Holocene climate optimum saw warm temperatures in large parts of China, but its impact on seasonal environmental changes is not fully understood yet. Here, we use high-resolution geochemical analyses of 7000 to 6000 year-old oyster shells from the Yangtze River Delta to reconstruct climatic and oceanographic patterns. The stable isotope (δ18O, δ13C) and clumped isotope data reflect prominent seasonal changes in temperature, precipitation, and river discharge. Summer months experienced warm temperatures and a distinct increase in rainfalls and river discharge. In contrast, winter months were characterized by a dry season, which might have been longer than today. Stable isotope data also indicate regular summer upwelling in the study area. These results partly disagree with available climate models raising doubts on the models’ reliability. Thus, our palaeo-proxy data offers the possibility to evaluate and correct climate models and thereby improve predictions for the future considering on-going global warming.

Changes in the spatiotemporal distribution of the timing and duration of the soil freeze–thaw status from 1979 to 2018 over the Tibetan Plateau

AbstractChanges 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.

A before after control impact experiment on a historically fished seagrass (Zostera marina) bed

AbstractSeagrasses are considered to be globally important for carbon sequestration and they provide a range of ecosystem services. However, they are also known to be vulnerable to various anthropogenic activities, not least bottom contacting fishing gears such as dredging and potting. We set out to test the effects of dredge fishing, in early spring and potting in late summer, in a historically fished but considered “pristine” seagrass meadow on the west coast of Ireland. We found that despite dredging and potting pressures, growth of seagrasses was driven by seasonal changes in light and temperature and that neither fishing activity had any effect on rhizome weight or shoot or blade densities during the growing season. We hypothesize that it is possible for fishing to co‐occur with seagrass if fishing activities are restricted to winter or early spring, before the main seagrass growing season, and/or if particular types of gear, such as the traditional gears described here are used. High levels of dredging and potting had positive increases in the count of both sessile and mobile epifauna suggesting that for mobile species at least, they may take advantage of post‐fishing scavenging opportunities.

Strawberry Volatile Organic Compounds for Targeted Metabolomics: The AMDIS Strawberry User Library from Korean Germplasm

Strawberry aroma, crucial for determining quality, involves complex volatile compounds which are challenging to identify. This study explores strawberry aroma analysis using Gas Chromatography-Mass Spectrometry (GC-MS) and the Automated Mass Spectral Deconvolution and Identification System (AMDIS). Central to our research is the creation of a bespoke strawberry Volatile Organic Compounds (VOCs) user library using AMDIS, specifically for analyzing strawberry aromas. The library contains VOCs from 61 strawberry cultivars, integrating information on 104 VOCs, including mass spectra, retention index, chemical class, CAS number, formula, odor threshold, and odor description. This custom library significantly outperformed a commercial library by reducing potential false hits by 200, decreasing the size of report files by over 96%, and, most importantly, shortening AMDIS analysis processing time from 31 s to 9 s, representing an approximate 71% reduction. Further, the study demonstrates the library’s practical application by contrasting the aroma profiles of strawberries harvested in winter and spring. This comparison revealed significant VOC variations depending on seasonal temperature changes, offering insights into environmental influences on strawberry aroma. In conclusion, this research marks a significant advance in strawberry aroma quality analysis. The strawberry VOC library developed in this study is expected to greatly aid targeted metabolomics and flavor research in strawberry breeding.

Pollen-based seasonal temperature reconstruction in Northeast China over the past 10,000 years, and its implications for understanding the Holocene Temperature Conundrum

The Holocene Temperature Conundrum refers to the mismatch between proxy-based temperature records and those based on climate model simulations. A possible reason for this mismatch is a putative proxy-based bias in reconstructed summer temperatures, and therefore, regional reconstructions of seasonal temperature are crucial for resolving the conundrum. In this paper, we reconstruct vegetation and climate changes over the last ∼10,000 years BP based on a high-resolution pollen record from Gushantun peatland, Changbai Mountains, Northeast China. Multiple quantitative reconstruction approaches were used and weighted averaging partial least squares regression (WAPLS) was found to be the most appropriate method for reconstructing Holocene temperature and precipitation. The reconstructed climate record shows that the Holocene Climate Optimum occurred between 8 ka and 6 ka and exhibited a cold month mean temperature that was 3 °C warmer than modern temperatures. Climate gradually cooled during late Holocene with a minimum cold month temperature of −19.6 °C. Four prominent cold events occurred around 8.7 ka BP, 7.8 ka BP, 5.7 ka BP, and 2.5 ka BP with an amplitude variation up to 3 °C. The synthesized seasonal temperature time series and a comparison with other proxies show that the decreasing trend in mean annual temperature is not a seasonal bias caused by summer temperature change. This study provides evidence of a Holocene seasonal temperature change at a regional scale and insights for further understanding of the Holocene Temperature Conundrum.

Exploring Performance of Using SCM Concrete: Investigating Impacts Shifting along Concrete Supply Chain and Construction

Concrete is one of the most used building materials globally, leading to a large amount of greenhouse gas (GHG) emissions. Using supplementary cementitious materials (SCM) as replacements for cement in concrete provides an effective way to reduce GHG emissions. However, quantifying the construction performance of using SCM concrete is hard because of complex interactions between concrete’s mechanical properties and construction characteristics, like local energy supply, surrounding temperature and construction plans, which leads to only the fragmental performance of using SCM concrete being explored in previous studies. There still lacks an effective way to quantify the comprehensive performance and provide decision support for contractors about how to use SCM concrete. To deal with the gap, this research proposes a Collection–Simulation–Calculation–Decision (CSCD) method to analyze the complex interactions between concrete and construction, and to quantify the performance of the supply chain–construction when using SCM. A case study is also conducted to demonstrate the effectiveness of the proposed method. The results show that the proposed method is effective in quantifying the performance of using SCM concrete in construction and providing decision support for construction decision makers. A scenario analysis is also conducted to demonstrate the effectiveness of the proposed method in different project characteristics, including the global warming potential (GWP) factors for different construction sites, seasonal temperature changes and different construction plans. The proposed method is an effective tool to quantify the construction performance of using SCM concrete considering complex interactions between concrete mechanical properties and construction characteristics. The results of the research can assist construction decision makers to make decisions about using SCM concrete by comprehensively understanding the impacts shifting along the concrete supply chain and construction.

STATISTICAL ASSESSMENT OF WATER QUALITY PARAMETERS FOR POLLUTION SOURCE IDENTIFICATION IN NOYYAL RIVER, COIMBATORE, TAMILNADU

<p>This study aimed to determine the extent of the water quality decrease in the Noyyal River in Tamilnadu by analyzing the seasonal change of water's physicochemical properties, identifying possible sources of pollution, and grouping the monitoring months based on shared characteristics. The measurements were taken during four different seasons. Forty percent of the water quality indices, including turbidity, DO concentration, EC, Cl concentration, TA, and COD in all seasons, were found to be outside the acceptable limits recommended by various agencies, according to the analytical data. A 95% confidence interval's worth of statistical analysis revealed that 52% of the contrasts differed significantly. Four factors accounted for 93.44% of the variation overall, according to the factor analysis, which showed the best fit between the parameters. The significant pollution loading, primarily attributed to toxicological chemicals and industrial discharge, was reflected in Total Dissolved Solids, Biochemical Oxygen Demand, Chemical Oxygen Demand, Electrical Conductivity, Turbidity, Dissolved Oxygen, and Chloride levels. Cluster analysis revealed a seasonal variation in surface water quality, indicating contamination from rainfall or other sources. Nevertheless, seasons did impact the levels of various physicochemical characteristics, with winter recording the highest pollution values. The Noyyal River's seasonal temperature change and increased rainfall were the causes of this self-refining tendency, which goes winter < summer < pre-winter < rainy season.</p>

Wyniki badań glonów i sinic w różnych ekotypach gleb w Adżarii w Gruzji

The publication deals with the studies on the diversity of species composition of Algae and cyanobacteria in various layers of soils (yell, red, soilsod-podzolic, marsh, urban) of the Adjara. The aim of the study was to identify and determine the composition of Algae and cyanobacteria; Establishment of the scale of development and spread of algoflora; Assessment of the ecological state of the Algae and cyanobacteria in adverse and favorable conditions. The diversity of algae and cyanobacteria was studied in soil cultures using the method of fouling glasses. Each treatment included 5 ste-rile cover glasses for micropreparations; cultures were wetted with distilled water. The presence of algoflora was detected in various soil samples based on morphological characteristics, percentage frequency, growth rate, and colony forming units. The study has found 171 species and subspecies of soil Algae and cyanobacteria, belonging to the divisions of Ochrophyta (59 species), Chlorophyta (51 species), Xanthophyta (8 species), Eustigmatophyta (1 species) and Cyanobacteria (52 species). Classes Bacillariophyceae, Chlorophyceae, and Cyanophyceae were considered polymorphic among the leaders. 11 species of algoflora involved in algoflora of the consortium have been specified as well. The most widely distributed algoflora in soil samples were of the genera Chlamydomonas (20 species), Eunotia (17 species), Phormidium (11 species), Pinnularia (11 species), Tetracystis (10 species), Leptolyngbya (9 species), Nitzschia (9 species), Chlorococcum (8) species, Nostoc (7) species and Oscillatoria (6 species) were dominant flora in all soil samples. Frequency percentage algoflor showed that from all of the soil, the maximum quantities of algoflora and cianobacteria in marsh soil that was 65.49%, in sod - podzolic soil 34.51%, in yell soil 19.88, in red soil 18.71%, the lowest frequency of occurrence of algoflora and cianobacteria was shown in urban soil 9.35%. Due to seasonal changes in soil and air temperature, there are 71 species (41.52%) in spring, 65 (38.95%) in summer, 78 (45.61%) in autumn, and 53 (30.99%) in winter. A lower level of biological activity in the urban soils was found. Morphometric trait differences in test objects activated on the soil samples have been observed. The study was found specialized species of Algal-cyanobacterial communitiesfrom each ecotype of soil. The soil samples collected from polluted sites were more affected by waste water which affected the population densities of Algal-cyanobacterial communities. Found that Adjara support a large and diverse community of Algal-cyanobacterial on soil, many species of which are previously undiscovered and undescribed. On this basis, works of longer duration and more intensive sampling are needed to obtain data regarding Algal-cyanobacterial communities, with more attention to specific variables such as microclimate, soil moisture, soil type, soil pH and vegetation types.

Soil-structure interaction issues in integral abutment bridges

Integral Abutment Bridges (IABs) are constructed without expansion joints and bearings, connecting the bridge deck monolithically to the end abutments. Therefore, the construction and maintenance costs of IABs are low compared to conventional bridges with bearings and joints. However, the soil-structure interaction issues are more complex for IABs due to the transfer of deck movements to the foundations through the abutments. Hence abutments of these bridges play an important role in the performance of the substructure and consequently the design approach for the substructure. In this paper, soil-structure interaction issues are investigated for the deck movements due to cyclic thermal loading, which occurs as a combination of daily and seasonal temperature changes. The development of a physical model facility to simulate the problem is described with scaling laws and material properties. The settlement problem at the bridge approach and stress ratcheting phenomena observed at the abutment soil interface are discussed using results from model tests. For the prediction of lateral earth pressure distribution behind abutments, currently available methods are discussed, and modifications are proposed. Finally, the effectiveness of Expanded Polystyrene (EPS) geofoam as an inclusion is discussed to mitigate approach settlement and stress ratcheting problems due to cyclic thermal loading. The results of this study confirm that EPS geofoam is a highly effective material to minimise adverse soil-structure interaction issues in integral bridge abutments.

A Simulator Based on Coupling of Reaction Transport Model and Multiphase Hydrate Simulator and Its Application to Studies of Methane Transportation in Marine Sediments

Summary Methane emissions at seafloor are generally associated with the upward methane migration from the deeper sediments, partly from hydrate dissociation. The anaerobic oxidation of methane (AOM) occurring in the surface sediments acts as an important barrier to methane emissions, caused by the reaction between sulfate ions and dissolved methane molecules. However, the current hydrate simulators rarely consider the transport of sulfate and the subsequent AOM reaction. In this study, to investigate AOM effects in hydrate systems, a new simulator named Tough+Hydrate+AOM (THA) is developed by combining the reaction transport model (RTM) with the widely used Tough+Hydrate (T+H) simulator. The THA simulator is validated using the single-phase cases of the Dvurechenskii mud volcano in Black Sea since the results obtained are in good agreement with previous ones. This simulator is then applied to investigate the response of a hydrate reservoir offshore West Svalbard to seasonal seafloor temperature change and also to confirm its adaptability in multiphase hydrate systems. The results obtained suggest that the AOM filter efficiency is as low as 5%, meaning that the majority of methane released from hydrate dissociation in the deeper sediments will escape into the ocean. The THA simulator considering AOM is expected to be an important tool for assessing methane emissions caused by hydrate destabilization.

Bioinspired Superhydrophobic All-In-One Coating for Adaptive Thermoregulation.

The development of scalable and passive coatings that can adapt to seasonal temperature changes while maintaining superhydrophobic self-cleaning functions is crucial for their practical applications. However, the incorporation of passive cooling and heating functions with conflicting optical properties in a superhydrophobic coating is still challenging. Herein, an all-in-one coating inspired by the hierarchical structure of a lotus leaf that combines surface wettability, optical structure, and temperature self-adaptation is obtained through a simple one-step phase separation process. This coating exhibits an asymmetrical gradient structure with surface-embedded hydrophobic SiO2 particles and subsurface thermochromic microcapsules within vertically distributed hierarchical porous structures. Moreover, the coating imparts superhydrophobicity, high infrared emission, and thermo-switchable sunlight reflectivity, enabling autonomous transitions between radiative cooling and solar warming. The all-in-one coating prevents contamination and over-cooling caused by traditional radiative cooling materials, opening up new prospects for the large-scale manufacturing of intelligent thermoregulatory coatings.

Impact of seasonal global land surface temperature (LST) change on gross primary production (GPP) in the early 21st century

Understanding the impact of global land surface temperature (LST) changes on gross primary production (GPP) is crucial for addressing global sustainability challenges effectively. This article explores the effects of winter and summer temperature variations on GPP from 2001 to 2020 on a global scale, employing a range of modeling techniques to investigate the complex relationship between temperature changes and GPP. The study employs various modeling approaches, including linear regression models, artificial neural networks, Random Forest (RF) models, and the XGBoost algorithm to examine both linear and non-linear relationships between global temperature changes and GPP. The results reveal that the RF and XGBoost models effectively capture the non-linear relationship between LST and GPP during both summer and winter, demonstrating a high level of statistical significance (P < 0.01) and achieving R2 values of 0.598. Furthermore, the study applies a Sen+MK trend analysis model to identify six distinct trend patterns in LST and GPP during both summer and winter seasons. In summer, the area exhibiting a non-significant increasing trend (NSI) for GPP covers 65,066,274.77 km2, whereas in winter, a strong significant decreasing trend (SSD) for GPP spans 64,537,108.31 km2. Notably, GPP patterns closely mirror those of LST, suggesting that rising high-temperature conditions during summer lead to reduced GPP, while increased low temperatures during winter promote GPP growth. Robust correlations between LST and GPP are observed under various trend conditions in both summer and winter, displaying strong statistical significance (P < 0.01), with SSD achieving a maximum R2 of 0.594. These findings contribute significantly to our comprehensive understanding of the dynamic relationship between LST and GPP and offer valuable insights for addressing the sustainable development of global climate change challenges.

A comprehensive framework for targeting the disturbance propagation path and debottleneck strategy of chemical process considering the topology and cascading effects

For the chemical processes, multiple fluctuations exist, and elucidating the system's dynamic changes is essential in improving its adaptability. With changes in reactor and separator operating conditions and cascading effects related to the system's topological structure considered, a comprehensive framework is established to target the disturbance propagation path and determine cost-effective debottlenecking strategies. Relations among distillation column parameters and the seasonal change in ambient temperature are deduced considering meteorological data, and the utility demand or column pressure under various conditions can be determined. All independent subsystems of the heat exchanger network and their heat surplus/deficit are identified based on the improved information flow diagram and output difference analysis, and the disturbance propagation path is determined. Correlations are deduced to clarify the heat transfer capacity requirement under fluctuating states, and the bottlenecks and cost-effective debottlenecking strategy without topology modification are identified at different stages. The proposed method is intuitive and efficient and can be applied in chemical processes' enhancement, retrofitting, and fault diagnosis. A benzene alkylation process is studied, with the total annual cost decreased by 3.4 %.

Three birds with one stone strategy: A tri-modal radiator based on the cooling-compensation-heating effect

Passive radiative using solar energy for energy gain is receiving increasing attention as a green and sustainable energy supply method. However, passive radiative designs of existing materials are usually static and unsuitable for dynamic seasonal and weather changes. Here, we explore an efficient design of a temperature-adaptive thermal management sandwich structure that integrates passive daytime radiative cooling/heating and temperature control of phase change materials. Compared with conventional passive radiators, the developed phase change material-enhanced radiative cooler/heater (PDHM) can be flipped to adjust thermal management performance according to seasonal and diurnal temperature changes. The radiative cooling layer (PDRC) has a high solar reflectance (95%) and a high infrared emissivity (97%). The phase change layer (PCM) acts as an effective compensation for temperature, causing the PDRC cooling power to rise and fall by 15 W·m−2 during daytime and nighttime. The radiative heating layer (PDRH) has a low infrared emissivity (75.6%) and a high solar absorptivity (85.7%). The final PDHM aerogel achieves 11 °C below ambient temperature and 25 °C above ambient temperature under direct sunlight in summer and winter, and it leads to an increase in the average nighttime temperatures of 2.1 °C and 1 °C in summer and winter, reducing the diurnal temperature difference. Thus, the temperature-adaptive PDHM shows great potential for passive radiative regulation, which can further extend the application of passive radiators.