Average Temperature Research Articles

Modeling the larval growth and survival of Pacific cod (Gadus macrocephalus) in the eastern Bering Sea

The eastern Bering Sea (EBS) is a highly productive ecosystem that supports several important commercial species such as the Pacific cod (Gadus macrocephalus). Climate variability affects the population dynamics of this stock throughout its life stages, especially early life stages, since they are particularly susceptible to environmental changes. In recent decades, warm and cold stanzas (i.e., 3–5 year periods) have been observed in the EBS, and there is evidence that they can modulate the recruitment of this stock, causing important socioeconomic impacts. Using a mechanistic individual-based model, this study investigates the spatial and temporal variability of growth and survival of Pacific cod's early life stages during 2000–2020. We examined changes by year and over space and compared our results with published literature to validate our model. We found that temperature played a key role in modulating the survival of fish larvae, observing an increase in starvation events in warmer years or locations. Periods or areas with low prey density, especially small-bodied copepods, also contributed to increased starvation. The average temperature in the fish habitat was negatively correlated with recruitment estimates from the stock assessment model. Growth was primarily temperature-driven; however, food-limited growth became more frequent when larvae were smaller during cold years. Spatially, we found that the environmental conditions in the southeastern Bering Sea may favor larval survival but reduce growth, and higher mortality may be persistent on the middle and outer shelf. Our model produces results that agree with previous field studies, and it offers a valuable tool to investigate other ecological questions on the impact of the environment on early life stages of fishes.

A Scaling Relation for Core Heating by Giant Impacts and Implications for Dynamo Onset

AbstractAccretional heating of Earth's interior during formation is pivotal to its subsequent thermal and chemical evolution. In particular, impact heating of Earth's core is expected, but its amplitude and radial distribution within the core is unknown and could influence the onset of the geodynamo. The uncertainty is due, in part, to the lack of constraints on the temperature of the interior following formation due to the difficulty of preserving a record of such a high energy environment, and the assertion that super‐heating during formation would be rapidly lost through magma ocean cooling. Here we systematically investigate core heating due to giant impacts using a Smoothed Particle Hydrodynamics (SPH) code with simulations spanning a range of impact angles, velocities, and masses. From these simulations we derive a scaling relation for core heating that depends on the impact parameters and predicts the radial core temperature profile following the impact. Our findings show that a significant amount of heat is deposited into the core, with a canonical impact scenario resulting in an average core temperature increase of about 3000 K, approximately 500 K higher than that of the overlying mantle. In this case the heat distribution within the core produces a strong thermal stratification. We use a parameterized cooling model to estimate that the core could have cooled to an adiabatic state ∼290 Myr after a canonical impact, which is consistent with the observed time span between the age of the Moon and evidence for an active geodynamo.

Sampling time for different matrices in stress assessment of farmed Atlantic salmon post-smolt

The sustainability of commercial aquaculture production depends critically on prioritizing fish welfare management. Besides monitoring welfare parameters such as fish behaviour and water quality, fish stress level can also provide a reliable measure of the welfare status of farmed fish. Cortisol and 5 of its metabolites (5β-THF, cortisone, 5β-DHE, 5β-THE, β-cortolone) were previously identified by the authors as suitable stress biomarkers of farmed Atlantic salmon. Based on this knowledge, the present study aimed to investigate the time-related dynamics of these metabolites in plasma, skin mucus, bile and faeces over a 72 h- period. The objective was to determine the optimal sampling time for each matrix and to understand the clearance pathway of these metabolites following stress. An experiment was carried out using a total of 90 Atlantic salmon with an average weight of 438 (±132) g. The average sea temperature was 6.9 °C during the experimental period. A control group of 10 fish was first collected before the remaining 80 fish were submitted to a stress of netting and subsequent relocation into two separate cages. From each of these two stress groups, 10 fish were sampled at 1h, 2h, 4h, 6h and 12h, 24h, 48h, 72h after the stress event respectively. The concentrations of cortisol and its metabolites were measured at each of the sampling timepoint. The results demonstrated that plasma cortisol metabolites reached the highest concentration 4h after stress and remained elevated despite the slight decrease for the remaining timepoints. The peak level was observed at 12h post stress in skin mucus and 24h in bile and faeces. The findings suggest that these timepoints are the optimal for sampling Atlantic salmon post-smolt following stressful events in acute stress studies. Furthermore, the results reveal that analysing cortisol and its metabolites, both in free and conjugated forms, rather than free cortisol provides greater flexibility as their concentrations are less affected by sampling procedure. This study confirms the appropriateness of skin mucus and faeces as less-invasive sample matrices for fish stress evaluation and provides a basis for further developing low invasive tools for monitoring the welfare of farmed salmonid.

Influence of loading on the heat transfer rate and specific water consumption of detached loosed fresh palm fruits during vertical mini-batch sterilization

This study presents the effect of loading on the heat transfer rate and specific water consumption of detached loosed fresh palm fruits during sterilization. Sterilization is an integral process of palm oil extraction that consumes a lot of water. However, most industrial research in the past focused on fresh fruit bunch (FFB) sterilization dynamics. At the same time, the medium- and small-scale industries sterilize already detached loosed fresh palm fruits (LFPF) that have been removed from the spikelet as purchased from aggregators. Therefore, the process data generated from the sterilization of FFB might not be optimal for sterilizing LFPF. This study, therefore, investigates the transient response of variation in LFPF loading of the sterilization chamber to steam injection during steam sterilization of LFPF at 3 ± 0.5 bars using a vertical, single-peak LFPF sterilizer that combines the boiler and sterilizer in a single unit. The LFPF were loaded at mass intervals of 0.2 kg ranging from 0.2 kg to 2 kg. The vapour temperature dynamics, heat transfer rate, steam energy utilization efficiency and specific water consumption parameters were studied. The average vapour temperature varied from 100 °C to 130 °C for the LFPF mass range of 0.2 to 2 kg at steam injection temperature of 140 °C and pressure of 3 ± 0.5 bars. This temperature range matched the saturated vapour temperature of pure water at 1.0––2.8 bars absolute pressure but slightly lower than the saturated vapour temperature of 133.54 °C for pure steam at 3 bars. The percentage of steam energy utilization effectiveness is inversely related to the steam mass flow rate. While energy effectiveness increased with loading mass, the steam mass flow rate decreased with increased LFPF mass. The value of the heat transfer rate ranged between 1.7––55.4 W, while the specific heat transfer rate ranged between 8.5–––41.8 W/kg. The average specific water consumption ranged from 0.014 to 0.09 kg-water/kg-LFPF, with an average value of 0.031 kg-water/kg-LFPF. This value is lower than 0.112–––0.5 kg-water/kg-FFB, with an average value of 0.256 kg-water/kg-FFB for conventional FFB steam sterilization. This represents an 87.9 % reduction in water consumption in conventional FFB steam sterilization. An empirical model deduced for specific heat transfer rate and water consumption for steam sterilization of LFPF at 3 ± 0.5 bars and vapour temperature range of 100––130 °C showed a high coefficient of determination above 99 %.

Optimal sowing time to adapt soybean production to global warming with different cultivars in the Huanghuaihai Farming Region of China

ContextThe Huanghuaihuai Farming Region (HFR) is one of China’s largest soybean production zones, with climatic conditions in the HFR being near ideal. In recent decades, however, global warming has increasingly inhibited soybean production in this region. ObjectiveOur aim was to determine whether planting time and/or genetics (heat-resilient and heat-sensitive cultivars) enable adaptation of soybean cropping systems to the changing climate. MethodsTwo-year split-plot design field experiments comprising five different sowing dates and three cultivars (namely heat-resilient, heat-sensitive and widely grown ones) were conducted in the HFR in 2020 and 2021. ResultsDelayed sowing dates significantly elevated the average minimum temperature in the vegetative growth stage, fostering soybean growth and consequently truncating the vegetative growth stage. Later sowing reduced the occurrence of heat stress and minimized negative influences of heat stress on yield. Higher heat stress in the first two sowing treatments (1 June and 10 June) negatively influenced yields of Hedou14 (heat-sensitive cultivar) and Zhonghuang13 in 2020, while the highest yield was obtained for the third sowing treatment (20 June) for these two cultivars. In general, Jidou21 (heat-resilient cultivar) showed greater tolerance to increasing temperature, with higher yield at earlier sowing. Delayed sowing decreased temperature exposure and growing degree days (GDD), reducing the duration of grain filling, leaf area index and photosynthesis, in turn decreasing grain number per plant and 100-grain weight. Taken together, such factors inhibited yield of all cultivars in the year without heat stress. In contrast, high precipitation (2021) prolonged grain filling and increased yield. ConclusionsWe contend that optimizing sowing time is crucial for mitigating heat stress in heat-sensitive cultivars. We suggest that high yield is more likely to be realized when crops are exposed to GDD > 500℃·d and precipitation > 250 mm during grain filling. ImplicationsFuture studies aiming to elicit optimal sowing times for soybean should consider cultivar heat sensitivity relative to long term climatic conditions of the target agro-ecological region.

Associations between heat wave during pregnancy and term birth weight outcomes: The PARIS birth cohort

BackgroundClimate change will make extreme weather events more frequent in the 21st century. Extreme ambient temperatures during the prenatal period have been associated with adverse pregnancy outcomes such as preterm birth. It is unclear, however, whether heat waves during pregnancy impact fetal growth in apparently healthy term newborns. ObjectivesWe aimed to investigate associations between heat wave during pregnancy and birth weight outcomes in term newborns from the PARIS birth cohort, and to explore meteorological conditions and air pollution as possible intermediate factors. MethodsWe examined data on 3,359 newborns born between 37 and 42 weeks in Paris, France, between 2003 and 2006. Associations of maternal exposure to heat wave (during whole pregnancy and each trimester) with birth weight and small for gestational age (SGA) at term were studied using linear and logistic regression models adjusted for potential confounders. Maternal characteristics were investigated as possible modifiers. We explored the mediating role of ambient temperature, relative humidity, and air pollution levels in the relationship between heat wave during the first trimester and term SGA. ResultsMothers who were pregnant during the 2003 French heat wave (n = 506, 15 %) were more likely to have a term SGA baby (aOR = 2.70; 95 %CI: 1.38, 5.28) compared to mothers who did not experience heat wave during pregnancy. The association was stronger when heat wave occurred during the first trimester (aOR = 4.18; 95 %CI: 1.69, 10.35). Primiparous women were identified as more vulnerable than multiparous women. Average ambient temperature and air quality index explained about 36 % and 56 % of the association between heat wave during the first trimester and term SGA, respectively. ConclusionsThis study suggests prenatal exposure to heat wave, especially during the first trimester, may adversely affect fetal growth of term newborns, which could be explained by both increasing ambient temperatures and worsening air quality.

Natural lignocellulosic biomass structure inspired CNF/Lignin/PBAT composite film with thermoplastic, antibacterial and UV-blocking abilities

The development of a thermoplastic, biodegradable composite material to replace conventional polymers derived from petroleum was the main area of concentration. Herein, a method for preparing antibacterial, UV-blocking and degradable CNF/Lignin/PBAT composite films (CLP) using cellulose nanofibrils (CNFs), lignin, and Poly (butylene adipate-terephthalate) (PBAT) as raw materials by solution casting method was described. With the adding of PBAT, the thermal stability, thermoplastic, mechanical properties were enhanced by improving the compatibility between components. The maximum tensile strength of CLP could reach 189.72 MPa, which increased 25.5 % compared to CNF/Lignin film. The average initial decomposition temperature could reach 321 °C, which much higher than that of CNF and lignin. At the same time, it holds good heat-sealing performance made it suitable for practical use. Meanwhile, the composite films had excellent UV resistance and could block over 95 % of UV light. The antibacterial results indicated that the films had a good inhibitory effect on E. coli and S. aureus, with a maximum inhibitory ring diameter of 5.56 and 6.36 mm. In addition, the composite film also had excellent barrier capability to liquid and gas. The prepared film had potential to produce flexible packing, industrial compositing and biomedical fields.

Multiple heating loads participate in the system power regulation control strategy

With the addition of a high proportion of new energy and power electronic equipment, the power system has shown characteristics such as low inertia and significant energy output fluctuation, which has brought great challenges to power/frequency regulation and control of the power system. Therefore, this article uses the inertia characteristics of heat energy on the load side and exerts reasonable start-stop control to play a positive and beneficial role in the power regulation of the power system. Firstly, the room temperature variation process was transformed into a lumped parameter equivalent model. A lumped parameter heat transfer model of a single typical load was built in Simulink, and its dynamic characteristics were analyzed by symbolic calculation. Based on this, a time-domain simulation was carried out to explore the influence of the law of system parameters and external input on the change of system state quantity. Based on time domain simulation, the behavior of the heating load is analyzed. Then, the effects of typical and multiple loads on system power regulation at different outdoor temperatures are studied. It is found that when the average outdoor temperature decreases, the sustainable time of system power upturn will increase, and the sustainable time of downturn will decrease. The power curve of multiple loads simultaneously is more stable, and the adjustment ability is stronger. The reasonable and flexible control method of load switch setting, namely the coherent characteristic load power regulation strategy, realizes the sustainable power optimization of the load to the system in the specified period.

Fabrication of carbon fiber/cement composites with controllable precise patterned structures via facile computerized embroidery

Carbon fibers exhibit good electrothermal performance; however, they break easily during the weaving process. This study used a facile computerized embroidery process to design and fabricate carbon fibers with controllable and precise patterned structures. The obtained carbon fiber/cement composites (CFCs) exhibited excellent electrothermal performance (100 ℃ under 30 V), low energy consumption (400 mW/℃), and homogeneous heat distribution with a unique heating element (carbon fibers) structure. The difference between the maximum and average surface temperatures improved, and the surface heat distributions of the CFCs under different structures were determined using a finite element simulation. CFCs with different complex heat element structures were successfully fabricated, and the mechanism regulating the heat distribution of the CFCs was revealed. Embroidery technology provides a novel strategy for the fabrication of carbon fiber/cement composite materials with a controllable carbon fiber structure, thereby significantly broadening the application of cement composites for electrothermal applications.

Water temperature and microenvironmental factors predict the presence and detection of the snail host of Fasciola hepatica in Andean Patagonia

The transmission of Fasciola hepatica occurs only where there are -or recently were- aquatic or amphibious snails of the Lymnaeidae family, the intermediate host of this parasite. Direct detection of these snails is time-consuming and imprecise, hindering accurate and detailed mapping of transmission risk. To identify which microenvironmental factors could be used as proxies for the occurrence of the lymnaeid snail Galba viator, a major intermediate host in South America, a total of 183 1-m2 quadrants across diverse water bodies in an endemic area in Andean Patagonia were manually timed-searched for snails and microenvironmental variables were registered. Data was analyzed using a Bayesian hierarchical occupancy model that assessed the effects of the microenvironmental variables on the presence of snails while considering imperfect snail detection. The model estimated that G. viator predominantly inhabits shallow aquatic environments, in the presence of grasses, where snails of the genus Biomphalaria are also detected, and with scarce tree canopy cover. Physical factors affecting occupancy presumably act as proxies for the average water temperature, while the temperature at the time of sampling was found to affect snail detectability. The identified variables are easy, fast, and inexpensive to measure, and can complement management decisions and risk maps based on coarser remote-sensing data, particularly relevant in a context of growing resistance to anthelminthic drugs.

Biomimetic phase change capsules with conch shell structures for improving thermal energy storage efficiency

Latent heat storage system utilizing a packed-bed setup with encapsulated phase change materials (EPCMs) can address the issues of mismatched energy supply and demand, in addition to preventing the leakage concerns associated with unencapsulated PCMs, which has a broad application prospect. Drawing on the principles of biomimicry, this work proposes bionic-conch and bionic-mitochondrial encapsulation models for PCMs and analyzes the heat transfer performance with different structures. Significantly, the thermal energy storage efficiency of the bionic-conch structure surpassed that of the bionic-mitochondrial and straight-fin structures by 43.11 % and 14.62 %, respectively. The enhanced thermal energy storage efficiency of the bionic-conch is attributed to the spiral fins within, which considerably amplify the heat exchange surface area. Furthermore, in order to obtain the bionic-conch capsule structure with optimal thermal properties, the present work investigates the influence of fins on the melting characteristics of PCMs. The results show that increasing fins empower the thermal energy storage efficiency by 402.89 % and thermal response rate by 616.93 %, respectively. However, there is an issue of slow melting process in the annular region and incorporating an array of a slightly off-center heat-conducting ring (SOHR) is considered to enhance localized heat transfer. The suggest that it can alleviate the problem of slow heat transfer rate in the local annular region and increase the average internal temperature. Furthermore, in order to compensate for the loss of thermal energy capacity of the fin structure, this work also investigated the effect of different wall thicknesses on the thermal performance of the phase change capsule. Interestingly, decreasing the wall thickness significantly increases the heat capacity. In concrete terms, the thermal energy capacity of 0.5 mm wall thickness is increased by 22.87 % compared to 2 mm. This study may provide new enlightenment for the optimization of green energy.

Improvement strategy evaluation from coupled energy-flow perspective on the GaSb thermophotovoltaic cell

Thermophotovoltaic (TPV) emerges as a novel high-efficiency generation technology, showcasing enormous potential in various sustainable energy solutions. Aiming to understand the complex conversion process between radiative, electrical and thermal energies within TPVs, a multi-physics coupled model is established. From the heat generation, temperature and carrier perspectives, the output performance is analyzed in detail. Under 1200 K black-body radiation, the energy loss distribution in the GaSb cell is analyzed meticulously, where Joule heat (40.4 %), surface recombination heat (23.1 %) and thermalization heat (20.8 %) play predominant roles. As it stands, the cell temperature rises to a maximum of 317.0 K with a cooling intensity of 300 W/(m2·K). The minimum of the average cell temperature (approximately 312.3 K) occurs at the optimized working voltage of 0.3 V. Subsequently, the electrical characteristics are illustrated. The results indicate a maximum output power underestimation of 4.6 % compared to the uncoupled isothermal case. Based on the coupled model, a quantitative analysis of the anti-reflection coating (ARC), the structural adjustment (SA) and the selective emitter (SE) is conducted. The results reveal that the ARC case exhibits the most enhancement in the output power (55.3 %) followed by the SA case, which effectively improves it by 12.2 %. Although the SE case partially decreases the output power (−9.8 %), it shows promise in promoting conversion efficiency. Integrating the above strategies, the TPV system achieves an impressive conversion efficiency of 29.38 %, representing a 76.46 % improvement compared to the prototype with the cell only.

Uncovering the evolution of ozone pollution in China: A spatiotemporal characteristics reconstruction from 1980 to 2021

Ozone pollution emerged as a significant environmental concern in China in recent years. Given the enduring impact of anthropogenic activities on the atmosphere, understanding the long-term evolutionary patterns of ozone pollution is crucial for effective pollution mitigation strategies. However, there have been limited studies to reconstruct spatiotemporal continuity ozone concentrations in China since 1980. In this research, monthly and daily MDA8 ozone concentrations from 1980 to 2021 were first estimated by reproducing the numerical relations between ozone pollution and the atmospheric environment based on a machine learning approach. The verification results from temporal, spatial, and sample-based cross-validation methods demonstrated the model performance in simulating MDA8 ozone concentration spatiotemporally, with correlation coefficients (R) ranging from 0.76 to 0.79, mean square error (RMSE) ranging from 22.72 μg·m−3 to 24.28 μg·m−3, and mean absolute error (MAE) ranging from 17.06 μg·m−3 to 18.25 μg·m−3. The evolution of ozone pollution in China can be delineated into two phases, characterized by an increasing trend since 2001, coinciding with significant rises in average annual temperature and hot weather frequency over the past four decades. The 90th percentile of ozone concentration from 2001 to 2021 increased by 1.79% compared to the period from 1980 to 2001. Notably, ozone episodes have expanded beyond summer months, partly due to global warming and frequent extreme climate events, contributing to an annual temperature increase of 0.03 °C. Despite several pollutant emission restrictions since 2013, the ozone pollution in China has persisted due to the increased emissions of VOCs. Spatially, severe ozone pollution hotspots are evident in Xinjiang province, the Jing-Jin-Ji urban agglomeration, and Northeast China, with notable increases observed in Tibet and the Guangdong-Hong Kong-Macao Greater Bay Area over the past six years. Moreover, the influence factors were identified by the average reduction of node impurity calculation. The evolution of ozone pollution was inextricably linked to solar radiation and atmospheric temperature, which played pivotal positive roles in ozone formation. Whilst, there is significant heterogeneity in the effect of meteorological conditions on ozone concentrations due to the disparity between land and oceanic climates.

Preparation and evaluation of GCD-1 lunar regolith simulant based geopolymer activated by solid sodium silicate

In this study, a new lunar regolith simulant, named "GCD-1", was formulated by combining various minerals, such as anorthite, albite, pyroxene, ilmenite, slag, and fly ash. Through X-ray fluorescence spectroscopy (XRF) and X-ray diffraction (XRD) analysis, it was verified that the main mineral composition of GCD-1 was basically the same as that of the lunar soil at the Apollo 14 landing site, in which the deviation in the main compound (i.e., SiO2 and Al2O3) was within 0.5%. Furthermore, GCD-1 based geopolymer was prepared by the one-part method, which was a mixture of solid GCD-1 precursor, solid sodium silicate (SS) activator, and water. The average daytime temperature at the lunar equator, which was calculated to be 60°C, was set as the curing temperature for the GCD-1 based geopolymer. The strength development of the GCD-1 based geopolymer was then characterized by unconfined compressive strength (UCS) for 3, 7, and 12 curing days to consider the effectiveness of the factors (solid SS to lunar regolith simulant [S/L] and water to binder ratio [W/B]). The micro-analysis tests including scanning electron microscope-energy dispersive spectrometer (SEM-EDS), mercury intrusion porosimetry (MIP), and brunner-emmet-teller (BET), were further conducted to investigate the microstructural development of the GCD-1 based geopolymer. Results showed that the increase of the W/B ratio in the GCD-1 based geopolymer tended to increase the total porosity of the sample, thereby inducing a lower UCS. At the same time, for a fixed W/B ratio, the higher S/L ratio had a certain inhibition effect on the hydration reaction, which caused the reduction in the UCS of the sample. The highest UCS of the GCD-1 based geopolymer reaching 30.54MPa, was achieved under the simulated lunar equatorial daytime temperature for 12 days with W/B and S/L ratios set at 0.25 and 0.18, respectively. Microstructure and mineralogy analyses indicated that the hydrated sodium aluminosilicate (N-A-S-H) gels contributed to reducing the sample's porosity, thereby enhancing the UCS. The relationship between the UCS and total porosity of GCD-1 based geopolymer was then derived. The results of the current study are crucial for lunar base construction with in-situ resources.

Performance optimization of adsorption hydrogen storage system via computation fluid dynamics and machine learning

Adsorption hydrogen storage paves an alternative way for reliable hydrogen storage. Here, impacts of dimensionless fin geometry configurations of the fin-tube metal hydride bed on the hydrogen storage performance are systematically investigated. Results show employing fins can strengthen the heat and mass transfer characteristics in the adsorbent bed and shorten the adsorption duration, especially at large fin numbers. Larger dimensionless fin thickness, height and width can lower the average bed temperature, which contributes to the adsorption kinetics and hydrogen fraction. At a small adsorption duration, larger dimensionless fin thickness, height and width improve the hydrogen storage amount due to obviously augmented hydrogen fraction. At a larger adsorption duration, there exist optimal dimensionless fin thickness, height and width leading to the maximum hydrogen storage amount originating from the compromise between the hydrogen fraction and adsorbent filled. Based on machine learning, the relationships between dimensionless fin geometry parameters and hydrogen storage amount have been obtained, and the optimal adsorption duration depended dimensionless fin configurations are obtained based on genetic algorithm. At a moderate adsorption duration, the optimized finned bed can significantly enhance the hydrogen storage amount. At the adsorption duration of 400s, the hydrogen storage amount is augmented by 12.8%.

The role of BRICS countries in the optimal low-carbon transition path for sustainable development

With the development of industrialization, greenhouse gas emissions caused by human activities, especially carbon dioxide emissions, continue to increase. The BRICS countries (Brazil, Russia, India, China, and South Africa) account for a significant share of global carbon emissions. This study focuses on the BRICS countries as the subject of inquiry, employing carbon emission-related data spanning the temporal range from 2000 to 2020. This study systematically assesses the interrelationships among variables using the Pearson correlation analysis and Granger causality test. Variables exhibiting pronounced correlation and causality, as discerned from the analytical outcomes, are subsequently identified and selected for further examination. Use the GCAM (Global Change Assessment Model) to simulate the Rcp-ref scenario (baseline scenario) and the Rcp2.6 scenario (assuming that the temperature will not rise by 2 degrees Celsius), and compare the optimal paths of key variables in the two scenarios, and draw the following conclusions. (1) By the end of this century, the total carbon emissions of the BRICS countries under Rcp2.6 scenario will be 6139MTC less than those under Rcp-ref scenario. (2) Compared with the Rcp-ref scenario, in the Rcp2.6 scenario, the proportion of fossil fuels such as oil, natural gas, and coal in the main energy consumption significantly reduces, while the proportion of renewable energy sources such as wind, solar, and biomass increases. It is worth noting that the proportion of nuclear is significantly rising. (3) The demand for electricity increases significantly in the Rcp2.6 scenario. This study reveals the specific directions for improving the energy structure of BRICS countries to achieve the global average temperature rise of no more than 2 degrees Celsius. It provides suggestions for the future policies of these countries' governments. In addition, BRICS countries should focus on observing changes in some factors, such as the increase in nuclear energy consumption and the increase in electricity demand. The reasons behind the changes in these factors are the direction of future research.

Micro-layered film and foam alternating structures: A novel passive daytime radiative cooling material

This study investigates the confined foaming mechanisms and passive cooling performance of Micro-/Nano-Layered (MNL) film/foam alternating structures. These structures consist of solid poly(carbonate) (PC) film layers and foamed poly(methyl methacrylate) (PMMA) layers. We examine the impact of confinement effects, layer thicknesses, and foaming conditions on cell morphology, cell nucleation, growth, and bulk expansion behavior. Samples ranging from 1 to 513 layers were foamed at 20 MPa and temperatures between 70 and 150°C. We identified three distinct cell structures—multiple, double, or single row(s) of cells—in MNL film/foam structures. We observed that cell size decreases and cell nucleation density increases with increasing layer count. The highest cell nucleation density (1.1×1013 cells/cm3) and smallest cell size (400 nm) were achieved in a 513-layer sample foamed at 70°C and 20 MPa. MNL samples primarily expand vertically, with the apparent expansion ratio ranging from 2.3 to 11 times as layers increase. Samples with double or single row(s) of cells exhibited tensile strengths (∼30 MPa) comparable to their solid counterparts and thermal conductivities (29.7 mW/m·K) comparable to air. Our samples exhibited high solar radiation reflection (93.5 %) and strong infrared emissivity (91.2 %) in the atmospheric transparent window. Mid-day passive cooling experiments showed an average temperature of 17.7°C lower under our sample than ambient conditions. Given these combined properties and the cost-effective nature of the manufacturing method, our samples are readily applicable for building applications, offering significant energy savings and contributing to the mitigation of global warming.

Integrated machine learning reveals aquatic biological integrity patterns in semi-arid watersheds

Semi-arid regions present unique challenges for maintaining aquatic biological integrity due to their complex evolutionary mechanisms. Uncovering the spatial patterns of aquatic biological integrity in these areas is a challenging research task, especially under the compound environmental stress. Our goal is to address this issue with a scientifically rigorous approach. This study aims to explore the spatial analysis and diagnosis method of aquatic biological based on the combination of machine learning and statistical analysis, so as to reveal the spatial differentiation patterns and causes of changes of aquatic biological integrity in semi-arid regions. To this end, we have introduced an innovative approach that combines XGBoost-SHAP and Fuzzy C-means clustering (FCM), we successfully identified and diagnosed the spatial variations of aquatic biological integrity in the Wei River Basin (WRB). The study reveals significant spatial variations in species number, diversity, and aquatic biological integrity of phytoplankton, serving as a testament to the multifaceted responses of biological communities under the intricate tapestry of environmental gradients. Delving into the depths of the XGBoost-SHAP algorithm, we discerned that Annual average Temperature (AT) stands as the pivotal driver steering the spatial divergence of the Phytoplankton Integrity Index (P-IBI), casting a positive influence on P-IBI when AT is below 11.8 °C. The intricate interactions between hydrological variables (VF and RW) and AT, as well as between water quality parameters (WT, NO3–N, TP, COD) and AT, collectively sculpt the spatial distribution of P-IBI. The fusion of XGBoost-SHAP with FCM unveils pronounced north-south gradient disparities in aquatic biological integrity across the watershed, segmenting the region into four distinct zones. This establishes scientific boundary conditions for the conservation strategies and management practices of aquatic ecosystems in the region, and its flexibility is applicable to the analysis of spatial heterogeneity in other complex environmental contexts.

Juvenile survival of little owls decreases with snow cover.

Global environmental changes are associated with warmer average temperatures and more extreme weather events, potentially affecting wildlife population dynamics by altering demographic processes. Extreme weather events can reduce food resources and survival in all seasons of the year. Estimates of season-specific survival probabilities are therefore crucial to understand the moderating effect of extreme events on annual mortality. Here, we analysed survival probabilities of 307 radio-tracked juvenile little owls (Athene noctua) over two-week periods from fledging to their first breeding attempt in the following spring to assess the contribution of extreme weather events. Survival probabilities were typically lowest during the first weeks after fledging in summer but were moderated by seasonal extremes in winter. The duration of snow cover in winter had a strong negative effect on survival probability, while being food supplemented during the nestling stage increased survival during the first weeks after fledging in summer and ultimately led to a larger proportion of birds surviving the first year. Overall annual survival probability over the first year varied by 34.3% between 0.117 (95% credible interval 0.052-0.223) and 0.178 (0.097-0.293) depending on the severity of the winter, and was as high as 0.233 (0.127-0.373) for food-supplemented fledglings. In years with mild winters, the season with the lowest survival was the summer post-fledging period (0.508; 0.428-0.594), but in years with extensive snow cover the winter was the season with the lowest survival (0.481; 0.337-0.626). We therefore show that extreme weather events occurring in a particular season reduced the proportion of first-year survivors. Increasing extreme weather events can moderate seasonal survival probability through altering food supply of juvenile little owls either during the nestling period or in winter, with similarly large effects on annual survival and the viability of populations.

A strategy to assess the use-phase carbon footprint from energy losses in electric vehicle battery

The electric vehicles are not completely emission-free. The vehicles consume power and the power generation processes involve carbon emissions, resulting in indirect vehicle usage carbon emissions. A use-phase carbon emissions assessment can help electric vehicle designers and manufacturers analyze the onboard carbon footprint and mitigate vehicle-related carbon emissions through energy consumption optimization. In this article, we focus on the use-phase carbon footprint based on the energy losses in electric vehicle battery packs. A battery pack energy loss model is established to examine the carbon footprint of four main subsystems of the battery pack, including the energy storage system, thermal management system, and battery junction box. We use the proposed method to evaluate the battery pack use-phase carbon emissions in four different cities from four main continents. The results show that the highest emissions appear in Tokyo (436.2 kgCO2) due to the relatively high greenhouse gas factor on the grid, the London has the lowest 207.5 kgCO2 emissions due to the massive adoption of sustainable energy during power generation. With a similar high greenhouse gas factor, but Sydney shows lower emissions (347.5 kgCO2) compared to Tokyo, which illustrates the closer the annual average temperature to the battery suitable operation range, the lower energy loss happens inside the battery pack due to the low thermal management load and resistance energy loss in the cells. This electric vehicle has the highest energy loss rate (20.8%) in New York, 343.6 kgCO2 emissions, and the highest thermal management system energy losses show the high seasonal temperature difference causing the high thermal management load to maintain the battery temperature. The proposed method can be used for different battery pack configurations and vehicle uses, providing researchers with a robust and versatile use-phase carbon emissions assessment strategy.