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The thermochemical water-splitting method is a promising technology for efficiently converting renewable thermal energy sources into green hydrogen. This technique is primarily based on recirculating an active material, capable of experiencing multiple reduction-oxidation (redox) steps through an integrated cycle to convert water into separate streams of hydrogen and oxygen. The thermochemical cycles are divided into two main categories according to their operating temperatures, namely low-temperature cycles (<1100 °C) and high-temperature cycles (<1100 °C). The copper chlorine cycle offers relatively higher efficiency and lower costs for hydrogen production among the low-temperature processes. In contrast, the zinc oxide and ferrite cycles show great potential for developing large-scale high-temperature cycles. Although, several challenges, such as energy storage capacity, durability, cost-effectiveness, etc., should be addressed before scaling up these technologies into commercial plants for hydrogen production. This review critically examines various aspects of the most promising thermochemical water-splitting cycles, with a particular focus on their capabilities to produce green hydrogen with high performance, redox pairs stability, and the technology maturity and readiness for commercial use.

The century-long search for the precise mechanisms responsible for urban heat islands continues, while urban warming worsens in many megacities. Most studies have focused on mean temperature, daily and annual temperature ranges and urban heat island intensity. We hypothesize that an analysis of the changes in the characteristics of the complete daily and annual temperature cycles, including not only the mean temperature and temperature ranges (amplitudes) but also the maximum and minimum temperatures and the phases, can provide more information on urban warming phenomena. Through a detailed analysis of long-term observations in Hong Kong, we found that the difference in the daily cycle between urban and rural stations is very distinct, whereas the annual cycles are much more similar, suggesting that the urban environment has a greater effect on the daily cycle than on the annual cycle. The daily phase has shifted a total of 1.77 h later over the last 130 years (1.36 h per century) in the urban area of Hong Kong according to the Hong Kong Observatory (HKO) data. The annual phase change at HKO reflects the globally observed phenomenon that the annual phase advances or seasons onset earlier.

The DN1 p clock neurons of Drosophila melanogaster continuously report temperature changes into the circadian neural network, to control the timing of sleep and activity. Small temperature changes control sleep Circadian rhythms and sleep cycles are regulated by both light and temperature, but central biological clocks are thought to be robust to small transient changes in environmental temperature. Orie Shafer and colleagues reveal that the DN1p clocks of Drosophila monitor minute-to-minute temperature changes in the environment, as reported by several peripheral organs, and control sleep timing accordingly. Although light and temperature are both markers of the differences between day and night, they are processed in fundamentally different ways by the neuronal networks of the biological clock. Circadian clocks coordinate behaviour, physiology and metabolism with Earth’s diurnal cycle 1 , 2 . These clocks entrain to both light and temperature cycles 3 , and daily environmental temperature oscillations probably contribute to human sleep patterns 4 . However, the neural mechanisms through which circadian clocks monitor environmental temperature and modulate behaviour remain poorly understood. Here we elucidate how the circadian clock neuron network of Drosophila melanogaster processes changes in environmental temperature. In vivo calcium-imaging techniques demonstrate that the posterior dorsal neurons 1 (DN1 p s), which are a discrete subset of sleep-promoting clock neurons 5 , constantly monitor modest changes in environmental temperature. We find that these neurons are acutely inhibited by heating and excited by cooling; this is an unexpected result when considering the strong correlation between temperature and light, and the fact that light excites clock neurons 6 . We demonstrate that the DN1 p s rely on peripheral thermoreceptors located in the chordotonal organs 7 , 8 and the aristae 9 . We also show that the DN1 p s and their thermosensory inputs are required for the normal timing of sleep in the presence of naturalistic temperature cycles. These results identify the DN1 p s as a major gateway for temperature sensation into the circadian neural network, which continuously integrates temperature changes to coordinate the timing of sleep and activity.

The soils surrounding energy geo-structures are exposed to high temperatures and temperature cycles. Changes in the engineering properties of soils should be investigated under thermal effects and soils that are highly durable against temperature changes are needed for thermo-active geo-structures. Generally, bentonite or sand–bentonite mixtures (SBMs) are preferred as natural barrier soil materials. Hence, the engineering properties of these natural soil materials against high temperatures should be improved. Boron, which has high thermal resistivity, reduces the heat expansion of materials, when added to soils may increase the durability of buffer materials at high temperatures. In the present study, the effects of tincal and ulexite additives were observed on the shear strength behavior of SBMs at 80 °C and room temperature. The general results showed that with the contribution of boron, the shear strength of the SBMs increased with increasing temperature. The effect was more pronounced for 20% SBMs at high temperature. Tincal and ulexite can be used to increase the shear strength of SBMs at high temperatures.

Atmospheric and surface urban heat islands (UHI) originate from common energetic processes, but the status of scientific knowledge on their time evolution is highly disparate. The diurnal cycles of atmospheric UHI are well known based on years of continuous measurements in cities; the cycles of surface UHI, however, cannot be measured continuously or in situ. In this article, we aim to reconcile these differences. We begin with a synthesis of previous work on the diurnal evolution of surface UHI, which leads to a novel but historically minded approach to the research problem. The approach involves a combination of microscale and mesoscale urban climate models, each of which is forced with universally described urban and rural surface parameters and atmospheric profiles. With these models, we produce theoretical time‐temperature curves for the surface UHI that are comparable to the classic curves of atmospheric UHI. This work prompts a critical look at the use of satellite thermal imagery to assess heat islands and heat risks in cities. To that end, we recommend new and more functional definitions of surface temperature. Conceptually, these represent “incomplete” temperatures defined by specific facets of the urban environment. Plain Language Summary Urban heat islands (UHI) refer to the added warmth in cities due to the abundance of buildings, vehicles, and paved ground. However, very little is known about the hourly and daily changes in the surface temperatures of the city. This is partly due to the technological difficulties of sampling surface temperatures in urban environments, and to the myriad of surface types in cities. In this article, we aim to overcome this difficulty by using a combination of urban climate models, which can replicate daily temperature cycles for the surface UHI. With these data, we recommend new indicators of surface temperature that more accurately describe the heat risks and building energy demands in cities. Key Points Three numerical climate models are used to characterize the diurnal evolution of the surface urban heat island Diurnal evolution of surface heat islands varies with regional climate, urban morphology, rural land cover, soil moisture, and wind speed Satellite‐based observations of surface heat islands are likely to overestimate (underestimate) actual daytime (nighttime) impacts

ICEEMDAN, a variant of Empirical Mode Decomposition (EMD), is used to extract temperature cycles with periods from half a year to multiple decades from the HadCRUT5 global temperature anomaly data. The residual indicates an overall warming trend. The analysis is repeated for the Southern and Northern Hemispheres as well as the Tropics, defined as areas lying at or below 30 degrees of latitude. Multiannual cycles explain the apparently anomalous pause in global warming starting around 2000. The previously identified multidecadal cycle is found to be the most energetic and to account for recent global warming acceleration, beginning around 1993. This cycle’s amplitude is found to be more variable than by previous work. Moreover, this variability varies by latitude. Sea ice loss acceleration is proposed as an explanation for global warming acceleration.

A growing body of research indicates that rock slope failures, particularly from exfoliating cliffs, are promoted by rock deformations induced by daily temperature cycles. Although previous research has described how these deformations occur, full three-dimensional monitoring of both the deformations and the associated temperature changes has not yet been performed. Here we use integrated terrestrial laser scanning (TLS) and infrared thermography (IRT) techniques to monitor daily deformations of two granitic exfoliating cliffs in Yosemite National Park (CA, USA). At one cliff, we employed TLS and IRT in conjunction with in situ instrumentation to confirm previously documented behavior of an exfoliated rock sheet, which experiences daily closing and opening of the exfoliation fracture during rock cooling and heating, respectively, with a few hours delay from the minimum and maximum temperatures. The most deformed portion of the sheet coincides with the area where both the fracture aperture and the temperature variations are greatest. With the general deformation and temperature relations established, we then employed IRT at a second cliff, where we remotely detected and identified 11 exfoliation sheets that displayed those general thermal relations. TLS measurements then subsequently confirmed the deformation patterns of these sheets showing that sheets with larger apertures are more likely to display larger thermal-related deformations. Our high-frequency monitoring shows how coupled TLS and IRT allows for remote detection of thermally induced deformations and, importantly, how IRT could potentially be used on its own to identify partially detached exfoliation sheets capable of large-scale deformation. These results offer a new and efficient approach for investigating potential rockfall sources on exfoliating cliffs.

Soils surrounding energy geo-structures are exposed to high temperature and temperature cycles. Such thermal changes may affect the engineering behavior of soils negatively. It is very important that the soils around energy geo-structures maintain its engineering parameters unchanged for a long time under thermal changes. Understanding how barrier is affected when exposed to high temperature is crucial for the long-term performance of the barrier. The aim of study is to keep the soils around the energy geo-structures such as nuclear waste disposal facilities, maintain their engineering characters without failure for a long time under high temperatures and thermal changes. In the present study, sand-bentonite mixtures, which are widely used as a barrier material, and colemanite, one of the boron minerals known for its thermal strength, were used. An experimental study investigated (1) the effect of high temperature (80 °C) on the shear strength (2) the effect of the thermal cycle (20-80-20 °C) on compression of additive free sand-bentonite mixtures and colemanite added sand-bentonite mixtures. The laboratory tests were performed in a temperature-controlled modified shear box and oedometer cell. Based on the results obtained, colemanite additive contributed to the improvement of shear strength of sand-bentonite mixtures at high temperature. However, colemanite addition increased the compression amount and thermal cycling effect reduced the compression index.

We investigated the residual rate and mass loss rate of litter, as well as the carbon release dynamics of litter and soil across seasons, to better understand the effects of seasonal fluctuations on carbon dynamics in mixed coniferous forests. The study was carried out in natural mixed coniferous forests in the Xiaoxinganling region of Heilongjiang Province, China, and the number of temperature cycles in the unfrozen season, freeze–thaw season, frozen season, and thaw season was controlled. The goal of the study was to examine how the carbon release dynamics of litter and soil respond to the freeze–thaw process and whether there are differences in carbon release dynamics under different seasons. Repeated-measures analysis of variance was used to analyze the residual mass rate and mass loss rate of litter, litter organic carbon and soil organic carbon during the unfrozen season, freeze-thaw season, frozen season, and thaw season. Litter decomposition was highest in the unfrozen season (15.9%~20.3%), and litter and soil carbon were sequestered throughout this process. Temperature swings above and below 0°C during the freeze–thaw season cause the litter to physically fragment and hasten its decomposition. Decomposition of litter was still feasible during the frozen season, and it was at its lowest during the thaw season (7.2%~7.8%), when its organic carbon was transported to the soil. Carbon migrates from undecomposed litter to semi-decomposed litter and then to soil. The carbon in the environment is fixed in the litter (11.3%~18.2%) and soil (34.4%~36.7%) in the unfrozen season, the carbon-fixing ability of the undecomposed litter in the freeze-thaw season is better, and the carbon in the semi-decomposed litter is mostly transferred to the soil; the carbon-fixing ability of the litter in the frozen season is worse (-3.9%~ -4.3%), and the organic carbon in the litter is gradually transferred to the soil. The carbon-fixing ability of the undecomposed litter in the thaw season is stronger, and the organic carbon in the semi-decomposed litter is mostly transferred to the soil. Both litter and soil can store carbon; however, from the unfrozen season until the thaw season, carbon is transported from undecomposed litter to semi-decomposed litter and to the soil over time.

The effects of variations in time of day of daily temperature extrema on regression-based statistical downscaling of daily temperature extrema were examined. These effects were analyzed by evaluating the performance of a regression-based downscaling model with multiple approaches to the incorporation of the relevant temperature data. The differing approaches included which predictor variables were selected for inclusion in the model, as well as variations in model methodology. Three different versions of the downscaling model were evaluated: (i) standard multiple linear regression, (ii) a weather classification scheme combined with multiple linear regression, and (iii) a weather classification scheme combined with multiple linear regression using dynamic time-step predictors. Bias and accuracy were measured on days with atypical and typical times of temperature extrema. The performance of regression models had the potential to be greatly degraded by days with atypical times of temperature extrema. The degree to which these atypical days were affected was dependent on which predictors were included in the regression models, with the temperature extrema derived from reanalysis data playing the most important role. Implementation of the weather classification scheme also improved downscaling performances for atypical days in a number of situations. For typical days, the improvements to RMSE values were smaller and were only present under certain predictor combinations.