Environmental Climate Research Articles

Multi-field and multi-scale dynamic numerical modeling of supercritical CO2 and fly ash mineralization

Fly ash-CO2 mineralization technology can effectively control gas–solid waste emissions and improve the climate environment. However, rationally describing the evolution mechanism of the fly ash-supercritical CO2 mineralization reaction and accurately predicting the efficiency of the mineralization reaction are of great significance for improving and evaluating the supercritical CO2 mineralization sequestration capacity. Fly ash micro- and nanopore multi-scale effects are the key to influencing the supercritical CO2 seepage-mineralization reaction mechanism. None of the current theoretical models consider the pore multi-scale effects, thus the validity and accuracy of predicting and describing the evolutionary mechanism of supercritical CO2 mineralization rates and efficiencies are questionable. To address this scientific issue, a multi-scale continuous pore structure theoretical model was established based on the structural characteristics of fly ash micro- and nanopores. Additionally, a new model of supercritical CO2 multi-field and multi-scale dynamic mineralization theory was developed by considering parameters such as temperature, pressure, and humidity. The accuracy of the model was verified through the mineralization experiments. The new model effectively describes the dynamic evolution mechanism of supercritical CO2 mineralized fly ash. The effects of parameters such as temperature, pressure, water vapor diffusion coefficient, supercritical CO2 permeability, and pore multi-scale effect on the efficiency and mineralization rate were investigated through numerical simulation. The results showed the following: The mineralization efficiency exhibited a parabolic increase with temperature, with 72℃ being the turning point for the growth rate of mineralization efficiency, and 82℃ being the optimal effective temperature to promote the mineralization efficiency of supercritical CO2. A 3.5-fold increase in supercritical CO2 pressure changes the mineralization efficiency by a maximum of only 0.0493 %. Increasing the water vapor diffusion coefficient by 5 orders of magnitude changes the mineralization efficiency by only 8.3 %. The pore attenuation coefficient increases by 3 orders of magnitude, and the supercritical CO2 mineralization efficiency changes by a factor of 2.27. A model that does not account for pore multi-scale effects overestimates the fly ash- supercritical CO2 mineralization efficiency by a factor of 2.47 at a permeability of 3 × 10-10 m2. Therefore, neglecting the pore continuum multi-scale effect can lead to a serious overestimation of the mineralization efficiency of supercritical CO2.

Resilient city construction efficiency and its influencing factors in China's Chengdu-Chongqing Economic Circle: Considering both construction input and resilience level of the city

The growing expansion of urban centers combined with a deteriorating climatic environment raises the likelihood and severity of urban disasters. Thus, there is an urgent need to accelerate the resilient city construction. Here, we use efficiency theory to structure an assessment indicator system of the resilient city construction efficiency to examine the actual correlation of urban resilience enhancement and urban resource consumption. Specifically, 16 key cities in the Chengdu-Chongqing Economic Circle (CCEC) are investigated using the super-efficient SBM and GTWR models. The findings reveal that the resilient city construction efficiency varies greatly among cities in the region, but most cities have relatively low resilient city construction efficiency, showing high resource consumption and low resilience levels. Also, the lower efficiency of regional resilient city construction is mainly due to the serious ineffectiveness of technical and resource inputs, insufficient outputs of ecological resilience and engineering resilience, and is also greatly influenced by factors such as the economic level and the technological innovation level. Upon this basis, we suggest the development strategies for resilient city construction in CCEC. This study broadens the perspective and scope of urban resilience research, and also provides a realistic reference for accelerating the construction of resilient cities.

A self-satisfying cooling system based on cold energy storage for the locomotive in a high geothermal tunnel

Effective thermal management of locomotive systems is crucial for ensuring the safe operation of trains through high geothermal tunnels. By taking advantage of the frequent alternation of high-temperature tunnels and cold climate environment, a self-satisfying cooling system based on cold energy storage is proposed, in which a phase change heat exchanger between air and phase change material (succinic acid with 20 wt% expanded graphite) is developed to store cold energy outside tunnels and improve air-cooling efficiency inside tunnels. Numerical models are established to examine the thermal environment in a typical tunnel and the effectiveness of the proposed cooling system. The results indicate that because of the heat exhausted from the train and the thermal dissipation from the surrounding hot rock, the air temperature in the tunnel can rise above 50 °C. The proposed cooling system can release the cold energy from phase change material to keep the air outlet temperature below 40 °C, increasing the energy efficiency and reliability of locomotive operation. By examining the effects of locomotive operating conditions and orthogonal analysis of multi-factors, the heat exchanger structure and other operating conditions are recommended for the self-satisfying cooling system. Finally, the cooling system’s effectiveness is confirmed for the full-line operation of the locomotive along the Ya’an-Nyingchi section of the Sichuan-Tibet Railway in both summer and winter climatic conditions. This study is significant because it provides a novel design scheme for locomotive’s thermal management in high geothermal tunnels and other similar engineering conditions with natural cold sources.

Twenty-five emerging questions when detecting, understanding, and predicting future fish distributions in a changing climate.

The 2023 Annual Symposium of the Fisheries Society of the British Isles hosted opportunities for researchers, scientists, and policy makers to reflect on the state of art of predicting fish distributions and consider the implications to the marine and aquatic environments of a changing climate. The outcome of one special interest group at the Symposium was a collection of questions, organized under five themes, which begin to capture the state of the field and identify priorities for research and management over the coming years. The five themes were Physiology, Mechanisms, Detect and Measure, Manage, and Wider Ecosystems. The questions, 25 of them, addressed concepts which remain poorly understood, are data deficient, and/or are likely to be impacted in measurable or profound ways by climate change. Moving from the first to the last theme, the questions expanded in the scope of their considerations, from specific processes within the individual to ecosystem-wide impacts, but no one question is bigger than any other: each is important in detecting, understanding, and predicting fish distributions, and each will be impacted by an aspect of climate change. In this way, our questions, particularly those concerning unknown mechanisms and data deficiencies, aimed to offer a guide to other researchers, managers, and policy makers in the prioritization of future work as a changing climate is expected to have complex and disperse impacts on fish populations and distributions that will require a coordinated effort to address.

Temperature-Dependent Post-Cyclic Mechanical Characteristics of Interfaces between Geogrid and Marine Reef Sand: Experimental Research and Machine Learning Modeling

The mechanical response of the marine reef sand–geogrid (RG) interface can be influenced by a high-temperature climate, grain size, and variable stress environments. These factors are critical to the effectiveness of geogrid reinforcement in reef sand engineering. However, there are few studies on the influences of grain size, temperature, and stress history on the mechanical characteristics of RG interfaces, with most studies centering on the influence of single factors on the mechanical characteristics of RG interfaces. In this paper, based on self-developed temperature-controlled large interface shear equipment, a series of before/post-cyclic shear tests were carried out on RG interfaces in the temperature range of 5–80 °C. The impact of different reef sand grain sizes on the RG interface was explored (S1: 1–2 mm; S2: 2–4 mm). It was shown that temperature and grain size had significant influences on the mechanical characteristics of the RS interface. Compared with the S1 RG interfaces, the S2 RG interfaces had higher sensitivity to temperature changes with respect to the before/post-cyclic maximum shear strength. Moreover, in comparison to the before-cyclic shear strength, the post-cyclic maximum shear strength is more responsive to temperature changes. The before/post-cyclic maximum shear strength of the S2 RG interfaces was greater than the maximum shear strength of the S1 RG interfaces as the temperature changed. Based on the results of physical tests, a machine learning model containing 450 datasets was constructed, which can accurately predict the shear strength of the RG interface.

Exploring the Spatiotemporal Evolution Patterns and Determinants of Construction Land in Mianning County on the Eastern Edge of the Qinghai–Tibet Plateau

Studying the spatiotemporal evolution and driving forces behind construction land amidst the intricate ecological and geological setting on the eastern edge of the Qinghai–Tibet Plateau offers invaluable insights for local sustainable development in a landscape transition zone and ecologically fragile area. Using construction land data from four phases, spanning 1990 to 2020, in Mianning County, this study employs methodologies like the Landscape Expansion Index (LEI) and land use transfer matrix to delineate the spatiotemporal evolution characteristics of construction land. A comprehensive set of 12 influencing factors across five categories—geomorphology, geological activity, climate, river and vegetation environment, and social economy—were examined. The Geographically Weighted Regression (GWR) model was then employed to decipher the spatial distribution pattern of construction land in 1990 and 2020, shedding light on the driving mechanisms behind its changes over the three decades. The research reveals distinct patterns of construction land distribution and evolution in Mianning County, shaped by the ecological and geological landscape. Notably, the Anning River wide valley exhibits a concentrated and contiguous development mode, while the Yalong River deep valley showcases a decentralized development pattern, and the Dadu River basin manifests an aggregation development mode centered around high mountain lakes. Over the study period, all three river basins witnessed varying degrees of construction land expansion, transitioning from quantitative expansion to qualitative enhancement. Edge expansion predominantly characterizes the expansion mode, complemented by leapfrog and infilling modes, accompanied by conversions from cropland and forest land to construction land. An analysis of the spatial pattern and drivers of construction land change highlights human-induced factors dominating the Anning River Basin, contrasting with natural factors prevailing in the Yalong River Basin and the Dadu River Basin. Future efforts should prioritize climate change considerations and environmental capacity, aiming for an ecologically resilient spatial pattern of construction land.

Coupled Climate–Environment–Society–Ecosystem Resilience Coordination Analytical Study—A Case Study of Zhejiang Province

The aim of this paper is to evaluate the coupled coordination degree of climate, environmental, socio-economic, and ecosystem resilience in Zhejiang Province from 2010 to 2022 and to propose optimization strategies. With the increasing impact of global climate change, the need to explore the construction of resilient cities and sustainable development models has become increasingly pressing. Assessing the coupled coordination among climate, environment, socio-economic, and ecosystem resilience aids in suggesting more precise and effective social and ecological recovery strategies in the context of climate change. Zhejiang Province, serving as a model for China’s urbanization development, demonstrates a balance between the natural environment, economic growth, and social development but still suffers from ecological and environmental pollution problems. In this study, an evaluation system was constructed utilizing the entropy weight method (EWM), and the coupled coordination among climate, environmental, socio-economic, and ecosystem resilience in Zhejiang Province was empirically analyzed over the period from 2010 to 2022. The results show that (1) the climatic-environmental, socio-economic, and ecological subsystems of cities in Zhejiang Province generally show an upward trend, despite fluctuations over different periods. (2) The climatic-environmental-social-ecological system resilience of the cities in Zhejiang Province increased as a whole, and six cities (Hangzhou: 0.805, Quzhou: 0.811, Huzhou: 0.827, Taizhou: 0.829, Wenzhou: 0.856, and Jinhua: 0.857) reached the “well-coordinated” level by 2022; however, the coupling coordination of Jiaxing City and Lishui City decreased from good to intermediate coordination. (3) The coupled coordination degree of climatic-environmental-social-ecological system resilience generally stagnated in each city during 2020–2022. Thus, the climate change adaptation strategy proposed in this study aims to enhance urban adaptive capacity to climate change impacts by controlling pollutant emissions, restoring ecosystems, optimizing industrial structures, and designing urban green spaces.

Fostering Student Success: The Synergistic Effects of Family Climate and School Environment

This paper delves into the notable, interconnected tasks of family climate and school environment in stimulating student success. It also traverses how these two important influences work synergistically – meaning their combined effect is more than the total of their individual parts – to determine student academic achievement, emotional well-being, and overall development. The paper analyzes the features of positive family climates and supportive school environments, pointing up factors such as communication, parental involvement, clear expectations, and a sense of belonging. It then examines the research on the synergistic effects of these factors, demonstrating how a healthy home environment can amplify the benefits of a positive school experience, and vice versa.

Multi-site solar irradiance prediction based on hybrid spatiotemporal graph neural network

Constructing accurate spatiotemporal correlations is a challenging task in joint prediction of multiple photovoltaic sites. Some advanced algorithms for incorporating other surrounding site information have been proposed, such as graph neural network-based methods, which are usually based on static or dynamic graphs to build spatial dependencies between sites. However, the possibility of the simultaneous existence of multiple spatial dependencies is not considered. This paper establishes a spatiotemporal prediction model based on hybrid spatiotemporal graph neural network. In this model, we apply adaptive hybrid graph learning to learn composite spatial correlations among multiple sites. A temporal convolution module with multi-subsequence temporal data input is used to extract local semantic information to better predict future nonlinear temporal dependencies. A spatiotemporal adaptive fusion module is added to address the issue of integrating diverse spatiotemporal trends among multiple sites. To assess the model's predictive performance, nine solar radiation observation stations were selected in two different climatic environments. The average root mean square error (RMSE) of the constructed model was 38.51 and 49.90 W/m2, with average mean absolute error (MAE) of 14.72 and 23.06 W/m2, respectively. Single-site and multi-site prediction models were selected as baseline models. Compared with the baseline models, the RMSE and MAE reduce by 3.1%–20.8% and 8.9%–32.8%, respectively, across all sites. The proposed model demonstrates the effectiveness of improving accuracy in forecasting solar irradiance through multi-site predictions.

Towards long-term, high-accuracy, and continuous satellite total and fine-mode aerosol records: Enhanced Land General Aerosol (e-LaGA) retrieval algorithm for VIIRS

Long-term, accurate, stable, and continuous aerosol records from space are a major requirement for climate and atmospheric environment research. Due to the limited period span of the single satellite mission, solving the problem requires the combination of multiple satellite missions. In this study, a novel aerosol retrieval algorithm, named enhanced Land General Aerosol Retrieval (e-LaGA), for Visible/Infrared Imager Radiometer Suite (VIIRS) was developed to continue Moderate-resolution Imaging Spectro-radiometer (MODIS) aerosol retrieval. e-LaGA utilizes a Surface Reflectance (SR) relationship model map to more accurately estimate the SR parameter, optimizes the priori aerosol-type map, and improves the multi-band retrieval strategy using the residual-interpolation approach. Additionally, e-LaGA expands the retrieval ability of the traditional Dark Target (DT) algorithm over bright surfaces, and can more accurately retrieve Aerosol Optical Depth (AOD), Fine-mode AOD (AODF), and Fraction (FMF). The validation using global 533 AERONET sites shows that the volume of matchups of AOD (AODF) is approximately 80000, the correlation coefficient (R) is 0.902 (0.879) and the fraction of meeting the expected error envelope (±0.05 ± 0.15τ) is 0.806 (0.804). The inter-comparison indicates that the accuracy of e-LaGA AOD retrievals is comparable to seven commonly used AOD products. The validation performance and spatial distribution pattern of e-LaGA AODF and FMF are in good agreement with the POLDER (Polarization and Directionality of the Earth's Reflectances) products. e-LaGA is also applied to MODIS sensors. The VIIRS e-LaGA AOD, AODF, and FMF retrievals have high consistency with MODIS e-LaGA. Their average bias of AOD is 0.006, which is smaller than 0.024 for the Deep Blue and 0.011 for the DT. These preliminary results demonstrate the robustness of the e-LaGA algorithm and its potential for establishing a long-term climate record of total and fine-mode aerosol by combining multiple satellite missions, which is expected to reduce the uncertainty of climate change research.

From nature to buildings: a biomimetic approach as an alternative against structures’ humidity issues in Jijel – Algeria

Purpose. This study aims to explore the plants’ potential to adjust to humid climates and understand their acclimation processes to inspire building designs and develop moisture-resistant building materials. It’s based on the top-down biomimetic approach and proposes a method for applying biological processes to architectural concepts, referring to the anatomical diagnoses of moisture-resistant plants. Results. The study revealed that mimicking the hierarchical structuring observed in leaf venation patterns significantly improved the mechanical strength and flexibility of the biomimetic materials. The results indicated that plants had evolved several morphological and physiological adaptations and validated the importance of considering both the cuticle and stomata as essential adaptive factors in developing a biomimetic process. Plant adaptation mechanisms led to a focus on porosity, external textures, hydrophobic additives, and multilayer structures of building materials to produce compositions suitable for humid climates inspired by these principles. Scientific novelty. This research contributes to our understanding of how plants adapt to high humidity levels and underlines the importance of adopting the principles developed by biological systems to survive and cope with changing conditions. Practical value. This study opens insights for more resilient bio-inspired architecture that responds adaptively to humid climatic environments and highlights the significance of creating suitable building materials for different climates and those adapted for climate change.

Inversion and Analysis of Global Ocean Chlorophyll-a Concentration Based on Temperature Zoning

In recent years, the frequent occurrence of eutrophication problems in water bodies has been caused by changes in the climate environment and overexploitation of natural resources by humans. Chlorophyll-a, as a key indicator for water body assessment, plays an important role in eutrophication research and has a profound impact on the global biogeochemical cycle of the climate process. Studies have shown that temperature can directly or indirectly affect the concentration of chlorophyll-a by influencing the growth of algae and water quality indicators in water bodies. Considering the temperature factor in the inversion of chlorophyll-a concentration is a novel research approach. Based on the influence of temperature on chlorophyll-a concentration, we propose the idea of inverting global ocean chlorophyll-a concentration based on temperature zoning. Using monthly average remote sensing reflectance data from VIIRS (Visible and Infrared Imaging Radiometer Suite), combined with the results of temperature zoning, the OC3V(SST) model was constructed to invert the monthly average chlorophyll-a concentration in the global ocean in October 2018. The OC3V(SST) model has been validated by applying it to the remaining 11 months of January, April, July, and October in 2017, 2018, and 2019, as well as the entire 31-day dataset of October 2018. The results indicate that temperature zonation can significantly improve the inversion accuracy of chlorophyll-a and further explore the spatial distribution patterns of global chlorophyll-a concentrations across various temperature ranges based on monthly averages from the global ocean. Additionally, the study investigates the continuity issues of various models and the correlation between temperature and chlorophyll-a.

Cosmogenic radionuclide Beryllium-7 and Beryllium-10 characteristics and influencing factors in different natural climate regions, China

The cosmogenic radionuclide 7Be (T1/2: 53.29 days) and 10Be (T1/2: 1.39 My), as unique tracers, play an excellent indicative role in atmospheric environmental changes and Earth surface processes. Currently, their different characteristics and influencing factors in various natural climate environments are still vague. Here, we used a state-of-the-art accelerator mass spectrometry to synchronously measure the ultra-trace 7Be and 10Be in aerosols, obtaining the spatial and temporal variability of daily-resolution atmospheric 7Be and 10Be in different natural climate regions (n = 11) of China. The survey results show that the 10Be and 7Be concentrations in the central/southern regions of China (22–38°N, 85–119°E) in 2020/21 are (0.5–18.7)·104 and (0.4–6.1)·104 atoms·m−3, respectively, with 10Be/7Be ratios of 0.7–3.3. Except for the Tibetan Plateau, there are differences in the concentration thresholds of 10Be and 7Be in various regions, especially in 10Be concentration. These 10Be/7Be thresholds are consistent in areas with an altitude range of 4–3420 m a.s.l and reach their highest values throughout the spring of the year. The analysis results indicate that both 7Be and 10Be are influenced by local meteorological conditions such as rainfall and boundary layer disturbances, while also exhibiting different distribution states. This distribution states is due to the re-suspended soil dust 10Be interference caused by soil wind erosion to varying degrees in different regions, with an average contribution to aerosol 10Be of 5.0 ± 2.6 %–24.2 % ± 13.3 %, and is controlled by local annual rainfall (r = 0.8, p < 0.01). Furthermore, unlike the characteristics of 10Be and 7Be concentrations influenced by local meteorological conditions, the daily variation of corrected 10Be/7Be exhibits independence from meteorological processes other than stratosphere troposphere transport, and its significant seasonal oscillations indicate changes in atmospheric circulation in the East Asian monsoon region.

Effects of Nitrogen Application at Different Levels by a Sprinkler Fertigation System on Crop Growth and Nitrogen-Use Efficiency of Winter Wheat in the North China Plain.

Nitrogen (N) is an essential macronutrient for crop growth; therefore, N deficit can greatly limit crop growth and production. In the North China Plain (NCP), winter wheat (Triticum aestivum L.) is one of the main food crops, and its yield has increased from approximately 4000 kg ha-1 to 6000 kg ha-1 in the last two decades. Determining the proper N application rates at different growth stages and in all seasons is very important for the sustainable and high production of wheat in the NCP. A field experiment with five N application rates (250, 200, 150, 100, and 40 kgN·ha-1, designated as N250, N200, N150, N100, and N40, respectively) was conducted during the 2017-2018 and 2018-2019 winter wheat seasons to investigate the effects of the N application rate on water- and fertilizer-utilization efficiency and on the crop growth and yield of winter wheat under sprinkler fertigation conditions. The results showed that in the N application range of 40-200 kg ha-1, crop yield and water- and fertilizer-use efficiencies increased as the N application rate increased; however, further increases in the N application rate (from N200 to N250) did not have additional benefits. The N uptake after regreening of winter wheat linearly increased with crop growth. Considering the wheat yield and N-use efficiency, the recommended optimal N application rate was 200 kg ha-1, and the best topdressing strategy was equal amounts of N applied at the regreening, jointing, and grain-filling stages. The results of this study will be useful for optimizing field N management to achieve high wheat yield production in the NCP and in regions with similar climatic and soil environment conditions.

Geochemistry of Pelites at Chengmen Area: Implications for Sediments Resource and Tectonic Environment.

The pelite samples were collected from drillholes from the Chengmen area of the Fuzhou Basin of Fujian, China to reveal the sediments resource and tectonic environment of these pelites via an analysis of its lithology and geochemistry. The rare earth element distribution pattern of the pelites exhibited a high degree of fractionation between light and heavy rare earth elements, moderate negative Eu anomalies, and positive Ce anomalies, which are consistent with the rare earth element distribution pattern of Minjiang sediments and Fujian soils. Moreover, the variations in trace elements are also generally consistent, indicating a common provenance. The extremely high chemical index of alteration (CIA) and index of chemical variability (ICV) values of the pelites suggest that the source area experienced intense weathering, indicating a subtropical hot and humid climate environment in the source area and the Fuzhou Basin at that time. The source rock attribute discrimination diagrams show that the main source of pelites is felsic igneous rocks. The ratios of REDOX parameters show that during the sedimentary period, the water body in the study area was predominantly in an oxidizing environment. Furthermore, the tectonic background diagrams reveal that the source area underwent geological tectonic evolution processes of active and passive continental margins, marking the transition from the continental margin above the subduction of the ancient Pacific plate to the continental margin extension after subduction cessation.

Landscape Image Defogging System Based on DCPA Algorithm Optimization

As the global climate environment deteriorates gradually, the collected images are covered by fog, which reduces the clarity of the images. Therefore, the processing of fog images is very important. In landscape image defogging research, the defogging process may be affected by factors such as data quality, noise interference, and computational efficiency. To improve the defogging effect of landscape fog images, a landscape image defogging system was put forward with the optimization of dark channel prior algorithm. The image defogging algorithm was combined with the improved atmospheric scattering model estimation algorithm and the dark channel convolutional network image defogging algorithm to achieve image defogging. The atmospheric light estimation method based on atmospheric scattering model combined transmittance map and grayscale map information to achieve optimization of defogging effect. In the improvement of the dark channel prior algorithm, a convolutional network was introduced for feature extraction to enhance the smoothing of image brightness changes and transmittance estimation. The research findings demonstrated that the signal-to-noise ratio of the image defogging algorithm estimated by the atmospheric scattering model could reach up to 19dB, which was about 15.4% higher than that of existing 5 image defogging algorithms on average, indicating that the image resolution of the algorithm was higher after defogging. In the Reside dataset, the image defogging algorithm based on dark channel prior increased the signal-to-noise ratio by about 9.5%, the average gradient by about 10.4%, the structural similarity by about 12%, and the information entropy by about 5.8%, indicating that the effect of the algorithm was stable and the image defogging effect was good. The dark channel convolutional network image defogging algorithm had less running time and reduced the complexity of the defogging structure, by contrast, it reduced the running time by about 67%. The average scores for the operability, stability, and defogging effect of the system were 9.87 points, 9.85 points, and 9.54 points, respectively, indicating good performance of the system. The user feedback on natural landscape fog maps, architectural landscape fog maps, and historical landscape fog maps is good, and the user experience is high.

A Method for Predicting Wear Behaviours of Roller Linear Guides Under the Influence of the Relative Humidity and Ambient Temperature

The wear of roller linear guides (RLG) has a direct impact on the tooling precision of CNC machine tool. Wear depends on working conditions: load P, speed V, work environment which includes relative humidity RH and ambient temperature T. In this paper the mathematical regression function describes the relationship between the wear amount U of RLG with the three factors P, RH and T built on the basis of experimental research. The results show that the wear regression function U has an exponential form, which is consistent with experiments about the influence of climatic environment. It describes the simultaneous impact of three factors P, RH, T that affect wear of CNC machine tool rolling guide. With Vietnam's hot and humid environmental conditions, relative humidity RH% = 51 - 99%, temperature T = 15 - 450C, and load P = 2 - 6kgf, the influence on rolling guide wear of normal load P is 2 times the humidity RH% and about 3.8 times that of temperature T. Therefore, it is possible to predict the change in wear amount according to two environmental factors when loading P at certain values.

Sediment source analysis in the korabelny stream catchment, King George Island, maritime Antarctica: Geomorphological survey, fingerprinting and delivery rate assessment

Research into sediment provenance identification in Antarctica is emerging as a relevant field of study, providing a unique insight into understanding geomorphological processes in extreme climatic environments. This study focusses on the mechanisms of sediment redistribution in the catchment of the Korabelny Stream, located at the western end of the Bellingshausen Ice Dome on King George Island (Shetland Islands). The catchment area of the stream covers 2.83 km2, with 1.17 km2 under the glacier. Two main sediment sources have been identified: a) the glacierized part, extending along the glacier edge and represented by a complex of moraine deposits lacking protective vegetation cover, along with part of the catchment under the glacier; b) the periglacial part, occupying territory with permafrost and a thin loose cover unevenly protected by early successional vegetation. We combine a tracer-based fingerprinting technique, sediment delivery estimates based on sediment flow connectivity index and geomorphological mapping to quantify the sources contribution to sediment yield. The proportional contribution of the glacierized part was 60–66 % of the total sediment yield based on two independent methods, suggesting the reliability of the results. It is noteworthy that sediment transport from the glacierized part exceeds that from the periglacial part. However, a significant portion of the sediment is redeposited in temporary reservoirs formed along the glacier edge and Lake Mesyats, located in the central part of the Korabelny Stream catchment. The main factor determining sediment yield in the catchment is the water reserves in snow at the beginning of the ablation season. In years when water reserves in snow significantly exceed long-term average values, such as observed in the austral summer of 2014–2015 when study was conducted, sediment yield was low. This is attributed to the faster melting of ice on the glacier compared to snow, due to differences in albedo.

Why does the courtyard spaces of same ethnic group present diverse characteristics in different regions： evidence based on ENVI-met climate modeling

The rapid urbanization in developing countries like China has led to a heightened challenge of climate degradation and the erosion of traditional ecological knowledge worldwide. The widespread distribution of Yi traditional settlements across various climatic zones in southwest China offers a unique opportunity to investigate the diverse courtyard spaces within the same ethnic group, influenced by distinct climatic environments. Through comprehensive field investigation, meticulous field measurement, and rigorous ENVI-met simulation, this study conducts a comparative analysis of microclimates in Yi typical courtyards across diverse climatic conditions. The results show that: 1) Courtyard plays a pivotal role in regulating microclimate dynamics across cold, temperate, and hot climatic conditions. 2) The microclimate regulation mechanism of a courtyard varies across different climatic environments. 3) The climate regulation efficacy of courtyards will diminish as the climate environment undergoes changes. 4) The aspect ratio (AR) is a key spatial factor which plays a crucial role in determining the efficiency of regulating courtyard microclimate. Concluded this study, the research findings not only provide valuable guidance for the protection planning and design of traditional Yi settlements in southwest China, but also offer significant insights for courtyard construction in other regions with extreme climates worldwide. In addition, this study constructs a new research framework for traditional settlements, which is of great significance for scientifically and accurately identifying the spatial value of traditional settlements and improving the theoretical system of traditional settlement protection and activation.

Effect of Depositional Environment and Climate on Organic Matter Enrichment in Sediments of the Upper Miocene—Pliocene Kampungbaru Formation, Lower Kutai Basin, Indonesia

The Upper Miocene–Pliocene Kampungbaru Formation crops out in the easternmost part of the Lower Kutai Basin, Indonesia. The sedimentological analysis of seven outcrops was carried out, and a total of twenty-five samples from these outcrops was analyzed for bulk geochemistry, organic petrography, and bulk and clay mineralogy to assess the effect of the climate and depositional environment on organic matter enrichment. The Kampungbaru Formation consists of interbedded sandstone, siltstone, claystone, and thick coal beds, which were classified into eleven lithofacies. Subsequently, seven facies associations were identified, namely the fluvial-dominated distributary channel, sheet-like sandstone, tide-influenced distributary channel, mouth bar, crevasse splay, delta plain, and delta front. The coal facies generally have a high amount of total organic carbon (TOC, 5.1–16.9; avg. 10.11 wt.%), and non-coal layers range from 0.03 to 4.22 wt.% (avg. 1.54 wt.%). The dominant maceral is vitrinite, while liptinite occurs only rarely in the samples. Organic matter is inferred to have originated from terrestrial plants growing in mangrove swamps. Identified clay minerals include varying proportions of kaolinite, illite, chlorite, and mixed layer illite/smectite (I/S). Kaolinite, which commonly constitutes up to 30% of the clay volume, indicates intensive chemical weathering during a warm and humid climate. In accordance with the Köppen climate classification, the paleoclimate during the deposition of the Kampungbaru Formation is classified as type Af, which is a tropical rainforest. Tropical climate was favorable for the growth of higher plants and deposition of organic matter under anoxic conditions and led to higher amounts of TOC in the Kampungbaru Formation.