Simulated Soil Research Articles

Development and evaluation of the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) version 1.0

Abstract. Land ecosystems are important sources and sinks of atmospheric components. In turn, air pollutants affect the exchange rates of carbon and water fluxes between ecosystems and the atmosphere. However, these biogeochemical processes are usually not well presented in Earth system models, limiting the explorations of interactions between land ecosystems and air pollutants from regional to global scales. Here, we develop and validate the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) by upgrading the Yale Interactive Terrestrial Biosphere Model with process-based water cycles, fire emissions, wetland methane (CH4) emissions, and trait-based ozone (O3) damage. Within iMAPLE, soil moisture and temperature are dynamically calculated based on the water and energy balance in soil layers. Fire emissions are dependent on dryness, lightning, population, and fuel load. Wetland CH4 is produced but consumed through oxidation, ebullition, diffusion, and plant-mediated transport. The trait-based scheme unifies O3 sensitivity of different plant functional types (PFTs) with the leaf mass per area. Validations show correlation coefficients (R) of 0.59–0.86 for gross primary productivity (GPP) and 0.57–0.84 for evapotranspiration (ET) across the six PFTs at 201 flux tower sites and yield an average R of 0.68 for CH4 emissions at 44 sites. Simulated soil moisture and temperature match reanalysis data with high R above 0.86 and low normalized mean biases (NMBs) within 7 %, leading to reasonable simulations of global GPP (R=0.92, NMB=1.3 %) and ET (R=0.93, NMB=-10.4 %) against satellite-based observations for 2001–2013. The model predicts an annual global area burned of 507.1 Mha, close to the observations of 475.4 Mha with a spatial R of 0.66 for 1997–2016. The wetland CH4 emissions are estimated to be 153.45 Tg [CH4] yr−1 during 2000–2014, close to the multi-model mean of 148 Tg [CH4] yr−1. The model also shows reasonable responses of GPP and ET to the changes in diffuse radiation and yields mean O3 damage of 2.9 % to global GPP. iMAPLE provides an advanced tool for studying the interactions between land ecosystems and air pollutants.

Synergistic effect of microorganisms and a direct current electric field on X70 steel corrosion in a near-neutral solution

In this paper, the corrosion behavior of X70 steel in the near-neutral simulated soil solution (NS4 solution) under the synergistic effect of sulfate reducing bacteria (SRB) and a direct current electric field (DCEF) were explored. The corrosion rate was determined with the electrochemical technique and the corrosion morphology and corrosion products were respectively characterized by SEM and XPS. In the sterile solution, corrosion morphology of X70 steel was pitting and the corrosion rate increased with the increase in DCEF intensity and exposure time. When DCEF was absent, the corrosion rate of X70 steel in bacterial NS4 solution was faster than that in the sterile solution and the corrosion morphology was general corrosion. The acceleration effect of DCEF on corrosion was more significant than that of SRB. Under the synergistic effect of SRB and DCEF, when DCEF intensity increased below 500 V/m, the metabolic activity of SRB was gradually enhanced and the corrosion rate of X70 steel decreased. The protective effect of biofilm weakened the acceleration effect of DCEF on corrosion and the corrosion behavior was controlled by SRB corrosion. When DCEF intensity increased above 1000 V/m, SRB cells were inactivated and the corrosion rate of X70 steel increased. The corrosion behavior of X70 steel was controlled by DCEF. Based on the above research results, preventative actions were proposed.

Simulated soil erosion predominantly affects fungal abundance in the rapeseed rhizosphere

Eroded agricultural soils have reduced soil organic carbon (SOC) levels that may affect the plant-microbiome interactions in the rhizosphere. We explored the impact of simulated erosion on major microbial groups in a pot experiment with rapeseed (Brassica napus L.) grown on arable soil with the potential to capture SOC. An erosion gradient was simulated by admixture (0%, 12%, 24%) of subsoil horizon (Bt) to topsoil (Ap) material. Rapeseed plants were pulse-labeled with 14CO2 at three growth stages and two soil compartments (bulk and rhizosphere soil) were sampled. Fungal ITS copy numbers were consistently higher in the rhizosphere and decreased with progressing plant growth stages. A significant increase of bacterial 16S rRNA gene copies in the rhizosphere only occurred at flowering. A response of fungal abundance to subsoil admixture was found detectable based on fungi:Bacteria and fungi:Archaea ratio at flowering. Archaea were neither affected by soil compartment nor subsoil admixture. 14C activity of microbial biomass, an indicator for relative input of freshly assimilated C into soil microbiome, was impacted by growth stage and compartment and decreased with ongoing growth stage. During the rosette growth stage, the 14C activity of the microbial biomass was elevated in the rhizosphere of the eroded soil indicating a plant response to the erosion factor. Our experiment revealed a compositional separation of the fungal community along the simulated erosion gradient and a selection of fungi for the two different soil compartments at flowering. Olpidimycetes, Fusarium and Rhizopus and putative pathogens were enriched in the rhizosphere at flowering. Fungi may have a competitive advantage in the rhizosphere of strongly eroded and nutrient diluted soils due to ecological adaptation and morphological traits i.e. hyphae that can bypass soil areas with low nutrient availability.

Electrochemical study characterizations of pyrite weathering in simulated acidic soil: Iron transformation, sulfur conversion and environmental implications

Pyrite in natural environments is susceptible to weathering, which results in acid mine drainage (AMD) and heavy metal pollution-related environmental problems. The increase in mining activities has led to a large amount of pyrite entering surroundings, which may aggravate soil acidification and heavy metal pollution. In situ electrochemical techniques were used to investigate the weathering behavior of pyrite in simulated acidic soil solutions, which is conducive to understanding the weathering mechanism and environmental impact. In this study, the polarization curves and electrochemical impedance spectroscopy reveal that a higher soil solution concentration, temperature and/or acidity accelerate pyrite weathering rate, with an activation energy of 21.21 kJ·mol-1. Further investigations reveal that the pyrite is initially oxidized to initially oxidized to S0 and released Fe(II), the Fe(II) is easily transformed into Fe(III), and part of the Fe species ultimately transforms into goethite γ-FeOOH and hematite α-Fe2O3. The S0 ultimately transform into sulfate, accompanied by the release of hydrogen ions (H+), resulting in serious soil acidification. These results specifically reveal the mechanism of pyrite weathering, especially the process of iron transformation and sulfur conversion, and they also quantitatively identify the pyrite weathering rate and the quantities of heavy metal ions released, providing an experimental basis for the risk assessment of pyrite in acid soils.

Influence of Starch on the Biodegradability of AGENACOMP®

The compostable blend AGENACOMP®, which combines thermoplastic starch with other biopolymers, has shown potential for producing plastic bags with reduced environmental impact upon disposal, thanks to its good processability and ability to form thin films when extruded. In this study, we produced a blend of AGENACOMP® with additional incorporated starch and evaluated its properties using extrusion, injection, mechanical tests, optical microscopy, and FTIR analysis. Furthermore, we tested its biodegradability by placing samples in simulated soil for three months. Our findings revealed that the addition of starch not only accelerated degradation but also increased the tensile modulus by approximately 20%. This indicates that the modified blend exhibits improved mechanical properties while remaining environmentally friendly due to its biodegradability.

Hydrological modelling for post-monsoon agricultural drought assessment and implications for the agro-economy

ABSTRACT Reliable drought monitoring is a prerequisite for minimizing potential agricultural losses. Soil moisture is a key variable for monitoring agricultural drought assessment. This study conducted in the Bundelkhand region of Uttar Pradesh uses a macroscale variable infiltration capacity (VIC) hydrological model to simulate soil moisture and calculate soil moisture deficit index (SMDI) for agricultural drought assessment for the Rabi crop growing season, 1998–2016. Crop yield was linked with SMDI and other covariates using a random forest machine learning-based regression technique. The results show that the VIC model effectively simulated root zone soil moisture when compared with the reference data. Major droughts were identified in the years 2000–01, 2007–08, and 2015–16 in the study region. The RF-based crop yield prediction accuracy improved when irrigational factors were added. The study provides a noteworthy reference for drought assessment and prevention, water resource management, and ensuring food security.

Development and evaluation of a multi-target droplet digital PCR assay for highly sensitive and specific detection of Yersinia pestis.

Plague, caused by the bacterium Yersinia pestis, is a zoonotic disease that poses considerable threats to human health. Nucleic acid tests are crucial for plague surveillance and the rapid detection of Y. pestis. However, inhibitors in complex samples such as soil and animal tissues often hamper nucleic acid detection, leading to a reduced rate of identifying low concentrations of Y. pestis. To address this challenge, we developed a sensitive and specific droplet digital polymerase chain reaction (ddPCR) assay for detecting Y. pestis DNA from soil and animal tissue samples. Three genes (ypo2088, caf1, and pla) from Y. pestis were used to develop a multi-target ddPCR assay. The limits of detection (LoD), reproducibility, and specificity were assessed for bacterial genomic DNA samples. The ability of the assay to detect low concentrations of Y. pestis DNA from simulated soil and mouse liver tissue samples was respectively evaluated and compared with that of quantitative real-time PCR (qPCR). The results showed that the ddPCR LoDs ranged from 6.2 to 15.4 copies/reaction for the target genes, with good reproducibility and high specificity for Y. pestis. By testing 130 soil and mouse liver tissue samples spiked with Y. pestis, the ddPCR assay exhibited a better sensitivity than that of the qPCR assay used in the study, with LoDs of 102 colony forming units (CFU)/100 mg soil and 103 CFU/20 mg liver. Moreover, the assay presented good quantitative linearity (R2 = 0.99) for Y. pestis at 103-106 CFU/sample for soil and liver samples. The ddPCR assay presented good performance for detecting Y. pestis DNA from soil and mouse tissue samples, showing great potential for improving the detection rate of low concentrations of Y. pestis in plague surveillance and facilitating the early diagnosis of plague cases.

Simulation of soil temperature under maize: An inter-comparison among 33 maize models

Accurate simulation of soil temperature can help improve the accuracy of crop growth models by improving the predictions of soil processes like seed germination, decomposition, nitrification, evaporation, and carbon sequestration. To assess how well such models can simulate soil temperature, herein we present results of an inter-comparison study of 33 maize (Zea mays L.) growth models. Among the 33 models, four of the modeling groups contributed results using differing algorithms or “flavors” to simulate evapotranspiration within the same overall model family. The study used comprehensive datasets from two sites - Mead, Nebraska, USA and Bushland, Texas, USA wherein soil temperature was measured continually at several depths. The range of simulated soil temperatures was large (about 10–15 °C) from the coolest to warmest models across whole growing seasons from bare soil to full canopy and at both shallow and deeper depths. Within model families, there were no significant differences among their simulations of soil temperature due to their differing evapotranspiration method “flavors”, so root-mean-square-errors (RMSE) were averaged within families, which reduced the number of soil temperature model families to 13. The model family RMSEs averaged over all 20 treatment-years and 2 depths ranged from about 1.5 to 5.1 °C. The six models with the lowest RMSEs were APSIM, ecosys, JULES, Expert-N, SLFT, and MaizSim. Five of these best models used a numerical iterative approach to simulate soil temperature, which entailed using an energy balance on each soil layer. whereby the change in heat storage during a time step equals the difference between the heat flow into and that out of the layer. Further improvements in the best models for simulating soil temperature might be possible with the incorporation of more recently improved routines for simulating soil thermal conductivity than the older routines now in use by the models.

Light grazing alleviates aeolian erosion–deposition effects on microbial communities in a semi-arid grassland

BackgroundSoil erosion affects the stability of terrestrial ecosystems and ecosystem services by directly or indirectly impacting the cycling of soil materials and energy and reducing the fertility of grassland soils. However, research on microbial adaptation to grazing and soil erosion is limited, particularly in relation to grassland ecosystem restoration. Here, we assess microbial communities subjected to simulated soil erosion and grazing in a semi-arid grassland of Inner Mongolia, China.ResultsNo significant change was observed in soil variables. However, the structure of the soil microbial community underwent significant changes as a result of soil erosion and soil erosion plus grazing, leading to a significant increase in the relative abundance of Cyanobacteria (116.80% vs 116.38%). Wind erosion and deposition contributed to an increase in the network complexity of soil bacterial and fungal communities. However, much of this effect was alleviated by grazing. Simultaneously, aeolian processes and grazing regulate soil microbial community assembly, leading to inconsistent patterns of change in bacterial and fungal communities. Under wind erosion and deposition, the relative contribution of deterministic processes (4.44% vs 31.11%) in bacterial communities increased, while the relative contribution of stochastic processes (2.23% vs 20%) in fungal communities reduced. Grazing resulted in a decrease in the relative contribution of deterministic processes (8.89%) in the bacterial community and an increase in the relative contribution of stochastic processes (8.89%) in the fungal community.ConclusionThis study presents a comprehensive investigation of the response of soil microbial communities to aeolian erosion–deposition and grazing in a semi-arid grassland. Our findings indicate that microbial communities in the semi-arid grassland show resistance to external disturbances and that light grazing mitigates the effects of aeolian erosion–deposition on microbial communities, which is essential for maintaining the stability and biodiversity of grassland ecosystems.

Temperature fluctuation in soil alters the nanoplastic sensitivity in wheat

Despite the wide acknowledgment that plastic pollution and global warming have become serious agricultural concerns, their combined impact on crop growth remains poorly understood. Given the unabated megatrend, a simulated soil warming (SWT, +4 °C) microcosm experiment was carried out to provide a better understanding of the effects of temperature fluctuations on wheat seedlings exposed to nanoplastics (NPs, 1 g L−1 61.71 ± 0.31 nm polystyrene). It was documented that SWT induced oxidative stress in wheat seedlings grown in NPs-contaminated soil, with an 85.56 % increase in root activity, while decreasing plant height, fresh weight, and leaf area by 8.72 %, 47.68 %, and 15.04 % respectively. The SWT also resulted in reduced photosynthetic electron-transfer reaction and Calvin-Benson cycle in NPs-treated plants. Under NPs, SWT stimulated the tricarboxylic acid (TCA) metabolism and bio-oxidation process. The decrease in photosynthesis and the increase in respiration resulted in an 11.94 % decrease in net photosynthetic rate (Pn). These results indicated the complicated interplay between climate change and nanoplastic pollution in crop growth and underscored the potential risk of nanoplastic pollution on crop production in the future climate.

Evaluating the impact of peat soils and snow schemes on simulated active layer thickness at pan-Arctic permafrost sites

Abstract Permafrost stability is significantly influenced by the thermal buffering effects of snow and active-layer peat soils. In the warm season, peat soils act as a barrier to downward heat transfer mainly due to their low thermal conductivity. In the cold season, the snowpack serves as a thermal insulator, retarding the release of heat from the soil to the atmosphere. Currently, many global land models overestimate permafrost soil temperature and active layer thickness (ALT), partially due to inaccurate representations of soil organic matter (SOM) density profiles and snow thermal insulation. In this study, we evaluated the impacts of SOM and snow schemes on ALT simulations at pan-Arctic permafrost sites using the Energy Exascale Earth System Model (E3SM) land model (ELM). We conducted simulations at the Circumpolar Active Layer Monitoring (CALM) sites across the pan-Arctic domain. We improved ELM-simulated site-level ALT using a knowledge-based hierarchical optimization procedure and examined the effects of precipitation-phase partitioning methods (PPMs), snow compaction schemes, and snow thermal conductivity schemes on simulated snow depth, soil temperature, ALT, and CO2 fluxes. Results showed that the optimized ELM significantly improved agreement with observed ALT (e.g. RMSE decreased from 0.83 m to 0.15 m). Our sensitivity analysis revealed that snow-related schemes significantly impact simulated snow thermal insulation levels, soil temperature, and ALT. For example, one of the commonly used snow thermal conductivity schemes (quadratic Sturm or SturmQua) generally produced warmer soil temperatures and larger ALT compared to the other two tested schemes. The SturmQua scheme also amplified the model’s sensitivity to PPMs and predicted deeper ALTs than the other two snow schemes under both current and future climates. The study highlights the importance of accurately representing snow-related processes and peat soils in land models to enhance permafrost dynamics simulations.

A Comparison of Different Protocols for the Extraction of Microbial DNA Inhabiting Synthetic Mars Simulant Soil.

Compared with typical Earth soil, Martian soil and Mars simulant soils have distinct properties, including pH > 8.0 and high contents of silicates, iron-rich minerals, sulfates, and metal oxides. This unique soil matrix poses a major challenge for extracting microbial DNA. In particular, mineral adsorption and the generation of destructive hydroxyl radicals through cationic redox cycling may interfere with DNA extraction. This study evaluated different protocols for extracting microbial DNA from Mars Global Simulant (MGS-1), a Mars simulant soil. Two commercial kits were tested: the FastDNA SPIN Kit for soil ("MP kit") and the DNeasy PowerSoil Pro Kit ("PowerSoil kit"). MGS-1 was incubated with living soil for five weeks, and DNA was extracted from aliquots using the kits. After extraction, the DNA was quantified with a NanoDrop spectrophotometer and used as the template for 16S rRNA gene amplicon sequencing and qPCR. The MP kit was the most efficient, yielding approximately four times more DNA than the PowerSoil kit. DNA extracted using the MP kit with 0.5 g soil resulted in 28,642-37,805 16S rRNA gene sequence reads and 30,380-42,070 16S rRNA gene copies, whereas the 16S rRNA gene could not be amplified from DNA extracted using the PowerSoil kit. We suggest that the FastDNA SPIN Kit is the best option for studying microbial communities in Mars simulant soils.

Simulation and Structural Analysis of a Flexible Coupling Bionic Desorption Mechanism Based on the Engineering Discrete Element Method.

Soil adhesion is one of the important factors affecting the working stability and quality of agricultural machinery. The application of bionic non-smooth surfaces provides a novel idea for soil anti-adhesion. The parameters of sandy loam with 21% moisture content were calibrated by the Engineering Discrete Element Method (EDEM). The final simulated soil repose angle was highly consistent with the measured soil repose angle, and the obtained regression equation of the soil repose angle provides a numerical reference for the parameter calibration of different soils. By simulating the sinusoidal swing of a sandfish, it was found that the contact interface shows the phenomenon of stress concentration and periodic change, which reflects the effectiveness of flexible desorption and soil anti-adhesion. The moving resistance of the wedge with different wedge angles and different serrated structures was simulated. Finally, it was found that a 40° wedge with a high-tail sparse staggered serrated structure on the surface has the best drag reduction effect, and the drag reduction is about 10.73%.

Corrosion behavior and mechanism of FeCoNi high-entropy alloy compared with X100 pipeline steel in a simulated alkaline soil environment

In this work, the corrosion behavior of FeCoNi HEA and X100 pipeline steel in a simulated Golmud soil environment was systematically studied utilizing electrochemical tests, surface analysis techniques and immersion measurement. The results indicate that FeCoNi HEA possesses superior anti-corrosion property than X100 steel by comparing the charge transfer resistance (Rct), passive current density (ip) and corrosion morphology. The microstructure and surface film are the principal factors causing the difference in corrosion resistance of the two alloys. More intact, uniform and dense passive film enhances the anti-corrosion performance of the HEA, while the nonprotective, loose and defective corrosion product film covering the surface of X100 steel is not conducive to inhibiting the corrosion of the steel substrate. The appearance of inclusions within the HEA can generate the micro-galvanic corrosion effect with the matrix, which promotes the substrate as an anode to induce pitting. Furthermore, multiple phases of X100 steel exhibits higher electrochemical activity compared to the HEA with a single Face Center Cubic (FCC) phase, which accelerates the corrosion of the steel. Moreover, the matrix of the HEA primarily experiences selected dissolution of Ni element.

Corrosion of API 5L X60 Pipeline Steel in Soil and Surface Defects Detection by Ultrasonic Analysis

The corrosion steels phenomenon is one of the main problems in the oil industry, such as in buried transmission pipelines used for high gas pressure for long distances. Steels are protected from the external soil corrosion through a bituminous coating, whose action is coupled with a cathodic protection system, which aims to maintain steel in its protection field and thus to avoid any corrosion risk. However, steels in service may experience external surface defects like corrosion pitting and cracking due to electrochemical or mechanical interactions of bare steel with an aggressive soil solution after steel protection failure. These are concerning phenomena and are the major threats of the pipeline transmission system’s reliability and ecological safety. Corrosion mechanisms are varied and can be evaluated by different methods, such as electrochemical measurements, which are influenced by various factors like temperature, pH, soil characteristics, resistivity, water content, and as well mechanical stresses. Corrosion results from simulated artificial soil solutions showed that steel is sensitive to corrosion by soil. Surface defects detection was carried out using an ultrasonic non-destructive method such as C-Scan Emission testing and the time of flight diffraction technique (TOFD) ultrasonic non-contact testing method. After propagation of the ultrasonic waves, the diffracted ultrasonic reflected wave occurring at the edges of the defects appears due to the presence of a corrosion defect by generating defect echoes. The C-Scan ultrasonic image shows surface reflection, including corrosion defects on interfaces with varying acoustic impedances. The cross-transverse speed ultrasonic propagation through the plate including defect is modified, revealing more surface defects, and cross-transverse speed is shown to increase ultrasonic detection presents some advantages, such as precision and speed of detection without alteration to the structure. This method can be used in the industrial context as an intelligent industrial robotics technique.

Experimental Study on Geopolymerization of Lunar Soil Simulant under Dry Curing and Sealed Curing.

The construction of lunar surface roads is conducive to improving the efficiency of lunar space transportation. The use of lunar in situ resources is the key to the construction of lunar bases. In order to explore the strength development of a simulated lunar soil geopolymer at lunar temperature, geopolymers with different sodium hydroxide (NaOH) contents were prepared by using simulated lunar regolith materials. The temperature of the high-temperature section of the moon was simulated as the curing condition, and the difference in compressive strength between dry curing and sealed curing was studied. The results show that the high-temperature range of lunar temperature from 52.7 °C to 76.3 °C was the suitable curing period for the geopolymers, and the maximum strength of 72 h was 6.31 MPa when the NaOH content was 8% in the sealed-curing mode. The 72 h strength had a maximum value of 6.87 MPa when the NaOH content was 12% under dry curing. Choosing a suitable solution can reduce the consumption of activators required for geopolymers to obtain unit strength, effectively reduce the quality of materials transported from the Earth for lunar infrastructure construction, and save transportation costs. The microscopic results show that the simulated lunar soil generated gel substances and needle-like crystals under the alkali excitation of NaOH, forming a cluster and network structure to improve the compressive strength of the geopolymer.

Effect of post-weld heat treatment on corrosion resistance of X90 pipeline steel joints

Abstract In order to improve the corrosion resistance of welded joints, X90 pipeline steel joints were subjected to post-weld heat treatment at 610 °C, 640 °C, and 670 °C (holding time was 1 h). Through electrochemical corrosion and full immersion corrosion experiments, the corrosion resistance of welded joints under various conditions was tested, and the surface morphology and corrosion products of the corroded samples were analyzed by scanning electron microscopy and X-ray diffraction analysis. The experimental results show that the corrosion products of X90 pipeline steel welded joints in simulated soil solution mainly include Fe(OH)3, γ-FeOOH, α-Fe2O3, γ-Fe2O3, and a small amount of Fe3O4, FeCl3 and Fe. After heat treatment at 610 °C, the corrosion current density of the parent metal, heat-affected zone, and weld metal of the joint changes from 1.081, 2.889, 2.079 (×10−5 A cm−2) to 0.977, 2.211, 1.810 (×10−5 A cm−2), respectively, the corrosion resistance is improved.

Evaluating soil moisture simulations from a national-scale gridded hydrological model over Great Britain

Study RegionThe study covers sites across Great Britain. Study FocusSoil moisture information is important for a range of applications including flood and drought monitoring, seasonal hydrological forecasting, and agricultural management. However, spatially distributed soil moisture estimates for sub-surface soils are scarce despite their importance. The Grid-to-Grid hydrological model (G2G) was primarily developed to simulate river flows at a national scale, but can also output simulated depth-integrated soil moisture on a 1 km grid. Here, we evaluate G2G soil moisture simulations against in situ neutron probe (NP) observations at 85 sites across Great Britain, to evaluate whether modelled soil moisture outputs have value and to identify areas for improvement. New Hydrological Insights for the Region:Despite large uncertainties in observed soil moisture within a site, there was a good temporal correlation between observed and modelled soil moisture, with Pearson correlation values exceeding 0.7 for 77% of sites. However, the model tended to under-predict soil moisture values (median bias of −12 cm/m) and over-predict variation (median standard deviation error of 2 cm/m). Model agreement with observations was generally better for areas with deep or mid-depth mineral soils and worst in areas of peat. Based on this evaluation against NP observations, we demonstrate that G2G soil moisture is a useful resource for estimating relative wetness of the soil, but not necessarily the soil moisture content values themselves.

Simulation Performance of Temperature and Precipitation in the Yangtze River by Different Cumulus and Land Surface Schemes in RegCM4

To improve the simulation performance of the RegCM4 model in climate simulations over the Yangtze River Basin (YRB), it is essential to determine the optimal cumulus convection and land surface process schemes from the numerous physical parameterization options within RegCM4. In this study, we selected five cumulus convection schemes (Kuo, Grell, Emanuel, Tiedtke, and Kain–Fritsch) and three land surface process schemes (BATS, CLM3.5, and CLM4.5) to configure 72 mixed schemes. Four years of short-term simulations (1990–1993) with a horizontal resolution of 50 km were conducted using ERA-Interim as the initial and boundary conditions for the 72 schemes. The climate simulation performance of all schemes in the YRB was comprehensively evaluated using a multi-criteria scoring approach. The results indicate that among the selected cumulus convection schemes, the Kain–Fritsch scheme, applied to both ocean and land, demonstrates optimal performance in simulating precipitation over the YRB, with spatial correlation coefficients between simulated and observed annual precipitation around 0.3. Compared to the Community Land Models (CLM3.5 and CLM4.5), BATS exhibits superior capabilities in reproducing the temperature features of the region, with spatial correlation coefficients between simulated and observed values typically exceeding 0.99 and standard deviations within 1.25 °C. Under the optimal KF scheme, the simulated soil moisture in the YRB using CLMs is notably drier, ranging from −7.79 to −8.39 kg/m2, compared to that achieved with BATS. The findings provide a localized reference for the parameterization schemes of RegCM4 in the YRB.

Effects of TiO2 on fiber spinnability, structure, and mechanical properties of glasses derived from simulated lunar soils

The construction of lunar stations for research and habitation requires high-performance building materials that can adapt to the harsh lunar environment. One of the feasible building materials is fiber-reinforced composites, for which the composition of glass fibers can be designed like lunar soils, i.e., terrestrial basalt, and in turn the “lunar glass” can be drawn into fibers. Because of a wide variation of TiO2 in lunar soils, our study focused on a series investigation on the effect of TiO2 (0.55 wt%-6.14 wt%) on fiber spinnability and strength of the simulated “lunar glass and glass fibers”. The baseline glass composition was derived from a simulated TiO2-lean lunar soil and other glasses were made at different TiO2 doping levels. The addition of TiO2 was found to reduce the thermal stability of the melt, there appears a TiO2 threshold (6.14 wt%), at which fibers cannot be drawn without breakage because of melt devitrification. The fiber tensile strength exhibits a nonlinear characteristic with an apparent maximum at 1.52 wt% TiO2. FTIR and Raman spectroscopic studies were carried out to investigate the glass network structure responses to TiO2 modifications and show TiO2 functions as a network modifier, depolymerizing the silicate network. Statistical structure (FTIR & Raman based)–property modeling was attempted to further elucidate the effect of TiO2-induced structure change on Tg and fiber tensile strength. Good agreements were found between the model predictions and the measured values.