Precipitation Time Research Articles

Effects of flocculant and corrosion inhibitor compounding on the electrochemical corrosion behavior of the anode in Al-air batteries

To solve the problem of precipitates affecting battery performance in aluminum-air batteries. This study employed a variety of techniques—including flocculant-simulated sedimentation experiments, electrochemical assays, constant current discharge tests, and microscopic morphology assessments—to evaluate the synergistic effects of corrosion inhibitors and flocculants in the electrolyte of aluminum-air batteries. The inorganic polymer compound polyalumi rlillm sulfate (PSA) and the inorganic compound aluminum sulfate were investigated in a 4 mol/L NaOH+ 0.06 mol/L Na2SnO3 solution to elucidate the electrochemical corrosion mechanism of the 5052 aluminum alloy anode, as well as the sedimentation time and effect of colloidal precipitation. The results showed that the compounding of the two flocculants with the conventional corrosion inhibitor Na2SnO3 enhanced both the sedimentation rate of aluminum hydroxide in alkaline media and decreased the corrosion rate of the aluminum anode. Specifically, 3 g/L PSA was found to be most efficacious, elevating the sedimentation efficiency by 70.6%. Additionally, 1 g/L PSA demonstrated the most significant inhibitory effect on the self-corrosion of 5052 aluminum alloy, leading to an increase in the anode battery's capacity density by 15.5–35.1%. The synergistic action of flocculants and corrosion inhibitors chiefly accelerated the sedimentation rate of precipitates, maintained electrolyte conductivity, and facilitated the formation of a protective film on the surface of the aluminum anode to reduce the self-corrosion rate of aluminum, thereby promoting the improvement of discharge performance of aluminum-air batteries.

Groundwater level response to precipitation at the hydrological observatory of Pinios (central Greece)

To study groundwater dynamics and their response to precipitation in the Pinios river basin (central Greece), the variation trends and seasonal patterns of fourteen monitored groundwater and two precipitation time series were examined using time series decomposition, autocorrelation, and wavelet analysis. The objective is to perform indirect methodologies based on groundwater level and precipitation data to attain a detailed understanding of the hydrogeological mechanisms of the aquifer system and develop an approach that can be easily employed worldwide. The three approaches confirm local groundwater circulation understanding by dividing the aquifer system into three parts characterised by varying transmissivity and storativity properties. The extended memory effect, ranging between 70 and 230 days suggests great inertia and storage capacity of the examined groundwater system. The wavelet analysis proves that the system acts as a filter which absorbs the precipitation frequencies converting them into GWL signals, as demonstrated by the 256 days periodicity shared by groundwater level and precipitation time series. Generally, GWLs present a hysteresis to precipitation due to the geological setup and local flow conditions and are particularly affected by a seasonal component, as also highlighted by time series decomposition. An evident annual periodicity is also observed in hydrological and hydrogeological time series. Results suggest the effectiveness of the proposed combination of methods in developing hydrological understanding and their general applicability to other regions where at least groundwater level and precipitation time series are available. By utilising such data-driven approaches, hydrogeologists and water resource managers can gain valuable insights into the behavior of aquifers, groundwater flow patterns, and the impact of human activities on groundwater quality and quantity.

Effect of Zr on static recrystallization of deformed austenite and strain-induced precipitation in Ti microalloyed steel

The static recrystallization and strain-induced precipitation behavior of Ti and Ti-Zr low carbon microalloyed steels were studied through isothermal stress relaxation experiments at different deformation temperatures (875–1025 °C). The precipitation kinetic curves of microalloyed carbides were obtained, and the effect of Zr on the precipitation kinetics of microalloyed carbides was analyzed. Two static recrystallization kinetic models were established, and the activation energies for static recrystallization of Ti steel and Ti-Zr steel were calculated to be 312.44 and 246.59 kJ/mol, respectively. The results indicate that the addition of Zr lowers the nose point temperature of the precipitation–time–temperature curve, shortens the incubation period for the nucleation of precipitates, promotes the nucleation of strain-induced precipitates in Ti microalloyed steel, and reduces the coarsening rate of precipitates particles by an order of magnitude. In addition, the addition of Zr also advances the end time of static recrystallization of deformed austenite, inhibits the growth of static recrystallization austenite grains in Ti steel during the isothermal process, and makes the austenite grains finer and more uniform.

Effect of changing precipitation in different periods on precipitation use efficiency in a semi‐arid grassland

AbstractQuestionClimate change intensifies global and regional water cycles, leading to changes in both the magnitude and timing of precipitation. Precipitation use efficiency (PUE) plays a crucial role in measuring the response of above‐ground net primary productivity (ANPP) to precipitation changes. However, little is known about how changes in precipitation during different periods affect PUE.MethodsUsing a manipulation precipitation experiment in a semi‐arid steppe, we simulated a 60% increase and decrease in precipitation during the early (April–June), late (July–September), and entire (April–September) growing seasons across 2015–2021 to examine the effects of changes in precipitation timing on PUE.ResultsThe results showed that: (1) decreased precipitation in the late growing season (DLP) and whole growing season (DWP) stimulated PUE by an average of 0.14 and 0.12 g m−2 mm−1 yr−1 respectively, whereas increased precipitation in the late growing season (ILP) and whole growing season (IWP) suppressed PUE by an average of 0.11 and 0.09 g m−2 mm−1 yr−1 respectively. By contrast, neither decreased nor increased precipitation in the early growing season affected PUE; (2) the increased PUE under DLP was primarily attributed to the increase of PUE in grass (GR) and annuals and biennials (AB), whereas the elevation of PUE under DWP was mainly due to an increase of PUE in AB. By contrast, the reduction of PUE under ILP was mainly caused by a decline of PUE in GR; (3) changes in evapotranspiration and leaf dry matter content (LDMC) explained the variation of PUE in AB while changes of PUE in GR was mainly due to the alteration of soil water content and LDMC.ConclusionsThese results suggest that precipitation during the late growing season has a crucial influence on PUE, highlighting the importance of evapotranspiration and LDMC in regulating ecosystem productivity in the semi‐arid steppe.

Подверженность населенных пунктов Республики Дагестан обвально-осыпным процессам

The object of the study is the landslide activity in the Republic of Dagestan. The paper considers the results of systematization and analysis of various sources containing information on the activity and danger of landslide processes in the settlements of the republic for 2004–2022. The conditions, causes, activity and danger of landslide manifestations on their territory are characterized. The role of natural and man-made factors in the development of this process and its obvious timing to the winter-spring-summer period of the year (the time of snowmelt and abnormal precipitation) is determined. 46 settlements were identified (in 21 administrative districts of the republic), where significant landslides occurred over the period under consideration. Most of these rural settlements are located in the low and middle mountainous parts of the republic. The largest number of affected settlements (from the studied processes) are located in the Tsumadinsky and Akhvakhsky administrative districts of the republic. It is noted that in the period from 2004 to 2022, the greatest landslide activity was observed in 2014, and a very weak degree was observed in 2010, 2013 and 2021. In 2006, 2017 and 2019, landslides in the settlements of the republic were not recorded. The most catastrophic landslide processes over the studied period of time were observed in the villages of Hebda and Golotl in the Shamil district. The article provides information on the scale of the collapse deformations and destruction of residential infrastructure on the territory of settlements. The analysis of the socio-economic consequences of the landslide allows us to speak about a fairly significant degree of their danger to the life of the population in the mountainous part of the republic.

Effect of emergency medical service response time on fatality risk of freeway crashes: Bayesian random parameters spatial logistic approach.

Emergency medical service (EMS) serves as a pivotal role in linking injured road users to hospitals via offering first aid measures and transportation. This paper aims to investigate the effect of emergency medical service (EMS) response time on the fatality risk of freeway crashes. Crash injury severity data from Kaiyang Freeway, China in 2014 and 2015 are employed for the empirical investigation. A Bayesian random parameters spatial logistic model is developed for analyzing crash severity. Bayesian inference of the random parameters spatial logistic model demonstrates the importance of reducing EMS response time on minimizing the fatality risk of freeway crashes. Fatality odds would increase by 2.6% for 1 min increase in EMS response time. Additionally, vehicle type, crash type, time of day, horizontal curvature, vertical grade, and precipitation are also found to have significant effects on the fatality probability of freeway crashes. It is crucial to reduce EMS response time to decrease the fatality likelihood of freeway crashes. Some countermeasures have been proposed to shorten EMS response time.

Multi-Temporal and Time-Lag Responses of Terrestrial Net Ecosystem Productivity to Extreme Climate from 1981 to 2019 in China

The escalating frequency and severity of extreme climate greatly impact the carbon dynamics of terrestrial ecosystems worldwide. To understand the multi-temporal response of net ecosystem productivity (NEP) to extreme climate, we investigated 11 temperature and precipitation extreme indices across different vegetation types in China. From 1981 to 2019, the results showed that NEP in China increased at a rate of 0.64 g·m−2·a−2. Extreme climate demonstrated a significant warming trend and a non-significant moistening trend; specifically, maximum daily minimum temperature (TNx) exhibited a significant increase at a rate of 0.34 °C/10 a, while maximum 5-day precipitation (Rx5day) showed an insignificant increase at a rate of 1.78 mm/10 a. NEP was significantly impacted by extreme temperature at the annual, seasonal, and monthly scales, but moderately impacted by extreme precipitation. Specifically, extreme temperature had the most significant effect on grassland, with minimal influence on cropland. In contrast, extreme precipitation had the most significant effect on forest, with minimal impact on cropland. Moreover, the lagged time for extreme precipitation was longer than that for extreme temperature. Extreme precipitation exhibited a corresponding lagged time of at least 2 months (p < 0.01), while extreme temperature exhibited a lagged time of at least 1 month (p < 0.01). The maximum lag time observed was 4 months (p < 0.01). Our findings provide valuable insights into the multi-temporal response of NEP to extreme climate in China and inform sustainable development practices in the region.

Origin of calcite cements in the Permian Lucaogou Formation tight reservoirs, Jimsar sag, Junggar basin, NW China: Constraints from geochemistry

Understanding the diagenetic evolution of carbonate cementation in hydrocarbon reservoirs is critical to better reconstruct the history of fluid flow during petroleum accumulation. The extensive occurrence of carbonate cements within the lower Permian Lucaogou Formation tight reservoirs is regarded as a major diagenetic factor that causes strong hydrocarbon reservoir heterogeneities. Petrographic and geochemical analyses, including optical microscopy fitted with cathodoluminescence, scanning electron microscopy, carbon and oxygen stable isotopes, in situ rare earth element, as well as fluid inclusion microthermometry, were carried out to decipher the origin of calcite cementation and understand its control on reservoirs quality. Petrography shows that the precipitating cements mostly consist of pore-filling blocky/mosaic calcite, with a dull orange luminescence color. Chondrite-normalized rare earth element (REE) patterns and C–O isotopic compositions of these calcite cements exhibit strongly negative Eu and Tb anomalies, enrichment in light REE, positive carbon (δ13CPDB = 0.58‰–7.45‰) and negative oxygen (δ18OPDB = −11.38‰ to −8.61‰) isotopic values, similar to the dolostone and micritized peloidal grains, suggesting that the calcite-precipitating fluids were derived from dissolution of lacustrine depositional carbonates. The relative timing of calcite precipitation in reservoirs was constrained based on the thermal-burial history of the study region and precipitation temperatures obtained from fluid inclusions. The results show that this cementation episode mainly occurred during the Late Triassic to Early Jurassic, which was synchronous with the tectonic uplift event. Moreover, homogenization temperatures of fluid inclusions and geochemical signatures of the calcite cement are similar to those of the fracture-fillings, suggesting that these two calcite phases may be genetically related and form coevally within one fluid flow system. It can be interpreted as a response to the compressional tectonic deformation given by the collision of the Qiangtang Block with the Eurasia Plate. This tectonic deformation event is regarded as the driver for calcite precipitation during the early burial stage, resulting in a considerable reduction of reservoir quality. Calcite cementation is pervasive and may play a main role in halting hydrocarbon migration through some of the permeable pathways in reservoirs.

Decadal prediction of Northeast Asian winter precipitation with CMIP6 models

This study evaluates the decadal prediction skill of 13 forecast systems in predicting winter precipitation over Eurasia, contributing to the Decadal Climate Prediction Project of the Coupled Model Intercomparison Project Phase 6. Northeast Asia stands out as a region with improved decadal prediction skill for forecast years 2–5 due to the initialization. Observations show anticyclonic and cyclonic wind anomalies over the North Pacific and Northeast Asia, respectively, with southwesterly flow to the east of Northeast Asia. Ten forecast systems reproduce such circulation anomalies favoring abundant winter precipitation in Northeast Asia. The significant positive (negative) correlations between the detrended Northeast Asian precipitation (NEAP) and AMV (PDO-like) time series are reproduced by seven (nine) forecast systems. However, most forecast systems underestimate the correlation between the NEAP and the AMV, and have relatively low skill in predicting the PDO. Further improvements in these aspects will help to improve the decadal prediction skill of winter precipitation over Northeast Asia. The multi-model ensemble (MME) is able to reproduce both links of NEAP with AMV and PDO-like variability. The MME demonstrates significant skill and outperforms the individual forecast systems in predicting the NEAP for all 4-year averaged periods in the range of 1–8 years, demonstrating the benefits of using the ensemble mean of multiple models.

Altered intra-annual precipitation patterns affect the N-limitation status of soil microorganisms in a semiarid alpine grassland

The ongoing intensification of the hydrological cycle due to global climate change alters intra-annual precipitation variability. Changes in precipitation patterns lead to disparities in soil moisture; however, the responses of soil extracellular enzyme activities (EEAs) and microbial metabolism limitations to them is unclear. This study conducted an in situ field experiment in the alpine grasslands of the Kunlun Mountains to simulate the same amount of precipitation but change the distribution time of precipitation within the plant growing season. We examined the effects of variability in intra-annual precipitation patterns on the stoichiometry of topsoil (0–5 and 5–20 cm) properties, microbial biomass, and EEAs. Results showed that altered precipitation patterns significantly increased soil moisture’s disparity index (D) by 57 %–89 %. The activity of nitrogen-acquiring enzymes (L-leucine aminopeptidase) was increased by 20.82–32.08 % (P < 0.05) with increased variability of precipitation, while phosphorus-acquiring enzymes (Acid phosphatase) and carbon-acquiring enzymes (β-glucosidase) both decrease by 9.25–23.35 % and by 17.86–33.04 %, respectively (P < 0.05). We determined that soil microorganisms in the study region were metabolism-limited by nitrogen (vector angles < 45◦), and increased precipitation variability exacerbated nitrogen limitation (decrescent vector angles) and alleviated carbon limitation (shortened vector length). In addition, soil EEAs can be both interactively influenced by biotic and abiotic factors, with abiotic factors (i.e., D, soil organic carbon content, and soil total nitrogen content) having a stronger effect. Our study provides an effective strategy for regulating soil EEAs, microbial biomass, and microbial metabolism limitation and contributes to developing nutrient management and restoration strategies in semiarid alpine grassland ecosystems.

Historical Shifts in Seasonality and Timing of Extreme Precipitation

AbstractGlobal warming impacts the hydrological cycle, affecting the seasonality and timing of extreme precipitation. Understanding historical changes in extreme precipitation occurrence is crucial for assessing their impacts. This study uses relative entropy to analyze historical changes in seasonality and timing of extreme daily precipitation occurrences on the global domain for 63 years of fifth generation of the European Reanalysis reanalysis data. Our analysis reveals distinct regional patterns of change. During the second half of the 20th century, Africa and Asia experienced high clustering of precipitation extremes. Over the past 60 years, clustering increased in Africa while becoming more spread out in Asia. North America and Australia had initially lower clustering and showed slight increases over time. Extreme events in extra‐tropical land regions mainly occurred in summer, with modest shifts in timing. These findings have implications for risk assessments of natural hazard like flash floods and landslides, emphasizing the necessity for region‐specific adaptation strategies.

Weather prediction using traditional knowledge in cold arid high altitude region of Ladakh in India

The Union territory of Ladakh in India is a cold arid high altitude region. The subsistence nature of agriculture being practiced (by majority of farmers) in the region is solely dependent on melted glacier water. The present study was undertaken in Leh district of Ladakh to identify, prioritize and understand the traditional knowledge (TK) used by the farming community for prediction of weather. The primary data were collected from 320 households from 20 villages in Leh district from 2015 to 2020. The primary data were aided and validated by Focused Group Discussions with key informants and stakeholders working in the region such as scientists from research institutions and officials from agriculture and line departments. Farmers used combination of indicators including behavioral changes of birds and animals, change in atmospheric events and inferences drawn from Lotho (almanac) to predict weather. Migration pattern of birds was the most ancient, common and widely prevalent TK used for prediction of onset and extent of snowfall and winter season by farmers. Building of nest by birds on poplar tree (Poplus sp.) at different heights and directions was used to predict temperatures in the forthcoming summer season. The duration of hibernation of Himalayan marmots (Marmota himalayana) was an indication of duration of snowfall and winter temperatures. Timing and extent of precipitation (rainfall and snowfall) was used to predict the distribution of snowfall and winter temperatures. Lotho was extensively used for planning agricultural operations till a decade ago. The farming community used different TK in totality to enhance the accuracy of weather prediction. It was found that improved connectivity of the region with the mainland, introduction of modern communication technologies and decreasing dependence on agriculture as a primary livelihood option (because of the emergence of non-farm based opportunities such as services and tourism) have made the use of TK less prevalent among young generation farmers. However, the majority of the farmers expressed the need for blending TK and modern science for addressing location-specific problems.

Comparison Link Function from Summer Rainfall Network in Amazon Basin

The Amazon Basin is the largest rainforest in the world, and studying the rainfall in this region is crucial for understanding the functioning of the entire rainforest ecosystem and its role in regulating the regional and global climate. This work is part of the application of complex networks, which refer to a network modeled by graphs and are characterized by their high versatility, as well as the extraction of key information from the system under study. The main objective of this article is to examine the precipitation system in the Amazon basin during the austral summer. The networks are defined by nodes and connections, where each node represents a precipitation time series, while the connections can be represented by different similarity functions. For this study, three rainfall networks were created, which differ based on the correlation function used (Pearson, Spearman, and Kendall). By comparing these networks, we can identify the most effective method for analyzing the data and gain a better understanding of rainfall’s spatial structure, thereby enhancing our knowledge of its impact on different Amazon basin regions. The results reveal the presence of three important regions in the Amazon basin. Two areas were identified in the northeast and northwest, showing incursions of warm and humid winds from the oceans and favoring the occurrence of large mesoscale systems, such as squall lines. Additionally, the eastern part of the central Andes may indicate an outflow region from the basin with winds directed toward subtropical latitudes. The networks showed a high level of activity and participation in the center of the Amazon basin and east of the Andes. Regarding information transmission, the betweenness centrality identified the main pathways within a basin, and some of these are directly related to certain rivers, such as the Amazon, Purus, and Madeira. Indicating the relationship between rainfall and the presence of water bodies. Finally, it suggests that the Spearman and Kendall correlation produced the most promising results. Although they showed similar spatial patterns, the major difference was found in the identification of communities, this is due to the meridional differences in the network’s response. Overall, these findings highlight the importance of carefully selecting appropriate techniques and methods when analyzing complex networks.

Space-time data-driven modeling of precipitation-induced shallow landslides in South Tyrol, Italy

Shallow landslides represent potentially damaging processes in mountain areas worldwide. These geomorphic processes are usually caused by an interplay of predisposing, preparatory, and triggering environmental factors. At regional scales, data-driven methods have been used to model shallow landslides by addressing the spatial and temporal components separately. So far, few studies have explored the integration of space and time for landslide prediction. This research leverages generalized additive mixed models to develop an integrated approach to model shallow landslides in space and time. We built upon data on precipitation-induced landslide records from 2000 to 2020 in South Tyrol, Italy (7400 km2). The slope unit-based model predicts landslide occurrence as a function of static and dynamic factors while seasonal effects are incorporated. The model also accounts for spatial and temporal biases inherent in the underlying landslide data. We validated the resulting predictions through a suite of cross-validation techniques, obtaining consistent performance scores above 0.85. The analyses revealed that the best-performing model combines static ground conditions and two precipitation time windows: a short-term cumulative precipitation of 2 days before the landslide event and a medium-term cumulative precipitation of 14 days. We demonstrated the model's predictive capabilities by predicting the dynamic landslide probabilities over historical data associated with a heavy precipitation event on August 4th and August 5th, 2016, and hypothetical non-spatially explicit precipitation (what-if) scenarios. The novel approach shows the potential to integrate static and dynamic landslide factors for large areas, accounting for the underlying data structure and data limitations.

Fe3+ and Al3+ removal by phosphate and hydroxide precipitation from synthetic NMC Li-ion battery leach solution

The removal of trivalent iron and aluminum was studied from synthetic Li-ion battery leach solution by phosphate and hydroxide precipitation (pH 2.5–4.25, t = 3 h, T = 60 °C). Phosphate precipitation exhibited both crystal nucleation initiation (pH 2 vs. pH 3) as well as complete (~ 99%) Fe and Al removal at lower pH compared to hydroxide precipitation (pH 3 vs. 3.5). The precipitation time of phosphate was shorter (40 min) than that of hydroxide precipitation (80 min). At pH 4 the loss of valuable metals (Li, Ni, Co) in the precipitate was negligible in the phosphate cake, whereas in the hydroxide process the co-precipitation was 4–5% for Li, Ni and Co. The filtration rate of phosphate precipitate was shown to be significantly faster. The presence of fluoride did not have any notable effect on phosphate precipitation, whereas in hydroxide precipitation, it potentially had a negative effect on aluminum extraction.

An Experimental Study on Some Thermophysical Characteristics of CuO-Water Nanofluid

This study presents the effects of the volume fraction of nanoparticles (0.15% ≤ Φ ≤ 0.74%) with ascorbic acid additive on some thermophysical characteristics of water based CuO nanofluids, such as thermal conductivity and viscosity, as well as agglomeration by analyzing microstructure, adhesion and precipitation time. The CuO nanofluids have been prepared and examined for five different volume fractions by using appropriate mixers. The microstructure of the samples, which are prepared with ascorbic acid additive in order to prevent the agglomeration of CuO nanoparticles and to ensure a homogeneous distribution, has been analyzed on the SEM images. In the adhesion experiments, an observational test was performed for 0.23% CuO-water sample. The samples prepared have been kept about 100 hours for observational examination of precipitation similar to the adhesion test. Thermal conductivity measurements have been conducted in a standard experimental set-up and a correlation equation has been proposed based on data acquired. The viscosity measurements have been carried out using a calibrated “falling-piston viscometer” and a correlation equation was also defined for thermal conductivity. The thermal conductivity measurements of the study have been compared to experiments given in the literature and a good agreement has been obtained at low volume fractions (less than 0.5%).

Optimization of ethanol precipitation process of Nauclea officinalis extract based on concept of quality by design(QbD)

The ethanol precipitation process of Nauclea officinalis extract was optimized based on the concept of quality by design(QbD). Single factor tests were carried out to determine the levels of test factors. The ethanol volume fraction, pre-ethanol precipitation drug concentration, and ethanol precipitation time were taken as critical process parameters(CPPs). With the comprehensive scores of strictosamide transfer rate and solid removal rate as the critical quality attributes(CQAs), Box-Behnken design was employed to establish the mathematical models and space design between CPPs and CQAs, and the obtained optimal operating space was validated. The optimal operating space included ethanol volume fraction of 65%-70%, pre-ethanol precipitation drug concentration of 22-27 mg·mL~(-1), and ethanol precipitation time of 12 h. Based on the concept of QbD, this study adopted the design space to optimize the ethanol precipitation process of N. officinalis extract, which provided a reliable theoretical basis for the quality control in the production process of N. officinalis preparations. Moroever, this study provided a reference value for guiding the research and industrial production of traditional Chinese medicines.

Carbonate Associated Sulfate Extraction Method Using Weakly Acidic Cation Exchange Resins

The sulfur (S) mass fraction of carbonate minerals can be used to reconstruct the environmental conditions and S sources at the time of precipitation. As S is present in a wide range of host materials, there is an urgent need to develop a method to extract S from a single mineral phase. We have developed a method to extract structurally substituted sulfate, termed carbonate‐associated sulfate (CAS), from geological and biogenic carbonate minerals using weakly acidic cation exchange resins. Two types of weakly acidic cation exchange resin (methacrylic acid and acrylic acid types) were tested to minimise the blank S contents and decompose carbonate. After repeated cleaning of the resins with high‐purity water or HCl, the blank S contents were reduced to &lt; 0.1 μg, which is &lt; 0.1% of the CAS in the samples. The cleaned resin was used to dissolve 10 and 25 mg of the JCp‐1 carbonate certified reference material (CRM; Japanese National Institute of Advanced Industrial Science and Technology, AIST). Samples and resin were added to 8 ml of high‐purity water at resin/sample ratios of 2, 5, 10 and 20, set on a shaking table, and reacted. The supernatant solutions were sampled sequentially from 0.5 h to 87 h after the start of experiments. The results show that the optimal conditions for decomposing 10 mg of carbonate is a resin/sample ratio of ≥ 10 with a reaction time of ≥ 40 h. Carbonate‐associated S mass fractions were measured for six geological and biogenic carbonate CRMs. The coefficient of variation in carbonate‐associated S mass fractions was ≤ 7%, regardless of the type of resins used. The mass fractions determined with this method recover 74–94% of the total S mass fractions reported in previous studies, suggesting that this method dissolved carbonate, and did not leach other S‐bearing fractions that are not resistant to weak acids. Another benefit of this method is that the decomposed solution can be introduced directly into the ion chromatograph, allowing for more sensitive analyses. We emphasise that this method can also be used for S isotopic measurements, as S contamination from other S‐bearing mineral phases is low.

Human or climate? Differentiating the anthropogenic and climatic drivers of lake storage changes on spatial perspective via remote sensing data

Lakes are an essential part of the terrestrial water system in which storage changes are controlled by water balance and human impact. Although there are some attempts to define storage changes on a global scale, examination of spatial relations is poorly quantified. In this study, therefore, lake storage changes have been investigated using remote-sensing-derived data around the globe. Hence, 372 artificial/natural lakes were obtained, covering between 1992 and 2019. Watersheds belong to river was extracted via HydroSHED data. Based on watershed, dominant climate types were determined via Köppen-Geiger classification. Similarly, the areal average CRU TS v.4.05 monthly gridded precipitation time series and human footprint data based on watersheds were obtained to understand the drivers of lake storage changes. The nonparametric Mann-Kendall and Sen's slope trend analyses were applied to the lake storage change and precipiation values in order to determine long-term increases and decreases. A bivariate map was constructed between storage changes trend vs precipitation trend and human footprint to reveal the drivers of lake storage changes in terms of spatial aspects. The trend analysis and bivariate map results show that North America, the East African Highlands, and the Tibet plateau are important increasing hotspots, where precipitation is a significant driver for storage oscillations, except for the Tibet plateau. Besides, the Brazilian Highlands, Pacific Mountain System, and Intermontane of conterminous USA are other decreasing hotspots in which human footprint and decreasing precipitation collectively affect these changes. Furthermore, results clearly show that anthropogenic influence is low in the northern and mountainous areas, and storage changes have a linear relationship with precipitation. In contrast, intense human climate interaction influences lake changes in plains areas and arid/temperate climates.

Bio‐inspired synthesis of bio‐hydroxyapatite/synthetic hydroxyapatite hybrid nanosystems

AbstractThe current study focuses on the synthesizing of novel hybrid nanosystems of bio‐hydroxyapatite (BioHAp)/synthetic‐hydroxyapatite (HAp‐Syn). Bio‐HAp was defatted, deproteinized, and then sonicated to obtain nanoparticles (nBioHAp). Hybrid nanosystems (HNS) were synthesized by wet chemical precipitation using nBioHAp as nucleation sites and applying four different precipitation times of 45, 90, 135, and 180 min. X‐ray diffraction (XRD) showed that the patterns of the nBioHAp and HAp‐Syn samples have broadened diffraction peaks due to simultaneous elastic and inelastic scattering. Their crystallite size is about 25 nm, while the hybrid nanosystems have a size between 35 and 40 nm. Fourier‐transform infrared spectroscopy (FT‐IR) revealed the main groups associated with hydroxyapatite (PO32−, OH−, and CO32−), and the nanometer character of the crystals was demonstrated by studying the full width at half maximum (FWHM) of the spectra. Scanning electron microscopy (SEM) revealed the differences between the morphologies of nBioHAp and HAp‐Syn. The shape of HNS resembled that of biogenic HAp, which was confirmed by transmission electron microscopy (TEM). Inductively coupled plasma spectroscopy (ICP‐OES) and energy dispersive X‐ray spectroscopy (EDS) were used to confirm the elemental composition of Mg, Na, K, and Zn as minority ions.