Synthetic Precipitation Research Articles

Ball milling of mackinawite and oxalic acid to fabricate an efficient and stable reductive material for remediation of Cr(Ⅵ)-contaminated soil.

Compared with zero-valent iron, iron sulfide has more diverse reactive species and higher reductivity, but it is still prone to be gradually deactivated due to various passivation factors. In this study, a novel reductive material (BMMW@OA) was prepared by ball milling of mackinawite (MW) as raw material and oxalic acid (OA) as modifier, so as to simultaneously improve its reductivity and stability by continuous releasing reductive species and maintaining freshness of the material surface. The BMMW@OA (w/w of MW/OA=4/1) effectively removed Cr(Ⅵ) from water with wide pH adaptability. Compared to the BMMW obtained by direct ball milling of MW, BMMW@OA shows good resistance to air exposure, alkaline environment and scale-forming ions. The Freundlich model can accurately describes the Cr(Ⅵ) removal capacity of BMMW@OA. BMMW@OA continuously releases Fe2⁺ and S2⁻ into aqueous solution, thus maintaining the freshness and reactivity of the material surface. The homogeneous reduction by dissolved Fe2⁺ and the heterogeneous reduction by Fe⁰/Fe2⁺ on the surface of BMMW@OA are two primary mechanisms for the efficient removal of Cr(Ⅵ). Adding 2% BMMW@OA reduced the Cr(Ⅵ) content in soil from 989.826mg/kg to 2.034mg/kg within 2h. The horizontal vibration, toxicity characteristic, and synthetic precipitation leaching procedure tests showed that the Cr(Ⅵ) concentration in the soil leachate was as low as 0.005-0.020mg/L and remained stable in 30d. This study developed a green and economic viable material for remediation of Cr(Ⅵ)-contaminated soil with high efficiency and stability.

Preparation of matrix-matched calibration standards for accurate determination of elemental concentrations in uric acid stones by LA-ICP-MS.

Accurate determination of elemental concentrations in uric acid (UA) stones is crucial for understanding their formation process. However, the lack of matrix-matched calibration standards has limited the application of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) in this field. This study addresses this limitation by preparing a synthetic UA precipitate (UA-1) doped with 17 elements using a recrystallization method. Reference concentrations of these elements were measured using pneumatic nebulization-ICP-MS (PN-ICP-MS) for calibration purposes. The synthetic standard was characterized through 30 random spot analyses, demonstrating a homogeneity of approximately 5%. Using this synthetic standard, a reliable analytical method was developed, achieving limits of detection (LODs) ranging from 0 to 0.42 μg g-1. The method's accuracy, with relative deviations between -8.33% and 0 and correlation coefficients (R2) greater than 0.99, confirms its reliability. Additionally, elemental distribution differences observed across various zones in a real UA stone suggest that this method offers a promising approach for the precise analysis of elemental concentrations in UA stones.

Hydrological Response to Climate Change: McGAN for Multi-Site Scenario Weather Series Generation and LSTM for Streamflow Modeling

This study focuses on the impacts of climate change on hydrological processes in watersheds and proposes an integrated approach combining a weather generator with a multi-site conditional generative adversarial network (McGAN) model. The weather generator incorporates ensemble GCM predictions to generate regional average synthetic weather series, while McGAN transforms these regional averages into spatially consistent multi-site data. By addressing the spatial consistency problem in generating multi-site synthetic weather series, this approach tackles a key challenge in site-scale climate change impact assessment. Applied to the Jinghe River Basin in west-central China, the approach generated synthetic daily temperature and precipitation data for four stations under different shared socioeconomic pathways (SSP1-26, SSP2-45, SSP3-70, SSP5-85) up to 2100. These data were then used with a long short-term memory (LSTM) network, trained on historical data, to simulate daily river flow from 2021 to 2100. The results show that (1) the approach effectively addresses the spatial correlation problem in multi-site weather data generation; (2) future climate change is likely to increase river flow, particularly under high-emission scenarios; and (3) while the frequency of extreme events may increase, proactive climate policies can mitigate flood and drought risks. This approach offers a new tool for hydrologic–climatic impact assessment in climate change studies.

A Localized Quantitative Precipitation Estimation for S-Band Polarimetric Radar in Taiwan

Abstract A polarimetric radar quantitative precipitation estimation (QPE) to estimate the rain rate R from specific attenuation A has been applied in Taiwan’s operational Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system since 2016. A 3-yr (2016–18) drop size distribution (DSD) dataset from an operational Particle Size and Velocity (Parsivel) network was used to derive a localized coefficient as well as the α(K) function in the R(A) scheme for S-band radar, where α is a key parameter in the estimation of A and K is the linear fitted slope of differential reflectivity ZDR versus reflectivity Z. The local drop size distribution data were also used to derive the localized R(Z) and R(KDP) relationships, and the relationships were evaluated using radar observations in heavy rain cases. A synthetic quantitative precipitation estimate combining the localized R(A), R(Z), and R(KDP) relationships is compared to its operational counterpart and showed about 8% reduction in the normalized mean error for the mei-yu cases. Typhoon cases exhibited similar improvements by the localized QPE relationships but showed higher uncertainties than in the mei-yu cases. The higher uncertainties in the typhoon QPE verification were likely due to the stronger winds in typhoons than in the mei-yu events that caused greater mismatches between the radar observations at an altitude and the gauges at the ground. Overall, the results demonstrated advantages of localized radar rainfall relationships derived from the disdrometer data to improve the accuracy of the operational rainfall estimation products. Significance Statement A 3-yr (2016–18) drop size distribution (DSD) dataset from the operational Parsivel network in Taiwan was utilized to localize parameters in the QPE relationships for S-band dual-polarimetric radar. These relationships were evaluated using radar observations in the mei-yu front and typhoon events in Taiwan. The results show that using localized radar rainfall relationships derived from the disdrometer data can enhance the accuracy of the operational rainfall products.

Assessing the mobility of Zn, Pb and Ni during the weathering of Nkana smelter copper slag, Zambia

Mine slag dumps could be point-sources of possible pollutants to the surrounding water and soils. The purpose of this study was to investigate the leaching behavior of zinc, lead and nickel from Nkana copper slag dump of Kitwe in Zambia. To assess the toxicity and hazardous nature of the slag, Bath Leaching EN 12,457–2:2002, Toxicity Characteristic Leaching Procedure (TCLP) and Synthetic Precipitation Leaching Procedure (SPLP) were employed. The results from these techniques revealed that the copper slag was inert in the open or natural environment. Sequential extraction analysis was conducted to analyze the fractionation of the zinc, lead and nickel using a seven-step procedure. The sequential extraction analysis showed that the 3 metals were predominantly present in the residual fraction. The risk assessment code (RAC) showed that zinc and lead's mobility could pose an environmental risk categorized as low risk, with RAC values of 1.31 % and 1.50 %, respectively. Nickel's mobility fell within the no-risk category with a RAC of 0.32 %. Additionally, the effect of pH, particle size and contact time on the release of the 3 metals were investigated. The results showed that the highest concentrations of zinc and nickel were observed for longer period of exposure (>33 days), in acidic environments (pH 2.2 and pH 3.0), for particle size distribution (<75 μm). However, lead leaching was not affected by the variation of pH or particle size distribution but mostly by duration of exposure. X-ray diffraction (XRD) analysis revealed that diopside (CaMgSi2O6) and quartz (SiO2) constitute the primary phases within the sample. It is recommended to limit the exposure of slag material to acidic environments and minimize the fragmentation of the slag into finer particles as these conditions would promote increased release of zinc, lead and nickel to the surrounding environment.

Influence of Pseudomonas aeruginosa-based biopolymer on mitigating soil erosion and heavy metal dispersion

Extreme weather phenomena caused by climate change have exacerbated soil erosion and the subsequent dispersion of pollutants. Pseudomonas aeruginosa is known to contribute to the remediation of polluted water and reduce the geochemical mobility of heavy metals in contaminated soil. However, studies on the influence of biopolymers produced by soil microbes and P. aeruginosa on physical soil properties and soil erosion are limited. We aimed to investigate the influence of soil microbes on the mitigation of soil erosion and geochemical dispersion of heavy metals using a naturally occurring microbial substance, P. aeruginosa-based biopolymer (PBB). The PBB comprised carboxyl, hydroxyl, and amine surface functional groups; consequently, the biopolymer effectively sequestered Cd (maximum sorption capacity qm = 45.7 mg/g), Cu (qm = 26.7 mg/g), Pb (qm = 64.9 mg/g), and Zn (qm = 26.1 mg/g) in the solution. The PBB amendment of the soil improved the physical properties associated with soil erosion, increasing soil aggregation stability and shear strength by 41.6% and 36.8%, respectively. The extraction of heavy metals from soil via synthetic precipitate leaching decreased by 54.2% following the PBB amendment, and a negative correlation was observed between soil aggregate stability and heavy metal extraction, indicating that this microbial substance could immobilize pollutants by adsorbing cationic metal ions and inhibiting water-induced disaggregation. In the soil erosion experiments, soil loss and heavy metal extraction decreased by 70.9% and 43.8%, respectively, following the PBB amendment. These aggregation and sorption effects of the PBB underscore the potential of soil microbes to mitigate soil erosion and immobilize the geochemical dispersion of heavy metals, thereby contributing to the conservation of soil and water quality in areas surrounding contaminated slopes and heavy metal-contaminated areas, such as cut slopes, agricultural fields, mine dumps, and dams.

Mineralogy and environmental geochemistry of copper slag from Butte, Montana

Herein we characterize the mineralogy, chemical composition, and environmental geochemistry of slag formed by historic (1880s to circa 1910) smelting of the copper-rich lodes of Butte, Montana. The air-cooled slag exists as monolithic “walls” that border Silver Bow Creek, the headwaters of the upper Clark Fork River Superfund site. The slag is mainly comprised of fayalite, hedenbergite, wollastonite, magnetite, and glass. Zinc is present at per cent levels in all of these phases. The overall high zinc content of the slag is partly due to the polymetallic character of the Butte ore bodies. Copper occurs mainly as tiny spheres, or “prills”, which are remnants of the molten Cu-sulfide matte that failed to separate from the slag during smelting. Minerals in the prills include bornite, chalcopyrite, chalcocite, pyrrhotite, pyrite, sphalerite, galena, elemental copper, and elemental silver. The prills are variably oxidized along shrinkage cracks that penetrate into the enclosing slag matrix. Secondary minerals, including hydrous ferric oxide and ferric clay, coat the cracks. Where the cracks meet the surface of the slag, secondary encrustations of calcite, Fe-Mn oxyhydroxides, and mixed Ca-Cu-Zn-Mn-Al-Fe sulfates have locally accumulated. Acid-base accounting tests show that the unweathered slag is non-acid-generating, with the acid potential from Fe-Cu sulfides offset by the neutralization potential of the Ca-Fe silicates (olivine, pyroxene). Interaction of the slag with synthetic precipitation (SPLP tests) confirms the slag's ability to buffer pH to values >8. Nonetheless, the SPLP leachate solutions contain ppb levels of copper, arsenic, zinc, and lead that approach or exceed current regulatory standards for protection of aquatic life (Cu, Pb, Zn) and human health (As). Leaching experiments using Silver Bow Creek water show an increase in dissolved As and W, but variable results for Cu, Pb, and Zn. Leaching of the secondary sulfate-salt deposits produced much higher concentrations of dissolved metals and metalloids which could be a source of contamination to Silver Bow Creek during heavy rain events. Based on bulk analyses, some metals in the slag, including Fe, As, Co, Mn, Pb, Zn, and W, exceed USEPA screening levels for residential and/or urban soils. Leachates containing organic acids (TCLP tests) show Pb concentrations that approach levels for the slag to be classified as hazardous waste. Rather than removing the slag walls, which have value as a form of industrial architecture, an alternate remedy currently under evaluation is to divert Silver Bow Creek around the smelter site and preserve the slag as part of a non-motorized recreational trail system in the reclaimed Butte-Anaconda mine-scape.

Using waste to treat waste: Utilizing pickling liquor for detoxification and extraction of valuable elements from electroplating sludge

Addressing the urgent need for sustainable solutions in waste management, this study focuses on the pivotal task of recycling heavy metals from electroplating sludge (ES), a critical issue both environmentally and economically. The research introduces a novel leaching process utilizing pickling liquor as a reagent to extract valuable metals from the sludge. Key parameters such as agitation speed, solid to liquid ratio (S/L), temperature, and duration were examined to optimize the leaching rate. Results revealed impressive extraction rates, with 92.33 % Cr, 89.49 % Cu, and 89.59 % Ni extracted within 120 min from S/L 10 g/L, at 300 rpm, and 25 °C. However, it was noted that increasing temperature negatively impacted the leaching rate and led to the formation of undesirable compounds. X-ray diffraction (XRD) analysis identified gypsum and potassium jarosite as predominant compounds formed on the leaching residues at different temperatures of 25 °C and 45 °C. Field emission scanning electron microscopy (FE-SEM) illustrated significant morphological changes in the residues, indicating the influence of temperature on compound formation. Additionally, environmental risk assessment of the residues was conducted using synthetic precipitation leaching procedure (SPLP) and toxicology characteristic leaching procedure (TCLP) methods. In conclusion, this research underscores the promising potential of the developed leaching process using pickling liquor to reclaim valuable metals from ES. By optimizing parameters and assessing environmental risks, this study contributes to advancing environmentally sound practices in industrial waste management.

Sustainable reuse of modified incineration sewage sludge ash (M-ISSA) for stabilization of highly As-contaminated soil

Arsenic (As) is an environmental hazardous contaminant, seriously threatening human health. Chemical activation can effectively enhance As adsorption performance of incinerated sewage sludge ash (ISSA). Through modification, the iron (mainly present as hematite) in the ISSA was rearranged to KFeO2. Based on the results of the present study, addition of modified ISSA (M-ISSA) in contaminated soil had a positive effect on As immobilization. A set of laboratory batch experiments including toxicity characteristic leaching procedure (TCLP), synthetic precipitation leaching procedure (SPLP), and sequential extraction procedure (SEP) were carried out to investigate effects of M-ISSA dosages and curing time on immobilization of As contaminated soil (100, 500, 1000 mg As/kg soil). Results indicated that a higher addition amount of M-ISSA enhanced the effectiveness of stabilization and significantly reduced the As leachability after a stabilization period of 28 d. Particularly, in 1000 mg As/kg soil, M-ISSA reduced the labile As concentration in the TCLP test from 21.45 to 0.73 mg/L and in the SPLP test from 27.75 mg/L to 7.83 mg/L. M-ISSA transformed As in soil to more stable forms that were bounded to amorphous iron hydrous oxides. The number of stable fractions saw a sharp rise from 31% to 60%, when the M-ISSA addition was 5%. Different characterizations were conducted including X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and scanning electron microscope (SEM), in order to demonstrate the stabilization behavior and mechanism of As and M-ISSA. The main stabilization mechanism was associated with adsorption and coprecipitation processes. Overall, this study proposed a novel recycling method for ISSA that could be chemically modified into a reliable and efficient additive for the immobilization of As contaminated soil.

A Novel Mathematical Investigation of Synthetic Precipitation Employing Diverse Variable -Order Non-linear Fractional Derivatives

An inadequate rainfall pattern results in water scarcity, groundwater depletion, pollution escalation, and ecological disruption. Addressing these challenges, comprehensive water management strategies will be necessary to ensure sustainability. This paper proposes a nonlinear fractional variable-order model of artificial rain making in the sense of Liouville-Caputo, Caputo-Fabrizio and Atangana –Baleanu fractional derivatives .The existence and uniqueness of fractional solutions has been established and numerical simulations have been carried out to study the influence of different parameters on the process of artificial rainmaking leading to rainfall.

Assessment of Subseasonal-to-Seasonal (S2S) Precipitation Forecast Skill for Reservoir Operation in the Yaque Del Norte River, Dominican Republic

Operational forecasters desire information about how their reservoir and riverine systems will evolve over monthly to seasonal timescales. Seasonal traces of hydrometeorological variables at a daily or sub-daily resolution are needed to drive hydrological models at this timescale. Operationally available models such as the Climate Forecast System (CFS) provide seasonal precipitation forecasts, but their coarse spatial scale requires further processing for use in local or regional hydrologic models. We focus on three methods to generate such forecasts: (1) a bias-adjustment method, in which the CFS forecasts are bias-corrected by ground-based observations; (2) a weather generator (WG) method, in which historical precipitation data, conditioned on an index of the El Niño–Southern Oscillation, are used to generate synthetic daily precipitation time series; and (3) a historical analog method, in which the CFS forecasts are used to condition the selection of historical satellite-based mean areal precipitation (MAP) traces. The Yaque del Norte River basin in the Dominican Republic is presented herein as a case study, using an independent dataset of rainfall and reservoir inflows to assess the relative performance of the methods. The methods showed seasonal variations in skill, with the MAP historical analog method having the strongest overall performance, but the CFS and WG methods also exhibited strong performance during certain seasons. These results indicate that the strengths of each method may be combined to produce an ensemble forecast product.

Evaluating the effectiveness of sulfidated nano zerovalent iron and sludge co-application for reducing metal mobility in contaminated soil

Sewage sludge has long been applied to soils as a fertilizer yet may be enriched with leachable metal(loid)s and other pollutants. Sulfidated nanoscale zerovalent iron (S-nZVI) has proven effective at metal sorption; however, risks associated with the use of engineered nanoparticles cannot be neglected. This study investigated the effects of the co-application of composted sewage sludge with S-nZVI for the stabilization of Cd, Pb, Fe, Zn. Five treatments (control, Fe grit, composted sludge, S-nZVI, composted sludge and S-nZVI), two leaching fluids; synthetic precipitation leaching procedure (SPLP) and toxicity characteristic leaching procedure (TCLP) fluid were used, samples were incubated at different time intervals of 1 week, 1, 3, and 6 months. Fe grit proved most efficient in reducing the concentration of extractable metals in the batch experiment; the mixture of composted sludge and S-nZVI was the most effective in reducing the leachability of metals in the column systems, while S-nZVI was the most efficient for reducing about 80% of Zn concentration in soil solution. Thus, the combination of two amendments, S-nZVI incorporated with composted sewage sludge and Fe grit proved most effective at reducing metal leaching and possibly lowering the associated risks. Future work should investigate the longer-term efficiency of this combination.

What controls the tail behaviour of flood series: rainfall or runoff generation?

Abstract. Many observed time series of precipitation and streamflow show heavy-tail behaviour. For heavy-tailed distributions, the occurrence of extreme events has a higher probability than for distributions with an exponentially receding tail. If we neglect heavy-tail behaviour we might underestimate the magnitude of rarely observed, high-impact events. Robust estimation of upper-tail behaviour is often hindered by the limited length of observational records. Using long time series and a better understanding of the relevant process controls can help with achieving more robust tail estimations. Here, a simulation-based approach is used to analyse the effect of precipitation and runoff generation characteristics on the upper tail of flood peak distributions. Long, synthetic precipitation time series with different tail behaviour are produced by a stochastic weather generator. These are used to force a conceptual rainfall–runoff model. In addition, catchment characteristics linked to a threshold process in the runoff generation are varied between model runs. We characterize the upper-tail behaviour of the simulated precipitation and discharge time series with the shape parameter of the generalized extreme value (GEV) distribution. Our analysis shows that runoff generation can strongly modulate the tail behaviour of flood peak distributions. In particular, threshold processes in the runoff generation lead to heavier tails. Beyond a certain return period, the influence of catchment processes decreases and the tail of the rainfall distribution asymptotically governs the tail of the flood peak distribution. Beyond which return period this is the case depends on the catchment storage in relation to the mean annual rainfall amount.

Utilization of phosphoric acid-modified biochar to reduce vanadium leaching potential and bioavailability in soil

Remediating vanadium (V) polluted soil has garnered widespread attention over the past decade. Yet, few research projects have investigated the stabilization of soil V using modified biochar, so the effects and interacting mechanisms between soil properties and modified biochar for V immobilization and stabilization remain unclear. Hence, this gap is addressed by determining the leaching behavior and mechanisms of soil V on different dosages of phosphoric acid (H3PO4) impregnated biochar (MLBC, 0.5%–4%). The applicability and durability in soil V immobilization was investigated under acid precipitation. The MLBC effect on V bioavailability and mobility was assessed first by CaCl2, Toxicity Characteristic Leaching Procedure (TCLP) and Synthetic Precipitation Leaching Procedure (SPLP) extractions in different periods. The V concentrations significantly reduced in CaCl2, TCLP, and SPLP extract with MLBC at each dosage (30 d), while slight to significant increase in SPLP and TCLP extract V was recorded in a long-term incubation (90 d). Column leaching test further demonstrated the high durability of 4% MLBC in V stabilization under continuous acid exposure. Compared to the control (no-biochar), the accumulated V content in the leaching solution significantly decreased in MLBC-amended soil. Acid soluble fraction of V showed significant negative correlation with both soil organic matter (SOM) and available P, which was positively correlated with pH, suggested that pH, available P and SOM were key factors affecting the bioavailability of V in soil. Moreover, combining with the characterization results of MLBC and amended soil, the results revealed that H3PO4 modified biochar played a vital role on V immobilization and soil improvement by forming electrostatic adsorption, ion exchange, redox reaction or complexation with the increase of functional groups. These revealed an efficient and steady development of soil quality and treatment for soil V contamination, under MLBC operation to soil polluted with exogenous V.

A saturated stochastic simulator: synthetic US Gulf coast tropical cyclone precipitation fields

The space–time fields of rainfall during a hurricane and tropical storm (TC) landfall are critical for coastal flood risk preparedness, assessment, and mitigation. We present an approach for the stochastic simulation of rainfall fields that leverages observed, high-resolution spatial fields of historical landfalling TCs rainfall that is derived from multiple instrumental and remote sensing sources, and key variables recorded for historical TCs. Spatial realizations of rainfall at each time step are simulated conditional on the variables representing the ambient conditions. We use 6 hourly precipitation fields of tropical cyclones from 1983 to 2019 that made landfall on the Gulf coast of the US, starting from 24 h before landfall until the end of the track. A conditional K-nearest neighbor method is used to generate the simulations. The TC attributes used for conditioning are the preseason large-scale climate indices, the storm maximum wind speed, minimum central pressure, the latitude and speed of movement of the storm center, and the proportion of storm area over land or ocean. Simulation of rainfall for three hurricanes that are kept out of the sample: Katrina [2005], Rita [2005], and Harvey [2017] are used to evaluate the method. The utility of coupling the approach to a hurricane track simulator applied for a full season is demonstrated by an out-of-sample simulation of the 2020 season.

Uncertainty Calibration of Passive Microwave Brightness Temperatures Predicted by Bayesian Deep Learning Models

Abstract Visible and infrared radiance products of geostationary orbiting platforms provide virtually continuous observations of Earth. In contrast, low-Earth orbiters observe passive microwave (PMW) radiances at any location much less frequently. Prior literature demonstrates the ability of a machine learning (ML) approach to build a link between these two complementary radiance spectra by predicting PMW observations using infrared and visible products collected from geostationary instruments, which could potentially deliver a highly desirable synthetic PMW product with nearly continuous spatiotemporal coverage. However, current ML models lack the ability to provide a measure of uncertainty of such a product, significantly limiting its applications. In this work, Bayesian deep learning is employed to generate synthetic Global Precipitation Measurement (GPM) Microwave Imager (GMI) data from Advanced Baseline Imager (ABI) observations with attached uncertainties over the ocean. The study first uses deterministic residual networks (ResNets) to generate synthetic GMI brightness temperatures with as little mean absolute error as 1.72 K at the ABI spatiotemporal resolution. Then, for the same task, we use three Bayesian ResNet models to produce a comparable amount of error while providing previously unavailable predictive variance (i.e., uncertainty) for each synthetic data point. We find that the Flipout configuration provides the most robust calibration between uncertainty and error across GMI frequencies, and then demonstrate how this additional information is useful for discarding high-error synthetic data points prior to use by downstream applications.

Newly-development of synthetic MnCO3 and MnO2 precipitate through biologically-induced mineralization for effective adsorption of As(V) in aqueous solution

As(V) is becoming one of the dangerous and toxic chemicals causing the global issue of water pollution. Among several synthesis processes of adsorbent, biomineralization method has shown good potential. This study presented the biologically-induced synthetic Manganese Carbonate Precipitate (BISMCP) through biologically-induced mineralization method and formation change of BISMCP material after calcination process which is becoming MDSMCP. Herein, the potential ability of BISMCP and MDSMCP was performed for removal of As(V) in an aqueous solution. Characterization results showed both materials were successfully synthesized by the biomineralization process. TGA analysis showed the phase transition from MnCO3 to MnO2 significantly at 200–450 ºC. The BET surface area of the as-prepared nanocomposites was found to be 109.006 m2/g (BISMCP) and 91.672 m2/g (MDS-300). EDX analysis showed the elements in the crystal BISMCP and MDSMCP were Mn, C, and O. XRD result of BISMCP and MDSMCP determined the crystal structure, which are close to rhodochrosite (MnCO3) and pyrolusite (MnO2), respectively. Effects of pH, contact time, and varying pollutant concentration were studied in detail. The pHPZC value of BISMCP and MDS-300 was 5.5 and 1.50, respectively. According effect of pH, BISMCP and MDS-300 had better adsorption capacity at pH 6 and 2, respectively. The kinetic study for BISMCP and MDS-300 indicated that well fitted with pseudo-second-order (PSO). The experimental equilibrium data followed the Langmuir isotherm model with a maximum monolayer adsorption capacity of 119.331 mg/g (BISMCP) and 112.107 mg/g (MDS-300). This study implies that BISMCP and MDS-300 are potentially useful adsorbents for the adsorption of As(V).

Evaluation of the effects of L-cysteine addition on the bioleaching of zinc and cadmium from sphalerite flotation concentrate

The primary zinc ore in the world is sphalerite, and roasting-leaching-electrowinning (RLE) is the most typical method of processing. This method has different disadvantages, and bioleaching is an alternative and eco-friendly method for sphalerite treatment. The major drawback of bioleaching is its slow kinetics. In this study, an evaluation of the effects of L-cysteine addition on the bioleaching of zinc and cadmium from a concentrate of sphalerite was investigated in the presence of mixed cultures of mesophilic and moderately thermophilic microorganisms. The results showed that L-cysteine addition increased the dissolution rates of zinc and cadmium while reducing them at higher concentrations. The optimal conditions were achieved by using 0.1 g/L of L-cysteine in mesophilic cultures with zinc recovery of 73.92% and cadmium recovery of 81.45%, respectively. Similarly, zinc recovery was 92.54% in thermophilic cultures, while cadmium recovery was 88.66%. Field emission scanning electron microscopy (FE-SEM) and X-ray diffraction (XRD) analyses have detected the formation of jarosite and elemental sulfur on sphalerite surfaces in mesophilic conditions, as well as ammoniojarosite and elemental sulfur in moderately thermophilic conditions. Fourier transform infrared (FTIR) spectroscopy was employed to identify molecular structures and functional groups on the surface of bioleached residues in mesophilic and moderately thermophilic conditions. To assess the environmental risk of residues, a combination of synthetic precipitation leaching procedure (SPLP) and toxicology characteristic leaching procedure (TCLP) methods were used.

Long-term stability and toxicity effects of three-dimensional electrokinetic remediation on chromium-contaminated soils

The three-dimensional electrokinetic remediation (3D EKR) achieved efficient removal of chromium (Cr) from the soil through mechanisms including electromigration, electroosmosis, and redox reactions. In this study, the long-term stability, leaching toxicity, bioavailability, and phytotoxicity of Cr in remediated soils were systematically analyzed to comprehensively evaluate the effectiveness of the 3D EKR method. The results showed that the concentration of hexavalent chromium (Cr (VI)) in the leachate of the 3D EKR system with sulfidated nano-scale zerovalent iron (S-nZVI) was more than 40% lower than those of the other 3D electrode groups, and the time required to reach the level III standard of groundwater quality criterion in China (0.05 mg/L, GB/T 14848-2017) was significantly shortened. The stabilization of Cr(VI) in contaminated soil after 3D EKR was maintained for 300 pore volumes (PVs), indicating that the treated Cr(VI) had good long-term stability. The leaching toxicity and bioaccessibility of Cr were assessed by the synthetic precipitation leaching procedure (SPLP), the toxicity characteristic leaching procedure (TCLP), and the physiologically based extraction test (PBET). The concentration of Cr(VI) in the SPLP, TCLP, and PBET leachates of the S-nZVI group decreased by more than 25% compared to the other 3D electrode groups, corresponding to the decrease in leaching toxicity and bioavailability of the treated Cr during the 15-day remediation period. In addition, the germination rate of wheat seeds and the average biomass of wheat seedlings in the S-nZVI group under alkaline conditions (EE) were higher than those in the non-polluting group (Blank-OH), indicating that the remediated soil had no obvious toxicity to wheat. In summary, 3D EKR achieved a satisfactory and stable remediation effect on Cr-contaminated soil, especially when using S-nZVI as the 3D electrode.

Scaling and intermittency in time of urban precipitation in Warsaw, Poland

Study regionA network of 25 rain gauges roughly covering an area of 517.2 km2 of Warsaw, in Poland. Study focusScaling and intermittency of data series of rainfall intensity are investigated for each of the network rain gauges using five multifractal framework methods: spectral density analysis, functional box-counting, trace moment, probability distribution/multiple scaling, and double trace moment. Synthetic precipitation series are then generated by means of continuous universal random cascade models. Cascade generators are defined by universal parameters calculated for selected Warsaw rain gauges, or rain gauge clusters displaying similarity of multifractal parameters. The generated synthetic precipitation time series are subject to statistical evaluation by comparing the complementary cumulative distribution function and the intermittency calculated for synthetic versus observed data. Finally, a novel filtering algorithm is proposed to correct the intermittency characteristics of synthetic precipitation time series. New hydrological insightsBased on our analyses, the temporal structure of the recorded Warsaw precipitation time series is found to be a multifractal set characterized by a scaling behaviour over a wide range of scales. Furthermore, it has been observed that most Warsaw rain gauges, have a distinct similarity of multifractal properties. It has also been demonstrated that, for the first time in Poland, the universal continuous cascades could be used in practice for the generation of synthetic rainfall series at fine (1-min) temporal resolution