Analysis and Assessment on the Heavy Metals in a Severely Degraded Subtropical Red Soil Region

5 different forests of Pinus massoniana, Schima superba, Liquidambar formosana, P. massoniana × S. superba, P. massoniana × L. formosana as the research object were set up to study the Cr, Cu and Zn content of degraded red soil region in subtropics. The soil heavy metal pollution degree was evaluated by national environmental quality standard (II class). The results showed that three soil metals of P. massoniana × S. superba were the highest, and the soil metals enrichment ability was strong. The order of single factor pollution index of metal elements was Cu (1.38) > Cr (0.81) > Zn (0.42), and moderately pollution, pollution warning and no pollution, respectively. There was no significant correlation between three soil heavy metals and soil total carbon (TC), total nitrogen (TN) and total phosphorus (TP). These results suggested that the accumulation of heavy metal elements was not derived from the parent material of soil. There was a significant positive correlation between the three metal elements which indicated that the sources of the three elements were similar. The structural equation model showed that the direct and indirect effects among the influencing factors ultimately affected the activity of heavy metals by cascade effects.

Microplastic and Heavy Metals Distributions in Urban Rivers Sediments,China

This study investigated the distribution of microplastics and heavy metals,along with the interaction between the two in the sediments of urban rivers in China.Results showed that the abundance of microplastics ranged from 2412±187.5 to 7638±1312items kg^(-1)dry sediment across different survey stations,with an average abundance at(4388±713)items kg^(-1)dry sediment.Upon further categorization,it was found that transparent fragments were the primary color and type of microplastics present.The potential ecological risk index(RI)of heavy metals in sediments suggested a low level of ecological risk within a majority of the urban rivers studied.Cd was identified as the main potential ecological risk factor in the sediments of the studied areas.There was a relatively good significant linear relationship between the RI of heavy metals and the abundance of microplastics,bolstering the linkage between these two environmental pollutants.However,the concentrations of heavy metals in microplastics were not dependent on their corresponding contents in sediments.In fact,the concentration of Cu,Cd,and As in microplastics were higher than those in the sediments.This finding confirmed that microplastics could serve as carriers of heavy metals and introduce potential risks to aquatic wildlife and human through the food chain.

Magnetism, heat capacity, magnetocaloric effect, and magneto-transport properties of heavy fermion antiferromagnet CeGaSi

We synthesize high-quality single crystal of CeGaSi by a Ga self-flux method and investigate its physical properties through magnetic susceptibility,specific heat and electrical resistivity measurements as well as high pressure effect.Magnetic measurements reveal that an antiferromagnetic order develops below T_(m)~10.4 K with magnetic moments orientated in the ab plane.The enhanced electronic specific heat coefficient and the negative logarithmic slope in the resistivity of CeGaSi indicate that the title compound belongs to the family of Kondo system with heavy fermion ground states.The max magnetic entropy change-ΔS_(M)^(max)(μ_(0)H⊥c,μ_(0)H=7 T) around T_(m) is found to reach up to 11.85 J·kg^(-1)·K^(-1).Remarkably,both the antiferromagnetic transition temperature and-ln T behavior increase monotonically with pressure applied to 20 kbar(1 bar=10~5 Pa),indicating that much higher pressure will be needed to reach its quantum critical point.

Heavy metal pollution of river water and eco-friendly remediation using potent microalgal species

Pollution of rivers is mainly caused by anthropogenic activities such as discharge of effluent from industrial facilities,maintenance of sewage/effluent treatment plants,and dumping of solid waste on river banks.This study dealt with the pollution issues of the Cooum River in the well-known city of Chennai in South India.Water samples from 27 locations were collected and analyzed for 12 elements,including Ba,B,and Al,as well as heavy metals such as Pb,Cr,Mn,Fe,Co,Ni,Cu,Zn,and Cd.The samples showed levels of these elements that exceeded World Health Organization recommendations.Pearson correlation analysis revealed the inter-dependency among elements,and the contribution of each element based on factor loadings showed its percentage contribution compared to others.Water samples from six significant locations were chosen for remediation with three algae:Chlorella vulgaris,Scenedesmus dimorphus,and Phormedium sp.The uptake of pollutants led to the continuous growth of algae during the incubation period of 15 d,effectively removing heavy metals from the river water.The increasing levels of algal counts and the chlorophyll a content confirmed the algal growth during the incubation period,followed by a declining stage after the incubation period.The scanning electron microscopic images of algae before and after the remediation showed no remarkable modification of morphological patterns.This study showed that the uptake of heavy metals using algae is an effective water pollution remediation measure,making the process practicable in the field on a large scale in the near future.

Relativistic Heavy Ion Collider and the Large Hadron Collider for Heavy Ion Fusion

Heavy Ion Fusion makes use of the Relativistic Heavy Ion Collider at Brookhaven National Lab and the Large Hadron Collider in Geneva, Switzerland for Inertial Confinement Fusion. Two Storage Rings, which may or may not initially be needed, added to each of the Colliders increases the intensity of the Heavy Ion Beams making it comparable to the Total Energy delivered to the DT target by the National Ignition Facility at the Lawrence Livermore Lab. The basic Physics involved gives Heavy Ion Fusion an advantage over Laser Fusion because heavy ions have greater penetration power than photons. The Relativistic Heavy Ion Collider can be used as a Prototype Heavy Ion Fusion Reactor for the Large Hadron Collider.

Uniformity Control of Scanned Beam in 300 MeV Proton and Heavy Ion Accelerator Complex at SESRI

In recent years,heavy ion accelerator technology has been rapidly developing worldwide and widely applied in the fields of space radiation simulation and particle therapy.Usually,a very high uniformity in the irradiation area is required for the extracted ion beams,which is crucial because it directly affects the experimental precision and therapeutic effect.Specifically,ultra-large-area and high-uniformity scanning are crucial requirements for spacecraft radiation effects assessment and serve as core specification for beamline terminal design.In the 300 MeV proton and heavy ion accelerator complex at the Space Environment Simulation and Research Infrastructure(SESRI),proton and heavy ion beams will be accelerated and ultimately delivered to three irradiation terminals.In order to achieve the required large irradiation area of 320 mm×320 mm,horizontal and vertical scanning magnets are used in the extraction beam line.However,considering the various requirements for beam species and energies,the tracking accuracy of power supplies(PSs),the eddy current effect of scanning magnets,and the fluctuation of ion bunch structure will reduce the irradiation uniformity.To mitigate these effects,a beam uniformity optimization method based on the measured beam distribution was proposed and applied in the accelerator complex at SESRI.In the experiment,the uniformity is successfully optimized from 75%to over 90%after five iterations of adjustment to the PS waveforms.In this paper,the method and experimental results were introduced.

Nanoscale Zero-Valent Iron(nZVI)for Heavy Metal Wastewater Treatment:A Perspective

Industries such as non-ferrous metal smelting discharge billions of gallons of highly toxic heavy metal wastewater(HMW)worldwide annually,posing a severe challenge to conventional wastewater treatment plants and harming the environment.HMW is traditionally treated via chemical precipitation using lime,caustic,or sulfide,but the effluents do not meet the increasingly stringent discharge standards.This issue has spurred an increase in research and the development of innovative treatment technologies,among which those using nanoparticles receive particular interest.Among such initiatives,treatment using nanoscale zero-valent iron(nZVI)is one of the best developed.While nZVI is already well known for its site-remediation use,this perspective highlights its application in HMW treatment with metal recovery.We demonstrate several advantages of nZVI in this wastewater application,including its multifunctionality in sequestrating a wide array of metal(loid)s(>30 species);its capability to capture and enrich metal(loid)s at low concentrations(with a removal capacity reaching 500 mg·g^(-1)nZVI);and its operational convenience due to its unique hydrodynamics.All these advantages are attributable to nZVI’s diminutive nanoparticle size and/or its unique iron chemistry.We also present the first engineering practice of this application,which has treated millions of cubic meters of HMW and recovered tons of valuable metals(e.g.,Cu and Au).It is concluded that nZVI is a potent reagent for treating HMW and that nZVI technology provides an eco-solution to this toxic waste.

Characterization of Nutrients,Heavy Metals,Petroleum and Their Impact on Phytoplankton in Laizhou Bay:Implications for Environmental Management and Monitoring

The Laizhou Bay(LB)represents a substantial ecological area that is vulnerable to human activities and confronts diverse environmental challenges.This study provides a comprehensive characterization of nutrients,petroleum,heavy metals,and phytoplankton community structure across seven distinct areas in LB.The results indicate relatively high concentrations of NO_(2)-N,SiO_(4)-Si,and NO_(3)-N in the Southwest Laizhou Bay(SWLB)and Huanghe River Estuary(HRE).In contrast,the East Laizhou bay(ELB)and the North of Huanghe River Estuary(NHRE)exhibit the highest concentrations of heavy metals(As,Cr and Hg).The areas with high phytoplankton density and community diversity are mainly located in the SWLB.After adjusting for basic environmental factors,phytoplankton density and Margalef richness index D are significantly associated with nutrients(NO_(3)-N,NO_(2)-N,NH_(4)-N,SiO_(4)-Si),and heavy metal(Cr)concentrations.We highlight that,in addition to Xiaoqinghe River,nutrients brought by the Mihe River in the SWLB and heavy metal(Cr)pollution in the ELB resulting from industrial and mining activities along the coast significantly influence phytoplankton growth and community structure.Therefore,it is recommended that more monitoring and management efforts be focused on these regions in the future.

Accumulation of Heavy Metals in Maga-Pouss Rice Fields (Far-North Region, Cameroon) and Transfer to Rice Grains

Monitoring of heavy metals contamination of agricultural products and their transfer and bioaccumulation in crops like rice has become a hot topic worldwide over the last two decades. The present study was carried out to determine the accumulation of heavy metals in rice fields and their transfer to rice grains. Soil, irrigation water and rice grains samples were gathered in Maga-Pouss, Far-North, Cameroon. Concentrations of six heavy metals (lead, cadmium, zinc, copper, iron and mercury) were evaluated by Atomic Absorption Spectrophotometer (AAS). Mercury was not detected in this study. Average concentrations of metals were in this order (in mg/kg): Fe (188.60 ± 97.06) > Pb (63.63 ± 7.11) > Cd (2.59 ± 0.29) > Zn (1.10 ± 1.05) > Cu (0.80 ± 0.73) in water and Pb (105.50 ± 31.11) > Fe (105.50 ± 31.11) > Cu (45.93 ± 14.39) > Zn (22.52 ± 6.40) > Cd (3.15 ± 0.49) in soil. Water in Maga-Pouss rice fields appears to be more harmful than the soil, notably for lead, cadmium and copper. In rice grains, heavy metals were found in this order (mg/kg): Fe (188.01 ± 82.62) > Cu (27.20 ± 0.00) > Zn (23.61 ± 12.42) > Pb (19.50 ± 19.91) > Cd (2.02 ± 1.05). The mean bioconcentration factor (BCF) of metals from soil to rice grains was in the following order: Fe (2.60) > Zn (1.05) > Cd (0.64) > Cu (0.59) > Pb (0.18). From water to rice grains, the order is: Cu (37.26) > Zn (22.49) > Cd (6.97) > Pb (2.74) > Fe (1.94). Rice field pH and electrical conductivity favored the uptake of lead, copper and cadmium by rice grains. The findings of this study will be good documentation for risk assessment, and decision-making by environmental managers in this region.

Spatio-Temporal Characteristics of Heavy Precipitation Forecasts from ECMWF in Eastern China

This study examines the spatio-temporal characteristics of heavy precipitation forecasts in eastern China from the European Centre for Medium-Range Weather Forecasts(ECMWF) using the time-domain version of the Method for Object-based Diagnostic Evaluation(MODE-TD). A total of 23 heavy rainfall cases occurring between 2018 and 2021 are selected for analysis. Using Typhoon “Rumbia” as a case study, the paper illustrates how the MODE-TD method assesses the overall simulation capability of models for the life history of precipitation systems. The results of multiple tests with different parameter configurations reveal that the model underestimates the number of objects’ forecasted precipitation tracks, particularly at smaller radii. Additionally, the analysis based on centroid offset and area ratio tests for different classified precipitation objects indicates that the model performs better in predicting large-area, fast-moving, and longlifespan precipitation objects. Conversely, it tends to have less accurate predictions for small-area, slow-moving, and shortlifespan precipitation objects. In terms of temporal characteristics, the model overestimates the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. In terms of temporal characteristics, the model tends to overestimate the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. Overall, the model provides more accurate predictions for the duration and dissipation of precipitation objects with large-area or long-lifespan(such as typhoon precipitation) while having large prediction errors for precipitation objects with small-area or short-lifespan. Furthermore, the model’s simulation results regarding the generation of precipitation objects show that it performs relatively well in simulating the generation of large-area and fast-moving precipitation objects. However, there are significant differences in the forecasted generation of small-area and slow-moving precipitation objects after 9 hours.

Impacts of Future Changes in Heavy Precipitation and Extreme Drought on the Economy over South China and Indochina

Heavy precipitation and extreme drought have caused severe economic losses over South China and Indochina(INCSC)in recent decades.Given the areas with large gross domestic product(GDP)in the INCSC region are distributed along the coastline and greatly affected by global warming,understanding the possible economic impacts induced by future changes in the maximum consecutive 5-day precipitation(RX5day)and the maximum consecutive dry days(CDD)is critical for adaptation planning in this region.Based on the latest data released by phase 6 of the Coupled Model Intercomparison Project(CMIP6),future projections of precipitation extremes with bias correction and their impacts on GDP over the INCSC region under the fossil-fueled development Shared Socioeconomic Pathway(SSP5-8.5)are investigated.Results indicate that RX5day will intensify robustly throughout the INCSC region,while CDD will lengthen in most regions under global warming.The changes in climate consistently dominate the effect on GDP over the INCSC region,rather than the change of GDP.If only considering the effect of climate change on GDP,the changes in precipitation extremes bring a larger impact on the economy in the future to the provinces of Hunan,Jiangxi,Fujian,Guangdong,and Hainan in South China,as well as the Malay Peninsula and southern Cambodia in Indochina.Thus,timely regional adaptation strategies are urgent for these regions.Moreover,from the sub-regional average viewpoint,over two thirds of CMIP6 models agree that maintaining a lower global warming level will reduce the economic impacts from heavy precipitation over the INCSC region.

Effects of Initial and Boundary Conditions on Heavy Rainfall Simulation over the Yellow Sea and the Korean Peninsula:Comparison of ECMWF and NCEP Analysis Data Effects and Verification with Dropsonde Observation

This study evaluated the simulation performance of mesoscale convective system(MCS)-induced precipitation,focusing on three selected cases that originated from the Yellow Sea and propagated toward the Korean Peninsula.The evaluation was conducted for the European Centre for Medium-Range Weather Forecasts(ECMWF)and National Centers for Environmental Prediction(NCEP)analysis data,as well as the simulation result using them as initial and lateral boundary conditions for the Weather Research and Forecasting model.Particularly,temperature and humidity profiles from 3D dropsonde observations from the National Center for Meteorological Science of the Korea Meteorological Administration served as validation data.Results showed that the ECMWF analysis consistently had smaller errors compared to the NCEP analysis,which exhibited a cold and dry bias in the lower levels below 850 hPa.The model,in terms of the precipitation simulations,particularly for high-intensity precipitation over the Yellow Sea,demonstrated higher accuracy when applying ECMWF analysis data as the initial condition.This advantage also positively influenced the simulation of rainfall events on the Korean Peninsula by reasonably inducing convective-favorable thermodynamic features(i.e.,warm and humid lower-level atmosphere)over the Yellow Sea.In conclusion,this study provides specific information about two global analysis datasets and their impacts on MCS-induced heavy rainfall simulation by employing dropsonde observation data.Furthermore,it suggests the need to enhance the initial field for MCS-induced heavy rainfall simulation and the applicability of assimilating dropsonde data for this purpose in the future.

Abnormal Thyroid Stimulating Hormone Level and Heavy Menstrual Bleeding

Heavy Menstrual Bleeding is one of the common Gynaecological issues. There are several causes. Some of the women presented with these issues found to have underling thyroid abnormality which was not discovered earlier. This research tries to find the prevalence of the Thyroid Disorder among the women present with Heavy menstrual bleeding in Sri Lankan women.

Assessment of Heavy Metals Contamination of Topsoil and Street Dust around Cement Factory in Southern Jordan

Evaluation of assessment of the metal processes governing the metals distribution in soil and dust samples is very significant and protects the health of human and ecological system. Recently, special attention has given to the assessment of metals pollution impact on soil and dust within industrial areas. This study aims to assess the metal contamination levels in the topsoil and street dust around the cement factory in Qadissiya area, southern Jordan. The levels of seven metals (namely Fe, Zn, Cu, Pb, Cr, Cd, and Mn) were analyzed using Flame Atomic Absorption Spec-trophotometer (FAAS) to monitor, evaluate, and to compare topsoil and road dust pollution values of metals of the different types of urban area. The physicochemical parameters which believed to affect the mobility of metals in the soil of the study area were determined such as pH, EC, TOM, CaCO3 and CEC. The levels of metal in soil samples are greater on the surface but decrease in the lower part as a result of the basic nature of soil. The mean values of the metals in soil can be arranged in the following order: Zn > Pb > Mn > Fe > Cu > Cr > Cd. The relatively high concentration of metals in the soil sample was attributed to anthropogenic activities such as traffic emissions, cement factory and agricultural activities. Correlation coefficient analysis and the spatial distribution of indices and the results of statistical analysis indicate three groups of metals: Fe and Mn result by natural origin, Zn, Pb, Cu and Zn result by anthropogenic origin (mainly motor vehicle traffic and abrasion of tires) while Cd is mixed origin. The higher content level values of metals of anthropogenic source in soil samples indicate that it is a source of contamination of air in the studied area. .

Evaluation of Agricultural Contamination Level by Heavy Metals and Pesticides in Sediments of Rivers and Water Bodies for Shrimp Fishing in the Lower Ouémé: Case of the Aguigadji, Ahlan and Sele Stations in Benin

This study assessed sediment contamination by heavy metals and pesticide active ingredients linked to chemical inputs used in agricultural activities in the lower Ouémé. Pesticide residues from the organochlorine, pyrethroid and organophosphorus families were investigated by gas chromatography, and heavy metals (Cd, Pb, As, Ni, Zn, Fe, Mg, Cr and Hg) by atomic absorption spectrophotometry. The metallic pollution indices, the contamination factor (CF) and the ecological risk index were calculated. The results revealed 8 active ingredients in the rainy season and 9 in the dry season. Glyphosate was the active ingredient with the highest concentration at all stations, 9.65 ± 0.84 mg/kg recorded in the dry season at the Aguigadji station. All glyphosate values were above the EQS. DDT, Atrazine and Endosulfan also showed high concentrations in the dry and rainy seasons. Emamectin, Abamectin and Lambda Cyhalothrin also showed high concentrations in the dry season at Aguigadji, Ahlan and Sele. Only glyphosate was recorded at the control station (Toho), but in very low concentrations. Lead showed the highest concentrations at all the stations, 265.96 ± 21.02 mg/Kg in the rainy season and 255.38 ± 79.09 mg/Kg in the dry season, all detected at the Aguigadji station and above the EQS. Zn, Ni, Fe, Cu and Cr were all representative in both the dry and rainy seasons at the contaminated stations. Manganese showed high concentrations in the rainy season. Pb showed very high contamination (FC ≥ 6) at the Aguigadji and Ahlan stations and significant contamination (3 ≤ FC 6) at the Sele station in both the rainy and dry seasons. Ni, Hg and Cd, showed either moderate or significant contamination at the contaminated stations. The risk values showed a considerable ecological Ri (190 ≤ Ri < 380) in the rainy season and a moderate ecological Ri (95 ≤ Ri < 190) in the dry season at these contaminated stations.

Heavy Metal Levels and Ecological Risk in Crude Oil-Contaminated Soils from Okpare-Olomu, Niger Delta, Nigeria

Crude oil spills have inflicted extensive disruption upon the Niger Delta ecosystem, resulting in crop loss and severe environmental damage. Such spills exacerbate heavy metal concentration within soil due to the presence of metallic ions. The Okpare-Olomu community has borne the brunt of crude oil pollution from illicit bunkering, sabotage, and equipment malfunction. This study targets an evaluation of ecological hazards linked to heavy metals (HMs) in crude oil impacted agriculturally soils within Okpare-Olomu in Ughelli South LGA of Delta State. In this study, 24 topsoil samples were obtained from areas affected by crude oil pollution;the heavy metal content was evaluated through atomic absorption spectrometry. The concentration ranges for HMs (mg/kg) in soil were: 24.1 - 23,174 (Cu);0.54 - 37.1 (Cd);9.05 - 54 (Cr);12 - 174 (Ni);18.5 - 8611 (Pb);and 148 - 9078 (Zn) at a soil depth of 0 - 15 cm. Notably, metal concentrations were recorded to be above permissible World Health Organization limits. Predominantly, Zn and Pb recorded higher heavy metal concentration when compared to other heavy metals analysed, notably at sampling points PT7 through PT24. Zinc and Pb contamination exhibited highly significant contamination factors, and contamination severity was evidenced across all sample points, signifying a grave risk level. Pollution load indices indicated pervasive extreme pollution levels. Geoaccumulation indices signaled moderate to strong pollution, mainly by Pb and Zn. Ecological risk assessments revealed variable levels of heavy metal contamination, from low to very high, with potential ecological risk reflecting markedly elevated levels. This study underscores the imperative for soil remediation to rectify ecological imbalances in agriculturally affected soil constituents.

The mechanisms of thermal solidification agent promoting steam diversion in heavy oil reservoirs

At high cycles of steam huff&puff,oil distribution in reservoirs becomes stronger heterogeneity due to steam channeling.Thermal solidification agent can be used to solve this problem.Its solution is a lowviscosity liquid at normal temperature,but it can be solidified above 80℃.The plugging degree is up to 99%at 250℃.The sweep efficiency reaches 59.2%,which is 7.3%higher than pure steam injection.In addition,simultaneous injection of viscosity reducer and/or nitrogen foams can further enhance oil recovery.The mechanism of this technology depends on its strong plugging ability,which changes the flowing pattern of steam to effectively mobilize remaining oil.Viscosity reducer and nitrogen foams further expand the sweep range and extends the effective period.Therefore,thermal solidification agent can plug steam channeling paths and adjust steam flowing direction to significantly enhance oil recovery at high cycles of steam huff&puff.

Non-Destructive Detection and Evaluation of Heavy Metal Pollution in Tailings Reservoir

Heavy metal pollution is a negative effect generated in the process of utilizing non-ferrous mineral. Studies about heavy metal migration detection are very important. A new method for rapid detection of heavy metal migration based on ground penetrating radar (GPR) was provided. Comparative tests were studied from field to lab with GPR and X-ray fluorescence analysis (XRF). A tailings reservoir in the Xiangjiang River basin at Hunan Province was taken as experimental site. The downward transfer rule of heavy metal migration was confirmed through tests on systematically arranged survey lines and sampling points in tailings site. Results showed: 1) Through GPR image recognition, tailings reservoir had 3 layers. Reclaimed soil layer (the first layer) and tailings layer (the second layer) had a clear interface. However, tailings layer (the second layer) and subsoil layer (the third layer) had an obscure interface on radar images. It was concluded that heavy metal component had migrated downwards. 2) Chemical component analysis verified image recognition conclusions. Concentrations of As, Cd and Pb were significantly out of limit, while concentration of Cr was under limit according to analysis results on samples from different depths. 3) Pollution degree was evaluated. Downward migration was the main form of heavy metal migration in tailings site, upward migration occurred through adsorption at the same time.

A Real-time Prediction System for Molecular-level Information of Heavy Oil Based on Machine Learning

Acquiring accurate molecular-level information about petroleum is crucial for refining and chemical enterprises to implement the“selection of the optimal processing route”strategy.With the development of data prediction systems represented by machine learning,it has become possible for real-time prediction systems of petroleum fraction molecular information to replace analyses such as gas chromatography and mass spectrometry.However,the biggest difficulty lies in acquiring the data required for training the neural network.To address these issues,this work proposes an innovative method that utilizes the Aspen HYSYS and full two-dimensional gas chromatography-time-of-flight mass spectrometry to establish a comprehensive training database.Subsequently,a deep neural network prediction model is developed for heavy distillate oil to predict its composition in terms of molecular structure.After training,the model accurately predicts the molecular composition of catalytically cracked raw oil in a refinery.The validation and test sets exhibit R2 values of 0.99769 and 0.99807,respectively,and the average relative error of molecular composition prediction for raw materials of the catalytic cracking unit is less than 7%.Finally,the SHAP(SHapley Additive ExPlanation)interpretation method is used to disclose the relationship among different variables by performing global and local weight comparisons and correlation analyses.

Separation of halogens and recovery of heavy metals from secondary copper smelting dust

The separation of halogens and recovery of heavy metals from secondary copper smelting(SCS)dust using a sulfating roasting−water leaching process were investigated.The thermodynamic analysis results confirm the feasibility of the phase transformation to metal sulfates and to gaseous HF and HCl.Under the sulfating roasting conditions of the roasting temperature of 250°C and the sulfuric acid excess coefficient of 1.8,over 74 wt.%of F and 98 wt.%of Cl were volatilized into flue gas.Approximately 98.6 wt.%of Zn and 96.5 wt.%of Cu in the roasting product were dissolved into the leaching solution after the water leaching process,while the leaching efficiencies of Pb and Sn were only 0.12%and 0.22%,respectively.The mechanism studies indicate the pivotal effect of roasting temperature on the sulphation reactions from various metal species to metal sulfates and the salting out reactions from various metal halides to gaseous hydrogen halides.