Identifying interactive effects of spatial drivers in soil heavy metal pollutants using interpretable machine learning models.

The accurate identification of spatial drivers is crucial for effectively managing soil heavy metals (SHM). However, understanding the complex and diverse spatial drivers of SHM and their interactive effects remains a significant challenge. In this study, we present a comprehensive analysis framework that integrates Geodetector, CatBoost, and SHapley Additive exPlanations (SHAP) techniques to identify and elucidate the interactive effects of spatial drivers in SHM within the Pearl River Delta (PRD) region of China. Our investigation incorporated fourteen environmental factors and focused on the pollution levels of three prominent heavy metals: Hg, Cd, and Zn. These findings provide several key insights: (1) The distribution of SHM is influenced by the combined effects of various individual factors and interactions within the source-flow-sink process. (2) Compared with the spatial interpretation of individual factors, the interaction between Hg and Cd exhibited enhanced spatial explanatory power. Similarly, interactions involving Zn mainly demonstrated increased spatial explanatory power, but there was one exception in which a weakening was observed. (3) Spatial heterogeneity plays a crucial role in determining the contributions of environmental factors to soil heavy metal concentrations. Although individual factors generally promote metal accumulation, their effects fluctuate when interactions are considered. (4) The SHAP interpretable method effectively addresses the limitations associated with machine-learning models by providing understandable insights into heavy metal pollution. This enables a comparison of the importance of environmental factors and elucidates their directional impacts, thereby aiding in the understanding of interaction mechanisms. The methods and findings presented in this study offer valuable insights into the spatial heterogeneity of heavy metal pollution in soil. By focusing on the effects of interactive factors, we aimed to develop more accurate strategies for managing SHM pollution.

Identifying influence factors and thresholds of the next day's pollen concentration in different seasons using interpretable machine learning.

The prevalence of pollen allergies is a pressing global issue, with projections suggesting that half of the world's population will be affected by 2050 according to the estimation of the World Health Organization (WHO). Accurately forecasting pollen allergy risks requires identifying key factors and their thresholds for aerosol pollen. To address this, we developed a technical framework combining advanced machine learning and SHapley Additive exPlanations (SHAP) technology, focusing on Beijing. By analyzing meteorological data and vegetation phenology, we identified the factors influencing next-day's pollen concentration (NDP) in Beijing and their thresholds. Our results highlight vegetation phenology data from Synthetic Aperture Radar (SAR), temperature, wind speed, and atmospheric pressure as crucial factors in spring. In contrast, the Normalized Difference Vegetation Index (NDVI), air temperature, and wind speed are significant in autumn. Leveraging SHAP technology, we established season-specific thresholds for these factors. Our study not only confirms previous research but also unveils seasonal variations in the relationship between radar-derived vegetation phenology data and NDP. Additionally, we observe seasonal fluctuations in the influence patterns and threshold values of daily air temperatures on NDP. These insights are pivotal for improving pollen concentration prediction accuracy and managing allergic risks effectively.

[Spatial Distribution of Soil Heavy Metals and Regional Control Strategies in China at Province Level].

It is important to understand the spatial distribution characteristics and health risks of soil heavy metals for the implementation of soil pollution control measures in different levels and regions. Based on the data of 706 core studies in the last 20 years, the spatial distribution characteristics, accumulation degree, and health risks of soil heavy metals in China were analyzed at the provincial level. The results showed that the soil heavy metals had obvious spatial differences on the provincial scale, with an overall trend of "high in the south and low in the north and high in the east and low in the west." The content of heavy metals in the soil of agricultural land and construction land was high, and the rate of exceeding the standard was higher than that of other land types. Soil heavy metal concentrations in most areas of China were higher than the regional background values and were highly cumulative. The accumulation indices were:Cd(1.80)>Pb(0.23)>Cu(0.17)>Zn(-0.05)>As(-0.56)>Cr(-0.69), with more than 85% of the provincial soils reaching moderate levels of Cd pollution. Non-ferrous metal resource-based provinces such as Yunnan, Guizhou, Guangxi, Hunan, and Jiangxi generally had higher soil heavy metal levels than those in other provinces, and local children faced higher cancer risks. Soil pollution in coastal areas such as Fujian, Zhejiang, Jiangsu, and Tianjin mainly originated from industrial production and urbanization construction. High intensity agricultural utilization was an important cause of soil heavy metal accumulation in Henan, Shandong, and Anhui.

Quantification adsorption mechanisms of arsenic by goethite-modified biochar in aqueous solution.

In this study, rice straw biochar (BC), goethite (GT), and goethite-modified biochar (GBC) were prepared and their differences in adsorption characteristics and mechanisms of arsenic were explored to provide theoretical and data reference for future design of modified biochar, aiming to address adsorption mechanism weakness and improve the efficiency of arsenic removal in water. Various characterization methods were employed to evaluate the influence of pH, adsorption kinetics, isotherms, and chemical analyses of the materials. At temperatures of 283 K, 298 K, and 313 K, the maximum actual adsorption capacity followed the order GBC > GT > BC, while at 313 K, the maximum Langmuir adsorption capacity of GBC reached 149.63 mg/g which was 95.92 times that of BC and 6.27 times of GT. Due to precipitation and complexation mechanisms, GBC exhibited more superior arsenic adsorption capacities than BC and GT, contributing to total adsorption ranging from 88.9% to 94.2%. BC was dominated by complexation and ion exchange mechanisms in arsenic adsorption, with contribution proportions of 71.8%-77.6% and 19.1%-21.9%, respectively. In GT, the precipitation mechanism played a significant role in total adsorption, contributing from 78.0% to 84.7%. Although GBC has significant potential for removing arsenic from aqueous solutions, the findings suggest that its ion exchange capacity needs improvement.

Quantitative source apportionment and driver identification of soil heavy metals using advanced machine learning techniques.

The accurate identification of pollution sources is essential for the prevention and control of possible pollution from soil heavy metals (SHMs). However, the positive matrix factorisation (PMF) model has been widely used as a conventional method for pollution source apportionment, and the classification of source apportionment results mainly relies on existing research and expert experience, which can result in high subjectivity in the source interpretation. To address this limitation, a comprehensive source apportionment framework was developed based on advanced machine learning techniques that combine self-organizing mapping and PMF with a gradient boosting decision tree (GBDT) model. Analysis of Cd, Pb, Zn, Cu, Cr, and Ni in 272 topsoils showed that the average contents of six heavy metals were 1.72-13.79 times greater than corresponding background values, among which Cd pollution was relatively serious, with 66.91 % of the sites having higher values than the specified soil risk screening values. The PMF results revealed that 79.43 % of Pb was related to vehicle emissions and atmospheric deposition, 79.32 % of Cd and 38.84 % of Zn were related to sewage irrigation, and 85.97 % of Cr and 85.50 % of Ni were from natural sources. Moreover, the GBDT detected that industrial network density, water network density, and Fe2O3 content were the major drivers influencing each pollution source. Overall, the novelty of this study lies in the development of an improved framework based on advanced machine learning techniques that led to the accurate identification of the sources of SHM pollution, which can provide more detailed support for environmental protection departments to propose targeted control measures for soil pollution.

A comprehensive framework for identifying contributing factors of soil trace metal pollution using Geodetector and spatial bivariate analysis.

The accurate identification of pollution sources is important for controlling soil pollution. However, the widely used Positive matrix factorization (PMF) model generally relies on knowledge and experience to accurately identify pollution sources; thus, this method faces significant challenges in objectively identifying soil pollution sources. Herein, we established a comprehensive source analysis framework using factor identification and geospatial analysis, and revealed the factors contributing to trace metal(loid) (TM) pollution in soil in the Pearl River Delta (PRD), China. Using the PMF model, we initially considered that the PRD may be affected by natural, atmospheric, traffic and industrial, and agricultural sources. Moreover, Geodetector model detected the relationship between TMs and 12 environmental variables based on the strong spatial "source-sink" relationship of pollutants. The parent material and digital elevation model were the key factors predicting the accumulation of Cr, Ni, and Cu. Industries and roads were the most important determinants of Pb, Zn, and Cd, whereas atmospheric deposition was more important for Hg accumulation. The accumulation of As was found to be closely related to agricultural activities such as the application of chemical fertilizers and pesticides. The spatial autocorrelation between soil TM pollution and environmental variables further supports this hypothesis. Overall, the obtained results showed that proposed approach improved the accuracy of source apportionment and provided a basis for soil pollution control.

Residents' Behavioral Intention of Environmental Governance and Its Influencing Factors: Based on a Multidimensional Willingness Measure Perspective.

The rapid development of industrialization has brought about a huge demand for mineral resources, and the mining industry has posed a threat to sustainable land use while promoting economic development. In the context of collaborative governance, residents are an important aspect of land pollution abatement. Therefore, understanding residents' willingness to participate in environmental governance and exploring its influencing factors have important implications for improving the motivation of residents to participate in environmental governance and improve the local habitat. Using the multidimensional willingness measurement data of rural households' perception of mining environment governance around the Dabaoshan mining area in Shaoguan in 2020, based on the extended theory of planned behavior, this study established a multidimensional measurement of willingness, including willingness to participate, willingness to pay, and willingness to mobilize, and used structural equation modeling to explore the factors influencing residents' behavioral intention of environmental governance. The results suggest that behavioral attitudes had a positive effect on willingness to participate and willingness to pay. In addition, subjective norms had no significant effect on willingness to participate but were negatively related to willingness to pay. Although perceived behavioral control had no significant effect on willingness to participate, it had a positive effect on willingness to pay. In addition, the results also show that the willingness to pay and willingness to participate of farmers were positively related to their willingness to mobilize. Based on the above findings, this study proposes some policy implications to improve residents' behavioral intention of land pollution abatement, including strengthening value perception, improving subjective awareness, building communication platforms, and improving personal capacity.

Characterization of soil microbial community activity and structure for reducing available Cd by rice straw biochar and Bacillus cereus RC-1.

The combination of biochar and specific bacteria has been widely applied to remediate Cadmium-contaminated soil. But little is known about how such composites affect the dynamic distribution of metal fractions. This process is accompanied by the alternations of soil properties and microbial community structures. Composite of rice straw biochar and Bacillus cereus RC-1 were applied to investigate its impacts on Cd alleviation and soil microbial diversity and structure. The bacterial/biochar composite treatment decreased the fraction of HOAc-extractable Cd by 38.82%, and increased residual Cd by 23.95% compared to the untreated control. Moreover, compared with the untreated control, the composite treatment significantly increased the soil pH by about 1.5 units, and the activities of catalase, urease and invertase enzymes were increased by 42.39%, 30.50% and 31.20%, respectively. Composite treatment increased soil bacterial and fungal alpha diversity, the relative abundance of Bacillus, Streptomyces, Arthrobacter, and Aspergillus species were also increased. Mantel test and correlation analysis indicated that the effects associated with fungal communities in influencing soil properties were lower than that those of bacterial communities by different treatment. Aggregated boosted tree (ABT) models analysis showed that soil chemical proprieties (as determined by SOM, CEC, AN, etc.,) contributed over 50% of the changes in bacterial and fungal communities by the composite treatment. The co-occurrence network results showed that all treatments enhanced the correlation between OUT groups and improved the possible relationships in the bacterial and fungal communities, especially the interrelationships between bacteria and fungi after the Cd fractions stabilized. These findings provide a new insight to optimal strategies for the remediation of Cd-contaminated soil.

Relative Contribution of Metal Content and Soil Particle Mass to Health Risk of Chromium-Contaminated Soil.

Three soil samples from a chromium (Cr)-contaminated field were classified into five particle fractions (i.e., 0-50 µm, 50-100 µm, 100-250 µm, 250-500 µm, and 500-1000 µm) and were further characterized to study their physicochemical properties and Cr bioaccessibility. The results indicated that the gastrointestinal bioaccessibility estimated by the Solubility Bioaccessibility Research Consortium (SBRC) method was on average 15.9% higher than that by the physiologically based extraction test (PBET) method. The health risk of all samples was within the safe range, and the health risk based on total Cr content may be overestimated by an average of 13.2 times compared to the bioaccessibility-based health risk. The health risk investigated from metal content was mainly contributed by the 50-250 µm fraction, which was 47.5, 50.2, and 43.5% for low-, medium-, and high-level polluted soils, respectively. As for the combined effect, the fractions of 100-250 µm and 500-1000 µm contributed the highest proportion to health risk, which was 57.1, 62.1, and 64.4% for low-level, medium-level, and high-level polluted soils, respectively. These results may further deepen the understanding of health risk assessment and quantify the contribution of the soil particle mass to health risk.

Effect of rice straw biochar on three different levels of Cd-contaminated soils: Cd availability, soil properties, and microbial communities.

Biochar can be effective in immobilizing soil cadmium (Cd), but the difference in its immobilization mechanisms for different levels of Cd-contaminated soils was overlooked. In this study, rice straw biochar (BC) was added to three Cd-contaminated soils following 180 days of incubation, in the process of which the dynamic changes of Cd speciation, soil properties and microbial community diversity were determined. BC could significantly reduce the ratio of acid-soluble in the three soils, especially in light and medium Cd-contaminated soils by more than 20%. The addition of biochar could significantly increase the soil pH, soil organic matter, cation exchange capacity, and the activities of catalase, but decrease the richness and diversity of bacterial communities in all soils. The associations between microbial communities were inhibited in light and medium Cd-contaminated soils, but promoted in heavy Cd-contaminated soils. Furthermore, the main pathway of BC effect on soil Cd availability was also analyzed by partial least squares model (PLS-PM), which indicated that BC indirectly reduced Cd availability mainly by regulating the microbial community in light Cd-contaminated soil, whereas BC directly reduced Cd availability primarily by its own adsorption in medium and heavy Cd-contaminated soils. This research deepened understanding of the mechanisms of stabilization of Cd by biochar for agricultural soils.

Cd and Pb immobilisation with iron oxide/lignin composite and the bacterial community response in soil.

Iron oxide is a natural mineral that generally exists in the form of iron oxide-organic complexes (Fe-OM) in soil. Lignin is a naturally occurring polymer that is considered to be an important part of soil carbon cycling. In this study we prepared a composite material (MGE) with iron oxide and lignin based on the Fe-OM present in the soil. MGE was then applied to remediate Cd and Pb in contaminated soil. The results show that DTPA-Cd and DTPA-Pb levels were reduced by 58.87% and 78.09%, respectively. The bacterial community diversity index decreased in the iron oxide (GE) group, but a slight increase was observed in the MGE group. In terms of species composition in the MGE group, the abundance of Proteobacteria, Gemmatimonadota and Acidobacteriota increased, while the abundance of Bacteroidota, Actinobacteriota and Firmicutes decreased. The outcome in the GE group was the opposite. In the MGE group, HCl-Fe2+, HCl-Fe3+, and pH were significantly higher than in the other groups, indicating that MGE stimulated the growth of iron-reducing bacteria (FeRB) and promoted iron redox reactions. Iron oxide could be reduced to Fe2+ due to the activity of FeRB, and then Fe2+ would be oxidised and hydrolysed, which led to an increase in soil pH. Secondary minerals were formed during this process. With the oxidation of Fe2+ and the formation of secondary minerals, Cd and Pb could be stabilised in the oxides and were not easily released through a co-precipitation mechanism.

Physiological responses and health risks of edible amaranth under simultaneous stresses of lead from soils and atmosphere.

Lead (Pb) is widely distributed in the environment that can impose potential risks to vegetables and humans. In this work, we conducted a pot experiment in Southern China to examine the physiological response and risk of edible amaranth (Amaranthus tricolor L.) under the simultaneous stresses of lead from soil and atmosphere. The results indicate that the lead content of amaranth substantially exceeded China's national standard when Pb concentration from soils and atmosphere was high, and comparing to teenagers and adults, children exposed a higher health risk after consuming the contaminated amaranth. Under the co-stress, the lead in roots of amaranth mainly came from the soil, but the Pb from atmospheric deposition can significantly affect the lead concentration in leaves. While lead from atmospheric deposition is found to promote the growth of amaranth, the stress of lead from the soils shows an inhibitory effect, as indicated by the increase in H2O2 content, the damage in cell membranes, and the limitation in chlorophyll synthesis. The antioxidant system in stems and leaves of amaranth can effectively alleviate the Pb toxicity. However, the stress of high lead concentration from soils can substantially suppress the antioxidant enzyme activity of roots. While it is found that heavy metals in soils can significantly affect the vegetables grown in a multi-source pollution environment, we also call for the attention on the potential health risk imposed by the lead from atmospheric deposition. This study provides an important reference for the prevention and control of crop contamination in multi-source pollution environments.

Magnetic biochars have lower adsorption but higher separation effectiveness for Cd2+ from aqueous solution compared to nonmagnetic biochars.

Magnetic biochars were prepared by chemical co-precipitation of Fe3+/Fe2+ onto rice straw (M-RSB) and sewage sludge (M-SSB), followed by pyrolysis treatment, which was also used to prepare the corresponding nonmagnetic biochars (RSB and SSB). The comparison of adsorption characteristics between magnetic and nonmagnetic biochars was investigated as a function of pH, contact time, and initial Cd2+ concentration. The adsorption of nonmagnetic biochars was better described by pseudo-second-order kinetic model, and the adsorption of RSB and SSB was better described by Langmuir and Freundlich models, respectively. Magnetization of the biochars did not change the applicability of their respective adsorption models, but reduced their adsorption capabilities. The maximum capacities were 42.48 and 4.64 mg/g for M-RSB and M-SSB, respectively, underperforming their nonmagnetic counterparts of 58.65 and 7.22 mg/g for RSB and SSB. Such a reduction was fundamentally caused by the decreases in the importance of cation-exchange and Cπ-coordination after magnetization, but the Fe-oxides contributed to the precipitation-dependent adsorption capacity for Cd2+ on magnetic biochars. The qualitative and quantitative characterization of adsorption mechanisms were further analyzed, in which the contribution proportions of cation-exchange after magnetization were reduced by 31.9% and 12.1% for M-RSB and M-SSB, respectively, whereas that of Cπ-coordination were reduced by 3.4% and 31.1% for M-RSB and M-SSB, respectively. These reductions suggest that for adsorbing Cd2+ the choice of conventional biochar was more relevant than whether the biochar was magnetized. However, magnetic biochars are easily separated from treated solutions, depending largely on initial pH. Their easy of separation suggests that magnetic biochars hold promise as more sustainable alternatives for the remediation of moderately Cd-contaminated environments, such as surface water and agriculture soil, and that magnetic biochars should be studied further.

High-efficiency removal capacities and quantitative adsorption mechanisms of Cd2+ by thermally modified biochars derived from different feedstocks.

Adsorption characteristics of Cd2+ on the three biochars modified by pyrolysis and calcination were investigated that were derived from rice straw (TRSB), chicken manure (TCMB) and sewage sludge (TSSB). The pH effect, adsorption kinetics, isotherms and thermodynamics, and desorption were determined, and qualitative analysis of adsorption mechanisms was performed by SEM, XRD, FTIR and XPS. Maximum adsorption capacities reached 177.28, 96.03 and 74.04 mg/g for TCMB, TRSB and TSSB, respectively, which were higher than that of many previously reported biochars. Even after five adsorption-desorption cycles, TCMB showed the strongest reusability without losing significantly adsorption capacity. This suggested that thermally modified biochars, particularly TCMB, could be a preferred adsorbent for Cd2+. Relative distribution of adsorption mechanisms was examined by direct and indirect calculation, in which the precipitation and cation-exchange dominated the whole chemisorption process, jointly accounting for 84% (TRSB) to 95% (TCMB) of total adsorption. While the complexation was of minor importance in total adsorption accounting for 5%-16%. The relationship of each mechanism with the properties of biochar was also discussed. These provided new insights on the adsorption effectiveness and mechanisms for Cd2+ in the aqueous solution that was critical for evaluating the application of modified biochars.

[Improved Regression Kriging Prediction of the Spatial Distribution of the Soil Cadmium by Integrating Natural and Human Factors].

Mastering the spatial distribution of heavy metals in the soil plays an important supporting role in the scientific formulation of soil pollution risk management and control strategies. Few factors were considered and multiple collinearity between parallel variables existed,resulting in low prediction accuracy. OK (common Kriging method), NRK (regressive Kriging method based on natural factors only), and NARK (regressive Kriging based on natural-human factors)were used to simulate the spatial distribution of soil Cd by selecting 23 natural-artificial influencing factors. The prediction accuracy was evaluated based on an empirical study of the area around Shaoguan Qujiang smelter. The results showed that the above-standard rate of soil cadmium in this area reached 85.93%, and the effect on the spatial heterogeneity of soil cadmium was shown as air emissions from smelters > air emissions from steel plants > pH > organic matter > Euclidean distance to road > Euclidean distance to river. The root-mean-square error and average absolute error of NARK's prediction results for soil cadmium were 26.86% and 30.56% lower than that of the OK method, respectively. The model determination coefficient R2 increased from 0.78 to 0.88. Compared with that of NRK, it was reduced by 24.15% and 24.23% and R2 increased from 0.81 to 0.88. The NRK combining natural and human factors significantly improved the simulation accuracy of the spatial distribution of soil cadmium, and the addition of human factors as auxiliary variables, especially atmospheric point source pollution emissions, greatly contributed to the improvement of the model accuracy.

Cadmium accumulation and physiological response of Amaranthus tricolor L. under soil and atmospheric stresses.

In this study, cadmium (Cd) solution spraying and Cd-contaminated soil pot experiments were conducted to investigate the influence of Cd from atmospheric deposition and soil on the growth, cumulative distribution, chemical morphology, physiological, and biochemical responses of Amaranthus tricolor L. The results indicated that Cd in plants mainly came from soil (92-98%) and was stored in the roots in large quantities while the portion from atmospheric deposition could also effectively increase Cd content in stems and leaves (2-3%). Cd was mainly stored in plant cell walls and would transfer to the soluble part under high-concentration soil stress Cd from atmospheric deposition alone promoted the growth of plants, but high Cd concentrations from soil had the negative influence. The contents of H2O2 and MDA in plants increased under soil and atmospheric Cd stress, indicating that the plant cells were damaged by oxidative stress. The content of antioxidant enzymes such as POD, CAT, SOD, and antioxidants like AsA and GSH increased under low-concentration Cd stress but decreased under elevated stress, suggesting that high Cd-contaminated soil poses severe toxicity on the antioxidant system of the plants. Hence, the accumulation and physiological response of plants under multi-source Cd contamination were mainly affected by high soil Cd concentrations. Though the effect of atmospheric deposition is relatively less, it cannot be ignored.

Removal of Cu and Pb from contaminated agricultural soil using mixed chelators of fulvic acid potassium and citric acid.

This study investigated the application of a specific soil washing method to remove Cu and Pb from contaminated agricultural soil. To develop an efficient leaching agent of heavy metal compounds for use in farmland soil, a mixed chelator (MC) was prepared using potassium fulvic acid (PFA, 3.2%) and citric acid (CIT, 0.16 M) in a volume ratio of 4:1 (PFA:CIT = 4:1); the optimal solid-liquid ratio (S/L = 1:20), initial pH value (4.51) and contact time (360 min) were also explored. Under optimal conditions, the removal efficiencies of MC for Cu and Pb were 42.92% and 50.46%, respectively, both of which performed better than PFA (27.86% of Cu and 17.91% of Pb) and CIT (42.04% of Cu and 41.46% of Pb). The effective states, bioavailability and relative mobilities of Cu and Pb in soil were also efficiently reduced by MC, which also increased the stability of these elements, thereby lowering the risk to soil health. More importantly, MC not only had little effect on the soil physicochemical properties (e.g., pH, organic matter (OM), cation exchange capacity (CEC), ammonium nitrogen (AN), available phosphorus (AP) and rapidly available potassium (AK)), but also improved the restored soil. Furthermore, soil structure, surface elements and the enzyme activity did not exhibit significantly loss. Therefore, MC has great potential for remediating agricultural soil.

Effect of lignosulfonate on the adsorption performance of hematite for Cd(II).

Lignin is a precursor of humus in soil and sediment. Lignin can be separated from vascular plants in the form of lignosulfonate via pulping processes. On the other hand, composites of iron oxide and organic matter can adsorb heavy metals, and thus influence the migration of these heavy metals in the environment. In this paper, a hematite/lignosulfonate composite (HLS) was prepared via coprecipitation to compare the adsorption performance of hematite (α-Fe2O3) toward Cd(II) before and after the incorporation of lignosulfonate (LS). The HLS is found to exhibit a weakly crystalline structure and possess a large number of nanoscale particles. Specific surface area of HLS (291.97 m2/g) is about 11 times that of α-Fe2O3, and the pore volume of HLS (0.22 cm3/g) is twice that of α-Fe2O3. The adsorption of Cd(II) is well illustrated by the pseudo-second-order adsorption kinetics and the initial adsorption rate (h) of HLS is 13.83 times that of α-Fe2O3. The maximum adsorption capacities are significantly improved from 4.89-6.35 mg/g (α-Fe2O3) to 39.03-53.65 mg/g (HLS). A greater affinity and more favorable association between Cd(II) and HLS is observed via fitting models. The incorporation of LS provides HLS with significantly better adsorption properties toward Cd(II) than α-Fe2O3, as is further confirmed by FT-IR and XPS characterization. Fe-O-O-H and Fe-O-H structures as well as more hydroxyl groups are observed, which promote the adsorption performance since the process are mainly influenced by complexation via coordination bonds.

Qualitative and quantitative characterization of adsorption mechanisms for Cd2+ by silicon-rich biochar.

The adsorption characteristics of rice-husk biochar (RHB) rich in silicon (Si) for Cd2+ in solution and soil were investigated. Three biochars were produced at different pyrolytic temperatures of 300 °C(RHB300), 500 °C(RHB500) and 700 °C (RHB700). The pH effect, adsorption kinetics and isotherms were examined, and chemical analyses of Cd2+-loaded biochars were conducted by SEM-EDS, FTIR, XRD and Boehm titration. Biochars produced at higher temperature have much larger pH and surface area, resulting in greater adsorption capacities and faster adsorption kinetics. Maximum adsorption capacities calculated from Langmuir isotherm were 62.75, 77.37 and 93.50 mg/g for RHB300, RHB500 and RHB700, respectively. Cd2+ adsorption was primarily attributed to cation exchange and precipitation, which jointly contributed 59.55% (RHB300) to 76.05% (RHB700) of the total adsorption, but the mechanisms of complexation and coordination were of minor importance in total adsorption. The relationship of each mechanism with biochar's properties was further discussed. Si-containing minerals within biochar made a much larger contribution to precipitation than total adsorption, as the respective contribution proportion were 33.92% and 8.33% on average. When added to highly Cd-polluted soil, the biochars could effectively reduce the availability of Cd2+ after incubation for 35 days, and ameliorate soil acidification through the speediness of Si released into soil solutions. These demonstrate that rice husk-derived biochar, produced at high temperatures, can be suitable applied to mitigate Cd-contamination of soil and water, and the presented analyses shed light on the mechanisms underlying the adsorption by this Si-rich biochar.

Adsorption Behavior and Relative Distribution of Cd2+ Adsorption Mechanisms by the Magnetic and Nonmagnetic Biochars Derived from Chicken Manure.

The present study investigated the adsorption of Cd2+ by nonmagnetic and magnetic biochars (CMB and M-CMB) derived from chicken manure, respectively. The adsorption characteristics were investigated as a function of initial pH, contact time, initial Cd2+ concentration and magnetic separation. Adsorption process of both biochars were better described by Pseudo-second-order kinetic equation and Freundlich isotherm model, which were spontaneous and endothermic in nature. It was found that maximum capacities were 60.69 and 41.07 mg/g obtained at the initial Cd2+ concentration of 180 mg/L for CMB and M-CMB, and the turbidity of adsorption-treated solution was reduced from 244.3 to 11.3 NTU after magnetic separation of 0.5 min. These indicated that M-CMB had lower adsorption capacity of Cd2+ than CMB, though it was successfully separated from the treated solutions. Furthermore, both biochars before and after adsorption were analyzed by SEM-EDS, XRD and FTIR. Adsorption mechanisms mainly included precipitation, ion-exchange, complexation and Cπ-coordination, in which precipitation and ion-exchange dominated the adsorption process by CMB, while in M-CMB, precipitation was always predominant mechanism, followed by ion-exchange. The two other mechanisms of complexation and Cπ-coordination were trivial in both biochars, jointly contributing 7.21% for CMB and 5.05% for M-CMB to total adsorption. The findings deepen our understanding of the mechanisms governing the adsorption process, which are also important for future practical applications in the removal of heavy metals from wastewater by the biochars.