An analytical deterministic model for simultaneous phytoremediation of Ni and Cd from contaminated soils

Development of simplified probabilistic models for predicting phytoextraction timeframes of soil contaminants: demonstration at the DDX-contaminated Kolleberga tree nursery in Sweden

Phytoextraction, utilizing plants to remove soil contaminants, is a promising approach for environmental remediation but its application is often limited due to the long time requirements. This study aims to develop simplified and user-friendly probabilistic models to estimate the time required for phytoextraction of contaminants while considering uncertainties. More specifically we: i) developed probabilistic models for time estimation, ii) applied these models using site-specific data from a field experiment testing pumpkin (Cucurbita pepo ssp. pepo cv. Howden) for phytoextraction of DDT and its metabolites (ΣDDX), iii) compared timeframes derived from site-specific data with literature-derived estimates, and iv) investigated model sensitivity and uncertainties through various modelling scenarios. The models indicate that phytoextraction with pumpkin to reduce the initial total concentration of ΣDDX in the soil (10 mg/kg dw) to acceptable levels (1 mg/kg dw) at the test site is infeasible within a reasonable timeframe, with time estimates ranging from 48-123 years based on literature data or 3 570-9 120 years with site-specific data using the linear or first-order exponential model, respectively. Our results suggest that phytoextraction may only be feasible at lower initial ΣDDX concentrations (< 5 mg/kg dw) for soil polishing and that alternative phytomanagement strategies should be considered for this test site to manage the bioavailable fraction of DDX in the soil. The simplified modes presented can be useful tools in the communication with site owners and stakeholders about time approximations for planning phytoextraction interventions, thereby improving the decision basis for phytomanagement of contaminated sites.

Bioremediation of cadmium-trichlorfon co-contaminated soil by Indian mustard (Brassica juncea) associated with the trichlorfon-degrading microbe Aspergillus sydowii: Related physiological responses and soil enzyme activities

Soil co-contaminated with heavy metals and organics is often difficult to remediate. In this study, pot experiments were conducted to investigate the concurrent removal of cadmium (Cd, two levels: Cd_L [10 mg kg^-1] and Cd_H [50 mg kg^-1]) and trichlorfon (TCF, 100 mg kg^-1) from co-contaminated soil by comparing the following remediation methods: natural remediation (NR), soil inoculated with Aspergillus sydowii (AS), soil planted with Brassica juncea (BJ), and soil planted with B. juncea and inoculated with A. sydowii (BJ-AS). The physiological responses of B. juncea and soil enzyme activities after remediation were also studied. B. juncea grew well in co-contaminated soil at both Cd levels. The biomass and chlorophyll content of B. juncea in Cd_H soil were lower than those in Cd_L soil, whereas the malondialdehyde content and activities of catalase, peroxidase and superoxide dismutase of B. juncea in Cd_H soil were higher than those in Cd_L soil. Cd accumulation in B. juncea was high in Cd_H soil, whereas high Cd removal efficiency was observed in Cd_L soil. TCF could be thoroughly degraded within 35 days in NR at both Cd-level soils. AS, BJ and BJ-AS promoted TCF degradation and enhanced the activities of catalase, urease, sucrase and alkaline phosphatase in soil compared with the NR. BJ-AS showed the highest phytoextraction ratio (3.32% in Cd_L and 1.34% in Cd_H soil) and TCF degradation rate (half-life of 2.18 and 2.37 days in Cd_L and Cd_H soil, respectively). These results demonstrate that BJ-AS could effectively remove Cd and TCF from soil and is thus a feasible technology for the bioremediation of these co-contaminated soil.

Simulation of Heavy Metals Migration in Soil-Wheat System of Mining Area

Heavy metals in the soil of mining areas have become a primary source of pollution, which could cause deleterious health effects in people exposed through soil-plant systems via multi-pathways. A long-term field experiment under natural conditions was carried out to explore the distribution characteristic and migration law of heavy metals in a soil-wheat system of a mining area in Xuzhou. According to the second level standard of environmental quality standards for soils of China (GB 15618-1995), 30.8 g of CrCl₃·6H₂O, 8.3 g of Pb(CH₃COO)₂·3H₂O, and 16.5 g of ZnSO₄·7H₂O were added into the soil of three experimental sites, respectively. The other experimental site with no additional compounds was used as the control site. The Cr, Pb, and Zn concentrations in the soil-wheat system were counted and their corresponding migration models were constructed. From 2014 to 2017, the mean concentrations of Cr (49.09 mg·kg⁻¹), Pb (20.08 mg·kg⁻¹), and Zn (39.11 mg·kg⁻¹) in the soil of the addition sites were higher than that of the control site. The mean concentrations of Cr, Pb, and Zn in wheat of the addition sites were greater than that of the control site with the values of 3.29, 0.06, and 29 mg·kg⁻¹. In comparison, the Cr, Pb, and Zn concentrations in the soil of all experimental sites were lower than the second level standard of environmental quality standards for soils of China (GB 15618-1995), whereas the Cr concentration exceeded its corresponding soil background value of Xuzhou in 2017. The Pb concentration in soil of the addition site was greater than its corresponding background value from 2014 to 2016. The Pb and Zn concentrations in wheat of all experimental sites were lower than the national hygienic standard for grains of China (GB2715-2005) and the national guidelines for cereals of China (NY 861-2004), but the Cr concentration significantly exceeded the national guidelines for cereals of China (NY 861-2004). By constructing the Identical-Discrepant-Contrary (IDC) gray connection models, the result showed that there was a non-linear relationship of Cr, Pb, and Zn concentrations in the soil-wheat system, and the absolute values of most correlation coefficients r were lower than 0.5 and the values of greyness fG(r) were more than 0.5. The curvilinear regression models could not reflect the relationship of Cr, Pb, and Zn concentrations in the soil-wheat system with the regression coefficient r2 values far less than 1. Due to the values of regression coefficient r2 being close to 1, this study suggested that the allocation estimation models could be used for simulating the Cr, Pb, and Zn migration in the soil-wheat system of a mining area in Xuzhou.

Chive (Allium schoenoprasum L.) response as a phytoextraction plant in cadmium-contaminated soils

Cadmium (Cd) soil contamination poses a major hazard to safe food production throughout the world, calling upon actions for decontamination using environmentally friendly methods, such as phytoextraction. In this study, the capability of chive (Allium schoenoprasum L.) for phytoextracting Cd from contaminated soils was tested. Growth of chive was studied in a soil spiked with 0, 15, 30, 60, and 120 mg Cd/kg soil, and then, concentrations of Cd in soil, plant shoots, and roots were measured after harvest. Chive dry matter production was not affected significantly by the different Cd levels in soil, except from the maximum Cd concentration (120 mg Cd/kg soil), where dry matter was reduced by 77%. Cadmium accumulation occurred mostly in roots rather than in shoots, with maximum Cd concentrations 482.48 and 26.65 mg/kg of dry matter, respectively. Translocation factor (the proportion of Cd concentration in the aerial plant parts to that in the roots) was below 1 in all contaminated levels and decreased with increasing Cd concentrations in soil, indicating low Cd reallocation from roots to shoots. Maximum amount of Cd absorption (Cd concentration in shoots), maximum contaminant uptake rate, and minimum clean-up time were all observed in Cd concentration 60 mg/kg soil. Based on chive potential to acquire Cd in its roots and shoots, it can be designated as a convenient species for reducing Cd from contaminated soils up to concentrations of 60 mg Cd/kg soil.

Estimating soil heavy metals concentration at large scale using visible and near-infrared reflectance spectroscopy

This study was aimed (i) to examine using diffuse reflectance spectra within VNIR region to estimate soil heavy metals concentrations at large scale, (ii) to compare the influence of different pre-processing models on predictive model accuracy, and (iii) to explore the best predictive models. A number of 325 topsoil samples were collected and their spectral data, pH, clay content, organic matter, Ni, and Cu concentrations were determined. To improve spectral data, various pre-processing methods including Savitzky-Golay smoothing filter, Savitzky-Golay smoothing filter with first and second derivatives, and standard normal variant (SNV) were used. Partial least squares regression (PLSR), principal component regression (PCR), and support vector machine regression (SVMR) models were employed to build calibration models for estimating soil heavy metals concentration followed by evaluation of provided predictive models. Results indicated that Cu had stronger correlation coefficients with spectral bands compared to Ni. Cu and Ni demonstrated strongest correlations at wavelengths 1925 and 1393 nm, respectively. Based on RMSE, R², and RPD statistics, the PLSR model with Savitzky-Golay filter pretreatment provided the most accurate predictions for both Cu and Ni (R² = 0.905, RMSE = 0.00123, RPD = 2.80 for Ni; R² = 0.825, RMSE = 0.00467, RPD = 2.04 for Cu) where such prediction was much better for Ni than for Cu. Reasonable results with lower accuracy and stability were obtained for PCR (R² = 0.742, RMSE = 0.00181, RPD = 1.91 for Ni; R² = 0.731, RMSE = 0.00578, RPD = 1.65 for Cu) and SVMR (R² = 0.643, RMSE = 0.00091, RPD = 3.80 for Ni; R² = 0.505, RMSE = 0.00296, RPD = 3.22 for Cu). We concluded that reflectance spectroscopy technique could be applied as a reliable tool for detection and prediction of soil heavy metals.

Distance-dependent varieties of microbial community structure and metabolic functions in the rhizosphere of Sedum alfredii Hance during phytoextraction of a cadmium-contaminated soil

The recovery of microbial community and activities is crucial to the remediation of contaminated soils. Distance-dependent variations of microbial community composition and metabolic characteristics in the rhizospheric soil of hyperaccumulator during phytoextraction are poorly understood. A 12-month phytoextraction experiment with Sedum alfredii in a Cd-contaminated soil was conducted. A pre-stratified rhizobox was used for separating sub-layer rhizospheric (0-2, 2-4, 4-6, 6-8, 8-10 mm from the root mat)/bulk soils. Soil microbial structure and function were analyzed by phospholipid fatty acid (PLFA) and MicroResp™ methods. The concentrations of total and specified PLFA biomarkers and the utilization rates for the 14 substrates (organic carbon) in the 0-2-mm sub-layer rhizospheric soil were significantly increased, as well as decreased with the increase in the distance from the root mat. Microbial structure measured by the ratios of different groups of PLFAs such as fungal/bacterial, monounsaturated/saturated, ratios of Gram-positive to Gram-negative (GP/GN) bacterial, and cyclopropyl/monoenoic precursors and 19:0 cyclo/18:1ω7c were significantly changed in the 0-2-mm soil. The PLFA contents and substrate utilization rates were negatively correlated with pH and total, acid-soluble, and reducible fractions of Cd, while positively correlated with labile carbon. The dynamics of microbial community were likely due to root exudates and Cd uptake by S. alfredii. This study revealed the stimulations and gradient changes of rhizosphere microbial community through phytoextraction, as reduced Cd concentration, pH, and increased labile carbons are due to the microbial community responses.

Phytostabilisation potential of giant reed for metals contaminated soil modified with complex organic fertiliser and fly ash: A field experiment

An orthogonal field experiment of giant reed (Arundo donax) modified with organic complex fertiliser (OCF), and OCF and fly ash (O&F), at different planting densities was carried out in metal-contaminated soil. The available percentage of arsenic (As) and lead (Pb) in soil decreased from 8.45% to 2.19% and from 29.6% to 13.5% by OCF, respectively, and that of cadmium (Cd) was reduced from 25.3% to 6.49% by O&F. The total biomass of giant reed was 631g per individual following application of O&F in contaminated soil. The accumulation of As, Cd, and Pb in giant reed was 1.57, 4.06, and 11.25mg per individual. Urease and sucrase activity were 87.4NH₄-Nμg/gd and 63.1glucosemg/gd in response to the treatments modified using OCF, while the highest dehydrogenase activity was 101 TPF (triphenyltetrazolium formazan) μg/gd in the treatments modified using O&F. Dominant bacteria (frequency>50%) were enriched with increasing planting density of giant reed. These results indicate that the phytostabilisation of metal-contaminated soil by giant reed could be improved by the application of O&F or OCF.

Landfill site selection for municipal solid wastes in mountainous areas with landslide susceptibility

Several cities across the world are located in mountainous and landslide prone areas. Any landfill siting without considering landslide susceptibility in such regions may impose additional environmental adversity. This study was aimed to propose a practical method for selecting waste disposal site that accounts for landslide exposure. The proposed method was applied to a city which is highly proneness to landslide due to its geology, morphology, and climatic conditions. First, information on the previously occurred landslides of the region was collected. Based on this information, proper landslide causative factors were selected and their thematic maps were prepared. Factors' classes were then standardized in 0-1 domain, and thematic layers were weighted by using analytical hierarchy process (AHP). The landslide susceptibility map was prepared afterwards. Unsuitable areas for landfill location were masked in GIS environment by Boolean method, retaining sufficient areas for further evaluation. Nine remaining alternatives were selected through comprehensive field visits and were ranked by using AHP. Consequently, 17 factors in three environmental, economical, and social perspectives were employed. Sensitivity analyses were performed to assess the stability of the alternatives ranking with respect to variations in criterion weights. Based on the obtained landslide susceptible map, nearly 36 % of the entire region is proneness to landslide. The prepared Boolean map indicates that potential areas for landfill construction cover 11 % of the whole region. The results further indicated that if landslide susceptible areas are not considered in landfill site selection, the potential landfill sites would become more than twice. It can be concluded that if any of these landslide prone sites are selected for landfilling, further environmental disaster would be terminated in the future. It can be further concluded that the proposed method could reasonably well be adjusted to consider landslide exposure when siting a solid waste landfill.

Accumulation and translocation of heavy metal by spontaneous plants growing on multi-metal-contaminated site in the Southeast of Rio Grande do Sul state, Brazil

In recent years, the number of cases of heavy metal contamination has increased worldwide, leading to reports on environmental pollution and human health problems. Phytoremediation can be potentially used to remove heavy metal from contaminated sites. This study determined heavy metal concentrations in the biomass of plant species growing on a multi-metal-contaminated site. Seven plant species and associated rhizospheric soil were collected and analyzed for heavy metal concentrations. While plant Cu, Zn, Cd, Ni, Pb, As, and Ba concentrations ranged from 8.8 to 21.1, 56.4 to 514.3, 0.24 to 2.14, 1.56 to 2.76, 67.8 to 188.2, 0.06 to 1.21, and 0.05 to 0.62 mg kg(-1), respectively, none of the plants was identified as hyperaccumulators. Those in the rhizospheric soil ranged from 10.5 to 49.1, 86.2 to 590.9, 0.32 to 2.0, 3.6 to 8.2, 19.1 to 232.5, 2.0 to 35.6, and 85.8 to 170.3 mg kg(-1), respectively. However, Zn, Cd, Pb, and As concentrations in the soil outside the rhizosphere zone were 499.0, 2.0, 631.0, and 48.0 mg kg(-1), respectively. Senecio brasiliensis was most effective in translocating Cu, Cd, and Ba. The most effective plant for translocating Zn and Pb was Baccharis trimera and, for element As, Dicranopteris nervosa and Hyptis brevipes. Heavy metal and metalloid levels in spontaneous plants greatly exceeded the upper limits for terrestrial plants growing in uncontaminated soil, demonstrating the higher uptake of heavy metal from soil by these plants. It is concluded that naturally occurring species have a potential for phytoremediation programs.

Competitive adsorption-desorption reactions of two hazardous heavy metals in contaminated soils

Investigating the interactions of heavy metals is imperative for sustaining environment and human health. Among those, Cd is toxic for organisms at any concentration. While Ni acts as a micronutrient at very low concentration but is hazardous toxic above certain threshold value. In this study, the chemical adsorption and desorption reactions of Ni and Cd in contaminated soils were investigated in both single and binary ion systems. Both Ni and Cd experimental data demonstrated Langmuir type adsorption. In the competitive systems, an antagonistic effect was observed, implying that both ions compete for same type of adsorption sites. Adverse effect of Cd on Ni adsorption was slightly stronger than that of opposite system, consistent with adsorption isotherms in single ion systems. Variation in ionic strength indicated that Ca, a much weaker adsorbate, could also compete with Cd and Ni for adsorption on soil particles. Desorption data indicated that Cd and Ni are adsorbed very tightly such that after four successive desorption steps, less than 0.5 % of initially adsorbed ions released into the soil solution. This implies that Ca, at concentration in equilibrium with calcite mineral, cannot adequately compete with and replace adsorbed Ni and Cd ions. This adsorption behavior was led to considerable hysteresis between adsorption and desorption in both single and binary ion systems. In the binary ion systems, desorption of Cd and Ni was increased by increase in both equilibrium concentration of adsorbed ion and concentration of competitor ion. The overall results obtained in this research indicate that Cd and Ni are strongly adsorbed in calcareous soil and Ca, the major dissolved ion, insignificantly influences metal ions adsorption. Consequently, the contaminated soils by Ni and Cd can simultaneously be remediated by environmentally oriented technologies such as phytoremediation.