A new approach to establish safe levels of available metals in soil with respect to potential health hazard of human.

Safe levels of extractable pollutant elements in soil have not been universally established. Prediction of metal solubility in polluted soils and the subsequent transfer of these metals from soil pore water to the human food supply via crops are required for effective risk assessment from polluted soils. Thus an attempt has been made to develop a novel approach to protect human health from exposure to toxic metals through assessing risk from metal polluted soils utilised for agriculture. In this study, we assess the relative efficacy of various forms of 'free ion activity model' (FIAM) for predicting the concentration of cadmium (Cd), lead (Pb), nickel (Ni), zinc (Zn) and copper (Cu) in spinach and wheat as example crops, thereby providing an assessment of risk to human health from consumption of these crops. Free metal ion activity in soil solution was estimated using the Windermere Humic Aqueous Model VII (WHAM-VII) and the Baker soil test. Approximately 91, 81, 75, 94 and 70% of the variability in Cd, Pb, Ni, Zn and Cu content, respectively, of spinach could be described by a FIAM using an estimate of the free ion activity of the metals provided by WHAM-VII. Owing to the different concentration of ethylenediamine tetraacetic acid (EDTA) and diethylenetriamine pentaacetic acid (DTPA) used in the present experiment, higher prediction coefficients were obtained using EDTA (0.05 M), rather than DTPA (0.005 M), as the metal extractant in an integrated solubility-FIAM model. Out of three formulations, the FIAM, based on free ion activity of metals in soil pore water, determined from solution extracted with Rhizon samplers, was distinctly superior to the other formulations in predicting metal uptake by spinach and wheat. A safe level of extractable metal in soil was prescribed using a hazard quotient derived from predicted plant metal content and estimated dietary intake of wheat and spinach by a human population. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12665-021-09988-7.

Pre-monsoon spatial distribution of available micronutrients and sulphur in surface soils and their management zones in Indian Indo-Gangetic Plain.

The efficient (site-specific) management of soil nutrients is possible by understanding the spatial variability in distribution of phyto-available nutrients (here after called available nutrients) and identifying the soil management zones (MZs) of agricultural landscapes. There is need for delineating soil MZs of agricultural landscapes of the world for efficient management of soil nutrients in order to obtain sustainability in crop yield. The present study was, therefore, undertaken to understand the spatial distribution pattern of available micronutrients (zinc (Zn), boron (B), iron (Fe), manganese (Mn) and copper (Cu)), available sulphur (S), and soil properties (soil acidity (pH), electrical conductivity (EC) and organic carbon (SOC) content) in soils of intensively cultivated Indo-Gangetic Plain (IGP) of India and to delineate soil MZs for efficient management of soil nutrients. Totally, 55101 soil samples from 0-15 cm depth were obtained from 167 districts of IGP during 2014 to 2017 and were analysed for different soil parameters. Soil pH, EC and SOC content varied from 4.44 to 9.80, 0.02 to 2.13 dS m-1 and 0.10 to 1.99%, respectively. The concentration of available Zn, B, Fe, Mn, Cu and S varied from 0.01 to 3.27, 0.01 to 3.51, 0.19 to 55.7, 0.05 to 49.0, 0.01 to 5.29 and 1.01 to 108 mg kg-1, respectively. Geostatistical analysis resulted in varied distribution pattern of studied soil parameters with moderate to strong spatial dependence. The extent (% area) of nutrient deficiencies in IGP followed the order: S > Zn > B > Mn > Cu > Fe. Principal component analysis and fuzzy c-means clustering produced six distinctly different soil MZs of IGP for implementation of zone-specific soil nutrient management strategies for attaining sustainability in crop yield. The developed MZ maps could also be utilized for prioritization and rationalization of nutrients supply in IGP of India.

Prediction of free metal ion activity in contaminated soils using WHAM VII, baker soil test and solubility model.

Bioavailability and ecotoxicity of metals in contaminated soils depend largely on their solubility. The present investigation was carried out to predict the free ion activity of Zn2+, Cu2+, Ni2+, Pb2+ and Cd2+ in contaminated soils as a function of pH, organic carbon content and extractable metal concentration. Twenty-five composite soil samples were collected from various locations which had a history of receiving sewage sludge (Keshopur and IARI, Delhi), municipal solid waste (Kolkata, West Bengal), polluted river water (Madanpur, Delhi) and industrial effluents (Debari, Rajasthan and Sonepat, Haryana). Four composite soil samples were also collected from adjacent fields which had not received contaminated amendments. Free ion activities (-log10 values), viz. pZn2+, pCu2+, pNi2+, pPb2+ and pCd2+ as measured by the Baker soil test, were 10.1 ± 1.12, 13.4 ± 1.23, 12.9 ± 0.85, 11.6 ± 0.74 and 12.6 ± 2.26, respectively. Free metal ion activities were also determined using the geochemical speciation model WHAM-VII following extraction of soil solution with porous Rhizon samplers from the rhizosphere of growing plants. pH dependent Freundlich model based on soil properties could explain the variation in pZn2+, pCu2+, pNi2+, pPb2+ and pCd2+ to the extent of 84, 52, 73, 60 and 70%, respectively, in the case of data from Rhizon samplers coupled with speciation modelling. Whereas, C-Q model could explain 84, 57, 82, 72 and 74% variability in pZn2+, pCu2+, pNi2+, pPb2+ and pCd2+, respectively, based on soil properties and free metal ion activity as determined with integrated use of Rhizon-WHAM-VII. Modelling approach was superior compared to that based on the Baker soil test solution.

Long-term impact of sewage irrigation on soil properties and assessing risk in relation to transfer of metals to human food chain.

A case study was undertaken to assess the risk of sewage-irrigated soils in relation to the transfer of trace elements to rice and wheat grain. For this purpose, peri-urban agricultural lands under the Keshopur Effluent Irrigation Scheme (KEIS) of Delhi were selected. These agricultural lands have been receiving irrigation through sewage effluents since 1979. Sewage effluent, groundwater, soil, and plant (rice and wheat grain) samples were collected with GPS coordinates from this peri-urban area. Under wheat crop, sewage irrigation for four decades resulted into a significant buildup of zinc (141 %), copper (219 %), iron (514 %), nickel (75.0 %), and lead (28.1 %) in sewage-irrigated soils over adjacent tube well water-irrigated ones. Under rice crop, there was also a significant buildup of phosphorus (339 %), sulfur (130 %), zinc (287 %), copper (352 %), iron (457 %), nickel (258 %), lead (136 %), and cadmium (147 %) in sewage-irrigated soils as compared to that of tube well water-irrigated soils. The values of hazard quotient (HQ) for intake of trace toxic elements by humans through consumption of rice and wheat grain grown on these sewage-irrigated soils were well within the safe permissible limit. The variation in Zn, Ni, and Cd content in wheat grain could be explained by solubility-free ion activity model (FIAM) to the extent of 50.1, 56.8, and 37.2 %, respectively. Corresponding values for rice grain were 49.9, 41.2, and 42.7 %, respectively. As high as 36.4 % variation in As content in rice grain could be explained by solubility-FIAM model. Toxic limit of extractable Cd and As in soil for rice in relation to soil properties and human health hazard associated with consumption of rice grain by humans was established. A similar exercise was also done in respect of Cd for wheat. The conceptual framework of fixing the toxic limit of extractable metals and metalloid in soils with respect to soil properties and human health hazard under the modeling framework was established.

Release of zinc and cadmium from sludge amended soil as influenced by varying levels of moisture and temperature.

Limited information is available related to the effect of moisture and temperature on release of metals from sludge treated soils. In an incubation experiment, effect of ten levels of sludge (0, 1.12, 2.24, 4.48, 8.96, 17.9, 35.8, 71.6, 142, 285 g kg(-1)), two levels of moisture (field capacity and 2.5 cm standing water) and two levels of temperature (20 and 35 degrees C) on the release of zinc and cadmium was evaluated in acid and alkaline soils. The results indicated that application of sludge was more effective in enhancing EDTA extractable Zn and Cd in acid soil than in alkaline soil. On an average, maximum increase in release of EDTA extractable Zn and Cd were 32.0 and 5.2 fold in sludge treated soil over control. There was decrease in EDTA extractable Zn and Cd by 37.7% and 25.4%, respectively under submergence as compared to that under field capacity. On an average, the amount of EDTA extractable Zn and Cd increased by 22.6% and 43.6%, respectively at 35 degrees C than that at 20 degrees C.

Predicting bioavailability of metals from sludge-amended soils.

We attempted to develop a protocol for fixing the maximum permissible limit of sludge in agricultural lands based on transfer of metals from sludge-amended soils to human food chain. For this purpose, spinach was grown as a test crop on acid and alkaline soils with graded doses of sludge (0, 1.12, 2.24, 4.48, 8.96, 17.9, 35.8, 71.6, 142 and 285 g kg(-1) of soil) in a pot experiment. Biomass yield of spinach was increased due to sludge application in both acid and alkaline soils. Among the chemical extractants, EDTA extracted the highest amount of metals from sludge-amended soil followed by diethylenetriaminepentaacetic acid (DTPA) and CaCl2. Elevated levels of Zn, Cu, Fe, Mn, Ni, Cd and Pb in spinach were observed due to sludge application over control. Application of sludge was more effective in increasing metal content in spinach grown on acid soil than alkaline soil. Solubility-free ion activity model as a function of pH, organic carbon and extractable metal was far more effective in predicting metal uptake by spinach grown on sludge-amended soils as compared to that of chemical extractants. Risk in terms of hazard quotient (HQ) for intake of metals through consumption of spinach by humans grown on sludge-treated soils was computed for different metals separately. In a 90-day pot experiment, safe rates of sludge application were worked out as 4.48 and 71.6 g kg(-1) for acid and alkaline soils, respectively.

Prediction of the solubility of zinc, copper, nickel, cadmium, and lead in metal-contaminated soils.

Risk assessment of metal-contaminated soil depends on how precisely one can predict the solubility of metals in soils. Responses of plants and soil organisms to metal toxicity are explained by the variation in free metal ion activity in soil pore water. This study was undertaken to predict the free ion activity of Zn, Cu, Ni, Cd, and Pb in metal-contaminated soil as a function of pH, soil organic carbon, and extractable metal content. For this purpose, 21 surface soil samples (0-15 cm) were collected from agricultural lands of various locations receiving sewage sludge and industrial effluents for a long period. One soil sample was also collected from agricultural land which has been under intensive cropping and receiving irrigation through tube well water. Soil samples were varied widely in respect of physicochemical properties including metal content. Total Zn, Cu, Ni, Cd, and Pb in experimental soils were 2,015 ± 3,373, 236 ± 286, 103 ± 192, 29.8 ± 6.04, and 141 ± 270 mg kg(-1), respectively. Free metal ion activity, viz., pZn(2+), pCu(2+), pNi(2+), pCd(2+), and pPb(2+), as estimated by the Baker soil test was 9.37 ± 1.89, 13.1 ± 1.96, 12.8 ± 1.89, 11.9 ± 2.00, and 11.6 ± 1.52, respectively. Free metal ion activity was predicted by pH-dependent Freundlich equation (solubility model) as a function of pH, organic carbon, and extractable metal. Results indicate that solubility model as a function of pH, Walkley-Black carbon (WBC), and ethylenediaminetetraacetic acid (EDTA)-extractable metals could explain the variation in pZn(2+), pCu(2+), pNi(2+), pCd(2+), and pPb(2+) to the extent of 59, 56, 46, 52, and 51%, respectively. Predictability of the solubility model based on pH, KMnO4-oxidizable carbon, and diethylenetriaminepentaacetic acid-extractable or CaCl2-extractable metal was inferior compared to that based on EDTA-extractable metals and WBC.