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Given the increasing concern over Cd contamination of agricultural soils in China, reducing the availability of the toxic metal has become an important remedial strategy. However, the lack of a unified evaluation framework complicates the assessment of remediation efficiency of different practices. Here, we evaluated the general extraction method (GEM) of available Cd in nine typical soil types by comparing extraction agents, including CaCl2, EDTA, Mehlich-Ⅲ, HCl and DTPA. The safe grain concentration of different agricultural products from National Food Safety Standards Limits of Contaminants in Food (GB 2762-2022) was then applied to understand soil limited available Cd concentration based on dose-response curves. We also derived environmental risk threshold (HC5) values for Cd remediation in agricultural soils by constructing species sensitivity distribution (SSD) curves. The results showed that Mehlich-Ⅲ best predicted Cd accumulation in crops (with 76.5% of explanation of grain Cd) and was selected as the GEM of soil available Cd for subsequent analyses. The regression coefficient (R2) of dose-response curves fitting between Cd absorption in crop tissues and soil available Cd extracted by GEM based on 30 different crop species varied from 51.0% to 79.5%, and the derived limit concentration of soil available Cd based on standard GB 2762-2022 was 0.18-0.76 mg‧kg-1. An HC5 of 0.19 mg‧kg-1 was then calculated, meaning that a concentration of available Cd in agricultural soil below 0.19 mg‧kg-1 ensures that 95% of agricultural products meet the quality and safety requirements of standard GB 2762-2022. The prediction model was well verified in the field test, indicating that can correctly estimate the soil available Cd based on the content of Cd in plant. This study provides a robust scientific framework for deriving the risk threshold for Cd remediation in agricultural soils and could be quite useful for establishing soil remediation standards.

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The establishment of ecological risk thresholds for arsenic (As) plays a pivotal role in developing soil conservation strategies. However, despite many studies regarding the toxicological profile of As, such thresholds varying by diverse soil properties have rarely been established. This study aims to address this gap by compiling and critically examining an extensive dataset of As toxicity data sourced from existing literature. Furthermore, to augment the existing information, experimental studies on As toxicity focusing on barley-root elongation were carried out across various soil types. The As concentrations varied from 12.01 to 437.25 mg/kg for the effective concentrations that inhibited 10% of barley-root growth (EC10). The present study applied a machine-learning approach to investigate the complex associations between the toxicity thresholds of As and diverse soil properties. The results revealed that Mn-/Fe-ox and clay content emerged as the most influential factors in predicting the EC10 contribution. Additionally, by using a species sensitivity distribution model and toxicity data from 21 different species, the hazardous concentration for x% of species (HCx) was calculated for four representative soil scenarios. The HC5 values for acidic, neutral, alkaline, and alkaline calcareous soils were 80, 47, 40, and 28 mg/kg, respectively. This study establishes an evidence-based methodology for deriving soil-specific guidance concerning As toxicity thresholds.

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Derivation of ecological risk threshold (the threshold concentration value that protect a certain proportion of species within the acceptable hazard level) of lead (Pb) is a yardstick and plays a key role in formulating soil protection policies, while the research about deducing soil Pb ecological risk threshold is still limited. In this study, toxicological data of Pb based on 30 different test endpoints was collected from our experiment and literature, and applied into interspecific extrapolation by species sensitivity distribution (SSD) method to derive the hazard concentration for 5% of species (HC5, that can protect 95% of species), the prediction models according to different soil properties were established. The results showed that EC10 (the effective concentrations of Pb that inhibit 10% of endpoint bioactivity) ranged from 205.6 to 1596.3 mg kg1, and hormesis induced by Pb were up to 118%. Toxicity data were corrected by leaching and aging process before SSD curves fitting. HC5 was then derived and prediction model was developed, as LogHC5 = 0.134 pH + 0.315 LogOC + 0.324 LogCEC + 1.077. The prediction model was well verified in the field test, indicating that can correctly estimate Pb ecotoxicity thresholds in different soils. This study provides a scientific frame for deriving the ecological risk threshold of Pb and is of great significance for ecological species protection.

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