Determining soil conservation strategies:Ecological risk thresholds of arsenic and the influence of soil properties

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.

Design Tide Hydrograph with A Given Risk Threshold by A Copula-Based Multivariate Method

This paper describes the development of a T-year design tide hydrograph （DTH）. A core innovation is that the proposed technique uses the design risk threshold and copula-based conditional risk probability to analyze the optimal combination of high waters and low waters of the DTH. A brief description of the method is presented. The in situ semi-diurnal tide data at the coast of Jiangsu Province in China are analyzed. Marginal distributions for high waters and low waters of tides are examined. Furthermore, the joint distributions, condition risk probabilities and risk thresholds of high waters and low waters are presented. Results of the DTH from the proposed method are compared with those from the traditional same-multiple enlarging design approach. It is demonstrated that the proposed method is preferable.

Determining threshold default risk criterion for trade credit granting

To solve the problem of setting threshold default risk criterion to select retailer eligible for trade credit granting, a novel method of solving simultaneous equations is proposed. This method is based on the bilevel programming modeling of trade credit decisions as an interaction between supplier and retailer. First, the bilevel programming is set up where the supplier decides on credit terms at the top level considering a retailer's default risk, and the retailer determines the order quantity at the lower level in response to the credit terms offered. By solving this bilevel programming, the relationship between the optimal terms and the corresponding default risk can be derived. Second, set the extreme scenario where the threshold default risk is approached as the point causing a zero marginal profit to the supplier. Another equation describing this particular scenario can also be derived. Thus, a system of two equations with two unknown variables can be obtained where the exact threshold default risk criterion can be found by solving them. A numerical example is presented as an illustration of the method proposed. It shows that the threshold criterion can be uniquely determined when the financial costs, inventory costs, and the marketing parameters of supplier and buyer are specified.