Ecological risk assessment of heavy metals in surface seawater and sediment near the outlet of a zinc factory in Huludao City, Liaoning Province, China

At present, the methods widely applied to assess ecological risk of heavy metals are essentially single-point estimates in which exposure and toxicity data cannot be fully used and probabilities of adverse biological effects cannot be achieved. In this study, based on investigation of concentrations of six heavy metals(As, Hg, Pb, Cd, Cu, and Zn) in the surface seawater and sediment near the outlet of a zinc factory, located in Huludao City, Liaoning Province, China, a tiered approach consisting of several probabilistic options was used to refi ne ecological risk assessment for the individuals. A mixture of various heavy metals was detected in the surface seawater, and potential ecological risk index(PERI) was adopted to assess the potential ecological risk of heavy metals in the surface sediment. The results from all levels of aquatic ecological risk assessment in the tiered framework, ranging from comparison of single effects and exposure values to the use of distribution-based Hazard Quotient obtained through Monte Carlo simulation, are consistent with each other. Briefl y, aquatic Zn and Cu posed a clear ecological risk, while Cd, Pb, Hg, and As in the water column posed potential risk. As expected, combined ecological risk of heavy metal mixture in the surface seawater was proved signifi cantly higher than the risk caused by any individual heavy metal, calculated using the concept of total equivalent concentration. According to PERI, the severity of pollution by the six heavy metals in the surface sediment decreased in the following sequence: Cd>Hg>As>Pb>Cu>Zn, and the total heavy metals in the sediment posed a very high risk to the marine environment. This study provides a useful mathematical framework for ecological risk assessment of heavy metals.

An experimental method to obtain the hard alpha anomaly distribution for titanium alloy aeroengine disks

A probability-based damage tolerance methodology has been proposed to improve the recognition of material anomalies, especially hard alpha(TiN) anomalies for aeroengine rotor disks. A key input to this method is hard alpha anomaly distribution, which reflects the occurrence rate and size of anomalies present in the finished part material of titanium rotors. Since anomalies rarely occur naturally, an experimental method is proposed to obtain the anomaly distribution for titanium alloy aeroengine disks to reflect and equivalently replace the manufacturing development in titanium industry. In general, the anomaly distribution information can be divided into two parts: the Probability of Detection(POD) curve and the detected anomaly distribution, which contains the size and frequency data of the detected anomalies. The distribution can be established based on several appropriate assumptions and derivation steps with different confidence levels of POD curves and detected anomaly distributions. In this case, the distribution can be obtained in a relatively short time as a key input to the probability-based damage tolerance methodology. Then the Probability of Failure(POF) can be calculated, and the value is found to vary with different confidence levels. On this basis, the conservative estimated POF can be obtained in conjunction with confidence levels.