Ecological Effects of Benzyl Chloride on Different Korean Aquatic Indigenous Species Using an Artificial Stream Mesocosm Simulating a Chemical Spill

In this study, an artificial stream mesocosm consisting of a head tank, faster-flowing riffle section, gravel section, pool section, lower-run section, and tail tank was installed to simulate a chemical spill in a river. The responses of freshwater periphyton algae, crustacea (Moina macrocopa), freshwater worm (Limnodrilus hoffmeisteri), benthic midge (Glyptotendipes tokunagai), and fish (Zacco platypus and Aphyocypris chinensis) were observed after exposure to benzyl chloride (classified as an accident preparedness substance, APS) at concentrations of 1, 2, and 4 µL/L for 22.5 h. Higher concentrations increased the inhibition (photosynthetic efficiency decrease) of periphyton algae and the mortality of M. macrocopa, whereas the reproduction of the female cladoceran decreased in the 4 µL/L treatment. Mortality of fish did not occur or was lower (≤20%) at all concentrations; however, toxic symptoms were observed for some time after chemical exposure termination and later, symptoms receded. G. tokunagai mortality increased at all concentrations except the control after seven days, and no significant toxic effects were observed in L. hoffmeisteri. The hazardous concentration of benzyl chloride was calculated as 94 µg/L. This study showed the different sensitivities of each species to benzyl chloride. The findings can assist in environmental risk assessment of APSs after chemical spills to protect Korean aquatic species.

Use of the Species Sensitivity Distribution Approach to Derive Ecological Threshold of Toxicological Concern (eco-TTC) for Pesticides

The species sensitivity distribution (SSD) calculates the hazardous concentration at which 5% of species (HC5) will be potentially affected. For many compounds, HC5 values are unavailable impeding the derivation of SSD curves. Through a detailed bibliographic survey, we selected HC5 values (from acute toxicity tests) for freshwater aquatic species and 129 pesticides. The statistical distribution and variability of the HC5 values within the chemical classes were evaluated. Insecticides are the most toxic compounds in the aquatic communities (HC5 = 1.4x10−03 µmol L−1), followed by herbicides (HC5 = 3.3 x10−2 µmol L−1) and fungicides (HC5 = 7.8 µmol L−1). Subsequently, the specificity of the mode of action (MoA) of pesticides on freshwater aquatic communities was investigated by calculating the ratio between the estimated baseline toxicity for aquatic communities and the HC5 experimental values gathered from the literature. Moreover, we proposed and validated a scheme to derive the ecological thresholds of toxicological concern (eco-TTC) of pesticides for which data on their effects on aquatic communities are not available. We proposed eco-TTCs for different classes of insecticides, herbicides, and fungicides with a specific MoA, and three eco-TTCs for those chemicals with unavailable MoA. We consider the proposed approach and eco-TTC values useful for risk management purposes.

Estimating species sensitivity distributions on the basis of readily obtainable descriptors and toxicity data for three species of algae, crustaceans, and fish

Estimation of species sensitivity distributions (SSDs) is a crucial approach to predicting ecological risks and water quality benchmarks, but the amount of data required to implement this approach is a serious constraint on the application of SSDs to chemicals for which there are few or no toxicity data. The development of statistical models to directly estimate the mean and standard deviation (SD) of the logarithms of log-normally distributed SSDs has recently been proposed to overcome this problem. To predict these two parameters, we developed multiple linear regression models that included, in addition to readily obtainable descriptors, the mean and SD of the logarithms of the concentrations that are acutely toxic to one algal, one crustacean, and one fish species, as predictors. We hypothesized that use of the three species’ mean and SD would improve the accuracy of the predicted means and SDs of the logarithms of the SSDs. We derived SSDs for 60 chemicals based on quality-assured acute toxicity data. Forty-five of the chemicals were used for model fitting, and 15 for external validation. Our results supported previous findings that models developed on the basis of only descriptors such as log KOW had limited ability to predict the mean and SD of SSD (e.g., r2 = 0.62 and 0.49, respectively). Inclusion of the three species’ mean and SD, in addition to the descriptors, in the models markedly improved the predictions of the means and SDs of SSDs (e.g., r2 = 0.96 and 0.75, respectively). We conclude that use of the three species’ mean and SD is promising for more accurately estimating an SSD and thus the hazardous concentration for 5% of species in cases where limited ecotoxicity data are available.

Comparison of Gradient Estimation in Cooperative Multi-Agent Source Seeking

Agent-based source seeking problem is addressed in this paper. This problem is relevant in, e.g., in hazardous gas leak in a chemical disaster. In the cooperative search, agents develop a formation to effectively search the source by communicating one to another via a communication topology. The source, or the search target, is represented by a scalar field y which might describe a temperature level, hazardous concentration of substances or vapor. Every agent has the information on its own position and the value of y at any instance. The agents are identical modeled as single and double integrator. Consensus filter is used to control the agent formation and comparison three types of gradient estimation are employed to search the source. Experiments show that the proposed schemes give good performance to solve cooperative search for source seeking problem