Probabilistic Risk Assessment Methods Research Articles

PROBABILISTIC RELIABILITY ASSESSMENT OF POWERHOUSES BY THE CRITERION OF STABILITY LOSS AGAINST DISPLACEMENT ON THE EXAMPLE OF HYDRO SCHEMES OF THE DNIEPER CASCADE

This work further develops the method for assessing reliability of powerhouses by the criteria of stability loss against forward and slanting displacement along flat and inclined surfaces. It also considers the random nature of mechanical properties of the soil in the foundation and correlations between mechanical properties of the soil . In the future, the proposed method of probabilistic risk assessment of stability loss of powerhouses could be used in probabilistic reliability analyses of hydraulic structures and cascades of hydro schemes, taking into account the correlations between natural factors: hydrological characteristics, ice, and wind, as well as temperature loads and impacts.

Studies on ecological risk assessment of pesticide using species sensitivity distribution.

Species sensitivity distribution (SSD) is a key concept of probabilistic analysis for quantifying ecological risk. I developed a method of probabilistic ecological risk assessment in Japan with a case study of the herbicide simetryn. Then, risk comparison among eleven herbicides was conducted using the developed method. However, one of the most important limitations of SSD application is the lack of sufficient toxicity data for SSD analysis. Thus, an ecotoxicity database was developed for the application of SSD to a wide range of pesticides. After that, I proposed that species batteries of the five species should be the standardized dataset for the SSD analysis of insecticides and herbicides. Finally, I have published a technical guidance document for SSD analysis written in Japanese to promote the application of SSDs in Japan. The remarkable point is that the supplemental Excel-based tool makes it easy to analyze SSDs and conduct ecological risk assessments.

VRAKA—A Probabilistic Risk Assessment Method for Potentially Polluting Shipwrecks

Shipwrecks around the world contain unknown volumes of hazardous substances which, if discharged, could harm the marine environment. Shipwrecks can deteriorate for a number of reasons, including corrosion and physical impact from trawling and other activities, and the probability of a leakage increases with time. Before deciding on possible mitigation measures, there are currently few comprehensive methods for assessing shipwrecks with respect to pollution risks. A holistic method for estimating environmental risks from shipwrecks should be based on well-established risk assessment methods and should take into account both the probability of discharge and the potential consequences. The purpose of this study was therefore to present a holistic risk assessment method for potentially polluting shipwrecks. The focus is set to developing a method for estimating the environmental consequences of potential discharges of hazardous substances from shipwrecks and to combine this with earlier research on a tool for estimating the probability of discharge of hazardous substances. Risk evaluation should also be included in a full risk assessment and is the subject of further research. The consequence assessment was developed for application in three tiers. In Tier 1, the probability of discharge and possible amount of discharge are compared to other shipwrecks. In Tier 2, a risk matrix, including a classification of potential consequences, is suggested as a basis for assessment and comparison. The most detailed level, Tier 3, is based on advanced tools for oil spill trajectory modeling and sensitivity mapping of the Swedish coast. To illustrate the method an example application on two wrecks is presented. Wreck number 1 present a lower probability of discharge and a lower consequence in a Tier 1 and Tier 3 assessment. For the Tier 2 consequence assessment, the two example wrecks present equal consequence. The tool for estimating the probability of discharge of hazardous substances from shipwrecks, and the approach for consequence estimation, offers a comprehensive method for assessing the risks presented by potentially polluting shipwrecks. The method is known as VRAKA (short for shipwreck risk assessment in Swedish) and provides decision support, facilitating prioritization of risk mitigation measures enabling efficient use of available resources.

Enhanced Decision Making through Probabilistic Shipwreck Risk Assessment: Focusing on the Situation in Greece

The potential leakage of oil trapped in the hull of fully or partially submerged shipwrecks has been a growing concern worldwide mainly due to major uncertainties therein and the great potential for environmental damage. The high cost of either preventing or reacting to potential oil discharges from shipwrecks into the environment mandates the use of risk analysis methods in order to identify the most dangerous cases and prioritize the allocation of resources. The purpose of this study is to present a probabilistic risk assessment method that will incorporate the various uncertainties into a structured and quantitative approach. One of the main factors affecting the release of oil from a shipwreck is the amount and progression of corrosion of the steel structure of the wreck, which is a dynamic process. The proposed model will take this into account by applying a time dependent approach that can be used to forecast how the risk rating, that is calculated for each case, changes as a function of time. The analysis will be concluded by applying a sensitivity analysis for the calibration of the model results. Geographically, this study will focus on Greece which presents a particularly interesting case due to its unique geomorphology and its rather developed maritime domain that is a direct consequence thereof. The great number of islands situated in Greece present an additional concern from a risk perspective because oil spill response operations are therefore constituted extremely difficult and costly. Another consideration, which is directly related to the high value of the various tourist activities, is the fact that even a small amount of spilled oil could be catastrophic for the local economies if the response is not fast enough. These issues indicate a growing need for the application of risk analysis tools that will aid in the decision making process relating to the optimum allocation of resources that are needed to efficiently address the problem as well as the prioritization of the most environmentally dangerous shipwrecks.

Branch-and-Bound algorithm applied to uncertainty quantification of a Boiling Water Reactor Station Blackout

Evaluation of the impacts of uncertainty and sensitivity in modeling presents a significant set of challenges in particular to high fidelity modeling. Computational costs and validation of models creates a need for cost effective decision making with regards to experiment design. Experiments designed to validate computation models can be used to reduce uncertainty in the physical model. In some cases, large uncertainty in a particular aspect of the model may or may not have a large impact on the final results. For example, modeling of a relief valve may result in large uncertainty, however, the actual effects on final peak clad temperature in a reactor transient may be small and the large uncertainty with respect to valve modeling may be considered acceptable. Additionally, the ability to determine the adequacy of a model and the validation supporting it should be considered within a risk informed framework. Low fidelity modeling with large uncertainty may be considered adequate if the uncertainty is considered acceptable with respect to risk. In other words, models that are used to evaluate the probability of failure should be evaluated more rigorously with the intent of increasing safety margin. Probabilistic risk assessment (PRA) techniques have traditionally been used to identify accident conditions and transients. Traditional classical event tree methods utilize analysts’ knowledge and experience to identify the important timing of events in coordination with thermal-hydraulic modeling. These methods lack the capability to evaluate complex dynamic systems. In these systems, time and energy scales associated with transient events may vary as a function of transition times and energies to arrive at a different physical state. Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. Unfortunately DPRA methods introduce issues associated with combinatorial explosion of states. This paper presents a methodology to address combinatorial explosion using a Branch-and-Bound algorithm applied to Dynamic Event Trees (DET), which utilize LENDIT (L – Length, E – Energy, N – Number, D – Distribution, I – Information, and T – Time) as well as a set theory to describe system, state, resource, and response (S2R2) sets to create bounding functions for the DET. The optimization of the DET in identifying high probability failure branches is extended to create a Phenomenological Identification and Ranking Table (PIRT) methodology to evaluate modeling parameters important to safety of those failure branches that have a high probability of failure. The PIRT can then be used as a tool to identify and evaluate the need for experimental validation of models that have the potential to reduce risk. In order to demonstrate this methodology, a Boiling Water Reactor (BWR) Station Blackout (SBO) case study is presented.

Human health risk assessment of mercury vapor around artisanal small-scale gold mining area, Palu city, Central Sulawesi, Indonesia

Emissions of elemental mercury, Hg(0), from artisanal small-scale gold mining activities accounted for 37% of total global Hg(0) emissions in 2010. People who live near gold-mining areas may be exposed to high concentrations of Hg(0). Here, we assessed the human health risk due to Hg(0) exposure among residents of Palu city (Central Sulawesi Province, Indonesia). The area around the city has more than 60t of gold reserves, and the nearby Poboya area is the most active gold-mining site in Indonesia. Owing to its geography, the city experiences alternating land and sea breezes.Sampling was done over a period of 3 years (from 2010 Aug. to 2012 Dec.) intermittently with a passive sampler for Hg(0), a portable handheld mercury analyzer, and a mercury analyzer in four areas of the city and in the Poboya gold-processing area, as well as wind speeds and directions in one area of the city. The 24-h average concentration, wind speed, and wind direction data show that the ambient air in both the gold-processing area and the city was always covered by high concentration of mercury vapor. The Hg(0) concentration in the city was higher at night than in the daytime, owing to the effect of land breezes. These results indicate that the inhabitants of the city were always exposed to high concentrations of Hg(0).The average daytime point-sample Hg(0) concentrations in the city, as measured with a handheld mercury analyzer over 3 days in July 2011, ranged from 2096 to 3299ngm−3. In comparison, the average daytime Hg(0) concentration in the Poboya gold-processing area was 12,782ngm−3. All of these concentrations are substantially higher than the World Health Organization air-quality guideline for annual average Hg exposure (1000ngm−3). We used the point-sample concentrations to calculate hazard quotient ratios by means of a probabilistic risk assessment method. The results indicated that 93% of the sample population overall was at risk (hazard quotient ratio ≥1 and cut off at the 95th percentile value of the sample population) of mercury toxicity, that is, damage to the central nervous system due to chronic exposure. The corresponding percentages for the northern, central, southern, and western areas of the city were 83%, 84%, 95%, and 95%, respectively. Our results indicate that the residents of Palu city are at serious risk from exposure to high concentrations of atmospheric Hg(0).

A method of probabilistic risk assessment for energy performance and cost using building energy simulation

Energy efficient buildings rely on simulation to predict energy performance. However, problems associated with simulation tools can lead to surprises when discrepancies are found between actual and predicted building energy performance; this frustrates building owners, investors, and designers.A probabilistic method of risk assessment for the calculation of energy use intensity and total utility cost in energy performance has been developed. Sensitive and uncertain parameters were selected and given a probability distribution instead of one fixed value for the simulations. Latin hypercube sampling was used to generate input combinations with parameter values picked stochastically from distributions based on the Monte Carlo method. With these input combinations, 10,000 simulations on seven distributed parameters were run using a cloud processing service. The output data, energy use intensity and energy cost, were analyzed using curve-fitting techniques to find a best-fit distribution, which could be used for risk analysis of energy performance and cost. The results illustrate the probability and reliability of prediction within a specific range. Instead of relying on a single value, these curves would help designers better evaluate design alternatives, and the probability distribution of energy performance and cost would be useful in making decisions about investments for energy efficient projects.

Risk management decisions for pesticides and threatened and endangered species: The role of uncertainty analysis

ABSTRACTDespite data gaps and information shortfalls, government agencies in the United States are expected to produce timely and defensible decisions to regulate pesticide use under the Federal Insecticide, Fungicide, and Rodenticide Act and in compliance with the Endangered Species Act. The decision to register a pesticide is predicated on a conclusion that no unreasonable effects will accrue to the environment, including threatened and endangered species. We recognize that the definition of acceptable risk is a policy judgment stemming from legislative language and judicial interpretation. However, a common risk assessment approach with similar technical underpinnings and a high degree of transparency used by all the agencies would be cost effective and more likely to achieve consensus among interested parties. Quantitative probabilistic risk assessment (PRA) methods can be used to develop risk estimates and to describe the level of confidence in these estimates. PRA methods can also differentiate among the contributions of natural stochasticity, measurement variability, and lack of knowledge. Because this approach enhances transparency and increases understanding of the implications of limited data sets and associated assumptions, we encourage the appropriate agencies to implement PRA methods as a means of reaching common ground when assessing risks of pesticides to listed species.

ASSESSMENT OF RUNWAY ACCIDENT HAZARDS IN NIGERIA AVIATION SECTOR

Aviation crashes all over the world have recently been on the high rise, stemming from negligence, mechanical faults, weather, ground control errors, pilot errors, taxing and maintenance crew errors as probable reasons for such accidents. This study models the probabilistic risk assessment of runway accident hazards in Nigeria aviation sector. Six categories of runway accident hazards with their corresponding basic events were identified and modeled using fault tree analysis method of probabilistic risk assessment. The six categories of runway accident hazards are runway surface conditions, weather conditions, collision risk, aircraft system failure, approach/takeoff procedures and human factors. The Fault Tree developed is a system of OR-gates and the weights for each hazard were derived through a domain/expert opinion. The estimated probability of occurrence of runway accident which is the top event of the Fault Tree model is 0.2624. Fault Tree Analysis; thus, identifies the most likely root causes of runway accident through importance measures. The results of the analysis show close relationship of runway accidents in Nigeria aviation sector with aircraft system failure, approach/takeoff procedures, human factor, weather conditions and collision risk.

Integrated probabilistic risk assessment for nanoparticles: the case of nanosilica in food

Insight into risks of nanotechnology and the use of nanoparticles is an essential condition for the social acceptance and safe use of nanotechnology. One of the problems with which the risk assessment of nanoparticles is faced is the lack of data, resulting in uncertainty in the risk assessment. We attempt to quantify some of this uncertainty by expanding a previous deterministic study on nanosilica (5–200 nm) in food into a fully integrated probabilistic risk assessment. We use the integrated probabilistic risk assessment method in which statistical distributions and bootstrap methods are used to quantify uncertainty and variability in the risk assessment. Due to the large amount of uncertainty present, this probabilistic method, which separates variability from uncertainty, contributed to a better understandable risk assessment. We found that quantifying the uncertainties did not increase the perceived risk relative to the outcome of the deterministic study. We pinpointed particular aspects of the hazard characterization that contributed most to the total uncertainty in the risk assessment, suggesting that further research would benefit most from obtaining more reliable data on those aspects.Electronic supplementary materialThe online version of this article (doi:10.1007/s11051-015-2911-y) contains supplementary material, which is available to authorized users.

An Approach to Grid-based Fire Frequency Analysis for Design Accidental Loads in Offshore Installations

This paper describes the approach for establishing the Design Accidental Load (DAL) fire based on a grid-based fire risk analysis. Representative cases are screened via an initial fire risk analysis where the leak frequencies, ignition probabilities and inventories are combined to determine the cases with the highest risk. The fire risk analysis is subsequently performed based on the consequence results and the fire frequencies. Although many initiates for risk assessment were taken, there are many limitation and uncertainties on frequency analysis. Especially, calculation of ignition probability for an accidental hydrocarbon release on an offshore platform is a complex issue. To overcome these limitations of historical accident data, time dependent ignition model is developed a model for probability of ignition of hydrocarbon gas leakages on offshore platforms on based of ignition model presented by some JIPs for offshore risk assessment and improved understanding of ignition mechanisms. In this paper, we reviewed the existing probabilistic risk assessment method, such as ignition models, fire and explosion models, and selected the ones most suitable for offshore conditions. Then applied grid-based fire frequency analysis in the risk assessment. Two main revisions were incorporated: a grid-based approach was adopted to enable better consequence/impact modelling and analysis of radiation, and an enhanced onsite ignition model was integrated in the consequence assessment process to obtain better results. This study will be useful for the fire frequency analysis on offshore platform topsides as one of procedures of quantitative risk assessment.

ICONE23-2017 BRANCH-AND-BOUND ALGORITHM APPLIED TO DYNAMIC PRA WITH UNCERTAINTY QUANTIFICATION FOR LWR STATION BLACKOUT

Probabilistic Risk Assessment (PRA) is an important tool for evaluating risk in nuclear power plants. Dynamic PRA (DPRA) is an extension of traditional PRA methods that account for dynamic and phenomenological effects associated with time-dependent complex dynamic systems. Here we investigated dynamic event trees and optimization per focus on identifying the highest probability of system failure. Using a Branch-and-Bound (B&B) algorithm that relies on and develops bounding functions to prune or delete branches that will not yield the optimal solution (i.e., clad failure). The approach also used novel LENDIT (length, energy, number, distribution, information, time) metrics and S2R2 (state, systems, resources, response) sets to support an expert-based approach that is linked to constraints per use of the B&B algorithm. Results to date indicate that this approach is effective in reducing simulation time and thus mitigating the state explosion of thermal-hydraulic states. The work demonstrated the ability to evaluate uncertainty such that a risk-informed, quantitative PIRT (phenomena identification ranking table) is generated. Quantitative PIRT (QPIRT) can be used to improve models and identify validation needs with respect to risk. Two case studies using reference PWR and BWR plant configurations under SBO were evaluated. The implementation of the B&B algorithm yielded a significant reduction (>50%) in simulation costs. QPIRT ranking for the PWR showed that lower fidelity models combined with system redundancy produces adequate results with respect to risk. For BWR SBO, the modeling uncertainty does not present a challenge with respect to risk. Recovery of the SBO requires either restoration of the AC power or activation of firewater injection combined with operator action to depressurize the system through the automatic depressurization system. The timing of both automatic and manual safety system actuation is indeed critical to the outcome reactor state. Reactor power and firewater injection capacity provided the highest degree of correlation to model success.

Risk assessment of population inhalation exposure to volatile organic compounds and carbonyls in urban China

Over the past three decades, China has experienced rapid urbanization. The risks to its urban population posed by inhalation exposure to hazardous air pollutants (HAPs) have not been well characterized. Here, we summarize recent measurements of 16 highly prevalent HAPs in urban China and compile their distribution inputs. Based on activity patterns of urban Chinese working adults, we derive personal exposures. Using a probabilistic risk assessment method, we determine cancer and non-cancer risks for working females and males. We also assess the uncertainty associated with risk estimates using Monte Carlo simulation, accounting for variations in HAP concentrations, cancer potency factors (CPFs) and inhalation rates. Average total lifetime cancer risks attributable to HAPs are 2.27×10−4 (2.27 additional cases per 10,000 people exposed) and 2.93×10−4 for Chinese urban working females and males, respectively. Formaldehyde, 1,4-dichlorobenzene, benzene and 1,3-butadiene are the major risk contributors yielding the highest median cancer risk estimates, >1×10−5. About 70% of the risk is due to exposures occurring in homes. Outdoor sources contribute most to the risk of benzene, ethylbenzene and carbon tetrachloride, while indoor sources dominate for all other compounds. Chronic exposure limits are not exceeded for non-carcinogenic effects, except for formaldehyde. Risks are overestimated if variation is not accounted for. Sensitivity analyses demonstrate that the major contributors to total variance are range of inhalation rates, CPFs of formaldehyde, 1,4-dichlorobenzene, benzene and 1,3-butadiene, and indoor home concentrations of formaldehyde and benzene. Despite uncertainty, risks exceeding the acceptable benchmark of 1×10−6 suggest actions to reduce exposures. Future efforts should be directed toward large-scale measurements of air pollutant concentrations, refinement of CPFs and investigation of population exposure parameters. The present study is a first effort to estimate carcinogenic and non-carcinogenic risks of inhalation exposure to HAPs for the large working populations of Chinese cites.

Optimization method to branch-and-bound large SBO state spaces under dynamic probabilistic risk assessment via use of LENDIT scales and S2R2 sets

Traditional probabilistic risk assessment (PRA) methods have been developed to evaluate risk associated with complex systems; however, PRA methods lack the capability to evaluate complex dynamic systems. In these systems, time and energy scales associated with transient events may vary as a function of transition times and energies to arrive at a different physical state. Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. Unfortunately DPRA methods introduce issues associated with combinatorial explosion of states. In order to address this combinatorial complexity, a branch-and-bound optimization technique is applied to the DPRA formalism to control the combinatorial state explosion. In addition, a new characteristic scaling metric (LENDIT – length, energy, number, distribution, information and time) is proposed as linear constraints that are used to guide the branch-and-bound algorithm to limit the number of possible states to be analyzed. The LENDIT characterization is divided into four groups or sets – ‘state, system, resource and response’ (S2R2) – describing reactor operations (normal and off-normal). In this paper we introduce the branch-and-bound DPRA approach and the application of LENDIT scales and S2R2 sets to a station blackout (SBO) transient.

Cancer risk to First Nations' people from exposure to polycyclic aromatic hydrocarbons near in-situ bitumen extraction in Cold Lake, Alberta.

BackgroundThe Alberta oil sands are an important economic resource in Canada, but there is growing concern over the environmental and health effects as a result of contaminant releases and exposures. Recent studies have shown a temporal and spatial trend of increased polycyclic aromatic hydrocarbon (PAH) concentrations in sediments and snowpack near the Athabasca oil sands operations (i.e., open pit mines), but thus far similar studies have not been done for the Cold Lake region where steam assisted gravity drainage (in situ) extraction is performed.MethodsMany PAHs are known mutagenic carcinogens, and this study measured soil and atmospheric concentrations of PAHs in the Cold Lake region to assess the excess lifetime cancer risk posed to the First Nations’ inhabitants of the region. Using both deterministic and probabilistic risk assessment methods, excess lifetime cancer risks were calculated for exposures from inhalation or inadvertent soil ingestion.ResultsThe mean excess cancer risk for First Nations’ people through ingestion who engage in traditional wilderness activities in the Cold Lake region was 0.02 new cases per 100,000 with an upper 95% risk level of 0.07 cases per 100,000. Exposure to PAHs via inhalation revealed a maximum excess lifetime cancer risk of less than 0.1 cases per 100,000.ConclusionsExcess lifetime risk values below 1 case per 100,000 is generally considered negligible, thus our analyses did not demonstrate any significant increases in cancer risks associated with PAH exposures for First Nations people inhabiting the Cold Lake region.

A probabilistic framework for correlated seismic downtime and repair cost estimation of geo‐structures

SUMMARYAn important component of probabilistic risk assessment methods is the development of models to quantify the direct consequences of damage to geo‐structural components for a given intensity of the hazard. This paper presents a general probabilistic framework for correlated repair cost and downtime estimation of geo‐structures exposed to seismic hazards. The framework uses as input the results of nonlinear time‐history analysis of geo‐structures for the set of earthquake records that are representative of the seismic hazard models for the region of interest. The repair cost and downtime are estimated for individual earthquakes probabilistically considering the uncertainties associated with damage states. In addition, the formulation of the repair cost and downtime accounts for the reduction in the repair requirements as the number of damaged components in the given damage state increases. An analytical linear and two bilinear regression models are proposed for conditional correlated seismic repair cost and downtime estimation of geo‐structures given the intensity measure. The proposed framework is demonstrated by developing seismic repair models of a typical pile‐supported wharf structure on the west coast of the United States. The presented framework is general and can be applied to other types of geo‐structures and hazards and can include other decision variables such as loss of life as well. Copyright © 2013 John Wiley & Sons, Ltd.

Application of probabilistic risk assessment at a coking plant site contaminated by polycyclic aromatic hydrocarbons

Application of Probabilistic Risk Assessment (PRA) and Deterministic Risk Assessment (DRA) at a coking plant site was compared. By DRA, Hazard Quotient (HQ) following exposure to Naphthalene (Nap) and Incremental Life Cancer Risk (ILCR) following exposure to Benzo(a)pyrene (Bap) were 1.87 and 2.12 × 10−4. PRA revealed valuable information regarding the possible distribution of risk, and risk estimates of DRA located at the 99.59th and 99.76th percentiles in the risk outputs of PRA, which indicated that DRA overestimated the risk. Cleanup levels corresponding acceptable HQ level of 1 and ILCR level of 10−6 were also calculated for both DRA and PRA. Nap and Bap cleanup levels were 192.85 and 0.14 mg·kg−1 by DRA, which would result in only 0.25% and 0.06% of the exposed population to have a risk higher than the acceptable risk, according to the outputs of PRA. The application of PRA on cleanup levels derivation would lift the cleanup levels 1.9 times for Nap and 2.4 times for Bap than which derived by DRA. For this coking plant site, the remediation scale and cost will be reduced in a large portion once the method of PRA is used. Sensitivity analysis was done by calculating the contribution to variance for each exposure parameter and it was found that contaminant concentration in the soil (Cs), exposure duration (ED), total hours spent outdoor per day (ETout), soil ingestion rate (IRs), the air breathing rate (IRa) and bodyweight (BW) were the most important parameters for risk and cleanup levels calculations.

Rockfall hazard and risk assessment of road slopes.

This paper presents and compares the main methods of hazard and risk assessment for road slopes. Hazard assessment is achieved by rating several parameters such as the slope’s geometry, traffic conditions, the geology and the rockmass properties, weather conditions, historical rockfall data etc. A hazard assessment can also be executed using 2D or 3D trajectory models, by combining the frequency of a rockfall and the kinetic energy of a falling rock. Several methodologies have been developed for risk assessment, varying from simplistic approaches to comprehensive probabilistic or quantitative risk assessment methods. Finally, the most suitable methods were used in order to assess the level of hazard and risk as an example (the data from two sections of the national road at Tempi Gorge, Greece) where many rockfall events occurred in the past few years.

Application of a fluorometric microplate algal toxicity assay for riverine periphytic algal species

Although riverine periphytic algae attached to riverbed gravel are dominant species in flowing rivers, there is limited toxicity data on them because of the difficulty in cell culture and assays. Moreover, it is well known that sensitivity to pesticides differ markedly among species, and therefore the toxicity data for multiple species need to be efficiently obtained. In this study, we investigated the use of fluorometric microplate toxicity assay for testing periphytic algal species. We selected five candidate test algal species Desmodesmus subspicatus, Achnanthidium minutissimum, Navicula pelliculosa, Nitzschia palea, and Pseudanabaena galeata. The selected species are dominant in the river, include a wide range of taxon, and represent actual species composition. Other additional species were also used to compare the sensitivity and suitability of the microplate assay. A 96-well microplate was used as a test chamber and algal growth was measured by in-vivo fluorescence. Assay conditions using microplate and fluorometric measurement were established, and sensitivities of 3,5-dichlorophenol as a reference substance were assayed. The 50 percent effect concentrations (EC50s) obtained by fluorometric microplate assay and those obtained by conventional Erlenmeyer flask assay conducted in this study were consistent. Moreover, the EC50 values of 3,5-dichlorophenol were within the reported confidence intervals in literature. These results supported the validity of our microplate assay. Species sensitivity distribution (SSD) analysis was conducted using the EC50s of five species. The SSD was found to be similar to the SSD obtained using additional tested species, suggesting that SSD using the five species largely represents algal sensitivity. Our results provide a useful and efficient method for high-tier probabilistic ecological risk assessment of pesticides.

Aquatic predicted no-effect concentration for three polycyclic aromatic hydrocarbons and probabilistic ecological risk assessment in Liaodong Bay of the Bohai Sea, China

Predicted no-effect concentration (PNEC) is often used in ecological risk assessment to determine low-risk concentrations for chemicals. In the present study, native marine species were selected for toxicity testing. The PNECs for three polycyclic aromatic hydrocarbons (PAHs), specifically phenanthrene (Phe), pyrene (Pyr), and benzo[a]pyrene (BaP), were derived from chronic and acute toxicity data with log-normal statistical methods. The achieved PNECs for Phe, Pyr, and BaP were 2.33, 1.09, and 0.011μg/L, respectively. In Jinzhou Bay and the Shuangtaizi River Estuary of Liaodong Bay in the Bohai Sea, China, the surface water concentrations of the three PAHs were analyzed by gas chromatography-mass spectrometry. Based on two probabilistic ecological risk assessment (PERA) methods, namely probabilistic risk quotient and joint probability curve, the potential risk of Phe, Pyr, and BaP in Jinzhou Bay and Shuangtaizi River Estuary was assessed. The same order of ecological risk (BaP > Phe > Pyr) was found by both models. Our study considered regional characteristics of marine biota during the calculation of PNECs, and the PERA methods provided probabilities of potential ecological risks of chemicals. Within the study area, further research on BaP is required due to its high potential ecological risk.