A refined ecological risk assessment for California red-legged frog, Delta smelt, and California tiger salamander exposed to malathion

Ecological Risk Assessment of Organochlorine Pesticides and Polychlorinated Biphenyls in Coastal Sediments in China

Although the ecological risk of emerging contaminants is currently a research hotspot in China and abroad, few studies have investigated the ecological risk of pesticide pollutants in Chinese coastal sediments. In this study, nine pesticide pollutants included in the "List of New Key Pollutants for Control (2023 Edition)" issued by the Chinese government were used as the research objects, and the environmental exposure of pesticide pollutants in China's coastal sediments was analyzed. The baseline sediment quality criteria were deduced using the balanced distribution method, and a multi-level ecological risk assessment of pesticides in sediment was performed. The results showed that the nine pesticide pollutants were widespread in Chinese coastal sediments, with concentrations ranging from 0.01 ng·g-1 to 330 ng·g-1. The risk quotient assessment showed that endosulfan and DDT posed medium environmental risks to the Chinese coastal sediment environment, and PCBs posed medium risks in some bays of the East China Sea. The semi-probabilistic, optimized semi-probability evaluation and joint probability curve (JPC) assessments all show that endosulfan and DDT pose a certain degree of risk to the environment.

Challenges with the current methodology for conducting Endangered Species Act risk assessments for pesticides in the United States

The US Environmental Protection Agency (USEPA or the Agency) is responsible for administering the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA). The Agency is also required to assess the potential risks of pesticides undergoing registration or re-registration to threatened and endangered (i.e., listed) species to ensure compliance with the Endangered Species Act. To assess potential risks to listed species, a screening-level risk assessment in the form of a biological evaluation (BE) is undertaken by the Agency for each pesticide. Given the large number of registration actions handled by the USEPA annually, efficient tools for conducting BEs are desirable. However, the "Revised Method" that is the basis for the USEPA's BE process has been ineffective at filtering out listed species and critical habitats that are at de minimis risk to pesticides. In the USEPA's BEs, the Magnitude of Effect Tool (MAGtool) has been used to determine potential risks to listed species that potentially co-occur with pesticide footprints. The MAGtool is a highly prescriptive, high-throughput compilation of existing FIFRA screening-level models with a geospatial interface. The tool has been a significant contributor to risk inflation and ultimately process inefficiency. The ineffectiveness of the tool stems from compounding conservatism, unrealistic and unreasonable assumptions regarding usage, limited application of species-specific data, lack of consideration of multiple lines of evidence, and inability to integrate higher-tier data. Here, we briefly describe the MAGtool and the critical deficiencies that impair its effectiveness, thus undermining its intention. Case studies are presented to highlight the deficiencies and solutions are recommended for improving listed species assessments in the future. Integr Environ Assess Manag 2023;19:817-829. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Occurrence, spatial distribution, and potential risks of organic micropollutants in urban surface waters from qinghai, northwest China

Lack of knowledge on the destiny of organic micropollutants (OMPs) in the Tibetan Plateau region of China prevents the public from being aware of the need for protecting these unique aquatic ecosystems that are precious water resources and source areas of the Yellow River. To address this knowledge gap, this study systematically investigated the multi-residue analysis, distribution, and potential risks of six types of OMPs, namely, neonicotinoid pesticides (NEOs), fungicides, organophosphate esters (OPEs), organophosphorus pesticides (OPPs), psychoactive substances (PSs), and antidepressants (ADs), in surface waters of major cities in Qinghai. A total of 31 compounds, consisting of 8 NEOs, 1 fungicide, 12 OPEs, 2 OPPs, 5 PSs, and 3 ADs, were detected in >50% of the sites, showing their ubiquitous nature in the study area. Results showed that the total OMP concentration in surface water was 28.3-908 ng/L, and OPEs were the dominant composition (48.6%-97.4%). The risk quotient values of the detected diazinon and dursban regularly exceeded 1 for aquatic organisms at all sampling sites, indicating moderate-high chronic ecological risk. The joint probability curves showed that dursban and NEOs have higher risk levels than other OMPs. Although the results of the non-carcinogenic total hazard quotient of the OMPs in the surface water was less than 1 in all age groups and the carcinogenic risk was lower than the negligible risk level, the potential risks to children and infants were considerably greater and should not be underestimated. In addition to pollutant concentration and exposure duration, ingestion rate and body weight (BW) are also important factors affecting health risk, with BW having a negative effect. To the best of the authors' knowledge, this report is the first to describe OMP pollution in Qinghai, and the results provide new insight into the ecological security of the water resources of the Tibetan Plateau.

A multi-scale approach for identification of potential pesticide use sites impacting vernal pool critical habitat in California

Spatially explicit ecological risk assessment (ERA) requires estimating the overlap between chemical and receptor distribution to evaluate the potential impacts of exposure on nontarget organisms. Pesticide use estimation at field level is prone to error due to inconsistencies between ground-reporting and geospatial data coverage; attempts to rectify these inconsistencies have been limited in approach and rarely scaled to multiple crop types. We built upon a previously developed Bayesian approach to combine multiple crop types for a probabilistic determination of field-crop assignments and to examine co-occurrence of critical vernal pool habitats and bifenthrin application within a 5-county area in California (Madera, Merced, Sacramento, San Joaquin, and Stanislaus counties). We incorporated a multi-scale repeated sampling approach with an area constraint to improve the delineation of field boundaries and better capture variability in crop assignments and rotation schemes. After comparing the accuracy of the spatial probabilistic approach to USDA Census of Agriculture crop acreage data, we found our approach allows more specificity in the combination of crop types represented by the potential application area and improves acreage estimates when compared to traditional deterministic approaches. In addition, our multi-scale sampling scheme improved estimates of bifenthrin acreage variability for co-occurrence analysis and allowed for estimates of crop rotations that were previously uncaptured. Our approach could be leveraged for more realistic, spatially resolved exposure and effects models both in and outside of California.

A critical review of effect modeling for ecological risk assessment of plant protection products

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).

Assessment of risks to listed species from the use of atrazine in the USA: a perspective

Atrazine is a triazine herbicide used predominantly on corn, sorghum, and sugarcane in the US. Its use potentially overlaps with the ranges of listed (threatened and endangered) species. In response to registration review in the context of the Endangered Species Act, we evaluated potential direct and indirect impacts of atrazine on listed species and designated critical habitats. Atrazine has been widely studied, extensive environmental monitoring and toxicity data sets are available, and the spatial and temporal uses on major crops are well characterized. Ranges of listed species are less well-defined, resulting in overly conservative designations of "May Effect". Preferences for habitat and food sources serve to limit exposure among many listed animal species and animals are relatively insensitive. Atrazine does not bioaccumulate, further diminishing exposures among consumers and predators. Because of incomplete exposure pathways, many species can be eliminated from consideration for direct effects. It is toxic to plants, but even sensitive plants tolerate episodic exposures, such as those occurring in flowing waters. Empirical data from long-term monitoring programs and realistic field data on off-target deposition of drift indicate that many other listed species can be removed from consideration because exposures are below conservative toxicity thresholds for direct and indirect effects. Combined with recent mitigation actions by the registrant, this review serves to refine and focus forthcoming listed species assessment efforts for atrazine.Abbreviations: a.i. = Active ingredient (of a pesticide product). AEMP = Atrazine Ecological Monitoring Program. AIMS = Avian Incident Monitoring SystemArach. = Arachnid (spiders and mites). AUC = Area Under the Curve. BE = Biological Evaluation (of potential effects on listed species). BO = Biological Opinion (conclusion of the consultation between USEPA and the Services with respect to potential effects in listed species). CASM = Comprehensive Aquatic System Model. CDL = Crop Data LayerCN = field Curve Number. CRP = Conservation Reserve Program (lands). CTA = Conditioned Taste Avoidance. DAC = Diaminochlorotriazine (a metabolite of atrazine, also known by the acronym DACT). DER = Data Evaluation Record. EC25 = Concentration causing a specified effect in 25% of the tested organisms. EC50 = Concentration causing a specified effect in 50% of the tested organisms. EC50_RGR = Concentration causing a 50% reduction in relative growth rate. ECOS = Environmental Conservation Online System. EDD = Estimated Daily Dose. EEC = Expected Environmental Concentration. EFED = Environmental Fate and Effects Division (of the USEPA). EFSA = European Food Safety Agency. EIIS = Ecological Incident Information System. ERA = Environmental Risk Assessment. ESA = Endangered Species Act. ESU = Evolutionarily Significant UnitsFAR = Field Application RateFIFRA = Federal Insecticide, Fungicide, and Rodenticide Act. FOIA = Freedom of Information Act (request). GSD = Genus Sensitivity Distribution. HC5 = Hazardous Concentration for ≤ 5% of species. HUC = Hydrologic Unit Code. IBM = Individual-Based Model. IDS = Incident Data System. K_OC = Partition coefficient between water and organic matter in soil or sediment. K_OW = Octanol-Water partition coefficient. LC50 = Concentration lethal to 50% of the tested organisms. LC-MS-MS = Liquid Chromatograph with Tandem Mass Spectrometry. LD50 = Dose lethal to 50% of the tested organisms. LAA = Likely to Adversely Affect. LOAEC = Lowest-Observed-Adverse-Effect Concentration. LOC = Level of Concern. MA = May Affect. MATC = Maximum Acceptable Toxicant Concentration. NAS = National Academy of Sciences. NCWQR = National Center of Water Quality Research. NE = No Effect. NLAA = Not Likely to Adversely Affect. NMFS = National Marine Fisheries Service. NOAA = National Oceanic and Atmospheric Administration. NOAEC = No-Observed-Adverse-Effect Concentration. NOAEL = No-Observed-Adverse-Effect Dose-Level. OECD = Organization of Economic Cooperation and Development. PNSP = Pesticide National Synthesis Project. PQ = Plastoquinone. PRZM = Pesticide Root Zone Model. PWC = Pesticide in Water Calculator. QWoE = Quantitative Weight of Evidence. RGR = Relative growth rate (of plants). RQ = Risk Quotient. RUD = Residue Unit Doses. SAP = Science Advisory Panel (of the USEPA). SGR = Specific Growth Rate. SI = Supplemental Information. SSD = Species Sensitivity Distribution. SURLAG = Surface Runoff Lag Coefficient. SWAT = Soil & Water Assessment Tool. SWCC = Surface Water Concentration Calculator. UDL = Use Data Layer (for pesticides). USDA = United States Department of Agriculture. USEPA = United States Environmental Protection Agency. USFWS = United States Fish and Wildlife Service. USGS = United States Geological Survey. WARP = Watershed Regressions for Pesticides.

Agriculture Development, Pesticide Application and Its Impact on the Environment

Pesticides are indispensable in agricultural production. They have been used by farmers to control weeds and insects, and their remarkable increases in agricultural products have been reported. The increase in the world's population in the 20th century could not have been possible without a parallel increase in food production. About one-third of agricultural products are produced depending on the application of pesticides. Without the use of pesticides, there would be a 78% loss of fruit production, a 54% loss of vegetable production, and a 32% loss of cereal production. Therefore, pesticides play a critical role in reducing diseases and increasing crop yields worldwide. Thus, it is essential to discuss the agricultural development process; the historical perspective, types and specific uses of pesticides; and pesticide behavior, its contamination, and adverse effects on the natural environment. The review study indicates that agricultural development has a long history in many places around the world. The history of pesticide use can be divided into three periods of time. Pesticides are classified by different classification terms such as chemical classes, functional groups, modes of action, and toxicity. Pesticides are used to kill pests and control weeds using chemical ingredients; hence, they can also be toxic to other organisms, including birds, fish, beneficial insects, and non-target plants, as well as air, water, soil, and crops. Moreover, pesticide contamination moves away from the target plants, resulting in environmental pollution. Such chemical residues impact human health through environmental and food contamination. In addition, climate change-related factors also impact on pesticide application and result in increased pesticide usage and pesticide pollution. Therefore, this review will provide the scientific information necessary for pesticide application and management in the future.

How Do Indirect Effects of Contaminants Inform Ecotoxicology? A Review

Indirect effects in ecotoxicology are defined as chemical- or pollutant-induced alterations in the density or behavior of sensitive species that have cascading effects on tolerant species in natural systems. As a result, species interaction networks (e.g., interactions associated with predation or competition) may be altered in such a way as to bring about large changes in populations and/or communities that may further cascade to disrupt ecosystem function and services. Field studies and experimental outcomes as well as models indicate that indirect effects are most likely to occur in communities in which the strength of interactions and the sensitivity to contaminants differ markedly among species, and that indirect effects will vary over space and time as species composition, trophic structure, and environmental factors vary. However, knowledge of indirect effects is essential to improve understanding of the potential for chemical harm in natural systems. For example, indirect effects may confound laboratory-based ecological risk assessment by enhancing, masking, or spuriously indicating the direct effect of chemical contaminants. Progress to better anticipate and interpret the significance of indirect effects will be made as monitoring programs and long-term ecological research are conducted that facilitate critical experimental field and mesocosm investigations, and as chemical transport and fate models, individual-based direct effects models, and ecosystem/food web models continue to be improved and become better integrated.

Resveratrol attenuates malathion-induced liver damage by reducing oxidative stress

BACKGROUND:

Malathion is an organophosphate insecticide which disrupts the antioxidant system of the body. Resveratrol is a phytoestrogen and antioxidant of the red grape.

AIM AND OBJECTIVE:

This study was designed to evaluate the effects of resveratrol against toxic effects of malathion to the liver of rats.

MATERIALS AND METHODS:

In this study, 48 male rats were randomly assigned to 8 groups: control normal (saline) and malathion control-treated groups (50 mg/kg), resveratrol groups (2, 8, and 20 mg/kg), and malathion + resveratrol-treated groups (2, 8, and 20 mg/kg). Treatments were administered intraperitoneally daily for 14 days. Griess technique was assessed for determined serum nitrite oxide level. Aspartate aminotransferase, alanine aminotransferase, and alkaline phosphatase concentrations were determined for liver functional disturbances. In addition, thiobarbituric acid reactive species, antioxidant capacity, the diameter of hepatocytes, and the central hepatic vein (CHV) were investigated.

RESULTS:

Malathion administration significantly improved liver malondialdehyde (MDA) and nitrite oxide level, the mean diameter of CHV and hepatocyte, and liver enzymes and decreased tissue ferric-reducing ability of plasma (FRAP) level compared to the normal control group (P < 0.01). The resveratrol and resveratrol + malathion treatments at all doses significantly reduced the mean diameter of hepatocyte and CHV, liver enzymes, kidney MDA, and nitrite oxide levels and increased tissue FRAP level compared to the malathion control group (P < 0.01).

CONCLUSION:

It seems that resveratrol administration improved liver injury induced by malathion in rats.

Ecological risk assessment of fifty pharmaceuticals and personal care products (PPCPs) in Chinese surface waters: A proposed multiple-level system

Interest in the risks posed by trace concentrations of pharmaceuticals and personal care products (PPCPs) in surface waters is increasing, particularly with regard to potential effects of long-term, low-dose exposures of aquatic organisms. In most cases, the actual studies on PPCPs were risk assessments at screening-level, and accurate estimates were scarce. In this study, exposure and ecotoxicity data of 50 PPCPs were collected based on our previous studies, and a multiple-level environmental risk assessment was performed. The 50 selected PPCPs are likely to be frequently detected in surface waters of China, with concentrations ranging from the ng L^-1 to the low-g L^-1, and the risk quotients based on median concentrations ranged from 2046 for nonylphenol to 0 for phantolide. A semi-probabilistic approach screened 33 PPCPs that posed potential risks to aquatic organisms, among which 15 chemicals (nonylphenol, sulfamethoxazole, di (2-ethylhexyl) phthalate, 17β-ethynyl estradiol, caffeine, tetracycline, 17β-estradiol, estrone, dibutyl phthalate, ibuprofen, carbamazepine, tonalide, galaxolide, triclosan, and bisphenol A) were categorized as priority compounds according to an optimized risk assessment, and then the refined probabilistic risk assessment indicated 12 of them posed low to high risk to aquatic ecosystem, with the maximum risk products ranged from 1.54% to 17.38%. Based on these results, we propose that the optimized risk assessment was appropriate for screening priority contaminants at national scale, and when a more accurate estimation is required, the refined probability risk assessment is useful. The methodology and process might provide reference for other research of chemical evaluation and management for rivers, lakes, and sea waters.

A sensitivity analysis of pesticide concentrations in California Central Valley vernal pools

Vernal pools are ephemeral wetlands that provide critical habitat to many listed species. Pesticide fate in vernal pools is poorly understood because of uncertainties in the amount of pesticide entering these ecosystems and their bioavailability throughout cycles of wet and dry periods. The Pesticide Water Calculator (PWC), a model used for the regulation of pesticides in the US, was used to predict surface water and sediment pore water pesticide concentrations in vernal pool habitats. The PWC model (version 1.59) was implemented with deterministic and probabilistic approaches and parameterized for three agricultural vernal pool watersheds located in the San Joaquin River basin in the Central Valley of California. Exposure concentrations for chlorpyrifos, diazinon and malathion were simulated. The deterministic approach used default values and professional judgment to calculate point values of estimated concentrations. In the probabilistic approach, Monte Carlo (MC) simulations were conducted across the full input parameter space with a sensitivity analysis that quantified the parameter contribution to model prediction uncertainty. Partial correlation coefficients were used as the primary sensitivity metric for analyzing model outputs. Conditioned daily sensitivity analysis indicates curve number (CN) and the universal soil loss equation (USLE) parameters as the most important environmental parameters. Therefore, exposure estimation can be improved efficiently by focusing parameterization efforts on these driving processes, and agricultural pesticide inputs in these critical habitats can be reduced by best management practices focused on runoff and sediment reductions.

Risk assessment considerations for plant protection products and terrestrial life-stages of amphibians

Some amphibians occur in agricultural landscapes during certain periods of their life cycle and consequently might be exposed to plant protection products (PPPs). While the sensitivity of aquatic life-stages is considered to be covered by the standard assessment for aquatic organisms (especially fish), the situation is less clear for terrestrial amphibian life-stages. In this paper, considerations are presented on how a risk assessment for PPPs and terrestrial life-stages of amphibians could be conducted. It discusses available information concerning the toxicity of PPPs to terrestrial amphibians, and their potential exposure to PPPs in consideration of aspects of amphibian biology. The emphasis is on avoiding additional vertebrate testing as much as possible by using exposure-driven approaches and by making use of existing vertebrate toxicity data, where appropriate. Options for toxicity testing and risk assessment are presented in a flowchart as a tiered approach, progressing from a non-testing approach, to simple worst-case laboratory testing, to extended laboratory testing, to semi-field enclosure tests and ultimately to full-scale field testing and monitoring. Suggestions are made for triggers to progress to higher tiers. Also, mitigation options to reduce the potential for exposure of terrestrial life-stages of amphibians to PPPs, if a risk were identified, are discussed. Finally, remaining uncertainties and research needs are considered by proposing a way forward (road map) for generating additional information to inform terrestrial amphibian risk assessment.