Integrated Environmental Assessment and Management最新文献

Offspring of adult Yellowstone cutthroat trout (YCT) exposed to a range of selenium (Se) concentrations in situ were reared in a laboratory setting to assess effects on survival, growth and abnormalities. Maternal whole body Se concentrations ranged from 2.6 to 25.7 mg/kg dry weight (dw) for Site fish while corresponding Se concentrations in embryos ranged from 3.4 to 47.6 mg/kg dw. A significant relationship was found between egg and whole-body tissue concentrations. Endpoints were evaluated at hatch to swim up and hatch to test termination for survival and abnormalities (e.g., deformities and edema). Dose response models were developed to visualize the data distribution and predicted EC10 (the effect concentration where a 10% effect is observed) values for survival and abnormality endpoints relative to egg Se concentrations. EC10s for the survival endpoint were nearly identical, ranging from 35.1 to 35.6 mg/kg dw while EC10s for the abnormality endpoint ranged from 10.6 to 35.3 mg/kg dw. Using the best fit models for survival and abnormality endpoints the EC10 for survival was 35.1 mg/kg dw and the EC10 for abnormalities was 35.2 mg/kg dw. The EPA's evaluation of these data, based on the abnormality data alone, suggested effects to YCT were likely greater than 30 mg/kg dw. The EPA suggested conversion factor for YCT is 1.96 based on a median value of the paired maternal whole body and egg tissue Se data available. However, a reanalysis of these data presented in the paper indicates a ratio of 1.43 is more appropriate; therefore, the egg to whole-body conversion factor for YCT recommended is 1.43 which results in a whole-body tissue EC10 of is 24.55 mg/kg dw at an egg tissue EC10 of 35.1 mg/kg dw.

This study investigates the ecological risks posed by organic micropollutants (OMPs) in wastewater treatment plant (WWTP) effluents in Flanders, Belgium based on single-compound risk characterization. Utilizing a five-year monitoring dataset from the Flemish Environment Agency (VMM) and employing seven ecological threshold values (ETV) types, this research characterizes the risk of 207 OMPs, including pharmaceuticals, pesticides, industrial chemicals, and other pollutants. Several OMPs persist in effluents at concentrations that pose significant ecological risks after secondary and tertiary treatment processes in the region of Flanders (Belgium). This study identified 32 OMPs with regional risk quotients (RQregion) exceeding 1, with 24 of these showing RQregion values over 10, marking them as high-priority pollutants. Notable high-risk substances include chlorpyrifos, benzo(b)fluorene, and several herbicides. The findings highlight the necessity for investment in advanced treatment processes to enable compliance with the updated Urban Wastewater Treatment Directive (UWWTD), which mandates an 80% reduction in a fixed set of micropollutant indicators in relation to their load in WWTP influent by 2045. Based on our prioritization of high-risk OMPs, the fixed set of indicators mandated by the UWWTD does not fully represent the range of harmful contaminants in WWTP effluents, indicating a need for a broader monitoring framework and a more inclusive indicator set. These results underscore the necessity for an expanded approach to monitoring and regulating OMPs to ensure comprehensive protection of aquatic environments.

Estimating pesticide concentrations in paddy rice systems is challenging due to unique cultivation methods and water management practices. Various models, ranging from simple exposure calculators to complex scenario-dependent tools, have been developed globally to address this issue (PADDY, MED-Rice, RICEWQ, PFAM). In Brazil, pesticides are used in paddy rice production, and there is a potential risk of these compounds reaching waterbodies. Legislative changes in 2023 made environmental risk assessment mandatory for pesticide registration in Brazil. However, Brazil has not officially adopted a specific modelling tool for paddy rice systems. This critical review evaluates (i) the strengths and limitations of pesticide exposure models for paddy rice most commonly used in Europe, North America, Asia and Latin America; (ii) it reviews the tools used in a regulatory context outside Brazil; (iii) it discusses exposure tools used in lower tiers and then proceeds to a discussion of more sophisticated tools used in higher tiers; (iv) provides and overview of paddy rice production system in Brazil, (v) performs a comparative analysis of the features of each exposure tool against the characteristics of the Brazilian paddy rice production system, and finally, this review (vi) discusses which exposure tools may be most appropriate for integration into a prospective regulatory ERA framework in Brazil. The goal of this review is to contribute to the ongoing regulatory changes and discussions by identifying appropriate models that can effectively assess the environmental risks associated with pesticide use in Brazilian paddy rice cultivation.

Traditional ecological and human health risk assessment often relies on deterministic frameworks that preclude the presence of variability or uncertainty among input parameters characterizing exposure, effects, and risk. To promote increased realism and generate more robust risk management decisions, probabilistic risk assessment (PRA) has been introduced as a foundational grouping of techniques that seeks to broadly characterize variability among its components. While multiple methods exist (e.g., Monte Carlo simulations, Bayesian networks) along with some federal and state regulatory guidance, gaps remain in prescriptive regulatory recommendations for the implementation of PRA methods. This article describes specific probabilistic approaches for risk characterization and assessment, regulatory support of PRA, challenges that may limit more widespread use, and opportunities for its expanded use in regulatory areas where it is not currently applied. Taken together, we hope to advance the understanding of probabilistic methodologies and their versatility for robust, transparent, data-based environmental risk assessment and standards derivation across a range of media that align with regulatory objectives to protect aquatic and terrestrial biota, human health, and vulnerable populations.

Environmental Quality Standards (EQS) derived under the European Water Framework Directive are legally binding and enshrined in individual European Member State Country national legislation. These EQS are derived following well-established guidance documents. In 2013, EQS for nickel were derived for freshwaters to be protective against long and short-term exposures, at 4 and 34 µg L-1, respectively. The value for long-term exposures uses chronic ecotoxicity data and accounts for bioavailability, whereas the short-term value uses acute data and does not account for bioavailability. In 2022, the European Commission revised these values as part of the on-going legislative process. Despite an increase in available data for both chronic and acute ecotoxicity endpoints, the update and development of chronic and acute Biotic Ligand Models (BLMs) published in peer-reviewed literature, and the accessibility of vastly more monitoring data (used in the European EQS derivation), the values for the nickel EQS were reduced by increasing the assessment factors, to account for increases in apparent uncertainties. The Commission's 2022 derivation failed to consider additional chronic data for more than 20 species as well as the updated and new acute and chronic BLMs. As a result, the derived nickel EQS is limited in its applicability and relevance to European freshwater ecosystems, as illustrated in practice by the observation that monitoring sites can comply with the chronic EQS but fail the acute EQS. Here, we provide an explanation as to why this has occurred and detail what it means for the risk assessment of nickel in European Member State freshwaters. Finally, we outline a path forward, that should be relevant for any risk-based and evidence-driven regulatory framework and acknowledging that political decisions are part of the process, but that these should be separate and after scientific aspects are undertaken.

Microplastics (MPs) have become a notable concern and are released into the environment through the disposal or fragmentation of large plastics. Rivers have been the major pathways for MPs present in the oceans, which significantly affects the marine environment. In the current study, water samples were collected from the upper stream and downstream of Damanganga and Tapi rivers across different sites in the state of Gujarat, India for exploration of MPs contamination. Additionally, samples were also collected from Dumas Beach to detect the presence of MPs. MPs were extracted from the samples through sieving, density separation and wet peroxide oxidation (WPO) techniques which were subsequently analyzed using μ-FTIR, optical microscope, Pyrolysis GCMS (Py-GCMS) and SEM. The concentration of MPs was also quantified from each stretch of Damanganga, Tapi rivers as well as Dumas Beach. Findings revealed that Damanganga showed a higher concentration (3.53 particles/L) of MPs as compared to others. Further, optical microscope and μ-FTIR analysis confirm the presence of MPs like Polypropylene (PP), Polystyrene (PS), Polyethylene terephthalate (PET), Polyethylene (PE) and Polymethyl Methacrylate (PMMA). Pyrolysis products of PP, PS and Polyamide (PA) were detected from Py-GCMS studies. Additionally, SEM images revealed that MPs were subjected to weathering, oxidation and atmospheric deposition over the years. The study additionally confirmed the flux of MPs in both the rivers and beach due to anthropogenic and industrial effects. Risk assessment of MPs was performed using the Pollutant Loading Index (PLI), which indicated that the overall MPs pollution in the studied sites was marginal. Nevertheless, the PLI scores revealed that Damanganga was the most prone to MP pollution among the three study sites.

Environmental risk assessment of chemicals (ERA) relies on single-species laboratory testing to establish the toxic properties of a compound. However, ERA is not concerned with toxicity under laboratory conditions: it needs to assess the impacts of the compound in the real world. Data-driven statistical analyses (e.g., hypothesis testing and interpolation) are the common approaches for analysing toxicity data, but such approaches are the wrong tool for the job at hand. ERA does not need a statistical description of the effects in the toxicity test (at the end of the standardised test duration), it needs to extrapolate from the laboratory test to longer and time-varying exposure. Such extrapolation requires mechanistic process models, providing a simplified representation of the mechanisms underlying toxicity. Any useful model for the toxicity process should explicitly consider both dose (e.g., exposure concentration) and time. In the history of effects analysis for ERA, the factor of time does not get as much attention as the dose, hence common use of the term 'dose-response analysis'. However, this is a historical oversight: time is a crucial factor for understanding toxicity and thereby essential for meaningful extrapolation from laboratory to field. Mechanistic models for ecotoxicity, considering both dose and time, have been around for quite some time and are classified as toxicokinetic-toxicodynamic (TKTD) models. TKTD models are starting to find their way into pesticide ERA in Europe, next to the classical statistical approaches. In this opinion paper, I argue that it is about time to leave statistical analysis of toxicity data behind us. Statistics remains important for ERA's effects assessment, but its role lies in the definition of appropriate 'error models', explaining the deviations between model output and observations, which is essential for parameter estimation, uncertainty quantification, and error propagation. The 'process model', essential for extrapolation, firmly belongs to TKTD modelling.

Road activities are recognized sources of pollution that affect the hydrochemistry of nearby water bodies. This study evaluated the Water Quality Monitoring Program in the Soberbo and Iconha rivers in the Guapi-Macacu watershed, which is affected by the BR-116 highway. The Rio-Teresópolis Concessionaire from 2009 to 2016 carried out quarterly sampling. The parameters analyzed were: temperature, pH, turbidity, settleable solids, DO, BOD, NO3-, NO2-, NH4+, PO4-3, total and thermotolerant coliforms, Fe, Ni, Cr and Zn. PO4-3, pH, BOD and thermotolerant coliforms sometimes exceed the freshwater limits set by the National Environment Council (CONAMA 357/05, 2005). However, these values did not change the classification of "good" according to the water quality index used by the Brazilian environmental authorities for river waters. Precipitation was an important factor in understanding the hydrochemistry. Monthly precipitation ranged from 779.8 mm in January 2013 to 2.8 mm in July 2010. Temporal analysis using non-parametric tests showed significant differences (p < 0.05) in almost all parameters, indicating a strong influence of precipitation patterns on water quality. On a spatial scale, only coliform was found to differ between rivers (p < 0.01), suggesting an anthropogenic influence. Principal component analysis showed that chemical weathering and mechanical erosion processes predominated in both rivers (PC1: Soberbo River - 20.3%; Iconha River - 26.7%). Rainfall was identified as a secondary factor associated with coliforms and NH4+, especially in the Iconha River (PC2: Soberbo River-10.8%; Iconha River-11.9%), whose altitude indicated the atmospheric contribution of pollution from the metropolitan region of Rio de Janeiro. The reports of the Water Quality Monitoring Program were critically evaluated, resulting in recommendations aimed at optimizing their effectiveness and providing support for decision-making on the management of water resources in environmental protection areas.

The consideration of scarcity and overexploitation of freshwater at the organizational level increased interest in the water footprint. The water footprint measures freshwater use for activities, taking into account water consumption and pollution contamination by classifying consumed water into groundwater and surface water (blue water), rainwater (green water), and polluted water (grey water). This study aims to identify a comprehensive water footprint inventory analysis for a denim washing organization and assess the grey water footprint (GWF) based on the effluent concentration of pollution indicators (chemical oxygen demand (COD), suspended solids (SS), ammonium nitrogen (NH4-N), and phenol) measured monthly in 2021. The company used well water for its operations, which constituted 61.79% of the total water use of the facility, water used by the organization by reverse osmosis accounted for 37.60% of total water consumption, and rainwater made up 0.61% of the volume of water used overall. The grey water footprints of COD, SS, NH4-N, and phenol were calculated as 59981.53 m3, 31747.21 m3, 10514 m3, and 48190 m3, respectively. The results illustrated that the COD, which accounted for 40% of the pollutants, had the highest grey water footprint in the organization, corresponding to the amount of freshwater required to assimilate pollutants to meet water quality standards. In addition, the effect of the reverse osmosis system on the blue water footprint of this organization was analyzed by considering two different scenarios. Reverse osmosis considerably impacted the blue water footprint, accounting for over 37% of this organization's water use. It suggests that a wastewater treatment plant using reverse osmosis is an ideal option for recovering water. The main contributions of this study are comprehensively assessing the water footprint components of the denim washing company and understanding sector-specific water footprint at the organization level.

Coagulation process is a well-known process that has been used in water treatment for many years. Coagulation process shows the treatment efficiency in terms of turbidity and suspended solids removal. However, despite all these good results, coagulant selection is not an easy task because a coagulant can effectively remove suspended solids but at the same time increase conductivity or coagulants can significantly increase chemical sludge production. The final selection of coagulants depends on the importance attributed to the parameter desired to be removed. In this study, the use of multi-criteria decision making (MCDM) is proposed to help select organic coagulants and hybrid coagulants, which have emerged as an alternative to inorganic coagulants in recent years due to the disadvantages of chemical coagulants and whose use and variety are increasing. Therefore, starting from the parameters determined by the coagulation process results, these techniques will allow weighting these parameters according to the judgments of drinking water treatment plant professionals and determining priorities among coagulants. The agreement between the obtained results and the literature shows that the AHP method is a useful tool for selecting coagulants. According to the results of the AHP matrix created with 4 criteria and 9 alternatives, it has been observed that hybrid coagulants with similar performances to inorganic coagulants have not yet been adopted by drinking water treatment professionals. This may have been due to the higher price of hybrid coagulants and the fact that they are not yet widely used in the drinking water industry.