Integrated Environmental Assessment and Management最新文献

The consideration of alternatives is central to environmental impact assessment (EIA), as decisions cannot be made without options to choose from. Despite its significance, the treatment of alternatives in EIA practice has inadequacies, driven by factors such as a lack of interest, predefined options, and a limited understanding of the possibilities. An essential requirement for alternatives is that they must be reasonable. We identify three types of unreasonable alternatives-false, contrived, and subtle-which may distort the EIA process. To address ambiguities in existing literature, we propose a taxonomy classifying alternatives into seven groups: implementation, spatial, timing, functional, design, constructive, and operational, answering the questions why, where, when, what, and how. The aim of this taxonomy is to enhance the consideration of alternatives in EIA practice by improving knowledge of the existing possibilities. Early integration of alternatives, particularly during the scoping phase, and a proactive approach are essential to strengthening EIA; otherwise, the process risks becoming a mere environmental authorization rather than a robust decision-making tool.

Digitalization in agriculture is rapidly progressing. Smart farming technology and usage of farm management information systems implementing detailed geospatial data are used more frequently. The authorization approach of plant protection products in Europe does not currently make use of these advances. A 90th percentile protection goal is currently often established based on a few scenarios representing a realistic worst case of agri-environmental conditions. Within this process, the products receive authorization and mitigation requirements on the product label, which usually cover all fields, no matter whether the field is very vulnerable or not. This is a pragmatic approach that may lead to sufficient protection of most fields while other fields are accepted as being underprotected. To overcome the limitations of the current assessment based on a few worst-case scenarios, a transformation of the current risk assessment scheme towards a digital-driven field-specific risk management is proposed in three phases. The risk assessment procedure on European Union and Member State level would remain in large parts as it is. All three phases make use of the availability of farm management information systems to distribute field-specific restrictions and mitigation requirements. In phase 1, the mitigation requirements, based on standard regulatory scenarios (e.g., FOCUS [Forum for Co-ordination of Pesticide Fate Models and Their Use]), are transferred to the specific fields showing the closest similarities of environmental conditions. In phase 2, field-specific modeling is performed where the standard parameterization can be adapted for local conditions. In phase 3, geospatial data are used to derive field-specific parameterizations for the exposure and effect models. In all phases, each field receives application restrictions and mitigation requirements depending on the local situation, which farmers can provide by combining different mitigation options from a mitigation toolbox. The proposed scheme increases protection of biodiversity without compromising yield production.

In terrestrial ecosystems, water and carbon cycles are closely coupled through processes such as photosynthesis, transpiration, and carbon allocation. Although advancements have been made in water-carbon coupling, existing studies predominantly focus on measurement methods and ecosystem model analysis, with insufficient attention paid to the linkages between hydrological processes and vegetation dynamics. This study employed the Yiluo River Basin as a case study, utilizing the Soil and Water Analysis Tool (SWAT) model to simulate the basin's hydrological cycle. By deconstructing and reconstructing the original Hydrological Response Unit (HRU) structure, this modified model was used to simulate actual evapotranspiration (E) and potential evapotranspiration (E0) for each HRU. By applying the light use efficiency (LUE) model and integrating E and E0 data, researchers determined the spatiotemporal distribution characteristics of carbon sequestration (gross primary productivity (GPP) and net primary productivity (NPP)), thereby enriching research on water-carbon linkages. Key findings include: (1) Both annual average GPP and NPP showed a significant upward trend, with NPP values slightly lower than GPP. (2) The annual average values in the upstream areas were notably higher than those in the downstream areas, closely related to vegetation types and evapotranspiration distribution. (3) Summer acted as the primary season for GPP and NPP accumulation, typically exhibiting high evapotranspiration rates and strong carbon sequestration. Over time, driven by climate change and vegetation restoration, spring cumulative contributions of GPP and NPP have gradually increased, thus narrowing the seasonal gap relative to summer.

An accurate evaluation of human health risks from exposure to contaminated soils depends on several factors, including an accurate estimation of the site-specific bioavailability of metals. This study aimed to evaluate the risks associated with exposure to arsenic (As) contaminated soils through ingestion, inhalation, and dermal contact pathways in children under six years old. Additionally, relative bioavailability (RBA) and in vitro bioaccessibility (IVBA) were considered in the ingestion risk calculation, while local inhalation rates (IR) were used for estimating inhalation risk. Forty-one soil samples were collected in this study. Arsenic RBA was determined using a mouse urinary excretion bioassay. Two IVBA methods-EPA Method 1340 and the physiologically based extraction test (PBET)-were evaluated against the RBA values. The RBA of As ranged from 15.4% to 21.8% at Guandu (GD) sites. IVBA values using EPA Method 1340 ranged from 12.0% to 33.1%, while PBET values ranged from 4.3% to 13.0% for the gastric phase (GP) and 5.2% to 12.0% for the intestinal phase (IP). The hazard quotients (HQs) for the soil ingestion pathway in children aged 0-3 and 3-6 years old were below 1 when incorporating RBA and IVBA values. This study demonstrates that site-specific bioavailability assessments provide more accurate risk estimates than total metal concentrations, and that implementing simple hygiene interventions such as frequent handwashing can effectively reduce cumulative health risks from multiple exposure pathways in contaminated soil environments.

Nitrification and urease inhibitors (NUIs) are chemical compounds that can reduce nitrogen (N) loss and potentially enhance fertiliser nitrogen use efficiency (NUE) when combined appropriately with N fertilisers. Many studies have highlighted their agricultural and environmental benefits, including improving crop yields, reducing nitrate leaching, and lowering nitrous oxide emissions. However, their unintended presence in the environment (e.g.,, surface water) and the food chain has raised concerns. Individual inhibitors exhibit different levels of risks and benefits that need to be evaluated separately. In this study, a risk-benefit ranking was conducted to prioritise 10 NUIs based on environmental exposure, toxicity, and benefit through the preference ranking organization method for enrichment evaluation (PROMETHEE). In general, the urease inhibitor N-(n-butyl) thiophosphoric triamide (NBPT) was identified as the most preferred with a net flow value (φ) of 0.11 in the risk-benefit ranking of all NUIs due to its significant agricultural and environmental benefits with low risk from its short half-life. This assessment was supported by the fact that sometimes NIs can increase ammonia emissions, reducing their overall effectiveness in improving NUE compared to UIs. Our results also illustrated that the nitrification inhibitor dicyandiamide (DCD) was a recommended alternative (φ: 0.08) among evaluated NIs. This study assists stakeholders to balance the benefits and potential risks regarding the environment and human health issues associated with the application of NUIs in agriculture.

Statistical methods and computational tools applicable to ecotoxicology have developed and improved over recent decades, but regulatory risk assessments haven't kept pace, instead relying on outdated statistical methods and tools. Sessions in recent SETAC meetings dedicated to the development of statistical methods and tools for ecotoxicology have generated a high level of interest and discussion. Ecotoxicologists have expressed interest in the revision of the 2006 OECD document No. 54, "Current approaches in the statistical analysis of ecotoxicity data: a guidance to application" because they believe that the guidance is no longer reflective of contemporary statistical methods and tools; its revision is ongoing. Against this background, a call for papers for Special Series in IEAM was launched in autumn 2024 with manuscript submissions accepted until summer 2025. The purpose of this Special Series was to survey the statistical ecotoxicology landscape and reflect on recent developments, processes, and opinions. The editors of the Special Series welcomed and encouraged contributions and viewpoints from all employment sectors. The resulting series comprises eleven papers (seven original articles, three brief communications, and a workshop synthesis), with authors from academia, industry, government, and other research organizations. The series covers topics such as: recent progress in concentration-response modelling and hypothesis testing, including use of generalized linear models; strengths and weaknesses of established toxicity metrics (ECX, NOEC, BMD); application of toxicity metrics for species sensitivity distribution (SSD) modelling; added values of mechanistic effect modelling; and case studies highlighting opportunities and challenges related to the various statistical methods. This introductory paper aims to give an overview of the papers in the Special Series, summarizes their main topics and methods, and addresses further challenges to progress statistical analysis for regulatory ecotoxicology.

A unified biotic ligand model (BLM) was developed to predict acute Zn toxicity to four invertebrates and two fish, and chronic toxicity to three invertebrates and a fish. Developed using a comprehensive ecotoxicity database, this unified BLM represents the first update to the unified Zn BLM in nearly 14 years. For comparative purposes, a unified Zn multiple linear regression (MLR) model was also developed. Both models are unified because they each use a single set of parameters to characterize the effects of toxicity modifying factors (e.g., pH, dissolved organic carbon [DOC], and major ions) on acute and chronic Zn toxicity. While both models were capable of accurately predicting Zn toxicity, the unified BLM performed marginally better based on quantitative model performance scores (MPS) and qualitative single-variable pH and DOC evaluations. The unified Zn BLM, which also performed better than the U.S. Environmental Protection Agency's hardness equation, was then used to normalize separate acute and chronic species sensitivity distributions (SSDs) to develop acute and chronic 5th percentile hazardous concentrations (HC5s) analogous to USEPA's aquatic life ambient water quality criteria (WQC). The unified Zn BLM-based WQC were shown to be protective of threatened and endangered species in California and appear to be protective of chemosensory endpoints for salmonids. Using monitoring data for California as a test case, chronic unified BLM-based WQC were lower than hardness-based WQC in 77% of samples, yet fewer WQC exceedances were observed. Implementation of the Zn BLM for site-specific water quality objectives (SSWQOs) using the fixed monitoring benchmark (FMB) approach indicates that for the California dataset, dry weather and wet weather samples should be considered separately to develop SSWQOs for each condition.

Concerns regarding the environmental risks of UV-filters used in suncare products have grown in recent years. Much of this concern has been driven by their use in products by consumers engaged in outdoor recreational activities, such as swimming, which can facilitate their direct emissions into aquatic systems. Uncertainties in estimating the amount of a UV-filter that might be directly emitted to water, however, represent a continuing challenge, and include the need to quantify the number of users of suncare products, the skin area covered, the concentration of the UV-filter in the product and the extent to which the UV-filter is 'washed-off'. This study aims to address this gap, which includes the development and application of screening-level exposure Models to Evaluate the direct Release of Cosmetic Ingredients (MERCI). The tier 1 and 2 MERCI models-SUNscreen and multi-SUNscreen-are described, with application to octocrylene, a well-studied UV-filter used in suncare products. Model results suggest that both tools provide reasonable estimates of environmental exposure. Specifically, the tier 1 SUNscreen model, estimates an environmental concentration of 422 ng·L-1 in freshwater and range from 191-428 ng·L-1 in marine water capturing differences between low-moderate tidal dilution rates, whereas sediment concentrations are estimated to be 206 ng·g-1 dw (freshwater) and 94-210 ng·g-1 dw (marine). The tier 2 multi-SUNscreen model, on the other hand, estimates freshwater concentrations of 81 ng·L-1 in water and 0.5 ng·g-1 dw in sediment, results that are observed to be within an order of magnitude of monitoring data. Overall, both models support a conservative, screening-level approach for estimating environmental exposure to UV-filters, and thus represent tools that can be readily utilized to support both risk assessment and research prioritization.

The majority of research on microplastic (MP) characterization and removal has focused on municipal wastewater treatment plants (WWTPs). Hence, this study was performed at an industrial zone WWTP with sectors of textile, plastic recycling, furniture, etc. Three monthly sampling campaigns were conducted to analyze the MPs (abundance, shape, color, size, polymer type), and to investigate their fate and removal rate in the WWTP. Furthermore, the environmental risk assessment using EPI Suite™ modeling was conducted for common MP polymer types. The results indicated that the highest MP concentration was detected in the sludge sample (3,734 MP/L), while the lowest one was observed in the effluent sample (52 MP/L). While large MPs (5 mm - 425 µm) were removed by primary treatment processes, smaller MPs (250-125 µm) showed a tendency for accumulation in the sludge. The most dominant MP shapes were fiber and fragment in both wastewater and sludge samples, while the most dominant polymer types were polypropylene (38%), polyethylene (24%), and polyethylene terephthalate (11%). The environmental risk assessment reveals that polyvinyl chloride, polyethylene terephthalate, and polystyrene, present in minimal quantities in this study, are more likely to impact the growth of living organisms significantly compared to more common polymer types like polypropylene and polyethylene. Although the overall MP removal efficiency of the industrial zone WWTP was 88%, a significant quantity of MPs (1.5x109 MP/day) was still discharged into the Kızılırmak river that is mostly used for irrigation. Effective control/reduction of MP discharge necessitates the implementation of tertiary treatment processes in industrial zone WWTPs to prevent soil pollution.

Remediation of contaminated sediment sites is complex and expensive, critical to the restoration of damaged ecosystems, and essential to the reduction of threats to human health. Along with the challenges of remediating a contaminated site is determining if the remediation has been effective. In this investigation, the use of bioavailability-based metrics was evaluated as a tool for assessing remedial effectiveness. Metrics included surface water concentrations and bioaccumulation in proxy species. Following the identification, collection, and curation of relevant retrospective bioavailability metric datasets, statistical analyses were performed comparing pre-remediation and post-remediation time periods. Statistical analyses used (i) hypothesis testing to identify significant reductions in bioavailability and (ii) regression to assess significant negative slopes. Datasets from three Superfund sites were evaluated in this investigation: Lower Grasse River, New Bedford Harbor, and Stauffer Chemical Company. Both the Lower Grasse River and New Bedford Harbor demonstrated decreases in the bioavailability of total PCBs as the remediations proceeded. Remedial effectiveness was more apparent for the Lower Grasse River compared to New Bedford Harbor most likely because remediation at the former had been completed for several years while it was still on-going at the latter. In contrast, effectiveness of remediation at Stauffer Chemical Company was less obvious based on statistical analyses of the bioavailability metrics. We speculate this reflects the more complicated environmental behavior of mercury compared to PCBs. This preliminary use of retrospective datasets of bioavailability metrics from Superfund sites to assess remediation effectiveness has shown promising results and merits further evaluation at other sites. In addition, contaminants like PCBs appear to be good candidates with this approach while mercury may not be. Also, datasets with good temporal separation of the pre-remediation and the post-remediation time periods are better candidates for this approach.