Integrated Environmental Assessment and Management最新文献

Microplastics (MPs) are prevalent in coastal environments of South Africa but there is a lack of knowledge about the prevalence and risks of MPs in coastal invertebrates. This study aimed to determine the prevalence, characteristics and ecological risks of MPs ingested by various echinoderm feeding groups. Sampling was conducted during low tide in the summer of 2020 at 14 rocky shores in the Western Cape of South Africa. By sampling various echinoderm feeding types, the abundance and characteristics of MPs (shape, colour, size by using microscopy and polymer type by using a Fourier-transform infrared spectroscopy (FTIR-ATR)) were measured. Potential ecological risks posed by MPs were assessed using hazards of respective polymer types. Mean abundance of MPs from all echinoderms was 9.32 (± 0.76 Standard Error of the Mean (SEM)) MPs/Individual, or based on weight, 1.11 (± 0.09 MPs/g soft tissue wet weight). The abundance of MPs was highest in echinoderms sampled from Kalk Bay (56.41 ± 4.37 MPs/I), with storm water outfall pipes and human activities identified as primary source of MP contamination. Filter-feeding sea cucumbers had the highest MP abundance (21.06 ± 3.03 MPs/I), suggesting that non-selective feeding echinoderms have higher MP uptake rates than other feeding strategy echinoderms. The MPs in echinoderms were mainly black/grey (45%) polyethylene terephthalate (PET) (50%) fibres (93%) that ranged from 1000 to 2000 μm (35%) in size. The potential ecological risk of MPs was highest at Kalk Bay (site 9) due to the prevalence low abundances of Polyvinyl chloride (PVC). This is the first study on MPs in coastal echinoderms of the Western Cape in South Africa and provides a baseline for MPs in echinoderms. The findings are significant because they offer the first indication that MP abundance may differ between echinoderm feeding groups.

The precautionary principle, a risk management tool used to justify deliberations and actions to prevent potential risks, has guided environmental policy development and implementation, both legally and culturally, and its application may play a pivotal role in the formal adoption of New Approach Methodologies (NAMs) in next generation environmental risk assessment. We consider the pace of NAM integration in environmental risk assessment and ask how, and why, a disconnect exists between policy development (where one finds precaution used as an argument for the adoption of NAMs) and policy implementation (where one finds precaution used as an argument against the adoption of NAMs). Reviewing how the precautionary principle is invoked in the Canadian context, we explore how competing interpretations of 'precaution' and 'risk' can be used to justify both regulatory action and inaction, hamstringing regulatory innovation related to the validation and acceptance of NAMs. Clarification among stakeholders of convergent and divergent interpretations and hence application of these concepts in practice is recommended to increase confidence in NAMs, providing a way forward for their incorporation in environmental risk assessment.

Soil mesofauna field studies conducted for ecological risk assessments of plant protection products (PPPs) require expertise for interpretation. The new statistical Closure Principle Computational Approach Test (CPCAT; introduced for Poisson-distributed count data) is proposed as alternative for established methods. However, the biological relevance of potential effects remains unclear. One aim was to investigate how to assess biological relevance. Biological Control Ranges (BCR) were calculated for each taxon and sampling time point within individual studies and it was compared whether the average abundance of a treatment group is in- or outside of the BCR. High control abundance variability of Collembola resulted in largely varying BCR values between studies. The second aim was to investigate performance of different statistical methods. Statistical analysis revealed that abundance data exhibited overdispersion in the majority of cases, instead of Poisson-distribution. Significant differences were observed in more than 50% of the comparisons using CPCAT, even before test item application happened in the field. Post-application, most statistical significances determined by CPCAT occurred despite the absence of a rate-response relationship and the arithmetic mean abundance values in the assigned treatment plots being within the BCR; thus, they should be considered as false positive results. In contrast, the Dunnett's test and Ranked Dunnett's test, either considering normally distributed data or being independent from the data distribution, barely detected a significant difference at pre-application when the abundance average values of assigned treatment plots were within the BCR pre- and post-application. In conclusion, pre-requisites for CPCAT (Poisson distribution, no over- or underdispersion of data) do not apply in the majority of the cases examined here. Holistic interpretation of field data needs to consider the ecological relevance of observations (via comparison with the BCR), presence of a rate-response-relationship, onset, scale, and pattern of the response, instead of solely focusing on statistics.

Developing countries are implementing strategies to mitigate the environmental impacts of municipal solid waste (MSW) in sustainable ways. Therefore, a holistic approach as municipal solid waste management (MSWM) has emerged to handle Sustainable Development Goals (SDG), in particular SDG 11 (Sustainable Cities and Communities) and SDG 12 (Responsible Production and Consumption). Increased MSW generation rates compel policymakers to develop feasible MSW management strategies to meet sustainable development goals. This study aims to assess the environmental and exergetic impacts of an integrated municipal solid waste management system by considering MSW collection and transportation, landfill site construction and operation, piping process, landfill gas (LFG) system, and electricity generation. Hotspots and major contributors within the system's sub-processes have been identified from the life cycle assessment (LCA) perspective. Results were normalized by one ton of disposed MSW and generated one kWh of electricity by LFG power plant. Global warming potential (GWP) and exergy consumption (CExD) for one ton of disposed MSW were calculated as 1.60E + 02 kg CO2-eq/ton and 2.45E + 3 MJ/ton, respectively. Furthermore, LFG power plant's impacts were calculated as 1.56E + 00 kg CO2-eq/kWh and 2.40E + 01 MJ/kWh, respectively. Results showed that hotspots of environmental and exergy impacts on overall system were accumulated in MSW collecting and transportation processes at 97.80% and 93.50%, respectively. This study highlighted that optimizing the waste truck routes, constructing transfer stations, and decreasing diesel use in waste trucks substantially influence the total life cycle performance of integrated MSWM systems.

The remediation of soils and aquifers contaminated by Light Non-Aqueous Phase Liquid (LNAPL) relies on a precise understanding of the LNAPL distribution above the water table. This study investigates the impact of groundwater table fluctuations and temperature change on LNAPL redistribution in a heterogeneous porous medium through laboratory-scale experiments. Experiments were conducted in a two-dimensional tank simulating aquifer condition, using diesel fuel as the LNAPL. The reservoir filled with coarse sand and fine sand low-permeability lenses, reproduced the subsurface heterogeneity. Following LNAPL infiltration from the top, controlled drainage and imbibition cycles simulated water table fluctuations. Experiments were conducted at 10 °C and 20 °C to characterize temperature effects. Fluid behavior was monitored using Time Domain Reflectometry (TDR) probes and high-resolution image analysis. TDR measurements provided quantitative dielectric permittivity data, which were converted to saturation profiles. Simultaneously, an image processing approach using the Biodock platform based on artificial intelligence and OpenCV was used to visualize the spatial distribution of LNAPL, water, and air. Applying the two methods allowed integrated methodology and a detailed understanding of the dynamics driving LNAPL migration. Results show that water table fluctuations significantly affect LNAPL redistribution, with each imbibition cycle leading to LNAPL entrapment in the capillary fringe due to wettability changes and capillary barriers. Higher temperature increased the mobility of LNAPL by reducing its viscosity, resulting in more efficient fluid displacement during drainage. This highlights the importance of studying the fate and transport of pollutants in the laboratory under temperature conditions relevant to the aquifers. Low-permeability lenses further modulated LNAPL migration, emphasizing subsurface heterogeneity critical role. Overall, the comprehensive experimental design combining TDR and advanced image analysis provides insight into the mechanisms of LNAPL behavior under dynamic environmental conditions and hints at further improvements for predictive models and remediation strategies in contaminated subsurface environments.

The intensive and repeated use of agrochemicals, including synthetic pesticides, herbicides, and fertilisers, has led to persistent contamination of agricultural soils, endangering soil health, ecosystem services, biodiversity, and sustainable food production. Soil microbiomes, with their remarkable metabolic versatility, represent a promising resource for in situ remediation of these pollutants. This review provides an integrated overview of the enzymatic and regulatory mechanisms underpinning microbial remediation, placing greater emphasis on enzymatic degradation as the central process driving pollutant breakdown. The biodegradation of soil pollutants is orchestrated by a network of microbial enzymes, including organophosphorus hydrolases, dehalogenases, oxidoreductases, dioxygenases, plastic-degrading and alkane-catabolising enzymes, that catalyse oxidation, hydrolysis, and dehalogenation reactions, transforming toxic compounds into less harmful intermediates that feed into metabolic pathways. Understanding the relationship between these enzymes, their encoding genes, and microbial hosts is crucial for designing robust bioremediation strategies. Complementing these biochemical processes, quorum sensing (QS) is discussed as a regulatory system that modulates microbial cooperation, biofilm formation, and catabolic gene expression during degradation. Emerging strategies, including microbial consortia design and synthetic biology-based engineering, are evaluated with a focus on the integration of QS-mediated interactions. Critical challenges, including soil heterogeneity, abiotic inhibition of QS signals, enzyme instability, biosafety concerns related to engineered strains, and horizontal gene transfer, are discussed. Future perspectives highlight enzyme engineering, QS-based biosensors, artificial intelligence-driven modelling, and synthetic QS circuits as tools to optimise bioremediation outcomes. Collectively, these insights outline pathways for advancing ecologically sound and sustainable approaches to the remediation of agrochemical-contaminated soils.

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 if the field is very vulnerable or not. This is a pragmatic approach that may lead to sufficient protection of most fields while at the same time other fields are accepted as being under protected. 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) or PERSAM (Vito NV, 2016)), are transferred to the specific fields resembling the closest similarities of the environmental conditions. In phase 2, field specific modelling 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 the farmers can fulfil by combining different mitigation options from a mitigation toolbox. The proposed scheme increases protection of biodiversity without compromising yield production.

Wastewater treatment plants (WWTPs) are recognized as major sources of organic micropollutants (OMPs) for aquatic environments. Yet, chemical monitoring alone may underestimate the ecological risks posed by complex OMP mixtures. Here, we combined an effect-based monitoring (EBM) approach with targeted chemical analysis to assess environmental risks of OMP mixtures in effluents from 16 WWTPs in Flanders, Belgium. Effluent sites were selected from a five-year regional monitoring dataset, prioritizing locations with high cumulative risk quotients. Bioassays using Microcystis aeruginosa (cyanobacteria growth inhibition) and Danio rerio (zebrafish larvae, light/dark locomotive assay) were conducted on effluent extracts. High-resolution mass spectrometry identified 130 compounds, with 26 OMPs quantified across classes, including pharmaceuticals, antibiotics, herbicides, and per- and polyfluoroalkyl substances. Median effective concentrations (EC50) and 10% effective concentrations (EC10) for cyanobacteria inhibition ranged between relative enrichment factors (REF) of 4.1-38 and 1.1-4.7, respectively. Iceberg modeling identified azithromycin and clarithromycin as the main drivers of cyanobacterial inhibition. Zebrafish behavioral responses were significantly affected in 8 of 16 samples (REF 1.25-20), but these differences could not be explained by the available chemical data. Only some suspect compounds were identified, including antidepressants and pesticides, and therefore this remains an interesting aspect for future investigations. Risk characterization for receiving surface waters using chemical-based risk quotients, margin of safety, and effect-based trigger values revealed ecological risk (RQ > 1) in 13 of 16 sites. This study highlights the added value of integrating EBM with chemical monitoring to explain mixture effects, identify key toxicants, and support improved regulatory frameworks for environmental management.

For several decades, the benchmark dose (BMD) methodology has been recommended for estimating safe exposure levels to toxic substances. When the response variable is continuous, the BMD and its lower confidence limit (BMDL) are often estimated using the hybrid method, which assumes a normal distribution to model the probability of an adverse response. Typically, this approach relies on a dose-response model with the assumption of constant standard deviation across all doses. However, when this assumption is violated, it can lead to biased estimates, and current implementations of the hybrid method do not account for this. In this paper, we introduce an extended class of dose-response models that allows for variation in the standard deviation across doses and adapt the hybrid method accordingly. We illustrate the proposed method using two data sets with two types of heteroscedasticity and show, through simulation, that addressing variance heterogeneity reduces bias and results in BMDL estimates with coverage closer to the nominal level.

Mesocosms can be used in higher tier aquatic risk assessments to assess the impact of Plant Protection Products (PPPs) on macrophytes. However, it is unclear whether these expensive and time consuming higher tier studies influence regulatory outcomes. This review highlights common shortcomings in the experimental design of mesocosm studies, with the aim of maximising the regulatory value of future mesocosm studies. Fourteen mesocosm studies, which have been submitted for the regulatory risk assessments for macrophytes in the EU or GB, were identified and reviewed. Results show that only five of the 14 mesocosm studies were deemed acceptable by the regulatory authorities, suggesting that mesocosm studies are not currently being used to their full potential. Issues with the submitted studies include not following a realistic PPP exposure profile (including incorrect dose timings and dilutions), only using one macrophyte morphology, not leaving enough time for the macrophytes to establish and a lack of replicates which increases variability within treatments. Glyceria maxima and Myriophyllum spicatum were frequently the most sensitive macrophyte species, whilst dry weight was often the most sensitive and least variable endpoint. Even though mesocosms provide the opportunity for recovery and community responses to be observed, such information has not been used by regulatory authorities. Future regulatory mesocosm studies can build upon the shortcomings highlighted here, providing a greater chance of regulatory impact.