Environmental Sciences Europe最新文献

Imidacloprid is an insecticide used in the UK for plant protection, biocides, and veterinary medicine. Concerns over its potential impact on non-target pollinators such as bees led to a ban in agricultural use in the EU in 2018 and earlier in the UK. It was added to the EU Water Framework Directive (WFD) watch list in 2015, with UK surface water monitoring starting in 2016. An assessment of monitoring data from 2016 to 2023 was conducted following WFD guidelines, using EU environmental quality standards (EQS) proposed for 2027, as no UK EQS has been established. The assessment checked site representativity and imputed missing data in England’s monitoring dataset to improve statistical analysis. Results showed a consistent decline in imidacloprid concentrations in surface water since 2016, aligning with the agricultural ban and tighter restrictions on other uses. Environmental imidacloprid sources include legacy residues in soils, sediments, groundwater, and wastewater treatment emissions. The role of veterinary products and biocides in imidacloprid detections was also explored, though biocide impact assessment was complicated by less stringent usage reporting. Current trends suggest further declines in surface water concentrations due to ongoing restrictions and responsible use programmes. Draft EU legislation aims for compliance with EQS by 2039, which seems achievable in the UK given current trends, though this timeline may not be adopted into UK law. The assessment of surface water monitoring data requires careful consideration and would benefit from more frequent, representative measurements.

Highlights.

• A systematic evaluation of imidacloprid in surface waters across the UK was conducted.

• Monitoring indicates a consistent decline of imidacloprid concentrations in surface water since 2016.

• Sources may include veterinary products, biocides, and legacy residues in soils.

• More extensive monitoring of imidacloprid would improve understanding of source contributions.

The implementation of sustainable ecological practices remains a substantial hurdle for emerging economies. While several studies have evaluated the environmental Kuznets curve, a holistic analysis of the load capacity curve (LCC) hypothesis in emerging seven economies is strikingly lacking. Hence, this study appraises the impact of fintech, structural change, total natural resource rents, and natural resource diversification on environmental quality within the LCC framework in emerging seven economies, comprising China, Russia, India, Mexico, Indonesia, Brazil, and Turkey. This research applied linear (bias-corrected method of moment estimators and panels corrected standard errors) and non-linear models (Method of Moments Quantile Regression) to analyze data from 1990 to 2022. The study validates the LCC hypothesis in these economies. Additionally, the study revealed that natural resource rent reduces environmental quality while natural resource diversification supports environmental stewardship. Fintech and structural change also play significant roles in enhancing ecological resilience in these economies. Finally, the study shows that growth, fintech, structural change, and resource dynamics exert mixed, country-specific impacts on ecological sustainability, highlighting the pivotal role of diversification and institutional quality. Therefore, policymakers should drive low-carbon structural changes, harness fintech for green finance, diversify resource use, and strengthen governance to align growth with ecological sustainability.

Persistent organic pollutants such as dioxins and furans (PCDD/F), and other contaminant classes are ubiquitously found in the environment. In this context, identifying potential sources of contamination when new hot spots appear presents a significant challenge. Assigning a hot spot to a specific source (e.g., a nearby small combustion plant) can be difficult, especially when multiple possible sources are involved and the pattern of pollutant load at the hot spot cannot be clearly linked to a single source. This may be due to similarities among the congener patterns of the potential sources or a lack of similarity to any of the known source patterns. Statistical methods such as Pearson correlation—although only indicating statistical associations and not causal relationships—between the congener pattern of a potential source and that of the hot spot can be helpful in this regard. We demonstrate through statistical simulations how the correlation-based quantification of statistical similarity can be improved by fundamentally changing the understanding of the data, thereby increasing the power of the correlation test. This methodology can support statistical similarity analysis by using unbiased statistical estimators—unlike traditional correlation analyses of congener profiles.

Background

With climate change the frequency and intensity of heavy rain events is expected to increase. These events can severely affect river pollution with organic micropollutants (OMPs)—implying adjustments in monitoring efforts. However, data on event-based pollution is still sparse for large rivers. This study aimed to provide an enhanced understanding of event-based emission and pollutant processes in a large river to support future monitoring. Here, daily water samples during rain events and monthly water and suspended particulate matter (SPM) samples were collected over several months in the Moselle River. Samples were analysed by target and non-target screening (NTS).

Results

During a heavy rain and flood event in July 2021, three main pollution patterns were identified in NTS data by cluster analysis reflecting (A) wastewater and immediate surface runoff emissions, (B) increasing groundwater emissions following peak discharge and (C) flood-related emissions. The identity and sources of flood-related features were largely unclear due to few annotations by our spectral library. Structure elucidation of unknown flood-related features let to unambiguous identification of three natural compounds—partially with potential environmental and (eco)toxicological relevance. The importance of the July event was further highlighted by high concentrations and loads of dissolved and particle-bound OMPs—above all pesticides and transformation products—compared to monthly averages. Two main pollution patterns, i.e., wastewater (A) and groundwater (B), were transferable to smaller rain events. While the two pollutant patterns were not directly relatable to precipitation and discharge, pattern-representative OMPs (e.g., benzotriazole and metolachlor ESA) indicated changes in predominant emissions pathways clearly.

Conclusions

Based on NTS and cluster analysis, the study provided comprehensive pollution data and revealed event-based emission processes in a large, regulated river. It was demonstrated that chemical water quality of large rivers can be considerably impaired by heavy rain events—with effects lasting for several weeks. The study highlights the importance to amend future (routine) monitoring by (i) flow-proportional water sampling and higher temporal resolution in SPM sampling to account for effects of high discharge and SPM events, (ii) incorporating structure elucidation efforts of natural compounds and (iii) using pattern-representative OMPs as indicators for pathway contributions.

Background

As the EU Green Deal accelerates the transition to a sustainable economy, access to reliable sustainability data from small and medium-sized enterprises (SMEs) becomes increasingly crucial for meeting regulatory and market demands. However, SMEs face significant challenges in complying with EU Taxonomy reporting due to complex criteria, high costs, and limited resources. The EU LIFE-CET-21 funded CONFESS project aims to bridge this gap by developing the Clean Leap Tool - a practical and accessible solution tailored to SME’s unique needs. This paper presents the methodology and framework behind the tool, with a particular focus on adapting EU Taxonomy criteria to reduce reporting complexity for clean energy SMEs.

Methods and results

The Design Science Research Methodology (DSRM) as proposed by Peffers et al. (2007) was used to systematically develop and evaluate an innovative tool addressing the identified problem of EU Taxonomy reporting complexity for SMEs. This study rigorously follows all six DSRM activities to develop and validate a comprehensive solution for voluntary and simplified EU Taxonomy reporting, ensuring both methodological consistency and practical applicability of the resulting Clean Leap Tool. The methods for criteria simplification follow a structured, four-step process ((1) improving user-friendliness by eliminating ambiguities and enhancing data accessibility, (2) strengthening SME capacities through guidelines and tools, (3) modifying assessment criteria to improve proportionality, and (4) substituting or exempting criteria where simplification is not feasible), suggested by (Giannotti et al. 2024), where the steps are used in combination to enhance accessibility and reduce reporting burdens. The resulting Clean Leap Tool ensures a more manageable compliance process while maintaining alignment with EU regulations.

Conclusions

By providing a user-friendly web application that simplifies criteria and streamlines the reporting process, it significantly lowers the barriers SMEs encounter in complying with EU Taxonomy requirements. The tool’s modular structure enables corporates to familiarize themselves with necessary standards without incurring substantial upfront costs. Beyond SMEs, its applicability could be extended to larger companies, particularly as voluntary sustainability reporting gains prominence due to regulatory developments such as the Omnibus Directive.

Rapid population growth in North-East India has led to urban sprawl, agricultural expansion, and industrialization, resulting in significant deforestation. Numerous studies have utilized Forest Canopy Density (FCD) coupled with remote sensing and GIS to assess forest cover changes. This study evaluates how FCD changed from 2000 to 2020, highlighting deforestation patterns in North-East India. Machine learning models, including Binary Logistic Regression (BLR), Random Forest (RF), REP-Tree, and XGBoost Regression (XGBR), were used to identify areas at risk of deforestation. Influencing factors considered were forest density, barren land, agricultural land, urban areas, distance to roads, and topographical characteristics. Results indicated that proximity to roads notably increases deforestation risk. Higher densities of agricultural and urban land also contribute to greater deforestation rates, whereas increased forest and barren land densities reduce this risk. Among the tested models, Random Forest showed superior performance with a high True Positive Rate (TPR) and low False Positive Rate (FPR), effectively identifying high-risk deforestation zones. Analysis also revealed a concerning shift from high-density to low-density forests, signifying substantial forest cover loss and potential threats to biodiversity and ecosystem services. The findings emphasize the need for integrated land-use planning and targeted conservation, specifically addressing road proximity, to effectively combat deforestation in North-East India and similar regions.

Pyrethroids represent a class of highly potent insecticides characterised by their widespread use, extreme toxicity to non-target aquatic organisms, complex regulatory status, and the unique challenges they pose for environmental monitoring and risk assessment. With cypermethrin already listed as a priority substance under the Water Framework Directive (WFD), and four additional pyrethroids now designated as such, this review aims to raise awareness of key issues related to the regulation, use, and monitoring of pyrethroids in order to reduce the contamination of surface waters. For this purpose, we evaluated measured pyrethroid concentrations in surface waters from different selected monitoring programs in Europe, and derived suggestions for environmental quality standards (EQS) where these were unavailable. Our analysis shows that the current analytical methods are still largely inadequate, as in most European countries the limits of quantification (LOQ) are too high to reliably assess compliance with EQS for pyrethroids. Where concentrations could be quantified with a sufficiently low LOQ, exceedances of the respective EQS were frequently observed, thus supporting the proposed inclusion of bifenthrin, deltamethrin, esfenvalerate, and permethrin on the list of priority substances under the WFD. Moreover, our analysis reveals that monitoring limitations prevent evaluations whether other pyrethroids, such as cyfluthrin, λ-cyhalothrin, etofenprox, tefluthrin, and transfluthrin, pose similar threats to surface water quality. In order to meet WFD surface water quality goals while maintaining the availability of pyrethroid insecticides, urgent and coordinated action is needed by all stakeholders involved in their regulation, use and monitoring. We recommend the following key measures: (i) reducing the use of pyrethroids and emissions to surface waters, (ii) investing in improved routine analytical capability, and (iii) harmonising pyrethroid regulations as well as promptly integration of new knowledge.

Graphical Abstract

Background

The eco-corona, consisting of environmental biomolecules formed around engineered nanomaterials (ENMs) when released to the environment, has gained increasing focus in the scientific literature and its role for ENM fate and toxicity is now widely acknowledged. The European chemicals legislation, REACH, entails reporting requirements when it comes to the transformation of nanoforms. Guidance provided by the European Chemicals Agency (ECHA) highlights eco-corona and biotransformation as relevant transformation processes. Still, no specific advice is given on how to test these processes. Based on the findings from the MISTRA Environmental Nanosafety project, we here map out methods to characterise ENM eco-corona and biotransformation and assess their effects. Furthermore, the regulatory relevance of the methods is evaluated.

Results

We identified methods to assess both eco-coronas formed ex vivo (by interaction with natural organic matter-based solutions or solutions with animal secretes) and bio-coronas formed in vivo (via biotransformation, i.e., filtration of ENMs through living organisms). We recommend implementing these methods and methodological considerations in a future update of ECHA’s guidance on ENM ecotoxicity and fate testing, both in the sections on transformation and aquatic pelagic toxicity. When exploring the characteristics and kinetics of eco-corona formation, various data are needed, including data on time-dependent interaction/adsorption/desorption between ENM and constituents in the medium (both with and without the addition of natural organic matter/biomolecules). It is, furthermore, proposed that environmental relevance is enhanced for hazard assessment of nanoforms in REACH. This can be done by incorporating eco-corona considerations in the persistency, bioaccumulative, and toxicity (PBT) assessment.

Conclusions

We here propose to update ECHA 's guidance on ENM ecotoxicity testing and the PBT assessment required under REACH to include eco-corona considerations. If updated, this will aid in implementing information requirements on ENM transformation, increase the environmental relevance of ENM ecotoxicity tests, and reduce uncertainties in the extrapolation of ENM ecotoxicity data.

The European Commission’s Safe and Sustainable by Design (EC SSbD) Framework aims to put together safety and sustainability considerations throughout the entire chemical and material innovation processes. Being a voluntary (pre-market) approach, the framework fosters the development of safe and sustainable chemicals, materials, processes, and products while drawing on existing legal frameworks. We explore the relationship between the EC SSbD Framework and current European legislation regarding safety and sustainability. We highlight commonalities and differences to deduce synergies, and identify opportunities for mutual support and benefit. By systematically evaluating each step of assessing safety and sustainability criteria, indicators, and elements in the EC SSbD Framework, we demonstrate how information generated during the innovation process can also support legal compliance while driving pro-active design improvements. Vice versa, we investigate how regulatory data and methodologies can inform SSbD assessment steps, ensuring a reciprocal flow of information between innovation and compliance efforts. Despite notable differences identified, our findings demonstrate that the voluntary EC SSbD Framework has an added value, and it fosters synergies between innovation of chemicals and materials and safety and sustainability provisions of relevant legislation.

Accumulation of xenobiotic chlorinated ethenes (CEs) at legacy industrial soil and groundwater sites around the world is a pressing environmental and public health issue. Understanding the biochemical pathways through which microorganisms degrade cDCE is key to developing cost-effective, sustainable bioremediation strategies for CE contamination. Two strains, Acinetobacter pittii CEP14 and Ectopseudomonas alcaliphila JAB1, isolated from contaminated industrial sites, have demonstrated the ability to cometabolically degrade cDCE in the presence of phenol. In this study, we integrate transcriptomics, using differential gene expression analysis to pinpoint genes induced during cDCE co‐metabolism, with proteomics to confirm protein‐level expression. We use heterologous expression experiments to demonstrate that phenol monooxygenase is responsible for oxidising cDCE in both strains. Furthermore, we show that CEP14 and JAB1 α-subunits share 71.4% identity with each other but only 14.6–26.5% identity with established monooxygenases with known cDCE-oxidising activity, highlighting the diversity of enzymes that may be capable of cometabolic cDCE degradation. Finally, we hypothesise on a two-branch phenol monooxygenase-mediated cDCE degradation pathway in which the chemical degradative intermediates 2,2-dichloroacetaldehyde and cDCE epoxides are formed. This study sheds light on the biochemical mechanisms by which monoaromatic compounds can enhance the biodegradation of cDCE and demonstrates the potential utilisation of strains CEP14 and JAB1 for the biodegradation of cDCE.