Environmental Sciences Europe最新文献

Background

Heavy rainfall causes not only high water levels and discharge but can also lead to the mobilization of sediments and pollutants to rivers. In contrast, droughts with low discharge can impair water quality due to minimized dilution. Both extremes—heavy rainfall as well as droughts—are aggravating under climate change; thus, it is important to understand the processes as well as the meteorological and hydrological preconditions that lead to elevated concentrations of sediments and pollutants. This study aimed at identifying event types that cause high discharges, and increased concentrations in suspended sediment and changing pollutant concentrations in a large river. We use a long-term (2010–2022) data set of high-resolution precipitation, discharge, suspended sediment concentrations as well as 14-day composite sample concentrations of six organic micropollutants (OMPs) in the central European Moselle River.

Results

By means of principal component analysis and cluster analysis, we identified typical as well as atypical events with high suspended sediment concentrations. The cluster analysis clearly identified a cluster of high-magnitude events with high discharge, precipitation amounts and high suspended sediment concentrations, which mainly occurred in winter. However, single atypical high-magnitude events such as the one associated with the July 2021 floodings in Western Europe also occurred in summer. For OMPs, the cluster analysis showed less clear results. Yet, general differences in concentrations dynamics related to high discharge regimes were identified for the herbicide metabolite metazachlor ESA and the pharmaceutical carbamazepine.

Conclusions

Our results show that the methodology is a powerful tool for the identification and characterization of high-magnitude suspended sediment transport and discharge events. However, it is limited by data availability for most OMPs. Nonetheless, the data set helped us to identify relevant time periods of high OMP concentrations in line with observations made in smaller catchments or for shorter observation periods.

This paper discusses the need for regulatory measures to include persistence and mobility of chemicals as hazard criteria to better protect freshwater, groundwater and drinking water. In the EU, the hazard criteria persistence and mobility are, regulatorily speaking, still new. These criteria have been included in environmental hazard classes in Regulation 1272/2008 on classification, labelling and packaging of substances and mixtures in 2023 (Commission Delegated Regulation 2023/707). Even though these substances may not be classified as toxic under existing criteria, their persistence and mobility pose potential hazards to the environment and human health. We show the perspective of the German stakeholder dialogue on trace substances and how chemicals are assessed in this national framework. Persistence and mobility criteria should also be integrated into regulatory approaches, namely the derivation of environmental quality standards for surface water and in the hazardousness definition of the Urban Wastewater Treatment Directive 2024/3019. To ensure regulatory consistency, we support harmonized criteria as laid down in Regulation 2023/707 for persistent and mobile substances across different legislative frameworks.

Background

Increasing numbers of chemicals with little-known adverse effects are released into the marine environment. The present study addresses the lack of marine-specific prioritisation schemes by developing a prioritisation tool for organic contaminants. This tool supports decision-making processes regarding which chemicals to study further in terms of their occurrences and biological effects in the marine environment. It was supported by a database containing approximately 1.13 million chemicals, developed within the PikMe project. Criteria for chemical prioritisation were identified by a comprehensive literature review, then selected using the outcomes of a survey among experts. The prioritisation tool consists of filtering chemicals in the PikMe database using three parallel schemes—persistence and bioaccumulation, toxicity, and persistence and mobility characteristics (step 1)—followed by scoring based on modes of action, occurrence, and emission (step 2) and ranking by the final score (step 3).

Results

Around 8000 chemicals were selected by filtering (step 1). The top 100 resulted from step 3 comprises 6PPD as the highest-ranked compound and other chemicals with high diversity of uses, e.g. pharmaceuticals as the predominant category of use, industrial chemicals, personal care products, flame retardants, and plastic additives. These chemicals were ranked in the top 100 due to dominant influence of diverse prioritisation criteria.

Conclusions

Using the hazard-based approach that encompasses different adverse effects that contaminants of emerging concern can exert, the marine-specific prioritisation tool can guide decision-making in monitoring, ecotoxicological studies, and regulations regarding contaminants of emerging concern in the marine environment.

The increasing prevalence of anthropogenic trace substances and organic micropollutants in wastewater necessitates advanced treatment stages in wastewater treatment plants (WWTP) to effectively remove these pollutants. Ozonation has proven to be an effective method for this purpose but poses the risk of generating toxic by-products like bromate, especially when treating bromide-containing wastewater at high ozone dosages. Bromate is classified as a possible human carcinogen (IARC Group 2B) and presents both acute and chronic health risks, along with various ecotoxic effects. With the new European Union Urban Wastewater Directive (2024/3019) mandating advanced treatment for micropollutant removal, the occurrence and monitoring of bromate will gain increasing relevance. Although no threshold value for bromate in wastewater has yet been established, the proposed environmental quality standard indicates ongoing regulatory efforts, resulting in the need to monitor bromate concentrations in WWTPs effluents to safeguard public health and the environment. This review systematically examines the toxicological and ecological relevance of bromate and evaluates existing analytical approaches for its detection in wastewater. Methods developed for drinking and surface waters, such as ion chromatography (IC) with conductivity (CD) or post-column reaction and ultraviolet detection (PCR-UV), as well as mass spectrometry (MS)-based techniques, have been applied to wastewater matrices with varying levels of success. Reported quantification limits range from 70 µg/L using IC-CD to as low as 0.1 µg/L using IC-MS/MS. Wastewater presents a significantly more complex matrix than drinking water, introducing interferences from dissolved organic matter, anions, and fluctuating compositions. These challenges reduce accuracy, reliability, and reproducibility of results. However, none of these methods have been standardized by ISO, ASTM, or CEN or validated through interlaboratory trials for wastewater analysis. Among the evaluated methods, IC-PCR-UV as well as IC-MS-based approaches appear most suitable to provide the required sensitivity and robustness. Developing a harmonized methodology tailored to wastewater matrices is essential for regulatory compliance, environmental protection, and safeguarding public health.

The contamination of groundwater systems by industrial activities represents a pervasive global issue threatening water quality and safety. This study investigated the hydrogeological characteristics of the chemical park along the Yangtze River, by employing MODFLOW and MT3DMS to construct numerical models for groundwater flow and solute transport; the migration path and spatial extents of representative contaminants [ammonia nitrogen (NH₃–N), manganese (Mn), 1,2-dichloroethane, and volatile phenols] were analyzed. The multi-year results indicated that after 20 years, the contaminant extent in the study area was further expanded. Under natural rainfall scenarios, the area of the contaminant plume increased by 88.55–249.38% compared to the initial state, while under heavy rainfall scenarios, the increase ranged from 72.03 to 222.62%. Contaminants migrated with groundwater flow to the Yangtze River coast and Huangmaotan River, with a faster migration rate observed during heavy rainfall scenarios. It is necessary to implement source treatment and pollution control at surface water boundaries to ensure the safety of the Yangtze River water quality. This method can also be used to assess the potential pollution of similar projects along the Yangtze River and aid decision makers and managers.

Greenhouse gas (GHG) emissions have a major impact on the environment, human health, and climate change. In addition, methane (CH₄) is the second most prevalent greenhouse gas in the world, after carbon dioxide (CO₂).This study investigates how methane emissions vary and are distributed throughout Sub-Saharan Africa, with a particular emphasis on how agricultural methods, animal production, waste management, and energy generation interact. The objective is to determine the main causes of methane emissions so that environmental management strategies can be informed. Using data from 85 observations, we evaluated the associations between methane emissions, animal production, fertilizer use, and agricultural land use using pooled OLS, random effects, and fixed effects models. The average methane emissions were 201.8 Mt CO₂e, according to the results, with agriculture and livestock production accounting for the largest shares (80.3 Mt CO₂e and 246 Mt CO₂e, respectively). With 243.7 Mt CO₂e, Nigeria was the largest emitter, primarily due to agriculture (50.33%) and substantial animal rearing (index: 106.1). Ethiopia came next with a livestock production index of 106.0 and 101.9 Mt CO₂e. Tanzania and Uganda, on the other hand, showed more sustainable practices with lower emissions (38.56 Mt CO₂e and 53.27 Mt CO₂e, respectively) and livestock indices of 98.8 and 99.8. Furthermore, according to International Energy Agency (IEA) data on worldwide methane emissions, the energy sector which includes bioenergy and abandoned facilities contributes significantly to total emissions, whereas agriculture is responsible for about 137,270.61 kt of emissions. Notably, fugitive emissions from oil and natural gas infrastructure are substantial; by 2024, onshore oil venting is expected to produce 19,180.82 kt of pollutants. These results highlight the need for coordinated approaches that support better waste management, sustainable farming methods, and increased energy efficiency. In order to successfully reduce methane emissions, comprehensive strategies linking various sectors to effectively mitigate methane emissions.

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.