Environmental Sciences Europe最新文献

Biological invasions pose a global challenge, threatening both biodiversity and human well-being. Projections suggest that as invasions increase, the financial costs associated with management and the ecological harm they cause will also escalate. Here, we examined whether long-term biomonitoring strategies were adequate to identify and track benthic aquatic non-native macroinvertebrate species by using the German subset (151 time series; 129 of which reported non-native species) of the currently most comprehensive European long-term dataset of 1816 macroinvertebrate community time series from 22 European countries. The detection of aquatic non-native species was directly linked to the availability of long-term sites and thus, monitoring effort, having identified the spatio-temporal occurrence of 32 non-native species. The available long-term monitoring site data were mostly concentrated in the western part of Germany, predominantly covering the Rhine River and its tributaries. The spatially biased network of long-term monitoring sites, therefore, naturally skews the detection and reporting of aquatic non-native species toward this area and underestimates Eastern and Southern regions, impeding the comprehension of invasion dynamics. However, based on the available data, we found that the absolute number of non-native species increased and the proportion of non-native species relative to native species decreased over time. This indicates complex ecological interactions between native and non-native species and underlines the value of long-term data for investigating invasion dynamics. Considering the value of comprehensive monitoring networks, a spatially biased network delays the application of management and mitigation plans, possibly worsening the ecological and economic effects of biological invasions in Germany. The results provided here indicate the disadvantages of biased datasets, but simultaneously underline the enormous potential of a dense network of long-term monitoring. Our results also highlight the urgent need to increase and diversify long-term biomonitoring efforts throughout Germany to cover the main freshwater resources and their connections where the introduction risk of non-native species is the highest. Centrally collating such data would provide a profound basis for the monitoring of spreading aquatic non-native species and could serve the implementation of national biosecurity efforts.

Background

Extreme floods are known to severely reorganise inhabited landscapes by inundation, clogging, scouring and damaging infrastructure and lives. However, their post-event impacts are poorly understood, especially concerning coupled hillslope channel feedbacks such as the reactivation of slope instabilities connected to the river and that may be able to block it upon sudden failure. The July 2021 Ahr valley flood exemplified this ability of concurrent and sustained landscape reorganisation. Here, we study a retrogressive slope instability near the town of Müsch, in the upper Ahr valley using field mapping, repeat airborne laser scanning, electrical resistivity tomography and passive seismic monitoring to reveal the failure geometry, its mechanisms and transient activity.

Results

The old landslide developed in lower Devonian rocks. It is 100 m wide, 200 m long and approximately 15–20 m deep, which leads to a total volume of about 430,000 m³. This landslide was severely undercut by the 2021 flood with 7000 m³ of material eroded at the landslide toe. The landslide has started to react. Given the narrow section of the river at this location, there is a potential landslide dam hazard. We modelled the inundation volumes and back fill times for different failure scenarios, ranging between 20,000 m³ and 330,000 m³ accumulating within 5 min and 20 h.

Conclusions

Our results imply a need to systematically screen flood impacted landscapes for sustained post-event hillslope activity that governs hillslope-channel coupling, driving both persistent sediment injection into the stream and sudden river blocking and subsequent damming.

Background

Fungicides are an effective tool for protecting crops and maintaining a steady food supply. However, as pathogens continue to evolve, it is crucial to prolong the effectiveness of fungicides by delaying resistance development. A key strategy to achieving this is to combine or rotate fungicides with different modes of action. As fungicides lack specificity, they inevitably affect both pathogenic and non-pathogenic fungi when surrounding environments are unintentionally contaminated. Our study aims to investigate the effects of recommended application methods to prevent resistance development, specifically repeated-single fungicide, simultaneous mixture, and sequential applications on non-target soil fungi, and the subsequent impacts on important soil processes. We used fungicides with different modes of action on soil microcosms inoculated with fungi at varying levels of diversity (3, 5, and 8 species) isolated from a protected grassland.

Results

We found that repeated treatments of individual isopyrazam and prothioconazole differentially inhibited fungal activity. Although mixture applications are considered more protectant against crop pathogen resistance than repeated application, our study revealed stronger negative effects of simultaneous application on saprobic fungi and consequently on soil processes. However, contrary to expectations, higher fungal diversity did not translate to improved soil function under these conditions.

Conclusions

The simultaneous application of fungicides with different modes of action (MoA) has more pronounced non-target effects on soil compared to the individual or sequential application of fungicides. These non-target effects extend beyond the intended control of pathogenic fungi, impacting saprobic and beneficial soil microbes and the critical processes they drive. When fungicides are applied concurrently, microbial activities in the soil are significantly altered, even in soils with high microbial diversity. Our study emphasizes the importance of carefully considering the unintended consequences of fungicide use in agriculture. As we strive for a secure food supply, it is crucial to investigate the broader environmental impacts of these chemical interventions, including their effects on non-pathogenic fungi and overall soil health.

Climate change affects the world economy, environment, and human well-being, jeopardizing overall sustainability. The escalating impacts of climate change emphasize the necessity to assess the moderating influence of environmental policy stringency (EPS) on the association of energy transition (ET) and GHG emissions from 1990 to 2020 across 36 OECD countries. Further, this study incorporates the direct impact of energy transition (ET), environmental-related technology (ERTs), green innovation (INV), and Gross Domestic Product (GDP) on GHG emission. For this purpose, study employs an extensive range of econometric techniques, including DOLS, FMOLS, CCR, and MMQR approaches to evaluate data attributes. The findings of MMQR demonstrate that interaction of ET*EPS contributes to lower GHG emissions from −0.271% to −0.300% across all quantiles (20th to 80th). This indicates that the implementation of environmental policies fosters adoption of energy transitions to mitigate the negative effects of climate change, particularly to reduce GHG emissions. Further, environmental-related technologies (ERTs) and green innovation (INV) decrease GHG emissions by 0.15%–0.13% and 0.967%–2.049%, respectively, across all quantiles, thus encouraging environmental sustainability. The heterogeneous effect of ERTs is due to varying levels of adoption of environmental technologies in sample countries. The findings highlight the crucial need for integrating environmental policy strictness and energy transition measures to effectively mitigate GHG emissions. It highlights the significance of adaptive, responsive policies that are in line with SDGs 7 & 13, which concentrate on sustainable energy practices and integrated climate action in OECD economies.

Graphical Abstract

Groundwater is a primary source of drinking water for billions worldwide. It plays a crucial role in irrigation, domestic, and industrial uses, and significantly contributes to drought resilience in various regions. However, excessive groundwater discharge has left many areas vulnerable to potable water shortages. Therefore, assessing groundwater potential zones (GWPZ) is essential for implementing sustainable management practices to ensure the availability of groundwater for present and future generations. This study aims to delineate areas with high groundwater potential in the Bankura district of West Bengal using four machine learning methods: Random Forest (RF), Adaptive Boosting (AdaBoost), Extreme Gradient Boosting (XGBoost), and Voting Ensemble (VE). The models used 161 data points, comprising 70% of the training dataset, to identify significant correlations between the presence and absence of groundwater in the region. Among the methods, Random Forest (RF) and Extreme Gradient Boosting (XGBoost) proved to be the most effective in mapping groundwater potential, suggesting their applicability in other regions with similar hydrogeological conditions. The performance metrics for RF are very good with a precision of 0.919, recall of 0.971, F1-score of 0.944, and accuracy of 0.943. This indicates a strong capability to accurately predict groundwater zones with minimal false positives and negatives. Adaptive Boosting (AdaBoost) demonstrated comparable performance across all metrics (precision: 0.919, recall: 0.971, F1-score: 0.944, accuracy: 0.943), highlighting its effectiveness in predicting groundwater potential areas accurately; whereas, Extreme Gradient Boosting (XGBoost) outperformed the other models slightly, with higher values in all metrics: precision (0.944), recall (0.971), F1-score (0.958), and accuracy (0.957), suggesting a more refined model performance. The Voting Ensemble (VE) approach also showed enhanced performance, mirroring XGBoost's metrics (precision: 0.944, recall: 0.971, F1-score: 0.958, accuracy: 0.957). This indicates that combining the strengths of individual models leads to better predictions. The groundwater potentiality zoning across the Bankura district varied significantly, with areas of very low potentiality accounting for 41.81% and very high potentiality at 24.35%. The uncertainty in predictions ranged from 0.0 to 0.75 across the study area, reflecting the variability in groundwater availability and the need for targeted management strategies.

In summary, this study highlights the critical need for assessing and managing groundwater resources effectively using advanced machine learning techniques. The findings provide a foundation for better groundwater management practices, ensuring sustainable use and conservation in Bankura district and beyond.

Background

Transport, accumulation, and degradation of microplastics (MiPs) in the aquatic environment represent a significant concern to the researchers and policy-makers, due to the detrimental impact on biota and human health through food ingestion. Although consistent investigations and research data are available worldwide, comparing the results is still challenging due to the need for more regulations regarding the sampling methods, analysis, and results reporting. The European regulatory efforts include studies on the MiPs transport in the western basin of the Danube River developed with active nets-based multipoint sampling methods from suspended sediments and proposed for standardization. In this context, the present study aimed to address for the first time the transport of MiPs in the Romanian sector of the Danube, starting after entering the country (Moldova Veche) and before the formation of the Danube Delta (Isaccea).

Results

The multipoint nets sampling procedure facilitated the collection of suspended sediments in the water columns as deep as 0.0–0.6 and 3.0–3.6 m depths and near riverbed sediments (autumn 2022 sampling) during an extensive spatio-temporal study from spring 2022 until spring 2023. The estimate of the maximum annual transport of 46–51 and 93–100 t·y⁻¹ for MiPs and total (micro–meso–macroplastics) MPs at Moldova Veche was based on 135 collected and processed samples using 2021 water flow data. Polyethylene (58–69%) and polypropylene (21–33%) were the main polymer components in the separated fragments, foils, microfibers, and different colors spheroids of MiPs ( < 5 mm), and the foils and fibers of meso–macroplastics (5–100 mm). Advanced investigations highlighted various microstructural degradations of the plastic fragments at the micro- and nanoscale and attached minerals (clays) and heavy metals.

Conclusion

This paper presents the first comprehensive data set for microplastic annual transport in the "Low Danube", filling the need for a complete transport assessment in one of the most significant European rivers. 4–5 times lower values were measured before the entrance to the Danube Delta than those from Moldova Veche. The investigations should continue, including flooding events, and the sampling points should be expanded to deeper water column layers during all the campaigns for further validation.

Graphical Abstract

Background

PM₁₀, comprising particles with diameters of 10 µm or less, has been identified as a significant environmental pollutant associated with adverse health outcomes in European cities. Understanding the temporal variation of the relationship between PM₁₀ and geographical parameters is crucial for sustainable land use planning and air quality management in European landscapes. This study utilizes Conditional Inference Forest modeling and partial correlation to examine the impact of geographical factors on monthly average concentrations of PM₁₀ in European suburban and urban landscapes during heating and cooling periods. The investigation focuses on two buffer zones (1000 m and 3000 m circle radiuses) surrounding 1216 European air quality monitoring stations.

Results

Results reveal importance and significant correlations between various geographical variables (soil texture, land use, transportation network, and meteorological) and PM₁₀ quality on a continental scale. In suburban landscapes, soil texture, temperature, roads, and rail density play pivotal roles, while meteorological variables, particularly monthly average temperature and wind speed, dominate in urban landscapes. Urban sites exhibit higher R-squared values during both cooling (0.41) and heating periods (0.61) compared to suburban sites (cooling period R-squared: 0.39; heating period: R-squared: 0.51), indicating better predictive performance likely attributed to the less heterogeneous land use patterns surrounding urban PM₁₀ monitoring sites.

Conclusion

The study underscores the importance of investigating spatial and temporal dynamics of geographical factors for accurate PM₁₀ air quality prediction models in European urban and suburban landscapes. These findings provide valuable insights for policymakers, urban planners, and environmental scientists, guiding efforts toward sustainable and healthier urban environments.

Background

Biodiversity loss is particularly pronounced in agroecosystems. Agricultural fields cover about one-third of the European Union and are crucial habitats for many species. At the same time, agricultural fields receive the highest pesticide input in European landscapes. Non-target species, including plants and arthropods, closely related to targeted pests, are directly affected by pesticides. Direct effects on these lower trophic levels cascade through the food web, resulting in indirect effects via the loss of food and habitat for subsequent trophic levels. The overarching goals of the European pesticide legislation require governments to sufficiently consider direct and indirect effects on plants and arthropods when authorising pesticides. This publication provides an overview of a workshop's findings in 2023 on whether the current pesticide risk assessment adequately addresses these requirements.

Results

Effects due to in-field exposure to pesticides are currently not assessed for plants and inadequately assessed for arthropods, resulting in an impairment of the food web support and biodiversity. Deficiencies lie within the risk assessment, as defined in the terrestrial guidance document from 2002. To overcome this problem, we introduce a two-step assessment method feasible for risk assessors, that is to determine (i) whether a pesticide product might have severe impacts on plants or arthropods and (ii) whether these effects extend to a broad taxonomic spectrum. When each step is fulfilled, it can be concluded that the in-field exposure of the pesticide use under assessment could lead to unacceptable direct effects on non-target species in-field and thus subsequent indirect effects on the food web. While our primary focus is to improve risk assessment methodologies, it is crucial to note that risk mitigation measures, such as conservation headlands, exist in cases where risks from in-field exposure have been identified.

Conclusions

We advocate that direct and indirect effects caused by in-field exposure to pesticides need to be adequately included in the risk assessment and risk management as soon as possible. To achieve this, we provide recommendations for the authorities including an evaluation method. Implementing this method would address a major deficiency in the current in-field pesticide risk assessment and ensure better protection of biodiversity.

During the July 2021 European floods approximately eight million empty dairy packaging (buttertubs) were flushed from a dairy processing facility in Belgium into the Vesdre river. Some were transported further downstream, into the Ourthe river and eventually the Meuse river. There are many unknowns when it comes to plastic transport in rivers, especially in response to floods. We therefore used this incident as an unique opportunity to study these buttertubs as a tracer for plastic transport dynamics in a riverine environment in response to an extreme flood event. Normally, it is unknown when and where individual plastic items found on riverbanks entered the environment. In this case, however, the ID stamps on the buttertups allowed for them to be traced back to the flooding of the factory. We studied the transport and deposition of these buttertubs in the Dutch Meuse over 2 years following the flood. We also collected buttertubs at different points in time to investigate their fragmentation and mass loss. Within 3 weeks of the flood, the buttertubs were transported up to 328 km from the spilling location. Overall, the majority (78%) of buttertubs we found within the first 3 weeks were deposited within less than 100 km of the point of emission. Over the following 2 years, the mean transport distance of the found buttertubs moved downstream from 100 km in July/August 2021, to 153 km in July 2023. The buttertubs average transport velocity decreased from 11.7 km/d within the first 3 weeks, to 0.2 km/d by July 2023. Based on the 89 buttertubs we collected and analyzed in detail over the 2 years, we did not find a significant mass loss. Of all 89 buttertubs found, 47 showed cracks and only 12 appeared to have pieces missing. This study shows that even during extreme flood events, the majority of spilled plastic litter is retained within a limited distance after being emitted into the river. The findings of this study can be utilized to improve plastic transport modelling, and overall better understand plastic transport in the freshwater environment.