Environmental Sciences Europe最新文献

N,N-Diethyl-m-toluamide (DEET) is one of the significant chemical formulations used extensively in personal care products as a preventive measure against mosquito-borne diseases. It has been detected in the aquatic matrix at various concentrations from ng/L to mg/L. Chlorella vulgaris is one of the potential algal species for the treatment of wastewater containing personal care products, and this study investigates the acute toxicity and removal potential of Chlorella vulgaris in the removal of DEET with its effects on pigments and biochemical composition. The 96-h EC₅₀ was calculated to be 17.4 mg/L, and the biochemical composition assessment revealed that lipid concentrations in Chlorella vulgaris increased until the tolerance limit. This investigation revealed that when DEET concentration crossed the tolerance limit (17.4 mg/L) in the medium, the pigments and biochemical concentrations reduced drastically, indicating Chlorella vulgaris inhibitory response beyond the tolerance limit, causing irreversible damage to the algal cells. Furthermore, Chlorella vulgaris removal potential at three different test runs, T1 (5 mg/L), T2 (10 mg/L), and T3 (25 mg/L) were studied. The most remarkable elimination in T1 test runs was 72% due to biodegradation, followed by T2 (35%) and T3 (15%). T1 conditions resulted in more significant lipid formation than other test runs, making biofuel for DEET-contaminated wastewater a feasible alternative.

One of the causes of greenhouse gas emissions in the world is agriculture. One of the main threats to global growth today is climate change. This study summarizes the relationship between agricultural emissions and climate action, as well as the climate action outlined in Goal 13 of the Sustainable Development Agenda. Using a sample of panel data from 9 African countries between 2014 and 2023, we used fixed effect, random effect, and pooled regression. This study assesses the emissions of methane (CH₄), carbon dioxide (CO₂), and nitrous oxide (N₂O) from agriculture in East African countries between 2014 and 2023. Average agricultural CO₂ emissions are 940.57 kilotons, average N₂O emissions are 900.23 metric tons of CO₂ equivalent, and average methane emissions are 1713.6 thousand equivalent tones of CO₂, according to descriptive statistics. The analysis shows a positive relationship between greenhouse gas emissions and agricultural activities, including the use of fertilizers and cereal production. Furthermore, statistical models suggest that higher levels of fertilizer use and cereal production are linked to higher levels of CH₄ and N₂O emissions. Interestingly, the findings suggest that while increased methane emissions may be caused by larger areas planted for cereal production, increased greenhouse gas emissions are caused by intensified livestock production. According to the findings of the Hausman test, the fixed-effects model is the recommended specification for this investigation.

Background

Dumped munitions in German coastal waters, particularly the explosive 2,4,6-trinitrotoluene (TNT), may pose significant environmental risks. TNT and its metabolites, such as 2-amino-4,6-dinitrotoluene (2-ADNT) and 4-amino-2,6-dinitrotoluene (4-ADNT), contaminate marine organisms, including fish. These TNT metabolites bioaccumulate in fish tissues, serving as markers for environmental monitoring. Traditionally, fish bile has been a primary matrix to investigate TNT exposure; however, the present study is the first to explore the use of fish urine to detect TNT metabolites. Three flatfish species, common dab (Limanda limanda), European plaice (Pleuronectes platessa), and European flounder (Platichthys flesus) from three regions with munition dumping sites in the Western Baltic Sea were investigated.

Results

Differences in the levels of contamination at the dumping sites are reflected in the concentrations of explosives found in the urine and bile. Fish from the Kolberger Heide dumping site in Kiel Bight exhibited the highest concentrations of explosive contaminants. In individual dab, contamination with 2-ADNT was recorded up to 26.356 ng/ml in bile and 36.120 ng/ml in urine. Concentrations of 4-ADNT ranged up to 95.908 ng/ml in bile and 26.877 ng/ml in urine. The patterns of TNT metabolites in urine and bile varied, and the concentrations of these metabolites in urine and bile did not always correspond in individual fish. However, the different mean contamination levels in the three regions were reflected in both: urine and bile. Contamination levels of explosives in the three regions decreased in the order Kiel > Schlei > Lübeck.

Conclusions

TNT metabolites were detected in fish urine for the first time. Urine and bile can serve as useful matrices to assess environmental exposure of fish to TNT. Additionally, dab, plaice and flounder can be utilized in studies focusing on the analysis of explosives in bile or urine. The present study supports the development of fish urine usage for reliable and effective monitoring strategies for explosives.

The pollution in Dhaka's navigable waterways, including the Buriganga, Balu, Tongi Khal, and Turag rivers, is a significant concern due to rapid industrial and urban expansion. Industrial discharges, domestic sewage and inadequate waste management are the primary sources of this pollution, degrading water quality and threatening aquatic ecosystems. This study aimed to predict the Water Quality Index (WQI) of these rivers using fourteen machine learning (ML) models: Decision Tree Regression, Linear Regression, Ridge Regression, Stochastic Gradient Descent (SGD) Regressor, Extreme Gradient Boosting (XGB) Regressor, Light Gradient Boosting Machine (GBM) Regressor, Elastic Net Regressor, Support Vector Regression (SVM), Random Forest Regression, Bayesian Ridge Regressor, Artificial Neural Network (ANN), AdaBoost Regressor, CatBoost Regressor and Extra Trees Regressor. The objective was to evaluate and compare these models to identify the most effective predictive method for WQI, enabling efficient environmental monitoring and management of urban waterways. Among the evaluated ML models, ANN and Random Forest Regressor performed the best. The ANN model demonstrated superior predictive capability, achieving a Root Mean Squared Error (RMSE) of 2.34, a Mean Absolute Error (MAE) of 1.24, a Nash–Sutcliffe Efficiency (NSE) of 0.97, and a Coefficient of Determination (R²) of 0.97. Furthermore, an Adjusted R² value of 0.965 further confirmed its ability to capture complex patterns in water quality data with remarkable accuracy. These findings emphasize the importance of using AI modeling techniques, specifically ANN and Random Forest Regression, to improve the accuracy of WQI forecasts for the waterways. This study contributes to the field of environmental science by offering a novel integration of feature selection techniques with ML models to enhance efficiency and cost-effectiveness of water quality monitoring. Unlike previous studies, this research specifically addresses the challenges of urban waterways in Dhaka, Bangladesh, a region significantly impacted by industrial and urban pollution. To our knowledge, this is the first study to apply such a comprehensive range of ML models to predict the WQI of Dhaka’s four major rivers. By providing a reliable methodology for WQI estimation, this study supports informed decision-making and proactive measures to protect vital water resources.

The 3rd Annual China–Norway Marine University Consortium Alliance Conference, held in October 2024, served as a vital platform for interdisciplinary exchange between the natural and social sciences. The event underscored the importance of academic cooperation in the context of the complex geopolitical landscape. The conference featured sessions on marine geology, ocean dynamics, marine ecology, genetic adaptation, marine health, renewable energy, and Arctic governance. Experts from China, Norway, and other countries presented on diverse topics, including climate change impacts, sustainable development, biodiversity protection, Arctic cooperation, and social science. The discussions highlighted the synergies between scientific and policy domains, emphasizing the need for collaboration in areas, such as low-carbon transitions, sustainable ocean governance, and green energy. This conference, the first to be held in person since the COVID-19 pandemic, marked a significant milestone in advancing China–Norway relations, fostering mutual trust, and promoting collaborative initiatives in marine science and Arctic governance—critical for addressing global challenges.

Background

A debate exists about the effects of environmental disclosure becoming mandatory on the quality and the actual commitment of such reporting. This study seeks to assess whether differences exist when comparing the disclosure quality and comprehensiveness of Spanish companies’ non-financial reports under voluntary and mandatory reporting regimes spanning the period 2015–2022.

Methods

We present a novel approach by utilizing cutting-edge Natural Language Processing (NLP) techniques, chiefly ClimateBERT (a transformer-LLM—Large Language Model) and ClimateBERT fine-tuned on ClimaText (a public database for climate change topic detection), to scrutinize and compare 729 voluntary and mandatory non-financial corporate reports from 96 Spanish companies spanning multiple sectors. Since transformers can only be accurately estimated by organizations with lots of computing power, but not by small organizations, we have also fine-tuned the transformer, something cheaper in computational terms, thus making it affordable to all companies, investors, regulators, policymakers, and other stakeholders.

Results

Our results document interesting patterns and strong trends of enhancement in specificity and commitment, particularly in risk-related texts, spanning the period 2015–2022. We provide descriptive evidence and an explorative appeal that underscores the regulations' influence, among many other factors also identified by prior literature (other stakeholders’ requirements and expectations from companies, aside from the regulatory stakeholders), in fostering a higher quality and more comprehensive approach to climate risk reporting by Spanish companies, with enhanced alignment to internationally recognized reporting guidelines. In addition, the comparative analysis between the transformer model and the fine-tuned transformer model revealed subtle yet insightful differences in how climate disclosures are interpreted. The fine-tuned model exhibited an increased sensitivity to elements of commitment, specificity, and neutrality in climate texts.

Conclusions

Our findings highlight the potential of cutting-edge NLP techniques, like fine-tuned transformers, in the quantitative assessment of the evolution and quality of environmental disclosures, either mandatory or voluntary. It is the first paper applying a fine-tuned transformer-LLM to compare the currently in force European mandatory environmental disclosure regulation’s impact on Spanish companies' environmental disclosure versus previous voluntary reporting.

As a type of environmental regulation, environmental protection taxes (EPTs) have a Porter hypothesis effect. The Porter hypothesis effect is a comprehensive effect that includes the compliance cost effect, the innovation compensation effect, the weak Porter hypothesis effect, and the strong Porter hypothesis effect. The comprehensive effect of the Porter hypothesis is discussed through an evaluation of the implementation of an environmental protection tax law (EPTL). On the basis of the data of 729 heavily polluting enterprises, the mechanism of the regulatory effect of EPTs on the comprehensive effect of the Porter hypothesis is discussed via multiple linear regression equations. The results show that the compliance cost effect is still significant and that the innovation compensation effect, the weak Porter hypothesis effect, and the strong Porter hypothesis effect are declining. To realise the Porter hypothesis effect of environmental protection tax regulation more effectively, it is necessary to take the following measures: cultivate complex tax personnel; consult taxpaying enterprises on their information needs; optimise the collection and management process by applying the concept of precise service; reset the local tax rate; and increase the punitive provisions of the environmental protection tax law (EPTL).

Microplastics (MPs) are ubiquitous environmental contaminants, and amphibians are especially susceptible owing to their dual aquatic and terrestrial life cycle and permeable integument. This research examines the presence, composition, and potential origins of microplastics in tadpoles, adult frogs, and their environments in different regions of Türkiye, concentrating on three Anatolian water frog species: Pelophylax ridibundus, P. bedriagae, and P. caralitanus. Samples were obtained from 11 sites, encompassing water bodies, sediments, tadpoles, and the gastrointestinal tracts (GITs) of adult frogs. MPs were examined for polymer type, morphology, and dimensions via stereomicroscopy and Fourier transforms infrared spectroscopy. Results indicated that microplastics were absent in 64% of sediment and water samples; nevertheless, elevated quantities were identified in areas with considerable human activity, such as İstanbul. Tadpoles demonstrated negligible MP intake, with merely 2 MPs identified among 157 samples, resulting in an average of 0.01 MP per individual. Conversely, 44% of the 100 adult frogs exhibited microplastics in their gastrointestinal tracts, averaging 1.52 microplastics per individual. The MPs were primarily fibers (90.8%) and comprised polymers such as ethylene–vinyl acetate (EVA) (32.5%) and polycyclohexylenedimethylene terephthalate (PCT) (20.8%). The study emphasizes the potential dangers of microplastics to amphibian health and reinforces the necessity of addressing microplastic pollution in freshwater habitats through focused conservation initiatives.

Background

To improve the process of achieving good ecological and chemical status of waters, it is proposed that issues regarding the sediment in water bodies be incorporated in national and international river basin management programs. For a more realistic sediment quality assessment, multidimensional approaches that include various methods are preferred. The northern part of Serbia has an intertwined network of canals that receive untreated industrial and municipal wastewaters and pollution from the surrounding agricultural land. This leads to the accumulation of large amounts of sediments with varying quality in the canals. To assess the quality of the Great Backa and Bega canal sediments, an analysis based on chemical, ecological and ecotoxicological methods was conducted and the sediment quality triad approach was applied. Ecotoxicological data was obtained in a battery of tests on standard organisms belonging to different trophic levels in various exposure scenarios. Sediment contact tests on Myriophyllum aquaticum, immobilization tests on Daphnia magna (in water–sediment and elutriates) and Allivibrio fischeri bioluminescence tests (in elutriates) were performed. In addition, a small-scale accumulation test of potentially toxic elements on exposed plants was conducted.

Results

Responses of test organisms in the Great Backa samples were in line with the results of chemical analysis or stronger, while the analysis of aquatic macroinvertebrates reflected bad ecological potential of the canal. The Bega samples were highly contaminated and the ecological potential of the canal was graded as bad, but the ecotoxicological tests did not reveal high toxicity of samples. Plants exposed to samples from both canals took in metals, but inhibition of growth was detected only in the Great Backa samples, while the growth in the Bega samples was stimulated. The principal component analysis revealed no significant correlation between organism responses and results of chemical analysis. Based on the SQT applied, there is a likelihood of adverse effects posed by sediments from both canals.

Conclusions

Ecotoxicological tests complemented the commonly applied methods for sediment quality evaluation. The triad approach applied with the addition of the accumulation test contributed to a more ecologically relevant sediment quality assessment. Results indicated that remediation, dredging or mitigation measures are required.

Sustainability and environmental impact assessments of trade and investment agreements need to address biodiversity more effectively. To showcase this, we examined a report, commissioned by Switzerland, on potential environmental impacts and risks of the trade between Switzerland and the Mercosur under the EFTA–Mercosur Free Trade Agreement. Our analysis focuses on chemical pollution, regulatory impact, duty-free precious minerals, deforestation, and greenhouse gas emission to develop a roadmap for (re-)interpreting (muted) risks on biodiversity in light of the Global Biodiversity Framework. Our analytical approach on normative and substantive effectiveness of impact assessments encourages broader responses to impacts of economic policies on biodiversity and ecosystems.