Environmental Sciences Europe最新文献

The impacts of environmental pollutants on prenatal health are a growing concern, yet we still have limited understanding of how specific pollutants like polychlorinated biphenyls (PCBs) impact inflammation and oxidative stress in umbilical cord blood. This study explores how exposure to PCBs in umbilical cord blood relates to biomarkers of inflammation and oxidative stress in newborns. Between June 2019 and August 2021, we conducted a study with 450 pregnant women. We measured umbilical cord blood PCB levels using advanced Gas Chromatography-Mass Spectrometry (GC–MS). We also assessed key biomarkers Tumor Necrosis Factor-Alpha (TNF-α), Interleukin-6 (IL-6), Interleukin-8 (IL-8), Transforming Growth Factor Beta (TGF-β), and Pro-oxidant Antioxidant Balance (PAB) using enzyme-linked immunosorbent assays (ELISA). To analyze the data, we employed multivariable regression models and quantile g-computation. Higher levels of specific PCBs were associated with increased levels of inflammatory markers like TNF-α and IL-6, as well as PAB. In particular, PCBs such as PCB-28, PCB-138, PCB-153, and PCB-180 were linked to elevated TNF-α and IL-6. The g-comp analysis also showed that as PCB levels increased, so did the levels of all five biomarkers, indicating a cumulative impact on inflammation and oxidative stress. This study is the first to link PCB exposure in umbilical cord blood with increased markers of inflammation and oxidative stress, shedding new light on the potential health risks for newborns. These findings highlight the importance of further research into how prenatal exposure to PCBs might affect long-term health outcomes.

Microbial pesticides are a class of biopesticide that includes microorganisms, such as bacteria, fungi, viruses, and protozoa, that are applied for pest control. Mammalian (human health) and non-target organism hazard testing are required to support registrations of microbial pesticides; however, developers and regulators of microbial pesticides face both new and old challenges for testing. New challenges include how to design or adapt new approach methodologies (NAMs), typically developed for chemicals, to mammalian health testing for microbial pesticides. Older challenges involve need for improved guidance for hazard testing with non-target organisms. Both are viewed as potential barriers to the development and adoption of microbial pesticides, which are potential alternatives to chemical pesticides. The 2022 conference, Innovating Microbial Pesticide Testing (hereafter, “the Conference”), sponsored by the Organisation for Economic Cooperation and Development (OECD) Cooperative Research Program (CRP), brought together experts on these topics from academic, industry, government, and non-governmental organizations to discuss the above challenges and establish plans to address them. Speakers presented on their perspectives of the challenges and potential solutions, which informed and guided panel discussions. This paper summarizes the contributions from presentations and panel discussions toward the conference conclusions and resulting workplans.

HFC-134a is the most prevalent hydrofluorocarbon used as a replacement for ozone-depleting CFCs and HCFCs. Due to its high global warming potential, it is regulated under various European and global frameworks, underscoring the importance of tracking its emissions. Emissions derived by the commonly used, bottom-up, methodology are affected by a certain degree of uncertainty. The bottom-up estimates can be aided with an independent top-down estimate based on atmospheric observations combined with an atmospheric transport model. This study presents HFC-134a emissions for Europe, with a specific focus on Italy, from 2008 to 2023. The emissions were estimated using a Bayesian inversion methodology, based on atmospheric observations collected at four European stations. Our analysis reveals a slightly increasing trend in HFC-134a emissions for Italy from 2008 to 2015 of 0.17 ({mathrm{Gg,yr}^{-1}}), followed by a steady decrease thereafter, highlighting the effect of European regulation on fluorinated gases that came into force in 2014. We observed a reduction in HFC-134a emissions in the Po Basin inferred from the inversion method for 2020, likely due to mobility restrictions imposed during the COVID-19 pandemic. The observed mild seasonality in emissions may be partly attributed to higher air-conditioning activity during summer. Comparison with the Italian National Emission Inventory indicates an improvement in iterative bottom-up estimates, with the 2024 inventory emission trend post-2015 aligning closely with our inversion results. This study emphasises the need for collaboration between the two independent approaches to enhance the accuracy of emission estimates. Such cooperation is crucial to narrowing the gap in quantifying emissions of potent greenhouse gases and effectively assessing the progress of international policies and regulations.

Background

Phthalates exposure and its potential link to cancer are increasingly drawing public attention, which are found in products frequently used by women, including plastic food packaging and cosmetics. Given the lack of consensus from existing studies on the association of phthalate exposure with breast cancer, conducting large-scale, well-designed epidemiological studies is crucial for clarifying this potential risk.

Methods

Utilizing data from the National Health and Nutrition Examination Survey (NHANES), this study assessed the correlation between exposure to phthalates and the risk of breast cancer. The analysis included ten phthalate compounds selected based on their prevalence and potential health impact. Multiple logistic regression was used to examine the correlation between phthalate exposure or other risk factors and breast cancer. Furthermore, machine learning-based predictive models were constructed to evaluate the significance of different variables.

Results

In the multivariate logistic regression analysis, four types of phthalates including MEP, DEHP, MEHHP, and MEOHP were identified as risk factors of breast cancer. In addition, MIBP, MINP, MEHP were also recognized as risk factors after adjusting for age. Conversely, MNBP and MCPP exhibited protective effects against breast cancer. Notably, MIBP demonstrated the most significant predictive power in machine learning models. The predictive model’s accuracy, as indicated by the area under the ROC curve, was 87.1%. Furthermore, survival analysis indicated that breast cancer patients with higher levels of phthalate exposure experienced significantly poorer survival outcomes than those with lower exposure levels. Intriguingly, subgroup analysis revealed a significant inverse association between phthalate exposure and breast cancer risk, particularly among individuals with elevated blood lipid levels.

Conclusions

The study revealed that exposure to specific phthalates was significantly associated with an elevated risk of breast cancer. Conversely, a higher concentration of blood lipids appeared to be negatively correlated with this risk.

Background

Particulate matter (PM), a mixture of solid and liquid particles suspended in the air, poses a significant environmental health risk. Exposure to PM has been linked to adverse cardiopulmonary effects, including cardiac fibrosis. Reversing the serious consequences of fibrosis or preventing its onset remains a significant challenge at present.

Methods

This project includes animal and cell-based experiments. In the animal component, C57BL/6J mice were serially exposed to PM for 3 or 6 months. Neonatal rat cardiac fibroblasts (NRCFs) were isolated and exposed to 100 μg/mL PM for different periods. Bafilomycin A1(BAF), compound C(CC) and siRNA were employed to explore potential pathways.

Results

Comprehensive analyses revealed that 6 months of PM exposure in mice and 48 h of exposure in NRCFs led to fibrosis. To explore potential preventive strategies for fibrosis caused by environmental damage, we focused on the fibroblast activation stage (3 months in mice and 24 h in NRCFs. Exposure to PM was found to elevate expression of hypoxia-inducible factor 1 alpha (HIF1α), activate of the AMPK–mTOR pathway and the accumulate autophagosomes both in vivo and in vitro. Treatment with the AMPK inhibitor, compound C reversed the autophagosome accumulation in PM-exposed NRCFs. Utilizing Bafilomycin A1, we demonstrated that PM blocked the fusion of autophagosomes and lysosomes (autophagy flux). Additionally, inhibiting HIF1α reduced fibroblast activation and autophagy alteration dependent on the AMPK–mTOR pathway.

Conclusion

Our findings indicate that fibroblast activation induced by PM exposure is dependent on blocked fusion of autophagosomes and lysosomes mediated by the AMPK–mTOR pathway, which is regulated by HIF1α. Targeting this pathway may provide a novel therapeutic approach for the prevention and treatment of PM-induced cardiac fibrosis.

Marine coatings used on merchant ships have recently emerged as a source of microplastics in marine environments. Marine coatings encompass all paints and coatings applied to various parts of a ship, primarily for anti-corrosion, antifouling anti-skid, heat-resistance, and cosmetic enhancement. However, marine coatings on merchant ships have evaded classification and were not included in the microplastic literature until recently. The purpose of this study is to examine the current state of the absence of a unified definition on a global scale, identify the factors that contribute to the exclusion of marine coatings under the microplastic classification and to analyse the thematic mapping and evolution of the keywords “definition”, “classification”, and “paint” or “marine coatings” in the field of microplastics. We conducted science mapping analysis using Bibliometrix software to examine 1078 papers and carried out a systematic narrative literature review to examine the current state of a standardised definition of microplastics and whether the absence of such impedes a unified interpretation and study of microplastics from marine coatings. Based on the science mapping analysis, this research indicates that “definition” and “paint” have become important keywords in the domain of microplastic research lately, playing a vital role in structuring the field. Meanwhile, the systematic narrative literature review unveiled that the absence of a standardised definition remains a subject of considerable debate, resulting in marine coatings evading classification as microplastics. With this study, we aim to advocate for the establishment of more precise guidelines and policies pertaining to microplastic pollution in marine environments and to promote the adoption of a unified approach towards the definition and classification of microplastics for the purposes of legislation and research. This will also path the way for the collection of better data on microplastic emissions from marine coatings, thereby closing the knowledge gap in this area.

Soil erosion is a major concern in the Kangsabati River basin, necessitating a comprehensive scientific approach for effective soil erosion management. This study aimed to predict soil erosion susceptibility zones in the basin using integrated soil erosion and deep learning (DL) based stacking framework. Additionally, the SHAP (SHapley Additive exPlanations) model was utilized to augment the interpretability of the DL model. The study employed the RUSLE model to estimate the soil loss. Through ArcGIS, 2000 erosion sites and 2000 non-erosion sites were randomly selected to generate an inventory map. The study considered 17 factors in four primary categories: topographic, climatic, soil, and land use/land cover (LULC). The Boruta algorithm assessed the importance of these variables. Random Forest (RF), (Deep Neural Networks) DNN, Convolution Neural Network (CNN), and stacking (Meta model) models were used to map soil erosion susceptibility based on the inventory map and controlling features. The RUSLE model revealed five erosion zones with soil loss rates ranging from very low (less than 9 t/ha/year) to very high (above 43 t/ha/year). The results demonstrated that 24.93% of the study area fell within the very high erosion susceptibility zone as predicted by DNN, while RF identified 34.32%, Meta model identified 24.84%, and CNN indicated 10.47% of the study area falling into the very high erosion susceptibility category. In terms of RMSE (value) and MSE, the Meta model demonstrates superior performance, whereas the DNN model excels in terms of MAE. The SHAP values output highlights the substantial impact of Land Use and Land Cover (LULC), the K factor, soil moisture, and elevation on the DNN model. These findings provide a scientific basis for developing strategies and policies to combat soil erosion in the Kangsabati River basin, aiding targeted interventions and sustainable land management decisions.

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.