Vestergaardditlevsen1035

Our findings provided insights into a new biological system with simultaneous C, N and P bioconversions, and improved the understanding of interactions among the key populations.Lead (Pb) is a highly toxic pollutant and represents a serious threat to wildlife, affecting various systems in animal bodies. Especially prone to Pb poisoning are waterbirds, which may inadvertently ingest spent gunshot, fishing sinkers and contaminated sediments. This research thus focused on evaluating Pb concentrations in the blood of 170 Mute swans (Cygnus olor; a widespread species of waterbirds) at their summer (urban locations in Małopolskie and rural locations in Świętokrzyskie regions) and winter (the urban section of Wisła River in Krakow) sites in Poland (Europe). The study concentrated on comparing blood Pb concentrations according to sites and locations, verifying the influence of sex and age factors, examining the impact on hematocrit (Ht), glutathione (GSH) levels and body condition. Mean blood Pb concentrations (measured with ICP-OES) differed significantly between summer and winter sites (Regression by Maximum Likelihood Estimation (RML), p 0.231). Pb concentrations correlated weakly with Ht and GSH levels (Spearman test) and had no influence on body condition (proxied by scaled mass index; GLM, p = 0.246). We concluded that differences between summer and winter sites were dictated mainly by the type of habitat (rural vs. urban) that birds occupied in different seasons.Understanding how climate change would affect biota inhabiting sensitive and highly valuable ecosystems, spanning broad regions, is essential to anticipate implications for biodiversity and humans, and to identify management and mitigation measures. Traditionally, assessments to evaluate climatic risks over broad regions and for many species implement models that allow the projection of a climate-driven redistribution of biodiversity. Still, the wealth and quality of the background information (e.g., species presence data) constrain the accuracy and representativeness of such frameworks. As an alternative, here, we developed a twofold approach to assess the vulnerability of 86 European freshwater fish. We accounted for shifts in a multidimensional climatic space of broader hydrological units that host freshwater bodies in Europe. We then linked metrics of their climatic stability with groups of species, which were generated from six intrinsic traits that shape species adaptive capacity to climate change. Our results demonstrated that the climate of all (n = 538) river sub-basins hosted in the European Union territory would change by 2100, with more than 10% of them being projected to gain completely novel climates. Sub-basins predicted to lose more than 90% of their current climatic space were mainly identified in the area around the Baltic Sea, but also in Mediterranean regions (i.e., Iberian Peninsula). Important numbers of fish species with life history strategies that are considered susceptible to climate change were identified in sub-basins that were predicted to completely lose their current climatic conditions. Clearly, the climate of valuable freshwater ecosystems is changing, affecting species and their communities in varying ways. The risk is high, and is not limited to specific regions; thus, new effective strategies and measures are needed to conserve freshwater fish and their habitats across Europe.Organic aerosols (OAs) in particulate matter with an aerodynamic diameter of smaller than 2.5 μm (PM2.5) can affect the atmospheric radiation balance through varying molecular structure and light absorption of the aerosols. In this study, daytime and nighttime PM2.5 mass, and contents of OA including nitrated aromatic compounds (NACs), polycyclic aromatic hydrocarbons (PAHs), n-alkanes, and hopanes were measured from April 11th to May 15th, 2017, at the coastal Sanya, China. The average concentration of 18 total quantified PAHs (∑PAHs) was 2.08 ± 1.13 ng·m-3, which was 2.8 and 12 times higher than that of ∑NACs and hopanes, while was 7.5 times lower that of n-alkanes. Combustion-derived PAHs contributed 74% to the ∑PAHs. This finding, in addition to a high benzo[a]pyrene/(benzo[a]pyrene+benzo[e]pyrene) ratio, indicates that the PAHs mainly derived from fresh fuel combustion during the sampling periods. Furthermore, dramatic day-night differences were observed in the loadings of total NACs, PAHs, and n-alkanes, which had a high coefficient of divergence values of 0.67, 0.47, and 0.32, respectively. Moreover, hopanes exhibited similar variation as well. The proportion of dimethyl-nitrophenol (DM-NP), dinitrophenol (DNP), and nitrosalicylic acid (NSA) in PM2.5 were higher in the daytime than at nighttime, suggesting the co-influence of primary emissions and secondary formation related to biomass combustion. The positive matrix factorization (PMF) model revealed that motor vehicle and biomass burning emissions were the two main pollution sources in the daytime, contributing 51.7% and 24.6%, respectively, of the total quantified OAs. The proportion of industrial coal combustion emissions was higher at nighttime (20.6%) than in daytime (10%). Both the PAHs and NACs displayed light absorbing capacities among OAs compounds over Sanya City, and thus their influence on solar radiation must be considered in the future control policies.Synthetic phenolic antioxidants (SPAs) are an environmental concern because they are widely detected in aquatic ecosystems and can pose potential threats to organisms. Studies have reported developmental deficits and behavioral changes in response to SPAs, indicating possible neurotoxic effects. However, their neuroactive potency as well as their mode of action (MoA) remain unclear. As such, this study evaluated the potential neurotoxicity of three SPAs [butylated hydroxytoluene (BHT), 2,4-di-tert-butylphenol (2,4-DTBP), and 4-tert-octylphenol (4-t-OP)] at three concentrations (0.01, 0.1 and 1 μM) to zebrafish larvae. Both 2,4-DTBP and BHT decreased spontaneous tail coiling (STC) at 28 hpf (hours post fertilization) whereas 4-t-OP increased STC. Locomotor activity, based on the velocity and distance of larvae (144 hpf) travelled, was promoted by 2,4-DTBP while it decreased in larvae with exposure to 4-t-OP and BHT. Selleck GANT61 In the light-dark preference assay, exposure to either 2,4-DTBP or BHT resulted in variability in the visiting frequency to the dark zone, and larvae (144 hpf) spent less time in the dark, suggesting anxiety-like behavior. Conversely, zebrafish exposed to 4-t-OP, especially at 1 μM concentration, were hypoactive and spent more time in dark, suggestive of anxiolytic-like responses. RNA-seq was conducted to discern mechanisms underlying behavioral responses. Transcriptomic analysis revealed that gene networks related to neuroactive ligand-receptor interaction as well as neurotransmitter-related pathways were altered by all three SPAs based on gene set and subnetwork enrichment analysis. Modulation of dopaminergic, serotoninergic, and/or GABAergic signaling at the transcript level was noted for each of the three SPAs, but different expression patterns were observed, indicating SPA- and dose-specific responses of the transcriptome. The present study provides novel insight into potential mechanisms associated with neurotoxicity of SPAs congeners.The measures taken to contain the spread of COVID-19 in 2020 included restrictions of people's mobility and reductions in economic activities. These drastic changes in daily life, enforced through national lockdowns, led to abrupt reductions of anthropogenic CO2 emissions in urbanized areas all over the world. To examine the effect of social restrictions on local emissions of CO2, we analysed district level CO2 fluxes measured by the eddy-covariance technique from 13 stations in 11 European cities. The data span several years before the pandemic until October 2020 (six months after the pandemic began in Europe). All sites showed a reduction in CO2 emissions during the national lockdowns. The magnitude of these reductions varies in time and space, from city to city as well as between different areas of the same city. We found that, during the first lockdowns, urban CO2 emissions were cut with respect to the same period in previous years by 5% to 87% across the analysed districts, mainly as a result of limitations on mobility. However, as the restrictions were lifted in the following months, emissions quickly rebounded to their pre-COVID levels in the majority of sites.E1 and E2 are considered as the parent natural estrogens (NEs) in human metabolism pathways of NEs, while the enantiomer of E2, αE2 was not included and ignored. In this study, αE2 along with the other eleven NEs with estrogenic activities were found in six healthy human urines with the total concentration levels of 62.9-99.3 μg/L. The concentration contributed ratios (CCRs) of αE2 to the total twelve NEs ranged from 4.7% to 11.0% with an average CCR of 7.0%. On the basis of the average CCR, αE2 was 1.5 times that of E2, which suggested that αE2 was one important NE in humans. As the main source of NEs in municipal wastewater was derived from human urine, αE2 should also be an important NE in municipal wastewater that can be proven by previous limited studies, in which the municipal effluent concentrations of αE2 ranged from not detection to 144.2 ng/L with an average concentration of 11.9 ng/L, indicating αE2 in municipal effluent was an important source to the natural environment. Although αE2 is a NE with weak estrogenic potency, the estrogenic effect of αE2 via municipal effluent to its receiving water body cannot be ignored because it can be bio-transformed into E2 under aerobic environment. This work is the first to indicate that αE2 is an ignored NE in human and its environmental risk via municipal effluent discharging cannot be ignored, which should be paid with attention.Biochar has been used widely in heavy metal contaminated sites as a soil remediation agent. However, due to the diversity of soils, biochars, and heavy metal contamination status, the remediation efficiency is difficult to measure, owing to a variety of parameters such as soil, biochar properties, and remediation procedure. Thus, an appropriate method to predict the remediation results and to select the appropriate biochar for the remediation is required. We initially created a database on soil remediation by biochars, which has 930 datasets with 74 biochars and 43 soils in it, based on collecting and organizing data from published literatures. Then, using data from the database, we modeled the remediation of five heavy metals and metalloids (lead, cadmium, arsenic, copper, and zinc) by biochars using machine learning (ML) methods such as artificial neural network (ANN) and random forest (RF) to predict remediation efficiency based on biochar characteristics, soil physiochemical properties, incubation conditions (e.g., water holding capacity and remediation time), and the initial state of heavy metal. The ANN and RF models outperform the lineal model in terms of accuracy and predictive performance (R2 > 0.84). Meanwhile, model tolerance of the missing data and reliability of the interpolation were studied by the predicted outputs of the models. The results showed that both ANN and RF have excellent performances, with the RF model having a higher tolerance for missing data. Finally, through the interpretability of ML models, the contribution of factors used in the model were analyzed and the findings revealed that the most influential elements of remediation were the type of heavy metals, the pH value of biochar, and the dosage and remediation time. The relative importance of variables could provide the right direction for better remediation of heavy metals in soil.