Notes

CD39 Regulation and procedures inside T Cells.
Numerical runout models are important tools for predicting the potential downstream impacts of tailings dam breaches that generate tailings flows, which is a crucial step in emergency preparedness and planning, and risk management. Most existing runout models were originally developed for the analysis of water floods or flow-like landslides (e.g. debris flows). In this study, we back-analyze two well-documented historical tailings dam breaches (1985 Stava, Italy and 1994 Merriespruit, South Africa) using four numerical models (DAN3D, MADflow, FLO-2D and FLOW-3D). The main objective of this multi-case, multi-model benchmarking exercise is to identify collective opportunities to adapt these types of models and associated modelling methods to tailings dam breach runout applications. Comparing best-fit simulation results, we find that all four models are capable of reproducing the bulk behaviour of the real events; however, (i) multiple sets of rheological parameters may produce very similar output results, (ii) the best-fit input parameter combinations are non-transferable between models and inconsistent with independently measured rheological properties of stored tailings, and (iii) choosing an appropriate set requires sufficient understanding of material rheological properties and expert judgment. Using a systematic sensitivity analysis with the First-Order Second-Moment (FOSM) approach, we also find that each model is sensitive to different input parameters, although the total released volume is among the main high-influence parameters in every scenario. We conclude that more case study back-analyses are needed to enhance our understanding of these sensitivities and develop better guidance on the use of these types of numerical models for tailings flow runout prediction.Air pollution stemming from human activities affects the environment in which plant and animal species live and interact. Similar to primary air pollutants which are emitted, secondary air pollutants, such as tropospheric ozone (O3) formed from nitrogen oxides, are also harmful to human health and plant physiology. Yet, few reports studied the effects of O3 on pollinators' physiology, despite that this pollutant, with its high oxidative potential, likely affects pollinators behaviors, especially the perception of signals they rely on to navigate their environment. Volatile Organic Compounds (VOCs) released by plants are used as signals by different animals. For pollination services, VOCs attract different insects to the flowers and strengthen these interactions. Here, we used the honey bee Apis mellifera as a model to characterize the effects of acute exposure to different realistic mixing ratios of O3 (80-, 120-, and 200-ppb) on two crucial aspects first, how exposed honey bees detect VOCs; and second, how O3 affects these pollinators' learning and memory processes. With electroantennogram (EAG) recordings, we showed that increasing O3 mixing ratios had a biphasic effect an initial 25% decrease of the antennal activity when bees were tested directly after exposure (O3 direct effect), followed by a 25% increase in activity and response when bees were allowed a two-hour rest after exposure (O3 delayed effect). In parallel, during olfactory conditioning, increasing O3 mixing ratios in both exposure protocols scarcely affected olfactory learning, followed by a decrease in recall of learned odors and an increase of response to new odors, leading to a higher generalization rate (i.e., discrimination impairment). These results suggest a link between O3-related oxidative stress and olfactory coding disturbance in the honey bee brain. If ozone affects the pollinators' olfaction, foraging behaviors may be modified, in addition with a possible long-term harmful effect on pollination services.Understanding the role of biodiversity in maintaining ecosystem functioning and stability under increasing frequency and magnitude of climatic extremes has fascinated ecologists for decades. Although growing evidence suggests that biodiversity affects ecosystem productivity and buffers ecosystem against climatic extremes, it remains unclear whether the stability of an ecosystem is caused by its resistance against disturbances or resilience towards perturbations or both. In attempting to explore how species richness affects resistance and resilience of above-ground net primary productivity (ANPP) against climatic extremes, we analyzed the grassland ANPP of the long-running (1997-2020) Bayreuth Biodiversity experiment in Germany. We used the Standardized Precipitation Evapotranspiration Index to identify climatic conditions based on 5- and 7-class classifications of climatic conditions. Mixed-effects models and post-hoc test show that ANPP varied significantly among different intensities (e.g. moderate or extreme) and directions (e.g. dry or wet) of climatic conditions, with the highest ANPP in extreme wet and the lowest in extreme dry conditions. Resistance and resilience of ANPP to climatic extremes in different intensities were examined by linear-mixed effects models and we found that species richness increased ecosystem resistance against all dry and wet climatic extremes, but decreased ecosystem resilience towards all dry climatic extremes. Species richness had no effects on ecosystem resilience towards wet climatic extremes. When the five level of species richness treatment (i.e., 1, 2, 4, 8, and 16 species) were considered, the relationships between species richness and resistance and resilience of ANPP under extreme wet and dry conditions remained similar. Our study emphasizes that plant communities with greater species richness need to be maintained to stabilize ecosystem productivity and increase resistance against different climatic extremes.The importance of selecting appropriate air pollution monitoring sites in a city is vital for accurately reporting air quality, enhancing the quality of high-resolution modelling and informing policy to implement measures to deliver cleaner air in the urban environment. COVID-19 restrictions impacted air quality in urban centres worldwide as reduced mobility led to changes in traffic-related air pollution (TRAP). As such, it offered a unique dataset to examine the spatial and temporal variations in air quality between monitoring stations in Dublin, Ireland. Firstly, an analysis of mobility data showed reductions across almost all sectors after COVID-19 restrictions came into place, which was expected to lower TRAP. In addition, similar changes in air quality were evident to other cities around the world reductions in fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations and an increase in ozone (O3) concentrations. Average daily and diurnal concentrations for these three pollutants presented more statistically significant spatial and temporal changes during COVID-19 restrictions at monitoring sites with urban or traffic classifications than suburban background sites. Furthermore, substantial reductions in the range of average hourly pollutant concentrations were observed, 79% for PM2.5 and 75% for NO2, with a modest 24% reduction for O3. Correlation analysis of air pollution between monitoring sites and years demonstrated an improvement in the R2 for NO2 concentrations only, suggesting that spatiotemporal homogeneity was most notable for this TRAP due to mobility restrictions during COVID-19. The spatiotemporal representativeness of monitoring stations across the city will change with greener transport, and air quality during COVID-19 can provide a benchmark to support the introduction of new policies for cleaner air.Piping is an erosive process in which subsurface soil particles are removed, causing the formation of underground tunnels. A variety of physical and chemical factors control pipe formation. This study focused on hydrophysical soil properties to propose a mechanism to explain the piping process in soils in a tropical climate in Brazil. We observed two levels of pipes in the field shallow pipes that form at the transition between E/B horizons (~0.30-0.45 m) and deep pipes that form between different Bt horizons (~1.50 m). We collected disturbed soil samples to determine the soil particle distribution and organic matter content, and undisturbed soil samples were collected to determine the hydrophysical attributes and for soil micromorphometric analysis. We found that the study area was prone to soil collapse and that physical properties controlled the process. The results showed a textural and structural gradient between the E and Bt horizons, where the Bt horizons presented a higher clay content and a well-developed structure (strong sub-angular blocks) compared to the essentially sandy E horizons (single grain). This gradient changed the soil porosity from macroporosity in the E horizon to microporosity in the Bt horizon, particularly represented by the decrease in complex pores. For deeper pipes, soil attribute gradients were found between different Bt horizons. A modification in the structure grade from moderate to weakly moderate, soil water retention curves with different slopes and shapes, and an increase in porosity correlating with soil depth, reflect an increase in larger complex pores. These changes in structure, texture, porosity, and pore type reflect the soil's hydraulic conductivity in the transition of different horizons, which can promote the accumulation and temporary stagnation of water at the top of the Bt horizons, and trigger the piping process when the lateral water flow reaches the critical flow velocity.Tetracycline antibiotics (TCs) introduced into agricultural fields via manure application tend to accumulate in soils and further reach water environments via surface runoff and leachate, posing potential risks to regional water environment. This study investigated the loss of tetracycline (TC), oxytetracycline (OTC), and chlortetracycline (CTC) in surface runoff and leachate samples collected from a vegetable farmland with manure application in Guangzhou, South China. A risk assessment method was constructed for evaluating the ecological and health risks of manure-associated antibiotics released from soil into water environment. The results showed that the concentrations of three TCs in surface runoff, 30-cm leachate, and 60-cm leachate after the first rainfall event were 2.79-35.97, 1.71-18.44, and 0.4-2.66 μg/L, respectively, which all decreased with sampling depth and the time after rainfall events. Up to 0.13% of TCs were transported into the surface water through surface runoff, while less than 0.01% of TCs were transported into the groundwater through leachate at 60 cm. OTC had a higher total mass percentage (0.13%) into surface water via runoff than CTC (0.11%) and TC (0.07%) likely due to its smallest Kd value and largest input mass. Based on loss percentages, their predicted environmental concentrations (PEC) ranged from 4.87 (TC) to 16.91 (OTC) ng/L in regional surface water and 1.42 (TC) to 5.20 (CTC) ng/L in regional groundwater. The risk assessment based on PEC results suggested non-negligible health risk (HQ > 1.0 × 10-6) and low ecological risk (RQ less then 0.1) in both regional surface water and groundwater, drawing concerns on the potential hazards of TCs released from manure-amended soil into water environments.
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