The increasing release of pharmaceutical pollutants, particularly antibiotics and analgesics, into aquatic environments poses a significant environmental challenge and necessitates sustainable removal strategies. In this study, lavender-derived biochar was produced by pyrolysis at 450 and 650 degrees C and subsequently modified with Zn2+ (3 and 5 mmol) via a solvothermal method. The resulting materials were evaluated as photocatalysts for the degradation of doxycycline and paracetamol in distilled water under UV-A irradiation. Structural and optical characterization (SEM-EDS, XRD, PL, FTIR) was conducted to elucidate structure-performance relationships relevant to photocatalytic activity. The sample pyrolyzed at 450 degrees C and modified with 5 mmol Zn2+ exhibited the highest photocatalytic performance, achieving degradation efficiencies of 62.78% for doxycycline (k = 0.0032 min-1) and 75.19% for paracetamol (k = 0.0113 min-1). The results demonstrate that controlled Zn incorporation into lavender-derived biochar enhances photocatalytic performance and highlight the role of synthesis parameters in governing catalytic behavior. This work underscores the potential of agro-waste-derived biochar as a functional matrix in sustainable photocatalytic systems.
Biological invasions, driven by the spread of non-native species, have become a critical global issue because of their far-reaching ecological and socioeconomic impacts. Effective communication of the risks of biological invasions is essential for implementing robust policy and legislation and gaining public support for conservation efforts. However, current policies often suffer from fragmentation and ineffectiveness, largely due to inadequate risk communication and complex multi-level governance. To address this challenge, we develop a global framework designed to enhance clearer communication about biological invasion risks. The framework contextualizes key terms across three domains in invasion science: species invasiveness, risk analysis, and decision support tools. Using both diffusion-of-English and ecology-of-language paradigms, and following a three-step process involving preliminary consensus, AI querying, and ground-truthing with final consensus, we validate the framework in 70 non-English languages which, together with English, have official status in at least one country and collectively cover all 195 countries worldwide. Our findings reveal that while terminology for risk analysis is well established, terminology for species invasiveness and, especially, for decision support tools remains underdeveloped in many languages, hindering effective communication and policy implementation. Our framework underscores the importance of cultural and political neutrality. By promoting clearer risk communication among scientists, policymakers, and the public globally, we aim to reduce policy fragmentation and foster enhanced collaboration in risk mitigation. We recommend expanding multilingual decision support tools to include the full risk analysis process: risk identification, risk assessment, and risk management. This will support intergovernmental mitigation efforts and promote a unified global response to biological invasions.
The M & oslash;lmer-S & oslash;rensen (MS) gate is a two-qubit controlled-phase gate in ion traps that is highly valued due to its ability to preserve the motional state of the ions. However, its fidelity is obstructed by errors affecting the motion of the ions as well as the rotation of the qubits. In this work, we propose an amplitude-modulated composite MS gate, which features high fidelity, robust to gate timing, detuning, and coupling errors and is also tolerant of ac Stark shifts and drifting detuning errors. With the proposed amplitude-modulated composite sequence, we maintain gate infidelities below 10-3 even under simultaneous detuning, timing, and coupling errors as large as 10-15%, outperforming both standard and multitone MS gate implementations. The physical origin of this improvement is due to a separation of the error channels: the amplitude modulation suppresses residual spin-motion displacement (hence reducing sensitivity to detuning and timing imperfections), while the composite phase schedule cancels the dominant over-and under-rotation of the entangling phase produced by coupling miscalibration.
Interaction of processes over land, sea and synoptic conditions resulted in a complex fog event over and along the Nova Scotia coast on 8 September 2021. This study was undertaken to understand how this occurred. A ridge moving eastward along Nova Scotia caused the fog to evolve in a unique three-phase pattern under an air temperature inversion at 150 m height. In the first phase, fog formed over the Nova Scotia coastline due to the slowing of onshore surface winds caused by the increased drag which generated convergence, lifting, and saturation. Weather Research and Forecasting (WRF) simulation of this phase was successful. In the second phase, changed wind direction to from the west over land advected initially land-formed fog over warmer water. In the third phase, surface winds advected a colder fog over warmer sea water which was unstable and facilitated the advance of the fog's leading edge parallel to the Point Nova Scotia coast. WRF simulations of fog cloud development and expansion over water in later stages were relatively poor due to the prescription of the sea surface temperature and not due to the configurations of the physics parameterizations.
High-resolution urban climate downscaling is used to assess city-scale climate risks, yet its key sources of uncertainty remain insufficiently examined. While most studies address emissions and model-driven uncertainties, those from local urbanisation pathways are rarely quantified. As a result, the reliability of urban climate projections used for impact assessment and adaptation remains poorly constrained. This study quantifies the uncertainties in urban climate projections associated with future urbanisation, with a case study of Hanoi, a rapidly urbanising metropolis in Southeast Asia. Urban climate is simulated using the Weather Research and Forecasting model within the pseudo-global warming dynamical downscaling approach under three urban growth scenarios (Status Quo, Objective Prediction, and Master Plan) and two emissions pathways (RCP 8.5 and RCP 4.5). The findings reveal that greenhouse-gas forcing and urban expansion significantly intensify local warming, with projected July temperatures rising by up to 3.8 °C under RCP 8.5 and the Master Plan scenario. Notably, temperature differences among urban scenarios reach 0.5 °C, with locally higher values of up to 1.0 °C in areas experiencing substantial land-use change. This difference is comparable to the spread between the two RCPs of 1.5 °C, highlighting the apparent uncertainty introduced by alternative urban transition pathways. It is worth noting that this urbanisation effect is spatially confined to the city and its immediate surroundings, rather than to the broader impacts of global warming. Together, this study highlights an often-overlooked challenge: the magnitude of urbanisation-related uncertainty, though limited in spatial extent, can be comparable to that associated with emissions scenarios or model spread. The results emphasise the need to explicitly integrate urban development scenarios into climate downscaling. This study contributes both methodological insights and a policy-relevant warning: future urban climate cannot be credibly assessed without accounting for the shape of the cities themselves.
