Synthetic musks in the natural environment: Sources, occurrence, concentration, and fate-A review of recent developments (2010-2023).

Synthetic musks (SMs) have served as cost-effective substitutes for natural musk compounds in personal care and daily chemical products for decades. Their widespread use has led to their detection in various environmental matrices, raising concerns about potential risks. Despite numerous studies on SM levels in different natural environments, a systematic review of their contemporary presence is lacking. This review aims to address this gap by summarising recent research developments on SMs in diverse natural environments, including river water, lake water, seawater, estuarine water, groundwater, snow, meltwater, sediments, aquatic suspended matter, soils, sands, outdoor air, and atmospheric particulate matter. Covering the period from 2010 to 2023, the review focuses on four SM categories: nitro, polycyclic, macrocyclic, and alicyclic. It systematically examines their sources, occurrences, concentrations, spatial and temporal variations, and fate. The literature reveals widespread detection of SMs in the natural environment (freshwater and sediments in particular), with polycyclic musks being the most studied group. Both direct (e.g., wastewater discharges) and indirect (e.g., human recreational activities) sources contribute to SM presence. Levels of SMs vary greatly among studies with higher levels observed in certain regions, such as sediments in Southeast Asia. Spatial and temporal variations are also evident. The fate of SMs in the environment depends on their physicochemical properties and environmental processes, including bioaccumulation, biodegradation, photodegradation, adsorption, phase exchange, hydro-dilution effects. Biodegradation and photodegradation can decrease SM levels, but may produce more persistent and eco-toxic products. Modelling approaches have been employed to analyse SM fate, especially for indirect processes like photodegradation or long-distance atmospheric transport. Future studies should further investigate the complex fate if SMs and their environmental influence. This review enhances understanding of SM status in the natural environment and supports efforts to control environmental contamination.

Unravelling the variations of the society of England and Wales through diffusion mapping analysis of census 2011.

We propose a new approach to identify geographical clustering and inequality hotspots from decadal census data, with a particular emphasis on the method itself. Our method uses diffusion mapping to study the 181 408 output areas in England and Wales (EW), which enables us to decompose the census data's EW-specific feature structures. We further introduce a localization metric, inspired by statistical physics, to reveal the significance of minority groups in London. Our findings can be adapted to analogous datasets, illuminating spatial patterns and differentiating within datasets, especially when meaning factors for determining the datasets' structure are scarce and spatially heterogeneous. This approach enhances our ability to describe and explore patterns of social deprivation and segregation across the country, thereby contributing to the development of targeted policies. We also underscore the method's intrinsic objectivity, guaranteeing its ability to offer comprehensive and unbiased analysis, unswayed by preconceived hypotheses or subjective interpretations of data patterns.

Understanding the spatial heterogeneity of COVID-19 vaccination uptake in England.

BACKGROUND: Mass vaccination has been a key strategy in effectively containing global COVID-19 pandemic that posed unprecedented social and economic challenges to many countries. However, vaccination rates vary across space and socio-economic factors, and are likely to depend on the accessibility to vaccination services, which is under-researched in literature. This study aims to empirically identify the spatially heterogeneous relationship between COVID-19 vaccination rates and socio-economic factors in England. METHODS: We investigated the percentage of over-18 fully vaccinated people at the small-area level across England up to 18 November 2021. We used multiscale geographically weighted regression (MGWR) to model the spatially heterogeneous relationship between vaccination rates and socio-economic determinants, including ethnic, age, economic, and accessibility factors. RESULTS: This study indicates that the selected MGWR model can explain 83.2% of the total variance of vaccination rates. The variables exhibiting a positive association with vaccination rates in most areas include proportion of population over 40, car ownership, average household income, and spatial accessibility to vaccination. In contrast, population under 40, less deprived population, and black or mixed ethnicity are negatively associated with the vaccination rates. CONCLUSIONS: Our findings indicate the importance of improving the spatial accessibility to vaccinations in developing regions and among specific population groups in order to promote COVID-19 vaccination.

Sensing dynamic human activity zones using geo-tagged big data in Greater London, UK during the COVID-19 pandemic.

Exploration of dynamic human activity gives significant insights into understanding the urban environment and can help to reinforce scientific urban management strategies. Lots of studies are arising regarding the significant human activity changes in global metropolises and regions affected by COVID-19 containment policies. However, the variations of human activity dynamics amid different phases divided by the non-pharmaceutical intervention policies (e.g., stay-at-home, lockdown) have not been investigated across urban areas in space and time and discussed with the urban characteristic determinants. In this study, we aim to explore the influence of different restriction phases on dynamic human activity through sensing human activity zones (HAZs) and their dominated urban characteristics. Herein, we proposed an explainable analysis framework to explore the HAZ variations consisting of three parts, i.e., footfall detection, HAZs delineation and the identification of relationships between urban characteristics and HAZs. In our study area of Greater London, United Kingdom, we first utilised the footfall detection method to extract human activity metrics (footfalls) counted by visits/stays at space and time from the anonymous mobile phone GPS trajectories. Then, we characterised HAZs based on the homogeneity of daily human footfalls at census output areas (OAs) during the predefined restriction phases in the UK. Lastly, we examined the feature importance of explanatory variables as the metric of the relationship between human activity and urban characteristics using machine learning classifiers. The results show that dynamic human activity exhibits statistically significant differences in terms of the HAZ distributions across restriction phases and is strongly associated with urban characteristics (e.g., specific land use types) during the COVID-19 pandemic. These findings can improve the understanding of the variation of human activity patterns during the pandemic and offer insights into city management resource allocation in urban areas concerning dynamic human activity.

Metal-driven hierarchical self-assembled zigzag nanoarchitectures with electrical conductivity.

Quasi-one-dimensional electroactive materials with zigzag shape are fabricated by supramolecular self-assembly of a tetrathiafulvalene (TTF) derivative and metal ions under mild conditions. This is the first time that self-assembled organic conductors with zigzag shape are reported.

Controllable synthesis of water-soluble gold nanoparticles and their applications in electrocatalysis and surface-enhanced Raman scattering.

We report a facile method to synthesize water-soluble gold nanoparticles (AuNPs) using a biosurfactant sodium cholate as reducing reagents and protective groups in aqueous solution at ambient temperature. The diameters (13-70 nm) of uniform AuNPs can be readily adjusted by changing the initial molar ratio of sodium cholate to chloroauric acid (HAuCl(4)). Also, the alkaline condition of preparative solution is found to affect the size of as-synthesized AuNPs. This synthetic approach is one-step and "green". The obtained AuNPs exhibit a good electrocatalytic activity toward methanol oxidation. Meanwhile, the AuNPs thin films can serve as an efficient substrate for surface-enhanced Raman scattering (SERS). Furthermore, platinum nanoparticles (PtNPs) are also prepared by reducing sodium tetrachloro platinate hydrate with sodium cholate.

Unique temperature-dependent supramolecular self-assembly: from hierarchical 1D nanostructures to super hydrogel.

Supramolecular self-assembly can not only lead to a better understanding of biological systems, but also can enable rational building of complex and functional materials. In this report, hierarchical one-dimensional (1D) architectures involving nanotubes, coiled-coil ropelike structures, nanohelices, and nanoribbons are created via lanthanum-cholate supramolecular self-assembly. These sophisticated self-assemblies are proven to be mediated by temperature. The entanglement of one-dimensional nanostructures is demonstrated to give rise to fascinating "super" hydrogel, which can realize water gelation at extremely low concentration. Unprecedented water gelation behaviors, that is, heating-enhanced stiffness and heating-promoted gelation, are found in lanthanum-cholate supramolecular hydrogel. The driving forces of self-assembled complex nanostructures and the unique role of temperature are also discussed.