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Aerosols affect Earth's climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard Aerosol Robotic Network (AERONET) aerosol products have been widely used for more than 30 years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. to extended datasets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatiotemporal variations of the obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon, and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), products in several regions of interest (Amazon zone, Indo-China Peninsula, North India, southern Africa, sub-Sahel, Gobi Desert, Middle East, Sahara Desert, and Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products (R = 0.60-0.85 for BC; R = 0.75-0.90 for dust). The new value-added and long-term aerosol composition product globally is available online (https://doi.org/10.6084/ m9.figshare.25415239.v1), which provides important measurements for the improvement and optimization of aerosol modeling to enhance estimation of the aerosol radiative forcing. SIGNIFICANCE STATEMENT: In the assessment of climate change, the uncertainty associated with aerosol radiative forcing is the largest one. The purpose of this study is to provide a new value-added and long-term aerosol composition (including absorbing and scattering aerosol species) inversion dataset derived from Aerosol Robotic Network (AERONET) measurements for characterizing their spatiotemporal variations at global scale. We find some new insights on the quantitative assessment of black carbon and dust column concentration products in the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Our results and aerosol composition inversion dataset will provide robust support for the overall improvement and optimization of aerosol modeling to better understand the aerosol radiative forcing. KEYWORDS: Algorithms; Remote sensing; Aerosol optical properties; Air pollution; Atmospheric composition, 1. Introduction Atmospheric aerosols are considered to be an important climate forcing factor that plays a key role in the global climate system (Charlson et al. 1992; IPCC 2021). For [...]

Magnetism in two-dimensional (2D) materials has attracted much attention recently. However, intrinsic magnetic 2D materials are rare and mostly unstable in ambient. Although heteroatom doping can introduce magnetism, the basic property especially the electrical-magnetic coupling property has been rarely revealed. Herein, both iron (Fe)-doped and vanadium (V)-doped MoS2 films were grown by chemical vapor deposition. Through studying the structure and electrical property of Fe-doped and V-doped MoS2, it was found that both Fe and V doping would decrease the electron concentration, exhibiting a p-type doping effect. Significantly, V-doped MoS2 displays a p-type conduction behavior. Although the carrier mobility decreases after heteroatom doping, both Fe and V doping could endow MoS2 with magnetism, in which the transfer curves of both MoS2 transistors exhibit a strong magnetic-dependent behavior. It is found that the magnetic response of Fe-doped MoS2 can be tuned from ~0.2 ​nA/T to ~1.3 ​nA/T, with the tunability much larger than that of V-doped MoS2. At last, the magnetic mechanism is discussed with the local magnetic property performed by magnetic force microscopy. The typical morphology-independent magnetic signal demonstrates the formed magnetic domain structure in Fe-doped MoS2. This study opens new potential to design novel magnetic-electrical devices.

The biases generated by state-of-the-art climate models in simulating dust optical depth (DOD) remain to be detailed. Here, a site-scale DOD dataset in March–August over northern China (NC) during 1980–2001 was reconstructed using the empirical relationship between MODIS-retrieved DOD and dust-event frequencies during 2001–21. Then, through the combined use of MODIS-based and reconstructed DOD, we evaluated the reproducibility of DOD from 10 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the historical period (1980–2001 and 2002–14) and under different Shared Socioeconomic Pathways (SSPs) during 2015–21. The results demonstrate that CMIP6 models and multimodel ensemble mean (MEM) are capable of capturing the spatial pattern of DOD, but with considerable uncertainty and intermodel variability in magnitude. Regionally averaged DOD is underestimated by 56.09% during 1980–2001 and overestimated by 30.97% during 2002–14 in MEM over NC. Simultaneously, the intermodel standard deviations are greater than MEM during 2002–14, suggesting large discrepancies among individual models. Very few models accurately capture the trends in DOD, which can mainly be attributed to the different trends in simulated wind speed (WS), soil moisture, and vegetation cover, and their contributions to dust evolution. Under four SSPs, despite the best correlation between SSP1-2.6-modeled and MODIS DOD over Gobi Desert (GD), overestimation of DOD is still observed. More models under SSP1-2.6 capture the positive DOD trend, mainly attributable to positive changes in simulated WS over GD. [ABSTRACT FROM AUTHOR]

Negative Air Ions (NAIs), essential for environmental and human health, facilitate air purification and offer antimicrobial benefits. Our study achieves hourly estimations of NAIs using a machine learning framework, developed from a multi‐layer selection pipeline of over 200 variables, to identify the key determinants critical for adapting to high‐resolution NAIs dynamics. Addressing site sparsity and NAIs volatility, we introduced a hybrid stacking incorporating pseudo sites generated from Kriging Spatiotemporal Augmentation (KSTA) to mitigate spatial overfitting. Our approach, validated in Zhejiang, China, demonstrates exceptional accuracy, achieving R2 values of 0.90 (sample‐based), 0.85 (temporal‐based), and 0.79 (site‐based). This work not only sheds light on NAIs behavior in relation to diurnal shifts, land use, and environmental events, but also integrates a health grading system, enhancing public health strategies through precise air quality assessment. Plain Language Summary: Our study advances the environmental science by developing a machine‐learning model capable of estimation the hourly concentrations of negative air ions (NAIs) across Zhejiang Province, China. NAIs, vital for air purification and human health, are significantly related to environmental conditions. Taking advantage of a novel approach that reduces errors commonly seen in similar models, we provide a highly accurate, hour‐by‐hour analysis of air quality. Our research goes beyond mere prediction; it investigates how various factors like vegetation, soil type, and weather events influence NAI levels. The insights gained offer a comprehensive view of how NAI distribution changes over time and across different landscapes, informing environmental policy and public health strategies with precise air quality assessments. This study contributes significantly to the field by introducing an essential tool for continuous environmental monitoring, thereby facilitating more effective decision‐making in environmental and public health sectors. Key Points: A hybrid stacking machine learning framework shows superior accuracy (R2 = 0.90), combing a filter pipeline dealing with more than 200 variablesKriging Spatiotemporal Augmentation (KSTA) as a pseudo‐label strategy to resolve spatial overfitting due to sparse sitesAn hourly estimate of NAIs reveals NAIs dynamics correlations with environmental factors and land use, supporting public health policy [ABSTRACT FROM AUTHOR]

ABSTRACT Purpose: The rat cervicitis model was established with 20% phenol glue to explore the therapeutic effect of Kangfuxiaomi shuan II on rat cervicitis and its mechanism. Methods: After modeling, the rats were treated with Shuangzuotai suppository (37.84 mg/kg), Kangfuxiaoyan shuan (205.6 mg/kg) and Kangfuxiaomi shuan II (40, 80, 160 mg/kg). The histopathological changes and injury degree of cervix in rats were evaluated by vulvar inflammation score and organ index. The therapeutic effect of Kangfuxiaomi shuan II on cervicitis was evaluated by detecting the levels of copper-protein (CP), C-reactive protein (CRP), Rat interleukin 6 (IL-6), superoxide dismutase (SOD) and malondialdehyde (MDA) in serum and epidermal growth factor (EGF), cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS) in cervical tissue. Results: Compared with the model group, the vulvar inflammation score and cervical index of rats in other groups decreased significantly (P

Winter construction in seasonally frozen soil areas is inevitable. The variation of ambient temperature causes the freeze-thaw of the filling soils and its impact is significant, and whether the countermeasures can be effectively established and adopted is particularly important for the management and control of the construction quality of the project. This paper conducts systematic research based on the winter construction process of the dam core wall of the Lianghekou Hydropower Station, which is the third highest earth-core rockfill dam in the world under construction. The results show that for the construction site in the seasonally frozen soil area, there is a development process of the short-term frozen soils for the filling soils under the environment with low temperature in winter. The soil underwent a high-frequency freeze-thaw process wherein it was frozen at night and completely thawed during the day. During the freezing process, a large number of thin-layered segregated ice developed inside the soil to form a thin-layered or integral cryostructure, which will have an adverse effect on the engineering properties and the quality of the filling soils. And, the field tests demonstrate that the filling compaction degree of the frozen soils is difficult to meet the designed requirements. In order to effectively cope with the adverse effect of the freeze-thaw on the construction quality during the construction process, based on the analysis of the freeze-thaw characteristics of soils and its influence, and the energy exchange process of soils on-site, the principles and methods for establishing the freeze prevention system during the winter construction process are established, and a comprehensive monitoring system suitable for on-site is established in this paper. This research will provide an important reference for the scientific management and efficiency improvement of the winter construction process of the dams in cold regions.