Notes

Mouse button Periosteal Cellular Tradition, within vitro Differentiation, and in vivo Transplantationin Tibial Fractures.
trogen and phosphorus nutrient salt of sediment is urgently required.Microplastics have been found in many environmental media such as sea water, coastal tidal flats, terrestrial water, sediments, and organisms. Microplastics pollution in inland freshwater lakes have received extensive attention; however, the correlation between eutrophication and microplastics pollution in freshwater lakes remains unclear. selleck compound In this study, 24 sampling sites were set up in the near shore surface waters of Dianchi Lake, and the pollution characteristics of microplastics such as abundance, composition, particle size, color, and form were evaluated. Water quality parameters related to eutrophication state were analyzed, and the eutrophication indices were further calculated. Specifically, sample pre-treatment was conducted according to the method issued by National Oceanic and Atmospheric Administration (NOAA) of the United States. The color and morphological characteristics of microplastic samples were observed using a stereoscopic microscope, and counts and particle size measurements were perform 8.33%, 58.33%, 29.17%, and 4.17% of the total sampling sites, respectively, and the main pollutant was total nitrogen (TN). Microplastics abundances in the near shore waters of Dianchi Lake were significantly positively correlated with TN concentrations (P0.05). The microplastics abundance and TN concentrations in the north bank water near the main urban area of Kunming were significantly higher than those in the other three banks. Microplastics and TN were considered to potentially have the same origin and be attributed to the tail water discharge from WWTPs.Watershed land use patterns combined with hydrological regimes affect riverine nitrogen (N) sources, transformation pathways, and exports, which can affect watershed health and freshwater ecosystem service supply. Understanding how land use and hydrological regimes affect riverine N exports is therefore useful for developing sustainable watershed management strategies. Based on in-situ observations during the period 2010-2017, watershed modeling, geospatial technology, and statistical analysis were coupled in this study to explore the responses of riverine nitrogen exports to watershed land use pattern and hydrological regime in a medium-sized watershed. Results showed that nitrate was the major form of dissolved inorganic N in the Jiulong River watershed; agricultural and urban watersheds had higher N exports and greater temporal variability than those in natural watershed. The seasonal fluctuation for watershed N concentrations and exports was obvious in wet years compared with dry years. Compared with the hydrological regime, the land use pattern had significant effects on N concentrations and exports. This study demonstrated that spatiotemporal variations of riverine nitrogen exports were mainly contributed by the coupled effects of watershed land use pattern and hydrological regime.Biocides are widely added to personal care products and enter the environment through sewage treatment plant (STP) discharge, which affects ecological health. This paper evaluated the pollution characteristics of triclosan and triclocarban in a river network during the COVID-19 epidemic. Moreover, a continuous dynamic river network model coupling a one-dimensional hydrodynamic model and four-level fugacity model was established to address the temporal and spatial heterogeneity of pollutants in the river network migration process; then, this model was applied to evaluate two biocides in the Shima River Basin. The model passed calibration and in-field concentration verification tests and yielded satisfactory simulation results. The results of the study showed that the concentration of biocides in the river network during the new crown epidemic was twice that of the non-epidemic period. The concentration of triclosan and triclocarban in the river channel first increased and then decreased with the increase of the river migration distance after STP discharge. The time variation characteristics of the concentrations were affected by the river flow. The biocide concentration in the river network of the low flow upstream area first increased and then decreased, gradually stabilizing in about 20 h. The pollution concentration in the high flow downstream area was increased, and the concentration did not stabilize at 24 h. These results indicate the necessity of evaluating the temporal and spatial characteristics of migration of typical biocides in the river network by stages and time on the premise of distinguishing the flow.The spread of atmospheric pollutants in the Sichuan Basin is difficult because of its unique topography, static wind, high humidity, and other meteorological conditions. Owing to the acceleration of urbanization and industrialization, PM2.5 pollution in the region is becoming increasingly severe, and the Sichuan Basin has become one of the key areas of national air pollution prevention and control. In this study, based on the remote sensing inversion product of PM2.5 concentration, spatial autocorrelation and gray correlation analyses are used to evaluate the spatial and temporal distribution characteristics and influencing factors of PM2.5 concentration in the Sichuan Basin. The results show that PM2.5 concentration has significant spatial aggregation; the high-high aggregation types are concentrated, low-low aggregation types are more dispersed, and coniferous forest has a significantly higher inhibitory effect on the absorption of PM2.5 than the shrub, grassland, and other vegetation types. The main meteorological factors affecting PM2.5 concentration in the Sichuan Basin are wind speed and temperature; population density and economic scale are the main human-activity factors affecting PM2.5 concentration in the Sichuan Basin, and the change in the industrial structure and scale also has a certain influence on the PM2.5 concentration.To investigate the pollution characteristics and sources of atmospheric brown carbon (BrC) in Chongming Island, a background site of the Yangtze River Delta (YRD) region in China, PM2.5 samples collected from December 2018 to January 2019 were analyzed to determine their chemical compositions and optical properties. The results showed that the light absorption coefficient (Abs365,M) of BrC extracted by methanol at 365 nm was (5.39±3.33) M-1·m-1, which was 1.3 times of the water extracted BrC. Both increased significantly with the increase of pH values, suggesting that less acidic conditions can enhance the light absorption ability of BrC. In winter, both Abs365 and MAE365 (mass absorption efficiency) were higher in the nighttime than in the daytime. A strong linear correlation observed between Abs365 and levoglucosan (R2=0.72) indicated that many light absorbing substances in Chongming Island were derived from biomass burning emissions. During the campaign, nitro-aromatic compounds (NACs) and PAHs accounted for (1.5±1.1) ng·m-3 and (8.3±4.7) ng·m-3, respectively, contributing to 0.1% and 0.067% of the absorption of the total BrC at 365 nm, respectively. Positive matrix factorization (PMF) analysis further showed that biomass and fossil fuel combustions were the main sources of BrC in Chongming Island in winter, accounting for 56% of the total BrC, followed by secondary formation, accounting for 24% of the total BrC, with road dust contributing only 6%.Ozone pollution has recently become a severe air quality issue in the Beijing-Tianjin-Hebei region. Due to the lack of a precursor emission inventory and complexity of physical and chemical mechanism of ozone generation, numerical modeling still exhibits significant deviations in ozone forecasting. Owing to its simplicity and low calculation costs, the time series analysis model can be effectively applied for ozone pollution forecasting. We conducted a time series analysis of ozone concentration at Shangdianzi, Baoding, and Tianjin sites. Both seasonal and dynamic ARIMA models were established to perform mid- and long-term ozone forecasting. The correlation coefficient R between the predicted and observed value can reach 0.951, and the RMSE is only 10.2 μg·m-3 for the monthly average ozone prediction by the seasonal ARIMA model. The correlation coefficient R between the predicted and observed value increased from 0.296-0.455 to 0.670-0.748, and RMSE was effectively reduced for the 8-hour ozone average predicted by the dynamic ARIMA model.Spatial features of PM2.5 concentration in the Yangtze River Delta in 2016 were analyzed using remote sensing data. Selecting factors among meteorology, topography, vegetation, and emission list of air pollutants, factors and their interaction effects on the spatial distribution of PM2.5 concentration were studied based on GAM, with an evaluation unit of 0.25°×0.25° for the grid. It showed that① With a more significant difference between the north and south, PM2.5 concentration was generally higher in the north and west but lower in the south and east. In the southern part of the delta, the concentration was mostly lower than 35 μg·m-3, with noncompliance of the PM2.5 concentration scattered in urban areas like islands. Meanwhile, PM2.5 concentration is generally over 35 μg·m-3, and the pollution appeared like sheets. ② Besides, PM2.5 concentration showed an apparent positive spatial autocorrelation with "High-High" PM2.5 agglomeration areas in the north of the delta and "Low-Low" PM2.5 agglomeration areas in the south. ③ Based on GAM, hypsography, temperature, and precipitation negatively affected PM2.5 concentration, whereas pollutant emissions positively affected it. The effect of wind was minor when its speed less then 2.5 m·s-1, and more negatively significant when its speed ≥ 2.5 m·s-1. Hypsography, temperature, and precipitation were higher in the southern part of the delta, but they were lower in the northern part, leading to a higher PM2.5 concentration in the northern parts and lower in the southern parts. A higher wind speed in the east and lower in the west also led to a concentration difference between them. ④ All factors had passed a significant pair interaction test, except for hypsography and PM2.5 emission, and they all showed a significant interaction effect on the distribution of PM2.5 in the Yangtze River Delta.This study analyzed the impacts of meteorological conditions and changes in air pollutant emissions on PM2.5 across the country during the first quarter of 2020 based on the WRF-CMAQ model. Results showed that the variations in meteorological conditions led to a national PM2.5 concentration decreased of 1.7% from 2020-01 to 2020-03, whereas it increased by 1.6% in January and decreased by 1.3% and 7.9% in February and March, respectively. The reduction of pollutants emissions led to a decrease of 14.1% in national PM2.5 concentration during the first quarter of 2020 and a decrease of 4.0%, 25.7%, and 15.0% in January, February, and March, respectively. Compared to the same period last year, the PM2.5 concentration measured in Wuhan City decreased more than in the entire country. This was caused by improved meteorological conditions and a higher reduction of pollutant emissions in Wuhan City. PM2.5 in Beijing increased annually before the epidemic outbreak and during the strict control period, mainly due to unfavorable meteorological conditions.
Website: https://www.selleckchem.com/products/autophinib.html