Spatial-temporal evolution characteristics of PM2.5 and its driving mechanism: spatially explicit insights from Shanxi Province, China.

In China, despite the fact that the atmospheric environment quality has continued to improve in recent years, the PM2.5 pollution still had not been controlled fundamentally and its driving mechanism was complex which remained to be explored. Based on the 1-km ground-level PM2.5 datasets of China from 2000 to 2020, this study combined spatial autocorrelation, trend analysis, geographical detector, and multi-scale geographically weighted regression (MGWR) model to explore the spatial-temporal evolution of PM2.5 in Shanxi Province and revealed its complex driving mechanism behind this process. The results reflected that (1) there was a pronounced spatial clustering of PM2.5 concentration within Shanxi Province, with PM2.5 concentrations decreasing from southwest to northeast. From 2000 to 2020, the levels of PM2.5 pollution demonstrated a decline over time, with its concentrations decreasing by 9.15 µg/m3 overall. The Hurst exponent indicated a projected decrease in PM2.5 concentrations in the central and northern areas of Shanxi Province, contrasting with an anticipated increase in other regions. (2) The geographical detector indicated that all drivers had significant influences on PM2.5 concentrations, with meteorological factors exerting the greatest effects then followed by human activity and vegetation cover showing the least effects. (3) Both gross domestic product and population density exhibited positive correlations with PM2.5 concentration, while vegetation fractional cover, wind speed, precipitation, and elevation exerted negative influences on PM2.5 concentration all over the space. This study enriched the research content and ideas on the driving mechanism of PM2.5 and provided a reference for similar studies.

Modeling the spatially heterogeneous relationships between tradeoffs and synergies among ecosystem services and potential drivers considering geographic scale in Bairin Left Banner, China.

Understanding the complex relationships of tradeoffs and synergies among ecosystem services (ESs) is essential to achieve a comprehensive, coordinated, and sustainable development for human well-being. However, the quantitative measurement for the properties and intensities within these relationships as well as the deeper exploration of its formation mechanism from a spatial-explicit perspective is still a challenge. In this study, a comprehensive and general methodology was developed to quantitatively illustrate the intensities of tradeoffs/synergies among pairwise ESs and explore the spatially heterogeneous relationships between these relations and several socio-ecological drivers, integrating InVEST, geographical detector and multi-scale geographically weighted regression (MGWR) methods. The results indicated that (1) the properties and intensities of tradeoffs/synergies among various ESs varied greatly over space and presented significant clustered distribution patterns; (2) different relations between ESs were dominated by diverse drivers and the combined effects from multiple factors were stronger than any single one within this process. The tradeoffs/synergies between soil conservation and other ESs were mainly affected by geomorphological drivers including elevation and slope, while relations involved habitat quality could be attributed to vegetation and climate drivers such as precipitation and vegetation fractional cover. The relationships among ESs were more susceptible to topographic and anthropogenic drivers when concerning the carbon storage service; (3) compared to global ordinary least squares and local geographically weighted regression (GWR), the MGWR obtained better performance in explaining relationships between tradeoffs/synergies among ESs and potential drivers by operating different spatial scales. Accordingly, several spatially targeted ecological measures were proposed and recommended to reduce ESs tradeoffs and ultimately achieve better synergies. This research could enrich the methods in revealing the complex evolvement mechanism behind the tradeoffs/synergies among ESs and the proposed framework also provided a new perspective in the field of ESs tradeoffs/synergies studies and might be valuable guidance for other regions worldwide.

Preparation and Antifouling Property of Polyurethane Film Modified by PHMG and HA Using Layer-by-Layer Assembly.

To reduce the possibility of bacterial infection and implant-related complications, surface modification on polyurethane (PU) film is an ideal solution to endow hydrophobic PU with antibacterial and antifouling properties. In this work, a variety of polyhexamethylene guanidine/ hyaluronic acid (PHMG/HA) multilayer films were self-assembled layer-by-layer on PU films using polyanions, carboxyl-activated HA, and polycations PHMG by controlling the concentration of these polyelectrolytes as well as the number of layers self-assembled. Attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) spectra, water contact angle (WCA), and A Atomic force microscope (AFM) of PU and modified PU films were studied. Protein adsorption and bacterial adhesion as well as the cytotoxicity against L929 of the film on selected PU-(PHMG/HA)5/5-5 were estimated. The results showed that PU-(PHMG/HA)5/5-5 had the best hydrophilicity among all the prepared films, possessing the lowest level of protein adsorption. Meanwhile, this film showed efficient broad-spectrum antibacterial performance as well as significant resistance of bacterial adhesion of more than a 99.9% drop for the selected bacteria. Moreover, almost no influence on cell viability of L929 enhanced the biocompatibility of film. Therefore, the modified PU films with admirable protein absorption resistance, antimicrobial performance, and biocompatibility would have promising applications in biomedical aspect.

Ecological quality and its relationships with human activities in China-Laos railway economic belt.

Regional ecological quality is largely affected by human activities, which restricts the sustainable development of regional economy. Taking the China-Laos railway economic belt as an example, we investigated the effects of human activities on ecological quality. The remote sensing images of 1999, 2009 and 2019 were selected to calculate remote sensing ecological index (RSEI). Spatial autocorrelation statistics and local G statistics were used to explore the spatial-temporal variations of ecological quality in the study area. Combined with the population density in the same period, a geographically weighted regression model was constructed to quantitatively analyze the ecological effects of different human activity intensities in the study area. The results showed that the ecological quality in the study area presented a trend of increasing firstly and then decreasing later from 1999 to 2019, and that the mean value of RSEI varied from 0.645 (1999) to 0.738 (2009) and then decreasing to 0.721 in 2019. Specially, the ecological quality fluctuated more apparently in the midlands. The results of fitting population density and ecological quality based on geographical weighted regression model (GWR) were significantly better than that of least square method. R2 of different periods based on GWR was higher than 0.7 and the fitting effect was stable. The fitting degree of GWR in 2019 was the best (R2 was 0.785), and R2 in 1999 and 2009 were 0.726 and 0.754, respectively. The ecological quality along the China-Laos railway south area (such as Vientiane) was more sensitive to human activities, with most of these places belonged to moderately sensitive regions. For the highly, moderately and lowly ecological sensitive regions, every 10, 100, 1000-fold increases in population density would lead to a decrease of 0.2, 0.4 and 0.6 to the mean value of RSEI in turn. The development of economic belt would increase population density. During the planning and layout of economic belt, human activities should be controlled to avoid the deterioration of ecological quality in the potential and current sensitive regions.

Synthesis of Al3+-doping-TiO2 monodisperse microspheres and their application for phosphopeptides and glycopeptides enrichment.

Glycosylation and phosphorylation are two of the most common and important post-translational modifications (PTMs) of proteins, which play critical roles in regulating a variety of complex biological processes and involvement in many diseases. Due to the low abundance of phosphopeptides and glycopeptides, highly selective enrichment methods are crucial to the identification of protein phosphorylation and glycosylation by mass spectrometry (MS). Here, monodisperse uniform Al3+-doping-TiO2 mixed oxide microspheres were easily synthesized. The morphology was controlled by a sol-gel method, during the hydrothermal treatment. The obtained microspheres with uniform particle size distribution (about 1-2 µm)，high surface area and improved pore structures, were characterized by SEM, TEM, XRD and N2 adsorption-desorption isotherms. Al3+-doping-TiO2 was applied in enriching glycopeptides and phosphopeptides respectively or simultaneously by using different enrichment conditions, achieving selective enrichment of glycopeptides and phosphopeptides. 20 glycopeptides and 25 phosphopeptides enriched from the tryptic digest mixtures of human serum immunoglobulin G (IgG) and α-casein (molar ratio of 1:1) were obviously observed with greatly improved signal-to-noise (S/N) ratio. Meanwhile, the enrichment results of non-fat milk and human serum also show the enrichment selectivity from complex biological samples. This study will provide a novel insight for selective enrichment of glycopeptides and phosphopeptides in post-translational modification proteomics research.

[Investigation on the Emission Difference of Air Pollutants from Common Residential Coal Stoves and Suggestions for Emission Reduction].

To explore the difference in the emission of air pollutants from coal stoves, five new and common residential coal stoves (square briquette, baffled heat exchange, heating and cooking integrated gasification positive burning, and gasification reverse burning stove) were selected. The emission level of major air pollutants was determined using simulated combustion in the laboratory for quantitatively evaluating the environmental effects of different coal stoves. Moreover, the factors and reasons for the differences were identified, and suggestions for the reduction of emission were proposed. The results showed that: ① the emissions of air pollutants from different coal stoves were significantly different; the heating and cooking integrated stove had the largest emission intensity (2.9 kg ·t-1) of air pollutants (SO2, NOx, and TSP), which was 1.6 times of the average value, and the square briquette stove had the lowest emission level, which was 65% of the average value. ② The emissions of gaseous pollutants from the coal stoves in different combustion stages also showed evident differences. In the high-fire stage, the NOx emission concentration of the square briquette stove was 0.49 mg ·m-3, which was 45%-72% lower than that of the other stoves; the SO2 emission concentration of the gasification reverse burning stove was 1.38 mg ·m-3, which was 28% lower than that of the other stoves. ③ The application technology and combustion type were the main factors affecting the emission levels of the coal stoves. The stove with square briquette technology and gasification reverse burning technology could have great environmental benefit. However, the cost of the two stoves was 20 and 18 thousand yuan, respectively, which was clearly higher than that of the other types of stoves. ④ Considering the difference in the emission of air pollutants from the different stoves, it was suggested to adopt differentiated economic policy and strict emission and product standards, promoting the use of energy-saving and environment-friendly coal stoves to reduce the emission of air pollutants from coal-fired stoves.