Using variances in hydrocarbon concentration and carbon stable isotope to determine the important influence of irrigated water on petroleum accumulation in surface soil

Hunpu is a wastewater-irrigated area southwest of Shenyang. To evaluate petroleum contamination and identify its sources at the area, the aliphatic hydrocarbons and compound-specific carbon stable isotopes of n-alkanes in the soil, irrigation water, and atmospheric deposition were analyzed. The analyses of hydrocarbon concentrations and geochemical characteristics reveal that the water is moderately contaminated by degraded heavy oil. According to the isotope analysis, inputs of modern C3 plants and degraded petroleum are present in the water, air, and soil. The similarities and dissimilarities among the water, air, and soil samples were determined by concentration, isotope, and multivariate statistical analyses. Hydrocarbons from various sources, as well as the water/atmospheric deposition samples, are more effectively differentiated through principal component analysis of carbon stable isotope ratios (δ¹³C) relative to hydrocarbon concentrations. Redundancy analysis indicates that 57.1 % of the variance in the δ¹³C of the soil can be explained by the δ¹³C of both the water and air, and 35.5 % of the variance in the hydrocarbon concentrations of the soil can be explained by hydrocarbon concentrations of both the water and the air. The δ¹³C in the atmospheric deposition accounts for 28.2 % of the δ¹³C variance in the soil, which is considerably higher than the variance in hydrocarbon concentrations of the soil explained by hydrocarbon concentrations of the atmospheric deposition (7.7 %). In contrast to δ¹³C analysis, the analysis of hydrocarbon concentrations underestimates the effect of petroleum contamination in the irrigated water and air on the surface soil. Overall, the irrigated water exerts a larger effect on the surface soil than does the atmospheric deposition.     

Adsorption of Cu2+ and methyl orange from aqueous solutions by activated carbons of corncob-derived char wastes

Corncob-derived char wastes (CCW) obtained from biomass conversion to syngas production through corncob steam gasification, which were often discarded, were utilized for preparation of activated carbon by calcination, and KOH and HNO₃ activation treatments, on the view of environment protection and waste recycling. Their adsorption performance in the removal of heavy metal ions and dye molecules from wastewater was evaluated by using Cu²⁺ and methyl orange (MO) as the model pollutant. The surface and structure characteristics of the CCW-based activated carbons (CACs) were investigated by N₂ adsorption, CO₂ adsorption, FT-IR, and He-TPD. The adsorption capacity varied with the activation methods of CACs and different initial solution concentrations, indicating that the adsorption behavior was influenced by not only the surface area and porosity but also the oxygen functional groups on the surface of the CACs. The equilibrium adsorption data were analyzed with the Langmuir, Freundlich, and Temkin isotherm models, and the adsorption kinetics was evaluated by the pseudo-first-order and pseudo-second-order models.     

咪唑啉硫酸酯盐的缓蚀性能及协同增效作用研究

参照SY/T 5405-1996《酸化用缓蚀剂性能试验方法及评价指标》,采用静态失重法评价咪唑啉硫酸酯盐缓蚀剂1-羟乙基-2-油酸基咪唑啉硫酸酯盐(ISES)与丙炔醇(BCC)、非离子表面活性剂OP-10组成的二元和三元复配缓蚀剂体系对N80钢的缓蚀性能,考察二元和三元复配缓蚀剂体系的协同增效作用。通过动电位极化扫描和电化学阻抗分析对ISES及其复配体系的电化学行为进行研究。     

Seasonal variations of CH(4) and N(2)O emissions in response to water management of paddy fields located in Southeast China

Water management is one of the most important practices that affect methane (CH₄) and nitrous oxide (N₂O) emissions from paddy fields. A field experiment was designed to study the effects of controlled irrigation (CI) on CH₄ and N₂O emissions from paddy fields, with traditional irrigation (TI) as the control. The effects of CI on CH₄ and N₂O emissions from paddy fields were very clear. The peaks of CH₄ emissions from the CI paddies were observed 1-2 d after the water layer disappeared. Afterward, the emissions reduced rapidly and remained low until the soil was re-flooded. A slight increase of CH₄ emission was observed in a short period after re-flooding. N₂O emissions peaks from CI paddies were all observed 8-10 d after the fertilization at the WFPS ranging from 78.1% to 85.3%. Soil drying caused substantial N₂O emissions, whereas no substantial N₂O emissions were observed when the soil was re-wetted after the dry phase. Compared with TI, the cumulative CH₄ emissions from the CI fields were reduced by 81.8% on the average, whereas the cumulative N₂O emissions were increased by 135.4% on the average. The integrative global warming potential of CH₄ and N₂O on a 100-year horizon decreased by 27.3% in the CI paddy fields, whereas no significant difference in the rice yield was observed between the CI and TI fields. These results suggest that CI can effectively mitigate the integrative greenhouse effect caused by CH₄ and N₂O emissions from paddy fields while ensuring the rice yield.     

氟化物对酸浸取沸腾炉渣中铝的影响

采用酸浸取法、加入助溶剂浸取沸腾炉渣中的铝,考察了各种因素对铝浸出率的影响。实验结果表明：在球磨时间为30min、固液比（沸腾炉渣质量与酸体积之比）为1：7、硫酸浓度为4mol／L、浸取温度为107℃、浸取时间为120min的条件下,铝浸出率最高（为29．72％）;KF,NH4F,NaF,CaF2等作助溶剂可明显提高铝浸出率,且助溶剂为CaF：时的铝浸出率最高,CaF2与沸腾炉渣的质量比为0．08时的铝浸出率大于75％。     

Efficient photoreduction of carbon dioxide into carbon-based fuels: a review

Environmental Chemistry Letters - The photocatalytic transformation of carbon dioxide into fuels is viewed as a promising solution to lessen global warming and to enter a circular economy, yet this...     

强电磁脉冲环境下计算机设备的防护

探讨了强电磁脉冲对计算机设备的损伤机理和破坏作用,介绍了国内外在强电磁脉冲防护领域的研究发展状况,对计算机脉冲防护技术和措施做了详尽的介绍.结合国内外研究现状和发展趋势,建议加强相关领域的研究,并指出今后的研究方向,以提高强电磁脉冲环境下计算机设备的生存能力.     

溴代甲烷在253.7nm条件下的光氧化机理及其对臭氧光解损耗影响的动力学

本文研究了在２５３．７ｎｍ的紫外光照条件下,ＣＨ３Ｂｒ,ＣＨ２Ｂｒ２以及ＣＨ３Ｂｒ＋Ｏ２／Ｏ３物ＣＨ２Ｂｒ３＋Ｏ２／Ｏ３等体系的光化学反应过程,通过ＦＴＩＲ以及ＵＶ－Ｖｉｓ对产物进行了分析。并提出反应机理予以解释。     

Vegetation dynamics during different abandoned year spans in the land of the Loess Plateau of China

In this semi-arid area, many studies focused on the two-phase vegetation pattern were carried out to explore a changing vegetation trajectory on degraded land. However, this study conducted an analysis of a two-phase vegetation pattern and explored the successional vegetation trajectories in a positive succession without disturbance. In this work, 60 randomly distributed plots (1?×?1 m) were invested on four abandoned land areas (4-, 12-, 22-, and 50-year abandoned land) to determine attributes of vegetation, and soil physical and nutritional properties. It was found that vegetation distribution development went from homogeneous on 4-year abandoned land to heterogeneous on 50-year abandoned land, with a positive succession. Meanwhile, there was a significant difference in soil physical and nutritional properties for the inside and outside of vegetation patches. Vegetation patches can supply better soil physical and nutritional properties for vegetation than bare patches along the abandoned time. Vegetation diversity changes without a regular trend which may be due to the effect of environment and interspecies competition. This work picked up the slack for vegetation patterns succession research and provided a quantitative analysis approach.     

Using a neural network approach and time series data from an international monitoring station in the Yellow Sea for modeling marine ecosystems

The international marine ecological safety monitoring demonstration station in the Yellow Sea was developed as a collaborative project between China and Russia. It is a nonprofit technical workstation designed as a facility for marine scientific research for public welfare. By undertaking long-term monitoring of the marine environment and automatic data collection, this station will provide valuable information for marine ecological protection and disaster prevention and reduction. The results of some initial research by scientists at the research station into predictive modeling of marine ecological environments and early warning are described in this paper. Marine ecological processes are influenced by many factors including hydrological and meteorological conditions, biological factors, and human activities. Consequently, it is very difficult to incorporate all these influences and their interactions in a deterministic or analysis model. A prediction model integrating a time series prediction approach with neural network nonlinear modeling is proposed for marine ecological parameters. The model explores the natural fluctuations in marine ecological parameters by learning from the latest observed data automatically, and then predicting future values of the parameter. The model is updated in a “rolling” fashion with new observed data from the monitoring station. Prediction experiments results showed that the neural network prediction model based on time series data is effective for marine ecological prediction and can be used for the development of early warning systems.