TPU纳米纤维膜对典型内分泌干扰素的吸附去除

利用静电纺丝技术成功制备了热塑性聚氨酯（TPU）纳米纤维膜（TPU-NFM）,通过扫描电镜、傅里叶变换红外光谱对TPU-NFM进行表征,并设置了动力学实验和热力学实验研究TPU-NFM对BPA、EE2的吸附性能及吸附机理,探讨了环境条件对膜吸附的影响.结果表明：静电纺丝TPU纳米纤维光滑纤细、直径均匀、有良好的网状结构以及丰富的表层基团.吸附实验表明TPU-NFM对BPA的吸附过程符合Langmuir模型和准二级动力学模型,吸附过程中单分子层的化学吸附占主导作用,最大吸附容量q_max=45.48mg/g,最大吸附速率k₂=0.754g/（mg·h）.对EE2的吸附过程符合Langmuir模型和Elovich模型,偏向各吸附机理综合作用的结果,其q_max=38.22mg/g,初始吸附速率a=5.355mg/（g·h）.此外,TPU-NFM对环境中盐度以及pH值的敏感度不高.     

Investigation on the urea deposit formation and thermal decomposition characteristics in the SCR aftertreatment system of a diesel engine

Selective catalytic reduction is the most efficient and reliable equipment for NOx control in current diesel engines. However, the issue of urea crystallization becomes increasingly serious with the implement of the new emissions standards. In this paper, urea deposit samples collected from engine test bed and tube furnace were characterized by thermogravimetric analysis and Fourier transform-infrared analysis to aid the comprehension of urea deposit formation. Moreover, thermogravimetric tests were conducted to disclose the effects of catalyst on the thermal decomposition processes of urea deposit. The results indicated that less temperature resistant species are formed in the engine test bed than in the tube furnace at conditions with the same temperatures. The main compositions in the World Harmonized Transient Cycle (WHTC) urea deposits are urea, cyanuric acid (CYA) and ammelide, implying that accelerating the decomposition of these species could prevent the accumulation of urea deposit. CuWTi, Cuβ and CuZSM catalysts could lead to increased yield of CYA during pure urea thermolysis. Cuβ, CuWTi and VWTi catalysts tend to promote the thermolysis of CYA while VWTi has the most significant catalytic effects on the thermal decomposition of ammelide and ammeline.     

纳米TiO2和ZnO颗粒对红壤理化性质的影响

通过对耕作红壤的现场实验,较为系统的反映了人工纳米颗粒(TiO_2、ZnO)对土壤理化性质的影响。数据表明,在本实验周期(90 d)内,耕作红壤掺杂不同剂量(0. 1 mg/g、0. 2 mg/g、0. 5 mg/g、1 mg/g、3 mg/g)人工纳米颗粒后,纳米颗粒显著提升了土壤pH和电导率值;纳米颗粒对土壤微生物菌落数有一定的抑制作用;纳米颗粒对土壤有机质含量的影响不明显。整体而言,人工纳米颗粒(TiO_2、ZnO)进入土壤体系后,对土壤理化性质产生了一定程度的影响,且剂量越大,影响越明显。     

唐山一次冬季重污染过程污染特征及成因分析

选取河北省唐山市2017年12月27~31日一次典型重污染过程,开展其污染特征及成因分析,对污染期间气象要素、大气颗粒物组分特征进行综合研究.结果表明,此次大气重污染过程中PM_2.5平均质量浓度为154μg/m³,重度污染及以上时PM_2.5/PM₁₀为0.7;PM_2.5中SNA质量浓度占比达58.0%,OC/EC的比值为4.1,说明颗粒物二次反应和有机物在此次污染过程有较大贡献;长期均压场以及近地面高湿、小风、逆温的出现导致唐山地区大气层结稳定,加之周边地区区域传输的贡献,是导致此次大气重污染过程的重要影响因素.     

群众路线指导下高职课堂教学改革研究

针对高职课堂教学中出现的重理论教学、轻实践教学、忽视学生学习需求的多样性和个体差异性等现实问题,以党的群众路线为指导,提出高职课堂教学改革应遵循"以学生需求为根本、以课堂教学质量为基础"的基本原则,坚持走学生路线,学会站在学生的立场看问题的教学方法,大力倡导"相信学生,依靠学生,从学生中来,到学生中去"的基本教学途径,努力提高学生对教学工作的认可度、满意度,争取更加良好的课堂教学效果。     

近40年陕西省农田土壤有机质时空变化及其影响因素

了解农田土壤有机质的时空动态变化对促进农田生态系统绿色发展具有重大意义。本研究对陕西省耕地土壤有机质含量进行测定,以期探讨长期耕种下陕西省农田土壤有机质时空变化特征及其影响因素。于2017年采集耕层土样705份,采用重铬酸钾氧化—外加热法测定其有机质含量,并运用ArcGIS 10.5和GS+9.0软件进行了数据分析。结果表明：陕西省耕地土壤有机质平均含量为15.90 g·kg^?1,4级水平占比最大;不同行政区有机质含量排序为：汉中＞西安＞安康＞咸阳＞宝鸡＞商洛＞渭南＞铜川＞延安＞榆林;陕西省各市有机质含量较20世纪80年代均有不同程度的提升,其中汉中市提升幅度最大;陕西省农田土壤有机质具有强烈的空间自相关性,最优拟合模型为高斯模型,呈现南高北低的空间分布特征;结构性因素（坡度、海拔、经度、纬度）和随机性因素（施肥、耕作、秸秆还田等）共同作用导致了陕西省农田土壤有机质的空间分布差异,不同类型土壤有机质含量差异显著（P＜0.05）。本研究为指导陕西省低碳农业的发展及实现碳达峰与碳中和提供了一定的科学依据。     

初始pH值对连续投加铝盐混凝去除小分子有机物的影响机制

以污水厂二级出水中小分子有机物强化混凝去除为目的,提出了连续投加混凝工艺(CDC),并以水杨酸为模型小分子有机物,研究了初始pH值对CDC工艺去除效果的影响以及铝离子与水杨酸的络合特性.结果表明,初始pH值6时CDC工艺的去除率最高,比常规混凝工艺提升了13.8%.但是初始pH值5和7时CDC工艺的提升效果较小.三维荧光结果表明,不同pH值下水杨酸和铝离子的络合特性不同.X射线光电子能谱和电喷雾质谱结果表明,pH值5时CDC工艺前期主要生成1:1络合物Al(OH)(C₇H₄O₃)(H₂O)₂.其络合作用强烈,稳定性较高,难以从水中去除.pH值6时前期主要生成中等聚合铝(如原位Al₁₃),其与水杨酸形成的络合物可以参与到铝离子的生长过程,最终生成表面崎岖形态松散的珊瑚礁状絮体,强化了水杨酸的去除.pH值7时,主要生成不定形氢氧化铝,通过絮体表面吸附小分子有机物.     

Cross-boundary transport and source apportionment for PM2.5 in a typical industrial city in the Hebei Province, China: A modeling study

Cross-boundary transport of air pollution is a difficult issue in pollution control for the North China Plain. In this study, an industrial district (Shahe City) with a large glass manufacturing sector was investigated to clarify the relative contribution of fine particulate matter (PM_2.5) to the city's high levels of pollution. The Nest Air Quality Prediction Model System (NAQPMS), paired with Weather Research and Forecasting (WRF), was adopted and applied with a spatial resolution of 5 km. During the study period, the mean mass concentrations of PM_2.5, SO₂, and NO₂ were observed to be 132.0, 76.1, and 55.5 μg/m³, respectively. The model reproduced the variations in pollutant concentrations in Shahe at an acceptable level. The simulation of online source-tagging revealed that pollutants emitted within a 50-km radius of downtown Shahe contributed 63.4% of the city's total PM_2.5 concentration. This contribution increased to 73.9±21.2% when unfavorable meteorological conditions (high relative humidity, weak wind, and low planetary boundary layer height) were present; such conditions are more frequently associated with severe pollution (PM_2.5 ≥ 250 μg/m³). The contribution from Shahe was 52.3±21.6%. The source apportionment results showed that industry (47%), transportation (10%), power (17%), and residential (26%) sectors were the most important sources of PM_2.5 in Shahe. The glass factories (where chimney stack heights were normally < 70 m) in Shahe contributed 32.1% of the total PM_2.5 concentration in Shahe. With an increase in PM_2.5 concentration, the emissions from glass factories accumulated vertically and narrowed horizontally. At times when pollution levels were severe, the horizontally influenced area mainly covered Shahe. Furthermore, sensitivity tests indicated that reducing emissions by 20%, 40%, and 60% could lead to a decrease in the mass concentration of PM_2.5 of of 12.0%, 23.8%, and 35.5%, respectively.