新型Fe3O4@α-MnO2活化过一硫酸盐降解水中偶氮染料

采用两步水热法制备了新型磁性纳米Fe₃O₄@α-MnO₂复合材料作为催化剂,用于活化过一硫酸盐（PMS）产生强氧化性的硫酸根自由基（SO₄^-·）氧化降解偶氮染料活性黑5（RBK5）.采用透射电子显微镜（TEM）,X射线粉末衍射仪（XRD）和振动样品磁强计（VSM）对制备的催化剂进行表征,证明成功合成了纳米α-MnO₂包覆Fe₃O₄形态的Fe₃O₄@α-MnO₂催化剂,催化剂的饱和磁化强度为39.89emu/g.Fe₃O₄@α-MnO₂催化剂活化PMS与单一的Fe₃O₄和α-MnO₂活化PMS相比,具有更高的催化效率,说明铁锰双金属存在协同作用.同时研究了催化剂的投加量、PMS的浓度和初始pH值等各种因素对RBK5的降解效率以及反应动力学的影响.实验结果表明,Fe₃O₄@α-MnO₂催化剂活化PMS降解RBK5的过程符合准一级反应动力学,在催化剂投加量为1.2g/L,PMS的浓度为4mmol/L,初始pH值为7.0,反应时间为60min的情况下,浓度为30mg/L的RBK5的降解效率可达到91%,此时RBK5的降解速率常数也达到最高值0.023min^-1.此外,通过加入自由基淬灭剂甲醇、叔丁醇和硝基苯判断了Fe₃O₄@α-MnO₂/PMS体系中起主要氧化降解作用的活性物种为SO₄^-·.     

环境升温过程对常温固化环氧树脂热力学性能的影响

目的提高常温固化环氧树脂体系的高温使用性能。方法采用常温固化剂T31、中温固化剂IPDA以及高温固化剂DDM作为混合固化剂,对E-44型和AG-80型混合环氧树脂体系进行常温固化反应,并分析环境升温过程对固化物热力学性能的影响。通过DMA分析、热变形测量、固化度测试,分别评价室温固化环氧树脂在环境升温过程前后的玻璃化转变温度、热变形量及体系内部的固化反应程度变化,并通过吸水率测试和弯曲强度测试对玻璃纤维布增强常温固化环氧树脂基复合材料的耐湿热性能以及高温条件下的力学性能进行分析。结果环氧树脂常温固化物的tg为85.21℃,经1.5℃/min的平均升温速率加热至90℃之后,该环境升温过程使固化物的固化度增大至92%以上,tg增长为132.06℃的同时热变形温度增大。其复合材料耐湿热性能提高,且100℃时弯曲强度的保持率为65%,对于加热至120℃的环境升温过程,固化物的固化度接近96%,tg增长为144.45℃的同时热变形温度进一步提高,其复合材料耐湿热性能改善程度更加明显,且130℃时弯曲强度保持率仍接近60%。结论常温、中温、高温混合固化剂的合理复配有助于环氧树脂体系在环境升温变化的诱导条件下发生梯度式固化反应,使体系内部的交联固化程度迅速升至较高水平,可以有效提高其玻璃化转变温度,显著改善常温固化环氧树脂体系在高温条件下的热力学性能。     

重度雾霾环境下篮球运动对人体心肺机能的影响研究

雾霾一直是影响人体健康的始作俑者之一,重度雾霾环境下人体的各项机能均会下降,甚至衰竭。针对重度雾霾环境下篮球运动对人体心肺机能的影响开展下列研究:对雾霾天气形成因素进行详细研究,经研究发现在城市中,有毒的颗粒物主要来源于汽车尾气、北方抵御冬季供暖生成的废气、工业生产中排放的气体、建筑工地与马路交通生成的扬尘等方面,特别是在长三角和珠三角地区,每年出现雾霾的天数要在100天以上,且个别城市超过了200天;将雾霾环境下篮球运动对人体心肺机能的影响划分为:易导致呼吸道及肺组织交叉感染、易导致慢性阻塞性的肺部疾病、易导致肺癌三大模块,并对形成的原因进行详细阐述。     

基于医疗大数据的空气污染类疾病信息分析研究

世界卫生组织表示,空气污染为造成全球疾病负担的一项重要因素,能够导致心血管疾病、呼吸系统疾病等各种疾病的发生,空气污染问题已经成为公共卫生领域关注的重点问题,对基于医疗大数据的空气污染类疾病信息进行分析。利用半参数广义相加的泊松回归模型,在控制时间、长期趋势、气象因素等一些复杂条件的基础上,对2012年1月1日至2016年12月31日,某市空气中SO2、PM10和NO2等一些主要空气污染物的监测浓度值与呼吸系统疾病(肺炎以及支气管炎与哮喘)住院人数的相关性进行研究,研究结果表明,空气颗粒物PM10对患病率的影响相对于气态污染物SO2、NO2更为严重。     

Reduction of heavy metal content in Hiroshima Bay oysters (Crassostrea gigas) by purification

Cultured oysters from Hiroshima Bay were analysed to determine the content of nine trace elements, cadmium (Cd), lead (Pb), chromium (Cr), arsenic (As), manganese (Mn), nickel (Ni), copper (Cu), zinc (Zn), and iron (Fe) and compared with oysters treated for 48 h in both artificial sea water and a solution of 0.5% ethylenediaminetetraacetic acid (EDTA) in artificial sea water. It was found that the values of As and Fe in both groups of treated oysters were significantly lower than in the untreated oysters and that the Pb and Mn levels tended to be lower. It was also found that oysters treated in 0.5% EDTA solution in artificial sea water had lower levels of Cd and Cu than the oysters treated only in artificial sea water.     

Development of monitoring technology for airborne particulate matter

Particulate matter suspended in the air has adverse effects onhuman health. Its level of concentration is an important parameter in evaluating the degree of hazard it poses to the atmosphere. Conventional methods used in measuring particulatematter are often filter-based, which indicates some disadvantagesbecause such a base requires labor and time. In this study, to achieve real-time measurements, a new electrical method was developed for measuring PM10 and PM2.5 concentrations. The basicprinciple is to electrically charge particles passing through thePM inlet using a corona charger and measure the currents createdby charged particles to obtain the number concentration of particulate matter. A new type inlet based on the particle cupimpactor configuration was designed and its performance was evaluated. A unipolar diffusion charger was developed and thecharger's efficiency was determined experimentally in terms ofPn, which represents the penetration through the charger,P, times the average charge number acquired by a particle,n, for different particle sizes. The correlation was constructed between the PM10 (or the PM2.5) mass concentrationsand the electrical currents due to particles, which were chargedby the diffusion charger.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Arsenic speciation in human hair: a new perspective for epidemiological assessment in chronic arsenicism

The analysis for arsenic in hair is commonly used in epidemiological studies to assess exposure to this toxic element. However, poor correlation between total arsenic concentration in hair and water sources have been found in previous studies. Exclusive determination of endogenous arsenic in the hair, excluding external contamination has become an analytical challenge. Arsenic speciation in hair appears as a new possibility for analytical assessing in As-exposure studies. This study applied a relative simple method for arsenic speciation in human hair based on water extraction and HPLC-HG-ICP-MS. The concentration of arsenic species in human hair was assessed in chronically As(V)-exposed populations from two villages (Esqui?a and Illapata) of the Atacama Desert, Chile. The arsenic concentrations in drinking water are 0.075 and 1.25 mg L(-1), respectively, where As(V) represented between 92 and 99.5% of the total arsenic of the consumed waters. On average, the total arsenic concentrations in hair from individuals of Esqui?a and Illapata were 0.7 and 6.1 microg g(-1), respectively. Four arsenic species, As(III), DMA(V), MMA(V) and As(V), were detected and quantified in the hair extracts. Assuming the found species in extracts represent the species in hair, more than 98% of the total arsenic in hair corresponded to inorganic As. On average, As(III) concentrations in hair were 0.25 and 3.75 microg g(-1) in Esqui?a and Illapata, respectively; while, the As(V) average concentrations were 0.15 and 0.45 microg g(-1) in Esqui?a and Illapata, respectively. Methylated species represent less than 2% of the extracted As (DMA(V)+ MMA(V)) in both populations. As(III) in hair shows the best correlation with chronic exposure to As(V) in comparison to other species and total arsenic. In fact, concentrations of As(total), As(III) and As(V) in hair samples are correlated with the age of the exposed individuals from Illapata (R= 0.65, 0.69, 0.57, respectively) and with the time of residence in this village (R= 0.54, 0.71 and 0.58, respectively).     

Floristics, performance and prognosis of historical trees in the urban forest of Guangzhou City (China)

Outstanding historical trees embedded in cities constitute pertinent environmental assets, yet they are widely threatened in third-world cities. Inadequate understanding of this valuable natural-cum-cultural heritage hinders proper conservation. A case study of Guangzhou in south China evaluated floristic composition, age profile and biomass structure of historical trees, assessed their performance in major habitats (institutional, park and roadside), and established a prognosis for future growth and management. The 348 historical trees examined belonged to only 25 species, vis-à -vis 254 trees in the entire urban forest, dominated by five species and native members. Roadside had more trees, followed by institutional and park, with merely the most common four species shared by all habitats. The limited commonality reflected tree-performance differentiation by habitats exerting selection pressure on species. The institutional growth-regime was more conducive to nurturing high-caliber specimens, whereas park is less capable. Individual species achievement by habitats, derived from tree-count ranking and relative-abundance indices, could inform species choice and tree conservation. Few trees exceeded 300 years of age in the millennium-old city, echoing a history of intense tree—city conflicts. Potential life-span, trunk and crown diameters indicated ample opportunities for further expansion of biomass and landscape impacts, which would be straitjacketed by the tightening urban fabric.     

Environmental and biological monitoring of methyl ethyl ketone (MEK)

This study was conducted to evaluate the usefulness of various biological parameters for monitoring of workers exposed to methyl ethyl ketone (MEK). Fifty male workers from a large magnetic videotape factory participated in this study. Personal air samples were collected using 3M organic vapor monitors and analysed for MEK by gas chromatography with flame ionisation detector (FID). 10 mL of urine; blood (1 mL) and exhaled air were also collected at the end of an 8-hour workshift. The headspace GC method was applied for measurement of urinary and blood MEK. MEK in expired air was analysed directly by using a GC/FID.The correlation coefficients (r) between environmental MEK and all other biological parameters measured show significant positive relationships. The r for environmental MEK and urine MEK was 0.84; for blood 0.73 and for breath 0.64. The correlation coefficients between blood and urine was 0.72; blood and breath was 0.88 and urine and breath 0.60. These findings suggest that measurements of unmetabolised MEK in blood, exhaled air and urine can be used for biological monitoring of MEK exposure. Nevertheless, laboratory methodological assessment is in favour of measuring urinary MEK as it is non-invasive and does not have to be analysed immediately after collection.