腐殖酸作用下沉积物中纳米氧化铜对铜锈环棱螺生态毒性的影响

为了探讨不同水平腐殖酸作用下沉积物中纳米氧化铜(CuO-NPs)对底栖生物生态毒理学效应的影响,以铜锈环棱螺(Bellamya aeruginosa)为受试生物,通过腐殖酸和CuO-NPs加标沉积物的慢性(28 d)生物测试,研究了肝胰脏中Cu的生物积累、Na+K+-ATP酶(ATPase)、超氧化物歧化酶(SOD)以及过氧化氢酶(CAT)活性的变化规律.结果表明,在低浓度CuO-NPs处理组(60 μg·g1),沉积物中腐殖酸水平对Cu的生物积累以及ATPase、SOD和CAT活性均没有显著影响.在中、高浓度CuO-NPs处理组(≥180 μg·g-1),Cu的生物积累均随腐殖酸水平的增加而显著升高;肝胰脏ATPase活性随腐殖酸水平的增加而显著下降;当腐殖酸水平为0.05 g·g-1时,SOD活性显著高于未添加腐殖酸组,表现为显著诱导,当腐殖酸水平≥0.1g·g-1时,SOD活性开始下降,并具有浓度依赖性;随腐殖酸水平的增加,肝胰脏CAT活性总体上表现为浓度依赖性显著下降.由于沉积物中腐殖酸的存在,显著增加CuO-NPs在沉积物中的分散稳定性,更容易被铜锈环棱螺摄取,从而通过增加CuO-NPs的生物积累而增强对铜锈环棱螺的生态毒性.     

滑石粉对阻燃聚丙烯土工格栅性能的影响

将滑石粉加入聚丙烯阻燃格栅料中制成聚丙烯阻燃土工格栅材料,并探讨滑石粉对阻燃格栅的力学性能、熔融指数、燃烧性能、热稳定性和结晶性能的影响。结果表明:滑石粉的加入能提高阻燃格栅的熔融指数和结晶度,但对力学性能和阻燃性能有负面影响。与未添加滑石粉的阻燃格栅相比,添加5%wt的滑石粉后,阻燃格栅的断裂伸长率下降了9633%,峰值热释放速率和总释放热分别增加了4736%和2164%;当滑石粉添加量进一步增加到10%wt时,阻燃格栅的阻燃性能略有提高,但断裂伸长率却下降了975%。热重和差热分析表明,阻燃格栅阻燃性能的下降与热稳定性下降有关,而熔融指数提高则与α晶型熔点下降有关     

硝基甲苯对小鼠睾丸生殖细胞DNA的损伤作用

为提供硝基甲苯的环境遗传毒理学依据和建立鱼类生殖细胞的培养方法,采用昆明小鼠睾丸支持细胞/生殖细胞共培养法以及彗星实验,研究了2,4-二硝基甲苯(2,4-DNT)、2,6-二硝基甲苯(2,6-DNT)、对硝基甲苯(4-NT)对小鼠睾丸生殖细胞DNA的损伤作用.结果表明,3种受试硝基甲苯化合物均能够诱导小鼠睾丸生殖细胞DNA单链断裂,而且其受损率与剂量对数具有明显的剂量-效应关系.2,4-DNT、2,6-DNT以及4-NT的各个剂量浓度引起细胞DNA损伤的程度,与对照组相比,均具有显着性差异(p<0.01,p<0.05).受试化合物的毒性顺序为2,6-DNT>2,4-DNT>4-NT,DNA的损伤作用二硝基甲苯大于单硝基甲苯.提示在体外条件下,2,4-DNT、2,6-DNT和4-NT具有生殖毒性,可以引起小鼠睾丸生殖细胞DNA损伤.     

从“土法改进”谈救灾帐篷居住环境的改善——以汶川8.0级地震救灾为例

帐篷在救灾过程中发挥着巨大作用,但内部热湿环境比较恶劣,空温、内表面均温都超出了人体所能适应的范围,严重影响灾区群众的身心健康。汶川8.0级地震的灾区群众利用一些土方法如搭遮阳网等对帐篷进行了改进。通过对门窗封闭和门窗开启情况下改进的帐篷与普通帐篷室内温度、相对湿度、内表面均温的对比,发现采取一些简单的改进方法能取得意想不到的效果,可以有效的降低帐篷内部温度和内表面均温,从而降低帐篷内的当量有效温度,改善帐篷内居住环境。从而得到很大启示,提出了一些在帐篷使用过程中的改善措施以及结构改进的方向。     

日本阪神大地震15周年

<正>2010年1月17日是日本阪神大地震15周年纪念日,日本当天举行各种纪念活动,追悼当年的死难者。日本首相鸠山在仪式上致辞说,阪神大地震发生15年来,灾区实现了重建,但现在仍有必要努力抚慰     

胞外聚合物对活性污泥吸附及再生的影响研究

通过研究胞外聚合物 (EPS)对活性污泥吸附及再生的影响 ,探讨吸附、再生机理。吸附试验表明 ,EPS与污泥吸附能力显著相关 ,随着污泥负荷的降低 ,EPS增加 ,污泥的吸附能力提高 ;并且有机物种类对污泥的吸附性能有显著影响 ,研究表明吸附机理主要是生物絮凝作用。此外 ,再生试验结果表明 ,再生能增加中负荷 (Ns) =0 3～ 0 5kgBOD5/kgMLSS·d污泥的吸附能力 ,但不能改变高负荷 (Ns) =2～ 3kgBOD5/kgMLSS·d污泥的吸附能力。其作用机理是再生过程可迫使中负荷污泥进入内源代谢期 ,使污泥中的EPS增加 ,絮凝活性增加 ,吸附能力提高 ,而高负荷污泥再生后EPS则无变化。同时 ,再生过程将使污泥的脱氢酶、OUR降低 ,代谢活性降低。对于高负荷污泥的再生是无效的。     

Migration and remediation of organic liquid pollutants in porous soils and sedimentary rocks: a review

Environmental Chemistry Letters - Underground pollution of soils and sediments is a major yet overlooked health issue, because pollutants are often trapped into inaccessible&nbsp;and complex...     

Predicting the elemental compositions of solid waste using ATR-FTIR and machine learning

● A method based on ATR-FTIR and ML was developed to predict CHNS contents in waste. ● Feature selection methods were used to improve models’ prediction accuracy. ● The best model predicted C, H, and N contents with accuracy R ² ≥ 0.93, 0.87, 0.97. ● Some suitable models showed insensitivity to spectral noise. ● Under moisture interference, the models still had good prediction performance. Elemental composition is a key parameter in solid waste treatment and disposal. This study has proposed a method based on infrared spectroscopy and machine learning algorithms that can rapidly predict the elemental composition (C, H, N, S) of solid waste. Both noise and moisture spectral interference that may occur in practical application are investigated. By comparing two feature selection methods and five machine learning algorithms, the most suitable models are selected. Moreover, the impacts of noise and moisture on the models are discussed, with paper, plastic, textiles, wood, and leather as examples of recyclable waste components. The results show that the combination of the feature selection and K-nearest neighbor (KNN) approaches exhibits the best prediction performance and generalization ability. Particularly, the coefficient of determination (R²) of the validation set, cross validation and test set are higher than 0.93, 0.89, and 0.97 for predicting the C, H, and N contents, respectively. Further, KNN is less sensitive to noise. Under moisture interference, the combination of feature selection and support vector regression or partial least-squares regression shows satisfactory results. Therefore, the elemental compositions of solid waste are quickly and accurately predicted under noise and moisture disturbances using infrared spectroscopy and machine learning algorithms.     

Effects of sulfur on variations in the chemical speciation of heavy metals from fly ash glass

● A higher sulfur content reduced the curing rate of Cr in glass. ● Depolymerization increased the amounts of heavy metals in the carbonate bound state. ● Reducing the CaO/SiO₂ ratio increased the proportion of stable heavy metals. This work designed a new CaO-Al₂O₃-SiO₂-SO₃ glass for the immobilization of multiple heavy metals found in dechlorinated fly ash having high amounts of calcium and sulfur. Increasing the (CaO + SO₃)/SiO₂ mass ratio (M(CS/S)) from 0.28 to 0.85 was found to lower the proportions of Mn, Ni and Zn in an unstable state, while an M(CS/S) ratio of 0.51 gave the lowest proportions of unstable Cr and Pb. Decreasing the degree of polymerization of the glassy network increased the proportions of Mn, Cr, Ni, Pb and Zn in the carbonate bound state. The leaching out of metals in this state was the primary cause of degradation of Q³ structural units in the glassy network. The amount of Mn in the iron-manganese oxide bound state was increased by increasing the number of Q² units in the silicate network. Decreasing the CaO/SiO₂ mass ratio (M(C/S)) raised the proportions of Mn, Ni and Zn in the unstable state. An M(C/S) value of 0.43 lowered the proportions of unstable Cr and Pb. A principal components analysis determined that the leaching of toxic heavy metals from the glass was primarily related to the proportions of these metals in the unstable state while there were no evident correlations between leaching and the proportions in stable states.     

合肥市冬季PM_(2.5)中水溶性离子化学特征分析

基于2021年12月1日-2022年2月28日合肥市细颗粒物(PM_(2.5))及其水溶性离子连续观测数据,分析了合肥市冬季PM_(2.5)中水溶性离子化学特征以及不同污染程度下水溶性离子化学特征。结果表明:采样期间合肥市PM_(2.5)污染较重,不同污染程度下PM_(2.5)浓度差异较大,中度及以上污染天的ρ(PM_(2.5))平均值分别是清洁天和轻度污染天的2.8和1.3倍。二次水溶性无机离子[硝酸根离子(NO_(3)^(-))、铵根离子(NH+4)和硫酸根离子(SO_(2)-4),简称SNA]是合肥市PM_(2.5)的重要组成部分,随着污染程度的加重,PM_(2.5)二次生成比例随之下降。NH+4是合肥市水溶性离子中中和能力最强的离子,易与NO_(3)^(-)和SO_(2)-4结合分别形成NH_(4)NO_(3)和(NH_(4))_(2)SO_(4)。合肥市SO_(2)和NO_(2)均易发生二次转化,且SO_(2)较NO_(2)更容易发生二次转化。钙离子(Ca^(2+))和镁离子(Mg^(2+))相关性较高,说明合肥市PM_(2.5)可能受扬尘影响较大;钾离子(K^(+))是生物质燃烧的指示离子,氯离子(Cl^(-))与K^(+)相关性较好,说明合肥市PM_(2.5)组分中的Cl^(-)和K^(+)主要来自生物质燃烧。PM_(2.5)中水溶性离子受降水和温度影响较大。