蚯蚓堆制处理牛粪的腐熟度指标初步研究

在最适湿度、接种密度和20℃的室内培养条件下,以赤子爱胜蚓(Eiseniafoetida)处理未腐熟牛粪,蚯蚓堆制产物的多种生物学和化学指标及相关分析表明:种子发芽指数、脲酶活性、NH+4 N、NO-3 N/NH+4 N可作为反映蚯蚓堆制处理腐熟度的优选指标;NO-3 N、磷酸酶活性可作为一般性指标;蔗糖酶活性,水溶性碳、氮和挥发性固体不宜作为腐熟度的指标。     

亚硝化厌氧氨氧化生物脱氮技术

回顾了传统废水生物脱氮技术的一般原理,介绍了废水生物脱氮领域近年出现的新技术——亚硝化和厌氧氨氧化生物脱氮技术的基本原理、工艺特点及研究应用状况,展望了生物脱氮新技术的应用前景并指出了今后的研究方向。     

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。     

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.     

随机地震作用下BRB加固既有结构的可靠度分析∗

随着服役年限的增加,既有结构会出现材料力学性能经时退化。为精细化分析随机地震作用下既有结构及其加固后的安全性,利用非平稳地震动过程的降维模拟,并结合基于概率密度演化理论和等价极值分布的首次超越破坏可靠度分析方法,以层间位移角为评价指标,制定了3 种在不同位置布设人字形BRB 的加固方案。根据随机地震作用下BRB 加固既有结构的动力可靠度来确定3 种方案中的较优者。同时,依次用V 字形和斜支撑替换较优方案中的人字形支撑,并对比分析它们的动力可靠度,以寻找最优随机非线性振动控制的BRB 布设位置和支撑形式,为维修加固及抗震设计提供更为合理的途径。结果表明：本文方法为既有结构及其加固结构的抗震可靠度精细化计算提供了新途径,BRB 的不同布设位置及支撑形式能在一定程度上提高既有结构的动力可靠性。     

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。     

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.     

Herbivorous amphipods inhabit protective microhabitats within thalli of giant kelp <Emphasis Type="Italic">Macrocystis pyrifera</Emphasis>

Many small marine herbivores utilize specific algal hosts, but the ultimate factors that shape host selection are not well understood. For example, the use of particular microhabitats within algal hosts and the functional role of these microhabitats have received little attention, especially in large algae such as kelps. We studied microhabitat use of the herbivorous amphipod Peramphithoe femorata that inhabits nest-like domiciles on the blades of giant kelp Macrocystis pyrifera. The vertical position of nest-bearing blades along the stipe of the algal thallus and the position of the nests within the lateral blades of M. pyrifera were surveyed in two kelp forests in northern-central Chile. Additionally, we conducted laboratory and field experiments to unravel the mechanisms driving the observed distributions. Peramphithoe femorata nests were predominantly built on the distal blade tips in apical sections of the stipes. Within-blade and within-stipe feeding preferences of P. femorata did not explain the amphipod distribution. Amphipods did not consistently select distal over proximal blade sections in habitat choice experiments. Mortality of tethered amphipods without nests was higher at the seafloor than at the sea surface in the field. Nests mitigated mortality of tethered amphipods, especially at the seafloor. Thus, protective microhabitats within thalli of large kelp species can substantially enhance survival of small marine herbivores. Our results suggest that differential survival from predation might be more important than food preferences in determining the microhabitat distribution of these herbivores.