Mg2+ improves biomass production from soybean wastewater using purple non-sulfur bacteria

Soybean wastewater was used to generate biomass resource by use of purple non-sulfur bacteria (PNSB). This study investigated the enhancement of PNSB cell accumulation in wastewater by Mg²⁺ under the light-anaerobic condition. Results showed that with the optimal Mg²⁺ dosage of 10 mg/L, biomass production was improved by 70% to 3630 mg/L, and biomass yield also was improved by 60%. Chemical Oxygen Demand (COD) removal reached above 86% and hydraulic retention time was shortened from 96 to 72 hr. The mechanism analysis indicated that Mg²⁺ could promote the content of bacteriochlorophyll in photosynthesis because Mg²⁺ is the bacteriochlorophyll active center, and thus improved adenosine triphosphate (ATP) production. An increase of ATP production enhanced the conversion of organic matter in wastewater into PNSB cell materials (biomass yield) and COD removal, leading to more biomass production. With 10 mg/L Mg²⁺, bacteriochlorophyll content and ATP production were improved by 60% and 33% respectively.     

Mercury adsorption characteristics of HBr-modified fly ash in an entrained-flow reactor

In this study, the mercury adsorption characteristics of HBr-modified fly ash in an entrained-flow reactor were investigated through thermal decomposition methods. The results show that the mercury adsorption performance of the HBr-modified fly ash was enhanced significantly. The mercury species adsorbed by unmodified fly ash were HgCl₂, HgS and HgO. The mercury adsorbed by HBr-modified fly ash, in the entrained-flow reactor, existed in two forms, HgBr₂ and HgO, and the HBr was the dominant factor promoting oxidation of elemental mercury in the entrained-flow reactor. In the current study, the concentration of HgBr₂ and HgO in ash from the fine ash vessel was 4.6 times greater than for ash from the coarse ash vessel. The fine ash had better mercury adsorption performance than coarse ash, which is most likely due to the higher specific surface area and longer residence time.     

低浓度苯系物在新疆干旱区土壤中的吸附行为研究

采集新疆干旱区石化废水库附近区域土壤,以苯、甲苯、乙苯、二甲苯(间、对二甲苯)等典型苯系物为研究对象,系统研究低浓度苯系物在干旱区土壤上的吸附行为,分析土壤有机质含量,溶液p H、溶液含盐量、温度对苯系物吸附的影响。结果显示土壤对低浓度苯系物的吸附16 h达到平衡;吸附等温线经拟合后符合Henry直线型吸附模型;土壤对苯系物的吸附量随着土壤有机质含量的增加而增加,土壤有机质含量与吸附量呈显著正相关(P0.01,R2≥0.919);溶液p H值对吸附过程无明显作用;随着溶液含盐量增大,土壤对苯系物的吸附量表现为先减小,再稳定;温度升高会抑制土壤对苯系物的吸附作用。     

河流线型对河流自净能力的影响

为研究河流线型对河流自净能力的影响,选取5条具有不同河流线型的河涌进行研究,以弯曲度和分形维数表征河流线型,以TP、NH 3-N、NO 2-N、NO 3-N、COD Cr、TOC、DOC、叶绿素(Chlorophyll)和蓝绿藻藻蓝蛋白(BGA-PC)等9项水质指标沿程削减率表征河流自净能力,并分析各研究河段的悬浮微生物生物量和生物活性,探讨河流线型影响河流自净能力的作用机制。结果表明:多项水质指标沿程削减率随河流线型蜿蜒程度的增加而提升。在直立式浆砌石挡墙河段,河流线型通过提高悬浮微生物生物活性,进而增强河流自净能力,使TP、NH 3-N、NO 3-N、DOC、Chlorophyll和BGA-PC的沿程削减率显著提升;而在格宾石笼挡墙河段,河流线型通过增加悬浮生物生物量和提高生物活性,进而增强河流自净能力,使NO 2-N、COD Cr、TOC和DOC的沿程削减率显著提高。     

电子垃圾重金属污染及防治对策研究

随着信息产业的飞速发展,电子产品更新换代加速,电子垃圾飞速增长,电子垃圾中的重金属对环境造成了越来越严重的污染.本文回顾了广东贵屿与浙江台州两大电子垃圾回收拆解区重金属污染的现状,分析了电子产品原材料、加工工艺和电子垃圾不当回收导致重金属污染的原因,提出了依靠政策法规引导、借鉴国外先进经验、进行电子垃圾回收处理产业化发展的相应防治对策,以期能改善电子垃圾导致的重金属污染.     

底栖动物在水质评价中应用的中文文献统计和分析研究

底栖动物长期生活在水体底部,水质的变化会直接影响到它们的生长和繁殖,因此底栖动物可以准确的反映水体的质量.利用底栖动物对水质进行生物评价,在国内已较多采用,并取得了一定的成果.在收集、整理了126篇底栖动物在水质评价中的应用的相关中文文献的基础上,统计出了这些文献的年度发表量及在各期刊的分布情况,其中核心期刊占有较大的比例.此外,还统计了文献的研究机构,主要是以高校为主体,以及文献所用的评价水质的方法,共计14种.     

锰渣填埋场渗滤液及周边水体的水化学特征和质量评价

本文在分析锰渣填埋场区渗滤液及周边水体水化学组成的基础上,运用改进的水质量指数(WQI)进行了水质评价,阐述了填埋场渗滤液对下游水体的影响过程。结果表明,研究区渗滤液pH呈中性偏酸性,EC在1 780~44 500μS/cm之间,渗滤液中NH4-N、Mn2+、Mg2+、SO2-4、NO-3的浓度较高,并呈现SO2-4Mn2+Mg2+NH+4-N的特征,并且浓度与堆存时间呈负相关性。填埋场下游水体的重金属浓度微量,但NH4-N和Mn2+浓度较高,均超过GB 3838—2002和GB/T 14848—93规定的限值,其中2014年5月份某地下水的这两个参数分别超标243倍和488倍。改进的WQI指数评价结果显示,地表水的渗滤液水污染指数(LWPI)值在2.89~7.83之间,受影响的地下水为172,说明渗滤液已对锰渣填埋场下游水体造成严重影响。     

Integration of chemical and biological methods: A case study of polycyclic aromatic hydrocarbons pollution monitoring in Shandong Peninsula, China

Polycyclic aromatic hydrocarbons(PAHs), as persistent toxic substances(PTS), have been widely monitored in coastal environment, including seawater and sediment. However, scientific monitoring methods, like ecological risk assessment and integrated biomarker response, still need massive researches to verify their availabilities. This study was performed in March, May, August and October of 2018 at eight sites, Yellow River estuary(S1), Guangli Port(S2), Xiaying(S3), Laizhou(S4), Inner Bay(S5), Ou...     

Wall losses of oxygenated volatile organic compounds from oxidation of toluene: Effects of chamber volume and relative humidity

Vapor wall losses can affect the yields of secondary organic aerosol. The effects of surface-to-volume (S/V) ratio and relative humidity (RH) on the vapor-wall interactions were investigated in this study. The oxygenated volatile organic compounds (OVOCs) were generated from toluene-H₂O₂ irradiations. The average gas to wall loss rate constant (k_gw) of OVOCs in a 400 L reactor (S/V = 7.5 m⁻¹) is 2.47 (2.41 under humid conditions) times higher than that in a 5000 L reactor (S/V = 3.6 m⁻¹) under dry conditions. In contrast, the average desorption rate constant (k_wg) of OVOCs in 400 L reactor is only 1.37 (1.20 under humid conditions) times higher than that in 5000 L reactor under dry conditions. It shows that increasing the S/V ratio can promote the wall losses of OVOCs. By contrast, the RH effect on k_gw is not prominent. The average k_gw value under humid conditions is almost the same as under dry conditions in the 400 L (5000 L) reactor. However, increasing RH can decrease the desorption rates. The average k_wg value under dry conditions is 1.45 (1.27) times higher than that under humid conditions in the 400 L (5000 L) reactor. The high RH can increase the partitioning equilibrium timescales and enhance the wall losses of OVOCs.     

确定性系数与地理探测器模型耦合的泥石流易发性评估方法研究∗——以安宁河流域为例

通过确定性系数与地理探测器模型耦合的方法研究耦合模型对泥石流灾害易发性评估的影响。基于遥感判识和野外考察确定安宁河流域内的 198 条泥石流沟作为评估样本,选取坡度、地面峰值加速度、地形起伏度、地层岩性、植被覆盖度、植被类型、地形湿度指数以及地貌演化指数作为评价因子,耦合确定性系数和地理探测器模型,分别计算各评价因子分级取值和因子权重,进行安宁河流域泥石流易发性等级分区。研究结果表明：(1)地理探测器方法定量分析安宁河流域内泥石流发育的主要贡献因子为地面峰值加速度、地形起伏度和坡度。(2)泥石流极高易发区和高易发区分别占流域总面积的 9.67% 和 12.02%,高易发区主要分布在安宁河流域两岸且呈条带状分布。 (3)利用 ROC 曲线对泥石流易发性评估精度进行验证,耦合模型的 AUC 值达到 0.824,相比单种模型 CF 模型的评估精度 0.786 提升了 4.8%,具有更高的准确率,评价效果更优。