沸石床多级生物膜焦化废水处理系统的NH_~4+-N去除稳定性研究

焦化废水处理中预处理蒸氨工艺不稳定容易引起生物处理出水NH+4-N的波动,为了在有机物去除的同时提高生物系统对NH+4-N的去除效果和稳定性,采用对NH+4-N有良好吸附性能的天然斜发沸石为生物填料构建沸石床多级生物膜系统,考察了进水负荷对系统运行稳定性的影响、抗冲击负荷能力以及系统的功能分区和污染物迁移转化规律.结果表明,当系统进水NH+4-N负荷≤0.21 kg/(m3·d)、COD负荷≤1.35 kg/(m3·d)时,出水NH+4-N和COD的平均浓度分别为(2.2±1.2)mg/L和(228±60)mg/L,平均去除率分别达(99.1±0.5)%和(86.0±2.6)%.在低、高两次NH+4-N冲击负荷[0.03 kg/(m3·d)和0.06 kg/(m3·d)]条件下,系统对NH+4-N的平均去除率仍然分别高达99.0%和92.9%,高于对比系统的96.8%和89.3%,表现出良好的抗NH+4-N冲击负荷性能与处理稳定性.系统好氧单元反应器沿程出现脱碳/硝化功能区(C/N区)和硝化功能区(N区),其中N区的NH+4-N 降解速率为C/N区的2～8倍.系统进水中相对分子质量＜1×103、 1×103～1×104、＞1×104的TOC浓度分别为227.6、104.8和35.0 mg/L,处理出水中的TOC浓度分别为31.2、 22.9和31.5 mg/L,其中相对分子质量＜1×103和1×103～1×104这2个范围的有机物降解良好,出水残余物质主要为相对分子质量＞1×103的有机物.     

催化臭氧氧化过程中溴酸盐的生成机制研究

以黄河下游某水厂滤后水为目标物,选择了9种催化剂,在间歇反应装置中研究了单独臭氧和催化臭氧氧化过程中溴酸盐（BrO 3-）的生成情况,结果表明,在催化臭氧氧化过程中,NiO、CuO、Fe3O4、Al2O3加入使BrO 3-质量分数分别降低34.0%、32.8%、29.2%、20.8%.选取Fe3 O4作为催化剂研究催化...     

弹性填料微孔曝气生物膜法修复污染水源除NH4+-N

采用弹性填料微孔曝气生物接触氧化法对受污染的水源进行修复除NH₄⁺-N效果研究.结果表明,在正常水温20℃～27℃条件下,当污染水源COD_Mn7～14mg/L,NH₄⁺-N 0.7～2.0mg/L和生物修复工艺运行参数HRT为1.4h,气:水=0.5:1,DO为7～9mg/L时,生物修复工艺可去除水源中的NH₄⁺-N为64%～95%;在较低水温7℃～12℃条件下,当污染水源COD_Mn6～11mg/L,NH₄⁺-N 1.2～8.0mg/L和生物修复工艺运行参数HRT为1.4h,气:水=0.5:1,DO为8～10mg/L时,生物修复工艺可去除水源中的NH₄⁺-N为40%～63%.     

硫酸盐还原菌介导的吸附态砷的迁移转化

自然界中砷(As)主要被吸附在铁氧矿物上,吸附态砷从铁氧矿物释放至水体是水中砷污染的主要来源.在此过程中,微生物起着至关重要的作用.本研究的目的是探究加入硫酸盐还原菌Desulfovibrio vulgaris DP4对吸附态砷迁移转化的影响.结果表明,0 h两体系砷释放量均为0μmol·L~(-1).与对照组相比,前84 h DP4促进了吸附态五价砷[As(Ⅴ)]的脱附,在13 h砷的释放量达到最大值12.6μmol·L~(-1),占初始总吸附量(16μmol·L~(-1))的79%,是对照组(1.5μmol·L~(-1))的8.4倍.而在84 h之后,DP4体系的砷浓度低于非生物对照组,表明溶解态砷被再次固定.此过程中,砷的释放量与氧化还原电位(Eh)显著相关(P=0.001).XRD结果表明,在DP4作用下针铁矿的结晶度降低了50%,且结晶度越低,吸附能力越强,这可能是后期砷被再次固定的原因之一.同时SEM-EDS表明DP4使得针铁矿发生团聚,部分被转化为硫铁矿.As的XANES结果表明固相中没有硫化砷生成,这进一步证明固相中生成的主要是硫铁矿,它对砷的再吸附导致了后期DP4体系中溶解态砷的浓度低于非生物对照组.此外,在固相中检测出了19%的As(Ⅲ),而液相中并未检测出溶解态的As(Ⅲ),据此推测硫酸盐还原菌原位还原了吸附态As(Ⅴ).     

悬浮泥沙对酚类化合物的吸附特性研究

研究了4种分别取自长江口和杭州湾的悬浮泥沙样品对苯酚、邻氯酚和2,4-二氯酚的吸附特性.结果表明,在12 h内可以达到对酚类化合物的吸附平衡,对苯酚的吸附量小,且不同样品间无显著差别,样品对酚类化合物吸附量随着酚类化合物氯化程度的提高而增大,与样品粒径分布、比表面积、有机物含量有关.在酚类化合物初始浓度＜2.0 mg/L时,样品对酚类化合物的等温吸附可以用Freundlich吸附等温式来表征,计算得到吸附常数Koc分别为622～1 410、3 287～3 707、6 444～8 787.挥发酚国家二级排放标准限定浓度为0.5 mg/L以下,此浓度下水体中悬浮泥沙能够有效吸附挥发酚,但高盐度不利于酚类化合物的吸附.     

活性炭负载Co3O4活化过一硫酸盐降解金橙G

通过浸渍煅烧法制备活性炭负载Co的活化剂(Co/AC),采用X射线衍射仪(XRD)、扫描电镜(SEM)及X射线能谱仪(EDS)技术对活化剂进行表征,发现Co主要以Co_3O_4的形式负载于活性炭表面,并利用Co/AC活化过一硫酸盐(PMS)产生硫酸根自由基(SO_4~-·)降解偶氮染料金橙G(OG),研究了活化反应机制及不同因素对OG降解的影响.结果表明,SO_4~-·在OG降解过程中起主要作用,并且随Co/AC用量、PMS浓度、温度的提高,OG降解效率明显增加.反应初始pH对降解OG有较大影响,当p H在4~8范围内,SO_4~-·均能有效降解OG,但在强酸碱条件下,则不利于OG降解.Cl~-对活化降解OG具有双重作用,低浓度时抑制降解,而在高浓度时促进降解.Co/AC在重复使用6次时仍具有较好活化性能.通过紫外可见光谱及气相色谱-质谱(GC/MS)对OG降解过程及中间产物进行了分析.     

对氯酚经Fenton体系预降解后的生物流化床处理

采用Fenton-生物流化床联用工艺处理对氯酚(4-CP)模拟废水,考察了不同Fenton处理程度时4-CP的降解产物和出水的可生化性,从而确定合适的Fenton体系预处理程度.同时,采用快速排泥法进行活性炭的挂膜以实现流化床的启动,并考察了流化床连续运行阶段停留时间(RT)、pH对降解效果的影响及反应器的抗冲击能力.最后研究了4-CP在Fenton-生物流化床联用工艺中的降解过程.结果表明,当4-CP初始浓度在1～2mmol·L-1时,通过Fenton体系可使83%左右的苯环破裂,转化成小分子有机酸;利用微生物作用可使剩余的苯环类物质和大部分的有机酸被降解,出水CODCr100mg·L-1.Fenton-生物流化床工艺具有高效处理难降解废水的优点,是一项具有应用前景的废水处理技术.     

乳酸和复合脂肪酸抑制奶牛对环境污染的效果分析

将20头荷斯坦产奶奶牛随机分为对照组和试验Ⅰ～Ⅲ组,对照组饲喂全混日粮(TMR),试验Ⅰ组每头奶牛每天饲喂TMR加150.0 g复合脂肪酸,试验Ⅱ组每头奶牛每天饲喂TMR加150.0 g乳酸,试验Ⅲ组每头奶牛每天饲喂TMR加150.0 g复合脂肪酸/乳酸(质量比为1∶1),分析探讨了复合脂肪酸和乳酸对奶牛粪尿、氮、总磷排泄量和CH4释放量的影响.结果表明,相比对照组,试验Ⅲ组1头奶牛1年CH4释放量减少30.64 kg,粪尿、氮、总磷排泄量分别减少1.43 t、28.32 kg和2.36 kg,标准乳(FCM)提高3.28%.在奶牛饲料中添加乳酸和复合脂肪酸的混合酸,能有效抑制奶牛对土壤、水体及空气的污染,显著提高奶牛的生态效益和经济效益.     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.     

Efficacy of extracting indices from large‐scale acoustic recordings to monitor biodiversity

Passive acoustic monitoring could be a powerful way to assess biodiversity across large spatial and temporal scales. However, extracting meaningful information from recordings can be prohibitively time consuming. Acoustic indices (i.e., a mathematical summary of acoustic energy) offer a relatively rapid method for processing acoustic data and are increasingly used to characterize biological communities. We examined the relationship between acoustic indices and the diversity and abundance of biological sounds in recordings. We reviewed the acoustic‐index literature and found that over 60 indices have been applied to a range of objectives with varying success. We used 36 of the most indicative indices to develop a predictive model of the diversity of animal sounds in recordings. Acoustic data were collected at 43 sites in temperate terrestrial and tropical marine habitats across the continental United States. For terrestrial recordings, random‐forest models with a suite of acoustic indices as covariates predicted Shannon diversity, richness, and total number of biological sounds with high accuracy (R² ≥ 0.94, mean squared error [MSE] ≤170.2). Among the indices assessed, roughness, acoustic activity, and acoustic richness contributed most to the predictive ability of models. Performance of index models was negatively affected by insect, weather, and anthropogenic sounds. For marine recordings, random‐forest models poorly predicted Shannon diversity, richness, and total number of biological sounds (R² ≤ 0.40, MSE ≥ 195). Our results suggest that using a combination of relevant acoustic indices in a flexible model can accurately predict the diversity of biological sounds in temperate terrestrial acoustic recordings. Thus, acoustic approaches could be an important contribution to biodiversity monitoring in some habitats.