水中六氯苯的高级氧化降解机理及其动力学探讨

采用UV、O3、UV/O3高级氧化法对水中六氯苯(HCB)的降解效果及机理进行了研究.结果表明, UV本身对HCB的去除贡献率不大, HCB可被O3、UV/03快速降解,即UV相似文献   

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.     

趋势分析法评价苯系物标准气体的时间稳定性

根据GB/T 15000.3—2008设计了苯系物标准气体的时间稳定性研究方案,制备了4瓶苯系物标准气体,随着时间的推移进行测定并将结果制图,结果显示量值随时间没有显著的变化趋势。以线性关系为模型,计算线性直线的斜率和斜率的标准偏差,用t检验判断斜率是否显著来评价标准气体的稳定性。计算结果显示,所有斜率均不显著,因此该研究制备的苯系物标准气体能够稳定保存22个月。根据时间稳定性数据计算由不稳定性引起的不确定度,并讨论了这种计算不稳定性引起不确定度的方法对结果有放大的可能性。     

萃取-催化氧化光度法测定生物体中H2O2含量研究

提出萃取-催化氧化光度法测定生物体中H2O2含量的新方法.用稀土催化H2O2产生羟基自由基以氧化二苯基碳酰二肼,生成红色二苯基碳酰腙,其最大吸收波长为563.0nm;当二苯基碳酰二肼浓度一定时,△A563与H2O2含量呈量效关系.在0～30μmol/L H2O2 含量范围内,该法能简单、快速、精确地测定生物样品中H2O2实际含量.     

MnFe2O4磁性纳米棒非均相Fenton催化降解水中四环素的研究

采用水热合成法成功制备出MnFe₂O₄磁性纳米棒(s-MnFe₂O₄),并考察了商品化的Fe₃O₄、MnFe₂O₄和合成的s-MnFe₂O₄纳米棒这3种磁性纳米颗粒作为非均相Fenton催化剂降解水中四环素抗生素的性能.同时,采用X射线衍射(XRD)、透射电镜(TEM)、N₂吸附-脱附、振动样品磁强计(VSM)及X射线光电子能谱(XPS)等技术对催化剂的理化性质进行了表征.非均相Fenton催化降解四环素的结果表明,s-MnFe₂O₄具有最高的催化活性,反应180 min,四环素的去除率可以达到87.6%,TOC的去除率达到47.5%.自由基捕获试验证实了羟基自由基(·OH)是非均相Fenton氧化过程中的主要活性物种.s-MnFe₂O₄磁性纳米棒的高催化活性归...     

有机肥与无机肥配施对潮土N2O排放的影响

华北平原是我国重要的粮食主产区,由于土壤有机质含量低,增加氮肥用量并不能导致玉米产量持续增加.有机肥和无机肥配施被广泛认为是同时实现粮食增产和提高土壤有机质的双赢措施,但是有机肥和无机肥配施对华北平原农田N₂O排放的影响尚不明确.本研究在华北平原潮土区,通过测定不同种类有机肥与无机肥配施后农田N₂O排放通量和作物产量,旨在揭示不同种类有机肥及其用量对潮土N₂O排放和作物产量的影响效应.田间试验共设置8个处理,分别为不施肥(CK)、化肥氮(NPK)、 40%牛粪氮+60%化肥氮(CM)、 40%鸡粪氮+60%化肥氮(FC)、 40%猪粪氮+60%化肥氮(FP)、 20%牛粪氮+80%化肥氮(1/2CM)、 20%鸡粪氮+80%化肥氮(1/2FC)和20%猪粪氮+80%化肥氮(1/2FP).整个玉米季N₂O排放通量均与土壤WFPS显著正相关(P<0.05).除NPK处理外,玉米季N₂O排放量与土壤可溶性有机碳(DOC)平均含量存在显著的线性关系.玉米季CK处理N_2<...     

磁性纳米Fe3O4@C对SBR脱氮除磷性能及其微生物种群组成的影响

为探究磁性纳米Fe₃O₄@C对序批式活性污泥反应器(SBR)污水处理系统脱氮除磷性能的影响,建立了2个相同的SBR(编号分别为0号和1号),其中,0号反应器未投加任何磁性材料(对照组),1号反应器中投加0.5 g·L^-1的Fe₃O₄@C(实验组),并采用高通量测序和实时定量PCR(qPCR)技术对2个反应器内生物种群结构及关键脱氮除磷功能菌群进行分析.结果表明:(1)Fe₃O₄@C对SBR除污性能有显著影响,其中,1号反应器化学需氧量(COD)的去除性能得到增强,24 d后去除率稳定在90%左右;0号和1号反应器总氮(TN)平均去除率分别为35.83%和52.18%;从第43 d起,1号反应器除磷性能明显高于0号反应器,运行70 d后,0号和1号反应器对总磷(TP)的平均去除率分别为47.52%和56.33%.(2)添加Fe₃O₄@C材料后,反应器内变形菌门(Proteobacteria)的...     

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.     

Perceived barriers to and drivers of community participation in protected‐area governance

Protected areas (PAs) are a frequently used conservation strategy, yet their socioeconomic impacts on local communities remain contentious. A shift toward increased participation by local communities in PA governance seeks to deliver benefits for human well‐being and biodiversity. Although participation is considered critical to the success of PAs, few researchers have investigated individuals’ decisions to participate and what this means for how local people experience the costs and benefits of conservation. We explored who participates in PA governance associations and why; the perceived benefits and costs to participation; and how costs and benefits are distributed within and between communities. Methods included 3 focus groups, 37 interviews, and 217 questionnaire surveys conducted in 3 communities and other stakeholders (e.g., employees of a nongovernmental organization and government officials) in PA governance in Madagascar. Our study design was grounded in the theory of planned behavior (TPB), the most commonly applied behavior model in social psychology. Participation in PA governance was limited by miscommunication and lack of knowledge about who could get involved and how. Respondents perceived limited benefits and high costs and uneven distribution of these within and between communities. Men, poorer households, and people in remote villages reported the highest costs. Our findings illustrate challenges related to comanagement of PAs: understanding the heterogeneous nature of communities; ensuring all households are represented in governance participation; understanding differences in the meaning of forest protection; and targeting interventions to reach households most in need to avoid elite capture.