FNA对短程硝化污泥菌群结构的影响

在SBR反应器增加游离亚硝酸（FNA）预处理单元,投加浓度为1.2mgHNO₂-N/L的FNA进行缺氧搅拌4.5h,连续处理3d,考察短程硝化污泥中FNA对氨氧化菌（AOB）,丝状菌和微生物菌群结构的影响.研究表明,FNA对AOB有短时抑制作用,并能够抑制优势丝状菌Candidatus_Microthrix（微丝菌属）和Cytophagaceae（噬纤维菌）的增殖,分别由5.1%和1.1%下降到0.78%和几乎不可见.SVI从281mL/g降低到100mL/g左右.NAR能够维持在90%左右,短程硝化不受到破坏.高通量结果显示,FNA处理后微生物菌群结构多样性与丰度出现下降,但Thauera（陶厄氏菌属）和Ottowia出现了增殖,分别增加到5.58%和7.82%,同步硝化反硝化（SND）作用明显,这使得即便只有短程硝化,总氮去除率依然能达到60%以上.     

A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

基于偏序集的采空区塌陷危险性评价研究

针对采空区塌陷危险性评价方法中的赋权争议问题,基于偏序集理论提出偏序集评价模型。首先阐明评价指标并确定其分级标准;然后应用偏序集评价模型得到Hasse图,并通过图展现的层集信息判别采空区塌陷危险程度;最后应用该模型对大宝山矿11个采空区的塌陷程度进行判别,评价结果准确合理。研究结果表明:该模型避免了以往研究中的赋权争议问题,克服了样本量不足致使模型无法应用的问题,而且能够应用更多的赋权方法识别排序的稳定程度,体现出样本间的分层信息。     

Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)

Leakage diagnosis of hydrocarbon pipelines can prevent environmental and financial losses. This work proposes a novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity. The OLGA software is employed to provide the pipeline inlet pressure and outlet flow rates as the training data for the Fault Detection and Isolation (FDI) system. The FDI system is comprised of a Multi-Layer Perceptron Neural Network (MLPNN) classifier with various feature extraction methods including the statistical techniques, wavelet transform, and a fusion of both methods. Once different leakage scenarios are considered and the preprocessing methods are done, the proposed FDI system is applied to a 20-km pipeline in southern Iran (Goldkari-Binak pipeline) and a promising severity and location detectability (a correct classification rate of 92%) and a low False Alarm Rate (FAR) were achieved.     

Regression analysis of forest inventory data with time and space dependencies

In this paper the data of a forest health inventory are analyzed. Since 1983 the degree of defoliation, together with various explanatory variables (covariates) concerning stand, site, soil and weather, are recorded by the second of the two authors, in the forest district of Rothenbuch (Spessart, Bavaria). The focus is on the space and time dependencies of the data. The mutual relationship of space-time functions and the set of covariates is evaluated. For this we use generalized linear models (GLMs) for ordinal response variables and semiparametric estimation approaches. By using goodness-of-fit measures it turns out that (i) the contribution of space-time functions is quantitatively comparable with that of the set of covariates, (ii) the contribution of space-time functions is small compared with the contribution of a set of variables describing the last-year and neighboring response values. By applying appropriate residual methods a detailed analysis of the individual sites in the area can be carried out. This analysis reveals where the predictive power of the covariates fail to explain the observed defoliation.     

不同驯化方式实现SBR中部分反硝化的对比研究

部分反硝化（NO₃^--N→NO₂^--N）是一种非常具有前景的硝酸盐废水处理方法,其可以结合厌氧氨氧化实现低碳源、低能耗脱氮.本文以葡萄糖为碳源,对比研究3种部分反硝化驯化方式：R1（SBR缺氧）、R2（SBR缺氧-好氧交替运行）、R3（SBR缺氧搅拌伴随低曝气）.经过120d驯化后,对三种反应器污泥进行沿程实验,探索3种反硝化规律.结果显示引入溶解氧驯化后的R2、R3污泥相比R1能够更好地实现部分反硝化,且R3最佳.采用高通量测序技术,对运行109d时R1,R2,R3进行微生物群落结构对比分析.结果显示在有溶解氧参与的R2,R3反应器中的优势菌属为Candidatus Saccharibacteria,相对丰度分别为45.44%和34.96%,这是该菌首次作为反硝化污泥优势菌属被报道.另外R1反应器中微生物多样性要远大于R2,R3,这也从侧面说明R2,R3的反硝化菌更专性.初始pH值对R3驯化污泥影响的批试实验表明,初始pH值对亚硝酸盐积累有明显影响,且初始pH值越高,亚硝酸盐积累越多.     

利用集合均方根卡尔曼滤波反演重庆地区SO2源排放

传统的"自下而上"清单方法估算的排放清单,其数据的准确性和时效性存在较大局限.基于集合均方根卡尔曼滤波的源清单反演方法,结合WRF-CMAQ（天气研究和预报模式-公共多尺度空气质量模型）被用于对以清华大学编制的2010年MEIC（中国多尺度排放清单模型）排放清单为基础制作的重庆地区SO₂排放源进行反演试验以解决准确性和时效性问题,试验时间段为2014年10月15-31日,重庆主城17个环境空气质量国控监测点ρ（SO₂）小时观测资料用于反演及检验.结果表明:该方法能够反演重庆地区SO₂源排放量,随着反演次数增加,基于反演排放源预报的ρ（SO₂）预报误差持续减小,反演4次后预报误差达到比较低的稳定的水平,其均方根误差均低于20 μg/m3. 5次反演后SO₂源排放量用于2014年10月24-29日每天起始预报,其预报的站点、时间平均的均方根误差从100~400 μg/m3降至30 μg/m3以下.反演中应用局地化尺度减少集合取样误差影响,54与81 km两个局地化尺度反演结果对预报改善效果相当,表明主要影响重庆主城ρ（SO₂）的源排放位于主城及周边地区,也说明内源排放对重庆主城ρ（SO₂）起主要影响.反演后面源排放量主城区降幅约为30 kg/（d·km2）,周边地区减少10~20 kg/（d·km2）,主城区部分SO₂点源排放量降幅约为25 kg/（d·km2）,说明2010年MEIC排放清单高估了试验时段重庆地区的SO₂排放.      

厌氧/好氧SPNDPR系统实现低C/N城市污水同步脱氮除磷的优化运行

为了解同步短程硝化内源反硝化除磷(SPNDPR)系统的脱氮除磷特性,以低C/N城市污水为处理对象,采用延时厌氧(180 min)/好氧运行的SBR反应器,通过联合调控曝气量和好氧时间,考察了该系统启动与优化运行特性.结果表明,当系统好氧段曝气量为0. 8 L·min~(-1),好氧时间为150 min时,出水PO_4~(3-)-P浓度约为1. 5 mg·L~(-1)左右,出水NH_4~+-N和NO_3~--N浓度由10. 28 mg·L~(-1)和8. 14 mg·L~(-1)逐渐降低至0 mg·L~(-1)和2. 27 mg·L~(-1),出水NO_2~--N浓度逐渐升高至1. 81 mg·L~(-1);当曝气量提高至1. 0 L·min~(-1)且好氧时间缩短至120min后,系统除磷、短程硝化性能逐渐增强,但总氮(TN)去除性能先降低后逐渐升高,最终出水PO_4~(3-)-P、NH_4~+-N分别稳定低于0. 5 mg·L~(-1)和1. 0 mg·L~(-1),好氧段亚硝积累率和SND率分别达98. 65%和44. 20%,TN去除率达79. 78%. SPNDPR系统内好氧段好氧吸磷、反硝化除磷、短程硝化、内源反硝化同时进行保证了低C/N污水的同步脱氮除磷.     

基于CESM-EnSRF系统全球甲烷及臭氧卫星资料同化试验研究

臭氧(O3)与甲烷(CH4)均是大气中重要的微量气体,对全球气候变化有着重要的影响.为提高全球范围的臭氧、甲烷在气候模式中的预报效果,使用集合平方根滤波(En SRF)同化方法及地球系统模式(CESM)构建了CESM-En SRF卫星资料同化预报系统,并通过设计试验,将大气红外探测器(AIRS)的臭氧与甲烷观测资料同化到气候模式中,对模式的同化再预报效果进行系统的测试与评估.结果显示,臭氧、甲烷分析集合均值的偏差及均方根误差皆低于背景集合均值的偏差及均方根误差.臭氧、甲烷的同化再预报偏差及均方根误差较控制实验都得到改善,但对5 h Pa以上高度臭氧预报准确性的改进效果很小.随循环同化的进行,平流层臭氧与甲烷的平均同化改进率呈增加趋势,并逐渐趋于稳定;对流层平均同化改进率随时间变化不明显.试验表明,该系统可有效利用臭氧与甲烷的观测资料对模式场进行合理的改善,从而有效地提高臭氧、甲烷在气候模式中的再预报效果,但对于平流层顶-中间层高度(5 h Pa以上)臭氧预报准确度的提高,模式中臭氧光化学过程的准确模拟较同化观测资料具有更重要的作用.此外,循环同化对提高5~150 h Pa高度臭氧及1~200 h Pa高度甲烷在CESM模式中的预报效果最有效.     

不同停曝比对连续流亚硝化颗粒污泥运行的影响

在（25~28℃）下,接种成熟亚硝化颗粒污泥于连续流反应器,为避免通过蠕动泵的污泥回流所造成的颗粒污泥破碎,采用内置沉淀区进行内回流,调整停曝比为1：1、2：1和1：2,研究不同停曝比对连续流亚硝化颗粒污泥系统稳定性的影响.结果表明,控制停曝比为1：1和2：1,亚硝化性能良好,阶段末期亚硝酸盐积累率分别为85.2%和94.5%,控制停曝比为1：2,亚硝化性能逐渐恶化,阶段末期氨氧化率和亚硝酸盐积累率下降至64.1%和58.7%.批次试验表明,间歇曝气相对连续曝气可在一定程度上较好地抑制亚硝酸盐氧化菌（NOB）的相对活性,停曝时间越长,对NOB的活性抑制越好,但由于停曝时间过长也将导致氨氧化率降低,故在亚硝化工艺中,可采用1：1停曝比并协同其他控制条件的方式来实现连续流亚硝化工艺的长期稳定运行.污泥性能分析表明,在停曝比为1：1~1：2范围内,停曝时间越长,颗粒污泥结构越稳定,停曝时间越短,反应器内选择压较小,致使污泥沉降性能变差,部分亚硝化颗粒污泥解体,此外,胞外聚合物（EPS）化学分析及三维荧光光谱分析显示,停曝比为2：1条件下,蛋白（PN）含量较高且蛋白/多糖（PN/PS）值也较高.