Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

生物滴滤塔处理氯苯废气的工艺性能

将活性污泥培养及驯化后接种于生物滴滤塔中,挂膜启动后处理模拟氯苯废气（简称氯苯废气）,考察了生物滴滤塔在挂膜启动阶段及稳定运行阶段的性能。实验结果表明：接种41 d后生物滴滤塔成功挂膜,此时氯苯去除率稳定在90%以上;生物滴滤塔稳定运行阶段,随着进气中氯苯质量浓度由303.82 mg/m³逐渐增至1 489.05 mg/m³,氯苯去除率从85.1%降至70.1%。处理氯苯废气适宜的工艺条件为：空塔停留时间超过45 s,喷淋液流量31.8 mL/min,氯苯负荷23.97~128.01 g/（m³·h）。生物滴滤塔对喷淋液的酸性环境有较好的适应性,喷淋液pH的变化对氯苯去除率无显著影响。     

镍渣的重金属浸出特性

在分析镍渣的矿物相组成和重金属元素含量的基础上,鉴定了镍渣样品的浸出毒性,并考察了pH、液固比和浸出时间等条件对镍渣样中铬、铅、铜和锌等重金属浸出特性的影响。结果表明,镍渣中的重金属总量约为渣样的0.9%,且铬、铜和锌的含量较高,需进行安全管理。实验所用镍渣样品为第Ⅰ类一般工业固体废物。在强酸条件下镍渣中重金属浸出浓度较大,pH3后浸出浓度显著降低;液固比40 L/kg时,镍渣中重金属不断溶出,液固比40 L/kg后,浸出达到饱和,浸出浓度趋于平衡;随着浸出时间的增加,重金属离子的浸出浓度先增加后减少,但由于各重金属性质不同,各重金属达到最大浸出浓度的时间不同。     

Corynebacterium glutamicum as an indicator for environmental cobalt and silver stress–A proteome analysis

Cobalt and silver are toxic for cells, but mechanisms of this toxicity are largely unknown. Analysis of Corynebacterium glutamicum proteome from cells grown in control and cobalt or silver enriched media was performed by two dimensional gel electrophoresis (2DE) followed by mass spectrometry. Our results indicate that the cell adapted to cobalt stress by inducing five defense mechanisms: Scavenging of free radicals, promotion of the generation of energy, reparation of DNA, reparation and biogenesis of Fe-S cluster proteins and supporting and reparation of cell wall. In response to the detoxification of Ag⁺ many proteins were up-regulated, which involved reparation of damaged DNA, minimizing the toxic effect of reactive oxygen species (ROS) and energy generation. Overexpression of proteins involved in cell wall biosynthesis (1,4-alpha-glucan branching enzyme and nucleoside-diphosphate-sugar epimerase) upon cobalt stress and induction of proteins involved in energy metabolism (2-methylcitrate dehydratase and 1, 2-methylcitrate synthase) upon silver demonstrate the potential of these enzymes as biomarkers of sub-lethal Ag⁺ and Co toxicity.     

Effects of combinations of malathion and cypermethrin on survivability and time of metamorphosis of tadpoles of Indian cricket frog (Fejervarya limnocharis)

This study was undertaken to determine the effect of environmentally realistic concentrations of two commonly used pesticides viz., malathion and cypermethrin, using a fully 3 × 3 factorial experiments on the survivability and time of metamorphosis in a common rice paddy field frog (cricket frog) Fejervarya limnocharis under laboratory conditions. The results suggest that cypermethrin is more toxic than malathion and combinations of higher concentrations of cypermethrin (50 μg/L) with malathion (250 and 500 μg/L) are more deleterious to the survivability of tadpoles. With increasing cypermethrin concentration, the survivability of tadpole decreased (r = ?0.986, P = 0.108). But cypermethrin alone induced early metamorphosis among the surviving tadpoles. However, there was a delay in the time required for metamorphosis induced by malathion and its combination with cypermethrin. The delay in metamorphosis may indicate the altered physiological fitness of the individual. The emergent froglets will be subjected to environmental stressors like high temperature and less humidity of post-monsoon tropical climate that could enhance negative influence triggered by pesticides.     

Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande1

Abudu, S., J.P. King, Z. Sheng, 2011. Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande. Journal of the American Water Resources Association (JAWRA) 48(1): 10‐23. DOI: 10.1111/j.1752‐1688.2011.00587.x Abstract: This paper presents the application of autoregressive integrated moving average (ARIMA), transfer function‐noise (TFN), and artificial neural networks (ANNs) modeling approaches in forecasting monthly total dissolved solids (TDS) of water in the Rio Grande at El Paso, Texas. Predictability analysis was performed between the precipitation, temperature, streamflow rates at the site, releases from upstream reservoirs, and monthly TDS using cross‐correlation statistical tests. The chi‐square test results indicated that the average monthly temperature and precipitation did not show significant predictability on monthly TDS series. The performances of one‐ to three‐month‐ahead model forecasts for the testing period of 1984‐1994 showed that the TFN model that incorporated the streamflow rates at the site and Caballo Reservoir release improved monthly TDS forecasts slightly better than the ARIMA models. Except for one‐month‐ahead forecasts, the ANN models using the streamflow rates at the site as inputs resulted in no significant improvements over the TFN models at two‐month‐ahead and three‐month‐ahead forecasts. For three‐month‐ahead forecasts, the simple ARIMA showed similar performance compared to all other models. The results of this study suggested that simple deseasonalized ARIMA models could be used in one‐ to three‐month‐ahead TDS forecasting at the study site with a simple, explicit model structure and similar model performance as the TFN and ANN models for better water management in the Basin.     

Evaluation of effects of exposure time on aquatic toxicity with zooplanktons using a reduced life expectancy model

Traditionally in toxicological studies time is not studied as quantifiable variable but as a fixed endpoint. The Reduced Life Expectancy (RLE) model which relates exposure time and exposure concentration with lethal toxic effects was tested previously using fish data. In this current paper the effects of exposure time on aquatic toxicity with zooplanktons and various toxicants were evaluated using the RLE model based on ambient exposure concentration. The model was evaluated by plotting ln LT₅₀ against LC₅₀ using toxicity data with zooplanktons from the literature for metal, metalloid and organic compounds. Most of the experimental data sets can be satisfactorily correlated by use of the RLE model, but deviations occurred for some data sets. Those data sets were satisfactorily fitted by a two stage RLE model. This model was based on two phases: one in the peripheral system and other in the central system. Both the single and two stage RLE model support the hypothesis that toxicity is time dependent and decreases in a systematic way with increasing exposure time. A calculated normal life expectancy (NLT) can be obtained from the single stage model and is in accord with reported NLT but those obtained from the two stage RLE model are in excellent agreement.     

SRT对MBR污泥性质的影响

以浸没式膜-生物反应器(SMBR)处理模拟赖氨酸废水为研究体系,考察SRT在10、20和40 d条件下,SMBR中的胞外聚合物(EPS)组分和含量、污泥沉降性能和污泥相对疏水性等污泥性质的变化及其对膜污染的影响。结果表明,随着SRT的延长,混合液中EPS总量呈递减趋势,TBEPS中蛋白质与多糖的比值呈上升趋势,污泥的沉降性能变差,相对疏水性增强;膜通量下降速率变大,膜污染加重。污泥性质与膜污染的相关性表明,膜污染与蛋白质和多糖的比值、污泥沉降性能和相对疏水性呈正相关关系,而与EPS呈负相关关系。     

纳米生态基对水产养殖污水的处理效果

采用三因子四水平的正交设计,实验研究了纳米生态基在不同温度、溶解氧和水力停留时间下对水产养殖污水的处理效果,确定了纳米生态基处理养殖污水的最佳条件。结果表明,含氨氮和亚硝氮浓度较高的模拟养殖污水用纳米生态基挂膜,所需时间约为22 d。纳米生态基对氨氮的去除效果明显,平均去除率达到93.5%。对氨氮去除率的影响程度,水力停留时间>温度>溶解氧。当温度为30℃,DO为5.43 mg/L,HRT为0.33 h时,纳米生态基对氨氮的处理能力最佳,去除率达到94.6%。纳米生态基对亚硝氮的平均去除率为69.3%。对亚硝氮去除率的影响程度,水力停留时间>溶解氧>温度。当温度为21℃,DO为6.40 mg/L,HRT为0.33 h时,纳米生态基对亚硝氮的处理能力最佳,去除率为71.5%。纳米生态基处理养殖污水的最佳条件:温度为30℃,DO为6.40 mg/L,HRT为0.33 h。     

不同填料载体生物膜对微囊藻毒素的去除效果

利用自行设计的生物膜培养装置,通过对4种不同填料载体进行连续曝气循环培养生物膜,对湖水中的溶解态微囊藻毒素(MCs)的去除作用进行了研究。结果表明,填料载体上生物膜从形成到稳定大约需要3周;生物膜形成后对MCs的去除效率由高到低的顺序是:颗粒活性炭柱>多密孔球型滤料柱>塑料悬浮填料柱>陶瓷滤球柱。在实验水质条件下,当水力停留时间(HRT)=5 h,进水MCs浓度为21.5～47.25μg/L时,颗粒活性炭、多密孔球型滤料柱对MCs的去除率最高可达100%,塑料悬浮填料柱对MC-LR和MC-RR的去除率分别为70%和88%。当HRT=2.5 h时,塑料悬浮填料柱对MC-RR的去除率为MC-LR的2倍。生物膜对MCs的降解效果随温度(5～20℃)和溶解氧的升高而增加。塑料悬浮填料作为合适的生物膜挂膜填料载体对水源水的生物预处理具有良好的应用前景。