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.     

用于石油污染土壤降解的高效降解菌的筛选及其降解条件优化

经过富集、分离优选出高效石油降解菌L-1,根据形态观察和生理生化特征初步鉴定为琼氏不动杆菌;采用单因素花盆实验模拟微生物原位修复并对其降解条件进行优化。结果表明,将高效石油降解菌应用于修复石油污染土壤,适宜接种量、表面活性剂浓度、CNP比、翻耕频率分别为15%、0.1%、100∶10∶1和1 d 1次;在该降解条件下修复28 d,可达到16.80%的石油降解率,远远高于土著微生物6.92%的降解率。     

中国流域生态补偿标准核算方法分析

补偿标准核算是建立流域生态补偿机制的重要内容,也是生态补偿机制实施的关键环节.本文选取政策视角归纳了我国10个省份已经发布和实施的流域生态补偿政策的基本内容,对这些政策的补偿标准核算方法进行了分类,提出以成本和价值作为补偿标准核算方法分类的依据.结合流域生态补偿标准相关的研究成果以及国外政策,对我国流域生态补偿标准核算的政策内容进行了分析,在此基础上对政策层面流域生态补偿标准核算方法的发展和完善提出了建议.为了体现经济规律,同时增强生态补偿制度的激励作用,流域生态补偿政策中的补偿标准在污染赔偿方面需要进一步体现水污染造成的损失,在保护补偿方面需要体现水资源保护的经济价值.在未来我国流域生态补偿实施的过程中,相关方面协商确定补偿标准的趋势将会日益明显,在这个过程中各种量化核算和调查方法可以发挥比较重要的支持作用.本文的分析结果对于推动国家层面流域生态补偿标准核算政策制定或规范地方实践活动具有一定的参考价值.     

构建湘江流域生态补偿机制的探讨

本文以湘江水质和水文数据为基础,首次结合各地市社会经济发展情况,引入补偿标准系数,以湘江流域所在区域为例进行生态补偿资金测算,提出湘江流域生态补偿机制构建初步设想和存在的主要问题,以期为湘江流域水资源保护提供指导,最终实现湘江流域区域共赢。     

微絮凝-直接过滤工艺用于东江流域典型印染废水回用的实验研究

以东莞地区某典型印染企业尾水为研究对象,针对东江流域饮用水源河流水质污染现状及纳污河流水质改善目标要求与企业对尾水回用的实际需求,进行了印染废水深度处理回用工艺的适用性研究.通过混凝烧杯实验,选用工业PACl、FeSO4、HPAC 3种药剂,对微絮凝-直接过滤集成工艺用于印染废水尾水深度处理后水质回用的可行性,进行了实...     

培养藻类制取生物能源的研究

能源紧张和环境污染是全世界所面临的共同问题,用藻类替代传统作物生产生物能源是生物质能的重要发展方向之一。文章介绍了国内外对藻类培养条件、光生物反应器型式、藻类基因工程、藻细胞收集方法以及能源藻类生产系统的研究成果。研究认为,以藻类为原料生产生物燃料具有良好的发展前景,并指出了今后能源藻类生长的重点研究方向。     

基于震后低压变化的供水管网功能可靠度分析

供水管网的抗震功能是指供水管网在地震作用下能够满足震后城市特定用水需要(需水量和水压)的能力。地震发生后,供水管网一般处于低压供水状态,使得管网中部分用户的水压和水量不能得到全部满足,导致管网部分节点的实际配水量小于需水量。为此,在传统的管网水力分析基础上考虑节点流量随节点水压的动态变化,通过求解非线性水力方程组,得到管网节点实际流量和水压;同时,借鉴结构可靠度分析方法,引入供水管网系统随机水力模型,给出了震后供水管网功能可靠度分析的一次二阶矩方法。以一实际管网为例,演示了震后低压供水时管网功能可靠度分析的应用方法。     

Assessment Tools for Urban Catchments: Defining Observable Biological Potential1

Abstract: Urbanization represents a strong and increasingly more prevalent impact on stream quality worldwide. One of the characteristic effects of increased urbanization is a consistent decline in biological stream condition. The characterization of this biological degradation with increasing urbanization presents a number of advantages for the study and management of urban streams and catchments. In this paper, the limitation of biological condition with urbanization, called observed biological potential, is characterized. Using an urban intensity index and a biological index developed specifically for urban systems in the Baltimore, Maryland; Cleveland, Ohio; and San Jose, California regions, two principal techniques were compared (quantile regression and bin regression) to define observed biological potential along urban gradients. Quantile regression was selected as the preferable tool for describing observed biological potential given the consistency with which it can be applied and its statistical efficiency, however, bin quantile regression performed similarly. Having identified a numeric approximation of observed biological potential, two methods for identifying factors related to distance from potential as a way of identifying critical environmental factors affecting biological condition in urban areas were explored. The results of this work can be used for identifying benchmarks for urban stream biological condition, identifying limiting catchment characteristics, and prioritizing urban stream management efforts.     

Modeled Summer Background Concentration of Nutrients and Suspended Sediment in the Mid‐Continent (USA) Great Rivers1

Angradi, Ted R., David W. Bolgrien, Matt A. Starry, and Brian H. Hill, 2012. Modeled Summer Background Concentration of Nutrients and Suspended Sediment in the Mid‐Continent (USA) Great Rivers. Journal of the American Water Resources Association (JAWRA) 48(5): 1054‐1070. DOI: 10.1111/j.1752‐1688.2012.00669.x Abstract: We used regression models to predict summer background concentration of total nitrogen (N), total phosphorus (P), and total suspended solids (TSS), in the mid‐continent great rivers: the Upper Mississippi, the Lower Missouri, and the Ohio. From multiple linear regressions of water quality indicators with land use and other stressor variables, we determined the concentration of the indicators when the predictor variables were all set to zero — the y‐intercept. Except for total P on the Upper Mississippi River, we could predict background concentration using regression models. Predicted background concentration of total N was about the same on the Upper Mississippi and Lower Missouri Rivers (430 μg l^?1), which was lower than percentile‐based values, but was similar to concentrations derived from the response of sestonic chlorophyll a to great river total N concentration. Background concentration of total P on the Lower Missouri (65 μg l^?1) was also lower than published and percentile‐based concentrations. Background TSS concentration was higher on the Lower Missouri (40 mg l^?1) than the other rivers. Background TSS concentration on the Upper Mississippi (16 mg l^?1) was below a threshold (30 mg l^?1) designed to protect aquatic vegetation. Our model‐predicted concentrations for the great rivers are an attempt to estimate background concentrations for water quality indicators independent from thresholds based on percentiles or derived from stressor‐response relationships.     

Mercury levels and trends (1993-2009) in bream (Abramis brama L.) and zebra mussels (Dreissena polymorpha) from German surface waters

Mercury concentrations have been analysed in bream (Abramis brama L.) and zebra mussels (Dreissena polymorpha) collected at 17 freshwater sites in Germany from 1993-2009 and 1994-2009, respectively, within the German Environmental Specimen programme. Mercury concentrations in bream ranged from 21 to 881 ng g⁻¹ wet weight with lowest concentrations found at the reference site Lake Belau and highest in fish from the river Elbe and its tributaries. Statistical analysis revealed site-specific differences and significant decreasing temporal trends in mercury concentrations at most of the sampling sites. The decrease in mercury levels in bream was most pronounced in fish from the river Elbe and its tributary Mulde, while in fish from the river Saale mercury levels increased. Temporal trends seem to level off in recent years. Mercury concentrations in zebra mussels were much lower than those in bream according to their lower trophic position and varied by one order of magnitude from 4.1 to 42 ng g⁻¹ wet weight (33-336 ng g⁻¹ dry weight). For zebra mussels, trend analyses were performed for seven sampling sites at the rivers Saar and Elbe of which three showed significant downward trends. There was a significant correlation of the geometric mean concentrations in bream and zebra mussel over the entire study period at each sampling site (Pearson’s correlation coefficient = 0.892, p = 0.00002). A comparison of the concentrations in bream with the environmental quality standard (EQS) of 20 ng g⁻¹ wet weight set for mercury in biota by the EU showed that not a single result was in compliance with this limit value, not even those from the reference site. Current mercury levels in bream from German rivers exceed the EQS by a factor 4.5-20. Thus, piscivorous top predators are still at risk of secondary poisoning by mercury exposure via the food chain. It was suggested focusing monitoring of mercury in forage fish (trophic level 3 or 4) for compliance checking with the EQS for biota and considering the age dependency of mercury concentrations in fish in the monitoring strategy.