焚烧飞灰重金属含量及浸出长期变化规律研究

通过对24个飞灰样品的重金属全量消解和高精度X射线荧光光谱法（HDXRF）快速检测结果进行线性回归分析,发现HDXRF法可较准确测定飞灰中Cu、Pb、Zn、Ni和Cd含量（线性回归决定系数R²³0.90）.采用HDXRF法对某焚烧厂飞灰重金属含量6个月快速检测及浸出毒性测定数据统计分析发现：飞灰重金属月均含量较稳定（变异系数CV<0.14）但日均含量波动较大（CV>2.54）;飞灰中Pb、Cu和Zn含量呈正相关（相关系数r>0.78）;金属浸出浓度受浸出液终点pH值影响显著,超标频率依次为Pb（68.9%）、Cd（66.1%）、Ni（24.0%）、Cu（14.2%）和Zn（1.6%）.短期飞灰金属含量和浸出毒性数据受焚烧工况,烟气处理工况和垃圾组分等多种因素共同影响,不具有代表性.为评估垃圾分类源头削减重金属效果,建议采用快速检测方法对焚烧飞灰重金属含量进行长期监测.     

Investigation of chlorinated phenols sorption mechanisms on different layers of the Danube alluvial sediment

The characteristics of the Danube river alluvial sediment are of great importance in assessing the risk for transport of pollutants to drinking water sources. Characterization of the sediment column layers has shown that the alluvial sediment, sampled near the city of Novi Sad, is a mesoporous sandy material with certain differences in the properties of individual layers. In order to investigate the sorption mechanisms of four chlorinated phenols (CPs) on the alluvial deposit, static sorption experiments were performed at pH 4, 7 and 10. The results of sorption experiments, confirmed by principal components analysis sugest different mechanisms govern the sorption process at different pH conditions. This can be attributed to the molecular characteristics of CPs, geosorbent properties and to variations in the surface charge of the sorbent at different pH conditions.     

郑州市氧化铝工业炉窑污染物及源谱特征

采用稀释通道采样法对郑州市一家拜耳法氧化铝企业及一家α-氧化铝企业的PM_2.5、PM₁₀样品进行采集,利用烟气分析仪检测SO₂和NO_x气体的质量浓度.对颗粒物样品中的38种化学组分进行分析,构建相应的源成分谱,运用分歧系数（CD）和组分差异权重分布函数R/U对其特征进行对比研究.结果表明：α-氧化铝源谱中以Cl^-为主（质量分数18.29%~25.21%）,拜耳法氧化铝源谱中以OC和NO₃^-为主（质量分数9.01%~41.87%）.源谱间的分歧系数（CD）显示,同一种生产工艺两种粒径间的源谱比较相似,相同粒径的两种生产工艺之间的源谱差异较大.R/U值对比结果显示,EC、Ca、F^-和Cl^- 4种元素可作为区分两种氧化铝生产工艺的标识组分.     

Relationship between physicochemical properties and dewaterability of hydrothermal sludge derived from different source

Sewage sludge (SS) and deinking sludge (DS) were used to comparatively study the hydrothermal dewatering of sludge with different components. For a better overview, an insight into the relationship between physicochemical properties and dewaterability of hydrothermal sludge was provided. Results found that not all kinds of sludge were suitably conditioned by hydrothermal treatment (HT) in term of the elevation of dewaterability. Higher hydrothermal temperature tended to enhance the dewaterability of SS rather than DS, which was supported by the variation of their physicochemical properties (including water distribution, bonding energy, extracellular polymeric substance (EPS), particles size, acid functional groups and zeta potential in this study). In addition, the changes in surface morphology suggested that the reverse effect of HT on sludge dewaterability was mainly due to their dewatering behavior. For SS, the destruction of EPS structure leaded to the release of bound water, thereby strengthening sludge dewatering. Conversely, “Bridging effect” generated by lignocellulose in DS was beneficial for sludge dewatering; however, the increasing hydrothermal temperature degraded part of lignocellulose and weakened “bridging effect”, finally resulting in worse dewaterability of DS.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Fractionation of Cu, Pb and Zn in certified reference soils SRM 2710 and SRM 2711 using the optimized BCR sequential extraction procedure

Sequential extraction of metals from solid media is a common analytical tool used in environmental and exploration geochemistry. A number of procedures exist, but without harmonization and standardization, meaningful comparisons are tenuous without baseline data. A newly developed, standardized sequential extraction procedure (optimized BCR) was applied to two contaminated certified reference soils from Montana, US (SRM 2710 and SRM 2711) for Cu, Pb and Zn. Four operationally defined fractions were isolated, acid extractable, reducible, oxidizable, and residual (by aqua regia). Fraction-specific concentrations, percentages and recoveries for Cu, Pb and Zn were used to explore differences between the optimized BCR procedure and three other sequential extraction schemes with published data for SRM 2710 and 2711 (i.e. Tessier scheme, Geological Survey of Canada scheme and the original BCR scheme). Results indicate significant differences between the four schemes, even for schemes that are closely associated (i.e. the original and optimized BCR schemes). Order-of-magnitude fraction-specific concentration differences were observed, especially for Pb in the reducible fraction. Differences between schemes are worrisome because trends varied between metals, between fractions and between reference soils. These data reinforce the need for increased adoption of standardized sequential extraction procedures and further examination of different solid media.     

煤中有害元素对环境和人体健康影响的评价参数

煤中有害元素对环境和人体健康影响的较为全面的评价体系一直未建立，环保部门也缺乏系统性评价参数对电厂等在煤煤过程中有害元素排向大气的释放量进行监测估算。本文在查阅大量资料（主要为外文）的基础上，认为评价煤中有害元素对环境和人体健康影响的参数应该包括以下方面的数据C、H、O、N、无机硫，有机硫，有害微量元素的含量，分布规律，赋存状态，迁移转化行为（在燃煤过程中），洁净能力，淋滤力，矿物质，有机化学特征，煤炭学特征，并对煤中有害元素的污染方法进行探讨，如果上述各参数的数据被全面提供，并据此数据作针对性的抑制措施，煤中有害元素对环境和人体健康危害影响必将降低到最小。     

ASM1中废水和污泥组分浓度的测定方法研究

对呼吸计量法应用于校准ASM1作了简明的阐述。在呼吸速率与模型组分关系的基础上,介绍了ASM1中废水与污泥各组分浓度的测定方法,并指出模型组分细化的意义。     

在污染条件下生物的生态效应

主要就污染物对动物、植物及人体健康的危害，以及在污染条件下生物的适应与进化作一综述。     

主成份分析法在大气环境质量综合评价中的应用

介绍了主成份分析法评价大气环境质量的基本原理，并对某市的大气环境质量进行了综合评价。最后，与其它方法的评价结果进行了对比分析，进一步证实了主成份分析法的科学性、合理性。