污泥淤砂分离器对分离分流污泥性质的影响

为解决我国很多城镇污水厂活性污泥的MLVSS/MLSS普遍偏低,污泥中泥沙淤积严重的问题,根据水力旋流器的分离原理,开发了污泥淤砂分离器,实现污泥中生物基质和淤砂的分离分流,研究污泥淤砂分离器主要结构参数排口比(底流口直径/溢流管直径)对分离分流污泥性质的影响。实验结果表明,排口比为0.4时,污泥经过污泥淤砂分离器后,得到的底流污泥MLVSS/MLSS比原污泥减小了34%,溢流污泥MLVSS/MLSS增大了16.8%,污泥中的生物基质富集在溢流污泥中,淤砂富集在底流污泥中;底流污泥浓度MLSS比原污泥增加了2.6倍,底流污泥SVI和CST分别减小了68%和70%,底流污泥浓缩效果明显,沉降性能和脱水性能大幅提高,有利于底流污泥的处理处置;进一步减小排口比,底流污泥浓缩效果、沉降性能和脱水性能均进一步提高。     

广东省道路交通噪声预测统计模型

为了建立符合广东省的道路交通噪声预测模型,在国内学者相关研究成果的基础上,对FHWA模型进行了深入分析,并根据道路交通噪声预测模型原理,引入等效车流量等概念建立了理论噪声预测统计模型。在此基础上,对广东省市政路和高速路的交通噪声实测数据进行多元线性回归分析,确定广东省交通噪声预测统计模型。经验证,在广东省交通噪声预测评价中该模型预测精度非常高。该研究思路与方法值得在全国各地区处理交通噪声环境问题的工作中加以推广与应用。     

Hydrogeo-chemical impacts of air sparging remediation on a semi-confined aquifer: Evidences from field monitoring and modeling

Air sparging (AS) was explored for remediation of a petroleum contaminated semi-confined groundwater system in NE China. Physical, hydro-chemical and hydraulic behaviors in subsurface environment during AS were investigated with support of modeling to understand the hydrogeo-chemical impacts of AS on the aquifer. The responses of groundwater, dissolved oxygen and temperature indicated that the radius of influence of AS was up to 8–9 m, and a 3D boundary of the zone of influence (ZOI) was accordingly obtained with volume of 362 m³. Water mounding unlike normal observations was featured by continuous up-lift and blocked dissipation. AS induced water displacement was calculated showing no obvious spreading of contaminant plume under this AS condition. Slug tests were employed before and after AS to reveal that the physical perturbation led to sharp increase in permeability and porosity. Modeling indicated that the regional groundwater flow field was not affected by AS except the physical perturbation in ZOI. Hydro-chemically increase of pH and Eh, and reduction of TDS, electrical conductivity and bicarbonate were observed in ZOI during AS. PHREEQC modeling inferred that these chemical phenomena were induced by the inorganic carbon transfer during air mixing.     

Enhanced-electrokinetic remediation of copper–pyrene co-contaminated soil with different oxidants and pH control

Electrokinetic (EK) remediation has potential to simultaneously remove heavy metals and organic compounds from soil, but the removal percent of these pollutants is very low in general if no enhancing treatment is applied. This study developed a new enhanced-EK remediation technology to decontaminate a heavy metal–organic compound co-contaminated soil by applying different oxidants and pH control. A red soil was used as a model clayed soil, and was spiked with pyrene and Cu at about 500 mg kg^?1 for both to simulate real situation. Bench-scale EK experiments were performed using four oxidants (H₂O₂, NaClO, KMnO₄, and Na₂S₂O₈) and controlling electrolyte pH at 3.5 or 10. After the treatments with 1.0 V cm^?1 of voltage gradient for 335 h, soil pH, electrical conductivity, and the concentrations and chemical fractionations of soil pyrene and Cu were analyzed. The results showed that there was significant migration of pyrene and Cu from the soil, and the removal percent of soil pyrene and Cu varied in the range of 30–52% and 8–94%, respectively. Low pH favoured the migration of soil Cu, while KMnO₄ was the best one for the degradation of pyrene among the tested oxidants, although it unfortunately prevented the migration of soil Cu by forming Cu oxide. Application of Na₂S₂O₈ and to control the catholyte pH at 3.5 were found to be the best operation conditions for decontaminating the Cu-pyrene co-contaminated soil.     

各国水体沉积物重金属质量基准的差异及原因分析

对8种重金属的海洋和淡水沉积物的质量基准进行了Box-Whisker图解分析,结果表明,各国水体沉积物重金属质量基准值均在2－3个数量级范围之间变化,相差超过4－5个数量级的极大值的出现,则通常与局部区域沉积物的污染程度和实验所用测试生物的敏感性有关,同时剖析了造成基准差异性的原因,以便从总体上对我国水体沉积物质量基准的制定有所启发和借鉴。     

Establishment of turbidity forecasting model and early-warning system for source water turbidity management using back-propagation artificial neural network algorithm and probability analysis

The purpose of this study is to establish a turbidity forecasting model as well as an early-warning system for turbidity management using rainfall records as the input variables. The Taipei Water Source Domain was employed as the study area, and ANOVA analysis showed that the accumulative rainfall records of 1-day Ping-lin, 2-day Ping-lin, 2-day Fei-tsui, 2-day Shi-san-gu, 2-day Tai-pin and 2-day Tong-hou were the six most significant parameters for downstream turbidity development. The artificial neural network model was developed and proven capable of predicting the turbidity concentration in the investigated catchment downstream area. The observed and model-calculated turbidity data were applied to developing the turbidity early-warning system. Using a previously determined turbidity as the threshold, the rainfall criterion, above which the downstream turbidity would possibly exceed this respective threshold turbidity, for the investigated rain gauge stations was determined. An exemplary illustration demonstrated the effectiveness of the proposed turbidity early-warning system as a precautionary alarm of possible significant increase of downstream turbidity. This study is the first report of the establishment of the turbidity early-warning system. Hopefully, this system can be applied to source water turbidity forecasting during storm events and provide a useful reference for subsequent adjustment of drinking water treatment operation.     

环境一号卫星多光谱数据在巢湖蓝藻动态监测中的应用

采用环境一号卫星(HJ1A/1B)的多光谱(CCD)数据,通过影像预处理提取巢湖湖域蓝藻的归一化植被指数(NDVI),对巢湖湖域的蓝藻进行动态遥感监测,在GIS平台上计算蓝藻在研究时段内的平均空间分布、模拟其变化趋势及平均改善速度,结果表明,HJ1A/1B-CCD影像数据具有较高时空分辨率,对巢湖湖域蓝藻的识别能力强;巢湖湖域生态环境总体较好,蓝藻只是在局部湖域暴发,其中蓝藻极高密度区、高密度区呈团状、片状,主要集中分布在巢湖西湖区北部沿岸,并且为楔形向中心延伸;巢湖蓝藻暴发的湖域总体呈现改善趋势,但各区改善的程度、速度差异较大,原因复杂,尤其是西湖区北部沿岸不仅改善速度缓、改善程度不佳,甚至出现退化;巢湖西区应以治理为主、监测为重,东区则以着重监测。     

Spatiotemporal Modeling of Ambient Sulfur Dioxide Concentrations in Rural Western Canada

The provinces of Saskatchewan, Alberta, and British Columbia are major oil- and gas-producing regions in western Canada. With increasing oil and gas production activities, there has been a growing concern of the effect of oil and gas industry emissions on health. Nevertheless, lack of proper tools to estimate the exposure to these emissions has been a hindrance to epidemiological studies and risk assessment. This paper presents a spatiotemporal modeling approach to estimating ambient sulfur dioxide (SO₂) levels based on environmental monitoring data (N = 10,295), which were collected at rural sites (591 per month on average) of this region from June 1, 2001 to May 31, 2002. Based on the model, illustrative maps consistently revealed high and low SO₂ concentration sub-regions. The sub-regions with elevated SO₂ concentrations had increased levels during the winter months from December 2001 to March 2002 and then decreased during the spring of 2002. This statistical modeling approach may help researchers estimate the SO₂ levels within the study area for their epidemiological studies or risk assessment.     

废弃农药厂土壤和地下水中有机磷农药的健康风险评价

采用气相色谱氮磷检测器法测定了某废弃农药厂土壤和地下水中有机磷农药(OPPs)的含量,并用美国环保署(USEPA)推荐的健康风险评价方法,对该场地土壤和地下水中OPPs引起的健康风险进行了初步评价。结果表明,土壤、地下水中∑OPPs的检出浓度范围分别为1.3~1 129μg/kg和48.0~149.2 ng/L,点位检出率分别为73%、100%。土壤和地下水中OPPs的非致癌总风险指数均小于1,致癌总风险指数均在10-4以下。根据USEPA的建议值,初步认为该场地土壤和地下水中OPPs不会对人体产生明显的健康危害。