两种AHLs信号分子对生物膜法养殖污水处理条件下水体内环境的影响

为提高生物膜法处理养殖污水的效果,对不同信号分子条件下的生物膜处理情况进行研究。在室内循环水养殖系统中,设定3个实验组和1个对照组,分别添加乙醇、C6-HSL、N-3-oxo-C8-HSL和蒸馏水,并在模拟过程中取样分析。实验结果表明,3个实验组附着基上的生物量明显多于对照组,尤其是添加N-3-oxo-C8-HSL组产生的生物量约为对照组的6倍;经添加C6-HSL和N-3-oxo-C8-HSL处理的养殖水体中,亚硝酸盐最终浓度比对照组低28.6%,但无机磷浓度稍高。数据因子分析结果表明,实验过程中(9～27 d),添加AHLs信号因子C6-HSL和N-3-oxo-C8-HSL两组养殖水体内环境的总体得分较高,说明养殖水体的内环境处于较好状态。     

碳源及反硝化芽孢杆菌强化低C/N比景观水体的生物脱氮

实验探讨了添加碳源及投加反硝化细菌对低碳氮比景观水体生物脱氮的影响。结果表明,有机碳源及B.subtilis FS05均能显著促进实验水体的生物脱氮作用,实验水体在28℃静置72 h后,乙醇添加组的TN、氨氮、硝酸盐及亚硝酸盐的去除率分别达到了62.7%、67.0%、69.8%和29.4%,而同样条件下,B.subtilis FS05投加组的去除率分别达到了66.9%、73.4%、66.0%和82.2%。从水质变化趋势可以看出,投加B.subtilis FS05能在更短时间内完成生物脱氮过程,其中,硝酸盐和亚硝酸盐去除速率最快,分别仅需要18 h和12 h。     

无机陶瓷膜处理油田采出水

针对陶瓷膜在油田采出水处理过程中操作参数的选择及污染机理进行了研究。通过现场实验,分析了不同的操作参数对膜通量的影响,陶瓷膜对含油量及悬浮物的去除效果,膜阻力组成及膜污染清洗方法。实验结果表明,在确定出水水质达到低渗透油田注水水质A1级标准条件下,陶瓷膜过滤最佳操作条件为:跨膜压差0.16 MPa、温度50℃、膜面流速5.0 m/s。同时发现,NaOH和HNO3联合清洗有助于恢复膜通量。     

气相色谱法测定气田产出水中的甲醇含量

文章建立了使用气相色谱仪分析气田产出水中甲醇含量的方法。通过实验在设定不同分流比的情况下,能有效监测出气田产出水中不同浓度的甲醇含量,此方法灵敏度高,最低检出限为0.02%,测定气田产出水中甲醇加标回收率达到93%～94%。     

树脂固定床吸附含酚废水预测模型研究

针对应用于实际工业化的树脂固定床吸附研究较少,而与之相关的固定床吸附穿透曲线可以用来确定固定床吸附操作参数,为固定床的设计和实际操作提供指导。通过对恒定波振荡理论和吸附等温方程的联合,来预测固定床吸附穿透曲线;并研究了不同操作条件对大孔弱碱树脂吸附对硝基酚穿透曲线预测模型的影响。以期望为树脂固定床的设计和实际工业应用产生指导意义。     

氯消毒新工艺对大肠杆菌灭活作用的研究

研究了短时游离氯后转氯胺的联合消毒方法对大肠杆菌的灭活作用,并对其协同作用以及pH值和温度对协同作用的影响进行了探讨。结果表明：pH值在6．5～8范围内,温度不超过30℃时,短时游离氯后转氯胺的消毒方法对大肠杆菌的灭活具有协同作用,且随pH值的降低而加强,在低温下该方法的协同效果更加明显。     

单标多点校正组合英蓝超滤测定地表水中多种阴离子

建立了利用组合单标多点校正和英蓝超滤单元的离子色谱法测定地表水中F-、C1-、NO3-、S0424—4-种离子的方法,方法操作简便,灵敏度高,线性范围广,抗干扰能力强,可同时快速测定不同数量级浓度的离子,降低了配置标准品和样品前处理的复杂性,减少了因前处理带来的干扰。     

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.     

Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model1

Moore, R.D. (Dan), J.W. Trubilowicz, and J.M. Buttle, 2011. Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model. Journal of the American Water Resources Association (JAWRA) 48(1): 32‐42. DOI: 10.1111/j.1752‐1688.2011.00595.x Abstract: Prediction of streamflow in ungauged basins is a global challenge, but is particularly an issue in physiographically complex regions like British Columbia (BC), Canada. The objective of this study was to assess the accuracy of a simple water balance model that can be run using existing spatial datasets. The model was developed by modifying an existing monthly water balance model to account for interception loss from forest canopy, glacier melt, and evaporation from lakes. The model was run using monthly climate normals from the ClimateBC application, which have a horizontal resolution of 400 m. Each ClimateBC grid cell was classified as forest, open land, glacier or water surface based on provincial scale digital maps of biogeoclimatic zones, glaciers, and water. The output was monthly mean runoff from each grid cell. These values were integrated within the catchment boundaries for streams gauged by the Water Survey of Canada. Annual runoff was predicted with modest accuracy: after updating the predicted runoff by interpolating errors from neighboring gauged streams, the mean absolute error was 25.4% of the gauged value, and 52% of the streams had errors less than 20%. However, the model appears to be quite robust in distinguishing between pluvial, hybrid, and melt‐dominated hydroclimatic regimes, and therefore has promise as a tool for catchment classification.     

An Ex Post Evaluation of Ohio’s Great Miami Water Quality Trading Program1

Newburn, David A. and Richard T. Woodward, 2011. An Ex Post Evaluation of Ohio’s Great Miami Water Quality Trading Program. Journal of the American Water Resources Association (JAWRA) 48(1): 156‐169. DOI: 10.1111/j.1752‐1688.2011.00601.x Abstract: Market‐based approaches to address water quality problems have resulted in only limited success, especially in trading programs involving both point and nonpoint sources. We analyze one of the largest point‐nonpoint trading programs – the Great Miami Trading Program in Ohio, administered by the Miami Conservancy District (MCD). Our evaluation focuses on the economic and institutional aspects of the program, including cost effectiveness, efficiency of bidding, transaction costs, trading ratios, and innovation. We use a unique dataset consisting of all bids from agricultural nonpoint sources and interviews of soil and water conservation district (SWCD) agents in the watershed. We find that the MCD’s reliance on county‐level SWCD offices to recruit and advise farmers has been essential to achieve relatively high rates of farmer participation. Additionally, the MCD is able to partly free ride on the administrative costs that SWCD offices receive to assist federal conservation programs, which is helpful to lower costs for a fledgling trading program. However, the involvement of SWCD offices reduced the potential cost savings from the reverse auction structure because some agents were able to learn about the threshold price over the six rounds of bidding and help farmers bid strategically. Overall, the program structure serves as an effective model for future trading programs in other regions that seek to involve agricultural nonpoint sources.