Fecal source tracking by antibiotic resistance analysis on a watershed exhibiting low resistance

The ongoing development of microbial source tracking has made it possible to identify contamination sources with varying accuracy, depending on the method used. The purpose of this study was to test the efficiency of the antibiotic resistance analysis (ARA) method under low resistance by tracking the fecal sources at Turkey Creek, Oklahoma exhibiting this condition. The resistance patterns of 772 water-isolates, tested with nine antibiotics, were analyzed by discriminant analysis (DA) utilizing a five-source library containing 2250 isolates. The library passed various representativeness tests; however, two of the pulled-sample tests suggested insufficient sampling. The resubstitution test of the library individual sources showed significant isolate misclassification with an average rate of correct classification (ARCC) of 58%. These misclassifications were explained by low antibiotic resistance (Wilcoxon test P < 0.0001). Seasonal DA of stream E. coli isolates for the pooled sources human/livestock/deer indicated that in fall, the human source dominated (P < 0.0001) at a rate of 56%, and that human and livestock respective contributions in winter (35 and 39%), spring (43 and 40%), and summer (37 and 35%) were similar. Deer scored lower (17–28%) than human and livestock at every season. The DA was revised using results from a misclassification analysis to provide a perspective of the effect caused by low antibiotic resistance and a more realistic determination of the fecal source rates at Turkey Creek. The revision increased livestock rates by 13–14% (0.04 ≤ P ≤ 0.06), and decreased human and deer by 6–7%. Negative misclassification into livestock was significant (0.04 ≤ P ≤ 0.06). Low antibiotic resistance showed the greatest effect in this category.     

Using Multiple Antibiotic Resistance and land use characteristics to determine sources of fecal coliform bacterial pollution

Multiple Antibiotic Resistance (MAR) analysis and regression modeling techniques were used to identify surface water areas impacted by fecal pollution from human sources, and to determine the effects of land use on fecal pollution in Murrells Inlet, a small, urbanized, high-salinity estuary located between Myrtle Beach and Georgetown, South Carolina. MAR analysis was performed to identify areas in the estuary that are impacted by human-source fecal pollution. Additionally, regression analysis was performed to determine if an association exists between land use and fecal coliform densities over the ten-year period from 1989 to 1998. Land-use variables were derived using Geographic Information System (GIS) techniques and were used in the regression analysis.MAR analyses were conducted by comparing the frequency and patterns of antibiotic resistance found in Escherichia coli isolates derived from surface water samples and from sewage sources in the Murrells Inlet sewage collection system. The MAR results suggest that the majority of the fecal pollution detected in the Murrells Inlet estuary may be from non-human sources, including fecal coliforms isolated from areas in close proximity to high densities of active septic tanks.A MAR Index, which measures the frequency of antibiotic resistance, was calculated for each of twenty-three water samples and nine sewage samples. The antibiotic resistance pattern comparisons were performed using cluster analysis. Although the MAR indices indicated that several surface water sites had potential human-source contamination, the cluster analysis suggests that only one sampling site had MAR patterns that were similar to those found in the sewage samples. This site was in close proximity to several large pleasure boats as well as a sewage collection system lift station, but was not near areas with active septic tanks. The results of the regression analysis also suggest that sewage sources and rainfall runoff from urbanized areas may contribute to fecal pollution in the estuary.     

海滨浴场的卫生细菌学调查及保护对策

从卫生细菌学角度，选用总大量菌群作为指标，对多年的海浴场监测结果进行了综合分析，以期了解近年来秦皇岛海滨浴场的水质变化情况，并提出了可行的保护对策。     

宜宾市三江水体粪大肠菌群污染现状调查

粪大肠茵群指数(FC)是综合评价城市污水，尤其是生活污水的一个重要指标。本文对宜宾市“三江”水体的FC进行了监测，结果表明“三江”受到了生活污水的污染。丰水期的FC指数超出我国地表水Ⅲ类标准的10倍。     

ENHANCING FECAL COLIFORM TOTAL MAXIMUM DAILY LOAD MODELS THROUGH BACTERIAL SOURCE TRACKING1

ABSTRACT: Surface water impairment by fecal coliform bacteria is a water quality issue of national scope and importance. In Virginia, more than 400 stream and river segments are on the Commonwealth's 2002 303(d) list because of fecal coliform impairment. Total maximum daily loads (TMDLs) will be developed for most of these listed streams and rivers. Information regarding the major fecal coliform sources that impair surface water quality would enhance the development of effective watershed models and improve TMDLs. Bacterial source tracking (BST) is a recently developed technology for identifying the sources of fecal coliform bacteria and it may be helpful in generating improved TMDLs. Bacterial source tracking was performed, watershed models were developed, and TMDLs were prepared for three streams (Accotink Creek, Christians Creek, and Blacks Run) on Virginia's 303(d) list of impaired waters. Quality assurance of the BST work suggests that these data adequately describe the bacteria sources that are impairing these streams. Initial comparison of simulated bacterial sources with the observed BST data indicated that the fecal coliform sources were represented inaccurately in the initial model simulation. Revised model simulations (based on BST data) appeared to provide a better representation of the sources of fecal coliform bacteria in these three streams. The coupled approach of incorporating BST data into the fecal coliform transport model appears to reduce model uncertainty and should result in an improved TMDL.     

AN EVALUATION OF THE AVAILABLE TECHNIQUES FOR ESTIMATING MISSING FECAL COLIFORM DATA1

ABSTRACT: This paper presents the findings of a study aimed at evaluating the available techniques for estimating missing fecal coliform (FC) data on a temporal basis. The techniques investigated include: linear and nonlinear regression analysis and interpolation functions, and the use of artificial neural networks (ANNs). In all, seven interpolation, two regression, and one ANN model structures were investigated. This paper also investigates the validity of a hypothesis that estimating missing FC data by developing different models using different data corresponding to different dynamics associated with different trends in the FC data may result in a better model performance. The FC data (counts/100 ml) derived from the North Fork of the Kentucky River in Kentucky were employed to calibrate and validate various models. The performance of various models was evaluated using a wide variety of standard statistical measures. The results obtained in this study are able to demonstrate that the ANNs can be preferred over the conventional techniques in estimating missing FC data in a watershed. The regression technique was not found suitable in estimating missing FC data on a temporal basis. Further, it has been found that it is possible to achieve a better model performance by first decomposing the whole data set into different categories corresponding to different dynamics and then developing separate models for separate categories rather than developing a single model for the composite data set.     

PREDICTING FECAL COLIFORM BACTERIA LEVELS IN THE CHARLES RIVER,MASSACHUSETTS, USA1

In Massachusetts, the Charles River Watershed Association conducts a regular water quality monitoring and public notification program in the Charles River Basin during the recreational season to inform users of the river's health. This program has relied on laboratory analyses of river samples for fecal coliform bacteria levels, however, results are not available until at least 24 hours after sampling. To avoid the need for laboratory analyses, ordinary least squares (OLS) and logistic regression models were developed to predict fecal coliform bacteria concentrations and the probabilities of exceeding the Massachusetts secondary contact recreation standard for bacteria based on meteorological conditions and streamflow. The OLS models resulted in adjusted R²s ranging from 50 to 60 percent. An uncertainty analysis reveals that of the total variability of fecal coliform bacteria concentrations, 45 percent is explained by the OLS regression model, 15 percent is explained by both measurement and space sampling error, and 40 percent is explained by time sampling error. Higher accuracy in future bacteria forecasting models would likely result from reductions in laboratory measurement errors and improved sampling designs.     

Molecular tools for bathing water assessment in Europe: Balancing social science research with a rapidly developing environmental science evidence-base

The use of molecular tools, principally qPCR, versus traditional culture-based methods for quantifying microbial parameters (e.g., Fecal Indicator Organisms) in bathing waters generates considerable ongoing debate at the science–policy interface. Advances in science have allowed the development and application of molecular biological methods for rapid (~2 h) quantification of microbial pollution in bathing and recreational waters. In contrast, culture-based methods can take between 18 and 96 h for sample processing. Thus, molecular tools offer an opportunity to provide a more meaningful statement of microbial risk to water-users by providing near-real-time information enabling potentially more informed decision-making with regard to water-based activities. However, complementary studies concerning the potential costs and benefits of adopting rapid methods as a regulatory tool are in short supply. We report on findings from an international Working Group that examined the breadth of social impacts, challenges, and research opportunities associated with the application of molecular tools to bathing water regulations.     

污水深度处理流程对污染物去除效果评价方法

城市污水再生处理流程大多采用几种深度处理单元组合而成,由单个处理单元对污染物的去除效果来准确评价组合流程整体的处理效率对于工艺方案的确定和实际运行具有重要意义。在对处理过程中污染物浓度分布变化分析的基础上,建立了污水深度处理流程污染物去除效果的评价分析方法,并根据3种常用再生处理单元的实验结果,以总大肠菌群为例,评价了混凝沉淀过滤与生物活性炭和超滤联用处理流程对总大肠菌群的去除效果,计算结果表明,这种评价分析方法是准确可行的。     

Fecal coliform loadings and stocks in buttermilk bay,Massachusetts, USA,and management implications

Abundance of fecal caliform bacteria is a weak index of the presence of human pathogens in wastewater entering coastal waters. In spite of this, use of fecal caliform indices for management purposes is widespread. To gain insight into interpretation of fecal coliform data, we evaluated size of stocks of fecal coliforms in water, sediments, and sea wrack, in Buttermilk Bay, a coastal embayment in Massachusetts. Sediments contained most of the fecal coliforms. Fecal coliforms in sediments were as much as one order of magnitude more abundant than in the water column or in sea wrack. The fecal coliforms in sediments of Buttermilk Bay were so abundant that resuspension of fecal coliforms from just the top 2 cm of muddy sediments could add sufficient cells to the water column to have the whole bay exceed the federal limit of fecal coliforms for shellfishing. The major sources of fecal coliforms to the bay were water-fowls, surface runoff, groundwater, and streams. Waterfowl were the largest source of fecal coliforms during cold months; surface runoff, streams, and groundwater were most important during warm months. Redirection of surface runoff pipes is unlikely to be a very successful management action since contributions via this source are insufficient to account for the measured increases in concentrations of fecal coliforms in water. Removal of waterfowl is also unlikely to be useful, since fecal coliform concentrations leading to closures of shellfish beds and swimming areas are most frequent during warm months when waterfowl are rarest. Rates of loss of fecal caliform cells from the water column by death and tidal exchange were high. Mortality of cells was about an order of magnitude larger than losses by tidal exchange. The amounts of fecal coliforms brought into the bay by waterfowl, surface runoff, groundwater, and streams are an order of magnitude smaller than the losses by mortality and tidal removal. This implies that there is an additional source of fecal coliforms within the bay. We suggest that resuspension of the upper layers of sediments can easily account for the fecal coliforms present in the water. Fecal coliform content of water and shellfish were not correlated. In contrast, sediment and shellfish fecal coliform abundances were significantly related. Monitoring of fecal coliforms in sediments may provide a better assessment of shellfish than sampling of water. The large fecal coliform stock in sediments should be the first priority for management. Efforts ought to be directed toward the reduction of sediment fecal coliform stocks. Lowering nutrient additions to coastal water bodies may be one practical approach.