Otto D. Simmons

Concentration and Detection of Cryptosporidium Oocysts in Surface Water Samples by Method 1622 Using Ultrafiltration and Capsule Filtration

ABSTRACT The protozoan parasite Cryptosporidium parvumis known to occur widely in both source and drinking water and has caused waterborne outbreaks of gastroenteritis. To improve monitoring, the U.S. Environmental Protection Agency developed method 1622 for isolation and detection of Cryptosporidium oocysts in water. Method 1622 is performance based and involves filtration, concentration, immunomagnetic separation, fluorescent-antibody staining and 4′,6-diamidino-2-phenylindole (DAPI) counterstaining, and microscopic evaluation. The capsule filter system currently recommended for method 1622 was compared to a hollow-fiber ultrafilter system for primary concentration of C. parvum oocysts in seeded reagent water and untreated surface waters. Samples were otherwise processed according to method 1622. Rates of C. parvumoocyst recovery from seeded 10-liter volumes of reagent water in precision and recovery experiments with filter pairs were 42% (standard deviation [SD], 24%) and 46% (SD, 18%) for hollow-fiber ultrafilters and capsule filters, respectively. Mean oocyst recovery rates in experiments testing both filters on seeded surface water samples were 42% (SD, 27%) and 15% (SD, 12%) for hollow-fiber ultrafilters and capsule filters, respectively. Although C. parvum oocysts were recovered from surface waters by using the approved filter of method 1622, the recovery rates were significantly lower and more variable than those from reagent grade water. In contrast, the disposable hollow-fiber ultrafilter system was compatible with subsequent method 1622 processing steps, and it recovered C. parvum oocysts from seeded surface waters with significantly greater efficiency and reliability than the filter suggested for use in the version of method 1622 tested.

Comparing the partitioning behavior of Giardia and Cryptosporidium with that of indicator organisms in stormwater runoff

Microbial association with particles can significantly affect the fate and transport characteristics of microbes in aquatic systems as particle-associated organisms will be less mobile in the environment than their free phase (i.e. unattached) counterparts. As such, similarities or dissimilarities in the partitioning behavior of indicator organisms and pathogens may have an impact on the suitability of a particular indicator to act as a surrogate for a pathogen. This research analyzed the partitioning behavior of two pathogens (Cryptosporidium, Giardia) and several common indicator organisms (fecal coliform, Escherichia coli, Enterococci, Clostridium perfringens spores, and coliphage) in natural waters under both dry and wet weather conditions. Samples were taken from several streams in two distinct sampling phases: (i) single grab samples; and (ii) intrastorm samples obtained throughout the duration of four storms. Partitioning behavior varied by microbial type, with 15-30% of bacterial indicators (fecal coliform, E. coli, and Enterococci) associated with settleable particles compared to 50% for C. perfringens spores. Both pathogens exhibited similar levels of particle association during dry weather (roughly 30%), with increased levels observed during wet weather events (Giardia to 60% and Cryptosporidium to 40%). The settling velocities of particle-associated microbes were also estimated, with those of the bacterial indicators (fecal coliform, E. coli, and Enterococci), as well as C. perfringens spores, being similar to that of the Giardia and Cryptosporidium, suggesting these organisms may exhibit similar transport behavior. With respect to intrastorm analysis, the highest microbial concentrations, in both particle-associated and free phase, occurred during the earlier stages of a storm. The total loadings of both indicators and pathogens were also estimated over the course of individual storms.

Effects of Seeding Procedures and Water Quality on Recovery of Cryptosporidium Oocysts from Stream Water by Using U.S. Environmental Protection Agency Method 1623

ABSTRACT U.S. Environmental Protection Agency method 1623 is widely used to monitor source waters and drinking water supplies for Cryptosporidium oocysts. Matrix spikes, used to determine the effect of the environmental matrix on the methods recovery efficiency for the target organism, require the collection and analysis of two environmental samples, one for analysis of endemic oocysts and the other for analysis of recovery efficiency. A new product, ColorSeed, enables the analyst to determine recovery efficiency by using modified seeded oocysts that can be differentiated from endemic organisms in a single sample. Twenty-nine stream water samples and one untreated effluent sample from a cattle feedlot were collected in triplicate to compare modified seeding procedures to conventional seeding procedures that use viable, unmodified oocysts. Significant negative correlations were found between the average oocyst recovery and turbidity or suspended sediment; this was especially apparent in samples with turbidities greater than 100 nephelometric turbidity units and suspended sediment concentrations greater than 100 mg/liter. Cryptosporidium oocysts were found in 16.7% of the unseeded environmental samples, and concentrations, adjusted for recoveries, ranged from 4 to 80 oocysts per 10 liters. Determining recovery efficiency also provided data to calculate detection limits; these ranged from <2 to <215 oocysts per 10 liters. Recoveries of oocysts ranged from 2.0 to 61% for viable oocysts and from 3.0 to 59% for modified oocysts. The recoveries between the two seeding procedures were highly correlated (r = 0.802) and were not significantly different. Recoveries by using modified oocysts, therefore, were comparable to recoveries by using conventional seeding procedures.

Endotoxin levels at Swine farms using different waste treatment and management technologies.

Concentrated animal feeding operations (CAFOs) are a major source of airborne endotoxins, which are air pollutants that can cause adverse health effects to both on-site farmers and neighbors. Release of airborne endotoxins to the environment can be reduced using proper waste treatment and management technologies. In this study, the levels of endotoxins released from two swine CAFOs using conventional lagoon-sprayfield technology were compared to those of 15 farms using various alternative waste management technologies in North Carolina. Over a 2-year period, 236 endotoxin samples were collected from the 17 farm units and analyzed using the Limulus amebocyte lysate (LAL) test. Concentrations of airborne endotoxins near barn exhaust fans were significantly higher than at the upwind boundary of the farm and at other farm sites. For most of the study sites, mean concentrations of endotoxins at the downwind boundary of the farm were higher than those at the upwind boundary of the farm, indicating the release of endotoxins from swine CAFOs to the neighboring environment. Endotoxin levels were significantly associated with concentrations of airborne bacteria but not fungi. Environmental factors, such as temperature, relative humidity, and wind velocity, affected the levels of airborne endotoxins at the farms. Based on the ratios of airborne endotoxins in downwind and upwind samples from the farm units, at least five different alternative waste management technologies significantly reduced the release of endotoxins from swine CAFOs. These results suggest that swine CAFOs are important sources of airborne endotoxins, the levels of which can be reduced by applying more robust and effective waste management technologies.

Uncertainty analysis of the recovery of hollow-fiber ultrafiltration for multiple microbe classes from water: a Bayesian approach.

In this study, we introduce a Bayesian approach to address uncertainty of microbial recoveries from hollow-fiber ultrafilters (HFUF) and to determine any sources of uncertainty. Microbial recoveries were measured under twenty conditions, including two types of water, two types of ultrafilters, and five types of microorganisms. The probability distributions of the recoveries were approximated using Bayesian statistics with Markov chain Monte Carlo sampling after integrating the likelihood function of the recovery data and prior information about the data. Then a variance-decomposition method was used for examining influential factors on microbial recovery by HFUF. The results revealed that HFUF efficiently recovered Escherichia coli KO11, E. coli O157:H7 and bacteriophage MS2, but recoveries for Bacillus atrophaeus spores and adenovirus 41 were markedly different between source and treated waters. The uncertainty analysis indicated that the probability distributions for recoveries had dissimilar patterns under different conditions. Among these test factors, the type of microorganisms and associated interaction effects had great impacts on the recovery. To sum up, the Bayesian approach to uncertainty analysis shows advantages in evaluating the recovery of HFUF by providing its full probability distribution.

Biological Characteristics of Aerosols Emitted From A Layer Operation In Southeastern U.S.

This preliminary study was to investigate biological characteristics of aerosols emitted from a commercial layer farm (egg production farm). Bioaerosol samples were taken on this farm at five sampling locations covering emission source (inside a layer barn) and four ambient stations at four wind directions. All glass impingers (AGI) were used for the field sampling. The AGI fluid samples were plated in duplicate on Trypticase Soy Agar (TSA) for growth of bacteria and Sabouraud Dextrose Agar (SDA) for growth of fungi. The most prominent bacterial colony types were identified using a combination of methods that include recording characteristics of colony morphology; performing a Gram staining method and metabolic analyses using the Biolog system. Results from one group of bioaerosol samples at the five stations indicate that the sampling duration played an important role in accurately determining bacteria concentration in air samples; there were significant reductions in total bacteria concentrations in the samples collected from ambient stations compared to the sample collected in the layer house; the most prominent bacteria species differed among all five stations and three of the most prominent bacteria from samples taken at all five stations were gram-positive; fungal type differed from station to station.

Evaluating microbial partitioning differences under storm and dry-weather conditions

The degree to which microbes in the water column associate with particles has important implications for microbial transport in receiving waters, as well as for microbial removal via sedimentation (e.g., detention basins). In this work, microbial partitioning between the particulate and suspended (i.e. unbound) phases is explored under storm and dry weather conditions. While previous stormwater studies have documented evidence suggestive of microbial-particle attachment, these relationships have not made a distinction between the types of particles to which the microbes are attached (i.e. organic vs. inorganic) and are therefore insufficient for evaluating the impacts of partitioning on microbial fate and transport. Unattached organisms in suspension, or those attached to less dense organic particles (density 3 ), will exhibit very different transport properties than those attached to denser clay or silicate particles (density 2–3 g/cm 3 ). Given that most water quality models currently assume that all microbes exist as unattached organisms, quantitative estimates of microbial partitioning to denser particles would be particularly useful in regulatory efforts to model the location and severity of water quality impairment (e.g. TMDL).

Intra-storm variability in stormwater quality and its impacts on microbial partitioning

1 Dept. of Environmental Science and Engineering, UNC School of Public Health, Chapel Hill NC 27599-7431; Graduate Assistant; email: krometis@email.unc.edu (corresponding author) 2 Dept. of Environmental Science and Engineering, UNC School of Public Health, Chapel Hill NC 27599-7431; Assistant Professor; email: charack@email.unc.edu 3 Dept. of Environmental Science and Engineering, UNC School of Public Health, Chapel Hill NC 27599-7431; Post-doctoral researcher; email: osimmons@email.unc.edu 4 Black and Veatch International Company, Raleigh, NC, 27636; Staff Engineer; email: diltsmj@bv.com 5 Dept. of Environmental Science and Engineering, UNC School of Public Health, Chapel Hill NC 27599-7431; Professor; email: mark_sobsey@unc.edu 6 Dept. of Environmental Science and Engineering, UNC School of Public Health, Chapel Hill NC 27599-7431; Research Assistant; email: clikir@email.unc.edu