Ashantha Goonetilleke

Real-Time PCR Detection of Pathogenic Microorganisms in Roof-Harvested Rainwater in Southeast Queensland, Australia

ABSTRACT In this study, the microbiological quality of roof-harvested rainwater was assessed by monitoring the concentrations of Escherichia coli, enterococci, Clostridium perfringens, and Bacteroides spp. in rainwater obtained from tanks in Southeast Queensland, Australia. Samples were also tested using real-time PCR (with SYBR Green I dye) for the presence of potential pathogenic microorganisms. Of the 27 rainwater samples tested, 17 (63%), 21 (78%), 13 (48%), and 24 (89%) were positive for E. coli, enterococci, C. perfringens, and Bacteroides spp., respectively. Of the 27 samples, 11 (41%), 7 (26%), 4 (15%), 3 (11%), and 1 (4%) were PCR positive for the Campylobacter coli ceuE gene, the Legionella pneumophila mip gene, the Aeromonas hydrophila lip gene, the Salmonella invA gene, and the Campylobacter jejuni mapA gene. Of the 21 samples tested, 4 (19%) were positive for the Giardia lamblia β-giardin gene. The binary logistic regression model indicated a positive correlation (P < 0.02) between the presence/absence of enterococci and A. hydrophila. In contrast, the presence/absence of the remaining potential pathogens did not correlate with traditional fecal indicators. The poor correlation between fecal indicators and potential pathogens suggested that fecal indicators may not be adequate to assess the microbiological quality of rainwater and consequent health risk.

Health Risk from the Use of Roof-Harvested Rainwater in Southeast Queensland, Australia, as Potable or Nonpotable Water, Determined Using Quantitative Microbial Risk Assessment

ABSTRACT A total of 214 rainwater samples from 82 tanks were collected in urban Southeast Queensland (SEQ) in Australia and analyzed for the presence and numbers of zoonotic bacterial and protozoal pathogens using binary PCR and quantitative PCR (qPCR). Quantitative microbial risk assessment (QMRA) analysis was used to quantify the risk of infection associated with the exposure to potential pathogens from roof-harvested rainwater used as potable or nonpotable water. Of the 214 samples tested, 10.7%, 9.8%, 5.6%, and 0.4% were positive for the Salmonella invA, Giardia lamblia β-giardin, Legionella pneumophila mip, and Campylobacter jejuni mapA genes, respectively. Cryptosporidium parvum oocyst wall protein (COWP) could not be detected. The estimated numbers of Salmonella, G. lamblia, and L. pneumophila organisms ranged from 6.5 × 101 to 3.8 × 102 cells, 0.6 × 10° to 3.6 × 10° cysts, and 6.0 × 101 to 1.7 × 102 cells per 1,000 ml of water, respectively. Six risk scenarios were considered for exposure to Salmonella spp., G. lamblia, and L. pneumophila. For Salmonella spp. and G. lamblia, these scenarios were (i) liquid ingestion due to drinking of rainwater on a daily basis, (ii) accidental liquid ingestion due to hosing twice a week, (iii) aerosol ingestion due to showering on a daily basis, and (iv) aerosol ingestion due to hosing twice a week. For L. pneumophila, these scenarios were (i) aerosol inhalation due to showering on a daily basis and (ii) aerosol inhalation due to hosing twice a week. The risk of infection from Salmonella spp., G. lamblia, and L. pneumophila associated with the use of rainwater for showering and garden hosing was calculated to be well below the threshold value of one extra infection per 10,000 persons per year in urban SEQ. However, the risk of infection from ingesting Salmonella spp. and G. lamblia via drinking exceeded this threshold value and indicated that if undisinfected rainwater is ingested by drinking, then the incidences of the gastrointestinal diseases salmonellosis and giardiasis are expected to range from 9.8 × 10° to 5.4 × 101 (with a mean of 1.2 × 101 from Monte Carlo analysis) and from 1.0 × 101 to 6.5 × 101 cases (with a mean of 1.6 × 101 from Monte Carlo analysis) per 10,000 persons per year, respectively, in urban SEQ. Since this health risk seems higher than that expected from the reported incidences of gastroenteritis, the assumptions used to estimate these infection risks are critically examined. Nonetheless, it would seem prudent to disinfect rainwater for use as potable water.

Understanding the physical processes of pollutant build-up and wash-off on roof surfaces.

Pollutants originating with roof runoff can have a significant impact on urban stormwater quality. This signifies the importance of understanding pollutant processes on roof surfaces. Additionally, knowledge of pollutant processes on roof surfaces is important as roofs are used as the primary catchment surface for domestic rainwater harvesting. In recent years, rainwater harvesting has become one of the primary sustainable water management techniques to counteract the growing demand for potable water. This paper presents the outcomes of an in-depth research study into particulate matter build-up and wash-off for roof surfaces. In this research, particulate matter was considered as the indicator pollutant where the processes related to other pollutants can be predicted based on the understanding generated for particulate matter. The study outcomes confirm that the build-up process on roof surfaces is comparatively similar to road surfaces. However, particle loads collected from roofs were significantly less compared to road surfaces and much finer in texture. Wash-off from roofs also showed significant similarities to wash-off from roads. A relatively high concentration of particulate matter was noted during the initial part of storm events. Furthermore, the amount of particulate matter remaining on the roof surfaces was significantly high for less intense rain events.

Prevalence and occurrence of zoonotic bacterial pathogens in surface waters determined by quantitative PCR.

The prevalence and concentrations of Campylobacter jejuni, Salmonella spp. and enterohaemorrhagic Escherichia coli (EHEC) were investigated in surface waters in Brisbane, Australia using quantitative PCR (qPCR) based methodologies. Water samples were collected from Brisbane City Botanic Gardens (CBG) Pond, and two urban tidal creeks (i.e., Oxley Creek and Blunder Creek). Of the 32 water samples collected, 8 (25%), 1 (3%), 9 (28%), 14 (44%), and 15 (47%) were positive for C. jejuni mapA, Salmonella invA, EHEC O157 LPS, EHEC VT1, and EHEC VT2 genes, respectively. The presence/absence of the potential pathogens did not correlate with either E. coli or enterococci concentrations as determined by binary logistic regression. In conclusion, the high prevalence, and concentrations of potential zoonotic pathogens along with the concentrations of one or more fecal indicators in surface water samples indicate a poor level of microbial quality of surface water, and could represent a significant health risk to users. The results from the current study would provide valuable information to the water quality managers in terms of minimizing the risk from pathogens in surface waters.

Impacts of Traffic and Rainfall Characteristics on Heavy Metals Build-up and Wash-off from Urban Roads

An investigation into the effects of changes in urban traffic characteristics due to rapid urbanisation and the predicted changes in rainfall characteristics due to climate change on the build-up and wash-off of heavy metals was carried out in Gold Coast, Australia. The study sites encompassed three different urban land uses. Nine heavy metals commonly associated with traffic emissions were selected. The results were interpreted using multivariate data analysis and decision making tools, such as principal component analysis (PCA), fuzzy clustering (FC), PROMETHEE, and GAIA. Initial analyses established high, low, and moderate traffic scenarios as well as low, low to moderate, moderate, high, and extreme rainfall scenarios for build-up and wash-off investigations. GAIA analyses established that moderate to high traffic scenarios could affect the build-up, while moderate to high rainfall scenarios could affect the wash-off of heavy metals under changed conditions. However, in wash-off, metal concentrations in 1-75 μm fraction were found to be independent of the changes to rainfall characteristics. In build-up, high traffic activities in commercial and industrial areas influenced the accumulation of heavy metal concentrations in particulate size range from 75 - >300 μm, whereas metal concentrations in finer size range of <1-75 μm were not affected. As practical implications, solids <1 μm and organic matter from 1 - >300 μm can be targeted for removal of Ni, Cu, Pb, Cd, Cr, and Zn from build-up, while organic matter from <1 - >300 μm can be targeted for removal of Cd, Cr, Pb, and Ni from wash-off. Cu and Zn need to be removed as free ions from most fractions in wash-off.

Comparison of molecular markers to detect fresh sewage in environmental waters.

Human-specific Bacteroides HF183 (HS-HF183), human-specific Enterococci faecium esp (HS-esp), human-specific adenoviruses (HS-AVs) and human-specific polyomaviruses (HS-PVs) assays were evaluated in freshwater, seawater and distilled water to detect fresh sewage. The sewage spiked water samples were also tested for the concentrations of traditional fecal indicators (i.e., Escherichia coli, enterococci and Clostridium perfringens) and enteric viruses such as enteroviruses (EVs), sapoviruses (SVs), and torquetenoviruses (TVs). The overall host-specificity of the HS-HF183 marker to differentiate between humans and other animals was 98%. However, the HS-esp, HS-AVs and HS-PVs showed 100% host-specificity. All the human-specific markers showed >97% sensitivity to detect human fecal pollution. E. coli, enterococci and, C. perfringens were detected up to dilutions of sewage 10(-5), 10(-4) and 10(-3) respectively. HS-esp, HS-AVs, HS-PVs, SVs and TVs were detected up to dilution of sewage 10(-4) whilst EVs were detected up to dilution 10(-5). The ability of the HS-HF183 marker to detect fresh sewage was 3-4 orders of magnitude higher than that of the HS-esp and viral markers. The ability to detect fresh sewage in freshwater, seawater and distilled water matrices was similar for human-specific bacterial and viral marker. Based on our data, it appears that human-specific molecular markers are sensitive measures of fresh sewage pollution, and the HS-HF183 marker appears to be the most sensitive among these markers in terms of detecting fresh sewage. However, the presence of the HS-HF183 marker in environmental waters may not necessarily indicate the presence of enteric viruses due to their high abundance in sewage compared to enteric viruses. More research is required on the persistency of these markers in environmental water samples in relation to traditional fecal indicators and enteric pathogens.

Evaluation of multiple sewage-associated Bacteroides PCR markers for sewage pollution tracking.

The host specificity of the five published sewage-associated Bacteroides markers (i.e., HF183, BacHum, HuBac, BacH and Human-Bac) was evaluated in Southeast Queensland, Australia by testing fecal DNA samples (n=186) from 11 animal species including human fecal samples collected via influent to a sewage treatment plant (STP). All human fecal samples (n=50) were positive for all five markers indicating 100% sensitivity of these markers. The overall specificity of the HF183 markers to differentiate between humans and animals was 99%. The specificities of the BacHum and BacH markers were>94%, suggesting that these markers are suitable for the detection of sewage pollution in environmental waters in Australia. The HuBac (i.e., 63%) and Human-Bac (i.e., 79% specificity) markers performed poorly in distinguishing between the sources of human and animal fecal samples. It is recommended that the specificity of the sewage-associated markers must be rigorously tested prior to its application to identify the sources of fecal pollution in environmental waters.

Characterising metal build-up on urban road surfaces.

Reliable approaches for predicting pollutant build-up are essential for accurate urban stormwater quality modelling. Based on the in-depth investigation of metal build-up on residential road surfaces, this paper presents empirical models for predicting metal loads on these surfaces. The study investigated metals commonly present in the urban environment. Analysis undertaken found that the build-up process for metals primarily originating from anthropogenic (copper and zinc) and geogenic (aluminium, calcium, iron and manganese) sources were different. Chromium and nickel were below detection limits. Lead was primarily associated with geogenic sources, but also exhibited a significant relationship with anthropogenic sources. The empirical prediction models developed were validated using an independent data set and found to have relative prediction errors of 12-50%, which is generally acceptable for complex systems such as urban road surfaces. Also, the predicted values were very close to the observed values and well within 95% prediction interval.

Human health risk assessment of heavy metals in urban stormwater.

Toxic chemical pollutants such as heavy metals (HMs) are commonly present in urban stormwater. These pollutants can pose a significant risk to human health and hence a significant barrier for urban stormwater reuse. The primary aim of this study was to develop an approach for quantitatively assessing the risk to human health due to the presence of HMs in stormwater. This approach will lead to informed decision making in relation to risk management of urban stormwater reuse, enabling efficient implementation of appropriate treatment strategies. In this study, risks to human health from heavy metals were assessed as hazard index (HI) and quantified as a function of traffic and land use related parameters. Traffic and land use are the primary factors influencing heavy metal loads in the urban environment. The risks posed by heavy metals associated with total solids and fine solids (<150μm) were considered to represent the maximum and minimum risk levels, respectively. The study outcomes confirmed that Cr, Mn and Pb pose the highest risks, although these elements are generally present in low concentrations. The study also found that even though the presence of a single heavy metal does not pose a significant risk, the presence of multiple heavy metals could be detrimental to human health. These findings suggest that stormwater guidelines should consider the combined risk from multiple heavy metals rather than the threshold concentration of an individual species. Furthermore, it was found that risk to human health from heavy metals in stormwater is significantly influenced by traffic volume and the risk associated with stormwater from industrial areas is generally higher than that from commercial and residential areas.

Influence of rainfall and catchment characteristics on urban stormwater quality

The accuracy and reliability of urban stormwater quality modelling outcomes are important for stormwater management decision making. The commonly adopted approach where only a limited number of factors are used to predict urban stormwater quality may not adequately represent the complexity of the quality response to a rainfall event or site-to-site differences to support efficient treatment design. This paper discusses an investigation into the influence of rainfall and catchment characteristics on urban stormwater quality in order to investigate the potential areas for errors in current stormwater quality modelling practices. It was found that the influence of rainfall characteristics on pollutant wash-off is step-wise based on specific thresholds. This means that a modelling approach where the wash-off process is predicted as a continuous function of rainfall intensity and duration is not appropriate. Additionally, other than conventional catchment characteristics, namely, land use and impervious surface fraction, other catchment characteristics such as impervious area layout, urban form and site specific characteristics have an important influence on both, pollutant build-up and wash-off processes. Finally, the use of solids as a surrogate to estimate other pollutant species was found to be inappropriate. Individually considering build-up and wash-off processes for each pollutant species should be the preferred option.