National scale assessment of total trihalomethanes in Irish drinking water.

Ireland reported the highest non-compliance with respect to total trihalomethanes (TTHMs) in drinking water across the 27 European Union Member States for the year 2010. We carried out a GIS-based investigation of the links between geographical parameters and catchment land-uses with TTHMs concentrations in Irish drinking water. A high risk catchment map was created using peat presence, rainfall (>1400 mm) and slope (<5%) and overlain with a map comprising the national dataset of routinely monitored TTHM concentrations. It appeared evident from the map that the presence of peat, rainfall and slope could be used to identify catchments at high risk to TTHM exceedances. Furthermore, statistical analyses highlighted that the presence of peat soil with agricultural land was a significant driver of TTHM exceedances for all treatment types. PARAFAC analysis from three case studies identified a fluorophore indicative of reprocessed humic natural organic matter as the dominant component following treatment at the three sites. Case studies also indicated that (1) chloroform contributed to the majority of the TTHMs in the drinking water supplies and (2) the supply networks contributed to about 30 µg L-1 of TTHMs.

"Exposure Track"-The Impact of Mobile-Device-Based Mobility Patterns on Quantifying Population Exposure to Air Pollution.

Air pollution is now recognized as the world's single largest environmental and human health threat. Indeed, a large number of environmental epidemiological studies have quantified the health impacts of population exposure to pollution. In previous studies, exposure estimates at the population level have not considered spatially- and temporally varying populations present in study regions. Therefore, in the first study of it is kind, we use measured population activity patterns representing several million people to evaluate population-weighted exposure to air pollution on a city-wide scale. Mobile and wireless devices yield information about where and when people are present, thus collective activity patterns were determined using counts of connections to the cellular network. Population-weighted exposure to PM2.5 in New York City (NYC), herein termed "Active Population Exposure" was evaluated using population activity patterns and spatiotemporal PM2.5 concentration levels, and compared to "Home Population Exposure", which assumed a static population distribution as per Census data. Areas of relatively higher population-weighted exposures were concentrated in different districts within NYC in both scenarios. These were more centralized for the "Active Population Exposure" scenario. Population-weighted exposure computed in each district of NYC for the "Active" scenario were found to be statistically significantly (p < 0.05) different to the "Home" scenario for most districts. In investigating the temporal variability of the "Active" population-weighted exposures determined in districts, these were found to be significantly different (p < 0.05) during the daytime and the nighttime. Evaluating population exposure to air pollution using spatiotemporal population mobility patterns warrants consideration in future environmental epidemiological studies linking air quality and human health.

Ptaquiloside in Irish Bracken Ferns and Receiving Waters, with Implications for Land Managers.

Ptaquiloside, along with other natural phytotoxins, is receiving increased attention from scientists and land use managers. There is an urgent need to increase empirical evidence to understand the scale of phytotoxin mobilisation and potential to enter into the environment. In this study the risk of ptaquiloside to drinking water was assessed by quantifying ptaquiloside in the receiving waters at three drinking water abstraction sites across Ireland and in bracken fronds surrounding the abstraction sites. We also investigated the impact of different management regimes (spraying, cutting and rolling) on ptaquiloside concentrations at plot-scale in six locations in Northern Ireland, UK. Ptaquiloside concentrations were determined using recent advances in the use of LC-MS for the detection and quantification of ptaquiloside. The results indicate that ptaquiloside is present in bracken stands surrounding drinking water abstractions in Ireland, and ptaquiloside concentrations were also observed in the receiving waters. Furthermore, spraying was found to be the most effective bracken management regime observed in terms of reducing ptaquiloside load. Increased awareness is vital on the implications of managing land with extensive bracken stands.

Maximizing the spatial representativeness of NO2 monitoring data using a combination of local wind-based sectoral division and seasonal and diurnal correction factors.

This article describes a new methodology for increasing the spatial representativeness of individual monitoring sites. Air pollution levels at a given point are influenced by emission sources in the immediate vicinity. Since emission sources are rarely uniformly distributed around a site, concentration levels will inevitably be most affected by the sources in the prevailing upwind direction. The methodology provides a means of capturing this effect and providing additional information regarding source/pollution relationships. The methodology allows for the division of the air quality data from a given monitoring site into a number of sectors or wedges based on wind direction and estimation of annual mean values for each sector, thus optimising the information that can be obtained from a single monitoring station. The method corrects for short-term data, diurnal and seasonal variations in concentrations (which can produce uneven weighting of data within each sector) and uneven frequency of wind directions. Significant improvements in correlations between the air quality data and the spatial air quality indicators were obtained after application of the correction factors. This suggests the application of these techniques would be of significant benefit in land-use regression modelling studies. Furthermore, the method was found to be very useful for estimating long-term mean values and wind direction sector values using only short-term monitoring data. The methods presented in this article can result in cost savings through minimising the number of monitoring sites required for air quality studies while also capturing a greater degree of variability in spatial characteristics. In this way, more reliable, but also more expensive monitoring techniques can be used in preference to a higher number of low-cost but less reliable techniques. The methods described in this article have applications in local air quality management, source receptor analysis, land-use regression mapping and modelling and population exposure studies.

The effect of long-range air mass transport pathways on PM10 and NO2 concentrations at urban and rural background sites in Ireland: Quantification using clustering techniques.

The specific aims of this paper are to: (i) quantify the effects of various long range transport pathways nitrogen dioxide (NO2) and particulate matter with diameter less than 10µm (PM10) concentrations in Ireland and identify air mass movement corridors which may lead to incidences poor air quality for application in forecasting; (ii) compare the effects of such pathways at various sites; (iii) assess pathways associated with a period of decreased air quality in Ireland. The origin of and the regions traversed by an air mass 96h prior to reaching a receptor is modelled and k-means clustering is applied to create air-mass groups. Significant differences in air pollution levels were found between air mass cluster types at urban and rural sites. It was found that easterly or recirculated air masses lead to higher NO2 and PM10 levels with average NO2 levels varying between 124% and 239% of the seasonal mean and average PM10 levels varying between 103% and 199% of the seasonal mean at urban and rural sites. Easterly air masses are more frequent during winter months leading to higher overall concentrations. The span in relative concentrations between air mass clusters is highest at the rural site indicating that regional factors are controlling concentration levels. The methods used in this paper could be applied to assist in modelling and forecasting air quality based on long range transport pathways and forecast meteorology without the requirement for detailed emissions data over a large regional domain or the use of computationally demanding modelling techniques.

Assessment of the impact of traditional septic tank soakaway systems on water quality in Ireland.

One of the key threats to groundwater and surface water quality in Ireland is the impact of poorly designed, constructed or maintained on-site wastewater treatment systems. An extensive study was carried out to quantify the impact of existing sites on water quality. Six existing sites, consisting of a traditional septic tank and soakaway system, located in various ranges of subsoil permeabilities were identified and monitored to determine how well they function under varying subsoil and weather conditions. The preliminary results of the chemical and microbiological pollutant attenuation in the subsoil of the systems have been assessed and treatment performance evaluated, as well as impact on local surface water and groundwater quality. The source of any faecal contamination detected in groundwater, nearby surface water and effluent samples was confirmed by microbial source tracking. From this, it can be seen that the transport and treatment of percolate vary greatly depending on the permeability and composition of the subsoil.

The use of sterol profiles, supported with other faecal source tracking methods, to apportion septic tanks contamination in rural catchments.

Identifying the origin of faecal pollution in water is needed for effective water management decisions to protect both human health and aquatic ecosystems. Traditionally used indicators of faecal contamination, such as E. coli, only indicate pollution from warm-blooded animals and not the specific source of contamination; hence, more source specific tracers are required. The study has focussed on separating the two main sources of contaminants within rural catchments in Ireland, agriculture and on-site wastewater treatment systems (predominantly septic tanks). While human-specific effluent tracers may assist in identifying potential pathways from individual septic tanks to surface waters, it is difficult to quantify the cumulative impact of such systems at a catchment scale. This study has investigated faecal sterols as a method to quantify such an impact on four small catchments in areas of low subsoil permeability with high densities of septic tanks. The results demonstrate the usefulness of faecal sterols which provide a quantitative evaluation of the respective impact between agricultural pasture inputs and on-site effluent showing differences between the four catchments. The study also highlights the need to derive more specific local reference sterol profile databases for specific countries or regions, using local source material of animal faeces and effluent. Two intensive sampling campaigns on the four catchments then used faecal sterols in parallel to fluorescent whitening compounds (FWCs), caffeine, artificial sweeteners and selected pharmaceuticals to gain further insights and confirmation about contamination hotspots as well as providing comparison between the different parameters. The combination of sterols, FWCs, caffeine, acesulfame and cyclamate has proven suitable to provide an estimate of the extent of human contamination in these rural catchments and has yielded additional information about potential pollution pathways and proximity of contamination. Overall, this methodology can help to facilitate a targeted and effective water management in such catchments.

Unregulated private wells in the Republic of Ireland: consumer awareness, source susceptibility and protective actions.

While the safety of public drinking water supplies in the Republic of Ireland is governed and monitored at both local and national levels, there are currently no legislative tools in place relating to private supplies. It is therefore paramount that private well owners (and users) be aware of source specifications and potential contamination risks, to ensure adequate water quality. The objective of this study was to investigate the level of awareness among private well owners in the Republic of Ireland, relating to source characterisation and groundwater contamination issues. This was undertaken through interviews with 245 private well owners. Statistical analysis indicates that respondents' source type significantly influences owner awareness, particularly regarding well construction and design parameters. Water treatment, source maintenance and regular water quality testing are considered the three primary "protective actions" (or "stewardship activities") to consumption of contaminated groundwater and were reported as being absent in 64%, 72% and 40% of cases, respectively. Results indicate that the level of awareness exhibited by well users did not significantly affect the likelihood of their source being contaminated (source susceptibility); increased awareness on behalf of well users was associated with increased levels of protective action, particularly among borehole owners. Hence, lower levels of awareness may result in increased contraction of waterborne illnesses where contaminants have entered the well. Accordingly, focused educational strategies to increase awareness among private groundwater users are advocated in the short-term; the development and introdiction of formal legislation is recommended in the long-term, including an integrated programme of well inspections and risk assessments.

Investigation of water consumption patterns among Irish adults for waterborne quantitative microbial risk assessment (QMRA).

Microbial and chemical contamination of drinking water supplies can cause human health problems. Microbial pathogens are of primary concern and quantitative microbial risk assessment (QMRA) is employed to assess and manage the risks they pose. Estimates of drinking water consumption, or distributions, are required to assess levels of waterborne pathogen exposure. To establish distributions for the Irish population, water consumption data were collected from 549 rural survey respondents. A further 110 participants completed a five-day water consumption diary. Average daily consumption of tap-water among the primarily rural-dwelling questionnaire respondents was 940 ml day(-1) (SD 670 ml day(-1)) and 1,186 ml day(-1) (SD 701 ml day(-1)) among the principally urban-dwelling diary respondents. Both mean figures are significantly less than the 2,000 ml day(-1) default figure currently used for QRMA; therefore its use may lead to overestimation of the waterborne health burden. As the observed daily consumption difference between rural and urban residents is statistically significant, use of separate consumption distributions for QMRA is advocated. Although males reported higher daily tap-water consumption rates than females, these differences were insignificant, so separate consumption distributions are not considered necessary. A log-normal distribution provides the most adequate fit for daily tap-water intake (ml day(-1)) within both datasets.

An assessment of contamination fingerprinting techniques for determining the impact of domestic wastewater treatment systems on private well supplies.

Private wells in Ireland and elsewhere have been shown to be prone to microbial contamination with the main suspected sources being practices associated with agriculture and domestic wastewater treatment systems (DWWTS). While the microbial quality of private well water is commonly assessed using faecal indicator bacteria, such as Escherichia coli, such organisms are not usually source-specific, and hence cannot definitively conclude the exact origin of the contamination. This research assessed a range of different chemical contamination fingerprinting techniques (ionic ratios, artificial sweeteners, caffeine, fluorescent whitening compounds, faecal sterol profiles and pharmaceuticals) as to their use to apportion contamination of private wells between human wastewater and animal husbandry wastes in rural areas of Ireland. A one-off sampling and analysis campaign of 212 private wells found that 15% were contaminated with E. coli. More extensive monitoring of 24 selected wells found 58% to be contaminated with E. coli on at least one occasion over a 14-month period. The application of fingerprinting techniques to these monitored wells found that the use of chloride/bromide and potassium/sodium ratios is a useful low-cost fingerprinting technique capable of identifying impacts from human wastewater and organic agricultural contamination, respectively. The artificial sweetener acesulfame was detected on several occasions in a number of monitored wells, indicating its conservative nature and potential use as a fingerprinting technique for human wastewater. However, neither fluorescent whitening compounds nor caffeine were detected in any wells, and faecal sterol profiles proved inconclusive, suggesting limited suitability for the conditions investigated.

Assessing the Impact of Vehicle Speed Limits and Fleet Composition on Air Quality Near a School.

Traffic is a major source of urban air pollution that affects health, especially among children. As lower speed limits are commonly applied near schools in many cities, and different governments have different policies on vehicle fleet composition, this research estimated how different speed limits and fleet emissions affect air quality near a primary school. Based on data of traffic, weather, and background air quality records in Dublin from 2013, traffic, emission, and dispersion models were developed to assess the impact of different speed limits and fleet composition changes against current conditions. Outside the school, hypothetical speed limit changes from 30 km/h to 50 km/h could reduce the concentration of NO2 and PM10 by 3% and 2%; shifts in the fleet from diesel to petrol vehicles could reduce these pollutants by 4% and 3% but would increase the traffic-induced concentrations of CO and Benzene by 63% and 35%. These changes had significantly larger impacts on air quality on streets with higher pollutant concentrations. Findings suggest that both road safety and air quality should be considered when determining speed limits. Furthermore, fleet composition has different impacts on different pollutants and there are no clear benefits associated with incentivising either diesel or petrol engine vehicles.

Using microbiological tracers to assess the impact of winter land use restrictions on the quality of stream headwaters in a small catchment.

Diverse land use activities can elevate risk of microbiological contamination entering stream headwaters. Spatially distributed water quality monitoring carried out across a 17 km(2) agricultural catchment aimed to characterize microbiological contamination reaching surface water and investigate whether winter agricultural land use restrictions proved effective in addressing water quality degradation. Combined flow and concentration data revealed no significant difference in fecal indicator organism (FIO) fluxes in base flow samples collected during the open and prohibited periods for spreading organic fertilizer, while relative concentrations of Escherichia coli, fecal streptococci and sulfite reducing bacteria indicated consistently fresh fecal pollution reached aquatic receptors during both periods. Microbial source tracking, employing Bacteroides 16S rRNA gene markers, demonstrated a dominance of bovine fecal waste in river water samples upstream of a wastewater treatment plant discharge during open periods. This contrasted with responses during prohibited periods where human-derived signatures dominated. Differences in microbiological signature, when viewed with hydrological data, suggested that increasing groundwater levels restricted vertical infiltration of effluent from on-site wastewater treatment systems and diverted it to drains and surface water. Study results reflect seasonality of contaminant inputs, while suggesting winter land use restrictions can be effective in limiting impacts of agricultural wastes to base flow water quality.

Comparison of particulate matter dose and acute heart rate variability response in cyclists, pedestrians, bus and train passengers.

Exposure to airborne particulate matter (PM) has been linked to cardiovascular morbidity and mortality. Heart rate variability (HRV) is a measure of the change in cardiac autonomic function, and consistent links between PM exposure and decreased HRV have been documented in studies. This study quantitatively assesses the acute relative variation of HRV with predicted PM dose in the lungs of commuters. Personal PM exposure, HR and HRV were monitored in 32 young healthy cyclists, pedestrians, bus and train passengers. Inhaled and lung deposited PM doses were determined using a numerical model of the human respiratory tract which accounted for varying ventilation rates between subjects and during commutes. Linear mixed models were used to examine air pollution dose and HRV response relationships in 122 commutes sampled. Elevated PM2.5 and PM10 inhaled and lung deposited doses were significantly (p<0.05) associated with decreased HRV indices. Percent declines in SDNN (standard deviation of normal RR intervals) relative to resting, due to an inter-quartile range increase in PM10 lung deposited dose were stronger in cyclists (-6.4%, 95% CI: -11.7, -1.3) and pedestrians (-5.8%, 95% CI: -11.3, -0.5), in comparison to bus (-3.2%, 95% CI: -6.4, -0.1) and train (-1.8%, -7.5, 3.8) passengers. A similar trend was observed in the case of PM2.5 lung deposited dose and results for rMSSD (the square root of the squared differences of successive normal RR intervals) followed similar trends to SDNN. Inhaled and lung deposited doses accounting for varying ventilation rates between modes, individuals and during commutes have been neglected in other studies relating PM to HRV. The findings here indicate that exercise whilst commuting has an influence on inhaled PM and PM lung deposited dose, and these were significantly associated with acute declines in HRV, especially in pedestrians and cyclists.

Groundwater source contamination mechanisms: physicochemical profile clustering, risk factor analysis and multivariate modelling.

An integrated domestic well sampling and "susceptibility assessment" programme was undertaken in the Republic of Ireland from April 2008 to November 2010. Overall, 211 domestic wells were sampled, assessed and collated with local climate data. Based upon groundwater physicochemical profile, three clusters have been identified and characterised by source type (borehole or hand-dug well) and local geological setting. Statistical analysis indicates that cluster membership is significantly associated with the prevalence of bacteria (p=0.001), with mean Escherichia coli presence within clusters ranging from 15.4% (Cluster-1) to 47.6% (Cluster-3). Bivariate risk factor analysis shows that on-site septic tank presence was the only risk factor significantly associated (p<0.05) with bacterial presence within all clusters. Point agriculture adjacency was significantly associated with both borehole-related clusters. Well design criteria were associated with hand-dug wells and boreholes in areas characterised by high permeability subsoils, while local geological setting was significant for hand-dug wells and boreholes in areas dominated by low/moderate permeability subsoils. Multivariate susceptibility models were developed for all clusters, with predictive accuracies of 84% (Cluster-1) to 91% (Cluster-2) achieved. Septic tank setback was a common variable within all multivariate models, while agricultural sources were also significant, albeit to a lesser degree. Furthermore, well liner clearance was a significant factor in all models, indicating that direct surface ingress is a significant well contamination mechanism. Identification and elucidation of cluster-specific contamination mechanisms may be used to develop improved overall risk management and wellhead protection strategies, while also informing future remediation and maintenance efforts.

Application of nonparametric regression methods to study the relationship between NO2 concentrations and local wind direction and speed at background sites.

Background concentrations of nitrogen dioxide (NO(2)) are not constant but vary temporally and spatially. The current paper presents a powerful tool for the quantification of the effects of wind direction and wind speed on background NO(2) concentrations, particularly in cases where monitoring data are limited. In contrast to previous studies which applied similar methods to sites directly affected by local pollution sources, the current study focuses on background sites with the aim of improving methods for predicting background concentrations adopted in air quality modelling studies. The relationship between measured NO(2) concentration in air at three such sites in Ireland and locally measured wind direction has been quantified using nonparametric regression methods. The major aim was to analyse a method for quantifying the effects of local wind direction on background levels of NO(2) in Ireland. The method was expanded to include wind speed as an added predictor variable. A Gaussian kernel function is used in the analysis and circular statistics employed for the wind direction variable. Wind direction and wind speed were both found to have a statistically significant effect on background levels of NO(2) at all three sites. Frequently environmental impact assessments are based on short term baseline monitoring producing a limited dataset. The presented non-parametric regression methods, in contrast to the frequently used methods such as binning of the data, allow concentrations for missing data pairs to be estimated and distinction between spurious and true peaks in concentrations to be made. The methods were found to provide a realistic estimation of long term concentration variation with wind direction and speed, even for cases where the data set is limited. Accurate identification of the actual variation at each location and causative factors could be made, thus supporting the improved definition of background concentrations for use in air quality modelling studies.