Drinking Water Quality Data Research Articles

Effects of community water fluoridation on child dental caries in remote Northern Territory, Australia: a difference-in-difference analysis.

Community water fluoridation (CWF) is a cost-effective intervention to reduce dental caries at population level. This Australian study used a difference-in-difference (DiD) analysis to measure dental caries in children exposed to CWF in the Northern Territory (NT), Australia. Oral health data obtained from the NT Department of Health contained 64 399 person-year observations from 2008 to 2020, totalling 24 546 children aged 1-17 years. Drinking water quality data for fluoride levels, held by the Power and Water Corporation, were obtained for 50 remote communities and linked to the oral health dataset. The DiD analysis used a treatment group and two control groups to compare the effects of CWF on dental caries outcomes in children, measured using the decayed, missing and filled teeth (dmft/DMFT) index. The treatment group consisted of records from children residing in five remote NT communities that implemented CWF in 2014.The control 1 group included records of children residing in communities with naturally occurring fluoride in drinking water supplies at levels at or above the Department of Health policy threshold of 0.5 mg/L. The control 2 group included records of children residing in communities with naturally occurring fluoride in drinking water supplies below the level recommended by the Department of Health policy (<0.5 mg/L). The data were grouped into time periods prior to the inception of CWF in five remote communities in 2014 (pre-intervention) and after 2014 (post-intervention). Our results demonstrated that dental caries was significantly decreased for children in the treatment group following the implementation of CWF at a greater magnitude than both control groups for the same time period. Overall, children assigned to the treatment group exhibited a decline in the number of teeth affected by caries by an average of 0.28 (p=0.001). Notably, children of ages 7-10 years and 11-17 years experienced significantly greater post-intervention declines in average dmft/DMFT, by 0.32 (p=0.051) and 0.40 (p=0.012) fewer affected teeth respectively. While dental caries disproportionately impacts Aboriginal children in remote and very remote NT, it is clear that CWF produces population-level reductions in overall dental caries for these populations. Additionally, our study demonstrates the application of the DiD method in a public health policy evaluation. Our findings suggest that the longstanding policy position of the NT Department of Health on CWF has supported improvements in oral health among child populations that experience high levels of dental caries in remote NT communities.

Premilinary Assessment for Physcio-Chemical Parameters of Ground Water in and Around Gundlapochampally, Medchal Malkajgiri District Telangana

Abstract: Ground water is one of the most valuable natural sources of drinking water and various usages with increase in urbanization and industrialization, health conditions are influenced by the chemical aspects of groundwater and geology of the region. Access to wholesome drinking water remains an urgent necessity Ground water is one of the most valuable natural sources of drinking water and various usages. Within the world as it is directly related to the health. Groundwater accounts for more than 80% of the rural domestic water supply in India. The integrated ground water prospects maps are preferred by using different thematic layers like Geology, Geomorphology, Structures, Hydrology, etc. Drinking water quality data of Rural Water supply sources situated in Gundlapochampally village, Medchal district is studied for the parameters of pH, Electrical Conductivity, Total Dissolved solids, Total Hardness, Calcium Magnesium, Sodium, Potassium, Alkalinity, Acidity, Chloride, Nitrate, Floride, Bi-carbonate. The results ware compare with the drinking water standards given by World Health Organization and Bureau of Indian Standards. Thus this research work recommended that the potassium and bicarbonates Contaminated water in Gundlapochampally region is not at all fit for drinking as a solution it was suggested that the solid waste treatment plant should be setup to handle crisis.

Automated scraping and analyses of drinking water quality data

Drinking water quality data, though regularly monitored, is not available in Germany as national overview, but only decentralized from the water suppliers. On the national level, only the number of limit exceedances are reported. An overview on drinking water qualities as complete as possible however is necessary to assess and develop regulations and helpful for authorities, political decision makers, the public and the scientific community. Due to the fragmented nature of the data sources, web-scraping was used in the present study to mitigate aforementioned challenges and knowledge gaps. Data from 502 water supply areas were compiled and further evaluated. The extent and form of reported values varied strongly, as did the availability of data for the different water supply areas. The results show, that the scraped values were not close to but well below associated legal limits or guidance values. For organic parameters, the reported values were mostly below the respective limits of quantification. However, further developments are needed to cover more water supply areas in Germany and internationally.

Modeling the formation of trihalomethanes in rural and semi-urban drinking water distribution networks of Costa Rica

Chlorination is one of the most important stages in the treatment of drinking water due to its effectiveness in the inactivation of pathogenic organisms. However, the reaction between chlorine and natural organic matter (NOM) generates harmful disinfection by-products (DBPs), such as trihalomethanes (THMs). In this research, drinking water quality data was collected from the distribution networks of 19 rural and semi-urban systems that use water sources as springs, surfaces, and a mixture of both, in three provinces of Costa Rica from April 2018 to September 2019. Twelve models were developed from four data sets: all water sources, spring, surface, and a mixture of spring and surface waters. Linear, logarithmic, and exponential multivariate regression models were developed for each data set to predict the concentration of total trihalomethanes (TTHMs) in the distribution networks. Concentrations of TTHMs were found between < 0.20 and 91.31µg/L, with chloroform being the dominant species accounting for 62% of TTHMs on average. Turbidity, free residual chlorine, total organic carbon (TOC), dissolved organic carbon (DOC), and ultraviolet absorbance at 254nm (UV254) showed a significant correlation with TTHMs. In all the data sets the linear models presented the best goodness-of-fit and were moderately robust. Four models, the best of each data set, were validated with data from the same systems, and, according to the criteria of R2, standard error (SE), mean square error (MSE), and mean absolute error (MAE), spring water and mixed spring/surface water models showed a satisfactory level of explanation of the variability of the data. Moreover, the models seem to better predict TTHM concentrations below 30µg/L. These models were satisfactory and could be useful for decision-making in drinking water supply systems.

Two novelty learning models developed based on deep cascade forest to address the environmental imbalanced issues: A case study of drinking water quality prediction

Environmental quality data sets are typically imbalanced, because environmental pollution events are rarely observed in daily life. Prediction of imbalanced data sets is a major challenge in machine learning. Our recent work has shown deep cascade forest (DCF), as a base learning model, is promising to be recommended for environmental quality prediction. Although some traditional models were improved by introducing the cost matrix, little is known about whether cost matrix could enhance the prediction performance of DCF. Additionally, feature extraction is also an important way to potentially improve the model's ability to predict the imbalanced data. Here, we developed two novelty learning models based on DCF: cost-sensitive DCF (CS-DCF) and DCF that combines unsupervised learning models and greedy methods (USM-DCF-G). Subsequently, CS-DCF and USM-DCF-G were successfully verified by an imbalanced drinking water quality data set. Our data presented both CS-DCF and USM-DCF-G show better prediction performance than that of DCF alone did. In particular, USM-DCF-G shows the best performance with the highest F1-score (95.12 ± 2.56%), after feature extraction and selection by using unsupervised learning models and greedy methods. Thus, the two learning models, especially USM-DCF-G, were promising learning models to address environmental imbalanced issues and accurately predict environmental quality.

From data to decisions: understanding information flows within regulatory water quality monitoring programs

Most countries maintain regulatory requirements for testing of drinking water supplies to guide treatment procedures and ensure safe water delivery to consumers. It is unclear, however, if water quality data are always used effectively, particularly in low-resource settings. Efforts to improve the use of water quality data will benefit from a comprehensive understanding of existing systems for managing and sharing information. This study evaluates the methods used to organize, analyze, and transmit drinking water quality data among 26 water supplier or surveillance institutions and two regulatory agencies in six countries of sub-Saharan Africa. Following extensive qualitative and quantitative data collection, we developed data flow diagrams to map formal and informal water quality networks. We found high levels of similarities between the information systems established by different institutions operating under different regulatory structures. We determined that the key barriers to information flows were the limited aggregation and analysis of data and the poor enforcement of data sharing requirements. Our results suggest that broad reforms are necessary to improve the use of these water quality data to manage water safety. These measures could include strengthening enforcement of testing and reporting, building staff capacity for managing and using data, and integrating collection of water quality data with other information systems.

Chemometric analysis of drinking water quality parameters of Sagar city, Madhya Pradesh, India

AbstractThe present study uses numerous chemometric techniques to evaluate and interpret a water quality data obtained from the drinking water resources namely municipal water (supplied by Rajghat dam on Bewas River), bore well, ground water of Sagar city, a divisional headquarter of Madhya Pradesh, India. Data was collected from May 2018 to June 2019 for 10 parameters used to assess the status of the water quality. Water quality was monitored at 15 sampling stations along the entire district. The data were analyzed using chemometric analysis such as principal component analysis, correlation matrix, multivariate linear regression analysis and hierarchical cluster analysis that reduced the data dimensions for better interpretation. Results of statistical analysis expressed that slightly higher value of BOD in some areas due to sewage contamination, need of chlorination treatment required at those places. This study also presents the value of diverse statistical methods for assessment and analysis of drinking water quality data for the reason of monitoring the effectiveness of water resource management. The study indicated that the maximum quality parameters of drinking water is in permissible limits of WHO and IS: 10500 guidelines on entire study places.

Nitrate in drinking water and colorectal cancer risk: A nationwide population-based cohort study.

Nitrate in drinking water may increase risk of colorectal cancer due to endogenous transformation into carcinogenic N-nitroso compounds. Epidemiological studies are few and often challenged by their limited ability of estimating long-term exposure on a detailed individual level. We exploited population-based health register data, linked in time and space with longitudinal drinking water quality data, on an individual level to study the association between long-term drinking water nitrate exposure and colorectal cancer (CRC) risk. Individual nitrate exposure was calculated for 2.7 million adults based on drinking water quality analyses at public waterworks and private wells between 1978 and 2011. For the main analyses, 1.7 million individuals with highest exposure assessment quality were included. Follow-up started at age 35. We identified 5,944 incident CRC cases during 23 million person-years at risk. We used Cox proportional hazards models to estimate hazard ratios (HRs) of nitrate exposure on the risk of CRC, colon and rectal cancer. Persons exposed to the highest level of drinking water nitrate had an HR of 1.16 (95% CI: 1.08-1.25) for CRC compared with persons exposed to the lowest level. We found statistically significant increased risks at drinking water levels above 3.87 mg/L, well below the current drinking water standard of 50 mg/L. Our results add to the existing evidence suggesting increased CRC risk at drinking water nitrate concentrations below the current drinking water standard. A discussion on the adequacy of the drinking water standard in regards to chronic effects is warranted.

Drinking water nitrate estimation at household-level in Danish population-based long-term epidemiologic studies

This study presents an approach making drinking water quality data from the Danish national geodatabase Jupiter available for epidemiological studies on long-term health effects of drinking water quality. Drinking water quality was assigned to all Danish households using spatial methods, and the related uncertainty due to sampling density was identified. Nitrate was used as an example contaminant. From 1978, 98% of all Danish households were geocoded with their precise location, yielding a total of 69 million evaluated household-years. Households supplied by a private well (4% of all household-years) were identified; the remaining majority was supplied by public waterworks. Water supply areas were connected to the Jupiter geodatabase to estimate drinking water quality at publicly supplied households. For privately supplied households, the exposure estimate had a substantially higher uncertainty, with 52% of household-years never being sampled, compared with 1% of publicly supplied household-years. For the 18% of all household-years with no nitrate samples, concentrations were estimated by interpolation and an uncertainty score based on the closest nitrate measurement was introduced. While nitrate was used as an example contaminant, the proposed approach is generic and can be used for all monitored drinking water parameters, after preprocessing and validation of the specific data and assumptions.

Development of a Web-based tool to collect and display water system customer service areas for public health action.

Significant illness is associated with biological contaminants in drinking water, but little is known about health effects from low levels of chemical contamination in drinking water. To examine these effects in epidemiological studies, the sources of drinking water of study populations need to be known. The California Environmental Health Tracking Program developed an online application that would collect data on the geographic location of public water system (PWS) customer service areas in California, which then could be linked to demographic and drinking water quality data. We deployed the Water Boundary Tool (WBT), a Web-based geospatial crowdsourcing application that can manage customer service boundary data for each PWS in California and can track changes over time. We also conducted a needs assessment for expansion to other states. The WBT was designed for water system operators, local and state regulatory agencies, and government entities. Since its public launch in 2012, the WBT has collected service area boundaries for about 2300 individual PWS, serving more than 90% of the California population. Results of the needs assessment suggest interest and utility for deploying such a tool among states lacking statewide PWS service area boundary data. Although the WBT data set is incomplete, it has already been used for a variety of applications, including fulfilling legislatively mandated reporting requirements and linking customer service areas to drinking water quality data to better understand local water quality issues. Development of this tool holds promise to assist with outbreak investigations and prevention, environmental health monitoring, and emergency preparedness and response.

Nitrate exposure from drinking water in Denmark over the last 35 years

In Denmark, drinking water quality data covering the entire country for over 35 years are registered in a publicly-accessible database. These data were analysed to determine the fraction of population exposed to elevated nitrate concentrations. Data from 2,852 water supply areas from the 98 Danish municipalities were collected in one dataset. Public water supplies are extensively registered; private wells supplying only few households are neither monitored nor registered sufficiently. The study showed that 5.1% of the Danish population was exposed to nitrate concentrations 25 mg L−1 in 2012. Private well users were far more prone to exposure to elevated nitrate concentrations than consumers connected to public supplies. While the fraction exposed to elevated nitrate concentrations amongst public supply users has been decreasing since the 1970s, it has been increasing amongst private well users, leading to the hypothesis that the decrease in nitrate concentrations in drinking water is mainly due to structural changes and not improvement of the groundwater quality. A combination of this new drinking water quality map with extensive Danish health registers would permit an epidemiological study on health effects of nitrate, as long as the lack of data on private well users is addressed.

Community Drinking Water Quality Monitoring Data

Environmental Public Health Tracking (EPHT) tracks the occurrence and magnitude of environmental hazards and associated adverse health effects over time. The EPHT program has formally expanded its scope to include finished drinking water quality. Our objective was to describe the features, strengths, and limitations of using finished drinking water quality data from community water systems (CWSs) for EPHT applications, focusing on atrazine and nitrogen compounds in 8 Midwestern states. Water quality data were acquired after meeting with state partners and reviewed and merged for analysis. Data and the coding of variables, particularly with respect to censored results (nondetects), were not standardized between states. Monitoring frequency varied between CWSs and between atrazine and nitrates, but this was in line with regulatory requirements. Cumulative distributions of all contaminants were not the same in all states (Peto-Prentice test P < .001). Atrazine results were highly censored in all states (76.0%-99.3%); higher concentrations were associated with increased measurement frequency and surface water as the CWS source water type. Nitrate results showed substantial state-to-state variability in censoring (20.5%-100%) and in associations between concentrations and the CWS source water type. Statistical analyses of these data are challenging due to high rates of censoring and uncertainty about the appropriateness of parametric assumptions for time-series data. Although monitoring frequency was consistent with regulations, the magnitude of time gaps coupled with uncertainty about CWS service areas may limit linkage with health outcome data.

Assessing the Microbial Quality of Improved Drinking Water Sources: Results from the Dominican Republic

Millennium Development Goal Target 7c (to halve between 1990 and 2015 the proportion of the global population without sustainable access to safe drinking water), was celebrated as achieved in 2012. However, new studies show that we may be prematurely celebrating. Access to safe drinking water may be overestimated if microbial water quality is considered. The objective of this study was to examine the relationship between microbial drinking water quality and drinking water source in the Puerto Plata region of the Dominican Republic. This study analyzed microbial drinking water quality data from 409 households in 33 communities. Results showed that 47% of improved drinking water sources were of high to very-high risk water quality, and therefore unsafe for drinking. This study provides evidence that the current estimate of safe water access may be overly optimistic, and microbial water quality data are needed to reliably assess the safety of drinking water.

Reliability of drinking water quality data used for compliance determinations

Public water systems are required by Safe Drinking Water Act regulations to collect and analyze samples of water for contaminants from each entry point within a system, generally on a quarterly basis. The averages of the quarterly sample results are used for compliance determinations and potential treatment decisions that may require costly actions by system operators. Analysis of data reported by the US Environmental Protection Agency in 2009 identifies a high degree of uncertainty in the average (mean) of four quarterly samples. Statistical analysis of 970 datasets for 10 analytes indicated wide variation in the sample data for more than one third of the cases. Moreover, when the means were at or near the maximum contaminant level for the contaminant measured, the variability was significantly more pronounced. Limited analysis indicated that the variability is not geographically dependent and increased sampling beyond quarterly is only practical for selected contaminants.

Web enablement of a Water Safety Plan via the municipal-based electronic Water Quality Management System (eWQMS)

Despite a good legislative framework, South Africa faces significant challenges in the sustainable provision of adequate and safe water services. To improve the situation, South Africa's Department of Water Affairs (DWA) and other water sector partners undertook initiatives to assist municipalities with operation and management of water services. By way of example, in 2006, the municipal engineering oriented electronic Water Quality Management System (eWQMS) was implemented, providing municipalities with a platform for loading drinking water quality data and tracking performance of key water services management functions. Following this in 2008, DWA introduced an incentive-based regulatory programme, Blue Drop Certification (BDC), and the associated regulatory drinking water quality information system, the Blue Drop System (BDS) which is, for example, populated with data loaded by municipalities onto eWQMS. An integral part of BDC is the development of Water Safety Plans (WSPs). Due to the challenges faced by municipalities in developing WSPs, the Water Research Commission (WRC) saw a need to assist municipalities, and subsequently a generic Water Safety Plan for Small Community Water Supplies was developed. The WRC also saw the need to develop an easy-to-use WSP tool for municipalities. The eWQMS was selected as the platform for making the tool available. This paper presents the development of a web-enabled WSP tool on the eWQMS which ultimately will provide the information to the BDS.

A review on arsenic concentrations in Canadian drinking water

Recent events have increased public awareness of drinking water quality in Canada. The goal of this review was to examine how much information about arsenic (As) in Canadian drinking water is available. Provincial, territorial, and federal Web sites were searched for information about As in drinking water. Major scientific databases (PubMed, Web of Science) were searched for drinking water As information for all provinces and territories. Resulting information was examined for availability, accessibility, quality, and timeliness. Most provinces provided at least basic fact sheets about As, and several provinces provided comprehensive databases containing actual test results. The vast majority of Canadian municipal drinking water systems with As data show a concentration below 10 μg/L, the current guideline level. Several locations in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Québec, and Saskatchewan have localized elevations of As (“hotspots”, &gt;10 μg/L As); this information is available at the provincial level, but may not include exact locations nor the degree by which they exceed the current guideline limit of 10 μg/L. For other locations, however, little information is available. The lack of a centralized information source represents a significant obstacle to obtaining drinking water quality data. Although difficult to implement, a centralized and standardized source of national drinking water quality data is urgently needed to determine the effects of As and other contaminants on Canadians.

Modification and Application of the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) for the Communication of Drinking Water Quality Data in Newfoundland and Labrador

Abstract In Newfoundland and Labrador (NL), drinking water quality monitoring is conducted by the provincial government on all public water supply systems and results are communicated to communities on a quarterly basis. This paper describes the application of the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) as a communications tool for reporting the drinking water quality results. The CCME WQI simplifies the communication of results while integrating local expert opinion, without challenging the integrity of the data. The NL Department of Environment and Conservation successfully tested the use of the CCME WQI on selected drinking water quality data sets, and developed a phased approach for its implementation as a practical means of presenting available physical, chemical, organic and microbiological results to communities. The CCME WQI index categorization schema was modified by adding a new ranking category to incorporate local expert opinion. This paper describes the development of the phased approach for calculating water quality indices, the testing methodology used, the rationale for modifying the existing CCME WQI index categorization schema, and the implementation of an automated CCME WQI calculator in the provincial drinking water quality database. The paper also discusses the challenges encountered in using the CCME WQI especially with respect to incorporation of contaminants, microbiological and trihalomethanes data. The benefits and downfalls of this application are also discussed.

Problems associated with collecting drinking water quality data for community studies: a case example, Fresno County, California.

This paper discusses methodology in developing exposure data for the water supply contaminant dibromochloropropane (DBCP) in Fresno County, California. There are 532 drinking water systems (49 large and 483 small) within Fresno County plus 14,000 private wells. We determined the number of wells per system, the output per well, and the population served by each system. The task of deriving water quality estimates for each census tract was complicated by the fact that a single census tract can be served by more than one system; each system usually has more than one well; and a single well can have several episodes of testing for various contaminants. We calculated a series of weighted averages for concentrations of DBCP, arsenic, and nitrates for each census tract, using water production figures for each well as the weighting factor. Water quality data were derived from a total of 14,861 laboratory reports, although the majority did not report on all contaminants. Mean DBCP levels ranged from 0.0041 ppb to 5.7543 ppb among the census tracts. We found no correlation between DBCP levels per census tract compared to either arsenic or nitrates. We believe that we made as complete an exposure assessment as practically feasible.