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Literature review: Water quality and public health problems in developing countries

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Eni Muryani; Literature review: Water quality and public health problems in developing countries. AIP Conf. Proc. 23 November 2021; 2363 (1): 050020. https://doi.org/10.1063/5.0061561

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Water’s essential function as drinking water is a significant daily intake. Contamination by microorganisms (bacteria or viruses) on water sources and drinking water supplies is a common cause in developing countries like Indonesia. This paper will discuss the sources of clean water and drinking water and their problems in developing countries; water quality and its relation to public health problems in these countries; and what efforts that can be make to improve water quality. The method used is a literature review from the latest journals. Water quality is influenced by natural processes and human activities around the water source Among developed countries, public health problems caused by low water quality, such as diarrhea, dysentery, cholera, typhus, skin itching, kidney disease, hypertension, heart disease, cancer, and other diseases the nervous system. Good water quality has a role to play in decreasing the number of disease sufferers or health issues due to drinking and the mortality rate. The efforts made to improve water quality and public health are by improving WASH (water, sanitation, and hygiene) facilities and infrastructure and also WASH education.

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Review article, effects of water pollution on human health and disease heterogeneity: a review.

• 1 Research Center for Economy of Upper Reaches of the Yangtse River/School of Economics, Chongqing Technology and Business University, Chongqing, China
• 2 School of Economics and Management, Huzhou University, Huzhou, China

Background: More than 80% of sewage generated by human activities is discharged into rivers and oceans without any treatment, which results in environmental pollution and more than 50 diseases. 80% of diseases and 50% of child deaths worldwide are related to poor water quality.

Methods: This paper selected 85 relevant papers finally based on the keywords of water pollution, water quality, health, cancer, and so on.

Results: The impact of water pollution on human health is significant, although there may be regional, age, gender, and other differences in degree. The most common disease caused by water pollution is diarrhea, which is mainly transmitted by enteroviruses in the aquatic environment.

Discussion: Governments should strengthen water intervention management and carry out intervention measures to improve water quality and reduce water pollution’s impact on human health.

Introduction

Water is an essential resource for human survival. According to the 2021 World Water Development Report released by UNESCO, the global use of freshwater has increased six-fold in the past 100 years and has been growing by about 1% per year since the 1980s. With the increase of water consumption, water quality is facing severe challenges. Industrialization, agricultural production, and urban life have resulted in the degradation and pollution of the environment, adversely affecting the water bodies (rivers and oceans) necessary for life, ultimately affecting human health and sustainable social development ( Xu et al., 2022a ). Globally, an estimated 80% of industrial and municipal wastewater is discharged into the environment without any prior treatment, with adverse effects on human health and ecosystems. This proportion is higher in the least developed countries, where sanitation and wastewater treatment facilities are severely lacking.

Sources of Water Pollution

Water pollution are mainly concentrated in industrialization, agricultural activities, natural factors, and insufficient water supply and sewage treatment facilities. First, industry is the main cause of water pollution, these industries include distillery industry, tannery industry, pulp and paper industry, textile industry, food industry, iron and steel industry, nuclear industry and so on. Various toxic chemicals, organic and inorganic substances, toxic solvents and volatile organic chemicals may be released in industrial production. If these wastes are released into aquatic ecosystems without adequate treatment, they will cause water pollution ( Chowdhary et al., 2020 ). Arsenic, cadmium, and chromium are vital pollutants discharged in wastewater, and the industrial sector is a significant contributor to harmful pollutants ( Chen et al., 2019 ). With the acceleration of urbanization, wastewater from industrial production has gradually increased. ( Wu et al., 2020 ). In addition, water pollution caused by industrialization is also greatly affected by foreign direct investment. Industrial water pollution in less developed countries is positively correlated with foreign direct investment ( Jorgenson, 2009 ). Second, water pollution is closely related to agriculture. Pesticides, nitrogen fertilizers and organic farm wastes from agriculture are significant causes of water pollution (RCEP, 1979). Agricultural activities will contaminate the water with nitrates, phosphorus, pesticides, soil sediments, salts and pathogens ( Parris, 2011 ). Furthermore, agriculture has severely damaged all freshwater systems in their pristine state ( Moss, 2008 ). Untreated or partially treated wastewater is widely used for irrigation in water-scarce regions of developing countries, including China and India, and the presence of pollutants in sewage poses risks to the environment and health. Taking China as an example, the imbalance in the quantity and quality of surface water resources has led to the long-term use of wastewater irrigation in some areas in developing countries to meet the water demand of agricultural production, resulting in serious agricultural land and food pollution, pesticide residues and heavy metal pollution threatening food safety and Human Health ( Lu et al., 2015 ). Pesticides have an adverse impact on health through drinking water. Comparing pesticide use with health life Expectancy Longitudinal Survey data, it was found that a 10% increase in pesticide use resulted in a 1% increase in the medical disability index over 65 years of age ( Lai, 2017 ). The case of the Musi River in India shows a higher incidence of morbidity in wastewater-irrigated villages than normal-water households. Third, water pollution is related to natural factors. Taking Child Loess Plateau as an example, the concentration of trace elements in water quality is higher than the average world level, and trace elements come from natural weathering and manufacture causes. Poor river water quality is associated with high sodium and salinity hazards ( Xiao et al., 2019 ). The most typical water pollution in the middle part of the loess Plateau is hexavalent chromium pollution, which is caused by the natural environment and human activities. Loess and mudstone are the main sources, and groundwater with high concentrations of hexavalent chromium is also an important factor in surface water pollution (He et al., 2020). Finally, water supply and sewage treatment facilities are also important factors affecting drinking water quality, especially in developing countries. In parallel with China rapid economic growth, industrialization and urbanization, underinvestment in basic water supply and treatment facilities has led to water pollution, increased incidence of infectious and parasitic diseases, and increased exposure to industrial chemicals, heavy metals and algal toxins ( Wu et al., 1999 ). An econometric model predicts the impact of water purification equipment on water quality and therefore human health. When the proportion of household water treated with water purification equipment is reduced from 100% to 90%, the expected health benefits are reduced by up to 96%.. When the risk of pretreatment water quality is high, the decline is even more significant ( Brown and Clasen, 2012 ).

To sum up, water pollution results from both human and natural factors. Various human activities will directly affect water quality, including urbanization, population growth, industrial production, climate change, and other factors ( Halder and Islam, 2015 ) and religious activities ( Dwivedi et al., 2018 ). Improper disposal of solid waste, sand, and gravel is also one reason for decreasing water quality ( Ustaoğlua et al., 2020 ).

Impact of Water Pollution on Human Health

Unsafe water has severe implications for human health. According to UNESCO 2021 World Water Development Report , about 829,000 people die each year from diarrhea caused by unsafe drinking water, sanitation, and hand hygiene, including nearly 300,000 children under the age of five, representing 5.3 percent of all deaths in this age group. Data from Palestine suggest that people who drink municipal water directly are more likely to suffer from diseases such as diarrhea than those who use desalinated and household-filtered drinking water ( Yassin et al., 2006 ). In a comparative study of tap water, purified water, and bottled water, tap water was an essential source of gastrointestinal disease ( Payment et al., 1997 ). Lack of water and sanitation services also increases the incidence of diseases such as cholera, trachoma, schistosomiasis, and helminthiasis. Data from studies in developing countries show a clear relationship between cholera and contaminated water, and household water treatment and storage can reduce cholera ( Gundry et al., 2004 ). In addition to disease, unsafe drinking water, and poor environmental hygiene can lead to gastrointestinal illness, inhibiting nutrient absorption and malnutrition. These effects are especially pronounced for children.

Purpose of This Paper

More than two million people worldwide die each year from diarrhoeal diseases, with poor sanitation and unsafe drinking water being the leading cause of nearly 90% of deaths and affecting children the most (United Nations, 2016). More than 50 kinds of diseases are caused by poor drinking water quality, and 80% of diseases and 50% of child deaths are related to poor drinking water quality in the world. However, water pollution causes diarrhea, skin diseases, malnutrition, and even cancer and other diseases related to water pollution. Therefore, it is necessary to study the impact of water pollution on human health, especially disease heterogeneity, and clarify the importance of clean drinking water, which has important theoretical and practical significance for realizing sustainable development goals. Unfortunately, although many kinds of literature focus on water pollution and a particular disease, there is still a lack of research results that systematically analyze the impact of water pollution on human health and the heterogeneity of diseases. Based on the above background and discussion, this paper focuses on the effect of water pollution on human health and its disease heterogeneity.

Materials and Methods

Search process.

This article uses keywords such as “water,” “water pollution,” “water quality,” “health,” “diarrhea,” “skin disease,” “cancer” and “children” to search Web of Science and Google Scholar include SCI and SSCI indexed papers, research reports, and works from 1990 to 2021.

Inclusion-Exclusion Criteria and Data Extraction Process

The existing literature shows that water pollution and human health are important research topics in health economics, and scholars have conducted in-depth research. As of 30 December 2021, 104 related literatures were searched, including research papers, reviews and conference papers. Then, according to the content relevancy, 19 papers were eliminated, and 85 papers remained. The purpose of this review is to summarize the impact of water pollution on human health and its disease heterogeneity and to explore how to improve human health by improving water pollution control measures.

Information extracted from all included papers included: author, publication date, sample country, study methodology, study purpose, and key findings. All analysis results will be analyzed according to the process in Figure 1 .

FIGURE 1 . Data extraction process (PRISMA).

The relevant information of the paper is exported to the Excel database through Endnote, and the duplicates are deleted. The results were initially extracted by one researcher and then cross-checked by another researcher to ensure that all data had been filtered and reviewed. If two researchers have different opinions, the two researchers will review together until a final agreement is reached.

Quality Assessment of the Literature

The JBI Critical Appraisal Checklist was used to evaluate the quality of each paper. The JBI (Joanna Briggs Institute) key assessment tool was developed by the JBI Scientific Committee after extensive peer review and is designed for system review. All features of the study that meet the following eight criteria are included in the final summary:1) clear purpose; 2) Complete information of sample variables; 3) Data basis; 4) the validity of data sorting; 5) ethical norms; (6); 7) Effective results; 8) Apply appropriate quantitative methods and state the results clearly. Method quality is evaluated by the Yes/No questions listed in the JBI Key Assessment List. Each analysis paper received 6 out of 8.

The quality of drinking water is an essential factor affecting human health. Poor drinking water quality has led to the occurrence of water-borne diseases. According to the World Health Organization (WHO) survey, 80% of the world’s diseases and 50% of the world’s child deaths are related to poor drinking water quality, and there are more than 50 diseases caused by poor drinking water quality. The quality of drinking water in developing countries is worrying. The negative health effects of water pollution remain the leading cause of morbidity and mortality in developing countries. Different from the existing literature review, this paper mainly studies the impact of water pollution on human health according to the heterogeneity of diseases. We focuses on diarrhea, skin diseases, cancer, child health, etc., and sorts out the main effects of water pollution on human health ( Table 1 ).

TABLE 1 . Major studies on the relationship between water pollution and health.

Water Pollution and Diarrhea

Diarrhea is a common symptom of gastrointestinal diseases and the most common disease caused by water pollution. Diarrhea is a leading cause of illness and death in young children in low-income countries. Diarrhoeal diseases account for 21% of annual deaths among children under 5 years of age in developing countries ( Waddington et al., 2009 ). Many infectious agents associated with diarrhea are directly related to contaminated water ( Ahmed and Ismail, 2018 ). Parasitic worms present in non-purifying drinking water when is consumed by human beings causes diseases ( Ansari and Akhmatov., 2020 ) . It was found that treated water from water treatment facilities was associated with a lower risk of diarrhea than untreated water for all ages ( Clasen et al., 2015 ). For example, in the southern region of Brazil, a study found that factors significantly associated with an increased risk of mortality from diarrhoea included lack of plumbed water, lack of flush toilets, poor housing conditions, and overcrowded households. Households without access to piped water had a 4.8 times higher risk of infant death from diarrhea than households with access to piped water ( Victora et al., 1988 )

Enteroviruses exist in the aquatic environment. More than 100 pathogenic viruses are excreted in human and animal excreta and spread in the environment through groundwater, estuarine water, seawater, rivers, sewage treatment plants, insufficiently treated water, drinking water, and private wells ( Fong and Lipp., 2005 ). A study in Pakistan showed that coliform contamination was found in some water sources. Improper disposal of sewage and solid waste, excessive use of pesticides and fertilizers, and deteriorating pipeline networks are the main causes of drinking water pollution. The main source of water-borne diseases such as gastroenteritis, dysentery, diarrhea, and viral hepatitis in this area is the water pollution of coliform bacteria ( Khan et al., 2013 ). Therefore, the most important role of water and sanitation health interventions is to hinder the transmission of diarrheal pathogens from the environment to humans ( Waddington et al., 2009 ).

Meta-analyses are the most commonly used method for water quality and diarrhea studies. It was found that improving water supply and sanitation reduced the overall incidence of diarrhea by 26%. Among Malaysian infants, having clean water and sanitation was associated with an 82% reduction in infant mortality, especially among infants who were not breastfed ( Esrey et al., 1991 ). All water quality and sanitation interventions significantly reduced the risk of diarrhoeal disease, and water quality interventions were found to be more effective than previously thought. Multiple interventions (including water, sanitation, and sanitation measures) were not more effective than single-focus interventions ( Fewtrell and Colford., 2005 ). Water quality interventions reduced the risk of diarrhoea in children and reduced the risk of E. coli contamination of stored water ( Arnold and Colford., 2007 ). Interventions to improve water quality are generally effective in preventing diarrhoea in children of all ages and under 5. However, some trials showed significant heterogeneity, which may be due to the research methods and their conditions ( Clasen et al., 2007 ).

Water Pollution and Skin Diseases

Contrary to common sense that swimming is good for health, studies as early as the 1950s found that the overall disease incidence in the swimming group was significantly higher than that in the non-swimming group. The survey shows that the incidence of the disease in people under the age of 10 is about 100% higher than that of people over 10 years old. Skin diseases account for a certain proportion ( Stevenson, 1953 ). A prospective epidemiological study of beach water pollution was conducted in Hong Kong in the summer of 1986–1987. The study found that swimmers on Hong Kong’s coastal beaches were more likely than non-swimmers to complain of systemic ailments such as skin and eyes. And swimming in more polluted beach waters has a much higher risk of contracting skin diseases and other diseases. Swimming-related disease symptom rates correlated with beach cleanliness ( Cheung et al., 1990 ).

A study of arsenic-affected villages in the southern Sindh province of Pakistan emphasized that skin diseases were caused by excessive water quality. By studying the relationship between excessive arsenic in drinking water caused by water pollution and skin diseases (mainly melanosis and keratosis), it was found that compared with people who consumed urban low-arsenic drinking water, the hair of people who consumed high-arsenic drinking water arsenic concentration increased significantly. The level of arsenic in drinking water directly affects the health of local residents, and skin disease is the most common clinical complication of arsenic poisoning. There is a correlation between arsenic concentrations in biological samples (hair and blood) from patients with skin diseases and intake of arsenic-contaminated drinking water ( Kazi et al., 2009 ). Another Bangladesh study showed that many people suffer from scabies due to river pollution ( Hanif et al., 2020 ). Not only that, but water pollution from industry can also cause skin cancer ( Arif et al., 2020 ).

Studies using meta-analysis have shown that exposure to polluted Marine recreational waters can have adverse consequences, including frequent skin discomfort (such as rash or itching). Skin diseases in swimmers may be caused by a variety of pathogenic microorganisms ( Yau et al., 2009 ). People (swimmers and non-swimmers) exposed to waters above threshold levels of bacteria had a higher relative risk of developing skin disease, and levels of bacteria in seawater were highly correlated with skin symptoms.

Studies have also suggested that swimmers are 3.5 times more likely to report skin diseases than non-swimmers. This difference may be a “risk perception bias” at work on swimmers, who are generally aware that such exposure may lead to health effects and are more likely to detect and report skin disorders. It is also possible that swimmers exaggerated their symptoms, reporting conditions that others would not classify as true skin disorders ( Fleisher and Kay. 2006 ).

Water Pollution and Cancer

According to WHO statistics, the number of cancer patients diagnosed in 2020 reached 19.3 million, while the number of deaths from cancer increased to 10 million. Currently, one-fifth of all global fevers will develop cancer during their lifetime. The types and amounts of carcinogens present in drinking water will vary depending on where they enter: contamination of the water source, water treatment processes, or when the water is delivered to users ( Morris, 1995 ).

From the perspective of water sources, arsenic, nitrate, chromium, etc. are highly associated with cancer. Ingestion of arsenic from drinking water can cause skin cancer and kidney and bladder cancer ( Marmot et al., 2007 ). The risk of cancer in the population from arsenic in the United States water supply may be comparable to the risk from tobacco smoke and radon in the home environment. However, individual susceptibility to the carcinogenic effects of arsenic varies ( Smith et al., 1992 ). A high association of arsenic in drinking water with lung cancer was demonstrated in a northern Chilean controlled study involving patients diagnosed with lung cancer and a frequency-matched hospital between 1994 and 1996. Studies have also shown a synergistic effect of smoking and arsenic intake in drinking water in causing lung cancer ( Ferreccio et al., 2000 ). Exposure to high arsenic levels in drinking water was also associated with the development of liver cancer, but this effect was not significant at exposure levels below 0.64 mg/L ( Lin et al., 2013 ).

Nitrates are a broader contaminant that is more closely associated with human cancers, especially colorectal cancer. A study in East Azerbaijan confirmed a significant association between colorectal cancer and nitrate in men, but not in women (Maleki et al., 2021). The carcinogenic risk of nitrates is concentration-dependent. The risk increases significantly when drinking water levels exceed 3.87 mg/L, well below the current drinking water standard of 50 mg/L. Drinking water with nitrate concentrations lower than current drinking water standards also increases the risk of colorectal cancer ( Schullehner et al., 2018 ).

Drinking water with high chromium content will bring high carcinogenicity caused by hexavalent chromium to residents. Drinking water intake of hexavalent chromium experiments showed that hexavalent chromium has the potential to cause human respiratory cancer. ( Zhitkovich, 2011 ). A case from Changhua County, Taiwan also showed that high levels of chromium pollution were associated with gastric cancer incidence ( Tseng et al., 2018 ).

There is a correlation between trihalomethane (THM) levels in drinking water and cancer mortality. Bladder and brain cancers in both men and women and non-Hodgkin’s lymphoma and kidney cancer in men were positively correlated with THM levels, and bladder cancer mortality had the strongest and most consistent association with THM exposure index ( Cantor et al., 1978 ).

From the perspective of water treatment process, carcinogens may be introduced during chlorine treatment, and drinking water is associated with all cancers, urinary cancers and gastrointestinal cancers ( Page et al., 1976 ). Chlorinated byproducts from the use of chlorine in water treatment are associated with an increased risk of bladder and rectal cancer, with perhaps 5,000 cases of bladder and 8,000 cases of rectal cancer occurring each year in the United States (Morris, 1995).

The impact of drinking water pollutants on cancer is complex. Epidemiological studies have shown that drinking water contaminants, such as chlorinated by-products, nitrates, arsenic, and radionuclides, are associated with cancer in humans ( Cantor, 1997 ). Pb, U, F- and no3- are the main groundwater pollutants and one of the potential causes of cancer ( Kaur et al., 2021 ). In addition, many other water pollutants are also considered carcinogenic, including herbicides and pesticides, and fertilizers that contain and release nitrates ( Marmot et al., 2007 ). A case from Hebei, China showed that the contamination of nitrogen compounds in well water was closely related to the use of nitrogen fertilizers in agriculture, and the levels of three nitrogen compounds in well water were significantly positively correlated with esophageal cancer mortality ( Zhang et al., 2003 ).

In addition, due to the time-lag effect, the impact of watershed water pollution on cancer is spatially heterogeneous. The mortality rate of esophageal cancer caused by water pollution is significantly higher downstream than in other regions due to the impact of historical water pollution ( Xu et al., 2019 ). A study based on changes in water quality in the watershed showed that a grade 6 deterioration in water quality resulted in a 9.3% increase in deaths from digestive cancer. ( Ebenstein, 2012 ).

Water Pollution and Child Health

Diarrhea is a common disease in children. Diarrhoeal diseases (including cholera) kill 1.8 million people each year, 90 per cent of them children under the age of five, mostly in developing countries. 88% of diarrhoeal diseases are caused by inadequate water supply, sanitation and hygiene (Team, 2004). A large proportion of these are caused by exposure to microbially infected water and food, and diarrhea in infants and young children can lead to malnutrition and reduced immune resistance, thereby increasing the likelihood of prolonged and recurrent diarrhea ( Marino, 2007 ). Pollution exposure experienced by children during critical periods of development is associated with height loss in adulthood ( Zaveri et al., 2020 ). Diseases directly related to water and sanitation, combined with malnutrition, also lead to other causes of death, such as measles and pneumonia. Child malnutrition and stunting due to inadequate water and sanitation will continue to affect more than one-third of children in the world ( Bartlett, 2003 ). A study from rural India showed that children living in households with tap water had significantly lower disease prevalence and duration ( Jalan and Ravallion, 2003 ).

In conclusion, water pollution is a significant cause of childhood diseases. Air, water, and soil pollution together killed 940,000 children worldwide in 2016, two-thirds of whom were under the age of 5, and the vast majority occurred in low- and middle-income countries ( Landrigan et al., 2018 ). The intensity of industrial organic water pollution is positively correlated with infant mortality and child mortality in less developed countries, and industrial water pollution is an important cause of infant and child mortality in less developed countries ( Jorgenson, 2009 ). In addition, arsenic in drinking water is a potential carcinogenic risk in children (García-Rico et al., 2018). Nitrate contamination in drinking water may cause goiter in children ( Vladeva et al.., 2000 ).

Discussions

This paper reviews the environmental science, health, and medical literature, with a particular focus on epidemiological studies linking water quality, water pollution, and human disease, as well as studies on water-related disease morbidity and mortality. At the same time, special attention is paid to publications from the United Nations and the World Health Organization on water and sanitation health research. The purpose of this paper is to clarify the relationship between water pollution and human health, including: The relationship between water pollution and diarrhea, the mechanism of action, and the research situation of meta-analysis; The relationship between water pollution and skin diseases, pathogenic factors, and meta-analysis research; The relationship between water pollution and cancer, carcinogenic factors, and types of cancer; The relationship between water pollution and Child health, and the major childhood diseases caused.

A study of more than 100 literatures found that although factors such as country, region, age, and gender may have different influences, in general, water pollution has a huge impact on human health. Water pollution is the cause of many human diseases, mainly diarrhoea, skin diseases, cancer and various childhood diseases. The impact of water pollution on different diseases is mainly reflected in the following aspects. Firstly, diarrhea is the most easily caused disease by water pollution, mainly transmitted by enterovirus existing in the aquatic environment. The transmission environment of enterovirus depends on includes groundwater, river, seawater, sewage, drinking water, etc. Therefore, it is necessary to prevent the transmission of enterovirus from the environment to people through drinking water intervention. Secondly, exposure to or use of heavily polluted water is associated with a risk of skin diseases. Excessive bacteria in seawater and heavy metals in drinking water are the main pathogenic factors of skin diseases. Thirdly, water pollution can pose health risks to humans through any of the three links: the source of water, the treatment of water, and the delivery of water. Arsenic, nitrate, chromium, and trihalomethane are major carcinogens in water sources. Carcinogens may be introduced during chlorine treatment from water treatment. The effects of drinking water pollution on cancer are complex, including chlorinated by-products, heavy metals, radionuclides, herbicides and pesticides left in water, etc., Finally, water pollution is an important cause of children’s diseases. Contact with microbiologically infected water can cause diarrhoeal disease in children. Malnutrition and weakened immunity from diarrhoeal diseases can lead to other diseases.

This study systematically analyzed the impact of water pollution on human health and the heterogeneity of diseases from the perspective of different diseases, focusing on a detailed review of the relationship, mechanism and influencing factors of water pollution and diseases. From the point of view of limitations, this paper mainly focuses on the research of environmental science and environmental management, and the research on pathology is less involved. Based on this, future research can strengthen research at medical and pathological levels.

In response to the above research conclusions, countries, especially developing countries, need to adopt corresponding water management policies to reduce the harm caused by water pollution to human health. Firstly, there is a focus on water quality at the point of use, with interventions to improve water quality, including chlorination and safe storage ( Gundry et al., 2004 ), and provision of treated and clean water ( Khan et al., 2013 ). Secondly, in order to reduce the impact of water pollution on skin diseases, countries should conduct epidemiological studies on their own in order to formulate health-friendly bathing water quality standards suitable for their specific conditions ( Cheung et al., 1990 ). Thirdly, in order to reduce the cancer caused by water pollution, the whole-process supervision of water quality should be strengthened, that is, the purity of water sources, the scientific nature of water treatment and the effectiveness of drinking water monitoring. Fourthly, each society should prevent and control source pollution from production, consumption, and transportation ( Landrigan et al., 2018 ). Fifthly, health education is widely carried out. Introduce environmental education, educate residents on sanitary water through newspapers, magazines, television, Internet and other media, and enhance public health awareness. Train farmers to avoid overuse of agricultural chemicals that contaminate drinking water.

Author Contributions

Conceptualization, XX|; methodology, LL; data curation, HY; writing and editing, LL; project administration, XX|.

This article is a phased achievement of The National Social Science Fund of China: Research on the blocking mechanism of the critical poor households returning to poverty due to illness, No: 20BJY057.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: water pollution, human health, disease heterogeneity, water intervention, health cost

Citation: Lin L, Yang H and Xu X (2022) Effects of Water Pollution on Human Health and Disease Heterogeneity: A Review. Front. Environ. Sci. 10:880246. doi: 10.3389/fenvs.2022.880246

Received: 21 February 2022; Accepted: 09 June 2022; Published: 30 June 2022.

Reviewed by:

Copyright © 2022 Lin, Yang and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Xiaocang Xu, [email protected]

This article is part of the Research Topic

Bioaerosol Emission Characteristics and the Epidemiological, Occupational, and Public Health Risk Assessment of Waste and Wastewater Management

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Research Article

Dissemination of Drinking Water Contamination Data to Consumers: A Systematic Review of Impact on Consumer Behaviors

* E-mail: [email protected]

Affiliation School for Policy Studies, University of Bristol, Bristol, United Kingdom

Affiliation School for Social and Community Medicine, University of Bristol, Bristol, United Kingdom

Affiliation Division of Epidemiology, School of Public Health, University of California, Berkeley, California, United States of America

• Patricia J. Lucas, 
• Christie Cabral, 
• John M. Colford Jr.

• Published: June 27, 2011
• https://doi.org/10.1371/journal.pone.0021098
• Reader Comments

Drinking water contaminated by chemicals or pathogens is a major public health threat in the developing world. Responses to this threat often require water consumers (households or communities) to improve their own management or treatment of water. One approach hypothesized to increase such positive behaviors is increasing knowledge of the risks of unsafe water through the dissemination of water contamination data. This paper reviews the evidence for this approach in changing behavior and subsequent health outcomes.

Methods/Principal Findings

A systematic review was conducted for studies where results of tests for contaminants in drinking water were disseminated to populations whose water supply posed a known health risk. Studies of any design were included where data were available from a contemporaneous comparison or control group. Using multiple sources >14,000 documents were located. Six studies met inclusion criteria (four of arsenic contamination and two of microbiological contamination). Meta-analysis was not possible in most cases due to heterogeneity of outcomes and study designs. Outcomes included water quality, change of water source, treatment of water, knowledge of contamination, and urinary arsenic. Source switching was most frequently reported: of 5 reporting studies 4 report significantly higher rates of switching (26–72%) among those who received a positive test result and a pooled risk difference was calculate for 2 studies (RD = 0.43 [CI0.4.0–0.46] 6–12 months post intervention) suggesting 43% more of those with unsafe wells switched source compared to those with safe wells. Strength of evidence is low since the comparison is between non-equivalent groups. Two studies concerning fecal contamination reported non-significant increases in point-of-use water treatment.

Despite the publication of some large cohort studies and some encouraging results the evidence base to support dissemination of contamination data to improve water management is currently equivocal. Rigorous studies on this topic are needed, ideally using common outcome measures.

Citation: Lucas PJ, Cabral C, Colford JM Jr (2011) Dissemination of Drinking Water Contamination Data to Consumers: A Systematic Review of Impact on Consumer Behaviors. PLoS ONE 6(6): e21098. https://doi.org/10.1371/journal.pone.0021098

Editor: Antje Timmer, Ludwig Maximilian University of Munich, Germany

Received: December 17, 2010; Accepted: May 20, 2011; Published: June 27, 2011

Copyright: © 2011 Lucas et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was funded by the Bill and Melinda Gates Foundation ( http://www.gatesfoundation.org/ ) with the Aquatest Project ( http://www.bris.ac.uk/aquatest/ ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Access to safe drinking water is essential for health and, some argue, a basic human right [1] . Drinking water contaminated by human and animal feces contributes significantly to diarrheal diseases, a major cause of death in developing countries [2] . Children under five and immuno-compromised adults are particularly vulnerable [3] . A recent systematic review estimates diarrhea related annual mortality in children under five to be 1.9 million globally, of which 78% (1.5 million) occurred in the developing world [4] . Chemical contamination of drinking water presents risks to a smaller global population but is a serious human health hazard for those affected [5] . Arsenic and fluoride in drinking water present the greatest health risks [6] , for example as many as 77 million people may be affected by Arsenic contamination of drinking water in Bangladesh [7] .

Much can be done to reduce the burden of disease attributable to unsafe drinking water. Estimates from meta-analyses suggest water quality interventions can reduce rates of child diarrhea morbidity by 42%, while water supply interventions have little effect [8] , [9] . There are two principal routes to improving the quality of consumed water: improving water quality at the source by better community management, or improving water quality in the home through ‘point-of-use’ (POU) treatment. The high cost of repeated multiple acts required to maintain high water quality combined with a low perceived threat have been observed as a possible explanation for the long- term failure of safe water interventions [10] . Moreover, in the developing world in locations where formal water supplies are of variable quality [11] and informal supplies abound, water consumers are unlikely to know which sources are contaminated and when POU treatment is necessary. The idea has emerged that testing water for contaminants (both chemical and microbiological) and disseminating the results to consumers might promote behavior change by increasing awareness of the threat and informing communities about the difference in water quality between different sources. The popularity of this approach is exemplified in UNICEF's ‘Water Alert’ game [12] which teaches young people that “testing the water, sharing the results and warning the villagers…is critically important” to protecting the health of the village.

This paper describes a systematic review of the literature examining the efficacy of the use of water quality information dissemination at changing either household or community water management behavior. The primary health outcomes of interest result from improvements in water quality, and are downstream to a number of interim outcomes which must occur:

• Knowledge of water contamination (consumers must know the results of tests undertaken before responding to them)
• Switching to the safest (or least contaminated) sources
• POU water treatment
• Improved management of shared water sources, usually through source treatment
• Water quality improvements since health improvement can only be expected if the actual quality of the water improves

The behavioral changes required will vary according to the contaminant identified and local context. For example, removal of arsenic from water is plausible [13] but rare whereas removal of pathogens by chlorination of either community or household water source is common and widespread.

The aim of the systematic review was to evaluate this literature to establish the evidence for impact of dissemination of water quality information about a) chemical contamination and b) microbial contamination on health outcomes, knowledge of risk, source switching, POU water treatment, source treatment, and water quality improvements.

A protocol for this review was developed and reviewed by colleagues external to this team and is available on request from the first author. Reporting guidelines set out in the PRISMA statement are followed here [14] .

Seven bibliographic databases were searched during January 2010 (CENTRAL, MEDLINE, PsychInfo, EconLit, Compendex, LILACS, IndMed). Search strategies varied by database, but were structured to include terms for [drinking water] AND [water contamination] AND [test]. The full search strategy for Medline (Ovid online platform) is provided in Supporting Information File S1 , and all further search strategies are available on request from the corresponding author. Particular efforts were made to locate unpublished reports using OpenSIGLE, relevant conference proceedings, Google searches and snowballing from known projects. Reference lists from included studies were screened for further studies and 5 non-systematic reviews were screened for further studies [15] , [16] , [17] , [18] , [19] .

The first 2,000 records were independently screened by 2 reviewers (CC & PL) for potential inclusion in the scoping review. Since agreement was high, 25% of the remainder were independently double screened. All studies identified as potentially relevant to the scoping review were then reviewed in full (independently by 2 reviewers) for inclusion in the systematic review. Any disagreements were settled through discussion and consensus.

Eligibility for inclusion was assessed against the following criteria:

• P opulations living in areas where chemical or microbiological contamination of drinking water posed a known health risk
• I nterventions in which drinking water contamination was tested and results disseminated to individuals or communities. Testing could take place at any local site (eg: private well or tap, shared well or tap, community source)
• C omparison. Only studies using alternate or no-treatment control groups were included
• O utcomes of interest were changes in: health, water source, water treatment, water quality, and knowledge of contaminant risk
• S tudy designs included were Randomized Controlled Trials (RCTs), Quasi-RCTs, Cohort Studies, Time series, and Controlled (including non-equivalent comparison groups) before and after studies

Exclusion criteria:

• Studies conducted in locations where water contaminants did not pose a significant public health threat (such as exposure to low concentrations of nitrites)
• Studies where general risks posed by unsafe water were highlighted, without dissemination of local contamination data following testing
• Studies where no outcomes of interest were collected or reported

Validity assessment

Risk of bias was assessed using current guidance from the Cochrane Collaboration [20] . This tool considers bias in: sequence generation, allocation concealment, blinding, missing outcome data, selective outcome reporting, and “other sources of bias.” For non-randomized controlled studies included, we substituted comparability of groups at baseline and follow-up for security and concealment of randomization. In addition we assessed intervention integrity, ie the uniformity of the intervention delivery.

Studies were categorized as having a low, moderate, or high risk of bias using standard criteria for each study type as advised and disagreements resolved through consensus. The risk of bias will be reported separately for each study and for each outcome. All outcome data will be reported regardless of level of bias reported but where risk of bias is high this will be highlighted in our assessment of the strength of evidence.

Data Abstraction

Abstraction was completed independently, in duplicate.

Study characteristics

Abstracted study characteristics were population characteristics, drinking water supply, intervention details (type and frequency of water testing undertaken, methods of information dissemination, intervention duration and any co-interventions), nature of control or comparison group, and period of follow up.

Outcomes extracted were:

• health outcomes attributable to consumption of contamination water (e.g. diarrhea, flourosis, arsenicosis) assessed by occurrence of symptoms in study populations from self report or health care data and converted into risk difference (exposed – non-exposed) where possible
• water quality measured using any standard methods for assessing potability of drinking water usually through tests for presence/absence of microbial or chemical indicators or concentrations of contaminants. Reported here as risk difference for dichotomous, or Standardized Mean Difference for continuous, outcomes where possible
• source switching measured using self reported proportion of households changing their main water source. These data are categorical (e.g. switching to less safe, not switching, switching to safer) but may be restricted to dichotomous data (eg proportion of study population switching to a safer source). Risk difference for dichotomized data will be reported here where possible. Proportions within each switching category will also be reported where data are available
• water treatment (at source or point of use) measured using self reported water treatment, researcher observed water treatment or standard tests for water treatment (e.g. tests residual free chlorine. Reported here as risk difference for dichotomized data where possible (e.g. treated/not treated, sufficient/insufficient chlorine)
• correct knowledge of contamination risk among study communities before and after intervention. The proportion of study population correctly knowing the safety of sources was reported as a risk difference where possible

Quantitative data synthesis

The study team agreed that the capacity for meta-analysis would depend on the heterogeneity of interventions, study types and outcomes available and was likely to be highly constrained. Therefore only subgroups and not meta-analytic strategy were planned in advance. These were: type of contamination, method of dissemination, level of contamination, and study design. We suggest that pooling of effect sizes will only be appropriate among studies of the same contaminant and using similar interventions. If data were to be available in later updates, continuous data would be pooled using inverse-variance methods. Methods for pooling risk differences would be determined by rate of events and study characteristics [20] .

More than 14,000 unique documents were located (including duplicates). Six studies (due to multiple publications, number of reports is larger than the number of studies) met the inclusion criteria for systematic review, see Figure 1 Flow chart of included/excluded studies. Excluded studies are shown in Supporting Information File S2 .

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0021098.g001

Excluded Studies

Twenty-two projects met intervention criteria, but not study design criteria. The variety of projects and studies identified confirms the interest in the use of water quality monitoring as part of community level public health activities. Since this is the first review of this body of literature, some readers may be interested in the range of these studies so further details are provided in Supporting Information Table S1 .

The characteristics of included studies are summarized in Table 1 . Four included studies concerned arsenic contamination [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] and 2 concerned indicators for fecal contamination ( E. coli or H 2 S-producing bacteria) [33] , [34] .

https://doi.org/10.1371/journal.pone.0021098.t001

All the participants in the study groups were shown to be at high risk of consuming contaminated water. Among the studies of arsenic contamination the proportion of wells with arsenic levels higher than the Bangladeshi safety limit of 50 micrograms per liter (50 µ/L) varied between 20% [30] and 66% [21] . The WHO standard is lower (10 µ/L), and using this standard 44% of wells were unsafe [27] . In the two studies of microbiological contamination the WHO approved safety standard is zero presence of fecal indicators and 60% [33] and 86.5% [34] of water sources were judged unsafe against this standard.

Four were based in Bangladesh (all concerning arsenic contamination), one study in India and one in Kenya (both microbiological contamination). All studies used external groups (the research team or NGOs) to test the water and disseminate results and all required behavior change at the individual rather than community level.

The risk of bias in these studies was judged as moderate to high in most cases considering study design, sampling and missing information (see Table 2 ). Two recent studies were (at the time of searching) still only available as working papers and further data or analyses may be available in later publications [32] , [34] . Only 3 studies used random allocation [32] , [33] , [34] , and only one of these included a no-information control group [33] . All except 1 study (where delivery differed between areas [21] , [22] ) studies had good intervention fidelity.

https://doi.org/10.1371/journal.pone.0021098.t002

There was only one occasion where sufficient data were available on common outcomes using compatible study designs to allow meta-analysis. A narrative (or qualitative) account of findings is provided here. Where possible (i.e. when data allow) outcome data has been converted into effect sizes, but are mostly reported as presented in the original studies. Unpublished data were available for two studies, study authors for an RCT of microbial contamination in India have made their data publicly available [35] , the first author of a second study provided additional information on source switching behavior [36] . Findings are summarized in Tables 3 and 4 .

https://doi.org/10.1371/journal.pone.0021098.t003

https://doi.org/10.1371/journal.pone.0021098.t004

Impact on Source Switching

The strongest evidence was for source switching in response to arsenic contamination information, with 4 studies reporting higher rates of switching (26–52%) in households previously drinking from contaminated wells (3 at statistically significant levels) [25] , [30] , [32] , [37] . Three studies compared within a cohort between those using safe or unsafe wells at baseline [21] , [25] , [32] and one between participants and non-participants in an education campaign [30] . In addition, comparison data from an area neighboring the Health Effects of Arsenic Longitudinal Study (HEALS) (group where well labeling had not yet taken place showed lower switching rates (8%) than among those with safe (14%) or unsafe (60%) wells in intervention areas [28] . In Kenya, a modest increase in the proportion of pre-treated stored water with low levels of microbial contamination (<10 colony forming units (Cfu) 100/ml) is taken to infer source switching [38] .

Although 5 studies report rates of switching a common estimate of effect (Risk Difference) could only be calculated for two studies both of which considered arsenic contamination of drinking water in Bangladesh, both with low/moderate risk of bias. Tarozzi and colleagues [32] showed that those with unsafe wells were more likely to switch sources 9 months after receiving the information [RD 0.28, CI 0.22–0.24]. In the HEALS studies 6–12 months after intervention those in the study areas were more likely to switch source than those in the comparison areas [RD 0.32, CI0.30–0.32] and within comparison areas those with unsafe wells were more likely to switch source than those with safe wells [RD 0.46 CI 0.43–0.49] [28] . At two year follow up differences between those with safe and unsafe wells were modest but remained [RD 0.08 CI 0.06–0.09] [25] . The data comparing switching rates between those with safe and unsafe wells at 6–12 month follow-up can be pooled to show a significant difference in rates of switching [RD 0.43 CI0.4–0.46] suggesting that 43% more of those who were informed that their well was unsafe switched sources relative to those who were told their water source was safe. The strength of evidence provided by these findings is low because the comparison made is between non-equivalent groups; those who have an unsafe well may be dissimilar to those who have a safe well introducing a potential source of bias.

Health Effects

Only one study reported health outcomes from information sharing. The HEALS study reports creatinine adjusted urinary arsenic in a cohort whose wells had been labeled to identify safe/unsafe levels of arsenic. They report a significant reduction of urinary arsenic among those using unsafe wells at baseline (109 vs 6.2 µ/L, effect size 0.86, 95% CI 0.18,1.5 unadjusted for baseline differences between groups, risk of bias in study judged to be low/moderate). This represents a Standardized Mean Difference of −0.42 [CI −0.45,−0.35] between groups, favoring those who had been informed that their wells were unsafe.

Water Quality

Only one study reported water quality as an outcome. Luoto compared the levels of E.coli in household water (colony forming units per liter of water: cfu/100 ml), comparing pre and post intervention only [34] . This study used alternate interventions presented sequentially in random order (i.e. all groups received source and household water quality information at some time) although this study was judged to have a high risk of bias considering differences at baseline between groups. A significant reduction in E.coli in household water following dissemination of source water quality results was reported (mean reduction of 0.6 log cfu/100 ml SE = 0.17, n = 1357, p<0.01), but not following information about household water quality (mean difference 0.11 log cfu/100 ml, SE = 0.18, p>0.1).

POU Water treatment

POU treatment is the primary outcome for both the included studies of microbiological contamination, both of which employed random allocation. In Kenya, Luoto states that POU rose significantly after being informed about source water quality, but not after being informed about household water quality [34] . In India in a study judged to have a moderate risk of bias, there was a reduction in purifying frequency of 1.5% among the control group, and an increase of 1.8% among intervention, however 48.8% of both groups never purified (original data made available to review authors and reanalyzed here) [33] . This new analysis showed a significant 2 way (χ 2 (df 13) = 36.07, p.001) but not 3 way (χ 2 (df 4) = 6.52, p = 0.16) interaction. Interactions were significant for both Group × outcome (χ 2 (df 4) = 16.34, p = 0.03) and Test result × outcome (χ 2 (df 4) = 11.21 , p = 0.02), but not for group × test result (χ 2 0.76 (df 1), p = 0.23). The groups were unbalanced; members of the experimental group were significantly more likely to receive a positive test result, significantly more likely to start purifying but also to stop purifying (10.3%) than the control group. It is difficult to say with certainty what the effect of the provision of contaminant information was in this case.

Knowledge of the contamination level

Knowledge of the contamination level of their water source was collected as an interim outcome in some studies. Where this outcome is reported, increases in knowledge of between 25–78% following intervention were observed [21] , [28] , [30] although all studies were judged to have a high risk of bias.

Planned Subgroups

The only common outcome reported between studies of chemical and microbiological contamination was source switching, where evidence of source switching was provided by four studies of arsenic contamination [21] , [22] , [25] , [28] , [30] , [31] , [32] , [34] and one study of microbiological contamination [34] . Given limited data availability it was not possible to compare impact according to contaminant risks discussed.

Similarly, it is difficult to draw conclusions from these studies regarding method of information delivery or level of contamination. None of the studies compared between modes of communication or personnel delivering results. Most studies used a combination of approaches including house-to-house visits, public education campaigns, and public displays of information (such as well labeling) but did not compare between strategies. The two most recent studies are an exception to this, where researchers compared different strategies for information dissemination. In Bangladesh binary and ‘degrees of risk’ information about arsenic contamination were compared [32] , and in Kenya message framing and sharing of source vs household water quality were compared [34] . One other study shared information on levels of contamination alongside a binary safe/unsafe message but did not compare approaches [25] . Positive framing of messages (i.e. emphasizing health benefits rather than health risks) increased the likelihood of POU [34] . Information about level of risk had the largest impact on behavior at the boundary of safe/unsafe level: those who were just above the risk level were more likely to switch source if they received the gradient message than those receiving binary information, but at higher levels those receiving binary information were more likely to switch [32] .

The three studies employing randomization were also the three most recent studies. Unfortunately the data collected regarding our outcomes of interest were limited. All three studies conclude that the provision of water quality information was successful in promoting behavior change, although Luoto notes this only held true for information about source, not household, water in her study [34] .

The search strategy for the review was deliberately wide to gather studies from across disciplines (health, engineering, economics and psychology) for any drinking water contaminant risks. We sought out published and unpublished sources. To our knowledge this review provides the most comprehensive collation of studies of this type yet published, and demonstrates the widespread interest in this intervention. Our review has identified the strengths and limitations of the existing evidence and indicated how future studies might report relevant exposures and outcomes in a way to allow for proper meta-analysis.

Limitations

The literature in this field is not well established and no studies with low risk of bias and complete reporting of outcome data of interest to this review were found. One limitation of this review is its reliance on narrative synthesis in response to heterogeneity in study designs and outcomes included. This is a common difficulty in public health research and particularly so in developing country public health [39] , [40] , and we believe that narrative synthesis is an appropriate strategy in this context.

Some bodies of literature are likely to have been missed by our approach to searching. For example, studies conducted within water engineering documenting incremental changes in water management systems may not have been retrieved. Since our aim was to explore the effects of information dissemination to communities or consumers we do not believe such studies would have met our inclusion criteria. Similarly, the rich literature on risk communication [41] , [42] , [43] which considers how information is most effectively presented is not included. This literature should be drawn on to design and interpret interventions in the field.

Policy Context

Considering all studies meeting the intervention criteria (including those excluded because of study design) this review demonstrates that the use of water testing and dissemination as a tool for behavior change, particularly with respect to microbiological contamination, is being promoted ahead of the evidence of impact. This adoption is often large scale; in just one state in India (Andhra Pradesh) 24,000 field kits (chemical parameters) and 13,50,000 H 2 S (Hydrogen Sulfide) tests have been distributed to Panchayats (village level government) in an effort to introduce community level monitoring of their water supply [44] . The evidence is encouraging, but not yet conclusive that this is an effective means of changing behavior. Twelve of the excluded projects aimed to promote better community management of their water supply [29] , [45] , [46] , [47] , [48] , [49] , [50] , [51] , [52] , [53] , [54] , [55] , [56] , [57] and improvements in local management are widely reported in these studies [29] , [50] , [53] , [54] , [58] , [59] , although these assertions are not always accompanied by supporting data.

Behavior Change

The studies reported here all attempt to change behavior by using information about contaminants in water as a lever. This solution certainly has some face validity, making visible hidden health risks. However, in order to fully understand the likely impact of this intervention we should consider what information, disseminated how, and in which contexts are most likely to lead to behavior change. Only one study [34] used an explicit theoretical model to design the format of the intervention. Evidence suggests that such theoretically driven interventions will have higher success rates [60] and best practice in methods for evaluating complex interventions in health suggest the importance of a broad approach to evaluation informed by both theory and context [61] , [62] .

Many studies in the water and sanitation field highlight the importance of social and cultural factors [63] and the complexity of behavior change required to improve community [64] or household water supplies. Gender, poverty, stigma, convenience and local social structures were identified as key social factors determining the likelihood of change in the arsenic mitigation programs in Bangladesh [25] , [31] . Programs were also thought more likely to succeed where there was a local history of self-mobilization and/or strong local leadership on the issue [31] .

This review has highlighted many gaps in the evidence to date. We have identified 4 key issues to consider in future studies:

• The need for evidence of impact using robust methods (e.g. random allocation of study participants, use of non-intervention control groups)
• The format of information provided (eg source and/or household, binary or continuous, risk or safety messages)
• The methods of information dissemination
• The use of community level interventions and outcomes

The need for such studies is greater in the dissemination of microbiological, rather than chemical contamination both because the scale of the health threat is larger and because of the smaller number of studies in this area. In the absence of randomized impact evaluations, ongoing projects could provide data on elements of implementation, behavior change and context. Any future evaluation should be informed by a careful consideration of the specific causal pathways implied by behavioral models [65] , [66] , [67] to ensure that moderating and mediating outcomes are assessed.

Conclusions

This systematic review confirms a growing interest in the use of dissemination of water contamination information to promote behavior change, particularly with respect to the provision of H 2 S to communities for self-testing of fecal contamination. Large cohort studies of arsenic mitigation programs in Bangladesh suggest that consumers were more likely to change wells if they were informed which were contaminated with arsenic but the evidence base is currently equivocal since there is not robust comparison data from the groups not receiving information. Our ability to draw strong conclusions is limited by the nature of the evidence collected to date where few studies have used robust control or comparison groups; rigorous studies on this topic are needed in which common designs and outcome measures are used.

Supporting Information

Full search strategy in Medline.

https://doi.org/10.1371/journal.pone.0021098.s001

Excluded Studies.

https://doi.org/10.1371/journal.pone.0021098.s002

Detail of Projects Meeting Intervention Criteria Not Included in Systematic Review.

https://doi.org/10.1371/journal.pone.0021098.s003

Acknowledgments

This study was completed as part of the Aquatest project and we are grateful to Stephen Gundry, the Aquatest Project Director, for his support in conducting this research. Our thanks also to the Aquatest team, and, in particular, to Jim Wright for comments received and Nora Deitrich for assistance with screening. We reserve our greatest thanks to the authors of the original studies we have included here, particularly those who provided original data and responded to queries for further information.

Author Contributions

Conceived and designed the experiments: PJL CC JMC. Analyzed the data: PL CC. Wrote the paper: PJL CC JMC.

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Detection of contaminants in water supply: A review on state-of-the-art monitoring technologies and their applications

Syahidah nurani zulkifli.

a Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia

Herlina Abdul Rahim

Woei-jye lau.

b Advanced Membrane Technology Research Centre (AMTEC), Faculty of Chemical and Energy Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia

Water monitoring technologies are widely used for contaminants detection in wide variety of water ecology applications such as water treatment plant and water distribution system. A tremendous amount of research has been conducted over the past decades to develop robust and efficient techniques of contaminants detection with minimum operating cost and energy. Recent developments in spectroscopic techniques and biosensor approach have improved the detection sensitivities, quantitatively and qualitatively. The availability of in-situ measurements and multiple detection analyses has expanded the water monitoring applications in various advanced techniques including successful establishment in hand-held sensing devices which improves portability in real-time basis for the detection of contaminant, such as microorganisms, pesticides, heavy metal ions, inorganic and organic components. This paper intends to review the developments in water quality monitoring technologies for the detection of biological and chemical contaminants in accordance with instrumental limitations. Particularly, this review focuses on the most recently developed techniques for water contaminant detection applications. Several recommendations and prospective views on the developments in water quality assessments will also be included.

List of Acronyms

1. introduction.

Waste production from agriculture, industrial sewage, animal and human activities are affecting the boundaries between clean water and wastewater, causing the reduction in the fresh water supply for human. Water ecology provides services such as food production, nutrient cycling, habitat provision, flood regulation, water purification and soil formation [1] . Biological and chemical contaminants in tap and drinking water, initiate the evolution of contagious diseases [2] . Therefore, fast and sensitive detection techniques are crucial to ensure safe and clean water supply. Unsafe water supply affects human health, causing contagious diseases such as hepatitis, influenza, SARS, pneumonia, gastric ulcers and pulmonary disease [3] . There are numerous non-biological contaminants existed in the water supply and some of the examples are silica, sodium, sulphur, ammonia and chlorine [4] . Other hazardous substance of heavy metals such as cadmium (Cd), lead (Pb), arsenic (As), mercury (Hg) and nickel (Ni) are also found in water supply [5] . These non-biological contaminants are among the commonly detected pollutants in urban areas that constitute a wide array of human activities.

The preservation of water quality has been regulated since the introduction of directive 91/271/EEC , which requires accurate treatment process targeting on organic contaminants, nitrogen and phosphorus [6] . In addition to these contaminants, other concern on the water quality includes the existence of microbiological contaminants in tap and drinking water at point of consumption. Derivation of pathogenic activity in water supply poses serious threats not only to human but also the entire water ecosystem. Pathogenic microorganisms can be categorised into bacteria (e.g., Salmonella typhi , Vibrio cholera and Shigella ), viruses (e.g., Poliovirus ) and protozoa (e.g., Giardia lambia and Cryptosporidium ). These types of microorganisms have been periodically detected in the water samples of river, groundwater and drinking water [7] , [8] . Hence, minimizing the exposure of deadly diseases is important by providing early warning detections on the presence of pathogens [9] . According to World Health Organization (WHO), the most commonly found microorganisms in the drinking water sources are Cryptosporidium, Legionella, Pseudomonas , Giardia and E. coli [10] , [11] , [12] , [13] . A list of possible water supply contaminants that is based on standard guideline is summarized in Table 1 .

List of the most commonly found contaminants in water supply [9] , [10] , [11] , [12] , [13] .

Recently, analytical technologies in water monitoring have taken a variety of directions. There are several water monitoring techniques, including conventional instrumental analysis (laboratory-based analysis), sensor placement approach, model-based event detection, microfluidic devices, spectroscopic approach and biosensors. Selecting suitable detection technique(s) is strongly dependent on the purpose of intended detection analysis, whether it requires quantitative, qualitative or hybrid measurement. Biological and chemical sensors have been in great demand for use in water monitoring technology, and they appear to be feasible for device integration and commercialization.

Previously, the detection of water contaminants has often been conducted manually in water laboratory facilities [14] . At the laboratory level, analyses are usually carried out by skilful personnel using high-end and cutting-edge technologies. Conventionally, multiple fermentation tube technique [15] , [16] , filtration method [17] , [18] , DNA amplification [19] , fluorescence in-situ hybridization (FISH) techniques [20] , [21] , capillary electrophoresis [22] , [23] , field-flow fractionation [24] , [25] , chromatography [26] , [27] and mass spectrometry [28] , [29] are the commonly used instruments to detect contaminants in the water samples. The potential benefits of laboratory-based analytical methods have been recognized for a long time, but studies have shown that they are not very efficient for on-site monitoring applications. With the technological advancement in the analytical chemistry, new techniques are developed through the introduction of advanced spectroscopy [30] , model-based event detection [31] , water quality sensors [32] , [33] , microfluidics [34] , [35] , [36] and biosensors [37] , [38] , [39] . Recently, wireless sensor network has been adapted in various detection techniques for portability. The evolution of water contaminant detection techniques is illustrated in Fig. 1 .

Evolution of contaminant detection techniques in water analysis application.

Contaminant detection analysis is gaining importance in the water monitoring and environmental applications. An initial growth in water quality sensor fabrication and optimal sensor placement for event detection has been introduced over the past several years [40] , [41] , [42] , [43] . The synthesis of the aligned water sensors, also known as sensor placement approach, could improve the device detection performance by increasing the detection sensitivity [44] , [45] . Deploying sensors in water distribution system allow the measurements of temperature, pH, turbidity, conductivity, oxidation reduction potential (ORP), UV-254, nitrate-nitrogen and phosphate both on-line and off-line. These water quality parameters are important to the treated water could meet the limit of detection (LOD) set by the United State Environmental Protection Agency (USEPA) [46] . However, the installation of numerous sensors along the distribution system seems not very practical owing to high installation cost [47] .

Determining the presence of contaminants in water requires accurate and fast response detection techniques. Intentional sabotage events such as water contamination in Japan [48] , the incidence of mesophilic Aeromonas within a public drinking water supply in Scotland [49] and occurrence of Aeromonas spp . in tap water in Turkey [50] triggered awareness on the need to have high-accuracy sensors installed along the water distribution system (WDS). Since then, obtaining optimal sensor placement has been widely explored for the security of WDS by utilizing model-based event detection technique. Optimal sensor placements, detection likelihood, expected contaminant concentrations and affected populations could be predetermined using detection algorithm by obtaining signals from conventional water quality sensors.

A surrogate approach for contamination detection is also suggested by the EPA to determine irregularities of water quality parameters obtained from sensing mechanism for an early warning of possible presence of contaminants [51] , [52] . Obtaining an early detection system using multiple sensor data station on-site is more beneficial compared to the data from a single site [53] . Most of the water quality parameters are used as primary indicators for contamination events in WDS, which are obtained from an online database, such as CANARY Database [54] , [55] , [56] , [57] . The main objective of the event detection method is to: (1) identify the possibility of event occurred, (2) characterize the event into subgroup (e.g., spatial area, time duration and severity level), and (3) detect contamination as accurately and early as possible. Achieving optimal time responses are superior for early indications of potential contaminants in WDS [58] . To minimize the spread of outbreaks, rapid and sensitive detection of pathogens is important.

As many different types of contaminants could present in WDS, case-to-case approach is necessary for accurate qualitative and quantitative analysis. To tackle the issues, handheld detection devices such as microfluidics sensors, miniaturized biosensors as well as portable spectroscopy are widely considered. Nowadays, lab-on-a-chip platforms that require microscopic amount of fluids (10 −9 –10 −18  l) are achievable for sampling, filtration, pre-concentration, separation and detection of biomolecules or analytes. Microfluidic composes channels with dimension up to hundreds of micrometers (μm). The integration of microfluidic sensors constitutes a multi-disciplinary theorems for sensing [59] . This kind of sensors is widely used in biomedical, science, genomics, forensics and environmental studies and for immunology or biochemistry applications [60] .

The most frequently used vibrational spectroscopy instruments in water monitoring technology are Infrared (IR) and Raman spectrometers. Vibrational spectroscopy is based on the correspondence of radiation absorptions to a discrete energy level, which is generated from the stretching or bending of atom molecule vibrations at frequencies of 1012–1014 Hz. In recent years, the integration of biosensor and spectroscopic techniques with digital microfluidic (DMF) devices is widely explored for the use in contaminant detections. The popularity of such integrated technique can be reflected by the number of technical papers published in the literature [61] , [62] , [63] , [64] . However, two major concerns regarding the DMF device are the complete elimination of analytes from sensing surface of DMF and disassemble of target analytes from the biosensor receptors for every sensing cycle [65] .

This paper intends to provide an overview on the developments of water monitoring technologies for both biological and non-biological contaminants determination. As detection mechanism varies with water contaminants, extensive review on analysis and data mining is also provided. This review emphasizes the current trend in water monitoring technologies and compares their performances with conventionally used methods. Significant limitations and drawbacks of the techniques are also discussed and recommendations are provided for future development in the water quality monitoring. Nevertheless, some analytical methods such as photo-acoustic, ultrasonic and microwave spectroscopy are not included in this review as they are very limited in applications.

2. Discontinuous (sample-based) methods

2.1. biological contaminants.

Microbiological parameter in tap and drinking water focuses on the detection of various pathogens using indicator organisms. Transmission route disease, also known as faecal-oral route, occurs when pathogens in faecal particles are transmitted into oral cavity of another host. According to the European Commission Drinking Water Directive, indicator bacteria E. coli and Intestinal enterococci should not be present in 100 mL of water volume [66] . The proliferation of water monitoring technology has prompted awareness over the safety of microorganism contaminants to human health and environment. Despite the advancement of the other techniques, the conventional culture-based methods are still in-use for the detection of microbiological parameters in water [67] .

2.1.1. Multiple tube fermentation (MTF) technique

Multiple tube fermentation (MTF) technique is one of the standard laboratory methods that can be used to detect microbiological activity in water samples. The MTF technique is executed in a three-stage procedure which is known as presumptive stage, confirmed stage and completed test [68] . Presumptive stage consists of a series of tube incubation process resulting in the formation of gas indicating positive presumptive test. Enumeration procedure for each bacterium sample is executed using suitable broth medium in the presumptive phase [69] . The inoculation process of testing tube samples should be performed instantly after any gas formation occurs. This procedure is known as confirmation stage.

According to EPA’s Standard Methods 9131 for Total Coliform: Multiple Tube Fermentation Technique [70] , completed test is finalized by gas formation and the presence of bacteria in the culture colonies. Detection of coliforms is often carried out by using MTF technique [71] . The concentration of bacteria in water samples is evaluated by examining a series of tubes containing suitable selective culture medium and dilutions of water sample. Formation of turbidity will occur accordingly due to the microbial growth and the results are expressed in terms of statistical estimation of the mean, known as the most probable number (MPN).

The presence of coliforms bacteria, known as ‘indicator’ organisms, is identified based on the MTF technique with an A-1 medium for a MPN test procedure described in the Standard Methods for the Examination of Water and Wastewater [72] . Using this technique, various types of coliform bacteria such as E. coli , Enterococci , Salmonella and Bacillus could be easily detected in different water samples [73] , [74] , [75] , [76] . On the other hand, MTF technique was also found to be effective in the process of yeast isolation and identification of E. coli , Enterococcus spp. and P. Aeruginosa densities [77] . The result showed the positive correspondence between yeast densities and counts of standard indicator, suggesting that yeast may also be considered as an organism indicators of sewage contamination.

MTF method was also used to determine E. coli in the water samples and high detection rate (100%) could be achieved compared to only 75.5% shown by a membrane filter (MF) method [78] . The presence of faecal contaminants in the water samples is confirmed based on turbidity measurements, which are reflected by the increase of water temperature and decrease of dissolved oxygen (DO) content [79] . Reduction in DO content may reduce the survival rate of coliform bacteria in aquatic environments [80] . However, determining DO measurement in surface level water samples is considered irrelevant due to high production of oxygen on its surrounding that leads an indirect proportional relationship between turbidity, DO and faecal coliform [81] .

2.1.2. Membrane filtration (MF) method

The MF technique is recognized by the USEPA and UNEP/WHO as a method for detecting biological contaminants of potable water. This technique is capable of isolating and eliminating discrete microbiology colonies in relatively large number of sample volume compared to the MTF technique [82] , [83] , [84] . Similar to the MTF technique, MF method is generally used for major indicator organisms [85] . In the past, both methods have been conducted at laboratory level, but due to the advancement of portable technologies, MF and MTF method are now able to be executed for on-site applications.

Incubation of MF on solid and/or liquid selective media at appropriate temperature allows the growth and development of organism cultures providing a direct count of total coliforms colonies. The choices of temperatures depend on the type of bacteria indicator and the selective media. For instance, P. aeruginosa , E. faecalis and Penicillium were able to be detected using cellulose nitrate membrane filters which after being incubated for 48 h at 44 °C on the solid and liquid selective media [86] . The MF technique has also been used for retaining virus, known as F-RNA coliphages via incubation using mixed cellulose nitrate and acetate membrane filters [87] .

Work conducted by Grabow et al. [88] indicated that theoretical efficiencies of 100% are achievable with procedures governing to direct plague assays on 100 mL samples and the presence-absence test on 500 mL samples. In addition, positively-charged filter media have been widely used for recovering bacterial viruses and phage. However, poor detection of viruses and phage was experienced following poor absorption and inactivation caused by extreme pH level exposures [88] , [89] . In general, microfiltration and ultrafiltration membranes are preferable to be used for the filtration purpose due to their appropriate range of surface pore sizes that could retain microorganism effectively [90] . Previous work has shown that the removal of bacterial contaminants in water could be carried out using microfiltration-based method by observing the in-vitro nitric oxide production and binding response of Limulus amebocyte lysate (LAL) assays [91] .

Instead of using single type of membrane filter, simultaneous use of microfiltration and ultrafiltration membrane filters were attempted in recent years. Xiong et al. [92] has established the first quantitative assessments in the water samples using integrated method and reported the total organic carbon (TOC), total suspended solid (TSS) and turbidity of the samples to be 95–630 mg/L, 180–1300 mg/L and 150-1900 NTU, respectively. The integrated method has also been used to reduce peroxidase activity in red beet stalks in order to maintain natural pigment stability [93] . Results showed that it achieved more than 99.5% reduction of peroxidase activity and 99.9% reduction in turbidity.

Previous work showed the applications of membrane bioreactor (MBR) process based on aerobic fermentation method [94] . MBR combines the membrane filtration process with reactor that involves biological reactions. The efficiency to monitor microbial population in water sample depends on the attachment of bacteria onto inert material inducing high biomass [95] , [96] . Integration of bioprocess and MF method provides a better efficiency in the removal of bacteria as, demonstrated by Adan et al. [97] in which a derivation of photo catalysis-microfiltration hybrid system was used to remove E. coli from water source.

MF, selective medium broth and culture plate methods have become the standard (ISO 16654:2001) to monitor the presence of E . coli and other pathogens in water [98] . However, the drawbacks of employing these methods are time-consuming, laborious and low sensitivity in detecting contaminants at low concentrations [99] . Limitation of selective culture or immunological methods due to lack of consistent differentiation in phenotypic traits may also affect detection accuracies [100] . The efficacy of various membranes was elaborated by Snyder et al. [101] in which MF is capable of reducing concentration of contaminants with specific properties. It was reported that the degree of contaminant removal was highly dependable on the characteristic of the membrane and the molecular properties of the targeted analytes. Microfiltration and ultrafiltration membranes showed the least value of contaminant removal whereas reverse osmosis membranes are capable of removing almost all investigated contaminants [101] . Fig. 2 illustrates a process that combined ultrafiltration and reverse osmosis as advanced treatment process for wastewater. The findings indicated that reverse osmosis membrane could remove almost all targeted contaminants, achieving values below the method reporting limits (MRL).

Process flow diagram of a submerged Zenon ZeeWeed™ 1000 (ZW1000) ultrafiltration unit integrated with a multi-pass reverse osmosis unit (Synder et al. [101] ).

2.1.3. DNA/RNA amplification

DNA amplification is used to detect molecular biology by amplifying a single copy or a few copies of targeted DNA molecules to produce specific DNA particles in vitro . Polymerase chain reaction (PCR) invented by Kary B. Mullis was the first DNA amplification method designed to study particular DNA molecules [102] . Traditionally, replicating DNA sequence requires days or weeks to complete. But, with amplification of DNA sequence using PCR, it only takes several hours [103] . Because of its high detection sensitivity and level of amplification, PCR is capable of replicating miniscule amount of DNA sequences and is extremely useful in commercial uses, including genetic identification, forensics, quality control industrial applications and in vitro diagnostics.

In general, PCR amplification reaction constitutes three major elements: (1) a thermo-stable DNA polymerase, (2) a mixture of deoxynucleotide triphosphates (dNTPs) and (3) two oligonucleotide primers [104] , [105] . One cycle amplification denotes a series of temperature and time, hence amplifies the amount of targeted DNA sequence after reaction takes place. There are three steps in PCR protocols, i.e., denaturation at 93–95 °C for 1 min followed by 45 s annealing at 50–55 °C and 1–2 min elongation at 70–75 °C [106] . Modification on the standard PCR protocol could also be performed using different techniques, e.g., a multiplex PCR protocol for detection of E. coli , Campylobacter spp. and Salmonella spp. in both drinking and surface water [107] , [108] , [109] .

Fig. 3 shows the PCR amplification product developed using oligonucleotide primers Rfb and SLT-I for the purpose of detecting E. coli O157 and E. coli virulence gene SLT-I in drinking water. Optimization of PCR protocol was tested with E. coli O157:H7 strain. Another example is conventional hot-start PCR technique for the detection of Actinobacillus actinomycetemcomitans by heating the reaction components under DNA melting temperature before mixing with polymerase to reduce non-specific priming amplification [110] , [111] . A touchdown PCR amplification was then established to identify the presence of bacteria in aquatic samples by gradually decreasing the primer annealing temperature in later cycles [112] , [113] , [114] . The analysis of bacterial water contaminant was performed using a universal conserved bacterial 16S rDNA sequence, which are specifically used for amplification of 16S rDNA fragments with GC-clamp-EUB f933 and EUB r1387 primers ( Table 2 ).

A typical PCR amplification product optimized using E. coli O157:H7 strain. (a) Lane 1: 1 kb DNA ladder; Lane 2: 292 bp O157 gene amplified with Rfb F and R primers. (b) Lane 1: 50 bp DNA ladder; Lane 2: 210 bp SLT-I gene amplified with SLT-I F and R primers (Imtiaz et al. [109] ).

Primer sequences and positions [114] .

Although the PCR method has a high detection successful rate, it is still associated with several limitations that include low sensitivity to certain classes of contaminants and reduction of amplification efficiencies in the case where inhibitors are in present in water samples [115] . Over the past few decades, there has been a diversity of newly developed technologies to overcome these limitations. Some of the examples are quantitative real-time PCR assays (qPCR), reverse transcription real-time PCR (RT-qPCR) protocol, loop-mediated isothermal amplification (LAMP) technologies, strand displacement amplification (SDA), ligase chain reaction (LCR), rolling circle amplification (RCA), helicase-dependant DNA amplification (HDA) and the most recently developed random amplified polymorphic DNA analysis (RAPD) [116] , [117] .

The qPCR automates both amplification and detection in quantitative measures. The simplified quantification is obtained through quantification cycles (Cqs) which are determined by fluorescence threshold or maximum second derivative [118] . Exponential phase in qPCR technique can be continuously observed for 30–50 Cqs and can be used to estimate the initial number of targeted DNA. The use of a qPCR assay to positively detect E. coli O157:H7 strains in drinking water was carried out using molecular beacons (MBs) oligonucleotide probes [119] , InstaGene™ matrix from Bio-Rad specially formulated 6% w/v Chelex resin [120] , minor groove binding (MGB) probes with 6-FAM (6-carboxyfluorescein) [121] and propidium monoazide (PMA-based) qPCR assay [122] . Quantitative PCR assay provides the possibility of quantitative analysis for E. coli target by using formulated structural quantification curve as shown in Fig. 4 . Such measure reduce the false positive results during analysis.

(a) Sensitivity of real-time PCR assay consist of ten-fold serial dilutions of DNA template isolated from E. coli JM109 strain ATCC 43985 and (b) Linear curve for real-time PCR assay with wide range of initial target concentrations (from 10 2 to 10 7 CFU mL) (Sandhya et al. [119] ).

There have been several commercially designed real-time PCR assays for the detection of pathogens (e.g., F. tularensis, B. anthracis and Y. pestis ) with high detection sensitivity and diversity of pathogen detection capabilities [123] , [124] . The qPCR techniques have been found useful for the detection of Naegleria sp . by referring to melting curve analysis SYTO9 and qPCR TaqMan assay [125] , [126] , [127] . Melting curve analysis is beneficial for the manipulation key conditions, including temperature interval and time delay before data are collected for each step. For example, melting curve that provides three informative peaks within temperature range of 79–86 °C ( Fig. 5 ) can be used to distinguish species based on the positions and height of the peaks obtained.

Melting curve analysis of the 5.8S rDNA/ITS product of seven Naegleria species: (a) N. fowleri , (b) N. lovaniensis , (c) N. italic , (d) N. australiensis , (e) N. gruberi , (f) N. byersi, (g) N. carteri and (h) Willaertia magna (Robinson et al. [125] ).

Another extended version of standard PCR method is the RT-qPCR, which is a useful technique to identify specific messenger RNA (mRNA) as well as DNA from any type of living microorganism cells, either qualitative or quantitative measures [128] , [129] , [130] . This technique evolved tremendously after the introduction of hybridization on target DNA sequence using an oligonucleotide probe. The RT-qPCR technique involves the hybridization of oligonucleotide primer to produce a complementary DNA (CDNA). This process of deoxyribonuclease I (DNase I) is used to eliminate contaminated DNA that triggers false positive results. The application of RT-qPCR assay approach has been used in detecting pathogens such as mRNA in E. coli cells [131] , family of Filoviridae viruses and RNA transcription from Ebola viruses [132] , cereulide-producing Bacillus cereus [133] , RNA molecules of Salmonella [134] and rotaviruses and coronavirus in feces contaminations [135] . The reverse transcription PCR (RT-PCR) techniques proven to provide high efficiencies by amplifying both DNA and RNA sequence. Conventional PCR methods meanwhile only amplifies DNA. As reported by Wang et al. [136] , RT-PCR has high detection sensitivity on bacterial quantity (as low as one bacterium) compared to those of PCR-based techniques.

Although PCR-based techniques could show significantly higher positive detection rate, performing accurate thermal cycling and utilization of sophisticated instrumentation (e.g., fluorescence measurement) require higher throughput and longer time [137] , [138] , [139] , [140] , [141] , [142] , [143] . Therefore, an alternative to PCR is isothermal-based amplification methods. This method can be carried out without undergoing repeated thermal denaturation procedure and does not require sophisticated instruments [144] . Typically, loop-mediated isothermal amplification (LAMP) mechanism comprises two pairs of primers (inner and outer) and are dependable to strand displacement synthesis of DNA polymerase to produce loops amplifications [145] . LAMP has been widely used for diagnosis of biological specimens and is commercially available for environmental monitoring applications [146] , [147] , [148] . It has high sensitivity and rapid detection capability as well as greater ability to quantify several bacteria [149] , [150] . A pilot study was conducted to detect Staphylococcus aureus , E. coli , Pseudomonas aeruginosa , Klebsiella pneumonia , Stenotrophomonas maltophilia , Streptococcus pneumonia , and Acinetobacter baumannii using quantitative LAMP (qLAMP) with better identification (P < 0.001) than that of traditional culture-based method [151] . The functionality of loop primers designed for LAMP assays improved the detection specificities and sensitivities by several magnitudes [152] . This was proven by Sotiriadou and Karanis [153] , by employing LAMP assays approach for the evaluation of Toxoplasma in water samples based on amplification of B1 and TqOWP Toxoplasma genes with 100% success detection rate. Separately, a gene amplification using hydroxyl naphthol blue could successfully detect Naegleria floweri within 90 min reaction time with a Kappa coefficient of 0.855 [154] .

Based on the previous discussion, one can realise that LAMP method is less expensive to perform as it involves no real-time thermal cycler. Furthermore, it has greater sensitivity and can be potentially deployed for on-site water contaminant detection. Gallas-Lindemann et al. [155] reported that Giardia spp. and Cryptosporidium spp. could be detected using LAMP assays with 42.7% and 43.6% detection rate, respectively compared to 33.5% and 41.9% shown by the conventional nested-PCR. Besides, the LAMP technique offers 100% detection sensitivity with LOD of 50 fg/mL compared to the conventional PCR method [156] . Integrating the extension method with the standard PCR could provide faster, less false positive indicators, better compatibility for detection of multiple pathogens [157] , [158] , [159] . Moreoevr, LAMP was comparable to the qPCR method for surveillance of Dehalococcoides spp. in groundwater using six LAMP primers designed for each three RDase genes [160] .

Enteric viruses generally yield between 105 and 1011 virus particles per gram of individual stool [161] , [162] . There is no direct relation between the occurrence of bacteria and enteric viruses, hence suggesting the need to separately evaluate the presence of viruses in water supply. Culture-based method is not the preferable approach for evaluating enteric viruses as it requires higher analysis cost and longer analysis period. It is also found to have complexity related to the permissive system of some non-cultivable viruses in vitro [163] .

According to Kim et al. [164] , molecular detection done by qPCR and qRT-PCR methods could overcome the issues regarding the sensitivity and analysis time. Huang et al. [165] and Jiang et al. [166] also agreed that in comparison to the conventional nested PCR approach, the qPCR method offers better efficiency (>95%) in quantifying enteric adenovirus serotype in environmental waters. However, no method is completely perfect by taking into account the principle and procedure of each method. For instance, the detection of pathogenic viruses is obtained in a disinfection procedure, but this method is not suitable for the detection of coliform bacteria due to low concentration of bacteria indicator [167] . The generation of DNA-based amplification method has evolved due to demands in producing combined method of detection with higher specificity and rapidity. Probe based real time loop mediated isothermal amplification (RT LAMP) assay was then introduced for the quantification of Salmonella invasion gene (InVA), aiming to achieve significantly higher sensitivity [168] .

2.1.4. Fluorescence in situ hybridization (FISH)

In situ hybridization is a technique that enables the detection, identification, localization and enumeration of microorganisms. Cellular component and targeted analytes can be visualized via fluorescence probe based on fluorescence in situ hybridization (FISH) technique. The FISH technique has been used in a wide variety of research fields such as cytogenetic, microbiology and genetic diagnostics applications [169] . There are a few important factors such as probe design and fluorophore selections that need to take into consideration before execution of FISH experiments. Commonly used probe is 15–30 nucleotides long that is labelled with fluoorophore of 3′ or 5′ at each end. These probing designs are specifically used for the detection of microorganism and mRNAs as shown in Fig. 6 . One of the earliest application to embrace the usage of FISH technique was microbial ecology. Similar to DNA amplification method, the most commonly used DNA probe is 16S rRNA sequences for the detection of bacteria in living tissues as well as in aquatic environment samples. In recent years, the FISH technique has been applied in microbiological monitoring field. However, FISH has low fluorescence signals which limits the detection factor to the specified microbial community [170] . To address this issue, a multi-labelled FISH technique is recommended so as simultaneous detection of microbial groups could be achieved by improving the fluorescence signals [171] .

mRNA localization of cyp6CM1 and ABC transporter genes in midgusts of the whitefly Bermisia tabaci using FISH, (a) bright field of a B. tabaci midgut, (b) FISH fr mRNA localization on this midgut showing cyp6CM1 gene expression mainly in the filter chamber, (c) bright field of a B. tabaci midgut and (d) FISH for mRNA localization on this midgut showing an ABC transporter gene expression mainly in the filter chamber. (Definition – am: ascending midgut; dm: discending midgut; ca: caeca; fc: filter chamber and hg: hindgut) (Kliot et al. [169] ).

Previous study reported the detection and quantification of β-Proteobacteria and Cytophaga-Flavobacterium cluster in an urban river after 3–7 days of formation [172] . A similar technique was used to detect various members of Cytophaga-Falvobacterium cluster, classes of proteobacteria and members of Planctomycetales in an aquatic environment, ranging counts of 50% cells detection [173] .

A FISH-probe using Bacillus subtilis 16 s rRNA has been also reported with the aim of distinguishing targeted nucleotides between 465 and 483 genes [174] . However, the results showed that FISH method was not able to identify strains, i.e., B. altitudinis, B. cereus, B. gibsonii, B. pimulus and B. megaterium . The development of FISH technique over the past several years has increased its usage in determining various types of MRNA and DNA molecules [175] . Fluorescent nanomaterials, also known by quantum dots (QDs), have been introduced to improve fluorescent-brightness, photochemical cohesion and coherence emission spectra [176] , [177] , [178] . The QD-FISH method offers the ability to detect specific target genes. For instance, synthesis of biotin-streptavidin deoxyuridine triphosphate (dUTP) labelled DNA probes via PCR using dNTP mixture enable the detection of Ectromelia virus (ECTV), a member of the Poxviridae family [179] , resulting a genome detection of 80% after 36 h of post-infection with significant visual of red fluorescence. The detection of green micro-algae, U. prolifera using FISH was also carried out targeting the 5S rDNA of U. polifera, Ulva linza and Ulva flexuosa molecular genes using 5S-1 and 5S-2 probes [180] . Six species of green algae were also tested, however only U. prolifera could be labelled by both specific probes. Because of the complex structure of bio-analytes, direct detection and quantification of single-cell bacteria using FISH are rather difficult. Therefore, an additional combination of flax desegregation protocol with quantitative FISH technique is recommended [181] .

2.2. Non-biological contaminants

Generally, there are two categories of non-biological water contaminants. Chemical contaminants consist of elements or compound, such as volatile organic chemicals, disinfection by-products and synthetic organic chemicals which can be occurred naturally or man-made. Whereas, radiological contaminants are from an unstable atom that emits radiation, for instance plutonium and uranium [182] . Another water contaminants that are starting to raise awareness are engineered nanoparticles/nanomaterial. Example of them are metallic nanoparticles (e.g., Ag, Au, and Fe), oxides (e.g., CeO 2 , TiO 2 and ZnO) and quantum dots (e.g., ZnS). Although nanomaterials are beneficial for many industrial applications, the release of them may unintentionally promote hazardous occupations to environment and posses health risk to humans.

According to the EPA’s Chemical Contaminants – CCL 4 that was recently drafted, it is found that non-biological contaminants are possibly present in tap and drinking water [183] . The majority of organic water contaminants are from industrial activities, environmental degradation, agricultural run-off and naturally-occurring elements. Whereas, an inorganic water contaminants are the derivation of natural minerals resulted from erosions and runoff. With respect to the analysis of non-biological contaminants, chemical parameters such as pH, hardness, temperature, dissolved organic nitrogen, total organic carbon (TOC) and chemical oxygen demand (COD) are always considered. According to the WHO Guidelines for Drinking Water Quality (Fourth Edition), a derivation of the tolerable daily intake (TDI) should be taken into account when involving drinking water municipal [184] .

2.2.1. Capillary electrophoresis (CE)

Capillary electrophoresis (CE) is a separation technique used to analyzes molecular polarity and atomic radius based on ions electrophoretic mobility. The movements of analytes through electrolyte solutions are directly proportional to the applied voltage, where high electric field leads to faster mobility. CE has the ability to perform separation in capillaries with diameters in mm and in micro to nano-fluidic channels. The CE technique is often related as capillary zone electrophoresis (CZE), however, there are other CE-based methods which include capillary gel electrophoresis (CGE), capillary isoelectric focusing (CIEF) and micellar electrokinetic chromatography (MEKC) [185] . There have been several studies related to the determination of NH 4+ , Na + , K + , Mg 2+ and Ca 2+ ions in environmental samples using the CE detection method [185] .

The determination of existing unions (nucleotides, metal-ethylenediaminetetraacetic acid, haloacetics, etc.) in aquatic environments is achievable by analyzing their electrophoretic mobility within detection wavelength of 350/20 nm. Researcher have proposed a method consisting 50-μm straight capillaries with baseline noise modification to determine existing unions [186] . This method was found to be useful for the screening analysis of anions in liquid samples. Anions separation was executed simultaneously using a highly alkaline pH condition to attract a negative charge, triggering migration towards anode as shown in Fig. 7 . Because of this, the existing anions in aquatic environment can then be analysed based on their electrophoretic mobility within selective wavelength [187] . CE technique has also been reported in peptide analysis, qualitatively and quantitatively [188] .

A typical electropherogram of a 43-component (7 inorganic anions; 5 organic acids; 16 amino acids; 15 carbohydrates) anion standard mixture (Soga et al. [187] ).

Analysis on trace chloroanilines in water samples was developed by Pan et al. [189] using CE technique and the method could achieve LOD between 0.01 and 0.1 ng/L for eight aniline compounds within 25 min of detection. Under the optimum conditions, the enrichment factors were obtained within the range of 51–239 and exhibited linear calibration over three orders of magnitude (r > 0.998). Water contaminated by herbicide species is contagious to human health and potentially reachable to toxic levels. The identification and quantification of herbicides can be obtained using an extended CE method coupled with low voltage eigenmode expansions (EME) modelling technique [190] . The preconcentration and detection of environmental pollutants, such as 2,4-dichlorophenoxyacetic acid (2,4-D), 4-(2,4-dichlorophenoxy) butanoic acid (2,4-DB), and 3,6-dichloro-2-methoxybenzoic acid in water samples were executed using a Box-Behnken design (BBD) and response surface methodology (RSM) related to extraction efficiency. Because of this, herbicides could be detected using a novel MEKC method [191] . The composition of 25 mM borate, 15 mM phosphate, 40 mM sodium dodeclysulfate (SDS) and 3% (v/v) of 1-propanol at pH 6.5 was used as an optimum buffer. A successful LOD ranging from 0.02 up to 0.04 ng/g and LOQ of 0.1 ng/g was reported within the optimized conditions.

A similar method with the combination of online sweeping preconcentration in MEKC method was developed for the detection of five triazine herbicides in water samples [192] . However, under optimized condition, the LOD was slightly different with value shown in a broader range (0.05–0.10 ng/mL) in comparison to the conventional MEKC method as presented in Fig. 8 . Due to vast usage of animal-based fertilizers in agriculture, the contamination of water with estrogenic compounds cannot be prevented. These estrogenic compounds were found present in mineral and wastewater samples with an alarming rate. The adjoint detection method proposed by D’Orazio et al. [193] using ammonium perfluorooctanoate (APFO) – based MEKC was effective to detect 12 estrogenic analytes with LOD ranging from 0.04 to 1.10 μg/L.

Comparison of the electropherograms obtained by (A) conventional MEKC method (sampling: 1.0 μg/mL of the triazine herbicides in BGS, direct injection at 0.5 psi for 5 s), (B) the sweeping-MEKC method (sampling: 0.5 μg/mL in 50 mmol/L H3PO4 (pH 2.5), direct injection at 0.5 psi for 120 s) and (C) the combination of DLLME with the sweeping-MEKC method (sampling: starting from 5.0 mL of 10 ng/mL water sample for DLLME). Peak identifications: 1: prometon; 2: simetryn; 3: propazine; 4: atrazine; 5: simazine; u: unidentified peaks (Li et al. [192] ).

Since contaminants in water can exist in nano-scale measures, application of nanoparticles together with CE techniques has been presented in order to achieve a safe and sustainable water supply. Sensitivity of analytes detection could be improved using electrophoretic mobility integrated near the inlet capillary. Whether the analytes bind specifically to the sensitive capillary, deployments of several arrays of these capillaries are required for simultaneous analysis. Because of the complexity of equipment arrangements, its industrial implementation is still ambiguous.

The commonly used techniques to distinguish nanoparticles are based on either gel electrophoresis or capillary electrophoresis [194] , [195] , [196] . Detection of engineered nanoparticles (ENPs) such as bioconjugated quantum dots, have been demonstrated using polyacrylamide gel electrophoresis (PAGE). However, due to small pore size of polyacrylamide (PA) gels (<10 nm), the separation method is not practical. Hence, Hanauer et al. [197] introduced the separation techniques for nanoparticles with applications of agarose gel electrophoresis (AGE), with pore size of agrose gel ranging between 10 and 100 nm. The work presented a derivation of silver and gold nanoparticles using polylethylene glycols that, acted as electrophoretic mobility controller. However, findings turned out to be unsatisfactory for gold nanoparticles separation at common CE conditions in comparison to the ICP-MS and UV detection methods [198] .

Bioconjugated quantum dots [199] , [200] and protein-nanoparticle interactions [201] have also been found to be able to distinguish environmental samples using CE. The detection of nanoparticles continued to be favourable in metal and metal oxide nanoparticles separation by using various inorganic buffers as electrolytes [194] , [195] , [196] . Using CE sodium dodecyl sulphate, various nanoparticles, such as Au, AU, Pt and Pd, were able to be detected with resolution as low as 5 nm [202] , [203] . The CE technique is getting more and more popular and a number of publications on the modification and integration of various CE-based detection methods could be found in literature. These advanced methods intend to overcome some limitations of CE instrument, such as unsymmetrical peak identification [204] , poor mobility time repeatability [205] , low separation resolution [206] and limited injection efficiency ranging only from 10 −3 to 10 −7  μL [207] .

2.2.2. Gas/Liquid chromatography-Mass spectrometry (MS)

Mass spectrometry (MS) is an analytical tool used to measure molecular mass of targeted sample. Mass spectrometer used for environmental analysis is commonly coupled with a separation method such as gas chromatography and liquid chromatography [208] . Recently, there have been combinational methods for determination of non-biological contaminants in water samples. For instance, Albishri et al. [209] used a UV-based reversed phase liquid chromatography with integration of liquid phase micro extraction for the determination of five organophosphorus pesticides with concentration of 0.01–0.1 ng/mL in tap, well and lake water samples. The derivation of pesticides in water samples has been detected by using a novel approach of sensitive ultrasound-assisted temperature-controlled ionic liquid (IL) diquid −phase microextraction combined with reversed-phase liquid chromatography. Five organophosphorus pesticides were investigated by varying the IL type, IL volume, ionic strength, sonication time, heating/cooling temperature, centrifugal time and speed. In comparison to the conventional liquid chromatography technique, the proposed method improved the extraction efficiency up to 98%. A selected group of pesticides in tap and drinking water was also distinguished using liquid chromatography in which pesticide dimethoate, carbaryl, simazine, atrazine, ametryne, tebuthiuron, diuron and linuron were perfectly isolated ( Fig. 9 ) [210] . A series of gas chromatography (GC) with a nitrogen-phosphorus detector (NPD) has also been reported with the capability of detecting trace amount of eight different type of pesticides presented in drinking water [211] . Despite providing high detection sensitivity ( Fig. 10 ), GC analysis is considered unsuitable for non-volatile and high molar mass compound such as pesticides [210] .

Chromatogram obtained for the separation of pesticide standards using liquid chromatography: (1) carbendazim, (2) dimethoate, (3) simazine, (4) tebruthiuron, (5) carbaryl, (6) atrazine, (7) diuron, (8) ametryne adnd (9) linuron (Queiroz et al. [210] ).

Chromatogram obtained for separation of pesticides using mixed standard solution (gas chromatograph) (Qian et al. [211] ).

Quantifications of nicotine in tap water and wastewater at trace levels were performed using a novel gas chromatography mass spectrometry (GC–MS) with liquid–liquid extraction process and a satisfactory LOD of 2.6 ng/mL was reported [212] . A study on detection of benzene, toluene, ethylbenzene and xylenes in the water sample was conducted by Franendez et al. [213] using the magnetic solid-phase extraction (SPE) method prior to GC–MS technique. The experiments showed LOD of 0.3 μg/L for benzene and 3 μg/L for other compounds.

Disinfection by-products (DBPs) are very likely to be found in drinking water and are strongly linked to cancer [214] , [215] . To date, profound usage of GC–MS for the determination of DBPs is due to the wide range of available mass spectral library databases [216] . Unfortunately, GS-MS has limited detection sensitivity, which can only detect compounds with low molecular weight (< 800 g/mol) [217] . Hence, a new technique that combined multiple solid phase extraction (SPE), dual-column liquid chromatography high resolution-LCMS and precursor ion elimination (PIE) was proposed by Richardson et al. [218] . Verstraeten et al. [219] and Erickson et al. [220] also employed such technique to analyse public water samples that contained hormones, pharmaceutical personal care products (PPCPs), polyfluoroalkyl substances and herbicides. Barnes et al. [221] validated the occurrence of pharmaceutical contaminants using LC–MS and reported that the concentrations of sulfamethoxazole and carbamazepine that exceeded 0.1 ng/L were recorded in 9 wells while another 5 wells showed 0.07 ng/L concengration. The determination of pharmaceutical contaminants could also be found in work of Llorca et al. [222] in which LC–MS was used to detect 33 analytes. Other works on the detection of sulfamethoxazole and carbamazepine in drinking water and groundwater can be found elsewhere [221] , [222] , [223] , [224] .

Separately, perfluorinated chemicals (PFCs) are a large chemical compound that are used in wide variety of heavy industries, such as aerospace, automotive, buildings and construction, due to its ability to reduce friction [225] . Unlike other chemical excess, PFCs are frequently released into the aquatic environment due to the massive usage in industrial activities and food productions. As previously reported, LC–MS technique could be used to analyze the content of water samples containing perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) with detection limit as low 10 ng/L [226] .

Field-flow fractionation (FFF) technique with higher analytes sensitivity and selectivity is a family of analytical separation technique used to extract detailed information on chemical composition, functionality and molecular architecture. It was initially introduced by Calvin Giddings to separate macromolecules and colloids [227] . The working principle of FFF is due to the use of external field that is applied perpendicularly to the direction of phase flow within a capillary to derive analytes separation. In comparison to traditional chromatography approach, FFF is beneficial to those of analytes detection techniques in terms of effective separation components, minimum shear degradation, ultra high resolution, adjustable separation ability and mild operation condition which allows fragile analytes analysis [228] , [229] , [230] . Measurements of colloidal phosphorus in natural waters were demonstrated using an asymmetric FFF technique integrated with high resolution of ICP-MS and membrane filtration [231] . This separation technique comprises two categories, which are centrifugal force-based sedimentation (SdFFF) and perpendicular flow-based (FlFFF) that is mainly used for discrimination of engineered nanomaterial (ENMs) in aquatic environments. High density particles, such as metallic nanoparticles with a relatively large size were detected by SdFFF [232] , [233] , [234] owing to their ability to achieve higher resolution during separations.

The use of analytical techniques to detect and quantify ENPs in environment is limited due to the complex matrices of samples and extremely low concentrations of nanoparticles. A novel approach based on coupling hydrodynamic chromatography (HDC) and FFF has been proposed to separate polystyrene, silver and gold nanoparticles from environment samples [235] . Measurement of hydrodynamic radii of nanoparticles and retention time was conducted using calibration curves and an exceptional polynomial fit from on-line detectors (DLS, SLS) with size ranging between 20 and 80 nm (R 2  = 0.98) could be obtained ( Fig. 11 (a)). Comparison of nanoparticle hydrodynamic radii was further made using manufacturer’s off-line detectors (DLS, AUC, SP-ICP-MS) with detection of particle radius of 20.3 ± 0.6 nm at 24.7 min as shown in Fig. 11 (b).

(a) Calibration curve based on the polystrene (black points), gold (red point) and silver (pink points) standards and (b) Partial chromatogram for river water sample spiked with 4 μg/L of nAg following separation by HDC and detection using SP-ICP-MS (Proulx et al. [235] ). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

By combining methods for differentiation of nanomaterial characterization, the possibility of assessing silver nanoparticles in water samples is achievable. As reported by Antonio et al. [236] , the proposed combined technique (asymmetric flow field-flow fractionation, ICP-MS and UV–vis) enable the agglomeration process of silver nanoparticles in artificial seawater. Several works have been carried out to investigate the stability and detection of nanoparticles, including Ag, Au, Se, TiO 2 , and ZnO in natural systems [237] , [238] , [239] . The existence of nanoparticles in the aqueous environments must be taken into account since the main factors causing the derivation are due to surrounding effects, such as temperature, light, oxygenation and total surface area [240] , [241] . In addition, separation techniques related to inorganic engineered nanomaterial are currently expanding with the aim of achieving nano domain analysis.

A method of coupling ICP-MS with FFF technique was used by Lyven et al. [242] to differentiate iron- and carbon-based colloidal carriers based on the particle size difference. Peak deconvolution analysis was used to quantify and estimate the distribution between organic carbon- and iron-rich colloids and the results indicated the consistencies of chemical properties from two carrier colloids [243] . Although chemical chromatography (HPLC, GC, GC/MS) could offer identification and quantification of analytes, it is only able to detect specific contaminants [244] . Besides, it often involves multi-stage protocols and suffers a number of biases, such as loss of absorption due to the high reactivity [245] . Nonetheless, it must be pointed out that the chemical chromatography is still the preferable method for chemical identification.

3. In-line sensor-based monitoring

Continuous monitoring for microbiological contaminants, especially for chemical contaminants, is a challenging task due to the presence of variety of contaminants at low concentrations [246] . As discussed in the previous sections, standard/sample-based laboratory methods for detection of various water contaminants are often based on the discontinuous approach (off-line analysis). Hence, a sensor-based detection methods such as sensor placement approach (SPA), microfluidics, spectroscopic techniques and biosensors have been tremendously evolved over the last decade.

3.1. Sensor placements approach (water quality sensors)

In contrast to conventional analytical methods, deployment of multiple sensor station in the distribution system is an alternative approach to detect contaminants in a simultaneous manner. In recent years, multi-parametric sensor arrays have emerged to be less cost-oriented and user-friendly to monitor quality of water ecology systems [247] . The performance of multiple sensor stations was evaluated by Jeffry et al. [248] using real-time contaminants drinking water and the sensor was reported to be able to detect the existence of aldicarb, glyphosate, colchicines and nicotine in water samples. The data analysis was conducted based on a combination of both distance-based statistics and contaminant transitions.

An alternative low-cost sensor network was developed by Lambrou et al. [249] using multiple electrochemical optical sensors to detect E. coli and As in real-time distribution system. The system comprised of six different types of water quality parameter sensors that were able to determine water flow, temperature, conductivity, pH, ORP and turbidity simultaneously as shown in Fig. 12 . As water distribution system is increasingly polluted with low concentration hazardous chemical, there is an urgent need for rapid detection.

System architecture sensor placement approach comprising three main subsystems: PIC32 MCU based board used for central measurements, a central node for data transmission via internet, charts and email/message alerts and water quality sensors installation (Lambrou et al. [249] ).

Similar method was also reported in the work of Che et al. [250] , but it was found that EC and UV-254 sensor failed to detect contaminants, owing to the possible hidden responses and fluctuations from water source. Instead of using single sensor researchers were preferable to determine water quality based on multiple sensor placement approach [251] , [252] , [253] . Since obtaining optimal sensor station requires certain expertise, Berry et al. [254] and Tratchman [255] introduced a complex optimization tools, TEVA-SPOT and PipelineNet that employed EPANET to provide guidance for simulation in water distribution systems. The sensor placement method for water contaminants detection however is relatively complicated [256] , [257] .

Researchers have different views regarding the use of multiple water quality sensor approach. Hypothetically, contaminants could present at any point within a specified time period along the water distribution system. Some contamination events may not be detected because of inaccurate sensor placements and low detection sensitivity [258] , [259] . Ever since the development of water monitoring technologies, detecting the presence of contaminants in the water supply has become an extremely complex task. Arrays of sensor platforms were implemented to identify unique contaminations according to the sensor capabilities [260] . A study conducted by Ostfeld et al. [261] evaluated the performances of different sensor placements by experimenting with 126 sensor node stations and 168 pipes, which were subjected to a simulation period of 48–96 h per step. Inaccurate analysis might occur as a result of long transmission delays and slow response times in capturing data using sensors [262] , [263] , [264] . In addition, sensor placement approach that requires major in-pipe water distribution system alterations could increase cost [265] . Although sensor placements are among the most analyzed research area, obtaining a ‘perfect sensor’ when any concentration of contaminants is in contact with the sensor leads to an immediate response, which is considered to be a complete uncertainty.

3.2. Microfluidic sensors

Micro-scale technologies have been previously used for detection of non-biological contaminants such as pesticides [266] , [267] , phosphate [268] , Hg in water [269] , ammonium ion [270] and As ions [271] . In addition, this technology has shown tremendous LOD improvements of biological contaminants. Previous work has successfully identified E. coli O157 and Salmonella typhimurium using microfluidic reactor with volume of 29–84 nL [272] . Another example of E. coli identification that established by Schwartz and Bercovici [273] involved the integration of high concentration labelled antimicrobial peptides (AMPs) within microfluidic channel, aiming to achieve limit of detection as low as 105 cfu/mL and yield 4 bacteria in 2 min. The fabrication of micro-scale sensors can be found in the work of Jiang et al. [274] in which the customized sensors were employed to determine the bacteria concentration in drinking water. Having to adopt the principle of electrical impedance spectroscopy method, the design of a low cost and sensitive bacteria sensor was successfully developed ( Fig. 13 ), aiming to achieve pre-concentration microfluidic-based with LOD of 10 bacterial cells per mL. As shown, wireless system integration is based on Bluetooth receiver via Android cellphone (HTC ONE X), a microcontroller and impedance converter network analyser (AD 5933). The fabrication of microfluidic sensors however varies depending on field of applications.

Wireless mobile phone bacteria sensing system, (a) syringe injection of water sample into sensor package, (b) EIS bacteria sensor package, (c) schematic diagram of smartphone sensing app and wireless bacteria sensor and (d) schematic diagram of wireless sensing system (Jiang et al. [274] ).

A miniature microfluidic using long-period fibre grating (LPEG) was designed by Wang [275] and used to measure chloride ion concentration in water samples. The fabricated unit was found to achieve excellent correlation (R 2  = 0.975) with light intensity transmitted at 1550 nm. The result showed that the miniature microfluidic could detect chloride ion at concentration of 5.0 × 10 −6  mW/mg/L within 2400 mg/L limit of detection. The design and actual setup of LPFG-based microfluidic chip is shown in Fig. 14 . Optical-based microfluidic platforms were also found useful to measure various types of chemical and biomolecules at different concentrations [276] , [277] , [278] .

(a) Schematic diagram of experimental setup for LPFG-based microfluidic chip system, (b) Actual setup of LPFG-based microfluidic system, (c) Microfluidic chip and (d) 3D illustration of the structure and fluidic operation (Wang [275] ).

Digital microfluidic (DMF) enables the precise control of droplets dispensations on a microliter (10 −6  L) to picoliter (10 −12  L) scale for liquid volumes of the fabricated micro-device. Recently, the studies based on nucleic acid amplification and detection assays using DMF technology could be found in several work [279] , [280] , [281] . The implementation of chip-based nucleic acid assays have led to a significant increase in microfluidic sensor production for the purification and extraction of nucleic acid samples. According to Kaler et al. [282] , DMF method is beneficial for proteomics and nucleic acid-based bio-diagnostics application via liquid handling technology, allowing execution of pre-treatments and analysis process on a single device.

A droplet-based sensor embedded on an electro wetting-on-dielectric (EWOD) microfluidics system was also developed by Zengerle et al. [283] by integrating SU-8 polymer micro resonator layered on top of an EWOD plate system. This system only required a single droplet of less than 100 nL of a liquid sample to trigger the sensing process. This trial was the first demonstration of a EWOD-based micro resonator-sensing system with full droplet movement capability. Because of its low power consumption coupled with extremely small sample volume and small data sets, microfluidic sensing platforms are chosen for portable point-on-care (POC) diagnostic devices. In contrast to the low potential of the DMF system for large deployments of chemical and biological micro-reactor applications, an intelligent digital microfluidic system with fuzzy-enhanced feedback for multi-droplet manipulation has been developed by Gao et al. [284] . This pilot DMF prototype aimed to (i) improve complicated image signal processing by using the ability to profile different droplet hydrodynamics, (ii) preserve up to 21% of the charging time using fuzzy-enhanced controllability to enhance the DMF chip’s lifetime and (iii) employ automation of multi-droplet routing countermeasure decisions in real-time. The DMF module was made of the following three operation layers: a chip holder, control electronics and a field-programmable gate array (FPGA) board. Volume growth of droplets enabled the execution of sensing module responses that were assembled between two adjacent electrodes. Samples of DI water, phosphate buffered saline (PBS) and 1% bovine serum albumin (BSA) in PBS were injected via a syringe pump into a 4 × 11 mm hole with a constant flow rate of 5 μL/min. The analysis was then carried out using a 0.1 mol/L concentration of Na 2 CO 3 , PBS, CaCl 2 and FeCl 3 .

Attempts have been made to use an identical approach to detect E. coli in drinking water [285] , nutritional biomarkers [286] , prostate specific antigen (PSA) [287] and A. acidoterrestris lysates in milk, juice and water [288] . The abilities of the microfluidic analytical platform to detect water contaminant at a very low concentration and minimum reduction of particle size could promote the usage to distinguish nanoparticles characterization in water samples. A single microfluidic channel has the ability to detect nanoparticles as small as 220 nm [289] . The proposed method utilized microfluidic resistive pulse sensor and was integrated with a submicron sensing gate and two detecting channels using differential amplifier. Detection of CdS electrochemical quantum dots nanoparticles in water sample was able to be detected using integration of hybrid polydimethylsiloxane-polycarbonate microfluidic chip with screen printed electrodes [290] . Under optimized condition, the fabricated microfluidic chip was able to detect CdS QDs with concentration of 50–8000 ng/mL, whilst having LOD of 0.0009 μA/(ng/mL). For more details regarding the detection and quantification of inorganic nanomaterial using microfluidic chip, one can refer to the relevant review article [291] .

There is a huge potential associated with microfluidic sensor fabrication and the introduction of a new cost-effective measure is forecasted to increase in response to commercialization demands [292] . Previously, the issue on chemical contaminant analysis using microfluidic platform was raised due to lack of ability to conduct concurrent analysis [293] . However, many studies have developed a method combining microfluidic and microarrays technologies, enabling multiplex detection of contaminants [294] , [295] , [296] . The pre-treatment of samples however is vital when utilizing chip-based microfluidic sensors. It must also be noted that this additional step may cause the overall process and operation system more complex [297] , [298] , [299] , [300] , [301] .

3.3. Spectroscopic techniques

In principle, spectroscopic technique employs a light electromagnetic radiation source to interact with matter, and requires a specific probe (depends on the features of a sample) to analyze chemical or biological components. The spectra obtained from different spectroscopic techniques provide an understanding of the properties associated with light electromagnetic radiation and its interaction with matter. Nowadays, there are many types of spectroscopic techniques available for utilization. These include impedance sensing, light emission, vibrational, Raman and surface-enhanced Raman spectroscopy.

3.3.1. Impedance sensing approach

Electrical impedance spectroscopy (EIS) and dielectric impedance spectroscopy (DIS) are the types of impedance sensing technique. Both spectroscopies have been productively used for the bio-detection of targets, such as bacteria and biomarkers. However, EIS is most likely the preferable method for bio-sensing detection applications [302] . It is correlated with microfluidic sensing systems, which implies the integration of electrodes (a working electrode, reference electrode, and counter electrode) that can be either conventional or screen-printed electrodes. Multi-layers of screen-printed electrodes are implemented on flat substrate surfaces. EIS has been widely used in fields, such as medicine, water quality analysis and environmental engineering [303] , [304] , [305] , [306] , [307] .

Previously, the development of impedance screen-printed electrodes has been explored by Zhang et al. [308] to monitor 2,4,6-trinitrotoluene (TNT) in water using a bio-sensing platform ( Fig. 15 ). The integrated system developed with an alternative current (AC) impedance of approximately 20 kHz consisted of an AD5933 impedance analyzer chip, an Arduino microcontroller and a smartphone-based platform. The detection limit concentration is as low as 10 −6  M TNT-specific impedance properties. Initially, the TNT was purposely attached to the peptide that was bonded to the electrode surface. This was to prevent electron transmission and allow electrode interface impedance. Signals was then transmitted to a smartphone app on real-time basis. The detection of TNT steadily increased at low frequency ranging between 10 and 30 kHz. However, the optimum frequency-dependent impedance measurement for TNT detection was reported to be 20 kHz [308] .

Smartphone-based impedance monitoring system principle and design for TNT detection, (a) Binding of biorecognition elements (peptides) and TNT analytes on the surface of the electrodes, (b) Schematic of screen-printed electrodes, containing working electrode, counter electrode and reference electrode, (c) Basic diagram of hand-held smartphone-based system, (d) Impedance monitoring device consist of expansion and arduino board and (e) Welcome window of the App in smartphone for TNT measurements (Zhang et al. [308] ).

On the other hand, Ghaffari et al. [309] developed a low-cost wireless multi-sensor to detect nitrate fertilizer in water sample using DIS platform. The measurements were monitored and controlled via a wireless network system. The DIS platform was developed by assembling commercial microelectronics components that included a multiplexer, a dielectric spectroscopy analyzer, a digital signal controller and a ZigBee transceiver. Similar to this approach, another impedance-based microelectronic sensor, known as a Real-Time Cell Electronic Sensor (RT-CES) was also developed by Xing et al. [310] for dynamic monitoring of cyto-toxicants in the water supply. Measurements of cells, including the cell number, viability, morphology and adherence, were carried out using an electrical impedance-based sensor. The system consisted of a circle-on-line microelectrode array that was specially designed to cover almost 80% of the bottom of the sensor area. These microelectrode arrays were then assembled on a glass slide separating 16-layered wells with 9 mm spacing between each one. The ability of the sensor was to select wells for measurement automatically and to conduct testing continuously.

3.3.2. Light emission/luminescence spectroscopy

The principle underlying light emission or luminescence spectroscopy is the high-energy level absorbance of molecular matter that emits energy as light. The excitation of a high-temperature energy source induces light emitted from matter, which is known as an optical emission. Classifications of light emission spectroscopy include absorbance, reflectance, chemoluminescence, luminescence and light scattering signal and optical-based spectroscopy [311] . Of the reported luminescence platforms, several characteristics have been associated with light emission spectroscopy. For instance, reagent-mediated activity in the form of a light emission medium was employed as an auxiliary reagent to detect and identify contaminants [312] . These emerging techniques have been extensively discussed as a potential tool to monitor water quality in-situ [313] .

Several studies have acknowledged the potential use of fluorescence spectroscopy in detecting dissolved organic matter (DOM), which can be used as an alternative for standard water quality parameters [314] , [315] , [316] . In addition, the fluorescence spectroscopy approach has also been reported useful to quantify the structural composition of DOM in water samples collected from eight different urban rivers [317] . In this work, the quality of river samples was analyzed using multivariable analysis by segregating the structural composition of DOM that was collected from the west side of Shenyang City, China River. River pollution is increasing at an alarming rate because of high concentration of phosphorus and ammonia nitrogen, released from industrial and domestic sewage [317] . Measurements of ammonia nitrogen (NH 4- N), nitrate nitrogen (NO 3- N) and DOC were carried out via the fluorescence-based water quality analyzer known as the YSI 600 multi-probe. Such analyses however required respective reagent to perform.

As the characteristics of lakes and rivers are influenced by climate changes, on-going industrial wastewater release and anthropogenic activities, in situ continuous detection and quantification of river water quality are thus urgently needed. A portable chromophoric dissolved organic matter fluorescence sensor (FDOM) is available in the market and can be used to monitor the conditions of different water environments such as wetlands, watersheds and tidal marshes. FDOM can be considered for the detection of DOC concentrations as well as other biogeochemical compositions [318] , [319] , [320] . Niu et al. [321] developed potential applications for real-time water monitoring using FDOM, by taking 218 water samples from Lake Taihu, China as target samples. The CDOM concentration of the lake water was determined using an in-situ CDOM fluorescence tool invented by TRIOS GmbH, Germany, with emission wavelengths of 370 and 460 nm.

Apart from the fluorescence-sensing platform, a great deal of the current methods is based on the liquid-based microelectrode glow discharges developed by Wilson and Gianchandani [322] . To improve the detection limit, the liquid electrode spectral emission chip (Led-SpEC) was used to trace Na and Pb concentrations in water samples with detection limit of <10 mg/L and 5 mg/L, respectively. Similar to the glowing detection techniques, a patented submersible spectrofluorometer for the real-time sensing of water quality was developed by Puiu et al. [323] . The submersible spectrofluorometer was designed to extend the fluorescence measurements into an LED excitation spectrum interval between 200 nm and 1100 nm, enabling the instrument to detect chlorophyll-a concentrations as low as 0.2 μg/L. A comparison of the temperature, turbidity, water Raman scattering and fluorescence emissions parameters was also conducted to validate the design.

Similarly, measurements of the DOM concentrations in water were also extracted by using a dipping-based deposition method [324] . A water sensor for global oxygen detection was invented, and it is generally known as anodized-aluminium pressure-sensitive paint (AA-PSP). AA-PSP was anodized in sulphuric acid followed by the dipping of the anodized aluminium coated model into a luminophore solution. It was placed at the bottom of a water tank, and a xenon lamp was excited through a 400 nm band-pass filter. Fourteen-bit CCD cameras were used to capture luminescent images through an optical fibre located 90 mm from the AS-PSP. The work found that AA-PSP was capable of detecting oxygen with a sensitivity of 4.0%/mg/L at a temperature of −2.8%/°C.

Light emission due to reagent-mediated activations, such as glucose, benzalkonium chloride and chromium (VI), has also been introduced over the years [325] . This approach is similar to the one used by Sharma et al. [326] to evaluate As and E. coli contamination in the India River via bioluminescent bio-reporter. For more details about the light emission spectroscopy via an optical fibre sensor platform, one can refer to the work conducted by Ibanez et al. [327] and Chong et al. [328] .

In relation to water quality monitoring, the detection of E. coli and B. subtilis in drinking water by employing quartz tubes as optical light guidance tools with UVC-light emitting diodes (LEDs) has been developed by Gross et al. [329] . The experimental setup consisted of two containers, a soda-lime AR glass and a 100 cm quartz glass, filled with 9 mL of E. coli and B. subtilis . These samples were compared in relation to their disinfection rates with and without the total reflection of UVC radiation for time interval of 10, 40 and 90 s. The determination of E. coli was also discussed in the work of Miyajima et al. [330] in which a fibre-optic fluoroimmunoassay system was employed to monitor the fluorescence dynamics. In addition to the optical spectroscopy approach, a multi-wavelength based optical density sensor for monitoring microalgae growth in real-time has also been established by Jia et al. [331] . In comparison with the previous studies, the sensing system constituted a laser diode module as a light source, photodiodes, a controller circuit, a flow cell and temperature controller housing for the sensor platform. The detection of the microalgae concentration was identified via optical density measurements at wavelength of 650, 685 and 780 nm.

Although emission, optical and luminescence methods are among the most commonly used water contaminant detection technologies, there are associated with several drawback. One notable drawback is the sensitivity of light emission spectroscopy to changing temperatures. Because of this, it requires expert guidance during monitoring process [332] . Furthermore, as the techniques are sensitive to illumination, extensive care must be taken when they are in-use.

3.3.3. IR, MIR and NIR

Several studies have been conducted to identify chemical/biological compositions, monitor reaction progress and study hydrogen bonding using Infrared (IR) spectra measurements based on three different spectra, i.e., the near-infrared (NIR), mid-infrared (MIR) and far-infrared (FIR). The IR spectroscopy is a noninvasive technique, known as a ‘ green ’ analytical method due to its reagent-free approach [333] . Instead of analysing measurements based on a singular mean or maximum value, compact data sets provided by employing vibrational spectroscopy can be easily interpreted, resulting in a continuous detection of contaminants and increasing the chance to overlook high contamination [334] .

The commercial MIR spectrometer has been expanding for the use in environmental monitoring assessments due to its dense spectral information and high intensity of its spectral peaks [335] . Previously, MIR spectrometer was reported for oil and grease determinations using tetrachloroethylene extraction [335] . A 100 mg/mL oil and grease solution, that contained octanoic acid and isooctane, was used as the target sample. Absorbance measurements were analysed using a PerkinElmer ® Spectrum™ 400 FT-IR spectrometer in MIR mode.

A comparison between NIR and MIR reflectance spectroscopy for measuring soil fertility parameters has been reported by Reeves et al. [336] using IR spectra method. The combination of these techniques with chemo-metric analysis led to good calibration for the detection of organic carbon, total nitrogen (TN) and soil texture. However, it appeared that MIR tended to provide better calibration than that of the NIR region. These precise new approaches for the acquisition of soil data correlate to various degrees of MIR abilities. Despite the high cost in comparison with NIR and UV sensors, the advantages of using MIR sensors outweigh its disadvantages to end users.

A simultaneous quantification analysis of xylene, benzene and toluene isomers in water has been successfully performed with detection limits reported to be 20 ng/L, 45 ng/L and 80 ng/L, respectively [337] . This study developed an evanescent field spectroscopy that correlates with ATR crystal or MIR transparent optical fibres that serves as an optical transducer. Approximately 18 min of operational time response was needed to determine the solute concentrations in water samples. In contrast to the MIR measurements, the in-situ monitoring of water parameter composition by NIR spectroscopy is increasingly favourable among scientists worldwide. This approach includes the detection of nucleation and polymorphic transformations using different types of sensor arrays [338] . A novel approach to chemo-metric analysis was introduced by applying a composite sensor array (CSA) to obtain better information and to detect various crystallization mechanisms. A comparison between CSA-based techniques using Raman, NIR, FBRM, PVM and thermocouple probes was made to determine the optimal robust detection of matter. Having a clear view of nucleation and polymorphic transformation was found to be very informative in relation to Raman and NIR spectra relative to other probe. However, the ability to detect nucleation, crystal growth and polymorphic transformation by NIR was limited due to presence of water in the system [338] .

A novel and simplified optoelectronic system was designed on the basis of an NIR technique at wavelength acquisitions of 630, 690, 750 and 850 nm using a LED as a light source for evaluating fruits and vegetables [339] . Validation was performed on dye solutions resulting in the system’s ability to discriminate among the reflectance rate’s low limit levels, which were in the range of 2–4%. The tendency to reduce the cost and size of instrument analysis has led to the development of an LED device as a source of narrow bands that are able to excite NIR radiation. As NIR can be used to measure translucent packaging material, there have been many deployments of NIR instruments in raw material quality control such as development of non-invasive detection of hydrogen peroxide and its concentration in a drinking bottle [340] .

3.3.4. Raman in comparison to surface-enhanced Raman spectroscopy

The principle of Raman spectroscopy correlates the excitation of atoms or molecules to a higher energy state using monochromatic light radiation. When an atom at a higher energy level returns to the ground state, energy is dispersed by Rayleigh scattering, which results in the frequency shifting of atoms known as the Raman effect. The basic Raman experimental setup consists of an angle configuration (90° and 180°), a wavelength selector, a filter, a mirror and an excitation source.

In developing advanced technology for analyte detection, an approach using Raman spectroscopy in microfluidics (MRS) was reported in the work of Ashok and Dholakia [295] . The Raman spectroscopy detection was assembled using an on-chip fibre with a polydimethylsiloxane (PDMS)-based microfluidic platform. The setup of a PDSM-based chip via soft lithography as presented in Fig. 16 involved an excitation probe, fluidic channels, a collection probe and an inlet and outlet. Device validation was conducted using a urea solution with a 200 mW laser at a 785 nm excitation wavelength with an acquisition time of 5 s. The minimum detection limit is 140 mM.

(a) Depiction of integrated microfluidic SERS device under LabRam Raman spectrometer. The inset shows an SEM image of the silver-PDMS nanocomposite at approximately 90 K magnification, (b) Schematic illustration of alligator teeth-shaped microfluidic channel. The confluent streams of silver colloids and trace analytes are effectively mixed in the channel through the triangular structures and (c) Schematic diagram of the integrated microfluidic chip and the biomolecular Raman imaging system. (Ashok and Dholaki [295] ).

An investigation of dissolved sulphate ions (SO 4 2− ) and methane (CH 4 ) in pure water was performed using Raman spectroscopy based on two new detection approaches, namely the liquid core optical fibre (LCOF) for SO 4 2− and an enrichment process for CH 4 [341] . Both methods employed Raman instrumental measurements, which primarily consisted of 0.3W laser power, a detachable dichroic mirror and a Raman optical fibre probe. An LCOF-based Raman signal for SO 4 2− was captured, and the analysis showed that the intensity was 10 times greater than that of conventional Raman setup. The extraction of CCI 4 for the detection of CH 4 indicated the location of the Raman peak at 2907 cm −1 with a methane concentration of less than 1.14 mmol/L.

The use of Raman spectroscopy for in-line water quality monitoring is also found in large-scale deployments due to its superiorities with respect to ease of use, portability, compactness and sensitivity to water environment [342] . Application areas such as environmental analysis of organic and inorganic samples [343] , tissue imaging [344] and liquid sample evaluations [345] have employed the Raman scattering spectroscopy technique to a tremendous extent. The non-destructive Raman approach has a fast operation time which enables detection of pesticides not only in the water samples but also food products. Raman spectroscopy is well recognized as a powerful method for the on-site evaluation and determination of chemical-biological molecular compositions [346] . However, one of the major challenges in bio-detection is the ability to instantly diagnose variety of low concentrated toxin contaminants. Hence, a cell-based Raman spectroscopy biosensor was introduced by Ioan [347] to differentiate the biochemical changes that occurred in cells with a large range of toxic agents. The target samples were nucleic acids, proteins, lipids and carbohydrates. An example of Raman spectra results is shown in Fig. 17 (a) in which different target samples were found in a living cell. More importantly, the cell-based biosensor Raman spectroscopy was able to quantify and qualify between live and dead cells as shown in Fig. 17 (b).

(a) Typical Raman spectra of a living cell and the main biopolymers components found in cells and (b) Comparison between Raman spectra of living and dead cells (Ioan [347] ).

A lower limit of detection is achievable by using the SERS technique in comparison with the standard level of LOD contaminants in water as set by the EPA [342] . Because of the high-intensity signal used in SERS, this technique is among the most useful tools for environmental science, electrochemistry and analytical chemistry/biology applications. The application of SERS technique is to discriminate antibacterial properties such as tranquilizer (phenothiazine), diclofenac sodium and diclofenac sodium β-cyclodextrin complex and non-natural β-amino acids [348] . In comparison with the Raman spectra signal analysis, the SERS spectra provided tremendous measurement information about the molecular structures and absorbance behaviours. A similar approach used for bacterial classification and discrimination was also reported in the work of Wu et al. [349] in which vancomycin-functionalized silver nanorod array (VAN AgNR) was considered. This analysis was conducted through the isolation of 27 different bacteria from 12 species. Measurements were obtained from an NIR diode laser excitation source at 785 nm, and underwent chemo-metric analysis using a combination of PCA and HCA approaches. The results showed that the use of VAN AgNR substrates tended to generate more SERS spectra, making the bacteria differentiation more accurately.

Although vibrational spectrometer measurement seems to be a promising technique for water monitoring technology, poor applicability to continuous on-line monitoring because of high water interferences must be addressed [350] . It has a tendency to operate efficiently because of its low light absorbance in water, but spectrum analysis presents a hurdle owing to the overtones and overlapping absorption bands [351] . For these reasons, the spectral bands become weaker.

3.4. Biosensors

Biosensors have been increasingly utilised in recent years in the field of pathogen detections. This kind of sensors has the ability to measure molecular signals by applying specific bio-recognition elements, such as enzymes, whole cells, antibodies and nucleic acids, which are integrated with electrical interfaces via transducer platforms to obtain measurable signals. Because of the high sensitivity and no requirement of sample pre-concentration step, biosensors offer a faster operational time in comparison to other conventional techniques [352] . An environmental pollution can be caused by both human activities and industrial discharge. A biology approach was reported to be useful in detecting heavy metal ions and bacterial compositions in water source [323] , [353] . Examples of genes that act as bio-receptors and have been previously determined by whole-cell biosensors are genetically modified mutant Pseudomonas sp. Dmpr , Pgp protein-based resistance genes and mer resistance genes [354] , [355] , [356] , [357] .

The efficiency of whole-cell biosensors to monitor the presence of water contaminants is dependent on bio-receptors, transducers and immobilization techniques [358] . For instance, study demonstrated by Kuncova et al. [359] using Pseudomonas putida strain TVA8 bio reporter was able to detect benzene, toluene, ethyl benzene and xylene in water samples with concentration in the range of 0.5–120 mg/L. Kubisch et al. [360] evaluated the robustness of different cell lines by detecting cytotoxic substances in wastewater using whole-cell biosensors via eukaryotic cell lines. The detection of selected target samples (i.e., NiCl 2 , CuSO 4 , nicotine and acetaminophen) was carried out on the basis of the cellular effects of each substance, which involved the pH, O 2 and the impedance of water. HT-29, canine hepatocytes, HepG2, L6 and NHDF cell lines were used to test the acidification rate of target samples, whereas V79 cells were used to obtain the respiration rate of the target samples. These cell-lines were assembled onto six different channels of a silicon surface biosensor chip. Nevertheless, the study was only aimed to identify the presence of contaminants. Quantifying single substances was not performed.

Nanosilver is known to be the most commonly used engineered nanomaterial for water treatments, thus it is likely that Ag + ions will be released to the environments [361] . Previous works have reported that such nanomaterial can be detected using label-free sensitivity biosensor approach [362] , [363] . In order to meet the need for reliable and sensitive methodology for the detection of nanoparticles in aqueous samples, a low-cost and portable detection assay was established to determine the reactivity and characterization of selected nanoparticles (Ag, Au, CeO 2 , SiO 2 and VO 2 ) with particle size ranging between 5 and 400 nm [364] . As a leading approach for detection and exploration of nanoparticles, whole-cell biosensors was developed by integrating golTSB genes from Salmonella enterica serovar typhimurium to induce Au (I/III) complexes as illustrated in Fig. 18 [365] . The quantification of gold nanoparticle complexes with concentration as low as 0.1 μM was able to be identified. The fabricated biosensor was also used to identify other metal ions, including Ag (I), Cu (II), Fe (III), Ni (II), Co (II), Zn and Pb (II). This contradicted a previous study where the response of golB genes only increased in response to Au (III)-complexes but not other metal ions [366] .

(a) The golTSB regulon regulated by Au ions in Salmonella enterica serovar typhimurium . A synthetic golTSB regulon was made by fusing a promoter-less lacZ reporter gene downstream of the golB open reading frame as a transcriptional fusion, (b) golTSB:lacZ transcriptional fusion was introduced as a single copy into the chromosome of E. coli , (c) A single clone was taken for testing and incubated overnight used to inoculate new media, then metals were added for incubation process (16 h), (d) Cells were permeabilized for access to the β-galactosidase produced by lacZ gene in the presence of Au and (e) The permeabilized cells were transferred to the electrochemical cell (Zammit et al. [365] ).

Another genetically engineered gene system found in the literature is yeast/mammalian cell line which was used to study galactosidase and luciferase activity in water sources [367] . However, it must be noted that engineered microbial biosensors do not provide complete quantification, but rather on semi-quantitative analysis [368] . Bioassays based on sulphur-oxidizing bacteria (SOB) reactor have also been used for the toxicity identification of Cr (III) and Cr (IV) in water samples [369] . The results indicated that significant increase in the slope of electrical conductivity could be obtained when SOB DNA was exposed to Cr (III) which may be caused by increment of salt concentration and exposures of unstable reactor conditions. On the other hand, a trace amount of atrazine in ground water supply was able to be identified using an integration of printed circuit board chip nanoporous alumina membrane label-free bioassays with electrochemical impedance spectroscopy [370] .

Bioassays adjacent to sophisticated biotechnology instrumentations demonstrate a fast response with a relatively simple method for identification of various water contaminants [371] . An inline water analyzer adjacent to whole-cell biosensor was established to carry out surveillance of water network using reporter gene of bacterial luciferase lux operon ( luxCDABE ) driven by E. coli promoter P rpoD [372] . In accordance with non-biological contaminants, a portable gold screen printed electrodes amperometric biosensor was developed by Salvador et al. [373] for the detection of Irgarol 1051 in water samples. The immunoassays reagents (As87- and 4e-BSA-based) used in this study were also found elsewhere [374] , [375] . Antibody peroxide (AntiIgG-HRP) was used for the binding reaction between target analytes and 4e-BSA competitor. In the presence of analytes, stable signals were able to achieve within 10 s upon initial acquisition. Separately, Belkhamssa et al. [376] designed a biosensor and used it to detect alkylphenol in water environment. The analytes detection was observed through an immunoreaction of 4-nonylphenol and the accuracy of developed biosensor was validated with enzyme-linked immunosorbent assay (ELISA). The outcomes are very promising with reproducibility of 0.56 ± 0.08%, repeatability of 0.5 ± 0.2% and LOD for nonylphenol as low as 5 μg/L.

Cytotoxic substances present in tap water could also be detected using bioluminescent E. coli bio-reporter strain TV1061 via integration of specific heat-shock grpe promoter with luxCDABE reporter operon [377] . The bioassays and microbial biosensors employed for the toxicity assessment involved Chlorella sp., Chlorella vulgaris, Monoraphidium sp., Scenedesmus subspicatus and Brachionus calyciflorus sp . [378] . Due to presence of countless toxic cyano-bacteria in water, Weller [379] made an attempt to study their existence using biosensors. Cyano-bacteria produces algal toxins in fresh water which are hazardous to aquatic ecosystem and human health. In order to reduce the risk of a possible breakdown of toxic cyanobacterial in drinking water, a multi-barrier approach, comprising prevention, source control, detection optimization and monitoring was recommended [380] .

On the other hand, a corresponding approach using an ammonia-oxidizing bacterium (AOB)-based nitrosomonas europaea biosensor has been designed by Zhang et al. [381] to determine allylthiourea and thioacetamide concentrations in water by measuring the ammonium oxidation rates. The results showed 0.17 μM and 0.46 μM for allylthiourea and thioacetamide , respectively. Another enzymatic-based (2-phospho- l -ascorbic acid trisodium salt) biosensor made of screen-printed carbon electrodes with modified gold nanoparticles was used to detect the tungsten ions present in tap water, purified laboratory water and bottled drinking water [382] . More information about the use of membrane-based biosensors for pathogen could be found elsewhere [383] , [384] , [385] , [386] .

Since E. coli is the frequently found contaminant in drinking water, a rapid and sensitive assays for bacterial identification is required. Rapid detection of E. coli was developed by Hassan et al. [387] using 4-methylumbelliferyl-β- d -glucuronide (MUG) substrates. The quantitative results was obtained due to the yielding of a fluorogenic 4-methylumbelliferone (4-MU) product via substrates hydrolization. Bacterial such as Klebsiella, Salmonella, Enterobacter and Bacillus , which were used for validating the MUG substrate specificity could result in significant fluorescence signals.

3.5. Wireless sensor network and remote sensing applications

Online monitoring is usually defined as a real-time measurements for sampling and analysis, providing larger data frequency in comparison to the conventional sample-based method. Online monitoring is more flexible and can be conducted in remote locations with faster response. The design of an online monitoring instrumentation strongly depends on the desired identification of water parameters. Table 3 summarizes the online water quality monitoring parameters for each category.

Parameters of online water quality monitoring.

Constructing an online monitoring detection system using wireless sensor network (WSN) could offer several advantages such as simultaneous data measurements, higher detection accuracy and sensitivity, sufficient data sets and easy monitoring assessments. Furthermore, WSN which requires low power consumption results in lower operating cost [388] . There have been several applications of WSN in water monitoring [389] , [390] . For instance, a WSN-based online monitoring system that consisted of data monitoring nodes, base station and monitoring centre was developed for the water quality assessment on the artificial lake at Hangzhou Dianzi University, China [391] . With this monitoring system, water quality parameters such as pH, dissolved oxygen, EC and temperature could be easily transmitted to a remote monitoring centre for further analyses via GPRS network. The measurement was automatically carried out every h generating sufficient data for monitoring purpose. On the other hand, Wu et al. [392] designed a self-powered mobile sensor for real-time contaminant detection in water distribution pipelines aiming to detect pH level, water hardness (Ca 2+ , Mg 2+ and HCO 3− ) and disinfectant-related ions (NH 4+ and CI − ). The mobile sensor operated within a 2.76 inch diameter of spherical-shaped shell consisting of potentiometric electrochemical-based multi-analyte biochip, microfluidics, electronics controller and energy harvesting system for power supply.

Furthermore, a low cost, miniaturized and sensitive microelectronic wireless nitrate sensor network was established for quantification of nitrate concentration in water environments [393] . The conceptual design of sensor network consisted of sensor interface (input and output parameter interface), a low-power processor and wireless communication named ‘Imote2′. To obtain wireless communication, electrochemical potentiostat was needed to be miniaturized and portable. The results showed that the microsensor was able to detect nitrate concentration in water samples with LOD between 25 and 83 ng/L. However, the implementation of such sensor network on field is still at the early stage of development.

Nitrate concentration in water samples was also identified using a similar approach based on a dielectric impedance sensor (DIS) node on ZigBee mesh communication [309] . The system was constructed to perform a continuous detection within a frequency between 5 and 100 kHz under 250 mW. According to the author, this was the first development of wireless platform via AD5933 touchscreen device and chemical sensor. The detection of waterborne disease-causing bacteria in water sources were carried out by Kim and Myung [394] using an enzyme substrate assay method. The colorimetric properties were monitored via Wi-Fi connection through a web-based user interface.

The use of WSN often involves multiple sensors to improve system stability and fault tolerance [395] . However, managing continuous long-range communication networks is a challenging task due to constant requirements in power supply. Energy harvesting system has been recommended to manage wireless-based sensor power supply, however, most energy harvesting systems rely on solar cells [396] . Several self-powering mobile sensors were found to be used in water distribution pipelines [397] , [398] . They are operated via rotational miniaturized motor, hydraulic energy and thermal energy in water-air-temperature gradient and kinetic energy in water pressure.

4. Algorithmic model-based event detection

Generally, there are two methods used to conduct detection algorithm. Initially, the model-based event detection method involves a signal-to-noise principles using laboratory and sensor test-loop evaluation. Indication of contamination events is derived from the chemical changes in background water quality signals which are responsive to integration of event detection technique [399] , [400] . However, it must be pointed out that the variation of the background water quality in the experimented systems would not be exactly the same as the variation of actual WDS [401] . Meanwhile, the second method used for event detection is based on signal processing and data-driven technique. Many studies have focused on the development of data-driven estimation model detection algorithm such as statistical, pattern-based recognition, machine learning approach, and image processing to detect contaminants based on real-time water quality measurements [402] , [403] , [404] , [405] . Contamination event detection in WDS has become a challenging research topic, in accordance with improved water system analysis.

At present, a wide variety of event detection approaches, including statistical, machine learning and optimization methods have been used. However, challenges in utilizing this methodology are the merging of single alarms that could be triggered by each quality indicator and the false detection alarms [406] . Because of this reason, an event detection model-based approach known as integrated logit detection (ILD) was proposed, which is an extended statistically based fusing process of dynamic threshold method (DTM) [406] . These two event detection models generate algorithmic evaluations to explore the most effective training phase performance for identifying contaminants using Receiver Operating Characteristic (ROC) curve, which represents the trade-off between false and true positive for probability threshold as shown in Fig. 19 . The ROC curve demonstrated that the higher true positive rate of ILD than that of rate of DTM. The observation resulted in high probability threshold of 0.9 and low probability threshold of 0.5 for ILD and DTM, respectively.

ROC curve comparing the performance of the two methods (ILD and DTM) on low type events (Housh and Ostfeld [406] ).

A similar methodology was used to study the effectiveness of two different event detection models of multivariate classification techniques. Commonly used sequence analysis of classifying events are an un-supervised minimum volume ellipsoid (MVE) and a supervised support vector machine (SVM) [53] . In terms of formulation and framework unity, the MVE model reduces the complexity of the algorithmic analysis in predicting contamination events relative to the SVM model. In addition, the Gaussian distribution data that were used for the MVE model approach could contribute high accuracy of 17% in separating modular boundaries. On the other hand, anomaly-based water contamination detection methods that include Artificial Intelligence (AI), have converged over the last decade. The classification of water quality measurements into anomalous categories often employs an artificial neural network (ANN) and a support vector machine (SVM) [407] , [408] , [409] .

In order to improve accuracy in data event modelling, combined method that included integration of data analysis from all sensors, hydraulic model networks and single spatial warning systems was introduced [44] . Several studies have made targeted improvements in event detection decision-making by extending a single-sensor event detection model to a spatial multiple sensor with an on-line approach. It has been previously reported that the conventional water quality sensors integrated with a real-time method based on the Mahalanobis distance approach was highly dependent on feature vector of each contaminant [55] .

Another type of model-based event detection approach is by using Monte-Carlo simulation. Such approach has been used to detect chlorine at various sensing locations along water distribution system [410] , [411] . The event detection model has a wide variety of optional algorithms based on the quality parameter analysis and their accuracies in determining different contaminants. Execution on the basis of multi-sensor fusion can also be achieved by deploying an extended Dempster-Shafer method [56] . Research on the prediction of future water quality parameters in the absence of automated on-line water quality sensors using an autoregressive model was also investigated to compare the performance of various event detection models. Several studies on chlorine concentration measurements in water have been reported using a Radial-Basis Function network [56] , [411] . Nonetheless, there are contradictory views on its efficiencies.

A web-based tool LOAD ESTimator (LOADEST) reported in the work of Park et al. [412] , [413] was developed to estimate the pollutant load by integrating stream-flow watershed data measurements and water quality data as the model inputs via server web access. A model-based event detection using a fuzzy comprehensive genetic algorithm was introduced by Wen et al. [57] to measure the toxicity of seawater samples with high levels of spatial variation, oil contamination, silicate and heavy metals (Zn and Pb). In short, assumptions of ideal and realistic sensor placements are essential for high accuracy in event detections [414] . The genetic algorithm has become the preferable method used by many researchers for water system design optimization techniques [415] , [416] . Although there are challenges associated with a wide variety of optimization problems, each water quality factor can be weighted carefully using additional logic simulation methods. Efforts to deploy the contamination event detection and surrogate approach has been made as alternative ways to overcome drawbacks regarding conventional laboratory-based analysis and the SPA method. A variety of techniques for water quality event detection have been well-developed, including the statistical, heuristic, machine learning and optimization methods used to analyze contaminant changes and the possibility of contamination [417] . Unlike other available methods, developing a model-based detection scheme involves intensive computational algorithm [406] . In addition, the requirements for calibrations and fabrications would further increase the complexity of the overall system [411] . Predictions and assumptions are the primary variables when utilizing an event detection model-based approach. The contamination evaluation process is complex due to high variability in environmental conditions [418] .

5. Future recommendations

Current global challenges caused by climate changes, urbanization and industrialization have prompted the need of safe, clean and readily treatable water resources. The production of high-quality water is becoming more challenging because of alignments in the detection limit concentration that correlates with the WHO and EPA water quality parameter standards. Owing to the fact that one in nine people around the world does not have access to clean water supplies, innovative water contamination detection technologies must be able to (1) achieve a fast response early warning detection, (2) improve water treatment efficiency, (3) minimize risk of harmful contaminant exposure, (4) quantify and identify the types of contaminants and (5) continuously detect unwanted contaminants simultaneously.

A comparison on the pros and cons of the state-of-the-art water monitoring technologies is summarized in Table 4 . The overall monitoring and detection system must acquire accurate data to minimize statistical methods, increase spatial hybridity (with a combination of quantitative and qualitative measurements), reduce operation time to evaluate the presence of contaminants and reduce the project cost. However, it is rather difficult to continuously monitor real-time water contaminants, especially when they reach the point of end-user.

Comparison between water contamination detection methods.

Although the achievements that have been made in the conventional analytical techniques are remarkable, the use of agents as receptors and transducers to capture contaminants could negatively affect raw data measurements to a certain extent [419] . More research efforts is still needed to develop efficient yet cost effective water quality monitoring systems. In general, the analyses done by the conventional instruments are not only labour intensive [420] but also relatively expensive [421] . These instruments in most of the cases are only capable to yield small data sets [422] , [423] . Major challenges that limit commercialization are instrumental complexity and large data mining capabilities.

Even though WSN and remote sensing technologies have been adopted in current water monitoring systems, many of them are lack of hybrid analysis and are not user friendly for continuous detection/monitoring [424] , [425] , [426] . Those wireless sensing detection devices are mainly focused on the deployments in water network distribution rather than the point of water consumption, which is end-user water supply. Hence, the opportunities to develop water monitoring tool kits with a graphical user-interface (GUI) that is user-friendly, easy to operate and re-usable are on demand. As micro-scale device is more sensitive to micro-organisms than macro-scale device, it is more ideal to overcome these challenges. Nano-scale sensing device meanwhile has received a great deal of attention in recent years owing to its extremely low detection limits for contaminant concentrations [427] , [428] .

Furthermore, it is highly recommended to incorporate two or more sensing devices, such as hybrid of microfluidic-based or biosensor-based platform with a spectroscopic detection system to enhance detection sensitivity and accuracy. This approach combines potential in-situ water monitoring technologies, such as NIR-Raman spectroscopy and NIR-FTIR-SERS techniques, which are particularly suitable for water analysis because of its simplicity, high speed detection response, strong light absorption in water and very low LOD [224] . It is quite certain that this innovative approach could play an important role in meeting the ever-increasing demand for water quality assessment.

In large deployments of an on-line monitoring system, it is crucial to minimize the complexity of the overall system to prevent data transmission interruptions, which might result in data losses. In view of this, highly reliable hand-held devices and novel user-friendly toolkits are crucial during water monitoring process. In assessing water quality using contaminant detection technologies, potential contaminants in potable water should also be considered by conducting intensive risk management, risk assessments and risk research to minimize the hazardous contaminants that are present in tap and drinking water.

Acknowledgments

The authors would like to express gratitude to the Ministry of Higher Education (MOHE) of Malaysia and Universiti Teknologi Malaysia (UTM) for supporting this research financially. A sincere appreciation to Dr. Zulkifli Mohamed Hashim, an expertise in physical chemistry from Institute of Nuclear Malaysia, for critically reviewing the manuscript and intensive discussions. The staff of University Laboratory Management Unit (UPMU), UTM deserves thanks for their generous assistance in providing useful information related to analytical instruments.

Biographies

Syahidah Nurani Zulkifli received her B. Eng. degree (Honours) in Electrical Engineering (Electronics) from Universiti Teknologi Malaysia (UTM), Skudai, Malaysia and M. Sc. in Innovation Engineering Design from Universiti Putra Malaysia (UPM), in 2012 and 2014, respectively. Currently, she is a PhD candidate in Control and Instrumentations, related to monitoring system for analytical chemistry applications at Universiti Teknologi Malaysia (UTM). Throughout her study and research, she has her interest in monitoring and control system, sensor technology and software engineering. Previously, she has worked with Malaysian Nuclear Agency for industrial training and was exposed to various chemical analytical techniques include Raman, X-ray Diffraction, NIR, GCMS and ICPMS.

Assoc. Prof. Ir. Dr. Herlina Abdul Rahim is an Associate Professor at Faculty of Electrical Engineering, Universiti Teknologi Malaysia. She received her BEng and MSc in Electrical Engineering (Control and Instrumentation) from Universiti Teknologi Malaysia in year 1998 and 2000, respectively. She received her PhD in Electrical Engineering from Universiti Teknologi MARA (UiTM) in year 2009. At present, she is actively involved in R&D and has filed 33 IPR including patent fillings and copyrights. Her research and teaching interest are in the field of sensor technology, artificial intelligent system, and analytical chemical instrumentation. Most of her project involves in NIR, MIR, Raman spectroscopy and SERS. She has been exposed in various analysis of chemical/biological compositions.

Dr. Lau Woei Jye is a senior lecturer senior lecturer at Faculty of Chemical and Energy Engineering and a research fellow at Advanced Membrane Technology Research Centre (AMTEC), UTM. He was an assistant professor at Universiti Tunku Abdul Rahman (UTAR), Kuala Lumpur. He obtained his Bachelor of Engineering in Chemical-Gas Engineering (2006) and Doctor of Philosophy (PhD) in Chemical Engineering (2009) from Universiti Teknologi Malaysia (UTM), Malaysia. Dr Lau has a very strong research interest in the field of water and wastewater treatment processes using membrane-based technology. As at May 2017, he has published over 95 scientific papers, 10 reviews and 7 book chapters with total citation of 2206 (Google Scholar) and 1672 (Scopus). He is the author of the book entitled Nanofiltration Membranes: Synthesis, Characterization and Applications published by CRC Press in December 2016. He has also written articles on the subject of water separation and purfication and published in newspapers and magazines at both national and international level.

• Open access
• Published: 10 May 2019

Factors influencing perceptions of private water quality in North America: a systematic review

• Abraham Munene   ORCID: orcid.org/0000-0001-9546-3574 1 &
• David C. Hall 1  

Systematic Reviews volume  8 , Article number:  111 ( 2019 ) Cite this article

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Metrics details

An estimated four million and 43 million people in Canada and the USA use private water supplies. Private water supplies are vulnerable to waterborne disease outbreaks. Private water supplies in Canada and the USA are often unregulated and private water management is often a choice left to the owner. Perceptions of water quality become important in influencing the adoption of private water stewardship practices, therefore safeguarding public health.

We conducted a systematic literature review to understand factors that shape perceptions of water quality among private water users. We searched six computer databases (Web of science, Medline, Scopus, EBSCO, PubMed and Agricola). The search was limited to primary peer-reviewed publications, grey literature and excluded conference proceedings, review articles, and non-peer review articles. We restricted the search to papers published in English and to articles which published data on surveys of private water users within Canada and the USA. The search was also restricted to publications from 1986 to 2017. The literature search generated 36,478 records. Two hundred and four full text were reviewed.

Fifty-two articles were included in the final review. Several factors were found to influence perceptions of water quality including organoleptic preferences, chemical and microbiological contaminants, perceived risks, water well infrastructure, past experience with water quality, external information, demographics, in addition to the values, attitudes, and beliefs held by well owners.

Conclusions

Understanding the factors that shape perceptions of water quality among private water users is an important step in developing private water management policies to increase compliance towards water testing and treatment in Canada and the USA. As many jurisdictions in Canada and the USA do not have mandatory private water testing or treatment guidelines, delineating these factors is an important step in informing future research and guiding policy on the public health of private water systems.

Peer Review reports

Introduction

An estimated four million and 43 million people in Canada and the USA use private water supplies [ 1 , 2 ]. In the absence of municipal water distribution systems in rural populations, private water supplies are an alternative source of domestic water in developed countries. Private water supplies are vulnerable to waterborne disease outbreaks [ 3 , 4 ]. Several chemical and microbiological contaminants can contaminate private water supplies. Nutrients (e.g. nitrates), pathogens, pharmaceuticals, hormones, heavy metals, nanomaterials and personal care products are some contaminants that have been identified in well water [ 5 , 6 , 7 , 8 , 9 , 10 ]. These contaminants are associated with illnesses including gastrointestinal illnesses, liver and kidney problems, endocrine disruption, cancer, reproductive issues and neurological disorders [ 11 ].

Private water supplies in Canada and the USA are often unregulated. Management of private water supplies (e.g. water wells, cisterns or boreholes) is the responsibility of the owner. As a guide to drinking water quality standards, the Guidelines for Canadian Drinking Water Quality set out national drinking water standards in Canada. Similarly, the Safe Water Drinking Act is used to set out national and enforceable drinking water guidelines in the USA. However, the legislation excludes private water sources that serve less than 25 people. Private water systems are defined by water systems that serve 25 people or less for at least 60 days within a year and have up to 15 service connections. Water wells make up the majority of private water systems with cisterns and residential wells also considered as private water systems [ 12 ]. Approximately four million and over 13 million people are estimated to rely on unregulated private water wells in Canada and the USA [ 13 , 14 ]. Although both Canada and the USA have national guidelines for the minimum standards of drinking water quality, there may be jurisdictional differences in the contaminants that are assessed [ 15 ]. Furthermore, individual provinces or states may have their own regulations on the construction of new wells, how many service connections can be served by a private water supply, and water testing recommendations, with some provinces or states requiring mandatory testing of wells upon the acquisition of new properties [ 12 , 16 ]. Unlike municipal water supplies which may be regularly monitored and treated, few regulations cater to testing and treatment of private water supplies in Canada and the USA [ 1 , 16 , 17 , 18 ].

In the absence of regulations on the management of private water supplies, compliance to private water testing and treatment becomes an essential mitigation strategy in protecting the health of private water users from diseases that could be contracted from consuming contaminated water. Recent studies indicate that compliance towards private water testing and treatment recommendations in various jurisdictions is low [ 2 , 19 ]. Roche et al. (2013) found that nearly 80% of respondents in their survey tested water quality at frequencies below the current provincial recommendations. Perceptions of water quality may influence the adoption and implementation of private water management practices [ 20 ]. The choice of when to test water quality, what to test for, and what treatment devices to use on private water systems are decisions that are based on both perception and knowledge of risks to private water contamination.

Perceptions have been broadly defined as a human being’s primary cognitive contact with the environment or simply the way in which we understand the world around us using our senses [ 21 ]. However, this narrow definition based on the sensory appraisal we make to understand our environment is myopic and does not capture the complexity of factors involved in shaping perceptions. Perception also has subjective components that are associated with learning and past experiences that are mediated by attention, memory, and the ability to retrieve information from memory [ 22 ].

Consequently, this raises the question; what factors are important in shaping the perceptions private water users have of their water quality? Little is known about the factors that influence perceptions of water quality among private water users. We conducted a systematic review of studies on people reliant on private water systems for domestic use in both Canada and the USA to determine the factors that influence the perceptions of water quality within these two countries. Describing and understanding the factors that shape perceptions of water quality among private water users is an important step in developing well water management policies to increase compliance towards private water stewardship practices such as water testing and treatment in Canada and the USA. To guide the scope of our systematic review, we wanted to answer the main question. What factors predominantly drive perceptions of private water quality in Canada and the USA?

PICO framework

A PICO framework [ 23 ] was used to help guide the questions of the review. As most studies included were observational, assessment for control groups was not feasible as there would be no adequate comparison for perceptions held by private water users to a similar group (Table  1 ).

Search strategy

Literature searches were made on both health and environmental databases. A search strategy was developed in consultation with a research librarian and the review team. Our review was informed by methods for conducting systematic reviews in agri-food research [ 24 ]. We searched six computer databases (Web of science, Medline, Scopus, EBSCO, PubMed, and Agricola). The search was conducted between January and December 2017. The search was limited to primary peer-reviewed publications and grey literature. The search excluded conference proceedings, review articles, and non-peer review articles. We restricted the search to articles published in English and to articles which published data on private water users within Canada and the USA. The search was restricted to publications within the last 31 years (01/01/1986–31/12/2017). This time frame was used to capture recent amendments in regulations within the Safe Water Drinking Act and the Guidelines for Canadian Drinking Water Quality which may influence what substances are considered as drinking water contaminants and at what maximum acceptable concentration (MAC). A combination of search phrases was used for each database but consisted of major search domains with associated synonyms required to capture relevant articles. Keywords searched were private water , domestic water , household water , well water , drinking water , perceptions , knowledge , belief , attitude , information , awareness , testing , treatment , survey, and rural . Reference lists for relevant primary articles and review articles were screened. Articles fitting the inclusion criteria, that is, articles that were published in English, articles that conducted surveys on human participants relying on private water sources through questionnaires or interviews, articles that surveyed participants in Canada or the USA, articles that were primary research and articles that had the outcomes of private water testing, treatment or investigate alternative water use in the context of private water users were added to the final list. All study approaches were considered including quantitative, qualitative, and mixed methods. As the focus was on perceptions of water quality among private water users, studies that directly surveyed private water owners were included in the final literature search (Table  2 with key terms used and the number of papers generated for each phrase search is provided. See Additional file  1 : Table S1).

Data extraction

Each paper included in the final review was read independently by the two authors and then assessed for relevancy in the review. The lead author extracted the following information: the main purpose of the study, the study population, study approach, methods of data collection, whether theoretical frameworks were used in the study, notes on the context of use of the private water systems, whether a formal intervention was present and results. The author also constructed a table identifying the study type, demographics, the intervention being evaluated and results of relevance to the present study (Additional file  2 : Table S2). The second author independently verified data extraction and tabulation for the included articles. Each article included in the final list was independently rated by both authors for relevance to the review. Both authors met regularly over a period of 4 months to discuss the findings. In instances of disagreement, articles were reassessed independently, and consensus was reached following deliberation and discussion by the authors. A PRISMA flow diagram was used to narrow our selection of articles [ 25 ]. Articles were preliminarily screened by (1) reviewing the article titles generated by the keywords search, (2) reviewing article abstracts, (3) reviewing the full articles, and (4) sorting on relevance for the review.

Quality of study and risk of bias

As a measure of the quality of study, articles were evaluated by whether they were published in a peer reviewed journal (as the assumption is that articles published in reviewed journals have been adequately scrutinised by reviewers before publication) or were technical reports. Reviewers also ranked the quality of the study relative to the review’s objectives on a scale. A risk of bias assessment from each study was conducted using the Strobe checklist assessment for risk of bias. Studies were ranked on a scale of 1 (high quality) to 4 (low quality) for their relevance to the review and based on the strobe checklist.

The database search included 36,478 articles using the keyword search. Web of Science ( n  = 4160), Medline OVID ( n  = 286), Scopus ( n  = 3875), PubMed ( n  = 4072), Agricola ( n  = 5506), EBSCO ( n  = 18,579). Ultimately, 204 papers were examined intensively of which 152 articles were excluded for not meeting the relevance criteria for this study (Fig.  1 ). Fifty-two studies were included in the final review. Of the 52 studies identified, 44 exclusively focused on surveys delivered to private water supply owners while ten studies surveyed both residents with private and municipal supplies. Most of the articles ( n  = 35) were from the USA while 17 articles reported on private water users in Canada. All studies were observational. Most of the studies used a cross-sectional design ( n  = 49) with the rest reporting on case control studies. Studies were also classified as quantitative ( n  = 48), mixed methods ( n  = 3) or qualitative ( n  = 3). Survey administration methods varied. Questionnaire mail deliveries were used in 35 out of 52 studies and telephone surveys were used in 11 out of 52 studies. Other methods used to elicit participation included face to face interviews (3 out of 52) and focus groups (6 out of 52).

PRISMA flow diagram for study selection

This systematic review included 52 journal articles with data collected on over 35,000 well water owners across Canada ( n  = 14,793) and the USA ( n  = 22,420). Perceptions of well water quality across Canada and the USA were found to be influenced by several factors. The main factors identified through this review were organoleptic properties of water, knowledge of chemical and microbiological contaminants, perceived risk, demographic factors, past experience with water quality, external information, values, attitudes, and beliefs about water, and water infrastructure.

Organoleptic properties of water

Private water owners primarily relied on the sensory properties of drinking water sourced from their wells when it came to decisions regarding well management options. Decisions on when to test water quality or the choice to consume water were often instigated by changes in either the taste, look or smell of the water [ 1 , 2 , 17 , 18 , 19 ]. Satisfaction with the organoleptic properties of water was not necessarily equated to concern over drinking water sourced from the wells. For example, although most respondents rated the organoleptic properties of their water from ‘good’ to ‘very good’, nearly 80% of respondents to the survey indicated being concerned about their water quality [ 1 ]. In contrast, organoleptic properties of drinking water were congruent with the perceptions of the safety of water for consumption. About 67% of participants who had issues with the organoleptic properties did not consider their water as safe to consume [ 26 ]. Sensory cues derived from the organoleptic properties of water were not only limited to water consumed but also to other water uses. For example, some people reported on the hardness of their well water as it tended to discolour their appliances or plumbing systems [ 17 ]. Due to psychological factors, people expect sensorial information on the taste odour, and colour of water to be congruent [ 20 ]. However, what is not clear from the studies is what sense dominated when well water owners indicated a change in their well water quality. Evidence on how well water owners perceive the taste, smell, and odour of water sourced from their wells relative to alternative water sources such as bottled water or municipal tap water was also evaluated in some studies. Well water owners were unwilling to change to municipal water supplies due to their personal preference for the taste of their well water and fear of ‘chemicals’ in city water [ 27 ]. Similarly, Jones et al. (2005) found that well water owners preferred their well water over bottled water due to preferences in taste and scepticism to where the bottled water came from.

Chemical and microbiological contaminants

Due to the soluble properties of water, several chemical and microbiological substances can be found in private water sources. Some chemical and microbiological substances can pose a health risk to individuals consuming well water. Of the 52 articles included, 13 out of 52 exclusively focused on assessing exposure to naturally occurring arsenic. Nitrate exposure was exclusively evaluated in 5 out of 52 articles. Radon exposure was exclusively evaluated in 1 out of 52 articles while 2 out of 52 articles evaluated the exposure of Escherichia coli and total coliforms on well water. Thirty-four articles were non-specific towards the chemical or microbiological contaminants (e.g. general microbiological and chemical contamination or a combination of both). For studies exclusively focusing on exposure to one contaminant, some studies were clear about the thresholds for the MAC for contaminants. The MAC is the specific level of a contaminant that is allowed in water for a specific purpose (e.g., human consumption). The contaminants assessed for and the MAC for specific contaminants may vary regionally [ 15 ]. However, the MAC’s of several contaminants in Canada and the USA are similar and reflect standards set out by the US Environmental Protection Agency. Studies examining naturally occurring arsenic as an exposure often quoted 10 μg/l as the MAC [ 2 , 28 , 29 ]. For nitrate as an exposure, the MAC used was 10 mg/L in six studies [ 30 , 31 , 32 ]. Lead exposure was assessed in one of the studies [ 33 ] with some studies quoting MAC’s for each contaminant assessed [ 34 ]. However, in some of the studies that assessed multiple exposure to contaminants or that were non-specific to a contaminant, MAC’s were not used [ 26 , 35 , 36 , 37 ].

Some studies also included a water testing component to evaluate the prevalence of contaminants of interest in their samples (Table  3 ).

Knowledge of the level of contaminants within well water was an important factor when well owners had to decide on treatment systems to use in their wells. For example, half of respondents indicated they would begin treating or finding other water sources before the concentration reached the MAC 10 mg/l of nitrates in their well water. Interestingly, a similar proportion of participants indicated that they would wait until the concentration of nitrates in their water was > 10 mg/l or higher [ 32 ]. However, the authors noted that stated intentions differed from the actual responses with only 21.9% opting to use a treatment system and about 25% opting to switch to bottled water and drilling a new well upon learning of exceedances. Flanagan et al. (2015) found that about 43% of well water owners installed water treatments with a further 30% seeking alternative water sources after being informed of exceedances in the MAC of arsenic in their well water. Therefore, even though some well owners knew their water wells exceeded the MAC for nitrates, their decision to adopt treatment or use alternative water sources may have been influenced by the perceived risk of the contaminant towards their health. These findings demonstrate the complexity in how the appraisal of the risks posed by contaminants may be highly subjective to individuals.

Perceived risk

Individuals respond to hazards they perceive within their environment. Risk perception is defined as the subjective judgement that an individual makes about the characteristics and severity of a risk [ 38 ]. In order for an individual to make a decision on whether or not to use treatments or seek alternative drinking water sources, they must first identify the hazard (e.g. nitrates), evaluate the risk of contamination based on potential risk factors in their environment and their exposure to hazards (e.g. test for contamination in an area with extensive manure or fertiliser spread and understand how likely they are to be exposed to nitrate contamination) and finally they must understand the consequences of the hazard and their ability to control those consequences (e.g. know about a health risk such as methemoglobinemia and make a judgement on the severity of the methemoglobinemia towards their own health). Given there are several contaminants that may be considered hazards to well water, the process of assessing the risk of general well water contamination without a specific preidentified hazard may be problematic for well owners therefore making the decision of treatment options, whether to switch to an alternative or what and when to test for water quality more difficult [ 1 ]. Individuals were less likely to drink well water if they thought there were health risks associated with consuming water with arsenic [ 39 ]. Similarly, well water owners were less likely to drink well water if they perceived a risk in drinking well water regardless of aesthetic concerns [ 40 , 41 ]. Perceived risk factors within the environment could also influence what people think of their well water quality. Participants reported proximity to livestock, proximity to septic systems, proximity to oil and gas activities, proximity to mining areas, proximity to nuclear power plants, flooding, severe runoff events, and drought as environmental risks that caused concern and motivated well owners to test their water [ 27 , 34 , 42 , 43 , 44 , 45 , 46 ]. However, the perceptions of water quality in response to environmental risk factors were indirectly mediated by actual changes in the aesthetic properties of water as some participants noted.

Demographic factors

Demographics can influence the choices well water owners make of drinking water options. Factors such a participant’s education, income, number of years within a residence, and place of residence have been noted as important factors that influenced perceptions of water quality and the willingness to use water treatment [ 26 , 29 , 30 , 47 , 48 ]. Low education and income were more likely to result in the lack of use of well water treatment devices [ 26 , 30 ]. Low education and income may also be socioeconomic factors that predispose well water owners to certain risk factors. Garcia et al. (2016) noted that residents living in underprivileged communities within New Mexico had unreliable drinking water systems, poor sanitation, and a lack of access to water testing and treatment. Despite the risk of arsenic being randomly distributed within socioeconomic groups, individuals with lower income and lower education were less likely to adopt protective behaviours such as well testing and treatment for their water wells [ 49 ]. Furthermore, psychological factors influencing testing and treatment were more prevalent among those with higher income and education. Similarly, higher education and income were positively associated with the decision to test well water quality and use water treatment devices [ 50 , 51 ]. Education and income were not always associated with positive outcomes on treatment and testing. No significant association was found between education and stewardship behaviours conducted by well water owners [ 52 ]. Similarly, no significant association was found between education and income and the use of well water treatments [ 34 , 46 ]. In contrast, Shaw et al. (2005) found a negative association between income, education, and the decision to use well water treatments. The number of years an individual had lived at a residence and the length of time they had used their well water also seemed to play an important role in predicting water testing and treatment behaviour. This is because well owners may get habituated to their drinking water source. Shaw et al. (2005) found that the longer an individual had lived in the household, the less likely they were to engage in well water testing behaviour. Similarly, the longer an individual had lived within the household, the less likely they were to conduct a water quality test within the last 5 years and the less likely they were willing to submit a water quality test [ 18 ]. However, some studies failed to find a significant association between the number of years lived within the home and water treatment practices [ 51 ].

Age and gender have also been explored as demographic variables that can influence perceptions of private water quality. Evidence to show associations between age and gender on perceptions of well water quality has been sparse. Age and gender did not predict well water testing behaviour among well owners [ 50 ]. With respect to gender, a significant association has been found between women and the use of well water treatment systems. This is because the presence of children within a household may be identified as a reason for concern among parents and a reason for well water owners to choose alternative drinking water sources [ 44 , 45 , 50 , 53 , 54 ].

Past experience

The role of past experience with water quality issues is important. Past negative experiences with well water quality were found to predict well water testing behaviour [ 55 ]. These experiences were either on the individual well or within the well owners’ community. Learning of water contamination among neighbours and experiencing unexplained gastrointestinal illness were noted as motivators for individuals to conduct well water testing [ 18 ]. Despite past negative experiences being noted to influence perception of drinking water quality, determining the validity of reported past negative experiences may be subject to recall bias among surveyed participants. Furthermore, participants may not always attribute personal health problems, such as gastrointestinal illness, to drinking water from their wells. As gastrointestinal illnesses may be underreported and deemed controllable, it may be difficult to get an accurate representation of how past negative experiences with gastrointestinal illness influence perceptions of well water quality [ 54 , 56 , 57 ]. For well water contaminants which do not present direct clinical symptoms and may have severe health consequences due to chronic exposure (e.g., arsenic), the role of past experience associated with negative health outcomes on perception of well water quality is difficult to determine. However, past negative experience with contamination indicated by well water testing may change the perspective of well water owners with regards to the safety of their drinking water [ 32 ].

Previous positive experience with water quality testing may also influence the likelihood of well owners testing water quality in the future. For example, well owners reported being more confident in their well water supplies and therefore less likely to test their well water quality if the result of the water quality test they had conducted in the past showed no evidence of contamination [ 1 ]. Recurrent problems with well water quality as indicated by water quality test may also cause individuals to worry more about their well water quality and therefore conduct frequent testing. For example, well owners who were identified as being high risk for arsenic contamination through water testing and who knew they were at a higher risk of arsenic contamination were more likely to conduct well water testing than individuals who were identified as low risk for arsenic contamination [ 49 ]. Similarly, well owners who had engaged in previous water testing and were aware of water quality issues were more likely to conduct routine testing [ 58 ].

External information

The impact of external information on changing perceptions towards well water quality to promote testing or treatment has been explored. External information sources may be in the from media campaigns, educational awareness programs or from prompts given by members of the society to encourage a behaviour. The format of the information presented may by varied including pamphlets and flyers distributed by public and private water public health agencies, news items, advertisements or advisories distributed through print media, social media, television or radio, information workshops, information solicited directly from water public health agencies (e.g. through phone calls) or information gathered from social informants (e.g. neighbours and friends) [ 2 , 29 , 40 , 58 , 59 ]. Participants’ responses to educational material may be varied. Nearly 43% of participants installed water treatment systems in response to elevated arsenic levels while nearly 31% switched to alternative drinking water sources [ 18 ]. Similarly, well owners were more likely to report higher arsenic testing rates in towns that had received educational intervention programs when compared to towns that did not receive programs [ 60 ]. In response to media reports on the risk of cancer associated with arsenic exposure, only 18% of participants used mitigation strategies that were useful against arsenic despite 66% having arsenic concentrations above the MAC [ 29 , 39 , 49 ]. Chappells et al. (2015) found that nearly 25% of participants reported making some change to their well water management practice in response to information received from either private testing laboratories or government departments. Well owners were more likely to engage in well testing programs after the dissemination of well management information through a well stewardship program [ 55 ]. Information on well water quality in the form of testing results can also be used to change participants’ perceptions of the safety of their drinking water [ 31 ]. Interestingly, not all information campaigns may increase water well stewardship. Nearly 28% of participants did not take any well stewardship action despite being aware of elevated arsenic concentrations within their well water [ 18 ]. Therefore, exposure to media or other forms of external information may not be sufficient to modify well stewardship behaviour [ 58 ].

Values, attitudes, and beliefs

Values, attitudes, and beliefs towards health or environmental protection may also influence well owners' willingness to adopt well stewardship practices. Well owners’ decisions to conduct stewardship practices were more influenced by whether they were satisfied with their water quality and with their knowledge and beliefs of water quality [ 46 ]. Satisficing was where well owners took on a simple belief about their water well and did not develop a strong enough knowledge base to accurately make judgements of their water quality. Furthermore, most individuals in their survey believed that it was best to not to do anything with the water well unless they had issues with it. Participants also held a wide variety of beliefs when it came to their water wells and these beliefs were not necessarily associated with negative health consequences. The role of imperfect and incomplete knowledge (e.g. wrong beliefs about aquifers and the origin of water in water wells) in the decisions of whether to adopt well stewardship practices was identified as a possible barrier [ 46 ].

Well water infrastructure

Available infrastructure, both physical and services available for well water quality maintenance, may also influence stewardship practices. The availability of free well water testing services has often been used to encourage water quality testing among well water owners [ 1 , 18 , 19 , 52 ]. Despite testing services being offered for free in several jurisdictions in Canada and the USA, compliance towards well water testing recommendations is usually low [ 19 , 60 ]. Several barriers have been identified that inhibit well water owners from conducting regular testing. Individual well owners may face multiple barriers when deciding to go through with water testing [ 46 , 52 ] (Table  4 ). To increase compliance towards well water testing, several studies have solicited participants’ suggestions on how to increase routine well water testing. Making pick up and drop off of water sampling kits more accessible, increasing reminders to participants to conduct water quality tests, increasing educational awareness forums, providing incentives, enforcing penalties or making well water testing mandatory through legislation have all been stated as possible measures to increase compliance towards well water testing. The availability and accessibility of infrastructure for well water treatment may also influence habits towards well water protection. However, few studies have explored the reasons behind well water owner’s choice of well water treatments

This systematic review included 52 journal articles with data collected from well water owners in Canada and the USA. Perceptions of well water quality across Canada and the USA were found to be influenced by several factors. Main factors identified through this review were organoleptic properties of water, knowledge of chemical and microbiological contaminants, perceived risk, demographic factors, past experience with water quality, external information, values, attitudes, and beliefs about water, and water infrastructure. The reliance on the organoleptic properties of water to make judgements on the safety of drinking water by private water users is profound and has been identified as a key factor in other reviews [ 20 ]. To the best of our knowledge, only two previous literature reviews [ 20 , 61 ] had attempted to provide a review on factors influencing perceptions of water quality.

Well water management practices are discussed in the context of testing and/or treatments. Well water testing practices often tend to be the focus for researchers and intervention strategies [ 1 , 19 , 52 , 60 , 62 ]. Widespread adoption of well testing and compliance towards recommendations set for testing tend to be problematic for well water owners to achieve. Interventions focusing on modifying well water testing behaviour based on incentives, legislation, education or community outreach activities have had moderate success on increasing compliance towards well water testing [ 2 , 52 , 60 ].

Interventions based on getting well water owners to adopt well water treatment are contingent on well owners understanding contaminants and the potential health risks they may pose. However due to the variety of possible contaminants found within well water, it may be very difficult to prescribe treatment devices, unless a contaminant is identified through testing, as one device may not be effective at removing all contaminants. The use of multiple well water treatment devices may offer more protection against several contaminants; however, water testing will still need to verify well water quality and identify possible risks to a well. Therefore, educating private water users on options available for them with respect to water treatment may enable private water users make more informed decisions based on the identified risks to their private water sources. The need for more information on water treatment has been identified in previous surveys [ 1 , 19 , 59 ]. Information from this study will be useful in informing private water users, researchers, and educators on some of the present gaps in the literature and research areas that need to be expanded on.

Gaps identified

Despite the focus on well water testing, very few studies have tried to discriminate which health risks are perceived to be associated with drinking water contamination and more specifically towards individual contaminants [ 63 ]. More studies are required to address this gap in knowledge between the perception of well water quality and the potential health consequences well water owners attribute to well water contamination.

Maintenance of well water stewardship behaviour such as testing, post intervention, is also an issue that has yet to be adequately addressed. Despite the role research may play in active surveillance of well water and instigating well owners to conduct water testing during the duration of the research program, there is very little evidence that behaviour such as water testing is continued after the research programs or other intervention programs end. Future research should look into assessing if well water testing behaviour is maintained among well owners and this could be done by broadening the methods to include cohort studies and not only cross-sectional designs. Broadening active surveillance periods using research may also help in determining the period prevalence of well contamination over time and address reliability issues associated with surveys by following up on well owners’ behaviour, in addition to determining the maintenance of well water stewardship practices.

Despite the amount of research that has been conducted on well water testing behaviour, compliance towards well water testing recommendations is still considered low in many jurisdictions. Changes in technology over the last 30 years and increased internet connectivity in Canada and the USA may provide well water owners with more access to information regarding their water wells. However, a potential problem that arises is what information sources should well owners trust given that current policies in well stewardship are only recommendations. More studies need to be conducted on the quality of information provided for by interventions such as educational programs or online information. Assessing the quality of information and how it is understood by well water owners may influence the adoption of well stewardship behaviours and may be important in dealing with satisficing and complacency among well owners. Furthermore, more research needs to be conducted on sources of information private water owners have access to and the uptake of information based on its trustworthiness [ 46 , 47 ].

The adoption of qualitative and mixed method designs to further study perceptions of private water quality over the last decade and the shift away from quantitative studies has helped in developing a richer understanding of the issues faced by well water owners with respect to water quality. Qualitative and mixed methods research may be more beneficial in capturing the unique personal experiences and knowledge private water owners have of their water quality. Furthermore, incorporating the voice of private water owners in research may be an important step in developing well management policy and practices that will directly tap into the needs of private water users.

Despite having identified factors that influence well owners' perceptions of well water quality, it is important to note the paucity of research on how combinations of these factors influence well stewardship behaviour. There is very little evidence to suggest that perceptions of well water quality and well stewardship practices (i.e. testing and treatment) are driven by a single factor and are more likely to be influenced by a combination of several factors. While research to date has done an adequate job of identifying factors that influence perceptions of well water quality and predictors of well water stewardship, there is a knowledge gap in how these factors interact with each other to produce the desired outcome (e.g. well testing) in well owners. For example, although external information (e.g. educational forums) may help encourage well testing, if well owners conduct a well test and have a negative test result due to the educational program, how does the past experience of having a negative well test result influence both their appraisal of susceptibility to well water contamination and their willingness to test their water in the future. More research is required on how factors that influence perceptions of water quality may act synergistically or antagonistically to influence well stewardship behaviour.

This review summarises research that has been conducted on well water owners’ perceptions of water quality over the last 30 years while identifying questions and areas that need further development in research. Policies and recommendations for well water testing, treatment, and other management practices are highly contextual to the regions; however, this study summarises the most pertinent factors driving perceptions of private water based on research that has been conducted.

Limitations

Publication bias may have been present due to the selection of articles from peer reviewed journals. Furthermore, because we only selected articles published within the last 30 years, there may have been a time lag bias with the selection of articles [ 64 ]. Despite the search for articles and selection of articles relevant for the review being restricted to the language spoken by the authors, no systematic bias has been found in reviews published in English [ 65 ].

Although their may be relationships between education and income to private water stewardship behaviours, it was difficult to operationalise or standardise income and education variables. This was because of differences in education standards and currency between Canada and the USA, income levels within different jurisdictions, and changes to income and education levels over a 30-year period. Furthermore, it was difficult to operationalise variables such as income and education levels because of differences in the what researchers choose to operationalise as ‘low education’ and ‘low income’ within their studies.

Given that perceptions of water quality among private water users are influenced by several factors, researchers, educators and policy makers should appreciate the heterogeneity and interplay of these factors when planning private water management programs or developing policies. Education and communication strategies that focus more on individual well owners and their needs, based on risks identified around their well, need to be adopted as opposed to blanket policies or programs. The use of questionnaire surveys and qualitative research to identify the needs of individual well owners may help. This is especially pertinent because of the different interacting, and sometimes confounding, factors that may motivate private water users to comply with water testing and treatment recommendations.

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Acknowledgements

We would like to thank the Diane Lorenzetti for her advise in formulating the search and selection strategy as well as Dr. Jocelyn Lockyer and Dr. Sylvia Checkley for their comments on developing the systematic review and their review of the manuscript.

This research was supported Alberta Innovates Energy and Environment Solutions (AIEES) grant number 2074 to Dr. David Hall and was the part of the literature review to inform the study investigating perceptions of well water quality in Alberta associated with livestock.

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AM and DCH conceptualised and designed the study. AM conducted the literature search. AM and DCH analysed the data. AM drafted the manuscript. All authors read and approved the final manuscript.

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Table S1. Search terms used and papers generated on each database with search terms. (DOCX 24 kb)

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Table S2. Data abstraction for articles included in the systematic review. (XLSX 96 kb)

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Munene, A., Hall, D.C. Factors influencing perceptions of private water quality in North America: a systematic review. Syst Rev 8 , 111 (2019). https://doi.org/10.1186/s13643-019-1013-9

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A Review About the Occurrence and Effectiveness of Conventional and Advanced Treatment Technologies of Persistent Organic Pollutants in Surface Water

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• Volume 262 , article number  11 , ( 2024 )

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Persistent organic pollutants (POPs) refer to various pollutants, including organochlorine pesticides (OCPs), industrial chemicals, and other unintended byproducts that are discharged through anthropogenic activities such as industrial processes, waste disposal, and agricultural activities, as well as natural sources such as forest fires and volcanic eruptions. POPs have the potential to harm ecosystems and humans due to their toxicity, high environmental persistence, global emissions, and bioaccumulation. Despite the significant progress in various treatment technologies for removing POPs in the previous literature, a report containing comprehensive information on the current effective treatment methods is lacking. In this study, the main mechanisms, key factors, and comparison of the performances between conventional and advanced methods for removing POPs are discussed. Moreover, the practical application of integration treatment systems in POPs removal is also analyzed, providing lessons and prospects for further research. The review results show that most POPs occur in surface water around the world and that some of them have been found in drinking water treatment systems. The adsorption process is one of the best options among conventional methods, achieving a high removal efficiency of POPs from surface water. Advanced oxidation processes (AOPs) such as O 3 /UV, fenton, and photofenton are suitable methods for eliminating POPs in surface water because of their high removal efficiency, easy operation, and integration into existing facilities. Despite having some limitations, such as being high cost and requiring highly skilled maintenance, NF and RO membranes have a high potential for application in removing POPs and other pollutants from surface water, especially drinking water treatment systems. In addition, the practical application of integration treatment systems has also been proven effective at eliminating POPs in large-scale systems. Therefore, an overview of these methods for treating POPs in surface water will enable a better understanding of the removal mechanisms, efficiency, and applications available in practice.

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Remediation of Persistent Organic Pollutants Using Advanced Techniques

Persistent Organic Pollutants (POPs): Sources, Types, Impacts, and Their Remediation

Treatment Technologies for the Environmental Micro-pollutant

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Nguyen, A.T., Le Tran, L. A Review About the Occurrence and Effectiveness of Conventional and Advanced Treatment Technologies of Persistent Organic Pollutants in Surface Water. Reviews Env.Contamination (formerly:Residue Reviews) 262 , 11 (2024). https://doi.org/10.1007/s44169-024-00062-4

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