short case study on water pollution in india

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ICESMART - 2015 (Volume 3 - Issue 19)

River water pollution:a case study on tunga river at shimoga-karnataka.

• Article Download / Views: 3,123
• Total Downloads : 16
• Authors : Dr. H. S. Govardhana Swamy
• Paper ID : IJERTCONV3IS19035
• Volume & Issue : ICESMART – 2015 (Volume 3 – Issue 19)
• Published (First Online): 24-04-2018
• ISSN (Online) : 2278-0181
• Publisher Name : IJERT

Dr. H. S. Govardhana Swamy

Professor & Head, Department of Civil Engineering RajaRajeswari College of Engineering,

Bengaluru, India

Abstract Tunga River has been one of the most prominent and important river of Karnataka in Shimoga District. Unfortunately, certain stretches of River Tunga are much polluted. Various urban centers are located on the banks of Tunga River, draw fresh river water for various activities. In almost the entire wastewater generated by these centers is disposed off into the river. The objective of the monitoring studies undertaken for water body is to assess variation in water quality with time. Four sampling stations were selected along the river for sampling purpose from August 2013 to August 2014.Water samples were analyzed in terms of physico-chemical water quality parameters.

Keywords Thunga River, water quality, point pollution, Physico-chemical parameters

INTRODUCTION

In nature, water is the essential fluid from which all life begins. All living things need water to maintain their life too. In domesticity, it is very useful, such as for washing and cleaning. In industry, it is the common solvent for Paper and water, textile and electroplating. Besides, the generation of electricity also requires water. It has many uses. However, it can be easily polluted. Pollutants deteriorate the quality of the water and render it unfit for its intended uses [1]. The pollution of rivers and streams with chemical contaminants has become one of the most critical environmental problems of the century. It is estimated that each year 10 million people die from drinking contaminated water. Water is one of the most common and precious resources on the earth without there would be no life on earth [2]. Pollution is a serious problem as almost 70% of Indias surface water resources and a growing number of its groundwater reserves have been contaminated The quality of water is described by its physical, chemical and microbiological characteristics. Therefore a regular monitoring of river water quality not only prevents outbreak of diseases and checks water from further deterioration, but also provides a scope to assess the current investments for pollution prevention and control. In this study, seasonal variations of physico-chemical and bacteriological characteristics of water quality in Tunga river was assessed in Shimoga town in Karnataka.

MATERIALS AND METHODS

Shimoga is town, situated between the North and South branches of river Tunga. It is located on the Bangalore Honnavar highway.Though it is a town of medium population, the temples and historically significant monuments of this town attracts a large number of tourist people resulting in a very high floating population. Because of this reason the river Tunga along Shimoga town stretch is prone to anthropogenic activities such as bathing, washing and disposal of wastes. The ground level in the town slopes towards river so that most of the storm and sewerage drains discharge into river Tunga. There are two stream monitoring stations and 15 drains located in this town stretch

Monitoring Stations

Station – S1

Station S1 is located on the north side of the river, near the Shimoga Thirthahalli new bridge. It is an upstream station and near this station water is being drawn for supply to the town.

Station – S2

This station is about 300 m downstream of station S1.The station S2 is located on a drain that enters the river from the industrial town areas. The flow in the drain is mainly comprised of industrial waste.

Station – S3

The station S3 is an most affected station and is positioned near the Vinayaka temple(Ramanna shetty park). It is downstream of the sewage disposal point from the station S3. A bathing ghat exists near this Station.

Station S4 is located on the south side of the river, near the Shimoga Bhadravathi new bridge. Two number of sewage drains dispose city sewage water in to the river directly.

Data Preparation

The data sets of 4 water quality monitoring stations which comprised of 10 water quality parameters monitored monthly over 2 years (2013-2014) are used for this study. The data is obtained from the water Quality Monitoring work of Tunga River Basin in Shimoga District,

Karnataka State Although there are more water quality parameters in these stations, only 10 most important parameters are chosen because of their continuity in measurement through the 12 years. The 10 selected water quality parameters include Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Chlorides (Cl), Total Dissolved Solids (TDS), Conductivity, Temperature and pH.

Analysis of samples

The water samples were collected from each of the five selected stat ions according to the standard sampling methods (IS: 2488, 1966 APHA, 1998).Samples for estimating dissolved oxygen (DO) and biochemical oxy gen demand (BOD) were collected separately in BOD(glass) bottles. Water temperature was recorded on the spot using thermometers.

RESULT AND DISCUSSION

Temperature was found to be ranged between 14 0C (minimum) to 280C (maximum) with average value of 210+9.90C from all the sites. Impinging solar radiation and the atmospheric temperature brings interesting spatial and temporal changes in natural waters. The rise in temperature of water accelerates chemical reactions, reduces solubility of gases, amplifies taste and odour and elevates metabolic activity of organisms (Usharani et al., 2010).

pH of the aquatic system is an important indicator of the water quality and the extent pollution in the watershed areas. pH was recorded to be varying from 6.43 (minimum) to 9.13 (maximum) with an average value of 7.78+1.91 from all the sites (Jonnalagadda et al.,2001). It has been mentioned that the increasing pH appear to be associated with increasing use of alkaline detergents in residential areas and alkaline material from wastewater in industrial areas (Chang, H., 2008)

Conductivity is a good and rapid method to measure the total dissolved ions and is directly related to total solids. Higher the value of dissolved solids, greater the amount of ions in water (Bhatt.,1999). The range of Electrical conductivity from all the sites was recorded as 340.00

µmhos (minimum) to 734.00 µmhos (maximum) with an average value of 537.00+278.60 µmhos

The value of Dissolved Oxygen is remarkable in determining the water quality criteria of an aquatic system. In the system where the rates of respiration and organic decomposition are high, the DO values usually remain lower than those of the system, where the rate of photosynthesis is high (Mishra et al., 2009). During the study period DO was found to be ranging between 4.90 mg/l (minimum) to 8.50 mg/l (maximum) from all the sites with an average value of 6.70+2.55 mg/l.

Biochemical Oxygen Demand is a measure of the oxygen in the water that is required by the aerobic organisms. The biodegradation of organic materials exerts oxygen tension in the water and increases the biochemical oxygen demand (Abida, 2008).BOD has been a fair measure of cleanliness

of any water on the basis that values less than 1-2 mg/l are considered clean, 3 mg/l fairly clean, 5 mg/l doubtful and 10 mg/l definitely. During the study period BOD varied from 3.00 mg/l (minimum) to 8.00 mg/l (maximum) with an average value of 5.50+3.54 mg/l at all the sites.

Chemical Oxygen Deand is a measure of the oxidation of reduced chemicals in water. It is commonly used to indirectly measure the amount of organic compounds in water. The measure of COD determines the quantities of organic matter

found in water. This makes COD useful as an indicator of organic pollution in surface water (King et al., 2003).COD pointing to a deterioration of the water quality likely caused by the discharge of municipal waste water (Mamais et al., 1993). In the present study COD was found to be ranging from 11 mg/l (minimum) to 24 mg/l (maximum) with average value of 17.50+9.19 at all the sites.

Alkalinity of water is a measure of weak acid present. Total alkalinity of water is due to presence of mineral salt present in it. Alkalinity was ranged between 123.00 mg/l (minimum) to 240.00 (maximum) mg/l with average value of 181.50+82.73 mg/l from all the sites.

Total hardness is the parameter of water quality used to describe the effect of dissolved minerals (mostly Ca and Mg), determining suitability of water for domestic, industrial and drinking purpose attributed to presence of bicarbonates, sulphates, chloride and nitrates of calcium and magnesium (Taylor, 1949). The variation in Total hardness during study period at all the sites was recorded as

mg/l to 475.00 mg/l with average value of 352.50+173.24 mg/l

Chlorides occur naturally in all types of water. High concentration of chloride is considered to be the indicators of pollution due to organic wastes of animal or industrial origin. Chlorides are troublesome in irrigation water and also harmful to aquatic life (Rajkumar, 2004). The levels of chloride in the present study were ranging from 18.00 mg/l (minimum) to 32.00 mg/l (maximum) with an average value of 25.00±9.90 mg/l at all the sites.

Fluoride concentration is an important aspect of hydrogeochmistry, because of its impact on human health. The recommended concentration of Fluoride in drinking water is 1.50 mg/l. The values recorded in this study was ranged between 0.40 mg/l (minimum) to 1.20 (maximum) mg/l with an average value of 0.80±0.57 mg/l from all the sites.

Table 1: Physico-chemical qualities of river water

Where D.O.= Dissolved Oxygen, BOD= Biochemical Oxygen Demand, COD= Chemical Oxygen Demand, TH= Total Hardness.

The present study concluded that river water of study area was moderately polluted in respect to analyzed parameters. pH, total hardness, chloride and fluoride were found within permissible limit but the higher values of BOD and COD in present study attributed river water was not fit for drinking purpose. It needs to aware local villagers to safeguard the precious river and its surrounding

APHA. Standard methods for the examination of water and wastewater.18thEdition, Washingoton, D.C 1992

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Chemical Properties Of Asa River Water, Kwara State, Nigeria. Science Focus Vol, 10 (l), 2005 pp 72 76.

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Meitei, N.S., Bhargava and Patil, P.M. Water quality of Purna river in Purna Town, Maharashtra state. J. Aqua. Biol., 19- 77, 2005

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Rajkumar, S., Velmurugan, P., Shanthi, K., Ayyasamy, P.M. and Lakshmanaperumalasamy, P.(2004). Water Quality of Kodaikanal lake, Tamilnadu in Relation to PhysicoChemical and Bacteriological Characteristics, Capital Publishing Company, Lake 2004, pp.339- 346

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for water pollution studies. Environ. Publication, Karad. Maharashtra, India ,1994.

Usharani, K., Umarani,K., Ayyasamy, P.M., Shanthi, K.Physico- Chemical and Bacteriological Characteristics of Noyyal River and Ground Water Quality of Perur, India. J. Appl. Sci. Environ. Manage. Vol.14(2) 29-35,2009

ACKNOWLEDGEMENT

I would like to thank principal of RajaRajeswari College of Engineering and Management of RajaRajeswari Group of Institutions for extending encouragement and support to present the paper in the International Conference at T.John College of Engineering, Bangaluru

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Water pollution is killing millions of Indians. Here's how technology and reliable data can change that

It's estimated that around 70% of surface water in India is unfit for consumption Image:  REUTERS/Babu

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Humans have wrestled with water quality for thousands of years, as far back as the 4th and 5th centuries BC when Hippocrates, the father of modern medicine, linked impure water to disease and invented one of the earliest water filters. Today, the challenge is sizeable, creating existential threats to biodiversity and multiple human communities, as well as threatening economic progress and sustainability of human lives.

As India grows and urbanizes, its water bodies are getting toxic. It's estimated that around 70% of surface water in India is unfit for consumption . Every day, almost 40 million litres of wastewater enters rivers and other water bodies with only a tiny fraction adequately treated. A recent World Bank report suggests that such a release of pollution upstream lowers economic growth in downstream areas, reducing GDP growth in these regions by up to a third. To make it worse, in middle-income countries like India where water pollution is a bigger problem, the impact increases to a loss of almost half of GDP growth. Another study estimates that being downstream of polluted stretches in India is associated with a 9% reduction in agricultural revenues and a 16% drop in downstream agricultural yields.

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India is suffering the 'worst water crisis in its history', what is the future of india’s rural water system, india's water crisis is hitting women hardest. here's why.

The cost of environmental degradation in India is estimated to be INR 3.75 trillion ($80 billion) a year. The health costs relating to water pollution are alone estimated at about INR 470-610 billion ($6.7-8.7 billion per year) – most associated with diarrheal mortality and morbidity of children under five and other population morbidities. Apart from the economic cost, lack of water, sanitation and hygiene results in the loss of 400,000 lives per year in India . Globally, 1.5 million children under five die and 200 million days of work are lost each year as a result of water-related diseases.

To set up effective interventions to clean rivers, decision-makers must be provided with reliable, representative and comprehensive data collected at high frequency in a disaggregated manner. The traditional approach to water quality monitoring is slow, tedious, expensive and prone to human error; it only allows for the testing of a limited number of samples owing to a lack of infrastructure and resources. Data is often only available in tabular formats with little or no metadata to support it. As such, data quality and integrity are low.

Using automated, geotagged, time-stamped, real-time sensors to gather data in a non-stationary manner, researchers in our team at the Tata Centre for Development at UChicago have been able to pinpoint pollution hotspots in rivers and identify the spread of pollution locally. Such high-resolution mapping of river water quality over space and time is gaining traction as a tool to support regulatory compliance decision-making, as an early warning indicator for ecological degradation, and as a reliable system to assess the efficacy of sanitation interventions. Creating data visualizations to ease understanding and making data available through an open-access digital platform has built trust among all stakeholders.

Beyond collecting and representing data in easy formats, there is a possibility to use machine learning models on such high-resolution data to predict water quality. There are no real-time sensors available for certain crucial parameters estimating the organic content in the water, such as biochemical oxygen demand (BOD), and it can take up to five days to get results for these in a laboratory. These parameters can potentially be predicted in real-time from others whose values are available instantaneously. Once fully developed and validated, such machine learning models could predict values for intermediary values in time and space.

Furthermore, adding other layers of data, such as the rainfall pattern, local temperatures, industries situated nearby and agricultural land details, could enrich the statistical analysis of the dataset. The new, imaginary geopixel, as Professor Supratik Guha from the Pritzker School of Molecular Engineering calls it, has vertical layers of information for each GPS (global positioning system) location. Together they can provide a holistic picture of water quality in that location and changing trends.

In broad terms, machine learning can help policy-makers with estimation and prediction problems. Traditionally, water pollution measurement has always been about estimation – through sample collection and lab tests. With our technology, we are increasing the scope and frequency of such estimation enormously – but we are also going further. With our machine learning models, we are trying to build predictive models that would completely change the scenario of water pollution data. Moreover, our expanded estimation and prediction machine learning tools will not just deliver new data and methods but may allow us to focus on new questions and policy problems. At a macro level, we aim to go beyond this project and hope to bring a culture of machine learning into Indian Public Policy.

Under the theme, Innovating for India: Strengthening South Asia, Impacting the World , the World Economic Forum's India Economic Summit 2019 will convene key leaders from government, the private sector, academia and civil society on 3-4 October to accelerate the adoption of Fourth Industrial Revolution technologies and boost the region’s dynamism.

Hosted in collaboration with the Confederation of Indian Industry (CII), the aim of the Summit is to enhance global growth by promoting collaboration among South Asian countries and the ASEAN economic bloc.

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Access to information has been an important part of the environmental debate since the beginning of the climate change movement. The notion that “information increases the effectiveness of participation” has been widely accepted in economics and other social science literature. While the availability of reliable data is the most important step towards efficient regulation, making the process transparent and disclosing data to the public brings many additional advantages. Such disclosure creates competition among industries on environmental performance. It can also lead to public pressure from civil society groups, as well as the general public, investors and peer industrial plants, and nudge polluters towards better behaviour.

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The great indian thirst: the story of india's water crisis, solutions to tackle it, the country is staring at a grave water crisis unless we get our act together, and fast..

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Ominously for India, history seems to be repeating itself. A NITI Aayog report in 2018 stated bluntly that 600 million people, or nearly half of India’s population, face extreme water stress. That three-fourths of India’s rural households do not have piped, potable water and rely on sources that pose a serious health risk. That India has become the world’s largest extractor of groundwater, accounting for 25 per cent of the total. That 70 per cent of our sources are contaminated and our major rivers are dying because of pollution. Its conclusion: ‘India is suffering from its worst water crisis in its history.’

• Gautam I. Menon 0

Gautam I. Menon is the director of the Centre for Climate Change and Sustainability at Ashoka University in Sonipat, India.

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Old Delhi’s Red Fort, a nearly 400-year-old structure where India’s flag is hoisted every Independence Day, is separated from the Yamuna River by a 55-kilometre ring road that circles the capital. I drive past it on this road, built on an old floodplain, on my way to work at Ashoka University in the neighbouring state of Haryana, a further 30 kilometres or so upstream. The river is hidden from view in places but it can be seen farther along, narrow and darkened by pollution for most of the year.

In July 2023, flood water from heavy monsoon rains entered the Yamuna from Haryana, flooding parts of Delhi. TV images of the river lapping at the walls of the Red Fort recalled nineteenth-century paintings of the old course of the river.

Nature Spotlight: India

The Yamuna forms from the melting glaciers of the lower Himalayas, running for more than 1,370 kilometres until it merges with the Ganga in the city of Prayagraj in Uttar Pradesh. Delhi lies along its banks for just 20 kilometres, less than 2% of the river’s total length. But in that short stretch, the city belches out around 80% of the pollution found in the Yamuna. In some seasons, a foamy mixture of sewage and industrial waste coats the river surface in parts of Delhi. Newspapers carry pictures of Hindu devotees offering morning prayers while standing knee-deep in this toxic foam.

Much of Haryana’s ground water is used to cultivate rice. Farmers pump it up using electricity that the state government heavily subsidizes to encourage agriculture. Without economic incentives to use this electricity sustainably, groundwater levels declined precipitously from the 1990s into the early 2000s. To combat this, legislation was introduced in 2009 to restrict the sowing of rice to mid-June onwards, timed to begin after the start of the monsoon season. Previously, rice planting had started as early as May.

This means that the rice-harvesting season ends even closer to the wheat planting season, which begins in November. Farmers need to get rid of their rice-crop residue as soon after harvesting as possible to clear space for the wheat.

Burning the crop residue is the cheapest solution. But in the early winter months, smoke and dust released from a combination of residue burning and other sources is concentrated by frequent changes in temperature and stagnant winds, and shrouds northern India. Schools are closed, construction work is halted and flights are grounded because of the poor visibility. Hospitals fill with people complaining of breathing difficulties. Each resident of Delhi is thought to lose nearly 12 years of their life to air pollution.

As the world’s climate changes, extreme events such as the rains that led to the Delhi floods in July will become more common. The southern Indian state of Kerala witnessed a devastating flood in 2018, the worst in almost a century of recorded history. More than one million people were evacuated to higher ground. A study that year showed that about 60% of the coast of Kerala was eroding, and areas where good fishing could be found were shifting, affecting the lives of one million fishers and their families.

Two large Indian cities, Chennai, on the Bay of Bengal, and Kolkata, on the banks of the Hooghly River, are expected to be at significant risk from sea-level rise in the next few decades. Along with the resulting intrusion of salt water into groundwater systems, this will increase climate-change-induced migration. The Sundarbans, an ecologically sensitive wetland system on the Bay of Bengal that contains the largest mangrove forest in the world, has already seen substantial climate-change-driven migration into the nearby city of Kolkata.

The Namami Gange Programme is one of many started since the mid-1980s to clean up India’s iconic holy river, the Ganga. Around US$3 billion for this has been set aside or spent since 2014, largely on new sewage-treatment plants.

But pollution levels remain stubbornly high, the result of lax enforcement of control measures and unregulated river-front development. More data are needed, and more transparency on the causes, so citizens can hold civic bodies and elected representatives responsible.

Science can help too. The Ministry of Earth Sciences is funding several initiatives aimed at improving India’s ability to model the monsoon. This will help provide actionable advance warnings of extreme rain events. More research on the geomorphology of coastal India, on near-shore ocean current patterns and on the impact of sea walls could aid the design of interventions to slow coastal erosion.

Fresh water is a finite and vulnerable resource that should be managed in a participatory fashion. Citizen groups in the south-Indian city of Bengaluru are helping to renew urban water bodies, reconfiguring them as centres around which communities can coalesce. In arid areas, such as the deserts of Rajasthan and Gujarat, old methods of rainwater harvesting are being revived, helped by traditional community knowledge.

Guaranteeing a minimum amount of fresh water for each individual, free of charge, will ensure broader societal equity. Beyond that limit, water usage should be priced, creating an economic incentive for its sustainable use. Such a policy was introduced nearly a decade ago by the Delhi government, but continued groundwater extraction using illegal borewells has partly neutralized this positive step.

Ensuring the sustainable use of water intersects climate change, agriculture, politics, pollution, migration and much more. Well-intentioned policy measures, such as subsidizing electricity for agriculture, can have unexpected consequences for water and its sustainable use.

Placing water at the centre of our thinking about sustainability can help avoid such pitfalls. We need more conversations about water.

Nature 624 , S25 (2023)

doi: https://doi.org/10.1038/d41586-023-03909-3

This article is part of Nature Spotlight: India , an editorially independent supplement. Advertisers have no influence over the content.

Competing Interests

The author declares no competing interests.

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How river pollution is killing people in an Indian village

Dozens of villages near India’s capital are suffering after years of unchecked industrial pollution has contaminated their water.

Gangnauli, India – Vikas Rathi lies, barely alive, on a cot in the sparsely furnished living room of a small two-story house in Gangnauli village in the northern state of Uttar Pradesh. The 23-year-old’s gaunt cheeks highlight his pinched nose and sunken eyes even more.

Vikas has been diagnosed with stunted growth and bone deformity. He is one of the hundreds of young adults and adolescents across the region who are afflicted by a host of ailments: stunted growth, liver diseases, cancers, and critical deformities.

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In Gangnauli – home to about 5,000 people and located about 180km (110 miles) from India’s capital New Delhi – about a third of the youth are sick.

Villagers say the diseases are striking more and more people, affecting almost every household. The contaminated groundwater they have been drinking, they say, is destroying their health.

More than 71 people died of cancer in Gangnauli alone between 2013 and 2018, according to data released by the National Green Tribunal (NGT) in 2019, the only official figure available.

Satendar Rathi, Vikas’ father, says his eldest son Vikas, whose name means growth in the Hindi language, has been bedridden since 2010

He was born healthy, his father continues, but his bones started deforming soon after he started drinking and eating solid food.

“We took him for traditional as well as English [modern] medicine treatment. Doctors suggested vitamin D supplements. We continued his treatment for nine years but nothing worked,” Satendar, a 48-year-old constable in the Delhi police, says as he sinks into a chair in the living room on the banks of the Krishna River.

His modest salary of $490 a month can barely cover medical expenses for Vikas.

“Finally, the doctors in Delhi told us there is a problem with the water we were consuming,” Satendar told Al Jazeera, referring to the groundwater.

“We can’t leave him alone for even a minute. If there is no one around he urinates and passes stool in his pants,” says Satendar, sighing helplessly as Vikas looks hauntingly at us.

“Vikas is a living corpse,” he says.

Carcinogens in the water

The NGT – the country’s top environmental court – confirmed in 2017 that water was indeed the cause of the mass sickness in villages across five districts in western Uttar Pradesh after the crisis was brought to its attention by environmental campaigners and it tested the groundwater and river water.

In the villages that did not have a piped water supply, villagers were drinking polluted groundwater pulled up by hand pumps.

The NGT recommended a door-to-door medical survey across the 48 hardest-hit villages in the region. It also called for providing piped drinking water, the establishment of specialised hospitals, and curbs on industrial effluents, among other measures.

But the health department in the state – India’s most populous – has not followed through on most of the recommendations, Al Jazeera found.

Dr Dinesh Kumar, chief medical officer of Baghpat district, where Gangnauli is located, admitted that carcinogenic elements had been found in the water.

“It is true that heavy elements and carcinogenic elements are present in the water but we can’t say for sure that they are responsible for cancer in the area. I am saying this because further studies have not been done on the cases studies found here to explore the links between the two,” he told Al Jazeera.

He added that a survey had been conducted more recently as part of anti-COVID health measures, during which officials were directed to identify cancer patients and people with co-morbidities.

“We found cases of skin diseases. Cases of Hepatitis C are found higher than usual in these villages.”

Industrial pollution

The fertile soil of the upper Doab region – the river basin of the Ganges and Yamuna Rivers – was home to a substantial agricultural community. Water from the Kali, Krishna and Hindon Rivers – important tributaries of the Yamuna River to the west – used to be a source of life and livelihood in the region some 20 years ago.

But Doab’s proximity to the capital led to many of its cities, such as Meerut, Baghpat, Saharanpur, Gautam Buddh Nagar and Ghaziabad, becoming industrial centres.

Dharmendar Rathi, the former village head of Gangnauli, says the groundwater started becoming poisonous as industries and mills started proliferating in the area , operating without the waste-treatment facilities they are required to have.

The industrial waste from sugar mills, slaughterhouses, paper mills, dye-making industries and distilleries empties into the rivers, turning them into sewage canals. Eventually, the unchecked industrial waste dumping contaminated the groundwater.

Dharmendar says: “Most of us kept drinking it till the last few years, our cattle drank it, and we used it to irrigate our farm and vegetables.”

He tells Al Jazeera there isn’t a single household in the village without a critically ill family member and that more than 200 people in Gangnauli had to sell their land to pay for medical expenses.

Many families have gone bankrupt treating their sick members, running from one hospital to another due to a lack of adequate health facilities in the state of 204 million people, he says.

“Our estimate suggests that more than 150 in this village alone have died of cancer, there are numerous cases of hepatitis, skin allergies and deformities. Just imagine the number of victims in other affected villages in this region.

“The future of this region is gone, the next generation has been destroyed at birth,” he says, showing a long list of villagers who died of cancer in the last decade.

Appealing to the NGT

Chandraveer Singh, from the nearby village of Daha, says his sister-in-law Urmila died of liver cancer earlier this year.

According to the 65-year-old retired scientist, people in more than 100 villages on the banks of the Kali, Krishna and Hindon Rivers have been drinking polluted groundwater for the last decade.

After he retired in 2013, Chandraveer, who worked at the pollution control board in the neighbouring state of Haryana, started working on water pollution in western UP. He petitioned the NGT in 2014 to intervene on the issue.

In 2014, he sent water samples from the Krishna for testing at SIMA Labs. SIMA labs are recognised by the Federal Ministry of Environment and Forests, and the Uttar Pradesh Pollution Control Board (UPPCB).

The results were disturbing – they confirmed an extremely high content of heavy metals and chemical compounds like arsenic, mercury, lead, zinc, phosphate, sulfide, cadmium, iron, nickel and manganese. All heavy metals are linked with cancer, bone deformity, and stomach-related diseases.

The total suspended solids in the river water measured 7,500mg/litre, as against the permissible 200mg/litre. The presence of sulfide was 285mg/litre as against the permissible 2mg/litre.

Extremely high levels of mercury and lead were also found. Lead was 0.115 as against the permissible limits of 0.01 mg/litre. Mercury was 0.12 mg/litre against the permissible limits of 0.01 mg/litre.

“No aquatic life survives in the river water,” says Chandraveer.

State of health services

Dharmendar says the local community health centres lack resources.

“The public health centres in the vicinity are not equipped to deal with a problem of this magnitude. Only a nurse or the doctor’s assistant is generally present at the health centres,” he says.

The closest big hospital is in Meerut – the largest city in the region – about 56km (35 miles) east of Gangnauli.

“The government hospital in Meerut is overcrowded and patients do not get the care they deserve,” he says, adding that there are not enough doctors.

The state, currently being governed by Prime Minister Narendra Modi’s Bharatiya Janata Party (BJP), ranks at the bottom of the health index prepared by the NITI Aayog – the government policy think-tank.

But the health crisis has hardly made it to the political agenda in the state as successive governments ignored the health issues people face. “What is the meaning of democracy when my people are dying of unexplained sickness and death? For decades we drank toxic water,” Dharmendar says.

“How could we dream of becoming a vishwa guru [super power] when we can’t provide the basic facilities which are essential to our fundamental right to life?”

Local BJP legislator Krishan Pal Singh defended the government, blaming previous governments for doing nothing to address the issue.

“Whatever relief people have got on this subject, happened under the BJP government,” he told Al Jazeera. The BJP came back to power in UP in 2017 after a gap of 15 years.

“When we came to power, we were given a state which barely saw any development. So it might take some time to solve people’s problems,” he adds.

NGT recommendations

Four years since the country’s top environmental watchdog recommended measures, local authorities have only partially implemented them.

Most of the polluting industries, mainly sugar mills, distilleries, electroplating workshops and slaughterhouses, continue to dump effluent into the rivers with little or no facilities put in place to treat industrial waste.

The NGT formed a supervisory committee in 2018 to monitor the implementation of its recommendations. The committee in its four reports since 2019 said no meaningful action had been taken by authorities to clean up the Kali, Krishna and Hindon Rivers. It accused Uttar Pradesh officials of “apathy” and even “stonewalling” its action plan and monitoring.

In its last directive – released in February 2021 and seen by Al Jazeera – the NGT notes that officials “did not comply” with most of its recommendations. The state government has not cooperated and its attitude was “disappointing”, the NGT said.

Out of the total of 133 sewage drains that needed to be covered, only 20 were covered and the remaining 113 are “in the process of being tapped”, as the progress report submitted by the government mentions. The sewage drain tapping would help control the spread of diseases.

Some of the recommendations, such as the preparation of micro plans to prevent groundwater pollution by industrial effluents, and identify and deal with other sources of water pollution – covering the entire stretch of drains, and identifying causes of ailments like skin diseases, jaundice and cancer – were not complied with, according to the February 2021 NGT order.

The only work that has been done to some measure is providing piped drinking water to more than 50 percent of the residents in these 150-plus villages, the committee said.

Local health officials in Baghpat told Al Jazeera COVID-19 had prevented them from making any plans. Singh, the local BJP legislator, also blamed the pandemic for the delay in implementing the NGT recommendations.

The NGT had highlighted repeatedly how the UPPCB couldn’t finish work on its recommendations: bio/phytoremediation of drains (using plants and micro-organisms to clean industrial effluents), covering drains, installing sewage treatment plants in water-polluting industries.

A senior official from the UPPCB, who wished to remain anonymous, told Al Jazeera: “As we mentioned in our ‘action taken report’ submitted before the NGT, bioremediation work on several drains over a total stretch of 76km is being done. The bioremediation on drains in Shamli, Muzaffarnagar and Baghpat has been initiated.

“[W]ork on the installation of sewage treatment plants in Muzaffarnagar and Budhana will be done soon. Work on the one in Saharanpur will be started soon,” he said, adding, “it will take some time before the work is completed.”

“By law, the industries are supposed to have a sewage treatment plant (STP) installed before they operationalise the factory. But, courtesy of corruption, in most cases the industries bribe officials and start functioning without an STP which is supposed to treat the effluents. So the state government is penalising the industries now in a big way, and pushing them to have an STP in their factories,” he added.

He added that among the decisions the UPPCB has taken to mitigate pollution is the imposition of a fine of 11.32 crore rupees ($1.41m) as environmental compensation on 230 industries for polluting river water in the last four years.

Environmental campaigner Chandraveer isn’t hopeful.

“The institutional and bureaucratic dysfunction of the world’s largest democracy continues to deprive the remaining residents of safe and clean drinking water,” he tells Al Jazeera.

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Ganga River: A Paradox of Purity and Pollution in India due to Unethical Practice

D C Jhariya 1 and Anoop Kumar Tiwari 2

Published under licence by IOP Publishing Ltd IOP Conference Series: Earth and Environmental Science , Volume 597 , National Conference on Challenges in Groundwater Development and Management 6-7 March 2020, NIT Raipur, India Citation D C Jhariya and Anoop Kumar Tiwari 2020 IOP Conf. Ser.: Earth Environ. Sci. 597 012023 DOI 10.1088/1755-1315/597/1/012023

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1 Assistant Professor, Department of Applied Geology, National Institute of Technology Raipur, Chhattisgarh-492010, India

2 Assistant Professor, Department of Humanities and Social Sciences, National Institute of Technology Raipur, Chhattisgarh-492010, India

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In India, the river Ganga is believed as a goddess, and people worship it. Despite all the respect for the river, the river's condition is worsening, and we Indians are unable to maintain the purity of the river. The Ganga is a river of faith, devotion, and worship. Indians accept its water as "holy," which is known for its "curative" properties. The river is not limited to these beliefs but is also a significant water source, working as the life-supporting system for Indians since ancient times. The Ganga river and its tributaries come from cold, Himalayan-glacier-fed springs, which are pure and unpolluted. But when the river flows downgradient, it meets the highly populated cities before merging into the Bay of Bengal. From its origin to its fall, its water changes from crystal clear to trash-and sewage-infested sludge. Thousands of years passed since the river Ganga, and its tributaries provide substantial, divine, and cultural nourishment to millions of people living in the basin. Nowadays, with the increasing urbanization, the Ganges basin sustains more than 40 percent of the population. Due to the significant contribution of the growing population and rapid industrialization along its banks, river Ganga has reached an alarming pollution level.

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Water Pollution in Bangalore City: A Threat to Sustainable Development Goal 6

• Dr. Jonas Richard A
• Oct 3, 2023
• Water Pollution

Water Pollution in Bangalore City: A Threat to Sustainable Development Goal 6 1 Mr. Raghav, 2 Dr. Jonas Richard A 1 Neev Academy, Bangalore 2 Professor & Head, Dept. of Social Work, Kristu Jayanti College, Bangalore

DOI: https://dx.doi.org/10.47772/IJRISS.2023.70966

Received: 08 August 2023; Revised: 27 August 2023; Accepted: 30 August 2023; Published: 03 October 2023

While there has been extensive research done on water pollution in Bangalore and its increasingly pernicious effect on local water bodies and communities, little has been done to collate information on local solutions to water pollution. This research paper aimed to research the causes of water pollution, consequences of water pollution, awareness levels of water pollution, and local suggestions and recommendations to help mitigate water pollution. Results of secondary research through literature and primary research using a google form on one hundred and three respondents showed that most residents, both within a kilometer and beyond that are aware of the presence and consequences of water pollution. However, there is much variance regarding possible solutions to water pollution in rural or slum-based communities. Nevertheless, this study narrowed down a few effective and salient suggestions to improve water pollution, such as waste relocation and watershed production.

Keywords: Water Pollution, SDG 6, contamination, Industrial pollution, Awareness Levels, Causes, and Consequences.

INTRODUCTION      

At one point, Bangalore was known as ‘the city of lakes because of the large number of water bodies that scattered the region. Even now, it is a city with more than a hundred lakes and a thousand water bodies. As time passed, however, most of these bodies, and especially the major lakes like Varthur and Bellandur, were subjected to high levels of pollution. Bangalore’s industrial growth has contributed to water pollution. Karnataka State Pollution Control Board (KSPCB) stated in 2021, industrial units in and around Bangalore were discharging a substantial amount of untreated or partially treated effluents into water bodies, contaminating them. Consequently, many locals and long-term residents who relied on the bodies of water either for income, sustenance, or both, suffered great economic, environmental, and medical setbacks to their way of life. The link between SDG 6 and water pollution is central to achieving sustainable development and ensuring universal access to clean water and adequate sanitation for all. SDG 6 focuses on “ensuring availability and sustainable management of water and sanitation for all” and encompasses several targets related to water quality, pollution reduction, and ecosystem protection. Addressing water pollution is vital to achieving SDG 6 and broader sustainable development. Governments, communities, and businesses must collaborate to implement effective water pollution control measures, invest in wastewater treatment, promote sustainable industrial practices, and raise awareness about responsible water usage to safeguard water resources and achieve the targets outlined in SDG 6.

To further contextualize the extent of this issue, the researcher has used the conditions set forth by the sixth Sustainable Development Goal (Clean Water and Sanitation) to identify areas and local methods of improvement regarding this city’s water-body ecosystems. The relevant goals of the sixth SDG are to protect and restore water-related ecosystems, to improve water quality by reducing pollution, and to support and strengthen the participation of local communities in improving water and sanitation management.

While there are four other goals, they are not as pertinent to this article at the moment. The goal of this paper is to investigate the causes, consequences, and possible solutions to water pollution with the aid of a community sample. This research has drawn from the literature review of sources describing the causes and consequences of water pollution in Bangalore. This study focused on the relevant content related to the issue and then narrowed the research to a few major topics such as water-borne diseases.

Overall this study is aimed at finding out the causes of water pollution, consequences of water pollution, awareness levels of water pollution, and local suggestions and recommendations to help mitigate water pollution.

Consequences of Water Pollution in Bangalore City

Contamination of drinking water sources is a serious problem caused by water pollution. It affects not only human health but also the economy, and it is a major concern in Bangalore. Central Pollution Control Board highlighted that around 50% of the water samples collected from various locations in the city was found to be contaminated with fecal coliform bacteria, which can cause various water-borne diseases. Additionally, water sources in the city are also affected by heavy metals, pesticides, and other pollutants, which can have harmful effects on human health. The situation is alarming as it is estimated that around 80% of the city’s population is dependent on groundwater as a source of drinking water. Bangalore Water Supply and Sewerage Board (BWSSB) mentioned that the water quality in the city has been deteriorating over the years, with the number of areas where water is not fit for drinking increasing from 51 in 2017 to 63 in 2019.

The death of life within the aquatic ecosystem due to water pollution is a serious problem in Bangalore. According to a study by the Indian Institute of Science, around 80% of the city’s lakes have been affected by water pollution, with many of them showing signs of eutrophication, a process where excess nutrients lead to an overgrowth of algae and other aquatic plants. This can lead to a decrease in oxygen levels in the water, making it difficult for fish and other aquatic life to survive. Statistics show that the death of aquatic life is a major problem in the city. Karnataka State Pollution Control Board found that the number of fish deaths in the city’s lakes had increased from around 2,000 in 2015 to over 8,000 in 2018. Additionally, a study by the Bangalore Development Authority found that the number of fish species in the city’s lakes had decreased from around 40 in the 1990s to just 20 in 2019.

Water pollution can cause significant damage to agriculture in Bangalore , as pollutants in the water can affect the growth and yield of crops, and the health of livestock. Indian Institute of Science once stated water pollution in the city is affecting the growth of crops such as paddy, sugarcane, and vegetables, with a reduction of up to 20% in crop yields observed in some areas. Additionally, around 75% of the water samples collected from agricultural fields in the city were found to be contaminated with pesticides, which can have harmful effects on crops and soil health discussed by Central Pollution Control Board.

Water pollution in Bangalore can lead to the production of more greenhouses. When water sources are polluted, it can be difficult for farmers to grow crops using traditional methods. As a result, some farmers may turn to greenhouse farming as a way to protect their crops from the effects of polluted water. Greenhouses can provide a controlled environment for crop growth, which can help to mitigate the effects of water pollution. Indian Institute of Science stated water pollution in the city has led to a significant increase in the number of greenhouses in the surrounding areas. The study found that the number of greenhouses in the region had increased by more than 50% between 2015 and 2018.

Water pollution in Bangalore is seriously impacting tourism in the city. Over 70% of the city’s water bodies, including lakes and rivers, are severely contaminated with pollutants such as sewage and industrial waste. This has led to the closure of several popular tourist spots, such as Ulsoor Lake and Sankey Tank, due to the high levels of toxicity in the water. In addition, the city’s once-thriving fishing industry has been devastated, with fish populations declining by over 60% in recent years. These impacts not only harm the local environment and economy but also discourage tourists from visiting the city.

Water-borne diseases , as the name suggests, are transmitted through the ingestion of contaminated water. These diseases are present inside water in the form of pathogenic microorganisms. Some of the more lethal and widespread water-borne diseases include cholera, shigella, typhoid, and hepatitis (A and E). While the large-scale impact of these diseases cannot be denied, many of the water-borne disease cases around the world are not reported due to incorrect diagnoses or no diagnosis at all. The majority of water-borne diseases are diarrheal. Their outbreaks are often credited to bacteria, protozoa, and parasites that thrive in specific physical conditions (like at the peak of summer). Additionally, the total disregard for basic hygiene along with crumbling or non-existent infrastructure leads to people having a higher risk of contracting said afflictions.

Relationship of water pollution and water borne diseases in Bangalore

The relation between water pollution and waterborne diseases in Bangalore city is a significant concern that highlights the interconnectedness of environmental and public health issues. Water pollution refers to the contamination of water bodies, such as lakes, rivers, and groundwater, with harmful substances, including pollutants, chemicals, and pathogens. This pollution can lead to the spread of waterborne diseases, which are illnesses caused by consuming or coming into contact with contaminated water. In the context of Bangalore city, several factors contribute to the relationship between water pollution and waterborne diseases:

• Industrial Pollution: Bangalore’s rapid urbanization and industrial growth have led to increased discharge of pollutants into water bodies. Effluents from industries can contain toxic substances and heavy metals that contaminate water sources. When people consume or use this contaminated water, it can result in various waterborne diseases such as gastrointestinal infections, skin diseases, and even long-term health issues.
• Waste Disposal: Improper disposal of domestic and commercial waste, including plastic and other non-biodegradable materials, can clog waterways and contribute to water pollution. Stagnant water bodies become breeding grounds for disease-carrying vectors like mosquitoes, which can lead to diseases like malaria and dengue.
• Sewage Discharge: Inadequate sanitation infrastructure in certain areas of Bangalore can lead to the direct release of untreated sewage into water bodies. This introduces harmful pathogens like bacteria, viruses, and parasites into the water supply, causing diseases like cholera, typhoid, and hepatitis.
• Agricultural Runoff: The use of pesticides and fertilizers in agriculture can result in runoff that contains harmful chemicals. When these chemicals enter water sources, they can contaminate the water supply and lead to various health issues when consumed by humans or animals.
• Unregulated Development: Rapid urbanization and construction can lead to deforestation and soil erosion. Sediments from construction sites can flow into water bodies, altering their quality and potentially introducing contaminants.
• Groundwater Contamination: The contamination of groundwater sources due to improper disposal of hazardous waste or leaking septic tanks can result in long-term pollution of drinking water sources. This can lead to the gradual build up of pollutants and the spread of waterborne diseases over time.
• Climate Change Effects: Changes in weather patterns and increased temperatures due to climate change can influence water quality and the prevalence of disease-carrying vectors. This can exacerbate the spread of waterborne diseases in the city.

Addressing the relationship between water pollution and waterborne diseases in Bangalore requires a multi-faceted approach. This includes improving sanitation infrastructure, regulating industrial discharges, promoting responsible waste disposal practices, implementing effective wastewater treatment, and raising public awareness about the importance of clean water and its impact on public health.

SAMPLING AND METHODOLOGY

To reiterate, the goal of this study is to understand the causes of water pollution, the consequences of water pollution, and the awareness levels of water pollution amongst residents, and local suggestions and recommendations to help mitigate water pollution. The study was conducted with 103 respondents having 30 questions on different segments on water pollution and its impact.

This sampling process was descriptive in nature. The researcher used a Google Form as the sampling tool for this study as it allowed for the widest number of people to contribute to the goal of my study (Convenience sampling). There were four major sections present in the form, which essentially covered the field of study across central Bangalore: participant demographics, their awareness of what water pollution is and its consequences, their awareness of the causes of water pollution, and possible solutions they might have to problems associated with water pollution. The goal of this questionnaire is to help understand how residents from various parts of Bangalore perceive water pollution and how they think it can be solved. At the end of the study, their solutions can be compared to existing systems put into place to combat water pollution.

Since the research tool was used online, the sampling technique was largely convenience-based. This was the most feasible way of gathering results from a large number of responders. Another reason this method and tool of sampling worked well since the field of study would benefit most from a descriptive research design.

RESULTS & DISCUSSION ON PARAMETERS OF THE QUESTIONNAIRE

Section-1-Demographics

1. Gender: (73.8% Female, 26.2% Male)

2. Area of Residence: 70% of the respondents were from the Whitefield area.

• This variable asks for the participant’s area of residence. It was especially important to the study to understand the certain geographic section of the city and therefore increase the diversity of my sample body.

3. With regard to the age group, the majority of respondents were in the age group of 46 – 50 years.

4. All of the participants have at the least graduated from twelfth grade.

5. Most of the participants stayed in Bellandur and Sarjapur, however, there was a spread of responses from areas such as RT Nagar, Whitefield, HSR Layout, Ulsoor, and others.

Section-2- and its consequences Awareness Level of Water Pollution:

• Self-assessment of awareness of water pollution
• This is a binary yes or no question meant to assess whether participants are aware of water pollution. The question helps, for the study, determine how many participants thought themselves to be aware of water pollution.

2.  Percentage of water that participants think is polluted

• Now that participants have been asked whether they were aware of water pollution, they are given a series of options ranging from 65% to 95% with increments of 10% and asked to choose which option most likely reflects the amount of water that is polluted in Bangalore. The correct answer is 85% as per a study conducted by the EMPRI.

3.  Diseases caused by water pollution

• As seen from the literature review, water-borne diseases are amongst the most lethal consequences of water pollution. This question asked participants whether they were aware of these diseases happening to people they knew directly. The purpose of this question is to gauge at a smaller scale the influence of water pollution on health.

4. Checklist of consequences of water pollution

• This part of the study was added not only to ensure that participants can communicate the extent to which they were aware of the consequences of water pollution but to also allow participants to think about the effects of water pollution they might not have consciously identified before.

5. Checklist of water bodies that are known to be polluted

• This part of the study helps us analyze another facet of the participant’s knowledge regarding their immediate exposure to the water bodies around them. Another way in which this question helps is that it gives me a good idea of which water bodies are more and less known as polluted bodies of water. These results can be compared to the actual pollution of the water bodies in Bangalore to see whether any correlation exists.

Section-3-Awareness Level of Causes of Water Pollution :

   6. Checklist of causes of water pollution

• This element serves the same purpose as asking the participants about the consequences of water pollution.

Section-4-Recommendations

   7. Participant suggestions.

• This question is especially important to the study. Knowing about local solutions to water pollution is crucial because it can help individuals and communities take action to address the problem at a grassroots level. While larger-scale solutions such as regulations and industrial waste management are essential, local solutions can also play a significant role in mitigating pollution, which is why the answers to this question might help shed light on some of the possible courses of action that the city can take towards a cleaner Bangalore.

FINDINGS RELATED TO THE PARTICIPANT AWARENESS

Figure No: 01 – Awareness on the water pollution in Bangalore city

• It has been interpreted that, the majority of the participants are well aware of the level of water pollution within Bangalore with most of them (91.3%) knowing that it exists. This is unsurprising considering the amount of attention given to the consequences of water pollution online and over social media.

Figure No: 02 – Awareness on the percentage of water pollution in Bangalore city

Less than forty percentage of the respondents (38.8%) expressed that 65% of the water polluted in the city whereas one third of the respondents (34%) stated that 75% of the water polluted in the city of Bangalore. These findings reflect the perceptions of the respondents and their understanding of the severity of water pollution in Bangalore. It’s important to note that these percentages are based on the opinions of the surveyed individuals and might not accurately represent the actual levels of water pollution.

Figure No: 03 – Awareness on the water borne diseases through water pollution

As an additional note, more than fifty percentage of the respondents (53%) reported not having heard of diseases apart from these five. We can see here that Cholera (96.2%) was the most well heard of disease. Through the above findings, it can be inferred that a majority of the surveyed individuals were not familiar with diseases beyond a specified list, and Cholera was the most recognized disease among them. Public awareness of diseases is crucial for public health efforts and interventions. For less familiar diseases, educational campaigns and outreach programs might be necessary to improve understanding and awareness. It’s also important to ensure accurate information is disseminated to the public to prevent misconceptions or misinformation.

Figure No: 04 – Awareness on the water polluted areas in Bangalore

Most participants correctly identified the four or five most polluted areas of Bangalore with Bellandur, Varthur, Mahadevapura, and Agaralake having the highest percentage of responses. This indicates that these areas are widely recognized for their pollution issues among the respondents. The recognition of specific pollution hotspots can be valuable for local authorities, environmental agencies, and community groups to target pollution control measures and interventions in these areas. It also suggests that public awareness about the pollution problem in these regions is relatively high, which could potentially lead to increased community engagement and efforts to address the pollution concerns in these areas.

Figure No: 05 – Awareness on the causes of water polllution

The largest number of participants (96.1%) selected “mismanagement of sewage” to be a cause of water pollution, while the least number of participants (43.7%) selected “flooding” as a cause of water pollution. From this data, it can be deduced that a vast majority of participants recognize “mismanagement of sewage” as a significant cause of water pollution. This highlights the importance of proper wastewater management and treatment to prevent contamination of water bodies.

On the other hand, a relatively smaller percentage of participants identified “flooding” as a cause of water pollution. Flooding can indeed lead to water pollution by carrying pollutants from various sources into water bodies, but the lower percentage of participants selecting this option might indicate a need for further education and awareness about the relationship between flooding and water pollution.

  Figure No: 06 – Awareness on the consequences of water pollution

• The largest number of participants (94.2%) selected “waterborne diseases” to be a consequence of water pollution, while the least number of participants (46.6%) selected “production of more greenhouse gasses” as a cause of water pollution, which is surprising. It is inferred that water pollution has severe consequences on the environment, human health, and economies. Polluted water bodies disrupt aquatic ecosystems, leading to reduced biodiversity, fish kills, and algal blooms. Contaminated water poses health risks to humans, causing waterborne diseases and long-term health problems. The pollution of drinking water sources leads to increased medical costs and economic burdens on communities. Moreover, impaired water quality affects agriculture, as contaminated water for irrigation negatively impacts crop yields and food safety. Industries reliant on water face increased operational costs due to the need for advanced treatment processes. The economic losses from water pollution are substantial, including reduced tourism revenue, devaluation of properties near polluted water bodies, and increased costs for clean-up efforts.

RECOMMENDATIONS AND SUGGESTIONS

These are the most common and effective (as corroborated with research) recommendations and suggestions given by the respondents.

• Proper waste management: Encourage responsible disposal of household waste and recycling to prevent pollutants from entering the waterways.
• Limit chemical usage: Minimize the use of fertilizers, pesticides, and herbicides, especially near the lake’s shoreline, to prevent runoff into the water.
• Adopt eco-friendly cleaning products: Use environmentally friendly and biodegradable cleaning products to minimize the introduction of harmful chemicals into the lake.
• Maintain septic systems: Regularly inspect and maintain septic systems to prevent leaks and ensure proper functioning to prevent contamination of groundwater and nearby lakes.
• Reduce storm water runoff: Implement measures like rain gardens, permeable pavement, and retention ponds to capture and filter storm water runoff before it reaches the lake.
• Support watershed protection: Get involved in local watershed protection programs and advocate for policies that safeguard water quality in the entire watershed, not just the lake.
• Organize lake clean-up events: Coordinate community clean-up events to remove trash, debris, and pollutants from the lake and its surrounding areas.
• Install buffer strips: Establish vegetation buffer strips along agricultural areas to reduce the amount of sediment, nutrients, and chemicals reaching the lake.
• Promote responsible fishing: Encourage catch-and-release practices, adhere to fishing regulations, and educate anglers about the potential impacts of certain fishing practices on water quality.
• Monitor water quality: Support or participate in water quality monitoring programs to identify pollution sources and take appropriate action to address them.
• Educate the community: Raise awareness about water pollution issues, its impacts on the ecosystem, and how individuals can contribute to solving the problem.
• Advocate for policy changes: Engage with local government officials and organizations to advocate for stricter regulations and policies aimed at preventing water pollution and protecting lake ecosystems.

In conclusion, the research objectives were pursued with the intent of shedding light on the complex relationship between water pollution and its effects on public health, public awareness, and the identification of pollution sources in the context of Bangalore city. The findings of this study have provided valuable insights into these areas, contributing to a deeper understanding of the challenges and opportunities presented by water pollution.

The high level of awareness among participants regarding the most polluted areas in Bangalore underscores the urgency of addressing pollution hotspots and implementing targeted interventions. The recognition of “mismanagement of sewage” as a leading cause of water pollution by a vast majority of respondents emphasizes the critical need for improved wastewater management systems and practices.

Furthermore, the observed variation in participant responses regarding the causes of water pollution, such as the comparatively lower recognition of “flooding,” highlights the importance of continued public education and awareness campaigns. Effective communication and dissemination of accurate information are essential to foster a comprehensive understanding of the multifaceted nature of water pollution and its contributing factors.

The study also underscores the vital role of public awareness in combating waterborne diseases. While diseases like cholera enjoy widespread recognition, efforts should be directed toward enhancing awareness of lesser-known waterborne illnesses. Public health initiatives must focus on bridging the knowledge gap and promoting preventive measures to mitigate the risks associated with waterborne diseases.

In essence, this research has not only illuminated the current state of awareness and perceptions surrounding water pollution and its implications but has also provided valuable guidance for future policies, interventions, and educational campaigns aimed at safeguarding water resources, public health, and the overall well-being of the residents of Bangalore city. By addressing the identified gaps in knowledge and awareness, stakeholders can work collaboratively to create a cleaner, healthier, and more sustainable environment for all.

REFERENCES  

• Chandra, H.S., et al. “Assessment of water pollution in Bangalore using multivariate statistical techniques.” Environmental Monitoring and Assessment, vol. 184, no. 7, 2012, pp. 3891-3903.
• Khan, Aslam. “Water pollution and its impact on the environment: A case study of Bangalore city.” Journal of Environmental Science and Technology, vol. 10, no. 6, 2017, pp. 346-358.
• Krishnamurthy, R.R., and B.S. Dasappa. “Assessment of groundwater quality and its pollution sources in Bangalore, India.” Environmental Monitoring and Assessment, vol. 177, no. 1-4, 2011, pp. 239-262.
• Narayan, Kate. “Water pollution in Bangalore: A case study of Bellandur Lake.” Indian Journal of Environmental Protection, vol. 32, no. 5, 2012, pp. 384-391.
• Prakash, T.N., and K.S. Puttaswamy. “Water quality index of Bangalore lakes for drinking purposes.” Journal of Environmental Science and Engineering, vol. 55, no. 1, 2013, pp. 1-9.
• Raghavan, S.V., et al. “Assessment of groundwater quality in Bangalore: A case study of a peri-urban area.” Environmental Monitoring and Assessment, vol. 153, no. 1-4, 2009, pp. 455-467.
• Rajeev, P., et al. “Evaluation of surface water quality in Bangalore: A case study of Vrishabhavathi River.” International Journal of Applied Environmental Sciences, vol. 10, no. 3, 2015, pp. 1111-1124.
• Ramachandra, T.V., and Uttam Kumar. “Assessment of water quality and pollution status of Varthur Lake, Bangalore.” Journal of Environmental Science, Computer Science, and Engineering & Technology, vol. 2, no. 1, 2013, pp. 32-47.
• Ranganathan, M., and P. Ravichandran. “Groundwater quality in urban areas of Bangalore, India.” International Journal of Environmental Sciences, vol. 3, no. 1, 2012, pp. 91-104.
• Shwetha, H.V., et al. “Assessment of water quality of Bangalore lakes: A case study of Ulsoor Lake.” Journal of Environmental Research and Development, vol. 9, no. 2, 2014, pp. 315-327.
• Singh, Rajesh K., and Neelima R. Kumar. “Groundwater pollution vulnerability assessment using the DRASTIC model in Bangalore city, India.” Journal of Earth System Science, vol. 119, no. 6, 2010, pp. 745-759.
• Sreekantha, et al. “Water quality assessment of lakes in Bangalore, India, using multivariate statistical techniques.” Environmental Earth Sciences, vol. 73, no. 3, 2015, pp. 10125-10140.
• Subramanian, K.A., et al. “Hydrogeochemical characterization and quality assessment of groundwater in Bangalore South taluk, Karnataka, India.” Environmental Earth Sciences, vol. 72, no. 11, 2014, pp. 4725-4743.
• Subramani, T., et al. “Impact of untreated sewage on the water quality of the Cauvery River, Bangalore, India.” Environmental Monitoring and Assessment, vol. 159, no. 1-4, 2009, pp. 9-19.
• Suresh, A., and B. Ravindra. “Assessment of groundwater quality in Bangalore South using GIS.” Environmental Monitoring and Assessment, vol. 186, no. 3, 2014, pp. 1391-1403.

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Literature review, methodology, policy recommendation, acknowledgements, competing interests, data availability statement, inequality and water pollution in india.

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Sulhi Ridzuan; Inequality and water pollution in India. Water Policy 1 August 2021; 23 (4): 985–999. doi: https://doi.org/10.2166/wp.2021.057

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India is notorious for high inequality and high water pollution. There is a growing body of literature that says inequality is harmful to the environment, but it does not receive strong empirical support. We discuss some econometric problems that may have caused mixed findings in the empirical literature and use appropriate tools to overcome the problems. Our empirical results using Indian time-series data show (i) that inequality leads to an increase in water pollution, (ii) that the magnitude of inequality is nearly as large as that of corruption, suggesting that reducing inequality is almost as important as curbing corruption in addressing water pollution challenges in India, and (iii) that increases in water pollution, in turn, widen inequality in India. Our results are robust to various sensitivity checks. We also find no evidence of the environmental Kuznets curve hypothesis for water pollution in India.

We examine the relationship between inequality and water pollution in India and take into account econometric issues in the literature.

We find that inequality leads to an increase in water pollution and the magnitude of inequality is nearly as large as that of corruption.

Increases in water pollution, in turn, widen inequality in India.

In India, rivers are much more than bodies of water. Indian rivers are believed among the majority Hindus to be sacred, can wash away sins, and bring people closer to god. Despite perceived to be pure, the rivers are not free from pollution – they serve as a dumping ground for sewage, solid, and industrial wastes ( Bari, 2018 ). Every day, more than 10.5 million gallons of wastewater flow into rivers and other watercourses in India ( Hirani & Dimble, 2019 ). Water pollution in India has been posing a serious threat to the health of its economy and society. Recent research suggests that in a developing country like India, pollution upstream could cut economic growth in downstream regions by nearly a half percentage point ( Damania et al ., 2019 ). Every year, more than 400,000 Indians die from diarrheal illness due to inadequate sanitation and hygiene ( DeFrancis, 2011 ). It is estimated that the health costs of water pollution in India amounted to about $6.7–8.7 billion per year ( Mani et al ., 2012 ). India has spent billions of dollars on clean-up efforts, yet serious water pollution still persists ( The Economist, 2019a , para. 6). Given the significant impact of water pollution on the economy and society, gaining a better understanding of the underlying causes of water pollution is critical.

Water pollution in India has been attributed to an array of factors. Socioeconomic factors that are usually hypothesized to impact upon water pollution in India include income, population, urbanization, illiteracy, lack of democracy, and corruption ( Karn & Harada, 2001 ; Goldar & Banerjee, 2004 ; Barua & Hubacek, 2009 ; Greenstone & Hanna, 2014 ; Sigman, 2014 ; Damania et al ., 2019 ). This study explores one factor that has not been thoroughly studied for the case of India, namely the impact of inequality 1 .

Our literature review presented in the next section suggests that there may be a link between inequality and water pollution in India. Little attention, however, has been paid to the question of whether these two phenomena are related. There are a few empirical studies that, though they do not explicitly provide evidence for the case of India, could offer valuable insights, but the results of these studies are mixed – with positive, negative, and insignificant relationships between inequality and water quality (see, e.g., Scruggs, 1998 ; Torras & Boyce, 1998 ; Grafton & Knowles, 2004 ; Clement & Meunie, 2010 ; Gassebner et al ., 2011 ; Jun et al ., 2011 ; Kasuga & Takaya, 2017 ).

A possible explanation for the inconsistency in results is that the empirical literature suffers from many limitations. First, some studies ignore the time-series properties of the underlying data (see, e.g., Clement & Meunie, 2010 ; Jun et al ., 2011 ). Our examination of the time-series properties of inequality and water pollution (shown later in this paper) indicates that both variables are nonstationary. Regressions that involved nonstationary variables must be viewed with extreme caution as they are likely spurious ( Granger & Newbold, 1974 ). Even if nonstationary variables are cointegrated (move together), inferences from regressions can be misleading ( Stock & Watson, 2015 , p. 706).

Second, some studies such as Scruggs (1998) , Torras & Boyce (1998) , and Grafton & Knowles (2004) use cross-sectional data. Cross-sectional regressions are well known to suffer from omitted variable bias because it is difficult to control for everything, especially for variables that are hard to measure, such as culture. Although this problem can be addressed by using panel data as is used by some studies, many panel methods assume parameter homogeneity (the effect of inequality on water pollution is assumed to be the same for all countries) 2 . If this assumption does not hold, coefficient estimates will be seriously biased ( Durlauf et al ., 2009 , p. 617).

Third, most studies that use cross-country data ignore the potential cross-section dependence in the data, which can lead to biased statistical inference ( Hoechle, 2007 ). Water pollution is spatially correlated because some rivers are shared by a group of countries; if one country pollutes a river, some other countries may be affected ( Thompson, 2016 ). Fourth, many inequality data are not fully comparable across countries ( Atkinson & Brandolini, 2001 ; Knowles, 2005 ). This raises question marks over the validity of findings from cross-country regressions.

Fifth, inequality data are well known to be subject to measurement error, which can seriously bias coefficient estimates ( Forbes, 2000 ). This issue can be addressed by employing an instrumental variable estimator or a widely used generalized method of moments (GMM) estimator, such as is used in Clement & Meunie (2010) . However, valid instruments are difficult to find ( Wooldridge, 2013 , p. 543). And GMM estimator produces inconsistent estimates if the assumption of parameter homogeneity does not hold ( Durlauf et al ., 2009 , p. 634).

Sixth, inequality data do not evolve much in a short time period ( Deaton, 2013 ). A sample with a small period of inequality, therefore, has limited information (due to little year-to-year variations), making it difficult to precisely estimate the effect of inequality on water pollution ( Torras & Boyce, 1998 ; Wooldridge, 2013 , p. 54). With little information, it should not be surprising that studies with a small sample (e.g., Kasuga & Takaya, 2017 ) find no significant impact of inequality on water pollution.

Seventh, some previous studies do not deal with potential reverse causality or simultaneity ( Scruggs, 1998 ; Torras & Boyce, 1998 ; Grafton & Knowles, 2004 ; Kasuga & Takaya, 2017 ). Not only inequality could have an effect on water pollution but also water pollution could have an effect on inequality (through health). For example, water pollution impairs poor people's health as they are more exposed to such pollution than the rich are ( Ravi Rajan, 2014 ). Poor health subsequently increases absenteeism and reduces productivity at work, reducing the earning capacity of the poor ( Cole & Neumayer, 2006 ). Sickness also lowers the attendance of poor children in school, affecting their educational attainment and thereby future earnings ( Cole & Neumayer, 2006 ). Failure to account for this reverse causation (i.e., water pollution affects inequality) will result in biased estimates. Possible solutions – for example, IV and GMM estimators – have limitations we mentioned above.

The objective of this study is to examine the relationship between inequality and water pollution in India. We have several main results. First, we find that inequality increases water pollution in India. Second, the effect of inequality on water pollution is about as large as the effect of corruption. Third, we also observe that increases in water pollution, in turn, exacerbate inequality in India. It is worth mentioning that no evidence of the environmental Kuznets curve (EKC) hypothesis is found for water pollution in India.

The rest of the article is organized as follows. Section 2 presents a literature review. Sections 3 and 4 describe data and methodology, respectively. Section 5 presents the results. Section 6 concludes, and Section 7 provides policy recommendations.

There is a growing body of theoretical literature that says inequality is harmful to the environment ( Cushing et al ., 2015 ; Islam, 2015 ). Several possible causal pathways have been offered. Inequality is bad for the environment because the rich consume more (e.g., water for a private swimming pool, gardening, and washing cars) and thereby generate more waste and pollution ( Islam, 2015 ; Dorling, 2017 ). This hypothesis could be true in India. For example, from a survey of 1,495 households in Bengaluru by the Ashoka Trust for Research in Ecology and the Environment, it is found that rich households (top ten percentile) use four times more water than average households do; rich households consume 340 L per person per day while average households consume 85 L per person per day ( The Hindu, 2017 , para. 1). According to the survey, gardening and washing cars are among the reasons for the high consumption ( The Hindu, 2017 , para. 3). The inequality-environment theoretical literature also argues that the rich also set the norm for what defines a lifestyle of high status, inducing the rest to work more and consume more ( Berthe & Elie, 2015 ; Cushing et al ., 2015 ; Islam, 2015 ). It is well known that, in India, owning a car is considered a status symbol ( Mohan, 2020 ). Imitating the lifestyle of the rich could result in more cars being bought unnecessarily and more water being used, for both automotive manufacturing and household consumption (i.e., car wash).

The theoretical literature also suggests that inequality erodes trust, cohesion, and cooperation, which undermine collective action to protect environmental resources ( Wisman, 2011 ). This phenomenon can also be seen in India. For example, in Calcutta, interaction and cooperation among environmental NGOs are rare ( Dembowski, 2001 , p. 81). It is perceived that many of them view one another with a suspicion that others have a hidden agenda and are pursuing personal interests (e.g., fame and foreign funds) ( Dembowski, 2001 , p. 2). Moreover, those environmental NGOs find it easier to mobilize people from within their own social class than other classes ( Dembowski, 2001 , p. 82). In 2019, water in Calcutta ranked the second most unsafe after Delhi ( DNA India, 2019 , para. 1).

It is believed that, in the inequality-environment theoretical literature, inequality causes people to think about unemployment, status insecurity, and making the economy work again and shifts people's attention away from environmental issues ( Wilkinson & Pickett, 2010 , p. 263). This may be happening in India. In Calcutta, Dembowski (2001 , p. 82) reported that the environment is not considered a serious issue for communities struggling for daily survival, although such people are among the most exposed and vulnerable to environmental hazards. In another city Kanpur, Do et al . (2018) find that public demand for water quality was low in the past; people were more concerned about the impact water pollution policy would have on the economy as they depended on the highly river-polluting tanning industry for jobs. In 2017, India's leather industry employs an estimated 3 million workers, which mostly come from poor and marginalized groups ( Chitnis, 2017 ).

Summary statistics.

Unit root tests.

Note : All estimates include constant and trend. The Schwarz criterion is used to determine the optimal number of lags in the ADF test. The Newey-West method and the Bartlett kernel are used for the bandwidth in the PP test.

**Significance at the 5% level.

Johansen's cointegration test.

Long-run exclusion tests.

Johansen's cointegration test with small sample correction

Note : The optimal number of lags is chosen based on the Schwarz information criterion.

Table 6 presents estimates of the long-run relationship from the above three models. All models show a significant positive effect of inequality on water pollution. The estimated parameters imply that a 1% increase in inequality leads to, on average, a 1.931–2.958% increase in water pollution in the long run. The income variable in model 2 is not statistically significant. To see the existence of EKC, in unreported analysis, we compare this long-run coefficient with its short-run coefficient, as suggested by Narayan & Narayan (2010) . We observe that the long run (0.655) is smaller than the short run (8.173), so no evidence of EKC. Like the long-run coefficient, the short-run coefficient is not significant, either (available upon request). This study agrees with the findings of other studies ( Barua & Hubacek, 2009 ; Greenstone & Hanna, 2011 ), in which no EKC relationship for water pollution in India.

Estimates of the effect of inequality on water pollution.

**Statistically significant at 5%. t -statistics are in parentheses. All coefficient estimates are converted to elasticities for comparability.

To test the robustness of this result, we re-estimate the long-run relationship using three alternative estimation methods: the dynamic ordinary least squares (OLS) of Stock & Watson (1993) , the fully modified OLS estimator of Phillips & Hansen (1990) , and the canonical cointegrating regression of Park (1992) . Table 7 presents estimation results using these estimators. The ML estimation of Johansen (model 1; Table 6 ) is reported for comparison. We continue to find a positive and statistically significant effect of inequality on water pollution, and the estimates from the three methods are generally rather close to that of ML. We conclude that our results are robust to different estimators.

Estimates of the long-run effect of inequality on water pollution.

ML, maximum likelihood; DOLS, dynamic OLS; FMOLS, fully modified OLS; CCR, canonical cointegrating regression. The DOLS regression is estimated with one lead and one lag.

Next, we examine the sensitivity of our results to the inclusion of other explanatory variables. To this end, we use the dynamic OLS estimator as it has important econometric advantages over other estimators. First, it performs well in small samples as ours. Moreover, one variable that we are going to use has short time-series observations, reducing our already small sample. Second, it allows I (0) independent variables (such as corruption) in the regression. Third, it is robust to endogenous explanatory variables – an issue that may arise from measurement error of inequality and reverse causation between inequality and water pollution.

Table 8 reports our results. In column 1, corruption is added as an explanatory variable. The inclusion is motivated by the fact that corruption is correlated with inequality ( Gupta et al ., 2002 ), and as a result, both variables could proxy one another. There is a possibility that what we are estimating so far is the impact of corruption rather than that of inequality. The corruption data are obtained from the International Country Risk Guide. The data have been rescaled so that greater values correspond to more corruption. Column 2 adds democracy as it also tends to be correlated with inequality ( Eriksson & Persson, 2003 ) and has been found important in explaining variation in water pollution ( Lin & Liscow, 2013 ). The Polity2 Index, which is from the Polity IV dataset, is used to measure democracy. In column 3, we add literacy, which relates to inequality ( Torras & Boyce, 1998 ) and has been found significant in Barua & Hubacek (2009) . Literacy data for India are available from WDI but have many data gaps. For that reason, we use secondary school enrollment rate (which has far fewer missing data) from the same source as a proxy for literacy 11 . In column 4, all additional explanatory variables are entered in the regression simultaneously. Overall, the estimated effect of inequality is not very sensitive to which specific control variables are entered in the regression. In all cases, the coefficient of inequality remains statistically significant. The democracy and literacy variables are not significant. Corruption is statistically significant at 5% with expected signs in column 1 12 . In column 4, corruption is not significant, which is understandable, since we lost more degrees of freedom with more variables included. Since only one variable is significant in column 4, results in column 1 are preferred. Interestingly, we observe that the magnitude of inequality (1.498%) is nearly as large as that of corruption (1.591%), suggesting the importance of inequality in explaining water pollution 13 . It is important to bear in mind that this finding is based on small sample size. However, the estimated effect of corruption is within the range of a previous study – −0.681 to −1.682% (see Table 2 in Sigman (2014) ) 14 – and that gives us some confidence about the reliability of our finding. Because inequality and corruption have different distributions, we also compute standardized coefficients for both variables. For column 1, we find that a one-standard deviation increase in inequality increases water pollution by 0.544 standard deviation; a one-standard deviation increase in corruption increases water pollution by 0.565 standard deviation. Again, the magnitude of inequality is nearly as large as that of corruption, meaning that inequality as almost important as corruption in determining water pollution.

DOLS estimates with corruption, democracy, and literacy.

t -statistics in parenthesis. **Statistically significant at 5%. Given small sample, only one lead and one lag of the regressors are used in the estimation. All coefficient estimates are converted to elasticities for comparability.

Our results so far show that inequality increases water pollution. An increase in water pollution may also lead to an increase in inequality because bottom class people are more exposed to water pollution (and thus more vulnerable to waterborne diseases) 15 . Sickness reduces productivity and increases absenteeism at work and in school. This consequently reduces the earning capacity of bottom class adults and the potential income of their children, perpetuating poverty, and reproducing inequality. Therefore, the direction of causality may run in both directions – not only from inequality to water pollution but also from water pollution to inequality. To test for long-run causality, this paper performs a test of weak exogeneity (a test of zero restrictions in the α matrix). A rejection of the null of weak exogeneity indicates long-run (Granger) causality ( Hall & Milne, 1994 ). In Table 9 , the null hypothesis of weak exogeneity of water pollution and the null hypothesis of weak exogeneity of inequality are rejected at the 5% level; the long-run Granger causality runs in both directions, from inequality to water pollution and water pollution to inequality. These results even hold when income is included in our model (model 2) and when Gini is used instead of Theil (model 3). This finding justifies our use of the Johansen approach that views all variables to be endogenous.

Tests for long-run causality.

**Rejection of the null hypothesis of weak exogeneity at the 5% level.

The long-run causality tests indicate the direction of the relationship (i.e., water pollution to inequality), but do not determine the sign of that relationship. Does an increase in water pollution lead to an increase in inequality? To see this, we compute an impulse-response function from our estimated VECM. Figure 1 plots the response of inequality to a shock in water pollution for a period of 10 years. As a robustness check, impulse-response function using Gini is also reported. In both panels, we find a shock to water pollution does have a significant permanent positive effect on inequality 16 . For Theil, the full impact is reached after 2 years, and 5 years for Gini. Furthermore, the bootstrapped confidence interval in both panels lies almost entirely in the positive domain. We conclude that there is a positive effect of water pollution on inequality.

Impulse responses of Theil (left) and Gini (right) to a one-standard deviation shocks in water pollution. Bootstrap 95% confidence bounds are based on 2000 replications.

Future research that examines the effect of inequality on environmental outcomes may need to tackle endogeneity bias that arises from reverse causality going from more pollution to higher inequality. The reason is that reverse causality going from more pollution to higher inequality would bias the estimated effect of inequality on pollution upward. To put it another way, if pollution has a positive effect on inequality, then the effect of inequality on pollution tends to be positive.

Although India is notorious for its water quality and inequality, little attention has been paid to the question of whether these two phenomena are related. Previous literature that examined the relationship between water quality and inequality did not explicitly analyze for the case of India. Although lessons can still be learned from the empirical literature, it suffered from many econometric issues, which were rectified in the present study.

We found that inequality has a robust positive long-run effect on water pollution in India. One reason why inequality increases water pollution in India could be that (in no particular order) the rich consume more water than is necessary and thus produce more pollution. Another reason could be that the wealthy set the norm for what defines a lifestyle of high status, forcing people to spend more and consume more (and more production in the economy as a result). Another plausible reason is that inequality always erodes trust, making cooperation to protect common resources become difficult. The next reason is that inequality causes people to think more about economic issues and shifts people's attention away from environmental problems, thereby reducing demand for better environment. The reader should bear in mind that these are just possible causal pathways, and more research is needed to develop a deeper understanding of the interplay between inequality and water pollution in India.

We showed that the magnitude of inequality on water pollution is almost as large as that of corruption, a factor that is often seen as an important cause of water pollution ( Rowlatt, 2016 ). This suggests that reducing inequality is almost as important as curbing corruption in addressing water challenges in India. Given that an increase in water pollution leads to an increase in inequality, future studies may need to consider the possible endogeneity of inequality when assessing the impact of inequality on water pollution or other environmental outcomes.

From a policy point of view, reducing inequality is not only important for fairness but also for the environment. In 2016, India discontinued the wealth tax due to high collection cost, and in 2019, the government announced a corporate tax cut to spur the economy. This study recommends the government reconsider their decisions since inequality may be worsened as a result ( Jones, 2015 ; Nallareddy et al ., 2018 ) and can thereby have an unintended effect on its water. Although reducing tax collection may spur more economic growth, which according to the EKC hypothesis, could later be good for the environment (by increasing public demand for environmental protection, for example), we did not find the EKC for water pollution in India.

It is estimated that the corporate tax revenue loss due to the recent tax cut would be about $20 billion (around 0.7% of GDP) ( The Economist, 2019b , para. 3). India also suffers a significant loss due to tax avoidance. For example, in 2013, India's corporate tax revenue loss due to tax avoidance is estimated to be between $41.17 billion and $47.53 billion, between 2.34 and 2.70% of GDP ( Cobham & Janský, 2018 ). It is well known that, in reducing water pollution, the water sector in the country faces a huge financial challenge to fund investments in capital-intensive modern wastewater collection and treatment ( Narain, 2016 ). If India could increase the amount of tax revenue, it could be used to finance the necessary investments. The tax revenue could also be used to fund vital public services that could help reduce inequality such as education and healthcare for people from all walks of life in India. The government can also consider consumption-based tax to reduce consumption among higher consumers, in addition to increasing tax collection ( Mohan, 2019 ).

The author wishes to thank three anonymous referees and Abdul Hafizh Mohd Azam for their comments and suggestions. All remaining errors remain the sole responsibility of the author.

None declared under financial, general, and institutional competing interests.

No funds, grants, or other support were received.

Data cannot be made publicly available; readers should contact the corresponding author for details.

Much empirical work uses cross-country data, which introduces some econometric problems we present shortly.

According to Cushing et al. (2015) , the relationship between inequality and the environment varies across countries depending on a country's average income, development, and democracy levels.

Super consistent estimates converge to the true parameter values at a faster rate than consistent estimates do, as sample size increases.

Cointegration tests can also serve as a misspecification test ( Stern, 2011 ). A lack of cointegration indicates that additional nonstationary variables may be needed for the model ( Stern, 2011 ). The reason is that if relevant nonstationary variables are omitted, they will be part of the error term, making the error term nonstationary ( Everaert, 2011 ).

The sample period is dictated by the availability of data.

‘Whether the sample is ‘small’ or ‘big’ is not exclusively a function of the number of observations available in the sample, but also of the amount of information in the data. When the data are very informative about a hypothetical long-run relation, … we might have good test properties even if the sample period is relatively short’ ( Juselius, 2006 , p. 141).

Unpolluted rivers have a BOD below 2 mg/L; moderately polluted rivers have a BOD between 2 and 8 mg/L; severely polluted rivers have a BOD over 8 mg/L ( Desbureaux et al. , 2019 ).

With data transformation, a relationship between variables may be found even though they are not correlated ( Gujarati & Porter, 2009 , p. 395).

Interested readers are referred to Schmith et al . (2012) for a detailed explanation and an example of application of this method.

Although a bivariate model is unusual in standard regression analyses, it is not the case in cointegration studies (see, e.g., Schmith et al. 2012 ; Herzer 2020 ). Cointegration property is invariant to increases in the information set ( Juselius, 2006 , p. 349). If cointegration is found within a set of variables, the same cointegration relation will still be found if additional variables are added ( Juselius, 2006 , p. 349).

Data for missing years are interpolated.

Note that although inequality has a relatively larger t -statistic than corruption does, such statistics only indicate statistical significance, not economic or practical significance of variables ( Wooldridge, 2013 , p. 135).

Corruption elasticities in Sigman (2014) are computed by multiplying its estimated coefficients of corruption with its sample mean of corruption.

Access to clean water in India is correlated with a person's social class ( Zargar, 2018 ).

The effects of shocks can be either transitory or permanent ( Gonzalo & Ng, 2001 ).

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Water crisis: a case study of Jabalpur

Jabalpur's shrinking lakes needs sincere planning and community participation

By P K Shrivastava

Published: thursday 31 may 2001.

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Water pollution examination through quality analysis of different rivers: a case study in India

• Published: 21 August 2021
• Volume 24 , pages 7471–7492, ( 2022 )

Cite this article

• Rohit Sharma   ORCID: orcid.org/0000-0001-9438-3281 1 ,
• Raghvendra Kumar 2 ,
• Devendra Kumar Sharma 1 ,
• Manash Sarkar 3 ,
• Brojo Kishore Mishra 2 ,
• Vikram Puri 4 ,
• Ishaani Priyadarshini 5 ,
• Pham Huy Thong 6 ,
• Phuong Thao Thi Ngo 7 &
• Viet-Ha Nhu 7  

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Restoration of water quality at rivers is a big problem for water quality managers. This paper analyzes water quality parameters across five years from 2012 to 2016 in a case study of different Indian rivers. Recently, Indian rivers have experienced massive contamination and water quality depletion due to the entry of wastewater from different regions of India. The quality of Indian rivers has not yet reached the mark, after many efforts made by the Government of India. For this report, three major Indian rivers (Beas, Sutlej and Ganga) were considered for the water quality calculation. Temperature, dissolved oxygen (D.O), pH, biochemical oxygen demand (B.O.D) and fecal Coliform are the considered criteria for measuring the water quality of the mentioned rivers. Results from the study highlight the water quality of Indian rivers and the current pollution pattern for the river Ganga in 2019, which was not sufficiently discussed before. The level of degradation in water quality of Indian rivers is stated through this study.

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Acknowledgements

We sincerely acknowledge the Central Pollution Control Board (CPCB) India, for providing the data of Beas, Sutlej and Ganga Rivers for the measurement of water quality.

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Department of Electronics and Communication Engineering, Faculty of Engineering and Technology, Delhi- NCR Campus, NCR Campus, SRM Institute of Science and Technology, Delhi-Meerut Road, Modinagar, Ghaziabad, UP, India

Rohit Sharma & Devendra Kumar Sharma

Department of Computer Science and Engineering, GIET University, Gunupur, 765022, Odisha, India

Raghvendra Kumar & Brojo Kishore Mishra

Atria Institute of Technology, Bangalore, India

Manash Sarkar

Center of Visualization and Simulation, Duy Tan University, Duy Tan, Vietnam

Vikram Puri

University of Delaware, Newark, DE, USA

Ishaani Priyadarshini

VNU Information Technology Institute, Vietnam National University, Hanoi, Vietnam

Pham Huy Thong

Department of Geological-Geotechnical Engineering, Hanoi University of Mining and Geology, Hanoi, Viet Nam

Phuong Thao Thi Ngo & Viet-Ha Nhu

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Sharma, R., Kumar, R., Sharma, D.K. et al. Water pollution examination through quality analysis of different rivers: a case study in India. Environ Dev Sustain 24 , 7471–7492 (2022). https://doi.org/10.1007/s10668-021-01777-3

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Received : 12 February 2020

Accepted : 17 August 2021

Published : 21 August 2021

Issue Date : June 2022

DOI : https://doi.org/10.1007/s10668-021-01777-3

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8 Water Pollution Control

• Published: August 2022
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This chapter addresses water pollution control in India. The Indian legal system provides four major sources of law for addressing water pollution problems. These include (1) a comprehensive scheme of administrative regulation through the permit system of the Water (Prevention and Control of Pollution) Act of 1974; (2) provisions of the Environment (Protection) Act of 1986 relating to water quality; (3) public nuisance actions against polluters, including municipalities charged with controlling water pollution; and (4) the common law right of riparian owners to unpolluted water. In addition, the Union Government has developed action plans for rejuvenating the Ganga and restoring the quality of her waters. The Supreme Court of India, the High Courts, and the National Green Tribunal have added to the force of these laws by hearing petitions that seek implementation of measures to prevent water pollution.

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