River pollution and social inequalities in Dhaka, Bangladesh

Abstract

River pollution through the discharge of untreated sewage and industrial effluent is a perverse outcome of rapid urbanisation and economic growth across Asia. To understand the socio-spatial and
seasonal inequalities in pollution risks, we designed a direct observation method to record people’s daily river use activities across dry and wet seasons, complemented by monthly monitoring of river
water quality, heavy metal and biotoxicity assessment a large-scale household survey along a 25km stretch of the Turag River and Tongi Khal in Dhaka, Bangladesh. We found very high ammonia and almost zero dissolved oxygen during the low flowseason, further exacerbated by heavy metals from the annual Bishwa Ijtema gathering and downstream industrial zones. Pollution exposure through
domestic activities prevailed throughout the year, particularly for women and girls along low-income settlements lacking adequate water and sanitation facilities. Swimming peaked among men and
children in the monsoon, risking exposure to pathogen pollution. Recognising the social inequalities in risk can support the sequencing of policy action involving short-term adaptation (improved
services, education, advocacy) and long-term mitigation (effluent treatment, regulation and enforcement) responses.

Full text

Environ. Res. Commun. 3(2021)095003 https://doi.org/10.1088/2515-7620/ac2458
PAPER
River pollution and social inequalities in Dhaka, Bangladesh
Sonia Ferdous Hoque
1
, Rebecca Peters
1
, Paul Whitehead
1
, Robert Hope
2
and Mohammed Abed Hossain
3
1
School of Geography and the Environment, University of Oxford, United Kingdom
2
School of Geography and the Environment and Smith School of Enterprise and the Environment, University of Oxford, United Kingdom
3
Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Bangladesh
E-mail: sonia.hoque@ouce.ac.uk
Keywords: Bangladesh, sustainable development goals, urban rivers, inequalities, pollution exposure
Supplementary material for this article is available online
Abstract
River pollution through the discharge of untreated sewage and industrial effluent is a perverse
outcome of rapid urbanisation and economic growth across Asia. To understand the socio-spatial and
seasonal inequalities in pollution risks, we designed a direct observation method to record people’s
daily river use activities across dry and wet seasons, complemented by monthly monitoring of river
water quality, heavy metal and biotoxicity assessment a large-scale household survey along a 25km
stretch of the Turag River and Tongi Khal in Dhaka, Bangladesh. We found very high ammonia and
almost zero dissolved oxygen during the low flow season, further exacerbated by heavy metals from
the annual Bishwa Ijtema gathering and downstream industrial zones. Pollution exposure through
domestic activities prevailed throughout the year, particularly for women and girls along low-income
settlements lacking adequate water and sanitation facilities. Swimming peaked among men and
children in the monsoon, risking exposure to pathogen pollution. Recognising the social inequalities
in risk can support the sequencing of policy action involving short-term adaptation (improved
services, education, advocacy)and long-term mitigation (effluent treatment, regulation and
enforcement)responses.
1. Introduction
River pollution through discharge of untreated wastewater has plagued developing economies since the dawn of
the industrial revolution (Parker 1932, Hostetter 2006). While high income countries in Europe and North
America today treat 70% of their wastewater before discharge, urban river pollution remains a major challenge
in low- and lower-middle income countries in Asia, where only 8% and 28% of the wastewater is treated
(UNEP 2016, WWDR 2017, Kookana et al 2020). Weak enforcement of environmental regulations on polluting
industries, coupled with the inability of municipalities to extend basic housing, water and sanitation services to
growing urban populations, have led to severe degradation of water resources—stretching from the Citarum
(West Java province, Indonesia)(Fulazzaky 2010)and Dong Nai rivers (Ho Chi Minh, Vietnam)(Nguyen et al
2019)in Southeast Asia to the Buriganga (Dhaka, Bangladesh)(Kamal et al 1999, Whitehead et al 2019)and the
Yamuna rivers (New Delhi, India)(Mandal et al 2010)in South Asia. The global target to minimise the disposal
of hazardous substances and maintain healthy river systems, as articulated in the Sustainable Development Goal
(SDG)target 6.3, require interventions that manage the political, economic and social trade-offs in reversing
environmental degradation, supporting economic growth and reducing population exposure to pollution (UN
General Assembly 2015).
While there is an extensive body of literature on the nature and distribution of pollutants across urban river
systems, the social inequalities in exposures have received little attention. Geospatial analysis at city or regional
scale, through superposition of socio-demographic indicators on pollution parameters, often found the location
of polluting factories and waste facilities to be associated with a higher proportion of socially disadvantaged
populations, such as scheduled caste and tribes (Chakraborty and Basu 2019, Morandeira et al 2019). However,
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these analyses reveal little about the daily risks faced by riverine communities who come into contact with toxic
pollutants through domestic, productive, and leisure activities. In addition to direct health impacts such as
gastro-enteritis and dermal diseases from contact or immersion in polluted water (Prüss 1998, Turbow et al
2003), and consumption of heavy metals accumulated in fish and crops (Wang et al 2005, Khan et al 2008), there
are wider impacts on wellbeing arising from poor visual amenities, unpleasant odours, limited recreational
opportunities and stigmatisation of communities (Damery et al 2008). Unlike the disease burden from unsafe
drinking water—estimated to cause 1.3 million deaths globally in 2015 (Landrigan et al 2018), the risks of
ambient water pollution are difficult to assess due to the multiple pathways of exposure and the undefined spatial
and temporal scales of observable impacts.
Here we present the first longitudinal analysis of the socio-spatial and seasonal dynamics of exposure to
urban river pollution, by systematically documenting who interacts with the river and for what purpose, and
how these activity patterns vary with the state water and sanitation facilities, river water quality, time of the year
and sociodemographic characteristics. We designed and implemented a river use observation study, generating
7900 unique observations over 33 days across two seasons along the Turag River and Tongi Khal in Dhaka—one
of the world’s most densely populated megacities. This is supported by 12 months of river water quality data that
illustrate the extent of pollution to which people are exposed, and surveys of over 1800 households along the
riverbanks. While evaluating the health impacts from pollution exposure is outside the scope of this study, we
identify individuals and groups at greatest risk with a view to prioritise spatial and temporal interventions for the
urban poor often marginalised by trade-offs between economic growth, river health and poverty reduction.
2. Background
2.1. Surface water pollution in Dhaka
Dhaka is one of the fastest growing urban agglomerations in the developing world, home to over 17 million
people spread over an area of 307 km
2
. The city is surrounded by six interconnected river systems—the
Buriganga and Dhaleshwari in the southwest, Turag and Tongi Khal in the north, and Balu and Sitalakhya in the
east—which support trade, transport, and stormwater drainage. However, in the past three decades, the water
quality in the rivers surrounding Dhaka has been severely degraded due to indiscriminate discharge of untreated
sewage, solid waste, and industrial effluent. Dhaka’s sewer system covers only 20% of the city, and feeds into one
sewage treatment plant operating at one-third of its capacity (DWASA 2019). In addition to the organic and
pathogen pollution load from the 1.2 million m
3
of untreated sewage, the rivers receive about 60,000m
3
of
industrial effluent every day from nine major industrial clusters. There are an estimated 500–700 wet processing
and dyeing textile factories releasing a range of chemicals including salts, dyes and bleaches, and 155 tanneries
discharging heavy metals, including chromium (Sagris and Abbott 2015). The biological oxygen demand (BOD)
and chemical oxygen demand (COD)of the textile wastewater are estimated to be 480 mg l
−1
and 696 mg l
−1
respectively, compared to a BOD of 2000 mg l
−1
and COD of 4500mg l
−1
for tannery effluent (Sagris and
Abbott 2015).
The textile and leather industries are critical to Bangladesh’s economic growth, with an average annual gross
domestic product (GDP)growth rate of 6.5% in the fiscal years (FY)from 2009 to 2018 (World Bank 2019).Asa
subset of the textiles industry, ready-made garments accounted for 83.5% of the country’s export revenues and
11.2% of the GDP in FY2017-18 and employs about 4 million people. The leather industry, which contributed to
3.5% of annual exports and 0.35% of GDP in FY2017-18, is also of strategic importance as the country is seeking
to diversify its manufacturing export base to sustain the growth trajectory (Hong 2018). While environmental
regulations, as articulated in the Environmental Conservation Act (1995), require these ‘red category’factories
to treat their wastewater, not all factories comply and many do not run their effluent treatment plants due to gaps
in financing for infrastructure and technology upgrades, or cost savings associated with the treatment chemicals
and electricity needed to run the system (Haque 2017, Restiani 2017). In December 2017, following decades of
domestic and international pressure to curb pollution, the tanneries in Hazaribagh (along the Buriganga River)
were relocated to a new 200-acre industrial park in Savar along the Dhaleshwari River. The park is equipped with
a centralised effluent treatment plant (CETP)with a daily capacity of 25,000m
3
compared to 40,000 m
3
of
wastewater being generated. As of August 2021, it is estimated that the tanneries dumped more than
16.4 million m
3
of untreated wastewater over the past three years, causing a parliamentary standing committee
to order temporary closure of the industrial park (Hasan 2021).
Recognising the severity of pollution, four of the rivers surrounding Dhaka—Buriganaga, Sitalakhya, Balu
and Turag—have been declared as ecologically critical areas in 2009 by the Department of Environment (DoE)
(The Daily Star 2009), with the Planning Commission labelling them as ‘unsuitable for any human use’(General
Economics Division 2015, p.423). In 2016, DoE reported that the mean dissolved oxygen (DO)in dry and wet
seasons ranged from 0. 17–2.98 mg l
−1
for Buriganga, 4.14–4.25 mg l
−1
for Sitalakhya, 0.4–4.51 mg l
−1
for
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Environ. Res. Commun. 3(2021)095003 S F Hoque et al

Turag, and 2.75–6.05 mg l
−1
for Dhaleshwari, compared to the environmental standard of >5mg l
−1
for
fisheries, irrigation and recreational uses (DoE 2017). Heavy metals contamination in surface water and their
accumulation in vegetables (Rahman et al 2017)and fisheries (Ahmed et al 2016, Rashid et al 2017)in areas
surrounding industrial clusters have been documented. Hasan et al (2019)’s analysis of hair and nail samples
reflected significantly higher chromium accumulation in leather factory workers and residents in Hazaribagh
compared to non-exposed people in a control village. The pollution also has significant implications for the
city’s growing water demand, 87% of which is currently sourced from groundwater as the extreme
contamination makes surface water treatment economically and technologically unfeasible (Arfanuzzaman and
Rahman 2017).
2.2. Water and sanitation challenges in low-income settlements
The industrial clusters in Dhaka are often interspersed with low-income residential areas or slums that
accommodate workers and their families. The underdeveloped water and sanitation facilities in slums, home to
35% of the urban dwellers in Bangladesh, counteracts the ‘urban health advantage’often generated from better
employment and health care services compared to rural areas (Vlahov et al 2005). The Bangladesh Urban
Informal Settlements Survey 2016 (Yanez-Pagans 2016), which included a representative sample of 588
households across small, medium and large slums in Dhaka, showed that 68% of the households accessed piped
water through a shared connection within the slum compound, with the poorest households sharing a
waterpoint with 43 other households on average compared to 23 sharers among the richest households (Haque
et al 2020). Landlords were the main providers of water infrastructure in small and medium slums on privately-
owned land. In large slums on government owned land, about 27% and 21% of the waterpoints were installed by
the Dhaka Water Supply and Sewerage Authority (DWASA)and NGOs, respectively. More than half of the
households also reported being exposed to flooding in the past year, which disrupted access to a functional water
source for 10 days on average.
In terms of sanitation, only 8% of the slum households had access to a flush toilet connected to a septic tank,
while 78% used improved pit latrines and the remaining 10% depended on hanging latrines (Haque et al 2020).
A toilet facility was shared among 16 households on average. Among those with improved sanitation facilities,
about 68% reported never emptying their pits or septic tanks, while 20% mentioned disposing the faecal sludge
directly to drains or nearby waterbodies. Amin et al (2020)’s study in two low-income neighborhoods in Dhaka
showed extensive V.cholerae, NoV-GII, Giardia, and Shigella/EIEC contamination in effluent from on-site
sanitation systems, to which children and adults may be exposed in their immediate residential environment. A
larger study of environment faecal contamination across 10 neighbourhoods found significantly higher E. coli
concentrations in non-municipal drinking water, bathing water, surface water, and soil samples in low-income
neighborhoods compared to high-income neighborhoods, indicating poor drainage systems, improper child
faeces disposal, and poor faecal sludge management in low-income neighbourhoods as the potential
contamination routes (Amin et al 2019).
Consequently, many of the immediate environmental burdens of pollution are borne by these low-income
residents. Longitudinal observations from hospital visits between 1993 and 2012 showed that children under five
living in densely populated slums were significantly more prone to diarrhoeal diseases from Vibrio cholerae and
severe dehydration compared to those in non-slum settings (Ferdous et al 2014). In Kamrangirchar, the largest
slum in Dhaka and home to about 600,000 people who generated income from the tanneries in adjacent
Hazaribagh area for wages, occupational and environmental exposure to toxic heavy metals, coupled with low
living standards and poor health seeking behaviour, contributed to high disease burden, including contact
dermatitis, work-related asthma, peptic disease, low back pain, malaise and injuries (Muralidhar et al 2017,
van Puijenbroek et al 2019).
3. Materials and methods
Our study area covers a 25 km stretch along the Turag River and Tongi Khal flowing along the borders of Dhaka
and Gazipur districts. We divided our study area into four zones, covering up to 1km on both sides of the
riverbank (figure 1). Zone-1 stretches about 6km along the upper reaches of the Turag River and includes the
Konabari-Kashimpur industrial cluster of knitting and dyeing factories, brick kilns and the Konabari settlement
built on private land along the river. Zone-2 covers six peri-urban settlement clusters along an 8km river stretch,
while Zone-3 includes a 6km stretch of the Tongi Khal passing through the Tongi industrial cluster with three
densely populated slums built illegally on government land. Since 1967, the Bishwa Ijtema, an annual gathering
of 3 million Muslims over three days in January, has been held along the Tongi Khal in Zone-3. Zone-4, the final
5km stretch of the Tongi Khal, includes part of the Tongi industrial cluster on the northern bank of the river,
with is a relatively quieter neighbourhood and a boat terminal on the southern bank.
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Environ. Res. Commun. 3(2021)095003 S F Hoque et al

We designed an interdisciplinary research approach, combining water quality monitoring, household
surveys and direct observation of river use behaviour to collect empirical evidence on the state of water
pollution, socio-economic profiles and water and sanitation challenges in riverbank settlements, and spatial and
seasonal variations in people’s interactions with the river water (table 1). Ethical approval for the surveys and
observations was granted from Oxford University’s Central University Research Ethics Committee (SOGE 18A-
6, November 2017).
3.1. Water quality analysis
We collected water samples from the Turag River and Tongi Khal as part of two sub-studies: (1)monthly
monitoring of 21 physiochemical parameters at 13 sampling points along the river from February 2018 to
January 2019 (figure 1);(2)analysis of 18 heavy metals and biotoxicity at 22 sampling points in December 2017
and January 2018 (figure 3). Samples were collected from a boat at 2m depth, followed by field analysis of
temperature, pH, dissolved oxygen, oxidation reduction potential, electrical conductivity, and total dissolved
solids using HACH HQ40d multiparameter device and turbidity with VELP Scientifica TB-1 portable
Turbidimeter.
Laboratory analysis of colour, alkalinity, dissolved organic carbon, ammoniacal nitrogen, nitrate,
phosphate, iron (ferrous), chloride, sulphate, and sulphide ions, and pathogens (total coliforms and E. coli)were
conducted at Bangladesh University of Engineering and Technology (BUET). Concentrations of heavy metals
Figure 1. Map of Turag River and Tongi Khal showing locations of households surveyed, river use observation points and water
quality sampling points, clustered into four zones.
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Environ. Res. Commun. 3(2021)095003 S F Hoque et al

Table 1. Outline of research methods and sampling across four study zones along Turag River and Tongi Khal.
Method Total Zone-1 Zone-2 Zone-3 Zone-4
Water quality
analysis
Monthly monitoring of physiochemical parameters
(Feb-18 to Jan-19)
13 sampling points 4 4 3 2
Heavy metal and biotoxicity assessment (Dec-17 and
Jan-18)
22 sampling points 8 7 4 3
Household survey (Dec-17)1826 446 730 510 140
Direct observation of river use behaviour (Feb-19 and Aug/Sep-19)10 observation points grouped into
six sites
2 points grouped as 1 site
(Konabari)
None 7 points grouped as 4
sites
1 point (Mausaid)
(2 in Ijtema,
2 in Tongi slum,
1 in Abdullahpur, and 2 in Railway
Bridge)
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Environ. Res. Commun. 3(2021)095003 S F Hoque et al

were analysed at the Department of Earth Sciences, Oxford University through Inductively Coupled Plasma
Mass Spectrometry (ICP-MS)using a PerkinElmer NexION 350D ICP-MS. The heavy metal data was previously
used for a separate study by Oxford Molecular Biosensors, which developed bacterially derived sensors to detect
the bioavailability of specific chemicals and their overall cell damage toxicity (refer to Rampley et al (2020)for
further details). Speciation analysis of few samples during the Ijtema preparatory phase in January 2018 were
done using Visual Minteq ver. 3.1 (May 2020 Edition).
3.2. Household survey
We conducted a household survey in December 2017, in collaboration with the University of Dhaka, to collect
baseline data on socio-economic and demographic profiles, indicators of multidimensional poverty, the state of
water and sanitation facilities, itemised household expenditures and general development concerns. The survey
was conducted in Bangla by 15 trained local enumerators using a semi-structured questionnaire on ONA, a
mobile data collection platform (https://ona.io/). We covered all settlements within 1km buffer zone along the
river, using a random walk method to select every 10th household within each settlement. If no consenting adult
was present at the time of visit, the next household was chosen instead. A total of 1826 households were
surveyed, of which 446 households were in Zone-1, 730 in Zone-2, 510 in Zone-3, and 140 in Zone-4. Data
analysis involved generation of zone-wise descriptive statistics and calculation of a multidimensional wealth
index through principal component analysis (PCA)of 11 variables on housing materials, education, and asset
ownership (see table B1 in appendix (available online at stacks.iop.org/ERC/3/095003/mmedia)). A k-means
cluster analysis was then applied to the factor scores of the first principal component (PC
1
)to disaggregate the
households into four wealth classes.
3.3. Direct observation of river use
We designed and implemented a ‘structured direct observation’study to monitor the gender- and age-
disaggregated daily river water use practices in relation to the spatial and temporal variations in water quality
risks. Direct observation is an established method in social science research whereby the researcher uses a pre-
designed questionnaire to collect standardised quantitative information on the research subjects in their usual
environment without any alterations. Early examples of direct observation can be found in the medical
anthropology literature, where researchers observed the patterns of human contact with water bodies to evaluate
the pathways of schistosomiasis transmission (Dalton 1976, Dalton and Pole 1978, Slootweg et al 1993)with
more recent applications is monitoring handwashing behaviour in rural South Asia (Halder et al 2010, Ram et al
2010).
We conducted our study in two phases. The first phase was carried out over an 18-day period in the dry
season (9–26 Feb 2019)which coincided with the Bishwa Ijtema held in two groups of three consecutive days.
The second phase was conducted for a 15-day period in the wet season (20 Aug–3 Sept 2019). We selected ten
observation points, two of which were in Zone-1, seven in Zone-3, and one in Zone-4. The site selection
involved multiple scoping visits to the household survey areas to identify spots with observable river use
activities, as well as ensuring spatial distribution, diversity of river interactions, accessibility and security for field
team, and alignment with river water quality monitoring points. Zone-2 was excluded as we did not find any
interactions with the river during our scoping visits, as the short river branch flowing through the bottom part of
Zone-2 remains dry for part of the year. During analysis, as shown in figure 1, we merged results from the ten
observation points into six sites in three zones, namely, Konabari (Zone-1), Ijtema field, Tongi slum,
Abdullahpur and Railway Bridge (Zone-2)and Mausaid (Zone-3).
Each observation day comprised three 3-hour slots: 7–10 am (morning); 10.30–1.30 pm (midday); and
2.30–5.30 pm (afternoon)during which enumerators recorded their observations in an electronic form in a
tablet, whereby an ‘observation’is defined as any activity conducted by an individual or group visible within the
enumerator’sfield of view (refer to appendix C for detailed observation schedule). Thus, each slot comprised
several observations, with each observation including one or more activities. Over the 33 study days, we recorded
about 7900 observations for 852 slots. River users were visually categorised as children and adolescents (<16
years of age)and adults, as male and female, and also as groups and individuals. Differentiation of age was based
on enumerators’judgment; some adolescents and young adults may have been misclassified. Activities were
listed as drinking, food washing, water collection, dish washing, laundry, washing oneself, bathing, using
hanging latrine, open defecation, urination, fishing, swimming, boating and other. These activities were listed as
multiple-choice questions, as multiple tasks were often conducted by different individuals in a group.
Enumerators were given clear guidelines for certain activities; for example, if fishing was done on a boat, the
activity was recorded as fishing and not boating. Enumerators also took a photo for each observation, following
approved ethical guidelines, which were inspected by the lead author to resolve issues in data entry.
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Environ. Res. Commun. 3(2021)095003 S F Hoque et al

4. Results
4.1. Spatial and seasonal variations in river water quality
Monthly analysis of water quality along the Turag River and Tongi Khal shows extreme spatial and temporal
variation in physiochemical parameters and heavy metal concentrations, with Zone-3 and Zone-4 exhibiting the
worst conditions (figure 2). During the dry season, DO levels are so low that the waters and sediments may be
presumed to be anoxic, with some metals from bound sediments and gases such as methane, ammonia, and
hydrogen sulphide being released. Organic pollution, as indicated by the total organic carbon (TOC), is highest
in January owing to the dumping of faecal and food waste in the Tongi Khal during Ijtema. TOC reduces as
monsoon approaches, albeit a spike in May from dredging activity undertaken during the sampling period.
Increase in temperature and DO, coupled with addition of different genre of coliform bacteria from the
monsoon runoff, also reduces the relative proportion of faecal coliform (E. coli) to total coliform. Likewise, the
concentrations of ammoniacal-nitrogen, nitrates, and phosphate decreases to below national standards in
monsoon, except for the spike in nitrates in June from rainwater accumulating on the surface during the
sampling. There is, however, diffuse runoff from the waste tips and polluted soils adjacent to the rivers and,
during storm events, there is significant local storm runoff from urban and industrial areas into the streams and
rivers, which is evident from elevated turbidity levels in rivers throughout the monsoon season.
The concentrations of heavy metals increased from December 2017 to January 2018 in general (figure 3)due
to combined effects of decreased river flow, resuspension of sediments caused by the disturbance of riverbed
during Ijtema preparatory work, and subsequent dissolution of metals due anaerobic condition. This sediment
disturbance continues throughout the Ijtema event with addition of different metals, such as aluminium,
chromium and iron from washing utensils, selenium from the likely consumption of medicines, lithium from
battery disposal, and manganese from fish residues. Chromium, lithium, lead and selenium contribute to
cellular toxicity to most microbes, while copper shows toxicity to bacteria and algae in mostly free ion form.
The heavy metal concentrations presented here, however, indicate the total concentration of each metal
instead of their availability as free cations. Most metals are bound in organic and inorganic complexes with
dissolved organic matter, sulfide and ammonia dictating complexation. Chromium and copper bind almost
Figure 2. Physiochemical properties of Turag River and Tongi Khal in comparison to Bangladesh Environmental Quality Standards
(MoEF 1997). Note: Boxplots show data from all 13 sampling points across the four zones, except for months with missing data for
certain parameters (see table A1 in appendix). The figure is adapted from Murgatroyd et al (2021).
7
Environ. Res. Commun. 3(2021)095003 S F Hoque et al

exclusively to organic complexes, and aluminium, manganese, cadmium, lead, selenium and lithium all show
considerable inorganic complexation to oxyhydroxides, chloride and ammonia. Lithium, selenium and zinc also
tend to be in free ionic forms. A speciation analysis of samples in January 2018, through Visual Minteq 3.1
confirmed high levels of organic complexation for copper and chromium near Ijtema sites. Similar organic
complexation was found for most metals except for selenium and lithium which had free ions as dominant
species. A parallel study using this dataset and involving the co-authors of this paper found that high level of
cellular toxicity was particularly associated with increased concentrations of selenium, zinc and chromium
(Rampley et al 2020). Hence, despite the overall increase in metal concentrations, the simultaneous dumping of
organic waste results in lower availability of free ions, which in turn lowers the toxicity in the samples collected
during the Ijtema.
4.2. Social inequalities in water and sanitation services
Zone-1 comprises land privately-owned by a few families descending from early settlers, as well as long-term
lease holders, who built and rented out houses to families and individuals working in nearby brick kilns, garment
factories, and as day labourers. In comparison, settlements in Zone-3 are on government-owned land, with most
tenants and homeowners lacking legal ownership, putting them at risk of eviction. Our survey reveals a high
clustering of poverty in Zone-3, with 41% of the households belonging to the poorest wealth class, compared to
23% and 18% in Zone-1 and Zone-2 respectively (table 2). About 20% of adult women in Zone-3, equivalent to
half of those in paid employment, work in one of the many garment factories nearby, while the men are engaged
in small businesses (22%), casual labour (22%)and garment factories (19%). Zone-4 is a relatively well-off area,
with 66% in the top wealth quartile and having the highest proportion of adults working in the service sector
(14% men and 6% women). The average household monthly expenditure in Zone-4 is BDT 25,500 (USD 307),
which is significantly higher than Zone-1, Zone-2 and Zone-3, with mean expenditures of BDT 13,500 (USD
162), BDT 16,300 (USD 196), and BDT 14,700 (USD 177)respectively. When disaggregated by wealth class, the
average monthly expenditure ranges from BDT 12,000 (USD 145)for the poorest to BDT 25,000 (USD 301)for
the richest class across all zones (Table B3 in appendix).
Households in Zone-1 and Zone-2 access water from motorised tubewells installed by NGOs, either through
pipelines drawn inside their dwelling or through shared taps in communal spaces. Those living on the southern
bank of the Tongi Khal in Zone-3 have access to piped water from DWASA, whether legally or illegally, while
people on the northern bank rely on community tubewells. While they have access to an improved source within
a few minutes of walking distance, water is often only available at certain times during the day, creating long
queues for a limited quantity that is prioritised for drinking and cooking. About 68% of the households in Zone-
3 reported sharing their water source with at least five other households. Households in Zone-4 usually have
their own tubewells, with only 25% sharing it with 5–10 households in the same compound.
Although none of the households are connected to formal sewerage infrastructure, 79% households in
Zone-4 use a flush toilet with a septic tank and 86% do not share their toilet with others. The sanitation
conditions are worst in Zone-3, with 27% reportedly using hanging latrines or practicing open defecation, with
the faecal waste discharging into the river. About half of the households in Zone-3 share their toilets with at least
Figure 3. (a)Heatchart showing variation in heavy metal concentrations between December 2017 and January 2018, along with cell
damage toxicity measured by Rampley et al (2020);(b)Map showing the 22 sampling points along Turag River and Tongi Khal.
8
Environ. Res. Commun. 3(2021)095003 S F Hoque et al

five households, suggesting the lower living standards and increased likelihood of spreading pathogens.
Improved pit latrines are more common in Zone-1 (68%)and Zone-2 (45%), followed by flush toilets with
septic tanks (19% and 41%).
The variations in living standards are also reflected in the concerns expressed by the surveyed households.
For households in Zone-3, clean environment (25%)ranked as the topmost concern, followed by water services
(17%)and sanitation (16%). In comparison, households in Zone-1, Zone-2 and Zone-4 prioritised roads and
transportation (35%, 33% and 37% respectively), followed by healthcare services or gas supply. However, when
surveyed households were specifically asked about their environment-related concerns, 50%–60% across all
zones mentioned the river being dirty as their main concern.
4.3. River use behaviour and pollution exposure
The types and intensities of river use activities were closely linked to the socio-demographic contexts of the
studied populations and the water quality. Direct contact with river water, through dish washing, laundry,
cleaning fish and vegetables, and personal washing was high in Zone-1 and Tongi slum in Zone-3 (figures 5
and 6), with averages of 14 and 15 people observed per 3-hour slot during the dry season, of which 10 people in
each site were women and girls (Table C3 in appendix). These sites were close to residential clusters, where
overcrowding at community water points and restricted supply only at certain times during the day, led to high
usage of river water for domestic activities. We also observed several boat dwellers along the Tongi Khal in Zone-
3, who used the river for almost all purposes other than drinking (figure 4). Domestic activities were relatively
fewer in Zone-4, owing to the better socio-economic status of residents in this area.
During the wet season, we observed a slight decrease in domestic activities in Zone-1 and Tongi slum in
Zone-3 (figure 5). In Zone-1, construction of new houses along the bank which partially deterred the local
residents from accessing one of the observation sites, while in Zone-3, around 60 houses were evicted as part of
the government’s drive to control river encroachment. However, we recorded a steep increase in swimming and
bathing activities in Zone-1 and Tongi slum in Zone-3, which changed the overall observation counts to 11 and
27 people observed per 3-hour slot. Recreational swimming was more prevalent among adult men and male
children, as cultural norms sometimes refrained women from sharing the same public space with men for
recreation (figure 6). This increased river interaction by men, along with the reduction in women carrying out
domestic activities, led to equal proportions of both genders observed per 3-hour slot. The rise in bathing and
Table 2. Characteristics of households living along the Turag-Tongi Rivers in Dhaka.
Household characteristics Zone-1 Zone-2 Zone-3 Zone-4
WEALTH QUARTILES 1 (Poorest)23% 18% 41% 4%
2 26% 28% 28% 11%
3 30% 26% 20% 18%
4(Richest)21% 28% 11% 66%
MAIN SOURCE OF DRINKING WATER Piped water into dwelling/yard 20% 6% 55% 1%
Motorised tubewell 73% 92% 42% 96%
Others 7% 2% 2% 3%
WATER SOURCE SHARING Not shared 44% 26% 11% 75%
Less than 5 households 33% 33% 21% 20%
5–10 households 14% 15% 27% 5%
More than 10 households 9% 26% 41% 0%
SANITATION Flush to septic tank 19% 41% 26% 79%
Improved pit latrine 68% 45% 43% 20%
Unimproved pit latrine 3% 2% 5% 1%
Hanging toilet/Open defecation 10% 12% 27% 1%
TOILET SHARING Not shared 61% 47% 20% 86%
Less than 5 households 27% 25% 33% 13%
5–10 households 9% 9% 25% 1%
More than 10 households 4% 19% 22% 0%
GENERAL CONCERNS Clean environment 3% 3% 25% 11%
Water supply 6% 8% 17% 0%
Sanitation 3% 2% 16% 4%
Healthcare 23% 6% 7% 24%
Roads and transportation 35% 33% 2% 37%
Gas supply 7% 32% 5% 6%
No concerns 1% 2% 13% 9%
Others 22% 14% 16% 9%
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swimming, which was also prevalent in other sites, can be attributed to the warmer weather and perceived
improvement in water quality.
Small-scale productive uses were also observed at some sites in Zone-3. These included washing and dyeing
denim, washing fish baskets or plastic sheets, collecting plastic waste and fishing. Denim washing was mostly
carried out by men, under the pillars of the railway bridge on the Tongi Khal (figure 4). During the wet season,
the platforms of the pillars were flooded which resulted in a decrease in this observed activity, which likely
shifted to another site not included in our study. Informal waste pickers could be spotted wading through the
river on a boat, collecting plastic bottles for resale while others were seen washing plastic sheets either on the
banks or in waist deep waters. These indigo tainted sheets are waste products from dye packaging, which serve as
an income source for these marginalised citizens. One of our observation sites in Zone-3 was near the local fish
market, where traders regularly used the river to wash their fish and the fish baskets. Fishing, with or without a
boat, was commonly observed across all sites during the wet season. In Zone-1, the abundance of fish along the
banks meant that women and children could easily catch these with their bare hands.
The river was heavily used for boating, mainly for transportation and sometimes for recreation. Boating
increased significantly in Abdullahpur and Ijtema field in Zone-3 and in Zone-4 during the Ijtema period in
February 2019 for transportation of people, food and construction materials. While temporary sanitation
facilities with faecal sludge containment was provided for the Ijtema devotees, urinating into the river was
commonly practiced, along with the disposal of organic food waste (figure 4).
5. Discussion
River pollution is a perverse though predictable outcome of economic growth in Asiancities. Our longitudinal
river use observation, supported by water quality monitoring and household surveys, reflect three main findings.
First, river water quality and usage behaviours are highly dynamic and contextualised, and while it is neither
straightforward nor desirable to quantify correlations, we observe that the spatial co-location of multiple
deprivations can increase pollution exposure (figure 7). For instance, despite having similar pollution levels,
Figure 4. (1)Aerial view of Konabari settlement (Zone-1);(2)Boat dwellers and hanging latrines along Tongi slum (Zone-3);(3)
Woman collecting plastic bottles from Tongi Khal (Zone-3);(4)People washing dye packaging near Konabari (Zone-1);(5)Children
swimming in the Tongi Khal in monsoon (Zone-3);(6)People washing denim under the Railway Bridge (Zone-3);(7)Man fishing in
the river at Mausaid (Zone-4);(8)Men washing and disposing food waste along the river bank during Ijtema (Zone-3); and (9)
Temporary urinals for Ijtema participants (Zone-3).
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Environ. Res. Commun. 3(2021)095003 S F Hoque et al

direct use of the river was substantially higher in Zone-3 than Zone-4, due to higher poverty levels and
inadequate water and sanitation facilities in the former. Second, the nature and timing of river interaction is
differentiated by gendered roles and cultural norms, with women and girls risking direct contact through
washing dishes, clothes, and other chores throughout the year, while perceived improvement in water quality in
monsoon led to increased swimming and bathing among men and children. Third, the Bishwa Ijtema gathering
increased concentrations of many heavy metals, though simultaneous disposal of organic waste may alter
availability of metal in their free ionic forms. However, given the anoxic conditions that already prevail during
the dry season, the additional toxicity contributed by the Ijtema may not be significant. Our study illustrates how
future monitoring systems can combine biophysical and social data to provide a more integrated framework for
the government’s planning cycles.
5.1. Poverty and pollution risks
Regardless of sampling location and season, the rivers have severe pathogen pollution, as indicated by the faecal
coliform count that is several hundred times higher than the recommended national and international standards
of <200cfu/1000ml for bathing and swimming (MoEF 1997, UNEP 2016). Swimming and bathing activities,
which increase in monsoon, are likely to cause infectious diseases from accidental ingestion and contact with
mucous membranes in eyes and ears. Results from a Quantitative Microbial Risk Assessment across three rivers
Figure 5. Intensity of river use activities disaggregated by zone and observation site.
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Environ. Res. Commun. 3(2021)095003 S F Hoque et al

in southwestern Bangladesh show that the overall risk of illness for a single exposure of pathogens during
bathing ranged from 9%–19% for children and 7%–16% for adults, which exceeds the USEPA acceptable risk of
3–6 illnesses per hundred bathing events (Islam and Islam 2020). Similarly, Hamner et al (2006)found
significant associations between the use of the Ganges River in Varanasi, India for bathing, laundry, and washing
utensils and the incidence of water-borne enteric diseases, with poor sanitation, low income and low education
as confounding factors.
Figure 6. Observations of river use disaggregated by gender and age.
Figure 7. Qualitative assessment linking water quality, socio-economic conditions, and direct contact with river across the four study
zones.
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Environ. Res. Commun. 3(2021)095003 S F Hoque et al

The bioaccumulation of heavy metals in fish and vegetables have also been documented in previous studies
(Ahmed et al 2016, Rashid et al 2017). Our observations show that fishing activities are prevalent in the monsoon
season, indicating potential consumption of accumulated heavy metals by families consuming fish and nearby
populations through the sale of caught fish at neighbourhood markets. Our study shows that women in low-
income settlements are regularly exposed to contaminated water, even during the dry season, through washing
clothes and dishes. Similarly, informal waste recyclers, standing in waist deep water to wash dye packaging, and
casual workers washing denim in the river, are risking exposure on a daily basis. While Hasan et al (2019)found
significantly higher concentrations of chromium in nails and hair samples of tannery workers, there has been no
similar research on bioaccumulation of heavy metals in these riverine dwellers, despite the measured
cytotoxicity potential of the river water. Systematic observation of human interaction with polluted river water is
unprecedented, providing opportunities for adapting our method to quantify health risks. Recent studies also
show high likelihood of heavy metal exposure through dermal contact, the risk being dependent on exposed
body surface area and duration of activity (Zhao et al 2019). However, these assessments of ‘total human
exposure’are based on retrospective snapshots of human activity patterns from surveys, which are prone to
recall and social desirability bias. In such cases, our method can be adapted in the future to include recordings of
the proportion of body surface exposed and duration of activity.
The riverbank settlements studied here are home to thousands of factory workers and their families, living in
dense, unsanitary conditions that they afford with their low wages. Though the aggregate benefits of economic
growth are enjoyed by the wider population, the negative externalities of unregulated industries and unplanned
urbanisation are disproportionately borne by those directly contributing to the growth process. While rural
migrants are often habituated to use surface water for domestic activities, the lack of adequate water services and
the resulting overcrowding at community waterpoints are key drivers of river usage for washing and bathing
purposes. Such unequal water-citizenship in Dhaka slums ‘is a daily reminder to the urban poor of their
abjection and undesired status in the city’(Sultana 2020, p.1413). While aggregate statistics by JMP (2019)
suggest that open defecation is non-existent in urban Bangladesh, the high prevalence of hanging latrines, as
observed in this study and previous work by Haque et al (2020), reveals that the challenges of marginalised
communities may be masked or ignored in the bigger picture.
5.2. Policy landscape and recommendations
While the export-oriented economic growth agenda has dominated the Government of Bangladesh’s political
and institutional approach since the 1990s, actions are being taken to curb river encroachment, reduce industrial
and municipal pollution, and regulate water use, with the High Court bestowing rivers with the same rights as
‘legal persons’in July 2019 (Islam and O’Donnell 2020). The ongoing construction of new sewerage treatment
plants under the ‘DWASA Masterplan 2011’, and the recently approved ‘Dhaka Sanitation Improvement
Project’, which includes plans to upgrade toilets and provide communal septic tanks in low-income
communities (The World Bank 2020), are two of the planned large-scale interventions to reduce municipal
pollution. The Water Resources Planning Organization (WARPO)in collaboration with United Nations
Economic and Social Commission for Asia and the Pacific(UNESCAP)is drafting the Industrial Water Use
Policy (UN ESCAP and WARPO (2019)), including the Greater Dhaka Watershed Restoration project to
promote industrial wastewater treatment and reuse (2030WRG 2017). The relocation of the tanneries has been
another major intervention, though in absence of a functioning centralised effluent plant, the pollution has
merely shifted from the Buriganga to Dhaleshwari River (Hasan et al 2020).
The Government of Bangladesh has ambitious goals to dramatically increase ready-made garment exports;
however, no equivalent bold environmental policies have been enacted to counter the potential harm from
increased wastewater (Hossain et al 2018). Government plans to achieve SDG 6.3 tend to rely on the technocratic
logic of dominant institutions, driven by physical interventions in manipulating river morphology through
dredging (General Economics Division 2015: p. 423). Industry efforts, largely pursued by international brands
sourcing from Bangladesh and donor institutions such as the World Bank and International Finance
Corporation, focus on creating zones of ‘cleaner production’that end up excluding the worst offenders that
supply only to the domestic market from external scrutiny (Selim 2018).
However, even if all these initiatives are executed effectively, the portfolio of engineering, judicial, and
institutional initiatives is likely to take years to translate into reduction of pollution risks for the most vulnerable.
In the short-term, responses to curb pollution exposure, through provision of safely managed water and
sanitation facilities and approaches like risk communication can minimise health risks of those living in riverine
communities.
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Environ. Res. Commun. 3(2021)095003 S F Hoque et al

Acknowledgments
This document is an output from the REACH programme funded by UK Aid from the UK Foreign,
Commonwealth and Development Office (FCDO)for the benefit of developing countries [Programme Code
201880]. However, the views expressed and information contained in it are not necessarily those of or endorsed
by FCDO, which can accept no responsibility for such views or information or for any reliance placed on them.
Data availability statement
The data that support the findings of this study are available upon reasonable request from the authors.
ORCID iDs
Sonia Ferdous Hoque https://orcid.org/0000-0001-7239-2312
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