Risk Assessment of PPCPs in Indian Waters - Assignment Submission
Human Health, Ecological, and AMR Risk Assessment of
PPCPs in Indian Waters
Based on: Sengar & Vijayanandan (2022), Science of the Total Environment 807: 150677
Course Assignment - EN/CE | Submitted: 19 April 2026
Question 1: Methodology - Risk Assessment Framework
Sengar and Vijayanandan (2022) evaluated 98 pharmaceuticals and personal care products
(PPCPs) detected across Indian surface waters, treated wastewaters, and groundwater using
a Risk Quotient (RQ) approach. The central logic of the method is straightforward: compare
what is actually present in the environment against what is considered safe, and flag anything
where the ratio exceeds 1. Three parallel assessments were conducted - human health risk,
antimicrobial resistance (AMR) selection risk, and ecological risk - each using a variation of
this ratio.
1.1 Key Terms Explained
MEC - Maximum Measured Environmental Concentration
MEC is the highest concentration of a PPCP that has been reported in a given water matrix.
The authors conducted a systematic review of 35 published papers and recorded the peak
detected concentration for each compound in each water type. Using the maximum rather
than an average gives the assessment a conservative, worst-case character - if the most
extreme observed value poses no risk, the typical situation is unlikely to be a problem either.
ADI - Acceptable Daily Intake
The ADI represents the dose of a substance a person can safely consume every day over an
entire lifetime without experiencing adverse health effects. It is expressed in micrograms per
kilogram of body weight per day (µg/kg-day). For 48 compounds, the authors sourced
published ADI values directly from literature. For the remaining 23, they derived ADI values
using either the Lowest Therapeutic Dose (LTD) for pharmaceuticals - dividing the LTD by a
safety factor of 1000 and the body weight of 70 kg - or the No-Observed-Adverse-Effect-Level
(NOAEL) for personal care products, applying a combination of five safety factors accounting
for species extrapolation, exposure duration, and population sensitivity.
DWEL - Drinking Water Equivalent Level
Because MEC values are expressed as concentrations in water (µg/L) while ADI is expressed
as a dose per body weight (µg/kg-day), a direct comparison is not possible. DWEL bridges
this gap by converting ADI into a water concentration that would correspond to the safe daily
dose, taking into account body weight, drinking water intake, absorption rate, and frequency
of exposure. The equation used was:
DWEL = (ADI × BW × HQ) / (DWI × AB × FOE)
Where HQ (hazard quotient) = 1, AB (gastrointestinal absorption) = 1, and FOE = 350/365
days.
PNEC - Predicted No Effect Concentration (Ecological)
PNEC is the concentration of a chemical in the environment below which adverse effects on
aquatic organisms are not expected to occur. It is derived from the Chronic Toxicity Value
(ChV) by applying an Assessment Factor (AF) of 100, which accounts for the uncertainty
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Risk Assessment of PPCPs in Indian Waters - Assignment Submission
involved in extrapolating laboratory results to real-world field conditions and for inter-species
variability.
PNEC = ChV / 100
PNEC_AMR - Predicted No Effect Concentration for AMR Selection
This is a separate threshold specific to antibiotic resistance. It represents the lowest
concentration at which an antibiotic can begin to exert selective pressure on environmental
bacteria, favouring the survival of resistant strains. These values were derived from Minimum
Inhibitory Concentration (MIC) data held in the EUCAST clinical database, adjusted with an
appropriate assessment factor. The PNEC_AMR values are typically much lower than PNEC
values for acute toxicity, reflecting the fact that resistance selection can occur at subtherapeutic concentrations.
ChV - Chronic Toxicity Value
ChV is the threshold concentration at which chronic toxic effects begin to manifest in a test
organism. Because measured chronic toxicity data was unavailable for all 98 compounds
across all three test species, ChVs were derived using ECOSAR v2.0 - a US EPA software
that estimates toxicity based on Quantitative Structure-Activity Relationships (QSAR),
essentially predicting how toxic a molecule is by comparing its structure to chemicals with
known toxicity data.
RQ - Risk Quotient
RQ is the core metric of the entire assessment. It is calculated as the ratio of the measured
environmental concentration to the relevant safety threshold:
For human health: RQH = MEC / DWEL
For AMR selection: RQAMR = MEC / PNEC_AMR
For ecological risk: RQ = MEC / PNEC
An RQ greater than 1 signals possible risk and flags the compound for regulatory attention.
Values between 0.2 and 1 suggest a more refined assessment may be warranted, while values
at or below 0.2 indicate no appreciable risk.
1.2 Why Different Age Groups for Human Health Risk?
The study calculated DWEL and RQH for seven distinct age groups ranging from 1–2 years
up to adults over 21 years. This matters because children are physiologically different from
adults in a risk-relevant way: young children consume more water relative to their body weight
than adults do, which means they receive a higher dose per kilogram of body weight from the
same concentration of contaminant in drinking water. In this study, children in the 1–2 year
age group consistently showed RQH values two to four times higher than those of older age
groups. Using age-differentiated analysis therefore reduces the uncertainty in risk estimates
and accurately identifies who is most vulnerable - in this case, toddlers - rather than averaging
the risk across a population where the most sensitive individuals would be missed.
1.3 Why Three Trophic Levels for Ecological Risk?
The three organisms chosen - algae (primary producers), daphnia (primary invertebrate
consumers), and fish (secondary vertebrate consumers) - represent distinct positions in the
aquatic food web. A chemical's toxic effects can vary dramatically across species; a compound
that is relatively harmless to fish might devastate algal populations. This is precisely what the
study found for caffeine, which showed an RQ of 4350 against algae while posing far less
threat to fish and daphnia. If only fish toxicity had been assessed, the risk from caffeine would
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Risk Assessment of PPCPs in Indian Waters - Assignment Submission
have been severely underestimated. Furthermore, ecological risk is not just about direct
toxicity to individual species - killing off algae disrupts the entire food base of the ecosystem,
causing indirect harm to organisms above them in the food chain. Testing across trophic levels
therefore captures both direct and indirect risks, giving a far more complete picture of
ecological impact.
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Risk Assessment of PPCPs in Indian Waters - Assignment Submission
Question 2: Limitations and Suggestions for Future Research
2.1 Critical Discussion of Limitations
Limitation 1 - Individual Compound Assessment Only, No Mixture Effects
The entire risk assessment framework treats each PPCP in isolation. In reality, water bodies
contain dozens of contaminants simultaneously, and compounds can interact with each other
in ways that amplify their combined toxicity - a phenomenon known as synergism. Even when
each individual compound is present at a concentration well within its safe ADI, the combined
effect of multiple compounds acting on the same biological pathway can exceed the threshold.
This is not a hypothetical concern - it is especially relevant for the Hyderabad industrial region
studied here, where numerous pharmaceuticals co-occur at extremely high concentrations.
By ignoring mixture toxicity, the study almost certainly underestimates true risk, which is a
fundamental limitation that the authors themselves acknowledge.
This limitation is particularly significant for the AMR assessment. Multiple antibiotics of
different classes acting simultaneously on environmental bacterial communities may select for
resistance more effectively than any single antibiotic alone, because resistance genes often
provide cross-protection against multiple compound classes. The current framework has no
way of capturing this dynamic.
Limitation 2 - Reliance on Modelled Rather Than Measured Toxicity Data
The ecological risk assessment is built entirely on ChVs generated by ECOSAR v2.0, which
predicts toxicity from molecular structure rather than from actual experimental measurements.
For compounds that are structurally similar to well-studied chemicals, QSAR predictions can
be reasonably accurate. However, for novel, complex, or structurally unusual pharmaceutical
molecules, these predictions can deviate significantly from actual toxicity values. There is no
empirical validation step in this study to check how well ECOSAR predictions match measured
chronic toxicity data for the specific compounds assessed.
Similarly, the PNEC_AMR values are derived from MIC data from the EUCAST database,
which catalogues resistance in clinically isolated bacterial strains. Environmental bacterial
communities are far more diverse, include organisms that cannot be cultured in a laboratory,
and operate in complex ecological contexts that laboratory MIC measurements do not reflect.
The real-world threshold for AMR selection in environmental systems may therefore differ
substantially from what the study assumes.
Limitation 3 - Geographical Data Gaps
The occurrence data underpinning the entire assessment is unevenly distributed. The study
draws on papers concentrated in Southern India - particularly around Hyderabad - and to a
lesser extent Delhi. Large portions of India, particularly Northern, Eastern, and North-Eastern
states, have very limited published occurrence data for PPCPs. The risk picture presented is
therefore not a true national picture but rather an assessment driven predominantly by the
most contaminated and most studied region. This means risks in underreported areas may be
going undetected, while the extreme values from Hyderabad may give a distorted sense of
national severity.
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Risk Assessment of PPCPs in Indian Waters - Assignment Submission
2.2 Suggested Improvements for Future Research
Improvement 1 - Mixture Risk Assessment Using the Concentration Addition Model
Future studies should move beyond individual compound RQs and adopt the Concentration
Addition (CA) approach, which is already an established method in environmental toxicology.
Under CA, the risk quotients of all compounds detected at a given site are summed to produce
a cumulative Hazard Index (HI). This approach is particularly appropriate when multiple
compounds share a common mechanism of action - for example, fluoroquinolone antibiotics
acting on the same bacterial enzyme. Applying CA to sites like Patancheru near Hyderabad,
where dozens of antibiotics and pharmaceuticals co-occur at very high concentrations, would
likely reveal substantially higher cumulative risk levels than the individual RQ approach
currently suggests. This would produce more accurate risk estimates and make the case for
remediation more compelling to regulators.
Improvement 2 - Incorporation of Environmental Fate Modelling and Bioavailability
Currently, the MEC is treated as the total dissolved concentration in water, and it is assumed
to be 100% bioavailable for uptake by organisms or humans. In reality, pharmaceuticals in the
environment undergo transformation processes - photodegradation, microbial breakdown, and
sorption onto sediment particles - that reduce the fraction of the compound actually available
to cause harm. Future studies should incorporate fate modelling tools such as SimpleBox or
the POCIS passive sampler approach to estimate the bioavailable fraction of each compound
rather than using total measured concentrations. This would produce more realistic (and likely
lower) risk estimates for most compounds, while also allowing researchers to identify which
compounds persist longer and therefore warrant the most regulatory attention. For the AMR
assessment specifically, understanding the bioavailable fraction is critical because only freely
dissolved antibiotic molecules exert selection pressure on bacterial communities.
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Risk Assessment of PPCPs in Indian Waters - Assignment Submission
Question 3: The Ecological Risk Assessment Process
Ecological Risk Assessment (ERA) is a structured scientific process used to evaluate the
likelihood and magnitude of adverse effects on ecosystems and aquatic life from exposure to
chemical stressors. The process follows a defined sequence of stages, each building on the
last, with a feedback loop that enables continuous refinement as new data becomes available.
The standard ERA framework, as applied in Sengar and Vijayanandan (2022) and consistent
with guidance from the US EPA and European Commission, consists of five core stages
described below.
3.1 Stage 1 - Problem Formulation
This is the defining stage of the entire ERA. It sets the scope and direction of the assessment
by identifying the chemical stressors of concern (in this case, 98 PPCPs), the ecological
receptors at risk (aquatic organisms across three trophic levels), and the pathways through
which exposure occurs (discharge from WWTPs and industrial effluent treatment plants into
surface water and groundwater systems). Problem formulation also establishes the
assessment endpoints - the specific ecological values that need to be protected, such as
population viability of fish or the photosynthetic productivity of algae. Getting this stage right
is critical because every subsequent stage is shaped by the decisions made here. If important
exposure pathways or receptors are overlooked at this stage, they will remain unassessed
throughout the entire ERA.
3.2 Stage 2 - Exposure Assessment
Exposure assessment quantifies how much of a stressor is present in the environment and
how organisms come into contact with it. In Sengar and Vijayanandan (2022), this involved
extracting the Maximum Measured Environmental Concentrations (MECs) for each PPCP
from 35 published studies covering surface water, treated wastewater, and groundwater
across India. The MEC represents the worst-case exposure scenario - the highest
concentration detected in any study at any location. Exposure assessment can also involve
modelling the fate and transport of chemicals through environmental systems, though this
study relied exclusively on measured data.
3.3 Stage 3 - Effects Assessment
Effects assessment establishes the toxicological benchmarks that define what concentrations
are harmful to aquatic organisms. In this study, the effects assessment involved deriving
Chronic Toxicity Values (ChVs) for each of the 98 PPCPs from the ECOSAR v2.0 predictive
software. ChVs were obtained separately for three test organisms: fish, daphnia, and green
algae. These ChVs were then converted into Predicted No Effect Concentrations (PNECs) by
applying an Assessment Factor of 100, which introduces a safety margin to account for the
uncertainty in extrapolating laboratory data to complex real-world ecosystems:
PNEC = ChV / 100
3.4 Stage 4 - Risk Characterisation
Risk characterisation is the analytical core of the ERA. It integrates the outputs of the exposure
assessment (MEC) and the effects assessment (PNEC) to calculate the Risk Quotient (RQ)
for each compound at each trophic level:
RQ = MEC / PNEC
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Risk Assessment of PPCPs in Indian Waters - Assignment Submission
An RQ of 1 or more indicates high ecological risk. Values between 0.1 and 1 represent medium
or moderate risk, and values below 0.1 indicate low risk. Risk characterisation also involves
communicating the uncertainty inherent in the estimates - in this study, the use of modelled
ChVs from ECOSAR and the conservative use of peak concentrations as MEC values are
both acknowledged as sources of uncertainty. Results are reported separately for each water
matrix and each trophic level to allow identification of the most at-risk organisms and the most
contaminated locations.
3.5 Stage 5 - Risk Management
When risk characterisation identifies compounds with RQ values exceeding 1, risk
management decisions follow. This stage moves the ERA from science into policy and
practice. In Sengar and Vijayanandan (2022), the risk management recommendations
included: immediate implementation of stricter regulatory standards for pharmaceutical
industrial effluents, particularly in the Hyderabad industrial region; upgrading existing
wastewater treatment plants with advanced technologies such as ozonation, powdered
activated carbon, membrane filtration, or advanced oxidation processes; and establishing
systematic national monitoring programmes to track PPCP concentrations across currently
underreported regions.
3.6 Monitoring and Feedback
ERA is not a one-time exercise. The monitoring and review stage feeds back into the problem
formulation stage, updating the risk picture as new concentration data, new toxicity
information, and new compounds emerge. This iterative character is essential because PPCP
contamination is dynamic - pharmaceutical consumption patterns change, new drugs enter
the market, and treatment technologies improve. Without regular re-assessment, risk
management decisions based on outdated data may either fail to protect ecosystems from
emerging threats or, conversely, impose unnecessary regulatory burdens on the basis of risks
that have since been reduced.
The flowchart below illustrates the complete ERA process described above, including the
decision point at risk characterisation and the feedback loop from monitoring back to problem
formulation.
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Question 4: Three Key Differences Between ERA and Human Health Risk
Assessment
Ecological Risk Assessment (ERA) and Human Health Risk Assessment (HHRA) share the
same structural backbone - both use the Risk Quotient approach of comparing measured
exposure against a safety threshold. However, beneath this surface similarity lie important
conceptual and practical differences that affect how risk is defined, measured, and managed.
Difference 1 - The Nature and Complexity of the Receptor
In human health risk assessment, the receptor is always the same: Homo sapiens. You are
protecting one species, with reasonably well-characterised physiology, through one primary
exposure route (in this study, drinking contaminated water). Even when the study
disaggregates by age group - as Sengar and Vijayanandan (2022) do - all the variation falls
within a single species whose physiological responses are well-documented from decades of
clinical and pharmacological research. The ADI and DWEL values rest on a large body of
human and mammalian toxicological data.
ERA, by contrast, must simultaneously protect thousands of species across multiple trophic
levels, each with fundamentally different physiologies, life histories, and sensitivities to
chemical stressors. Using only three test species - fish, daphnia, and algae - as proxies for an
entire ecosystem is a significant simplification. The challenge is not just that different
organisms respond differently to the same chemical: it is that harm to one trophic level
propagates through the food web and indirectly harms others. If a chemical wipes out algal
populations, the daphnia that feed on algae will collapse even if the chemical is not directly
toxic to daphnia at that concentration. This ecosystem-level cascade is something HHRA
simply does not need to contend with, because human risk does not propagate through food
webs in the same way.
This difference is not just academic. In this study, caffeine showed an ecological RQ against
algae of 4350 - catastrophic - while posing far less direct risk to fish. A human health risk
assessment would have flagged caffeine as low-concern and moved on. ERA reveals it as a
major ecological stressor, precisely because the receptor in ERA is the whole ecosystem, not
just the most visible or commercially valuable organism in it.
Difference 2 - The Type of Harm Being Prevented
Human health risk assessment is fundamentally oriented towards protecting individuals from
adverse health outcomes - toxicity, carcinogenicity, organ damage, developmental effects.
The thresholds used (ADI, NOAEL) are derived from dose-response studies designed to
identify the concentration at which no clinical effect occurs in the most sensitive individual.
The entire framework is built around the idea of avoiding measurable harm to specific people,
and the safety factors applied are designed conservatively to protect even the most vulnerable
member of the population (in this study, children aged 1–2 years).
ERA is not primarily about protecting individual organisms - it is about protecting population
viability and the functional integrity of ecosystems. A small number of individual organisms
being harmed by a chemical is generally acceptable in ecological terms, as long as the
population can sustain itself and the ecosystem continues to function. The PNEC is set to
protect the most sensitive species at the population level, not the most sensitive individual
organism. This is a meaningful distinction because ecosystems have a degree of resilience they can absorb some level of chemical stress without collapsing - but they can also pass
invisible tipping points after which recovery is extremely difficult or impossible. The RQ
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framework as applied in this study captures none of this non-linearity. It treats risk as a smooth,
proportional function of concentration, when in reality ecological systems can show sudden
and irreversible regime shifts when thresholds are crossed.
This difference also manifests in the endpoints of concern. HHRA asks: will this person
develop a health condition? ERA asks: will this population decline? Will this ecosystem lose a
functional component? These are fundamentally different questions, and they require different
kinds of evidence to answer well.
Difference 3 - How Uncertainty is Structured and Handled
Both frameworks acknowledge uncertainty and both use safety factors to manage it. But the
sources of uncertainty differ substantially, and the strategies for addressing them reflect those
differences.
In HHRA, the main sources of uncertainty are biological variability between individuals (some
people are more sensitive than others), interspecies differences when animal data is used to
predict human effects, and the extrapolation from short-term toxicological studies to lifetime
exposure. These uncertainties are well-characterised and are addressed through established
multiplicative safety factors - typically factors of 10 for interspecies extrapolation, 10 for
intraspecies variability, and so on. The WHO, US EPA, and other bodies have decades of
experience calibrating these factors, and while the specific values can be debated, the
structure of the uncertainty is relatively well understood.
In ERA, the structure of uncertainty is fundamentally more complex. The Assessment Factor
of 100 applied to ChV to obtain PNEC is a single blunt instrument trying to account for an
enormous range of uncertainties: the sensitivity of the three test species relative to the most
sensitive organism in the real ecosystem; the applicability of laboratory chronic toxicity data to
field conditions where organisms experience multiple simultaneous stressors; the accuracy of
QSAR-derived ChVs for compounds with unusual molecular structures; and the
representativeness of MIC data from clinical isolates for environmental bacterial communities.
Unlike HHRA, where the populations being protected (humans) are the same species as the
organisms studied in toxicology tests, ERA is always making a leap from a small number of
well-studied test species to a vast and largely uncharacterised ecological community. The AF
of 100 covers this leap, but it does so with very limited insight into whether 100 is the right
number for any given compound. In some cases it may be far too lenient; in others,
unnecessarily conservative. This structural opacity in the uncertainty framework is, in my view,
the most significant methodological difference between ERA and HHRA.
Reference
Sengar, A. and Vijayanandan, A. (2022). Human health and ecological risk assessment of
98 pharmaceuticals and personal care products (PPCPs) detected in Indian surface
and wastewaters. Science of the Total Environment, 807, 150677.
https://doi.org/10.1016/j.scitotenv.2021.150677
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