Shellfish water quality monitoring using chemical tracers, environmental microbiology and satellite remote sensing

Carlos J. A. Campos

Water Quality Scientist

Cefas, Weymouth Laboratory

Transfer of microbiological contaminants to watercourses

2

Faecal indicator bacteria

Flows

Source: Kelsey et al. (2010) Source: Stapleton et al. (2015)

Pollutants of concern and impacts of combined sewer overflows

3

Pollutants Main consequences

Bacteria (faecal coliforms, E. coli, enterococci) Viruses Protozoa

Shellfish bed closures Beach closures Drinking water

contamination

Litter and floatables

Aesthetic deterioration Devaluation of property Odours Beach closures

Organic compounds Metals Oil and grease Toxic pollutants

Deterioration of aquatic life Adverse public health

effects Fishing and shellfishing

restrictions

Biochemical oxygen demand

Reduced oxygen levels Fish kills

Nutrients (nitrogen, phosphorus)

Eutrophication Algal blooms Aesthetic deterioration

Source: EPA (2010)

Economic impacts of CSO discharges on shellfisheries

4

Economic losses are significant and depend heavily on

tidal activity, and the size, frequency and timing of

closures.

In 2001-2009, temporary pollution closures contributed to

the loss of $3.6 M (27.4% of total revenue).

Closures linked to CSOs from the Machias wastewater

system produce the majority of these losses ($2 M).

The largest losses occurred during the peak harvest

season (May-August).

Water quality improvements following sewage treatment upgrades: the Chichester Harbour case study

5

2007

2008

2009

2010

2011

2012

2013

2014

2015

10.0

8

9.76

8.14

6.88

6.12

5.55

3.27

2.80

0.95

0.05

1000000

100000

10000

1000

100

10

Log1

0E. c

oli (

cfu/

100m

l)

250500

10.0

8

9.76

8.14

6.88

6.12

5.55

3.27

2.80

0.95

0.05

1000000

100000

10000

1000

100

10

Log1

0E. c

oli (

cfu/

100m

l)

250500

10.0

8

9.76

8.14

6.88

6.12

5.55

3.27

2.80

0.95

0.05

1000000

100000

10000

1000

100

10

Log1

0E. c

oli (

cfu/

100m

l)

250500

◄ Headwaters Estuary mouth ► Distance (km) from WwTW outfall

Station number: 1 2 3 4 5 6 7 8 9 10

UV and activated sludge plants at Chichester STW UV plant at Bosham STW

UV plant in storm tank at Chichester STW

Birdham Spit: C►B

Birdham Spit: B►C

Thorney: C►B

Dell Quay: C►B

Bosham STW

Chichester STW

2016

UV disinfection plant at Chichester STW

Accumulation/clearance of faecal bacteria in response to CSO spills

6

E. coli levels exceed class C limit (46,000/100g) following CSO spill and

decay during subsequent discharge-free periods.

Suggestion that the concentration/depuration response are independent of

CSO spill volumes.

7

Estimating norovirus impact through dye tracing and microbiology

The application of this method successfully demonstrated physical linkage between sewage inputs and shellfish flesh quality (norovirus and E. coli) in contrasting coastal environments

Rhodamine dye

Dye injected into the final effluent

Deionised water

STW flow monitor

Chemical tracer experiment

8

Dye-tagged effluent tracking in the shellfish water using towed fluorometer

“Average” exposure

Maximum exposure

Bacteria and virus monitoring in shellfish

9

Shellfish samples tested for NoV GI and

GII by RT-PCR (ISO/TS15216-1 ) and

E. coli (MPN) (ISO16649-3)

Predictive modelling

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Dilution ratio

Mean concentration of norovirus (copies/g)

Mean concentration of E. coli

(MPN/100g) 300:1 1,200 260

1,000:1 600 100 5,000:1 200 30

10,000:1 100 15

100001000100

10000

1000

100

Minimum dilution in the receiving water

Nor

oviru

s (G

I+G

II) (c

opie

s/g)

300 1000 5000 10000

1200

600

200

100

AAA

A

A

A

A

B

B

BB

Site A: embayment impacted by secondary-treated sewage Site B: estuary impacted by UV disinfected sewage and sewer overflows

Models: log10Norovirus=4.528-0.581*log10dilution (adjusted R2=74%; p=0.001) log10E. coli=4.359-0.787*log10dilution (adjusted R2=54%; p=0.010)

Monitoring water quality from space

11

Benefits: Satellites can revisit the same spot on

the planet every day, or every few days. Improved algorithms can enhance

accuracy in problematic areas. Cloud problematic but spatial resolution

improving. Limitations: Satellites can only observe the top few

metres of the ocean. Interference from dust, cloud, glint, fog

and smoke. Reduced accuracy in ‘complex’ waters

including coastal areas.

Monitoring water quality from space

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Optical water quality variables that can be derived from Earth Observation data:

Directly assessed: Chlorophyll Cyanobacterial pigments Coloured dissolved organic matter Total suspended matter

Indirectly assessed: Vertical attenuation/light coefficient Turbidity

Image of East Devon, taken by Landsat 8 on 4 November 2013. Source: USGS.

When to use EO for water quality monitoring in aquaculture sites

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Nature of the water quality problem: What water quality issues need to be considered? What policies/regulations drive water quality improvements? Who are the beneficiaries of solution(s) to the problems?

Assess the status of existing data and monitoring networks: What measurements are currently available? What is the condition of the data networks? Are there impediments to data sharing? What has been done in the past to address the water quality issues? Evaluate the adequacy of existing in situ data: Are the observations well defined? Are the density, frequency and continuity specified? Are observations accurate and available?

Current sensors relevant to UK coastal waters

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Sensor system Pixel size (m)

Revisit cycle

Chl Cyp TSM CDOM Kd Turb

Ocean-coastal low spatial resolution

Meris & OCM1 300 2-3 days

VIIRS & JPSS1 750 2x/day

Multi-spectral mid-spatial resolution

Landsat1 30 16

High spatial resolution

IKONOS, Quickbird, SPOT-

5, GeoEYE

2-4 2-60 days

RapidEye 6.5 Daily

Worldview-2 2 On demand

Ocean-coastal low spatial resolution

Sentinel-31 300 3 days

Highly suited Suitable Potential 1 Free

Future sensors relevant to UK coastal waters

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Highly suited Suitable Potential 1 Free

Sensor system Pixel size (m)

Revisit cycle

Chl Cyp TSM CDOM Kd Turb

Multi-spectral mid-spatial resolution

LDCM1 30 16

Hyper-spectral EnMap1 30 On demand

PRISMA1 20 25 days

HySpIRI1 60 19 days

Specific objectives: Develop early warning indicators of microbiological hazards (E. coli); Extend satellite-based harmful algal bloom (HAB) early warnings for shellfish

farms; Develop hazard bulletins for the shellfish industry.

Further information: www.shelleye.org

This project aims to develop satellite Earth observation and simple modelling tools for monitoring and forecasting water quality for shellfish aquaculture

Improving the sustainability of shellfish aquaculture through satellite monitoring

Integration of satellite data with in situ measurements

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Low water Low water-2h

Low water+2h High water

E. coli in shellfish D

epth (m)

4 3 2 1

14

12

10

8

6

4

2

Physical and chemical characteristics of the water

Landsat 8 images of suspended solids

Detection of sewage plumes

18

Synthetic aperture radar image taken at high water on 12 June 2016

Sentinel-2 image taken at high water+1h on 5 November 2015

Mapping of E. coli risk

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Water quality bulletin service

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Algal bloom monitoring

Satellite monitoring

images

Biotoxin and E. coli forecasts

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SEAFOODTOMORROW is a €7m European Union Horizon 2020-funded project that aims to develop innovative

sustainable solutions for improving the safety and dietary properties of seafood in Europe.

Addressing the challenge to meet the growing market need for safe and sustainable seafood, the project will generate

new knowledge to develop commercial solutions for improving the socio-economic and environmental sustainability of

the European seafood production and processing industry.

Sustainable management of shellfish production areas through delineation of buffer zones

Development of predictive models for norovirus based on virus epidemiology, shellfish physiological status, temperature, hydrography, wastewater treatment and oceanography

Oyster biotag (heart rate/gap sensors)

Hydrographic dye tracing Drogue tracking

Further information: http://seafoodtomorrow.eu/

Example of multi-sensor platform for real-time monitoring in shellfish farm

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Instrumented with a SeaBird systems MicroCat sensor to collect data on temperature, dissolved oxygen, and salinity, fluorometer sensors for phytoplankton monitoring and current profilers.

Summary

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Characterisation of the variability in relative contributions from catchment (diffuse), sewage treatment works and CSOs requires carefully designed monitoring programmes to quantify adequately the relative magnitude of these sources through events.

The integration of tracers and environmental microbiology provides accurate quantitative information on individual sources and the movement of sewage pollution in the marine environment.

A significant amount of environmental information is available within satellite image archives.

The state of the science is sufficiently advanced to produce satellite remote sensing‐based water quality information at multiple spatial and temporal scales to benefit shellfish farming.

Acknowledgements

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Reports and papers:

carlos.campos@cefas.co.uk

Tel: 01305 206749

Food Standards Agency

Defra

BBSRC/NERC

Cefas Seedcorn