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Environmental risk assessment: from perception to decision
Paul Kwan-sing LAM
Department of Biology and Chemistry City University of Hong Kong
Hong Kong State Key Laboratory in Marine Pollution Hong Kong
Challenges in the information age
Challenges in the information age
Ability to collect relevant information
Sources of information Internet Television programmes, newspaper,
magazines Politicians, NGOs, Green groups, Books Seminars, forums and talks Quasi-scientific literature Scientific publications in academic journals
Ability to handle misinformation
Perception Vs Science
Fact or Fiction Myths or Truth
….virtually nothing left to fish from the seas by the middle of the century….?
Global Loss of Seafood Species %
of
spe
cie
s co
llap
sed
Years Source: Science/FAO
Global fisheries data (1950-2003)
Extrapolated long-term trend
..... Himalayan glaciers could melt to a fifth of current levels by 2035 (or 2350?)?....
http://pictures.howbits.com/the-unseen-effect-of-global-warming/
CHINESE WHITE DOLPHINS Chinese White Dolphins: 400 in 1990 80 in 1995 Extinction in 5 years' time
About US$ 1 million in 3 years
Population of Chinese White Dolphins > 1,200
CHINESE WHITE DOLPHINS
Ability to interpret information
Adopt a Risk-based approach
Management options
• Suspicion-based • Hazard-based • Risk-based*
• Risk-based, with cost-benefit considerations
*Risk = f (hazard x exposure)
Science Pre-caution
- HOW?
Management options
• Suspicion-based • Hazard-based • Risk-based*
• Risk-based, with cost-benefit considerations
*Risk = f (hazard x exposure)
Science Pre-caution
- HOW?
THE PRECAUTIONARY PRINCIPLE (North Sea Convention)
“accepting the principle of safeguarding the marine ecosystem of the North Sea by reducing polluting emissions of substances that are persistent, toxic and liable to bioaccumulate at source by the use of the best available technology and other appropriate measures…………….
PRECAUTIONARY PRINCIPLE (CONT.)
This applies especially when there is reason to assume that certain damage of harmful effects on the living resources of the sea are likely to be caused by such substances even when there is no scientific evidence to prove a causal link between emissions and effects (the principle of precautionary action)”
PRECAUTIONARY PRINCIPLE
Under-protection will lead to inadequate protection of ecological systems
Over-protection will lead to wastage of valuable resources which should be better targeted to protecting genuinely vulnerable and important systems. Not sustainable
Provide an estimate of the risk levels in a particular setting
Risk quotient (RQ) analysis Determine PEC or MEC PNEC
PEC/PNEC ratio 1: low risk PEC/PNEC ratio > 1: high risk
Risk characterization
Provide an estimate of the risk levels in a particular setting
Risk quotient (RQ) analysis Determine PEC or MEC PNEC
PEC/PNEC ratio 1: low risk PEC/PNEC ratio > 1: high risk
Risk characterization Predicted Environmental Concentration
Provide an estimate of the risk levels in a particular setting
Risk quotient (RQ) analysis Determine PEC or MEC PNEC
PEC/PNEC ratio 1: low risk PEC/PNEC ratio > 1: high risk
Risk characterization Measured Environmental Concentration
Provide an estimate of the risk levels in a particular setting
Risk quotient (RQ) analysis Determine PEC or MEC PNEC
PEC/PNEC ratio 1: low risk PEC/PNEC ratio > 1: high risk
Risk characterization Predicted No Effect
Concentration
How to derive PNECs
(Predicted No Effect Concentration)
How to derive PNECs
Some examples
Waterbird Study (Herons and Egrets)
Map of South China showing the sampling sites
Quanzhou
Xiamen
Hong Kong
Collection of eggs from nests located
on top of tall bamboos using a cherry
picker
Collection of eggs from nests located
on tall trees by a professional climber
Analyses of POPs
POPs
HCB, Endrin, Dieldrin,
Aldrin, Heptachlor,
Mirex, PCBs,
Chlordane, DDTs
Toxaphene Co-PCB &
PCDD/Fs
GCMS-NCI (negative chemical ionization)
HRGC-HRMS Two micro-ECD
with dual-column
Gas Chromatograph
Derivation of threshold effects level
BIOLOGICAL EFFECTS OF DDE
2.5 3.0 3.5 4.0 4.5 5.0-10
0
10
20
30
40
50Henny et al. (1984)Findholt (1984)Findholt & Trost (1985)
Log10 DDE (ng/g, wet weight)
% R
ed
uc
tio
n i
n S
urv
iva
l o
f Y
ou
ng
2.5 3.0 3.5 4.0 4.5 5.0-10
0
10
20
30
40
50Henny et al. (1984)Findholt (1984)Findholt & Trost (1985)
Log10 DDE (ng/g, wet weight)
% R
ed
uc
tio
n i
n S
urv
iva
l o
f Y
ou
ng
BIOLOGICAL EFFECTS OF DDE
2.5 3.0 3.5 4.0 4.5 5.0-10
0
10
20
30
40
50Henny et al. (1984)Findholt (1984)Findholt & Trost (1985)
Log10 DDE (ng/g, wet weight)
% R
ed
uc
tio
n i
n S
urv
iva
l o
f Y
ou
ng
BIOLOGICAL EFFECTS OF DDE
2.5 3.0 3.5 4.0 4.5 5.0-10
0
10
20
30
40
50Henny et al. (1984)Findholt (1984)Findholt & Trost (1985)
Log10 DDE (ng/g, wet weight)
% R
ed
uc
tio
n i
n S
urv
iva
l o
f Y
ou
ng
BIOLOGICAL EFFECTS OF DDE
2.5 3.0 3.5 4.0 4.5 5.0-10
0
10
20
30
40
50Henny et al. (1984)Findholt (1984)Findholt & Trost (1985)
Log10 DDE (ng/g, wet weight)
% R
ed
uc
tio
n i
n S
urv
iva
l o
f Y
ou
ng
BIOLOGICAL EFFECTS OF DDE
2.5 3.0 3.5 4.0 4.5 5.0-10
0
10
20
30
40
50Henny et al. (1984)Findholt (1984)Findholt & Trost (1985)
Estimated threshold
Log10 DDE (ng/g, wet weight)
% R
ed
uc
tio
n i
n S
urv
iva
l o
f Y
ou
ng
Deviation from zeroOne sample t-test:
t=1.92, P=0.0421000 ng/g wet wt.
Estimated threshold:
1,000 ng/g wet wt.
BIOLOGICAL EFFECTS OF DDE
Risks of DDE to Birds
Relationship between [DDE] in eggs of piscivorous birds and % fledging success for a
sustainable population showing the regression line and 95% confidence intervals.
DDE
2.5 3.0 3.5 4.0 4.5 5.00
50
100
150
200
Log concentration (ng/g wet wt.)
Su
rviv
al
of
yo
un
gfl
ed
ged
(%
)
Risks of DDE to Birds
Relationship between [DDE] in eggs of piscivorous birds and % fledging success for a
sustainable population showing the regression line and 95% confidence intervals.
DDE
2.5 3.0 3.5 4.0 4.5 5.00
50
100
150
200
Log concentration (ng/g wet wt.)
Su
rviv
al
of
yo
un
gfl
ed
ged
(%
)
(3.45)
Estimated threshold:
2,818 ng/g wet wt.
Risks of DDE to South China Waterbirds
DDE
Log concentration (ng/g wet wt.)
2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8
Cu
mu
lati
ve P
rob
ab
ilit
y%
0.1
1
10
30
50
70
90
99
99.9
Hong Kong
Xiamen
Quanzhou
Threshold (3.45)
Quanzhou
Xiamen
Hong Kong
Quanzhou
Xiamen
Hong Kong
Fish-eating
birds
Herons
Risks of DDE to South China Waterbirds
DDE
Log concentration (ng/g wet wt.)
2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8
Cu
mu
lati
ve
Pro
bab
ilit
y%
0.1
1
10
30
50
70
90
99
99.9
Hong Kong
Xiamen
Quanzhou
Threshold (3.45)
(2818 ng/g) Fish-eating birds
鹭鸟 吃鱼的鸟类
(1000 ng/g) Herons
Ability to extrapolate
Marine cetacean
Indo-Pacific Humpback Dolphin Sightings () in Pearl River Estuary (AFCD).
Hong Kong
Source: AFCD
Exposure Pathway
Sewage Outfall
Contaminated Mud Pit
Sea Water
Sediment
Contaminated Mud Pit
Fish Samples
Lionhead
(Collichthys lucida)
Croceine croaker
(Pseudosciaena crocea)
Mullet (Mugil sp.)
Croaker (Johnius sp.)
Anchovies
(Thryssa sp.)
Hairtail
(Trichiurus sp.)
Diet of dolphin comprise >90% fish
Threshold effect levels (No Observable Adverse Effect Levels; NOAELs)
Safety factors Scaling factor
RfD (human) TRV (other mammals)
Laboratory Toxicological Data
Threshold effect levels (No Observable Adverse Effect Levels; NOAELs)
Safety factors Scaling factor
RfD (human) TRV (other mammals)
Laboratory Toxicological Data
参考剂量(人类)
Variable Values
Contaminant concentration in
fish (CF)
Maximum; 95th and 50th
percentiles
Ingestion rate (IR) 0.076 kg/day
Fraction ingested (FI) 0.007-0.4
Exposure frequency (EF) 350 days/year
Exposure duration (ED) 70 years
Body weight (BW) 60 kg
Average time (AT) 25,550 days
Variable Values
Contaminant concentration in
fish (CF)
Maximum; 95th and 50th
percentiles
Ingestion rate (IR) 9 kg/day for dolphin
Fraction ingested (FI) 0.9 for dolphins
Exposure frequency (EF) 365 days/year
Exposure duration (ED) 35 years for dolphin
Body weight (BW) 185 kg for dolphin
Average time (AT) 12,775 days for dolphin
Variable Values
Contaminant concentration in
fish (CF)
Maximum; 95th and 50th
percentiles
Ingestion rate (IR) 9 kg/day for dolphin
Fraction ingested (FI) 0.9 for dolphins
Exposure frequency (EF) 365 days/year
Exposure duration (ED) 35 years for dolphin
Body weight (BW) 185 kg for dolphin
Average time (AT) 12,775 days for dolphin
Variable Values
Contaminant concentration in
fish (CF)
Maximum; 95th and 50th
percentiles
Ingestion rate (IR) 9 kg/day for dolphin
Fraction ingested (FI) 0.9 for dolphins
Exposure frequency (EF) 365 days/year
Exposure duration (ED) 35 years for dolphin
Body weight (BW) 185 kg for dolphin
Average time (AT) 12,775 days for dolphin
Threshold effect levels (No Observable Adverse Effect Levels; NOAELs)
Safety factors Scaling factor
RfD (human) TRV (other mammals)
Laboratory Toxicological Data
Threshold effect levels (No Observable Adverse Effect Levels; NOAELs)
Safety factors Scaling factor
RfD (human) TRV (other mammals)
Laboratory Toxicological Data
Derivation of MAC based on TRV
Toxicity Reference Values (TRV) were derived for the dolphin based on NOAELs from
mammalian surrogates following Sample et al. (1996) as follows:
Scaling factor: TRVr = NOAELt (BWt/BWr)1/4
Where: TRVr = Toxicity reference value for receptor species (mg kg-1
ww day-1
);
NOEAL = No observable adverse effect level for test species (mg kg-1
ww
day-1
);
BWr = Body weight of the receptor species (kg ww);
BWt = Body weight of the test species (kg ww);
Do not procrastinate - Extrapolate
Do not procrastinate - Extrapolate
(if cannot be based on science, should at least be transparent)
Ability to handle uncertainties
PEC or MEC RQ = PNEC
Sources of uncertainties
Measurement Understanding Time/space
Measurement Understanding Time/space
Measurement Understanding Biological variation
Risk characterization Determination of PEC/PNEC or MEC/PNEC ratio
Frequency
PEC and MEC
Frequency
PNEC
PEC, MEC and PNEC are not simple single numbers, but ranges, and even frequency distributions
RISK ASSESSMENT - CRITICISMS
• Too complex; too slow
• Too simplistic; too naive
• Too opaque
• Too unrealistic
Back to the precautionary principle;
Don’t wait for science
Ability to simplify complex issues
Ability to simplify complex issues
One example
Does RQ indicate unacceptable risk? Step 1: Examine worst-case RQ (i.e. highest MEC/lowest PNEC) If RQ > 1 => requires further estimate; If RQ < 1 => little concern
Does RQ indicate unacceptable risk? Step 2: Examine best-case RQ (i.e. lowest MEC/highest PNEC) If RQ > 1 => manage; If RQ < 1; refine estimates (?)
Does RQ indicate unacceptable risk? Step 3: Apply re-sampling techniques to estimate probability that RQ exceeds critical values and check sensitivity of distribution assumptions
Risk characterization Determination of PEC/PNEC or MEC/PNEC ratio
Frequency
PEC and MEC
Frequency
PNEC
PEC/PNEC or MEC/PNEC ratio
Ratio 1: low risk
Ratio > 1: high risk)
Frequency
RQ
RISK ASSESSMENT Feasible Affordable Scientifically-based Transparent
RISK ASSESSMENT Feasible Affordable Scientifically-based Transparent
FAST
Ability to adopt a multidisciplinary
approach
Framework for Risk Assessment and Management
Dose-response assessment (Toxicity assessment)
Exposure assessment
Risk characterization
Risk communication
Risk management
Hazard identification
Framework for Risk Assessment and Management
Dose-response assessment (Toxicity assessment)
Exposure assessment
Risk characterization
Risk communication
Risk management
Hazard identification
Science
Framework for Risk Assessment and Management
Dose-response assessment (Toxicity assessment)
Exposure assessment
Risk characterization
Risk communication
Risk management
Hazard identification
Science
Environmental economics
Ability to separate science from politics in decision making
Nature Conservation Policy Statement (Hong Kong)
Our nature conservation policy is to regulate, protect and manage natural resources that are important for the conservation of biological diversity of Hong Kong in a sustainable manner, taking into account social and economic considerations, for the benefit and enjoyment of the present and future generations of the community
Why should we conserve?
Intrinsic rights to live
Heritage for future generations
Biodiversity
Ecosystem functions
Ecosystem functions
Nutrient cycling Waste treatment Pollination Biological control Refugia Raw materials Genetic resources Recreation Cultural
Gas regulation Climate regulation Disturbance regulation Water regulation Water supply Erosion control Sediment retention Soil formation Food production
Ecosystem functions
Goods and services
Clean water Clean air Clean food Safe environment
NUMBER OF SPECIES
‘REDUNDANT SPECIES’ ‘RIVET’ HYPOTHESIS ‘IDIOSYNCRATIC’ HYPOTHESIS HYPOTHESIS
Three hypothetical relationships between the rate of an ecosystem process (e.g. primary production, rate of decomposition) and ecosystem species richness
What should we conserve?
“Hot spots” of high diversity
Rare species
Representative species assemblages
What should we conserve?
“Hot spots” of high diversity
Rare species
Representative species assemblages
Can we achieve all?
A Conservation Policy Why should we conserve? What should we
conserve? What is acceptable and
what is not?
A Conservation Policy Why should we conserve? What should we
conserve? What is acceptable and
what is not?
Conclusion - Ability to: collect relevant information handle misinformation interpret information extrapolate handle multiple stressors (mixtures) handle uncertainties simplify complex issues separate science from politics in
decision making
Acknowledgements Dr. Nobuyoshi Yamashita (AIST, Japan), Prof. John Giesy (University of Saskatewan , Canada), Prof. Shinsuke Tanabe (Ehime University, Japan), Prof. Kannan Kurunthachalam (SUNY, USA), Dr. Sachi Taniyasu (AIST, Japan), Dr. Yuichi Miyake (AIST, Japan), Prof. Des Connell (Griffith University, Australia), Dr. Keerthi S. Guruge (NIAH, Japan), Mr. Leo W.Y. Yeung (CityU, HK), Mr. Ridge K.F. Lau (CityU, HK), Dr. James C.W. Lam (CityU, HK), Dr. Margaret Murphy (CityU, HK) Dr. Iris M.K. So (CityU, HK), Dr. Bruce Richardson (CityU, HK) K.S. Cheung, Ivan Chan, Joseph Sham (AFCD) Stephanie Ma (EPD)
Research Grants Council, HK; City University of Hong Kong;
Agriculture, Fisheries and Conservation Dept., HKSAR
Thank You