in in Environmental Environmental

ModelingModelingandand

IndicatorsIndicators

ManagingManaging

As far as … As far as … mathematics refer mathematics refer to reality, they are to reality, they are not certain; and as not certain; and as far as they are far as they are certain, they do certain, they do not refer to not refer to reality.reality.Einstein’s remarks to the Prussian Academy of Sciences

Einstein gotEinstein gotit rightit right

Why does uncertainty Why does uncertainty matter?matter?

10.6 million tons of SOx emitted in 2003 in the U.S.

14.4 ug m2 Hg dry deposited in Lake Waccamaw, NC per year

0.131 IQ loss per ppm increase in Hg

U.S. EPA’s Mercury Rule

Credible Credible metrics metrics Credible Credible decisionsdecisions

Consideration of Uncertainty in

Some Air Quality Examples

Current AQI - Ozone

Current AQI - Particle Pollution(PM2.5)

Current AQI – Particle Pollution(PM2.5)

Current AQI - Particle Pollution(PM2.5)

Current AQI - Particle Pollution(PM2.5)

Current: 1-day forecast guidance for ozone Developed and deployed initially for

Northeastern US, September 2004 Deploy Nationwide by 2009

Intermediate (5-7 years): Develop and test capability to forecast particulate matter

concentration • Particulate size < 2.5 microns

Longer range (within 10 years): Extend air quality forecast range to 48-72 hours Include broader range of significant pollutants

National Air Quality ForecastingPlanned Capabilities

EnviroFlash

• EnviroFlash gives individuals instant information that they can customize for their own needs, allowing them to protect their health and their family’s.

• Air quality information allows them to adjust your lifestyle when necessary on unhealthy air quality days.

• EnviroFlash is especially helpful for people with sensitivities, such as the young, people with asthma, and the elderly.

Satellite Data

• Emerging source of data(1-10 km grids)

• Spatial and Temporal Gaps

• Algorithm uncertainties(clouds)

• Routinely available data

Can Satellite Data help assess influences of large wildfires on surface PM2.5 for public health assessments?

Data source: NASA MODIS-Aqua

Alaskan Fire Complexes

June 30, 2004

18 July 2004 Smoke from Alaskan/Yukon Fires Over U.S.

19 July 2004 Smoke from Alaskan/Yukon Fires Impact U.S.

12 September 2002

MODIS AODLinear Interpolation Surface PM2.5 Monitors

Satellite measurements capture important spatial gradients and meteorology influences, extremely important for public health side of air quality.

“Real-Time” Fire and Smoke

Information

Two Different User

Perspectives

Of Uncertainty

CMAQ Uncertainty

Forecastingversus

Environmental Decision Making(i.e. Developing AQ Implementation Plans

CMAQ Modeling System

SMOKE

Anthro and Biogenic Emissions processing

Fifth Generation Mesoscale Model (MM5)

(WRF in 2005)

CMAQ AQ Model-

Chemical-Transport Computations

Met-Chem Interface Processor (MCIP)

Met. data prep

NOAA Weather Observations

EPA Emissions Inventory

Hourly 3-D Gridded Chemical Concentrations

Observed Forecast

7/21/04: 8-hour Peak Ozone

7/22/04: 8-hour Peak Ozone

ForecastObserved

Forecast and Observed Surface Ozone Distributions

June 9th Peak Ozone Forecast

-125 -120 -115 -110 -105 -100 -95 -90 -85 -80 -75 -70 -65

25

30

35

40

45

8.02.0

1.6

1.8

5.6

1.6

1.7

1.8

9.4

3.1

7.9

11.5

4.14.0 6.5

5.1 9.44.7

9.6

3.2

3.7

7.9

0.6

4.6

0.7

6.46.76.4

3.9

5.6

5.4

7.0

2.1

11.6

5.9

1.6

15.214.55.1

15.713.5

3.5

3.1

4.7

2.3

4.04.15.13.14.54.2

5.9

4.34.3 4.2

1.6

4.2

8.8

4.0

11.6

14.2

7.7

3.5

9.9

11.412.0

15.1

10.0

8.9

13.8

13.3

11.4

13.8

7.7

5.8

9.89.3

11.58.9

13.2

2.7

8.9

3.2

2.1

12.0

8.0

6.510.6

2.7

3.3

7.9

5.2

6.2

7.5 7.68.7

6.1

8.81.0

0.9

1.2

8.3

15.2

3.9

1.6

12.8

3.2

1.9

2.3

1.31.7

1.4

1.2

0.7

1.9

0.8

0.9

1.5

1.5

1.5

1.3

4.3

10.7

1.7

10.1

1.5

1.2

2.1

0.5

1.5

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

SO 4 from C astnet and STNLM 8, Ju ly 17 - Aug 13, 2001

CMAQ

REMSAD

Observed Data

Sulfate PM July 17- Aug. 13 Average

Monthly Average SO4 for Ohio River Valley (2001)

0.00

2.00

4.00

6.00

8.00

10.00

12.00

[SO

4 ] u

g/m

3

Observations(CASTNET)

CMAQ

REMSAD

CMAQ’s predictions are much closer to the observations than REMSAD’s

Models in Environmental RegulatoryDecision Making

Committee on Models in the Regulatory Decision Process

Board on Environmental Studies and Toxicology

Division on Earth and Life Studies

June 2007

Life-Cycle of a Model

Problem Formulation

Conceptual Model

Constructed Model

Model Use

Life-Cycle Model Evaluation

All models should have a life-cycle evaluation plan of a size and complexity commensurate with its regulatory significance

Plan should address how model evaluation will occur throughout a model’s life cycle

The committee did not make organizational recommendations of how EPA should achieve this

A conceptual commitment to life cycle model evaluation is needed

Two ApproachesRepresent uncertainties probabilistically and calculate the probability distribution of any model result

difficult to carry out obscures the sensitivities of the outcome to

individual sources of uncertainty

Scenario assessment and/or sensitivity analysis often more transparent may ignore important information corresponding to

other scenarios not included in assessment and whatever is known about their relative likelihoods

Assessing/Communicating Uncertainty

Assessing/Communicating Uncertainty

Many instances require probabilistic methods to properly characterize uncertainties, propagate them through the modeling exercise, and clearly communicate the overall uncertainties

Recommend the use of case-specific hybrid approaches in which some unknown quantities are treated probabilistically, and others can be manipulated in a scenario-assessment mode by the decision makers

Requires communication between modelers and decision-makers

Examples of TransAtlantic Examples of TransAtlantic Activity on Uncertainty Activity on Uncertainty AnalysesAnalyses• Harmoni-CA guidance on Harmoni-CA guidance on uncertainty for Water Framework uncertainty for Water Framework DirectiveDirective

• Dutch National Institute for Dutch National Institute for Public Health and the Public Health and the Environment (RIVM) work on Environment (RIVM) work on uncertainty in environmental uncertainty in environmental informationinformation

• TransAtlantic Uncertainty TransAtlantic Uncertainty Colloquium (TAUC) in 2006 in Colloquium (TAUC) in 2006 in Washington, DCWashington, DC

• US EPA call for research in US EPA call for research in uncertainty in integrated models uncertainty in integrated models

Harmoni-CA guidance on Harmoni-CA guidance on uncertainty for Water uncertainty for Water Framework DirectiveFramework Directive““Estimates of … level of Estimates of … level of confidence and precision of … confidence and precision of … results provided by … monitoring results provided by … monitoring programmes shall be given ..”programmes shall be given ..”Water Framework

Directive

Asked to estimate Asked to estimate vulnerability to vulnerability to pollution in a pollution in a Copenhagen Copenhagen catchment, 5 catchment, 5 consultants gave 5 consultants gave 5 different estimatesdifferent estimates

Refsgaard et al, 2005. Harmoni-CA Guidance to Uncertainty Analysis

Present value of Present value of income loss/child income loss/child = $= $8,8008,800 * d(IQ) * d(IQ)

d(IQ) = d(IQ) = 0.1310.131 * c(Hg) * c(Hg) in maternal hairin maternal hair

c(Hg) = c(Hg) = f f ((

))

• c(MeHg) in fishc(MeHg) in fish• fish consumption ratefish consumption rate• no. of pregnant women no. of pregnant women

who consume fish who consume fish

Eulerian air Eulerian air model (36 x model (36 x 36 km grid)36 km grid)

Hg depositionHg deposition

US EPA call for research in US EPA call for research in uncertainty in integrated uncertainty in integrated models models How does How does

uncertainty uncertainty propagate propagate withinwithin and and acrossacross models models used to develop used to develop metrics?metrics?

US EPA call for research in US EPA call for research in uncertainty in integrated modelsuncertainty in integrated models

Examples of proposed research

• using Sensitivity Analysis for air quality models,

• using Bayesian approaches to deal with discount rates to analyze the economic impacts of climate change, and

• using Monte Carlo to look at probability distributions in mercury regulation.

2006 TransAtlantic Uncertainty 2006 TransAtlantic Uncertainty Colloquium (TAUC) in Washington, Colloquium (TAUC) in Washington, DCDC

To discuss the legal, To discuss the legal, scientific, and political scientific, and political consequences of consequences of uncertainty in uncertainty in environmental models and environmental models and metrics from the metrics from the perspective of the EC and perspective of the EC and the USthe US

See http://www.modeling.uga.edu/tauc/

EC-US EPA EC-US EPA Implementing Implementing ArrangementArrangementCooperation may focus on Cooperation may focus on methods to:methods to:

• formally analyze and manage formally analyze and manage uncertainty; anduncertainty; and

• provide stakeholders with provide stakeholders with uncertainty information so uncertainty information so they may engage fully in they may engage fully in environmental policy-makingenvironmental policy-making

Adapted from 2007 EC-EPA Implementing Arrangement

Opportunities for Opportunities for continued collaborationcontinued collaborationJoint call for research on Uncertainty Joint call for research on Uncertainty AnalysesAnalyses Funding institutions across US and EU could Funding institutions across US and EU could collaborate on similar language (encouraging collaborate on similar language (encouraging TransAtlantic investigation), jointly review TransAtlantic investigation), jointly review proposals, and co-host workshopsproposals, and co-host workshops

Staff ExchangeStaff Exchange Institutionalize program to allow Institutionalize program to allow environmental agency staff to conduct environmental agency staff to conduct discrete, short-term projects in uncertainty discrete, short-term projects in uncertainty analyses and indicator developmentanalyses and indicator development