WOLFGANG SCHÖPP

The RAINS model:

Modelling concept and problem framing

Cost-effectiveness needs integration

• Economic/energy development (projections)

• State of emission controls, available technologies, costs

• Atmospheric processes

• Environmental sensitivities

• Health impacts

The RAINS model:Scenario analysis mode

Energy/agriculture projections

Emissions

Emission control options

Atmospheric dispersion

Costs

Driving forces

Health & environmental impact indicators

A multi-pollutant/multi-effect framework

√√√√Health impacts:- PM

Primary PM

via secondary aerosols√√√√√√√√√√√√√√√√

NH3VOCNOxSO2

√√√√√√√√√√√√Acidification

√√√√√√√√Eutrophication

√√√√√√√√- Ozone

√√√√√√√√Vegetation damage: - Ozone

RAINS: A modular approach

Economicactivities

Emission controlpolicies

Agriculture

NOx emissions

SO2 emissions

Solvents, fuels,industry

Energy use

NH3 dispersion

S dispersion

VOC emissions

NH3 emissions

Transport

Critical loadsf. acidification

Critical loads f.eutrophicationNOx dispersion

O3 formation

NH3 control& costs

NOx/VOC control&costs

VOC control& costs

Emission control costs

Critical levelsfor ozone

Environmentaltargets

Primary PM dispersionOther activities PM control

& costs

Primary PM emissions

Secondary aerosols

PM Population exposure

SO2 control& costs

NOx control& costs

O3 Populationexposure

Economicactivities

Emission controlpolicies

Agriculture

NOx emissions

SO2 emissions

Solvents, fuels,industry

Energy use

NH3 dispersion

S dispersion

VOC emissions

NH3 emissions

Transport

Critical loadsf. acidification

Critical loads f.eutrophicationNOx dispersion

O3 formation

NH3 control& costs

NOx/VOC control&costs

VOC control& costs

Emission control costs

Critical levelsfor ozone

Environmentaltargets

Primary PM dispersionOther activities PM control

& costs

Primary PM emissions

Secondary aerosols

PM Population exposure

SO2 control& costs

NOx control& costs

O3 Populationexposure

Environmental impacts

For PM2.5

Endpoint: annual mean concentrations of PM2.5 composed of

• Primary emissions of PM2.5 from anthropogenic sources

• Secondary inorganic aerosols (ammonium sulfate, ammonium nitrate) due to precursors SO2, NOx, NH3

• Water associated with secondary inorganics

• Secondary organic aerosols (from VOC emissions)

• Natural background (mineral, sea salt, organic matter)

• A fraction that is chemically not identified by the measurements

• Thus: calculations do not reproduce complete observed mass

Endpoint: annual mean concentrations of PM2.5 composed of

• Primary emissions of PM2.5 from anthropogenic sources

• Secondary inorganic aerosols (ammonium sulfate, ammonium nitrate) due to precursors SO2, NOx, NH3

• Water associated with secondary inorganics

• Secondary organic aerosols (from VOC emissions)

• Natural background (mineral, sea salt, organic matter)

• A fraction that is chemically not identified by the measurements

• Thus: calculations do not reproduce complete observed mass – Focus on anthropogenic fraction!

Objectives of health impact assessment in RAINS

• Focus on cost-effectiveness of emission control strategies – judged against improvement in the effects of air pollution

• Quantification of health impacts in response to emission reductions, consistent approach for all of Europe

• RAINS does not address compliance with local short-term hot spot exceedances of air quality limit values (including NO2), if they are not directly health-relevant

Approach for PMEstimating the loss of life expectancy attributable to PM

• Endpoint: – Loss in statistical life expectancy – Related to long-term PM2.5 exposure, based on cohort studies– All-cause mortality data used,

main effect from cardio-vascular diseases

• Life tables provide baseline mortality for each cohort in each country

• For a given PM scenario: Mortality modified through Cox proportional hazard model using Relative Risk (RR) factors from literature

• From modified mortality, calculate life expectancy for each cohort and for entire population

Functional relationships for PMdeveloped for RAINS

PM2.5j Annual mean concentration of PM2.5 at receptor point jI Set of emission sources (countries)J Set of receptors (grid cells)pi Primary emissions of PM2.5 in country isi SO2 emissions in country ini NOx emissions in country iai NH3 emissions in country i�S,W

ij, �S,W,Aij, �W,A

ij, �Aij Linear transfer matrices for reduced and oxidized

nitrogen, sulfur and primary PM2.5, for winter, summer and annual

)2**2),1**3214

*1**1,0min(max(*5.0

)**(*5.0

**5.2

jiIi

Wijji

Ii

Wiji

Ii

Wij

iIi

Siji

Ii

Sij

iIi

Aij

Iii

Aijj

knckscac

na

spPM

++−+

+++

++=

���

��

��

∈∈∈

∈∈

∈∈

νσα

να

σπ

Validation of PMCAFE baseline 2020 [�g/m3]

0

5

10

15

20

25

0 5 10 15 20 25

EMEP model

RA

INS

app

roxi

mat

ion

“Urban impact” on PM2.5 in ViennaSource: Puxbaum et al., 2003

0

1

2

3

4

5

6

7

Jun-9

9Ju

l-99

Aug-99

Sep-99

Oct-99

Nov-99

Dec-99

Jan-0

0

Feb-00

Mar-00

Apr-00

May-00

µg/m

³ NH4, SO4Na, CaOCBC

Urban impact PM2.5 (difference between urban and rural twin site)

0

1

2

3

4

5

6

7

Jun-9

9Ju

l-99

Aug-99

Sep-99

Oct-99

Nov-99

Dec-99

Jan-0

0

Feb-00

Mar-00

Apr-00

May-00

µg/m

³ NH4, SO4Na, CaOCBC

�PMsub-grid = (EDsub-grid - EDEMEP) * (k1 - k2*Vwind)

�PMsub-grid .. Difference in PM concentration between sub-grid (urban/rural) area and EMEP grid average

EDx … Emission density for low sources (x=urban/rural/EMEP grid average)

Vwind … Annual mean wind speed in EMEP grid cellk1, k2 … Parameters derived from the City-Delta ensemble

model

Functional relationship for PM

Input data

Emissiondensities

Population density ratios

Wind speed

Urban increments

Input to life expectancy calculation

• Urban/rural population in each 50*50 km grid cell –LANDSCAN, etc

• Population data by cohort and country, 2000-2050 – UN

• Life tables (by country) – UN

• Air quality data: annual mean concentrations – PM2.5 (sulfates, nitrates, ammonium, primary particles),

excluding SOA, natural sources

– 50*50 km over Europe, rural + urban background

– for any emission scenario 1990-2020

Loss in life expectancyattributable to anthropogenic PM2.5 [months]

Loss in average statistical life expectancy due to identified anthropogenic PM2.5Average of calculations for 1997, 1999, 2000 & 2003 meteorologies

2000 2010 2020

Loss in life expectancyattributable to anthropogenic PM2.5 [months]

0

3

6

9

12

15

Aus

tria

Bel

gium

Den

mar

k

Finl

and

Fran

ce

Ger

man

y

Gre

ece

Irela

nd

Italy

Luxe

mbo

urg

Net

herla

nds

Por

tuga

l

Spa

in

Sw

eden UK

Tota

l EU

-15

Cze

ch R

ep.

Est

onia

Hun

gary

Latv

ia

Lith

uani

a

Mal

ta

Pol

and

Slo

vaki

a

Slo

veni

a

Tota

l NM

S

Tota

l EU

-25

2000 2010 2020

PM25 CP_CLE 2020

PM25 NL-CLE for EU 2020

Difference in PM25

NHx deposition 2020 (OPS)