rains review 2004 the rains model: health impacts of pm
Post on 19-Dec-2015
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Main issues
• Methodology for health impact assessment
• Dispersion modelling for PM
• Quantification of population exposure in cities
• Uncertainties
Estimating the loss of life expectancy in RAINSApproach
• Endpoint:
– Loss in statistical life expectancy
– Related to long-term PM2.5 exposure, based on cohort studies
• 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
Input to life expectancy calculation
• Life tables (by country)
• Population data by cohort and country, 2000-2050
• Urban/rural population in each 50*50 km grid cell
• Air quality data: annual mean concentrations
– PM2.5 (sulfates, nitrates, ammonium, primary particles), excluding SOA, natural sources
– alternatively PMcoarse, PM10, black carbon
– 50*50 km over Europe, rural + urban background
– for any emission scenario 1990-2020
• Relative risk factors
Critical assumptions reviewed by TF on Health
• Choice of appropriate RR and shape of C-R curve
• Mortality related to PM2.5 (mass)
• PM2.5 includes effects from SO2, NO2, carbonaceous, diesel
• Are ozone effects independent? (SOA are excluded, thus no potential double-counting of ozone effects)
• Extrapolation beyond 35 μg/m3 PM2.5
• Treatment of natural background
• Exposure calculation: (Urban) background concentrations (annual mean) * population
• No effects for younger than 30 years
• Quantification of uncertainties (CI of RR, alternative impact theories, potential biases, linearity, etc.)
• Regional scale
• Urban scale
• Uncertainties
Modelling of health-relevant PM formation and transport in the atmosphere
Atmospheric dispersion of PM
• Health-relevant metric: annual mean PM2.5 mass
• Performance of EMEP Eulerian model for PM
– TFMM 2003 review:
• Rural sulphates: ok.
• Rural nitrates: observations missing, model probably ok.
• Anthropogenic primary PM: to be demonstrated
• Secondary organic aerosols: missing
• Natural contributions: missing
– Thus: not able to reproduce observed total PM mass, but possible to track PM changes due to anthropogenic emissions
S-R relations for RAINS
Linearity of changes in PM due to changes in emissions is crucial for the mathematical design of RAINS
• 87 model experiments with the new EMEP model:
– Response of European PM2.5/10 concentrations to changes in SO2, NOx, VOC, NH3, PPM2.5/10 emissions
– For German, Italian, Dutch, UK and European emissions
– 3 emission scenarios:
• CLE (current legislation 2010) = CAFE baseline for 2010
• MFR (maximum technically feasible reductions 2010
• UFR (ultimately feasible reductions) = MFR/2
– Regional scale
– Urban scale
– Uncertainties
Modelling of health-relevant PM formation and transport in the atmosphere
City-Delta objectives
• Identify systematic differences in urban AQ results computed by
– regional scale models
– urban scale models.
• Identify differences in model results (deltas) across
– Emissions (2000, 2010, maximum feasible reductions),
– cities in Europe,
– scales,
– models,
– pollutants (PM, O3, for health-relevant metrics).
• 17 models, 8 cities, 9 scenarios
PM10 as a function of emission density
PM10 concentration as a function of emission density,
primary PM10 from UK road transport (2001)
0
5
10
15
20
25
30
35
40
0 1 2 3 4 5
PM10 emission density, t km -2 yr-1
5 km x 5 km
[PM
10],
ug
m-3
Roadside sites
Urban sites
Rural sites
PM10 concentration as a function of emission density,
primary PM10 from UK road transport (2001)
0
5
10
15
20
25
30
35
40
0 1 2 3 4 5
PM10 emission density, t km -2 yr-1
5 km x 5 km
[PM
10],
ug
m-3
Roadside sites
Urban sites
Rural sites
“Urban impact” on PM2.5 in ViennaSource: Puxbaum et al., 2003
Urban Impact PM2.5
0
1
2
3
4
5
6
7
Jun-
99
Jul-9
9
Aug-9
9
Sep-9
9
Oct-99
Nov-9
9
Dec-9
9
Jan-
00
Feb-0
0
Mar
-00
Apr-0
0
May
-00
µg
/m³ NH4, SO4
Na, CaOCBC
Urban Impact PM2.5
0
1
2
3
4
5
6
7
Jun-
99
Jul-9
9
Aug-9
9
Sep-9
9
Oct-99
Nov-9
9
Dec-9
9
Jan-
00
Feb-0
0
Mar
-00
Apr-0
0
May
-00
µg
/m³ NH4, SO4
Na, CaOCBC
– Regional scale
– Urban scale
– Uncertainties
Modelling of health-relevant PM formation and transport in the atmosphere
Euro-Delta model inter-comparison
• Evaluate the performance of regional-scale atmospheric dispersion models against observations
• Identify differences in model results (deltas) across
– emissions (2000, 2010, maximum feasible reductions),
– regions in Europe,
– models,
– pollutants.
• Put the EMEP model performance into perspective, derive quantitative information for uncertainty analysis
Annual mean PM2.5 and sulphate levels (μg/m3)9 German sites, as computed by the Euro-Delta models
PM2.5 Sulphate
Observations are shown in black
PM2.5 responses of the Euro-Delta models
Receptor regions:
00 .. Europe01 .. Austria08 .. France09 .. Germany12 .. Italy 14 .. Netherlands19 .. Spain
22 .. British Isles
Further work
• Develop regional source-receptor (S-R) relationships for PM
• Complete City-Delta analysis for PM, develop urban-regional SR relationships
• Investigate inter-annual meteorological variability
• Quantify uncertainties, explore use of ensemble-model
• Finalize uncertainty analysis for health-impact analysis