Federal Department of the Environment, Transport, Energy and Communications DETEC Federal Office for the Environment FOEN Modelling the spatial distribution of particulate matter in Switzerland 26. October 2006 Air Pollution Control and NIR Division Rudolf Weber, Air Quality Management Section Swiss Federal Office for the Environment

2 11th EIONET Workshop AQ Rudolf Weber Is particulate matter a problem in Switzerland? Switzerland WHO AQ guidelines 2005 EU (1999/30/EC) Annual mean 20 μg/m 3 40 μg/m 3 #days > 50 μg/m Air quality limit values

3 11th EIONET Workshop AQ Rudolf Weber Measurements More than 60 stations

4 11th EIONET Workshop AQ Rudolf Weber Measured PM10-levels in Switzerland Annual mean > 20 μg/m 3 (CH) 60%61%74%93%70%71% Annual mean > 40 μg/m 3 (EU) 0% 1% Maximal annual mean #24h-means >50μg/m3 CH EU 90% 9% 97% 5% 95% 8% 100% 20% 90% 6% 78% 14% Maximal daily mean

5 11th EIONET Workshop AQ Rudolf Weber PM10: Evolution => Constant since 2000

6 11th EIONET Workshop AQ Rudolf Weber Maps Why maps? Better visualization Population exposure Models based on emission grids allow reduction scenarios Models 3d chemical models simple dispersion, no chemistry interpolation from measured data

7 11th EIONET Workshop AQ Rudolf Weber Modelling concept BUWAL report: UM-169, 2003 „Modelling of PM10 and PM2.5 ambient concentrations in Switzerland“ Source-receptor matrix; 1-year meteorology Emission grids with temporal cycles Primary secondary (from precursor maps) Only annual mean values

8 11th EIONET Workshop AQ Rudolf Weber Emissions Emissions of primary particles Road: traffic model „bottom-up“ Rail: „top-down“ Air: up to 200 m, ZH, GE Industry, households, agriculture/forestry: „top- down“, area statistics Secondary particles 1) Concentration maps of precursors, spatially smoothed (reaction time) NO 2 => NH 4 NO 3 SO 2 => (NH 4 ) 2 SO 4 2) Emission grids of precursors anthropogenic und biogenic VOC

9 11th EIONET Workshop AQ Rudolf Weber Background Background (Imported and not modelled fractions) from particulate sulfate: Height profile of primary PM + secondary PM (modell versus resulats of NFP41) + Contribution in Ticino + Contribution in Sottoceneri Includes undidentified / not quantified Swiss sources (like ships, air traffic > 200 m …)

10 11th EIONET Workshop AQ Rudolf Weber Dispersion Source-receptor method (Gaussian model) Near-area: 200 m-grid on 6 x 6 km 2 area Far-area: 2 km-grid on 200 x 200 km 2 area Following TA Luft 1986, Stability from Swiss Meteorological Institute Meteo-data: 1h-values of the year 1998 Source categories Elevated (20 m): Diurnal cycle in 4 seasons ground-level: Diurnal cycle => Different source-receptor matrices

11 11th EIONET Workshop AQ Rudolf Weber Transfer functions for PM2.5 Short-range IsotropicAlpine valley Long-range 6 km 420 km

12 11th EIONET Workshop AQ Rudolf Weber Climatological regions Swiss Plateau region Alpine valleys remaining part of Switzerland

13 11th EIONET Workshop AQ Rudolf Weber Summary transfer functions

14 11th EIONET Workshop AQ Rudolf Weber Flow chart of dispersion model Idea: split emissions, sum up ambient concentrations Example: road passenger traffic

15 11th EIONET Workshop AQ Rudolf Weber Model structure For secondary PM: conversion from precursor maps

16 11th EIONET Workshop AQ Rudolf Weber Model versus measurements Street canyon, flat model Alpine valleys Modelled PM10 Measured PM10

17 11th EIONET Workshop AQ Rudolf Weber Map of PM0

18 11th EIONET Workshop AQ Rudolf Weber Map of PM2.5

19 11th EIONET Workshop AQ Rudolf Weber Scenario “maximum feasible reduction” Primary PM: - 40% Precurors of secondary PM: - 20% PM10 in 2010

20 11th EIONET Workshop AQ Rudolf Weber maximum feasible reduction: PM2.5 PM2.5 in 2010

21 11th EIONET Workshop AQ Rudolf Weber Population exposure Average population eposure Anthropogenic CH 9.5 μg/m 3 Anthr. not-CH 8.7 μg/m 3 ( or ignored, underest., unknown) Natural 1.4 μg/m 3 Total 19.6 μg/m 3 Influence of road traffic 22% 41% of population live in areas above annual air quality limit (annual mean > 20 μg/m3) Measurements: road traffic 33% urban background, 45% street canyon

22 11th EIONET Workshop AQ Rudolf Weber Population exposure from measurements Idea: use the measured data of stations not as area representative but as type representative. Types of stations in national network Suburban

23 11th EIONET Workshop AQ Rudolf Weber Average population exposure from measured data

24 11th EIONET Workshop AQ Rudolf Weber Summary Simple dispersion model agrees well with measurements. Estimation of population exposure with station data is possible. Use type of station, not simply the location and area. Future: Include soot (EC), BaP Full chemical model (CamX) Interpolation from measurements