EXERCISE 2:
The Primary Bio-aerosol
Pollution (The Emission and Transport)
Model used: Enviro-HIRLAM
and SILAM
(Enviro-HIRLAM is based on the DMI version
of the HIRLAM -
HIgh Resolution Limited Area Model)
Teachers: Mikhail Sofiev (FMI, Finland),
Group 2.1:
Laura Veriankaite (Lithuania), Sara Ortega Jimenez (Spain), Anton Svetlov (Russia), Anastasia Gernega (Ukraine), Elena Filatova (Russia)
Group 2.2:
Pilvi Siljamo (Finland), Lukasz
Grewling (Poland), Ekaterina Yakovleva (Russia), Ekaterina Khoreva (Russia)
Introduction & Background:
Release of many species into the atmosphere is not controlled by the
anthropogenic activity (or controlled indirectly). These species can originate
from physical processes, such as wind-driven soil erosion or sea-salt
production (so-called natural components), biological processes in vegetation
(biogenic species), wild-land fires (partly natural, partly human-induced),
etc. Release of such type of pollutants into the atmosphere and their
subsequent transport are largely driven by meteorology. Usually, such species
are parameterized in the atmospheric composition models via various emission
models. In rare cases, fixed time-dependent emission fluxes are prescribed. Meteorology-driven
transport of the non-anthropogenic species follows the same principles but the
source areas evidently differ from those for anthropogenic pollutants. Therefore,
depending on specific transport conditions, distribution patterns of
anthropogenic and non-anthropogenic species can be both very similar and very
diverse.
The considered case is an example of meteorology-promoted synchronous release
and transport of anthropogenic pollutants, smoke from wild-land fires, and
birch pollen.
Main Goal:
The goal of the exercise is to study how the meteorological forcing affects the
non-anthropogenic emissions, first of by driving the biogenic processes, how
the inter-action of anthropogenic and natural phenomena determines the
large-scale atmospheric composition changes, and how the selection of
meteorological driver for transport model influences the predicted dispersion
patterns of various pollutants.
Specific Objectives:
We consider simulations of two-week period in 2006 where plumes from
anthropogenic sources, wild-land fires in Russia and birch forests in the
Eastern Europe and Russia were synchronized by continental-scale meteorological
developments and transported over Central and Northern Europe together causing
strong degradation of air quality. For the case simulations group 2.1 will use
the SILAM model with the ECMWF input meteorological data, group 2.2 will utilize
the HIRLAM/EnviroHIRLAM fields. Both groups will perform the same set of the
model simulations and compare the results.
1) General description of emission
processes. Write down and discuss the main meteorological processes determining
the emission intensity from (i) anthropogenic sources, (ii) wild-land fires,
(iii) vegetation flowering.
2) Perform three independent SILAM simulations
with the prescribed meteorological datasets. Simulations should include: pollen
emission and transport, anthropogenic-emission driven chemical simulations and anthropogenic
plus fire chemical simulations. Compare the output between the groups with
regard to (i) pollen emission fields, (ii) concentrations of main chemicals and
pollen, (iii) meteorological parameters provided by the drivers.
3) perform comparison with observations
and try to identify the root causes of specific performance characteristics of
each model setup. The validation shall include a calculation of normalized mean
square error, bias, and correlation coefficient.
4) Summarise the results of the simulations in a form of oral
presentation (max. 15 min.).
Literature List:
The students in both groups shall read these papers before the Summer School.
REQUIRED
SILAM
user’s guide.
Sofiev, M., Siljamo, P., Ranta,
H., Rantio-Lehtimäki, A. (2006) Towards numerical forecasting of long-range air
transport of birch pollen: theoretical considerations and a feasibility study. Int J. on Biometeorology, DOI 10
1007/s00484-006-0027-x, 50, 392-402
Hidalgo, P.J., Mangin, A., Galan,
C., Hembise, O., V´azquez, L.M., Sanchez,
O. An automated system for surveying and forecasting Olea pollen
dispersion. Aerobiologia 18: 23–31, 2002.
Saarikoski,
S., Sillanpää, M., Sofiev, M., Timonen, H., Saarnio, K., Teinilä, K., Karppinen,
A., Kukkonen, J., Hillamo, R. (2007) Chemical composition of aerosols
during a major biomass burning episode over northern
Arctic smoke – record high air pollution levels
in the European Arctic due to agricultural fires in
ADDITIONAL
Sofiev M., Siljamo, P., Valkama,
Pasken, R.,
Pietrowicz, J.A. Using dispersion and mesoscale meteorological models to forecast
pollen concentrations. Atmospheric Environment 39 (2005) 7689–7701