Carmen Galán, UCO (Spain) & Mikhail Sofiev, FMI (Finland)

Biological aerosol sources are located where biological activities exist and are exposed to air movements: most of the terrestrial surface can be considered as huge potential source of aerobiological material.

It should be consider natural sources; those generated by human activities: i.e. farming, agricultural and forestry processing; and those generating indoors.

indoor human activities

natural sources

outdoor human activities

There are different organisms by using the air for their transport:

a) those by using the wind to transport the complete organisms;

b) those that transport their propagules through the wind.

fountain, biodeteriory

bacteriavirus cianobacteria

microalgi insects

There are different organisms by using the air for their transport:

a) those by using the wind to transport the complete organisms;

b) those that transport their propagules through the wind.

Moss spores Fern sporesFungal spores

Lower plants

tricolporate pollen grain

Tormo, R. (http://www.unex.es/polen/LHB/)

Cupressus sempervirens

Dactylis glomerata

Platanus hispanica

Olea europaea

Phenology is generally described as the art of observing life cyclephases or activities of plants and animals in their temporaloccurrence through the year (Lieth, 1974)

Cupressus sempervirens

Dactylis glomerata

Platanus hispanica

Olea europaea

Phenology includes the study of periodic events as influenced bythe environment, especially temperature changes driven byweather and climate (Schwartz, 2003)

0

200

400

600

800

1000

12

-4

19

-4

26

-4

3-5

10

-5

17

-5

24

-5

31

-5

7-6

14

-6

21

-6

28

-6

5-7

12

-7

Po

llen

gra

ins/

m3

of

air

Poaceae, 2007

Discipline that study passive transport of biological matter and living organisms through the air; paying attention to the production sources of these organisms and material emitted to the atmosphere, their emission, transport anddeposition, and their impact on fungi, vegetables, animals and humans.

start end

pollen season

peak

Knowledge about pollen content in the air offers a quantitative value on floral phenology

EMISSION

DISPERSION AND/OR TRANSPORT

DEPOSITION

REFLOTTING

PRODUCTION(i.e. pollen, spores)

EFFECT(i.e. polination, polinosis)

Gridded wind field

Diagnostic model

PollenEmission

Pollenproduction

Blossoming module

Pollen count Emission module

T° (summation)

precipitationhumidity

Meteo dataanalysis / forecast

Land use Topography

Land use Topography

Dispersion

Forecast system for aeroallergen dispersion overall processing chain

A.S.T.H.M.A. Project

The forecast system includes four computational modules:

1. a meteorological module to resample the low resolution dataprovided by the meteorological agencies to a higher resolutionneeded by the dispersion module;

2. a blossoming module to predict the pollen season onset;3. an emission module split into two parts: the potential pollen

production to be spread (it depends on land use, topography andphenological behaviour) and the emission rate of pollen (it dependson external factors – e.g. humidity, wind);

4. a dispersion module to predict the evolution of pollen countsanywhere in the computational domain.

Forecast system for aero-allergen dispersion

A.S.T.H.M.A. Project

The forecast system includes four computational modules:

1. a meteorological module to resample the low resolution dataprovided by the meteorological agencies to a higher resolutionneeded by the dispersion module;

2. a blossoming module to predict the pollen season onset;3. an emission module split into two parts: the potential pollen

production to be spread (it depends on land use, topography andphenological behaviour) and the emission rate of pollen (it dependson external factors – e.g. humidity, wind);

4. a dispersion module to predict the evolution of pollen countsanywhere in the computational domain.

Forecast system for aero-allergen dispersion

A.S.T.H.M.A. Project

I.e.: Winter duration and severity & spring warming control the start and intensity of temperate tree pollination

Floral phenology / Aerobiology: pheno-climatic parameters

Floral phenology / Aerobiology: pheno-climatic parameters

Senoidal extrapolation (Snyder, 1995)

Heat units accumulation

Average temperature

Threshold temperature

Pollen season start

Altitud Average Tª Threshold Tª Heat Unit Bio-climatology

Málaga 5 18.0º 10 179.6º Termomediterran

Córdoba 123 18.0º 12.5 210.6º Termomediterran

Jaén 550 17.0º 7 345.9º Mesomediterran

Granada 685 15.5º 6 421.7º Mesomediterran

Priego 650 14.4º 5 379.4º Mesomediterran

Galán et al. (2001)

Real Date Forecast Forecast-Real date

Málaga 70 67 -3Granada 108 105 -3Jaén 113 106 -7Priego 106 109 +3Córdoba 97 105 +8Mean value 4.8

Dactylis glomerata

*)(1

FtRft

t

f

The models assumes that flowering (tf) occurs when the state of development of flowers, described by forcing function (Sf), reaches a critical value (F*). The state of forcing function is described by a daily sum of rate of forcing, starting at day t0 such as

Sf(tf)=

Where Rf(t)= with x(t), the daily temperature

*)(1

FtRft

t

f

*)(1

FtRft

t

f

))((1

1etxd

e

))((

11

etxde

))((1

1etxd

e

))((1

1etxd

e

García-Mozo et al. (2008)

Dactylis glomerata

Day t1 is defined by the day when a critical amount of rainfall (R*) has occurred within the last 7 days such as

*)(1

1 7

RtRf

t

t

with R(t) the daily rainfall

Accumulation of rainfall takes place when a critical photoperiod (P*) has been reached such as P(t0)=P* with P(t) the daily photoperiod, calculated as a function of latitude, and t0<t1-7.

The model has thus 5 parameters (F*, P*, R*, d and e).

García-Mozo et al. (2008)

Dactylis glomerata

Graphic representation of the relationship between temperature and heat accumulation calculated with the process-based models for the start and peak

García-Mozo et al. (2008)

The forecast system includes four computational modules:

1. a meteorological module to resample the low resolution dataprovided by the meteorological agencies to a higher resolutionneeded by the dispersion module,

2. a blossoming module to predict the pollen season onset.

3. an emission module split into two parts: the potential pollenproduction to be spread (it depends on land use, topographyand phenological behaviour) and the emission rate of pollen(it depends on external factors – e.g. humidity, wind).

4. a dispersion module to predict the evolution of pollen countsanywhere in the computational domain.

Forecast system for aero-allergen dispersion

A.S.T.H.M.A. Project

EMISSION

DISPERSION AND/OR TRANSPORT

DEPOSITION

REFLOTTING

PRODUCTION(i.e. pollen, spores)

EFFECT(i.e. polination, polinosis)

In aerobiological studies sometimes pollen can not be distinguishing between different genera or species as they share the same characteristics under light microscopy, they are stenopalynous.

QuercusPlatanus hispanicaCupressaceae

Studies about pollen production per plant provide information on the relative contribution of each species to the total amount of pollen enabling to estimate the average potential pollen emission.

Poaceae

Pinaceae

1 ml

1 l

CRUDEN (1977)

Cupressus arizonica

Producción de polen, Cupressus (Hidalgo et al., 1999)

Number of pollen grains/flowerNumber of pollen grains/flower

0

5

10

15

20

25

30

35

40

45

Cupressus

macrocarpa

Cupressus

sempervirens

Cupressus

arizonica

x1

04

Number of pollen grains/flowerNumber of pollen grains/flower

0

5

10

15

20

25

30

35

40

45

Cupressus

macrocarpa

Cupressus

sempervirens

Cupressus

arizonica

x1

04

Number of flowers/branch Number of flowers/branch (20(20--30 cm)30 cm)

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

Cupressus

sempervirens

Cupressus

arizonica

Cupressus

macrocarpa

Number of flowers/branch Number of flowers/branch (20(20--30 cm)30 cm)

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

Cupressus

sempervirens

Cupressus

arizonica

Cupressus

macrocarpa

Number of branch/mNumber of branch/m22

0

5

10

15

20

25

30

35

40

45

Cupressus

sempervirens

Cupressus

macrocarpa

Cupressus

arizonica

Number of branch/mNumber of branch/m22

0

5

10

15

20

25

30

35

40

45

Cupressus

sempervirens

Cupressus

macrocarpa

Cupressus

arizonica

Total pollen production

Cupressus sempervirens

Cupressus macrocarpa

Cupressus arizonica

(1.16 x 1012)

(6.4 x 1010)

(1.27 x 1011)

Total pollen production

Cupressus sempervirens

Cupressus macrocarpa

Cupressus arizonica

(1.16 x 1012)

(6.4 x 1010)

(1.27 x 1011)

831

274

145

36

30

19

1:0.1:0.05

15

Vu

lpia

myu

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spa

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mo

nsp

elie

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nic

um

rep

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rba

ta

Ph

ala

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Ho

lcu

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Cyn

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Elym

us

rep

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lcu

s se

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Cyn

osu

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ech

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Ag

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is s

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Hyp

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ia h

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Vu

lpia

gen

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Arr

hen

ath

eru

m a

lbu

m

Loliu

m r

igid

um

Pip

tath

eru

m m

ilia

ceu

m

Da

ctyl

is g

lom

era

ta

Fest

uca

aru

nd

ina

cea

Tris

eta

ria

pa

nic

ea

Sorg

hu

m h

ale

pen

se

Po

llen

gra

ins

per

infl

ore

scen

ce (

x 1

06)

10

20

Vu

lpia

myu

ros

Ho

rdeu

m m

ari

nu

m

Bra

chyp

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dis

tach

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Lam

arc

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au

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Aeg

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s g

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ta

Aeg

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str

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cia

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Des

ma

zeri

ari

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Bro

mu

sd

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dru

s

Ro

stra

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cri

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ta

Stip

aca

pen

sis

Bro

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ola

tus

Bro

mu

s m

atr

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sis

Bro

mu

s h

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us

Ho

rdeu

m le

po

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um

Ph

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ma

Pa

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pa

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Ave

na

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ilis

Po

lyp

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nsp

elie

nsi

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Pa

nic

um

rep

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Ave

na

ba

rba

ta

Ph

ala

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min

or

Ho

lcu

s la

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Cyn

od

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da

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on

Elym

us

rep

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Ho

lcu

s se

tig

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Cyn

osu

rus

ech

ina

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Ag

rost

isst

olo

nif

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Hyp

arr

hen

ia h

irta

Vu

lpia

gen

icu

lata

Loliu

mri

gid

um

Pip

tath

eru

m m

ilia

ceu

m

Tris

eta

ria

pa

nic

ea

Sorg

hu

m h

ale

pen

se

- annual + perennial

Grass pollen production per inflorescence (Prieto-Baena et al., 2003)

0

5

20 haOrthophoto

Olive crop

nº catkin/ m2

.r

.r

Nº flowers/catkin

m2

4πr2

Nº pollen/anther

Olea Potential Production Map in Cordoba area

20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00 180.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

180.00

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

A.S.T.H.M.A. Project

Hidalgo et al. (2002)

EMISSION

DISPERSION AND TRANSPORT

DEPOSITION

REFLOTTING

PRODUCTION(i.e. pollen, spores)

EFFECT(i.e. polination, polinosis)

It is needed some energy for particle emission to the air:

a) active, explosive or hygroscopic mechanisms;

b) passive, through a external agent.

Lycopodium Peziza

Cladosporium

Passive spore emission

Active spore emission

http://www.unex.es/polen/LHB/)

MOSS: i.e. Polytrhichum FERN: i.e.Pteridium

http://www.unex.es/polen/LHB/)

stigma

Stamen: filament, anther

Pistil: ovary, style, stigma

filament

anther

style

Section young anther

Mature anther Anther dehiscence

Photo (Sulmont, 2005)

Cupressus

Parietaria

Poaceae

Some Angiosperms, active mechanisms for pollen dispersal

Most Angiosperms,passive mechanisms for pollen dispersal

Gymnosperms, passive mechanisms for pollen dispersal

DISPERSION AND/OR TRANSPORT DEPOSITION

REFLOTING

EMISSION

HumidityTemperature

Mature anther Anther dehiscence

Mature pollen in the anthers is completely saturated and holds no internal room for air.

After dehiscence of pollen sac, water evaporates extremely rapidly from the pollen grain and the pollen becomes fully buoyant.

A number of hours before anthesis the anther is able to dehisce. At anthesis the dehydrating endotheciumcells bend the locule walls bordering the pore in outward direction.

Photo (Sulmont, 2005)

R2 = 0.81; p <0.01

Transference functions Equations

sigmoid

(x)= 1/ 1 + e-x

step

1 if x 0

(x)=

0 if x 0

linear

(x)= x

INPUT VARIABLES

In_2 Average temperature (D-1)

In_3 Maximum temperature (D-1) In_4 Minimum temperature (D-1)

In_5 Humidity (D-1) In_6 Accumulative rainfall (D-1)

In_7 Accumulative average temperature (D-1) In_8 Accumulative humidity (D-1) In_9 Accumulative pollen concentration (D-1)

In_10 Pollen concentration (D-1)

Sánchez-Mesa (2005)

R2=0.60

Sánchez-Mesa et al. (2005)

GEOSTATISTIC ANALYSIS:

1) DESCRIPTIVE STATISTICAL ANALYSIS

2) VARIOGRAM CALCULATION

3) KRIGING (Interpolation)

4) MAPPING

PHENOLOGICAL

PHASES

PRIEGOCARCABUEY

CABRA

ESPEJO

ALCOLEA

BAENA

García-Mozo et al. (2006)

DISPERSION AND/OR TRANSPORT

REFLOTING

EMISSION

DEPOSITION

Humidity

Temperature

Atmospheric stability Rainfall Wind speed and direction

Rainfall

Wind speed