Urban air quality: from ultrafine to coarse particles

“Urban air quality: the challenge of non-exhaust emissions"

11-12 July Barcelona (BDEBATE - IDAEA)

Urban air quality:

from ultrafine to coarse particles (focus on Southern Europe)

Critical air quality parameters

The problem of PM

PM temporal trends

UFP, NH3, BC, Coarse PM

Non exhaust PM in Spain

Measuring urban exopsure: Urban background or traffic?

CONTENT

CON TRIBUTORS TO THE STUDIES

IDAEA-CSIC

UNIVERSITY OF HUELVA

CREAL-UPF

CIEMAT

TNO

PAUL SCHERRER INSTITUTE

UNIVERSITY OF FLORENCE

EMPA

UNIVERSITY OF BIRMINGHAMM

UNIVERSITY OF AVEIRO

MINISTRY OF AGRICULTURE, FOOD AND ENVIRONMENT OF SPAIN

AJUNTAMENT DE BARCELONA

GENERALITAT DE CATALUNYA

JUNTA DE ANDALUCÍA

DIPUTACIÓ DE BARCELONA

BARCELONA NETA

SPRINGER - CITY OF KLAGENFURT

SPRINGER

Review of the air quality policy: Ultrafine Particles, NH3, Black Carbon, Coarse PM

Critical parameters (exceedances)

293

K , 101,3 kPa,

Directive 2008/50/EC, RD 102/2011 except PM and metals, Evriron. Cond.

Hourly 350 µg/m3 SO2 24 times per year

Daily 125 µg/m3 SO2 3 times per year

Annual prot. ecos. 20 µg/m3 SO2 not exceeding annual & mean 1 Oct-31 Mar

Hourly 200 µg/m3 NO2 18 times per year

Annual 40 µg/m3 NO2 not exceeding

Annual prot. vegetation 30 µg/m3 NOx (reported as NO2) not exceeding

Annual 30 (5) µg/m3 Benzene not exceeding

Mean 8-h max. in a day 10 mg/m3 CO not exceeding

Annual 500 ng/m3 Pb not exceeding

Annual 40 µg/m3 PM10 not exceeding

Daily 50 µg/m3 PM10 n<35 per year

Annual (25 and 20 (18) µg/m3 PM2.5) not exceeding

2010-2020 (reducing 20% PM2.5 triennial for mean of urban background)

CRITICAL AIR QUALITY PARAMETRES

2004/107/EC, RD 102/2011

Annual 6 ng/m3 As not exceeding

Annual 20 ng/m3 Ni not exceeding

Annual 5 ng/m3 Cd not exceeding

Annual 1 ng/m3 Benzo[]pirene not exceeding

0

20

40

60

80

PM

10 (

µg

/m3)

268 estaciones de vigilancia y control calidad del aire (España 2006), 25% superan VLA

Remotas

Rurales regionales

y próximas a ciudades

Sub-urbanas de fondo

Sub-urbanas de tráficoUrbanas de tráfico

Urbanas de fondo9%

35%

42%

Rurales y urbanas, 2006

4%

27%

0

20

40

60

80

PM

10 (

µg

/m3)


Remotas

Rurales regionales



Sub-urbanas de tráfico

Urbanas de tráficoUrbanas de fondo16%

29%

26%


30%

0

20

40

60

80

PM

10 (

µg

/m3)


Remotas

Rurales regionales



Sub-urbanas de tráfico

Urbanas de tráficoUrbanas de fondo

10%

21%

15%


11%

0

20

40

60

80

PM

10 (

µg

/m3)

177 estaciones de vigilancia y control calidad del aire (España 2006), 24% superan el VLA

Regionales-industriales

y próximas a ciudades-industriales

Sub-urbanas industrialesUrbanas Industriales

5% 6%

29%

40%

Industriales, 2006

0

20

40

60

80

PM

10 (

µg

/m3)





2%

21% 43%

Industriales, 2007

0

20

40

60

80

PM

10 (

µg

/m3)





13%

13% 10%

Industriales, 2008

Exceedances in 2010

VLA: Avilés2, Avilés3

VLD: Torrejón, Alcalá, Murcia, Aviles1, Avilés2, Avilés 3, Gijón, Camargo,

Puertollano

Exceedances in 2011

VLA: Avilés2

VLD: Sevilla, Granada, Córdoba, Villanueva del Arz., Huelva, Bailén, Alfaro,

Bilbao, Puertollano, Avilés, Gijón, St. Vicenç Horts, Sta Pertétua de la M.,

Granollers, Lleida, Vic, Barcelona, A Coruña

THE PROBLEM OF PM

EMEP Cusack et al., 2012. Atmospheric Chemistry and Physics

THE PROBLEM OF PM

SPAIN (2002 –

2012); PM2.5

[mg/m3]

Pey J., et al. 2009. Atmospheric Environment

N13-20 (2336 cm-3

)

1253; 54%536; 23%

336; 14%

97; 4%56; 2%

59; 3%

Tráfico

Crustal

Industrial

Marino

Fotoquímica

Regional / F. Urbano

Comb. Fuel-Oil

N50-200 (14813 cm-3

)

4261; 85%

85; 2%

68; 1%

159; 3%

319; 6% 76; 2%

29; 1%

Tráfico

Crustal

Industrial

Marino

Fotoquímica


Comb. Fuel-Oil

0.10 µm 1.00 µm

Nu

mb

er

of

part

icle

s

Nucleation Aitken Accumulation CoarseNucleation Aitken Accumulation Coarse

0.01 µm 10.00 µm

N400-800 (22 cm-3

)

10; 52%

2; 8%

2; 10%

0,1; 1%

0,1; 1%

5; 26%

0,4; 2%Tráfico

Crustal

Industrial

Marino

Fotoquímica


Comb. Fuel-Oil

ORIGIN OF ULTRAFINE PARTICLES: BARCELONA

Traffic

Crustal

Industrial

Marine

Photochemical

Regional / Urban back.

Fuel-Oil combustion

THE PROBLEM OF PM

BC & ULTRAFINE PARTICLES

Reche et al., 2011. Atmospheric Chemistry and Physics

0 2 4 6 8 10 12 14 16 18 20 22

Hour (UTC)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Bla

ck

Ca

rbo

n (µ

g/m

3)

N (>2.5nm) BC

0

5000

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15000

20000

25000

30000

35000

40000

45000

50000

0 2 4 6 8 10 12 14 16 18 20 22

Hour (UTC)

Nu

mb

er

of

pa

rtic

les

(n

/cm

3) N (>2.5nm) BC

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Hour (UTC)

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pa

rtic

les

(n

/cm

3)

0

2

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8

10

12

Bla

ck

Ca

rbo

n (µ

g/m

3)

N (>7nm) BC

0

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0 2 4 6 8 10 12 14 16 18 20 22

Hour (UTC)

Nu

mb

er

of

pa

rtic

les

(n

/cm

3)

0

1

2

3

4

5

6

Bla

ck

Ca

rbo

n (µ

g/m

3)

N (>7nm) BC

0 2 4 6 8 10 12 14 16 18 20 22Hour (UTC)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0B

lac

k C

arb

on

(µg

/m3)

N (>7nm) BC

0 2 4 6 8 10 12 14 16 18 20 22

Hour (UTC)

N (>7nm) BC

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

0 2 4 6 8 10 12 14 16 18 20 22

Hour (UTC)

Nu

mb

er

of

pa

rtic

les

(n

/cm

3) N (>5nm) BC

BCN LUG

BERN

NK

HU SCO

MR

0 2 4 6 8 10 12 14 16 18 20 22

Hour (UTC)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Bla

ck

Ca

rbo

n (µ

g/m

3)

N (>2.5nm) BC

0

5000

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20000

25000

30000

35000

40000

45000

50000

0 2 4 6 8 10 12 14 16 18 20 22

Hour (UTC)

Nu

mb

er

of

pa

rtic

les

(n

/cm

3) N (>2.5nm) BC

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

0 2 4 6 8 10 12 14 16 18 20 22

Hour (UTC)

Nu

mb

er

of

pa

rtic

les

(n

/cm

3)

0

2

4

6

8

10

12

Bla

ck

Ca

rbo

n (µ

g/m

3)

N (>7nm) BC

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

0 2 4 6 8 10 12 14 16 18 20 22

Hour (UTC)

Nu

mb

er

of

pa

rtic

les

(n

/cm

3)

0

1

2

3

4

5

6

Bla

ck

Ca

rbo

n (µ

g/m

3)

N (>7nm) BC

0 2 4 6 8 10 12 14 16 18 20 22Hour (UTC)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Bla

ck

Ca

rbo

n (µ

g/m

3)

N (>7nm) BC

0 2 4 6 8 10 12 14 16 18 20 22

Hour (UTC)

N (>7nm) BC

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

0 2 4 6 8 10 12 14 16 18 20 22

Hour (UTC)

Nu

mb

er

of

pa

rtic

les

(n

/cm

3) N (>5nm) BC

BCN LUG

BERN

NK

HU SCO

MR

THE PROBLEM OF PM

0

1

2

3

4

5

6

7

8

9

10

BCN MAD ACOR VAL STCT HUEL

NH

3 u

g/m

3

Winter Summer

NO3- (µg/m3) PM10

<11-22-33-4

4-5>5

EMEP

130 mNH3 (µgm-3)

130 m130 mNH3 (µgm-3)

URBAN NH3

Reche et al. (2013) Atmospheric Environment, submitted

THE PROBLEM OF PM

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

EC

(µg

/m3)

REMOTE RURAL SUB-URBAN INDUSTRIAL/RURAL INDUSTRIAL/URBAN URBAN TRAFFIC

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

OC

(µ

g/m

3)

OCEC

x 30 for EC x 5 for OC

OC & EC

Querol et al. (2013) Atmospheric Chemistry and Physics

THE PROBLEM OF PM

OC & EC

y = 3.43x0.356

R² = 0.83

0

1

2

3

4

5

6

0 1 2 3 4 5

OC

(µ

g/m

3)

EC (µg/m3)

y=3.43x0.356

R2=0.83

PM10PM2.5

Remote & Regional Back.Industrial-RuralIndustrial-UrbanUrban BackgroundTraffic

y = 3.72x0.493

R² = 0.45

0

5

10

15

20

0 1 2 3 4 5 6 7 8

OC

(µ

g/m

3)

EC (µg/m3)

Remote & Regional Back.Urban, traffic, industrial

Traffic sites Portugal

Biomass burning influenced sitefrom Portugal

Biomass burning influenced sitesFrom central Europe and Portugal

Urban background sites

with high traffic influence

y = 3.42x-0.644

R² = 0.94

0

5

10

15

20

25

0 1 2 3 4 5

OC

/E

C (

µg

/m

3)

EC (µg/m3)

PM10PM2.5

Remote & Regional Back.Industrial-RuralIndustrial-UrbanUrban BackgroundTraffic

y=3.42x-0.644

R2=0.94

y = 3.62x-0.498

R² = 0.79

0

5

10

15

20

0 20 40 60 80 100 120 140 160 180 200

OC

/ E

C (

µg

/m3)

EC (µg/m3)

y = 3.62x-0.507

R² = 0.76

0

5

10

15

20

0 1 2 3 4 5 6 7 8

OC

/ E

C (

µg

/m3)

EC (µg/m3)

y=3.62x-0.498

R2=0.79Traffic sites Portugal

Traffic tunnel Portugal

Biomass burning influenced sitesfrom central Europe and Portugal

Remote clean sitesSpain

Remote & Regional Back.Urban, traffic, industrial


THE PROBLEM OF PM

Eeftens et al. (2012) Atmospheric Environment

ESCAPE

THE IMPORTANCE OF THE COARSE FRACTION

THE PROBLEM OF PM

Mineral matter (µg/m3) PM10

J F M A M J J A S O N D

Seasonal trend

African contribution

Low re-suspension

Influence from Traffic

Influence from Traffic

<3

3-5

5-7

7-10

10-15

15-18

>18

Obras

Salida Puerto

Ronda de Dalt

Ronda Litoral

Plaça Cerdá

Meridiana

3-9 mg/m2

10-20 mg/m2

21-40 mg/m2

41-80 mg/m2

>81 mg/m2

Masa PM10

3-9 mg/m2

10-20 mg/m2

21-40 mg/m2

41-80 mg/m2

>81 mg/m2

Masa PM10

Av. Diagonal

Centre City C4

0.01

0.10

1.00

10.00

100.00

OC

EC

CO

3=

Al2

OC

a K Fe P S

SO

NO

3-

NH

4+

Ti V Cr

Mn

Co

Ni

Cu

Zn

As

R

b Sr

Zr

M

o

Cd

S

n

Sb

B

aP

b

Mas

s p

erce

nt

PhD F. Amato

ROAD DUST

THE PROBLEM OF PM

Obres

Sortida Port

Ronda de Dalt

Ronda Litoral

Plaça Cerdà

Meridiana

Sb ( µg/g PM10)

Sb (µg/ g PM 10)

0

20

40

60

80

100

120

140

1

Brake pads Tires

Ferodo (A) Bendix Road House Bosch Ferodo (B) Bridgeston Michelin

C tot 28 26 28 32 - 83 79 Al 0.4 2.3 0.8 0.9 1.0 0.06 0.06 Ca 0.4 1.8 3.6 1.7 0.3 1.31 0.46 K <0.1 0.4 <0.1 <0.1 <0.1 0.04 0.06 Na <0.1 1.0 0.1 0.1 <0.1 0.03 0.03 Mg 1.0 4.1 0.5 0.8 0.8 0.04 0.01 Fe 50 16 33 30 26 0.02 0.03 S 2.2 2.6 3.6 3.1 1.9 1.17 1.32

%

P <0.1 <0.1 0.1 <0.1 <0.1 <0.1 <0.1

Li 1.8 4.4 2.4 1.1 2.2 1.4 0.1 Sc 1 4 1 1 3 <0.1 <0.1 Ti 605 744 567 209 335 31 17 V 173 16 30 42 40 5 4 Cr 210 170 1270 49 2834 1 2 Mn 1783 1703 12636 1464 1827 3 3 Co 26 13 14 19 10 80 94 Ni 51 61 78 74 33 <0.1 <0.1 Cu 82.3 24493 270 13732 117551 4.8 6.9 Zn 66.6 4083 3462 1118 14862 19849 15073 Ga 9.8 5.7 4.1 3.1 6.2 <0.1 <0.1 Ge 2.8 1.4 1.2 0.8 4.1 <0.1 <0.1 As 4.0 5.0 4.6 42 8.4 0.8 0.7 Se 5.0 7.6 3.5 11.0 7.1 <0.1 <0.1 Rb 30.5 38.5 14.3 1.2 4.9 1.1 3.1 Sr 1007 857 818 1773 26 17.8 3.1 Y 0.9 15.5 6.5 1.2 16.4 <0.1 <0.1 Zr 4.4 1260 70.3 12.0 945 1.2 <0.1 Nb <0.1 <0.1 65.8 1.7 <0.1 <0.1 0.8 Mo 3.1 5.4 16 162 3093 0.4 0.6 Cd 0.5 1.6 0.6 1.9 23 2.7 1.5 Sn 2.4 31 40 147 10 2.5 2.1 Sb 2.1 1293 14.8 7.5 6944 11.5 2.0 Cs 1.0 1.7 0.7 <0.1 1 <0.1 <0.1 Ba 69343 67291 39013 37213 772 10.2 15.5 La 2.3 6.9 32.3 <0.1 5 1.8 3.5 Ce 4.2 14.9 50.7 2.1 11.5 0.5 0.6 Pr <0.1 1.2 4.0 <0.1 1.2 <0.1 <0.1 Nd 2.8 8.5 17.0 0.8 5.2 21.0 22.9 Hf <0.1 49.5 1.7 <0.1 36 <0.1 <0.1 Ta <0.1 <0.1 5.7 <0.1 <0.1 <0.1 0.9 W <0.1 <0.1 18.7 0.6 <0.1 <0.1 <0.1 Tl <0.1 <0.1 0.9 <0.1 <0.1 <0.1 <0.1 Pb 253 173 42.0 292 6.6 20.0 25.8 Bi <0.1 23.6 0.0 12.2 <0.1 <0.1 0.6 Th <0.1 4.1 4.1 <0.1 4 <0.1 <0.1

ppm

U <0.1 4.7 1.5 <0.1 4 <0.1 <0.1

SOURCES OF ROAD DUST

Amato et al., 2013 ATMENV

THE PROBLEM OF PM

ROAD DUST EMISSION FACTORS IN BARCELONA

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VAL1 VAL2 COR

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VAL1 VAL2 COR

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VAL1 VAL2 COR

µg/m

3µ

g/m

3

0

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VAL1 VAL2 COR

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VAL1 VAL2 COR

NOx

PM10

0

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VAL1 VAL2 COR

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VAL1 VAL2 COR

µg/m

3µ

g/m

3

0

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0

23:0

0

VAL1 VAL2 COR

0

10

20

30

40

50

60

70

80

90

0:00

1:00

2:00

3:00

4:00

5:00

6:00

7:00

8:00

9:00

10:0

0

11:0

0

12:0

0

13:0

0

14:0

0

15:0

0

16:0

0

17:0

0

18:0

0

19:0

0

20:0

0

21:0

0

22:0

0

23:0

0

VAL1 VAL2 COR

NOx

PM10

DUST LOAD

<10µm

(mg m-2)

* Amato et al., (2009) ATM ENV

** Amato et al., (2010) STOTEN

***Bukowiecki et al. (2010) ATM ENV

EMISSION RATE

mixed fleet

(mg veh-1 km-1)

Barcelona

Zürich

82**

27***

8.9*

0.7

THE PROBLEM OF PM

Amato et al. STOTEN, 2010

EFFECT OF ROAD MOISTURE

Barcelona

Utrecht

1a

1b

2a

2b

3a

3b

4a

4b

5a

5b

6a

6b

7a

7b

..a

..b

0,000

0,001

0,002

0,003

0,004

0,005

0,006

0,007

0,008

0 50 100 150 200 250 300

t (hours after rain)

Du

st

load

ing

s (

g m

-2)

Barcelona

Utrecht

0,000

0,001

0,002

0,003

0,004

0,005

0,006

0,007

0,008

0 50 100 150 200 250 300

t (hours after rain)D

ust

load

ing

s (

g m

-2)

Barcelona

Utrecht

0,000

0,200

0,400

0,600

0,800

1,000

1,200

0 50 100 150 200 250 300

t (hours after rain)

No

rma

lize

d d

us

t lo

ad

ing

s (

g m

-2)

Barcelona

Utrecht)1(max

tr

t eEFEF

Amato et al., 2013 ATMENV

THE PROBLEM OF PM

Vehicle Exhaust;

4.4; 30%

Nitrate; 2.8; 19%

Road dust; 0.3; 2%Heavy oil; 0.6; 4%

Industrial; 0.5; 3%

Sulfate; 5.6; 38%

Mineral; 0.2; 1%

Sea salt; 0.2; 1%

African dust; 0.3;

2%

Vehicle Exhaust;

6.6; 25%

Nitrate; 4.0; 16%

Road dust; 2.9;

11%Heavy oil; 0.8; 3%

Industrial; 0.9; 3%

Sulfate; 7.0; 28%

Mineral; 1.9; 7%

Sea salt; 1.0; 4%

African dust; 0.9;

3%Vehicle Exhaust;

7.5; 18%

Nitrate; 4.5; 11%

Road dust; 8.8;

22%Heavy oil; 1.0; 2%Industrial; 1.0; 2%

Sulfate; 6.7; 17%

Mineral; 5.6; 14%

Sea salt; 4.1; 10%

African dust; 1.5;

4%

PM10 PM2.5

PM1

ROAD DUST CONTRIBUTIONS, BARCELONA (2003-2010)

Road traffic 48% Road traffic 49%

Road traffic 46%

Shipping 2% Shipping 3%

Shipping 4%

Non road

resuspension 14%

Non road

resuspension 4%

Non road

resuspension 1%

THE PROBLEM OF PM

ROAD DUST CONTRIBUTIONS, ANDALUCÍA (2003-2010)

THE PROBLEM OF PM

RB

RB

TR

TR

TR

Motor exhaust Road dust

Trend of source contributions (Algeciras Bay 2005-2010)

Amato et al., in prep.

THE PROBLEM OF PM


Glories

0

10

20

30

40

50

60

015

3045

60

75

90

105

120

135

150

165

180195210225

240

255

270

285

300

315

330345

% frecuencia viento

STREET WASHING

THE PROBLEM OF PM

Daily mean reduction

At the cleaning site: - 8.8 µg m-3

At the reference sites: - 3.7-4.9 µg m-3

StC-induced reduction: - 4-5 µg m-3 (7-10%)

EFFECT OF WASHING ON PM10

Monitoring site StC days

(µg m-3)

no-StC days

(µg m-3)

Kerbside Cleaning site 44.4 53.2

Kerbside Reference site 50.3 54.0

Urban background Reference site 38.9 43.8




Reference sites

- 3-5 µg m-3

0

10

20

30

40

50

60

70

80

90

0 1 2 3 4 5 6 7 8 9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

Local time

PM

10 (

µg

m-3

)

no-StC days StC days

Cleaning site

- 8.8 µg m-3

10

20

30

40

50

60

70

80

90

0 1 2 3 4 5 6 7 8 9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

Local time

PM

10 (

µg

m-3

)

no-StC days StC days

THE PROBLEM OF PM

0

30

60

90

7.4.08

8.4.08

9.4.08

10.4.0

8

11.4.0

8

12.4.0

8

13.4.0

8

14.4.0

8

15.4.0

8

16.4.0

8

17.4.0

8

18.4.0

8

19.4.0

8

20.4.0

8

21.4.0

8

22.4.0

8

23.4.0

8

24.4.0

8

25.4.0

8

26.4.0

8

27.4.0

8

28.4.0

8

29.4.0

8

30.4.0

8

1.5.08

2.5.08

3.5.08

4.5.08

Ti

(ng

/m3)

0

4

8

12

16

Pre

p.(

mm

)

Street cleaning Precipitation Downwind site Upwind site

Mineral dust

0

10

20

30

7.4.08

8.4.08

9.4.08

10.4.0

8

11.4.0

8

12.4.0

8

13.4.0

8

14.4.0

8

15.4.0

8

16.4.0

8

17.4.0

8

18.4.0

8

19.4.0

8

20.4.0

8

21.4.0

8

22.4.0

8

23.4.0

8

24.4.0

8

25.4.0

8

26.4.0

8

27.4.0

8

28.4.0

8

29.4.0

8

30.4.0

8

1.5.08

2.5.08

3.5.08

4.5.08

Sb

(n

g/m

3)

0

4

8

12

16

Pre

p.(

mm

)


Brake dust

010

2030

405060

7080

90100

7.4.08

8.4.08

9.4.08

10.4.0

8

11.4.0

8

12.4.0

8

13.4.0

8

14.4.0

8

15.4.0

8

16.4.0

8

17.4.0

8

18.4.0

8

19.4.0

8

20.4.0

8

21.4.0

8

22.4.0

8

23.4.0

8

24.4.0

8

25.4.0

8

26.4.0

8

27.4.0

8

28.4.0

8

29.4.0

8

30.4.0

8

1.5.08

2.5.08

3.5.08

4.5.08

V (

ng

/m3)

0

4

8

12

16

Pre

p.(

mm

)


Fuel oil comb.

0

10

20

7.4.08

8.4.08

9.4.08

10.4.0

8

11.4.0

8

12.4.0

8

13.4.0

8

14.4.0

8

15.4.0

8

16.4.0

8

17.4.0

8

18.4.0

8

19.4.0

8

20.4.0

8

21.4.0

8

22.4.0

8

23.4.0

8

24.4.0

8

25.4.0

8

26.4.0

8

27.4.0

8

28.4.0

8

29.4.0

8

30.4.0

8

1.5.08

2.5.08

3.5.08

4.5.08

EC

(µ

g/m

3)

0

4

8

12

16

Pre

p.(

mm

)


EC

0

5

10

7.4.08

8.4.08

9.4.08

10.4.0

8

11.4.0

8

12.4.0

8

13.4.0

8

14.4.0

8

15.4.0

8

16.4.0

8

17.4.0

8

18.4.0

8

19.4.0

8

20.4.0

8

21.4.0

8

22.4.0

8

23.4.0

8

24.4.0

8

25.4.0

8

26.4.0

8

27.4.0

8

28.4.0

8

29.4.0

8

30.4.0

8

1.5.08

2.5.08

3.5.08

4.5.08

Cl- (

µg

/m3)

0

4

8

12

16P

rep

.(m

m)


Sea salt

0

2

4

6

8

10

12

7.4.08

8.4.08

9.4.08

10.4.0

8

11.4.0

8

12.4.0

8

13.4.0

8

14.4.0

8

15.4.0

8

16.4.0

8

17.4.0

8

18.4.0

8

19.4.0

8

20.4.0

8

21.4.0

8

22.4.0

8

23.4.0

8

24.4.0

8

25.4.0

8

26.4.0

8

27.4.0

8

28.4.0

8

29.4.0

8

30.4.0

8

1.5.08

2.5.08

3.5.08

4.5.08

NO

3- (

µg

/m3)

0

4

8

12

16

Pre

p.(

mm

)


Nitrate

Amato et al., Atm. Env. 2009

Cleaning site Control site Cleaning site Control site

THE PROBLEM OF PM

EFFECT OF WASHING ON AEROSOL TYPES

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http://images.google.com/imgres?imgurl=http://www.lastampa.it/redazione/cmssezioni/cultura/200903images/insoddisfatto01p.jpg&imgrefurl=http://www.lastampa.it/redazione/cmsSezioni/cultura/200903articoli/42215girata.asp&usg=__vAuDj_VoGbLpx_EkYDk8enmiTBs=&h=104&w=100&sz=5&hl=en&start=8&sig2=4Zkn7s8Fqq9XcV8nJFSz6A&um=1&tbnid=QsW7LfH787_6rM:&tbnh=84&tbnw=81&prev=/images?q=faccetta+sorridente+triste&hl=en&rls=com.microsoft:en-us:IE-SearchBox&rlz=1I7ACAW&sa=N&um=1&ei=LNS5SqWFL9fNjAeK0Lm7Bg

EFFECTIVENESS OF CMA AND MGCL2 IN BARCELONA

• Four kerbside monitoring vans, one background monitoring station

• CMA and MgCl2 applications at 6 am (dosages 10-15 g m-2 )

• Friction tests

• Conductivity tests

THE PROBLEM OF PM

MODELING CONTRIBUTION FROM ROAD DUST EMISSIONS

• Yearly average 2010

in Barcelona

(URBIS model)

Amato et al., in prep

THE PROBLEM OF PM

PM10

Road dust

SPATIAL VALIDATION

With resuspension

R2 = 0.6432

0

10

20

30

40

50

0 10 20 30 40 50

Observed PM10

Mo

de

lled

PM

10

Kerbside

Background

Without resuspension

R2 = 0.5751

0

10

20

30

40

50

0 10 20 30 40 50

Observed PM10M

od

elle

d P

M1

0

Kerbside

Background

THE PROBLEM OF PM

TEMPORAL VALIDATION (1-HOUR) VS COARSE PM INCREMENT

THE PROBLEM OF PM

• Levels if air pollutants in 39 schools

• 2 weeks measurements at each school

• Indoor and outdoor simultaneoulsy

• A UB reference site

Reference Station

NO2 (µg·m3)

< 40

40 – 60 > 60

EC (µg·m3)

< 1.5 1.5 – 2.3

> 2.3

PM2.5 (µg·m3)

< 35 35 – 60

> 60

N (103 pt·cm3)

< 17 17 - 27

> 27

BREATHE Schools EC levels perimeter

Low High

URBAN BACKGROUND OR TRAFFIC EXPOSURE?

INDOOR OUTDOOR REFERENCE STATION

Mean SD Mean SD Mean SD

NO2

(µg·m-3) 32 13 50 19 42 20

PM2.5 (µg·m-3) 52 16 43 24 19 8

N (pt·cm-3)

17371 6673 22972 9514 16081 6034

BC (µg·m-3) 2.4 0.9 2.5 1.1 1.7 0.8

Levels

NO2 outdoor levels for the rest of schools in Barcelona = 50 µg·m-3

• Very high levels of PM2.5 in schools Local focus of PM2.5

• Pollutants levels found at schools more similar to traffic sites than

to urban background

URBAN BACKGROUND OR TRAFFIC EXPOSURE?

Conclusions

1. Air Quality has markedly improved in the last decade concerning PM

2. The concentration of ultrafine particles in our cities is greatly affected by the

photochemical processes from the center of Europe, not only by primary traffic emissions

3. Urban NH3 may contribute to increase difficulty of abating PM2.5 in some cities. It is

important to control these emissions

4. Except in specific areas, in Spain residential biomass burning does not contribute to

increase levels of PM and PAHs in a large proportion as it occurs in central Europe

5. Road dust contributes 20-35% to urban PM10 in Spain, causing high number of

exceedances

6. Road dust emission potential in Spain is governed by mineral particles (road wear, soil,

works) and meteorology

7. Road washing showed decrease at kerbside up to 7-10% of daily PM10

8. First results on CMA and MgCl2 in Mediterranean cities will be available soon (AIRUSE)

9. The population of our cities (with reference to the schools) is subject to pollutant exposure

levels intermediate between stations traffic and urban background

Thanks for your attention!

[email protected]

BDEBATE, MAGRAMA-LIFE+AIRUSE-BREATHE-ERC Ministerio de Economía y Competitividad del Gobierno de España

Departamentos Calidad del Aire: Generalitat de Catalunya, Andalucía, Aragón, Asturias, Baleares, Canarias, Cantabria, Castilla la Mancha, Castilla León, Euskadi, Extremadura, Galicia, Generalitat Valenciana, Madrid, Melilla, Murcia, Ayuntamientos de Madrid y Barcelona

ACKNOWLEDGEMENTS

Motor exhaust Other mineral

Trend of source contributions (Córdoba 2007-2010)

Amato et al., in prep.

Road dust

THE PROBLEM OF PM



Exposure during commuting

Car Bus Pedestrian Motorbike Cycle Taxi Metro Mexico PM2.5

1 -- 70 -- -- -- -- 61

PM2.52 -- 51 -- -- -- -- 33

Houston PM3.5

3 35 -- -- -- -- -- --

New York PM2.5

4 -- -- -- -- -- -- 62

London PM2.5

5 -- -- -- -- -- 33 246

London PM2.5

6 36 39 -- -- 30 -- 202

Southampton, UK PM3.5

7 -- -- -- -- 135 -- --

Manchester, UK PM4

8, 9 42 338 -- -- 54 -- --

Belgian cities PM10

10 35-75 -- -- -- 42-78 -- --

Dublin PM2.5

11 83 128 63 -- 88 -- --

Florence PM2.5

12 -- 33-75 -- -- -- 20-70 --

Munich PM10

13 -- 137 -- -- -- -- --

Taipei PM10

14 42 70 -- 113 -- -- 65

PM2.514

22 39 -- 68 -- -- 35 PM1

14 16 31 -- 48 -- -- 26

Hong Kong PM10

15 -- 97 -- -- -- 58 50

PM2.515

-- 71 -- -- -- -- 33 Guanzhou PM10

16 -- 156 -- -- -- 104 67

PM2.516

-- 123 -- -- -- 89 44 Barcelona Mean PM10 -- -- -- -- -- -- 83 PM2.5 -- -- -- -- -- -- 27 PM1 -- -- -- -- -- -- 25 Barcelona L9 PM10 -- -- -- -- -- -- 60 PM2.5 -- -- -- -- -- -- 19 PM1 -- -- -- -- -- -- 16

0

100

200

300

400

500

600

700

05/07

6:00

06/07

6:00

07/07

6:00

08/07

6:00

09/07

6:00

10/07

6:00

11/07

6:00

12/07

6:00

13/07

6:00

14/07

6:00

15/07

6:00

16/07

6:00

17/07

6:00

18/07

6:00

19/07

6:00

20/07

6:00

21/07

6:00

22/07

6:00

23/07

6:00

24/07

6:00

25/07

6:00

PM

x (

µg

/m3)

PM10 PM2.5 PM1

SAGRERA STATION (L9) 05-25 July 2011

10

0

30

20

50

40

60

Fondo

rural

Fondo

urbano

Fondo

industrial

Hotspot

tráfico/

industrial

PM

10

µg/m

3

10

0

20

40

30

Fondo

rural

Fondo

urbano

Fondo

industrial

Hotspot

tráfico/

industrial

PM

2.5

µg/m

3

PM10PM2.5

Fondo

suburbano

Fondo

suburbano

10

0

30

20

50

40

60

Fondo

rural

Fondo

urbano

Fondo

industrial

Hotspot

tráfico/

industrial

PM

10

µg/m

3

10

0

20

40

30

Fondo

rural

Fondo

urbano

Fondo

industrial

Hotspot

tráfico/

industrial

PM

2.5

µg/m

3

PM10PM2.5

Fondo

suburbano

Fondo

suburbano

1999-2007 2009-2010 1999-2007 2009-2010

THE PROBLEM OF PM

0

1

2

3

4

5

6

Ba

rce

lon

a

Ma

dri

d

Va

lèn

cia

Am

ste

rda

m

Be

lgra

de

Be

rlin

Be

rn

Bo

log

na

Bu

da

pe

st

Sto

ckh

olm

Fire

nze

Fra

nk

furt

Ge

no

a

Ha

mb

urg

He

lsin

ki

Lon

do

n2

00

7

Luxe

mb

urg

Mil

an

Mu

nic

h

Na

po

li

Osl

o

Pra

ha

Ro

ma

To

rin

o

Wie

n

Zu

rich

Cars x 1000 / km2

Alta densidad de vehículos (#/km2),

Además >50% de los vehículos circulantes en la ciudad don externoa a la misma

0

500

1000

1500

2000

2500

3000

Ba

rce

lon

a

Ma

dri

d

Va

lèn

cia

Am

ste

rda

mB

elg

rad

e

Be

rlin

Be

rnB

olo

gn

a

Bu

da

pe

st

Sto

ckh

olm

Fire

nze

Fra

nk

furt

Ge

no

a

Ha

mb

urg

He

lsin

ki

Lon

do

n2

00

7

Luxe

mb

urg

Mil

an

Mu

nic

h

Na

po

li

Osl

o

Pra

ha

Ro

ma

To

rin

o

Wie

n

Zu

rich

Cars x1000

THE PROBLEM OF NO2

Ámsterdam

Madrid

Barcelona

500m

Napoli

THE PROBLEM OF NO2

Reche et al. (2013) Atmospheric Environment, submitted

URBAN NH3

THE PROBLEM OF PM

AOT40 [expressed in (µg/m3·h] = as sum of the difference between hourly levels exceeding 80 µg/m3 and 80 µg/m3 along

a given period using only hourly values measured between 8.00 and 20.00 h, Central Europe Time (CET), for every day.

Target value

Protection human health

Maximum of 8 h means of a day 120 µg/m3 O3 not exceeding 25 day/year

mean for 3 years

Target Value

Protection of vegetation

AOT40, hourly values from May- July 18.000 µg/m3·h O3 not exceeding

as a mean of 5 years (c)

Information threshold value: hourly 180 µg/m3 O3

Alert threshold value : hourly 240 µg/m3 O3

High levels out of urban agglomerations

CRITICAL AIR QUALITY PARAMETRES

Urban air quality: from ultrafine to coarse particles

Documents

Transcript of Urban air quality: from ultrafine to coarse particles