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HEALTH EFFECTS OF TRAFFIC AIR POLLUTION: new
findings for regulation
Jordi SunyerCREAL
June 2010
Known adverse effects of airborne particles (PM) on health WHO air quality guidelines - global update 2005
- Mortality and hospital admissions in chronic obstructive pulmonary disease patients
- Exacerbation of symptoms and increased use of therapy in asthma
- Mortality and hospital admissions in cardiovascular disease patients
- Mortality and hospital admissions in diabetes mellitus
- Increased risk for myocardial infarction
- Lung inflammation
- Systemic inflammation
- Endothelial and vascular dysfunction
- Development of atherosclerosis
- Increased incidence of infection
- Respiratory cancer
Ultrafine particles promote early atherosclerosis and systemic oxidative stress
Araujo et al. (Circ Research, 2008)
big3dist
s(bi
g3di
st, 3
)
0 100 200 300 400 500
-10
1
Distance to busy road0 100 200 300 400 500 meters
Ast
hma
risk
RR=1.0
Southern CaliforniaAssociation between residential distance to busy roads
and childhood asthma
McConnell et al, EHP2006
RR=1.4
Novel evidenceTraffic proximity and chronic disease
HEI report*
Exposure metricOutomceAuthor
Living ≤50m to major roadAsthma incidenceMorgenstern et al
2007 Munich, Germany
Living within 50m major roadsCoronory Heart diseaseHoffmann et al. 2009,Germany
Distance from freeway or main road (50m)
Cardiovascular mortalityCerebrovascular mortality
Fickelstein, Jerrett, & Sears 2005Ontario, Canada
*Source: Health Effects Institute panel on the health effects of traffic-related air pollution. Traffic-related air pollution: a critical review o the literature on emissions, exposure, and health effects.
New evidenceTraffic proximity and exposure
Beckerman et al. 2008
Particulate Matter and health effectsGaps of knowledge
• What is causing health effects?
• What are the sources of the most toxic agents?
• What are the biological mechanisms of toxicity of agents?
Outline
• 1. Size of PMs
• 2. Coarse PM and Saharan dust
• 3. New effects early in life
• 4. Impact assesment
Urban PM fractions and health effects in Barcelona Mass distribution
11.180.11.9(10.3)20.0931PM1 (µg/m3)
4.545.50.6(3.8)5.5931PM2.5-1 (µg/m3)
11.093.10.1(9.5)14.0931PM10-2.5 (µg/m3)
IQRMax.Min.(sd)MeannVariables
1.00PM1
0.241.00PM2.5-1
0.090.451.00PM10-2.5
PM1PM2.5-1PM10-2.5Correlation
Urban PM fractions and health effectsPerez et al.2009
Odds ratio per 10 ug/m3*
1.063(1.004-1.124)
Lag1
1.028(1.000-1.058)
Lag1Not significantPM1
Not significantNot significant1.206 (1.028-1.416)
Lag2PM2.5-1
1.098 (1.030-1.171)
Lag1
1.059 (1.026-1.094)
Lag1Not significantPM10-2.5
Cerebrovascularmortality
Cardiovascular mortality
Respiratory mortality
Fraction
*Only maximum lag effect for tri-pollutant model presented
PM fraction composition in BarcelonaElemental carbon
Adapted from Perez et al. Atmos. Environ. 2008
78%
PM fraction composition in BarcelonaMetals
Adapted Perez et al. Atmos. Environ. 2008
Combustion Break, tire and road erosion
Saharan dust outbreaks in Barcelona
•Occur 7-15 times a year•Predominant in spring and autumn•On average, outbreak lasts 3-5 days (Rodriguez et. al 2003)
Saharan dust and health effectsDistribution daily mass concentrations (µg/m3)
0.07-93.1
1.6-36.7
0.07-93.1
6.1-85.0
9.8-65.2
6.1-85.0
Min-Max
10.7
11.0
10.7
11.5
12.2
12.8
IQR
PM10-2.5
15.1 (9.7)602All days
16.4 (7.8)90Saharan dust days
14.9 (10.0)512Non Saharan dust days
24.0 (11.6)512Non Saharan dust days
29.9 (11.2)90Saharan dust days
24.9 (11.7)602All days
PM2.5
Mean (SD)nPollutant
R correlation PM2.5-PM10-2.5=0.34 (all days, Lag 1)
R correlation PM2.5-PM10-2.5=0.22 (Saharan dust days, Lag 1)
Saharan dust and health effectsResults-Total mortalityLag 1 per 10 µg/m3*
0.558
--
Pinteraction
Yes
No
1.084(1.015, 1.158)
1.050 (1.005, 1.097)
0.052
1.013 (0.992, 1.034)
1.035 (1.016, 1.055)
By Saharan dust days
--1.016
(0.996, 1.036)1.032
(1.015, 1.05)All days
P interaction
PM10-2.5PM2.5
*Two-pollutant model
Saharan dust and health effectsGrowing evidence
*: p <0.05 for comparision of mass adjusted concentrations
Chemical composition of PMs in BarcelonaSaharan dust days (n=9) vs Non-Saharan dust days (n=80)
TRAFFIC, SUSCEPTIBILITY AND
CHILDHOOD ASTHMA(McConell R; Env Health Persp 2006)
UFP and brain in rats• Intratracheal instillation of particles<100 nm labeled
with tech-99, radioactivity was subsequentlydetected in the brain (Nemmar AJRCCM 2001)
• Direct translocation Mn (8nm) in contralateralolfactory bulb (Elder EHP 2006)
• PM>200 nm (TiO2) may be phagocytized by macrophages and dendritic cells which may carrythe particles to lymph nodes in the lung or to thoseclosely associated with the lungs (Peters 2006)
• Oxidative stress and pro-inflammatory cytokinesoverexpressed in brain tissue (Calderon C 2008, Campbell 2009)
57 sampling points were selected to represent the gradient of exposure in the cohort
Cohort addressesSampling points500m- grid
1. SAMPLING SITES SELECTION
SPAINSabadell
SPAINSabadell
SPAINSabadell
Longitudinal growth curves
20
300
580
860
1140
1420
1700
1980
2260
2540
2820
3100
3380
3660
3940
Est
imat
ed
Fet
al W
eig
ht (
gr)
10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
gestational age (weeks)
female male30
70
110
150
190
230
270
310
350
Hea
d ci
rcum
fere
nce
(m
m)
10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
gestational age (weeks)
female male
Head circumference Estimated fetal weight
BTEX
-59.7 (-130.9 to 11.5)
3rd
trimester
-101.9 (-176.2 to -27.6)
2nd
trimester
-52.5 (-125.8 to 20.8)
1st
trimester
-76.6 (-146.3 to -7.0)
9-month
Birth weight (g) for an IQR increase (µg/m3) in exposure to NO2 during pregnancy and each trimester (Aguilera 2009)
a Adjusted for child's sex, gestational age, season of conception, parity, maternal educational
level, maternal smoking, maternal height and pre-pregnancy weight and paternal height
Change in Z-scores of fetal size and growth for an IQR increase in exposure to NO2 (µg/m3) between
weeks 1-12(Aguilera, EHP2010)
* Adjusted for season of conception, parity, maternal education, and maternal smoking
-12
-10
-8
-6
-4
-2
0
2
4
6
8
10%
Cha
nge
FL HC AC BPD EFW
w_12 w_20 w_32 w_12_20 w_20_32
Mortality WHO scenario
2% (1%-2%)520 (350-690)Death due to acute exposure per year
15 (7-22)
3.500 (2.200-4.800)
Mean (95% CI)
13% (6%-19%)Infant deaths per year
Of which
12% (7%-16%)Deaths per year
% of total cases(95% CI)
Indicator
Morbidity per yearWHO scenario
Hospitalizations
Respiratory
3% (2%-5%)1.150 (630-1.670))Respiratory causes
2% (1%-3%)620 (310-930)Cardiovascular causes
11% (6%-14%)12.400 (6.400-15.200)Asthma attacks children
11% (6%-16%)41.500 (21.000-60.500)Asthma attacks adults
31.100 (17.500-40.500)
5.100 (550-8.500)
Mean (95% CI)
49% (28%-64%)Acute bronchitis children
25% (3%-41%)Chronic bronchitis adults
% of total cases(95% CI)
Indicator
Estimating impact of traffic exposurePopulation distribution from roads >10,000 vehicle/ day
Conclusions: Particle Size
– In urban areas, all PM size fractions have health effects.
– PMs generated by both traffic-related combustion and non-combustion processes may increase mortality.
– PMs generated by both traffic-related combustion and non-combustion processes may share a common mechanism of action.
Conclusions• Saharan dust
– In some areas exposure to coarse PMs from natural sources such as Saharan dust may increase daily mortality.
• Early life exposure – Provides unexpected new effects due to air
pollution
• Health impact assessment– Very likely have been underestimated
Thank [email protected]
Perera FP. Env Health Persp2006;114:1287-92.
• PAH in particulate mode—collected with individual pumps during two consecutive days in 181 pregnant women from New York City (USA)— was associated to mental health measured at age 3 in the offspring
• Limitations: The short measurement of the exposure (only two days), their narrow variability (only low and high levels), and the poor specificity of PAH (the principal source is smoking)
Suglia SF. Am J Epidemiol2008;167:280-6.
• Average air pollution during childhood (carbon particles at home address derived by spatial modeling) to intelligence at age 9 in 202 children from Boston (USA)
• Limitations: follows only 20% of those recruited and did not measure prospectively the variations in air pollution or the time-activity patterns of the participants. No adjustment for noise.
3%Tire erosion
100%Total
30%Soil resuspension
6%Pavement erosion
5%Brake erosion
56%Combustion
% of PM10 emissions in Barcelona
Source
Source: Departament de Mediambient i Habitatge, 2007
Non-combustion traffic related particlesis an important source of health effects
PM10 in Barcelona metropolitanarea
** Mapa elaborado por el Departamento de Medio Ambi ente y Vivienda
Media anual de PM10 indicador de la contaminació atmosfèrica