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Particulate and Lung Disease David Brown EHHI

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Particulate and Lung Disease David Brown EHHI Powered By Docstoc
					Particulate and Lung Disease
David Brown Sc.D. EHHI

How should the Public Health system work with uncertain but plausible health hazards?

Can We Assume That Compliance With Federal Clean Air Standards Protects Against Short Term Health Impacts?
• Standards are set by expert committees • There are safety factors built in standards • Standards must have a bright line for attainment • Compliance is monitored

Public Health Risks Are Significant
Particles are linked to:  Premature death from heart and lung disease  Aggravation of heart and lung diseases  Hospital admissions  Doctor and ER visits  Medication use  School and work absences  And possibly to  Lung cancer deaths  Infant mortality  Developmental problems, such as low birth weight in children
18 Feb 2004 Environment Northeast 7

DIESEL PARTICLE
PM 2.5 RANGE

How particles increase exposure of irritants to the deep lungs
WATER ADSORBED

Irritant gases

Deep lung exposure to irritants
IRRITANT GAS ABSORBED IN WATER

Results from the Harvard Six-cities study: All Cause Mortality Rates most exposed to least exposed City Fine Particles
• • • • • • All cause death 1.26 (1.08-1.47) Lung Cancer 1.37 (0.81-2.31) Cardio pulmonary 1.37 (1.11-1.68) Other causes 1.01 (0.79-1.30) Range of exposure 11-29.6 ug/m3 Dockery, NEJM 1993; 329: 1753-1759

Health actions from exposures of 2 hours or less.
• Peters etal. pm 2.5 & myocardial infarction
– 1.48 odds ratio 2 hr after 25ug/m3 increase – 1.69 odds ratio 1 day after 20ug/m3 increase

• Gent etal. Severe asthma & O3, pm 2.5
– 35% increase wheeze 1 hr after 50ppb O3 inc. – 47% increase in chest tightness 1 hr after. – 1.24 odds ratio Chest tightness 12-18ug/m3 pm

Moral stewardship in search of an intellectual framework.
Theories of Deontology and Utilitarianism 1) Value of an act is found within the act.
2) The value of an act is found in the outcome. Four ideas 1600-1700: Bacon…..A new science Newton…Reductionism a new approach Kant…….The whole is more than the sum of the parts Bentham….Charity- science serves the needs of men.

Uncertainty paradox of Good Science in Public Health
• Science- Assume something is not true until proven at a level of statistical certainty.
– Preferred action is to collect more data

• Public Health- Assume something may be true
based on suggestive but statistically inconclusive evidence – Preferred action is to intervene to prevent potential health effect.

Result of application of “Good Science” is loss of time, lives and treasure
• • • • • • • Smoking Dioxin Asbestos Chordane Mercury Particulate Asthma at the end of the 20th century

Health events that occur to students and teachers in schools
• • • • Accidents Colds, flu and headaches Asthmatic attacks/ treatment Others

• Could any of these be environmental?

Health events are rarely linked with environmental exposures
• • • • • Most health events have multiple causes Only a small part of the group responds The exposures are not known sufficiently Investigations are complex and data is sparse The cause of the effect is other than environmental but there may be an environmental role

But there are environmentally
induced diseases and responses
• Some are related to molds and other factors in buildings • Some have been found to be related to 6 to 12 pollutants found in outside air • Two agents, Ozone and PM, are linked to short term asthmatic and cardiac responses

• How do we respond to these agents?

It is necessary to understand the following
• The Health Effects that are related to air quality • Pollutant sources • Movement of air into and within the school • Ways to reduce the potential for exposures

“Bad” Air Quality
• • • • • • • Ozone Particulate Matter Nitrogen Dioxide Sulfur Dioxide Hazardous Air Pollutants (Toxins) Lead Carbon Monoxide

Ozone
Adverse effects following low-concentration exposure:
– – – – – chest pains, coughing, nausea, throat irritation, and congestion.

It also can worsen bronchitis, heart disease, emphysema, and asthma, and reduce lung capacity.

Studies conducted in the northeastern United States and Canada that show that ozone air pollution may be associated with 10-20 percent of all of the summertime respiratory-related hospital admissions.

US Environmental Protection Agency, Criteria Document in support of proposed 8-hour ozone standard

Particulate Matter
• Premature death; • Respiratory related hospital admissions and emergency room visits; • Aggravated asthma; • Acute respiratory symptoms; • Chronic bronchitis; • Decreased lung function; and • Work and school absences.

Particulate Matter
• EPA has revised the primary (health-based) PM standards by adding a new annual PM2.5 standard set at 15 micrograms per cubic meter (µg/m3) and a new 24-hour PM2.5 standard set at 65 µg/m3. • EPA is retaining the current annual PM10 standard of 50 µg/m3 and adjusting the PM10 24-hour standard of 150 µg/m3 by changing the form of the standard.

EPA’s AQI for PM-2.5
AQI Index Values AQI Descriptor Concentration range (24-hour ave.)

Color

0 to 50 51 to 100

Good Moderate Unhealthy for Sensitive Groups Unhealthy Very Unhealthy

0 g/m to 3 15.4 g/m
3

Green Yellow Orange Red Purple

15.5 g/m to 3 40.4 g/m
3

101 to 150

40.5 g/m to 3 65.4 g/m
3

151 to 200 201 to 300

65.5 g/m to 3 150.4 g/m
3

150.5 g/m to 3 250.4 g/m
3

1

What does this mean?
• Air exposures induce plausible health risks from short term elevation during regulatory attainment of clean air standards. • Science should be brought to the legal decision making. • Investigation of the quantitative health risk from localized short term air exposures is needed.

Question: How to use existing information to assess environmental exposures? • Attainment model approach • Evoked response model approach • Statistical analyses
– – – – – Expected spatial distributions Expected temporal distributions S plus approach Cluster analysis Edge theory analysis

As part of the process to determine whether an area meets the EPA particulate matter standard, this 3-month long series of hourly observations would be collapsed to a single value… 9.2 ug/m3… Totally obscuring any “structure” or other “content” within the data set (Carmine Dibattista, CT DEP).
60

Hourly Fine Aerosol
50

40

ug/m3

30

20

10

0

1/ 1/ 01

8/ 1/ 01

15 1/ 1 /0

22 1/ 1 /0

29 1/ 1 /0

5/ 2/ 01

12 2/ 1 /0

19 2/ 1 /0

26 2/ 1 /0

5/ 3/ 01

12 3/ 1 /0

19 3/ 1 /0

26 3/ 1 /0

5/23 5/24 5/25 5/26 5/27 5/28 5/29 5/30 5/31 6/1 6/2 6/3 6/4 6/5 6/6 6/7 6/8 6/9 6/10 6/11 6/12 6/13 6/14 6/15 6/16 6/17 6/18 6/19 6/20 6/21 6/22 6/23 6/24 6/25 6/26 6/27 6/28 6/29 6/30

Hfd da ave NH da Ave Wby da ave 6.00 0.08 1.70 8.09 3.49 4.17 8.52 4.60 5.12 8.87 4.42 4.60 6.96 4.32 4.50 12.60 11.87 13.00 11.85 12.67 10.37 4.10 1.78 3.35 5.68 2.40 5.20 7.40 5.99 5.74 7.51 8.48 8.66 9.08 6.24 7.40 7.79 10.03 10.20 8.98 7.24 9.88 7.10 5.26 7.46 7.39 5.99 7.65 7.92 9.23 7.08 8.32 6.07 5.41 9.41 7.95 6.04 19.03 23.03 12.58 13.52 14.94 9.43 26.58 35.21 28.76 30.15 28.81 22.66 23.90 18.33 15.85 13.35 11.26 11.98 7.36 3.27 4.05 12.46 9.10 9.49 19.25 22.88 16.13 27.71 23.72 21.57 11.18 14.67 7.86 10.60 10.39 6.34 8.73 9.45 6.25 6.41 5.80 5.03 9.71 7.33 4.54 13.36 12.54 8.85 22.21 22.36 17.70 33.57 32.86 30.01 8.06 7.71 6.31 3.06 3.06 1.34

HFD max

5/23 5/24 5/25 5/26 5/27 5/28 5/29 5/30 5/31 6/1 6/2 6/3 6/4 6/5 6/6 6/7 6/8 6/9 6/10 6/11 6/12 6/13 6/14 6/15 6/16 6/17 6/18 6/19 6/20 6/21 6/22 6/23 6/24 6/25 6/26 6/27 6/28 6/29 6/30

8.33 11.90 16.33 11.97 10.23 15.13 15.67 6.73 11.87 12.10 11.47 14.00 12.47 12.13 8.97 10.60 10.27 11.33 14.13 25.33 18.03 44.43 35.87 32.33 15.43 14.70 18.27 31.93 45.33 18.63 22.53 12.00 9.80 22.30 18.27 33.90 43.43 17.70 12.10

NH max Wby max 0.60 2.77 7.73 8.20 7.90 7.93 5.67 6.23 8.03 8.77 15.63 16.93 16.97 12.97 2.40 5.13 4.03 11.30 9.47 10.30 9.87 12.57 14.40 13.80 20.47 16.97 14.30 12.20 9.73 11.60 9.97 20.17 21.63 9.57 13.13 8.43 15.03 10.57 27.07 17.40 20.63 15.70 53.87 43.63 35.30 30.80 29.27 20.43 16.03 15.43 7.83 11.17 15.63 13.57 29.67 29.47 36.37 38.40 25.13 16.43 22.17 12.97 14.10 10.87 11.03 7.97 14.13 8.00 19.43 13.33 34.97 31.43 39.53 39.33 16.50 12.87 12.10 7.47

PM 2.5 New Haven, Hartford and Waterbury (ug/m3)
June daily average 70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00 5/29

6/3

6/8

6/13

6/18

6/23

6/28

7/3

Fine particles, or haze, restrict our ability to see long distances
Unadjusted Hourly conc. of fine particles – 4 g/m3

Hartford
Oct. 8, 2002 4 p.m. EDT

Hartford
Oct. 2, 2002 4 p.m. EDT

Unadjusted Hourly conc. of fine particles – 24 g/m3

33 Air Toxics in Connecticut
8% Highw ay 43% Off Highw ay Area Point

29%

20%

Consider the different sources of toxics in outdoor air separately
• Transport from other regions
– Fossil fuel and ozone

• Transport from the within the region
– Utilities, fossil fuel and transportation

• Local sources such traffic and area sources
– Transportation, off road commercial

• Immediate sources near the buildings
– Vehicles diesel, pesticides and construction

School child exposure, continuous nephelometer 15 minute averages
0.1 0.08 0.06 0.04 0.02 0
07 :3 7 : 08 26 :2 5 : 09 26 :1 3 : 10 26 :0 1 : 10 26 :4 9 :26 11 :3 7 : 12 26 :2 5 : 13 26 :1 3 : 14 26 :0 1 : 14 26 :4 9 : 15 26 :3 9 :26

mg/m3

Bus 7:30 to 8:40 and 2:30 to 3:40

School child exposure, continuous nephelometer
Central Ct. town, PM 10, 5 min. moving average

0.12 0.1 0.08 0.06 0.04 0.02 0
School School School School School School School School School School School School Wait BUS BUS

mg/m3

8:30 am to 3:35 pm

PM 2.5 Ct. Coastal Town ( 5min moving average) 17 minute bus ride
0.08
mg/m3

0.06 0.04 0.02 0
School School School School School School School School School School School BUS Wait

8:15am to 3:20 pm

School Child Exposure Continuous Nephelometer

Individual Student Exposure to Particulates (PM 2.5 ug/m3)
200 180 160 140 120 100
Maximum

80
75th %

60
Mean

B

B B B B

40 20

25th %

0
Minimum

Bridgeport 1

Bridgeport 2

Fairfield

Haddam

Vernon

Red Line Locates Average Daily Connecticut Urban PM 2.5 (12.5 ug/m3)

Comparing ambient pm with School and Buses
120.00 100.00 80.00 60.00 40.00 20.00 0.00
1 1 1 1 /0 /0 /0 /0 /0 1

120.0 100.0
24 hr ave Max hr

80.0 60.0 40.0 20.0 0.0
Apr 24 Mar 15 Mar 20 Mar 29 Feb 27 Apr 26 M ar 8' May 14 May 15

ave school ave Bus

2/ 27

3/ 27

4/ 27

5/ 27

6/ 27

Compare Bus to School and Ambient monitor for PM.
100 80 60 40 20 0
24 hr ave Max hr Ave school Ave bus

Fe b 27 M ar M 8' ar 15 M ar 2 M 0 ar 29 Ap r2 Ap 4 r2 M 6 ay 1 M 4 ay 15

Difference in amount of exposure between times of day
8/27/99 PM 2.5 exposure ug
35.00 30.00 25.00 20.00 15.00 10.00 5.00 0.00
3.0 0 6.0 0 9.0 0 12 .00 15 .00 18 .00 21 .00 24 .0 Ma 0 x3 h Av r ed ly

Pm 2.5 exposure for 3 hr periods
160.00 140.00 120.00 100.00 80.00 60.00 40.00 20.00 0.00 8/27/99 24.00 21.00 18.00 15.00 12.00 9.00 6.00 3.00

Actual inhaled dose varies between day, time of day, activity and location for child
Ug PM/day shown by 3 hr dose indoor and outdoor ( based on ambient levels and normal activity) 1000.00 900.00 800.00 700.00 600.00 500.00 400.00 300.00 200.00 100.00 0.00
8/ 20 /9 9 8/ 22 /9 9 8/ 24 /9 9 8/ 26 /9 9 8/ 28 /9 9 8/ 30 /9 9 9/ 1/ 99 9/ 3/ 99 9/ 5/ 99 9/ 7/ 99 9/ 9/ 99

24.00 21.00 18.00 15.00 12.00 9.00 6.00 3.00

Buildings have memories of outside exposures
A 400 ppm diesel particulate emission from a bus that idles for one hour next to the school exposes the students for over 3 hours
One half the volume in each hour

One half the volume out each hour School
250 200 150 100 50 0 inside outside

ou ts id e 1s th ou r 2n d ho ur 3r d ho ur

Possible diurnal influence on school air
25% air change in building (ug/m3) out door contribution only

50 40 30 20 10 0
10 12 10 0 2 4 6 8 2 4 6 8

outdoor indoor

Possible diurnal influence on school air
50% exchange rate outdoor contribution only 50 40 30 20 10 0
12 0 3 6 9 3 6 9

outdoor indoor

Comparison of PM2.5 24-hr avg and 3-hr max avg for New Haven CT site, 2001
80.00 70.00 24 hr avg 60.00 50.00
ug/m3

3 hr max avg

40.00 30.00 20.00 10.00 0.00
1 106 121 136 151 166 181 196 211 226 241 256 271 286 301 316 331 346 361 16 31 46 61 76 91

PM2.5 values ascending by day, 2001

Analyzing fine PM data by comparing 3-hr exposure distributions to daily and annual averages reveals significant underestimation of potential health risk.

Effect of „morning‟ decrease in local windspeed and mixing volume during sun rise
Hourly average pm 2.5 Jan/jun 2001

12 10 8 6 4 2 0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Local air quality events that are seen inside the school
• • • • • • • • • Buses idling Morning traffic Commercial vehicles Construction Sun rising and sun setting Nocturnal Jet Sun rising and sun setting Changes in the weather Pesticide applications

Information from existing data
• Vt. monitoring data shows 11 compounds drive most of risk. • Using CEP and NATA, EPA characterized types of risk and sources at county levels. • Multi-city studies determine level of health risks from PM and ozone nationally. • Levy shows local and regional risk from two power plants.

Fine Particulates PM2.5 Spatial Distribution in NE
• Current monitoring network analyses average away PM2.5 variability. • Are spatial and temporal factors (local sources, unique terrain, meteorology) influencing concentrations and creating PM gradients? • If so, micro-scale exposure assessments must be refined. • May reveal downward bias of health effects estimates: are missing populations at risk?

Lessons learned or hints
• Short term local exposures are disproportionate, 5 to 15% of days in NE. • Sources of variability are:
– – – – – Location Season Time of day Sources Meteorology, weather patterns in NE

Six ways to reduce the potential for exposures
• Identify sources near the building • Restrict emissions during periods of poor air mixing • Reduce idling of engines during the 3 hours prior to student occupancy of building • Increase „make up‟ air during clean periods • Prevent stagnation of air within the school • Adjust student activities

Conclusions
• A more robust reporting statistic is needed in addition to attainment levels. • The weather variable is discontinuous existing in 4 forms in the NE. • National analyses do not characterized NE risk. • Averaging time is critical for understanding health risk • Health outcome should drive the risk analysis