1

What did we learn? :Effect of Air Pollution on Health Status of

Participants

2

Figure 13. Scatterplots of selected air pollutant/health outcome associations

Scatter plot of % "yes" of Wheezing on bihourly log among children w ith persistent asthma vs. previous

day mean PM10 in ppb.

20.0

25.0

30.0

35.0

40.0

0.0 10.0 20.0 30.0 40.0 50.0 60.0

PM10 (Lag 1)%

"yes

"

Scatter plot of % "yes" of Wheezing on bihourly log among children with persistent asthma vs. previous

day mean SO2 in ppb.

20.025.030.035.040.0

0.0 5.0 10.0 15.0 20.0

SO2 (Lag 1)

%"y

es

"results from corresponding regression model: OR=1.13; p-value=0.032

results from corresponding regression model: OR=1.34; p-value<0.0001

3

Presence of SymptomsFigure 34. Odds ratios (OR)1 for presence of symptoms reported on bi-hourly logs for changes in measured levels of PM102, SO23 and NO24 at the school grounds for the prior day among all students with persistent asthma5: from logistic regression models using generalized estimating equations (GEE)6

1.07 1.05 1.07 1.09 1.06

1.16 1.13

1.34

1.18 1.141.08 1.09

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Cough Wheezing Chest tightness or heaviness Shortness of breath

4

Results from PF & FEV1Figure 38. Percent change in within-day variability1 of FEV1 and peak flow (PF) and of lowest best2 FEV1 associated with measured levels of PM103, SO24 and NO25 at the school grounds on the prior day among all students with persistent asthma6: from logistic regression models using generalized estimating equations (GEE)7

-2.88

5.38 5.17

3.824.13

5.13

3.16

-4.52

-2.91

-6

-4

-2

0

2

4

6

PM10 SO2 NO2 PM10 SO2 NO2 PM10 SO2 NO2

within_FEV1 within_PF lowest_best_FEV1

5

Where Are the Pollutants Coming From?

We used three methods to analyze pollutant sources:

Wind and Pollution ‘Roses’

Emissions

Air Quality Modeling

6

16 Sectors Around School

7

Roses for Four

Pollutants at the School

8

Scale (direction = longest)

Wentworth: SW = 18 ppb

S. Works: W = 52 ppb

Settlers: NE = 17 ppb

Airport (Blue): Wind direction

SO2 Pollution

Roses

Merebank AreaMonitoring sites:B = Southern WorksC = Settlers SchoolEmission sources:4 = Illovo Sugar 5 = Engen refinery 6 = Mondi Paper 7 = Sasol Fibers

10

Emissions from major sources in South Durban

Source(T/yr) (%) (T/yr) (%) (T/yr) (%) (T/yr) (%)

Shell & BP SA Petroleum Refineries (SAPREF)14,392 34.7 332 6.5 1,460 7.7 12,266 11.3Engen 13,021 31.4 278 5.4 1,403 7.4 208 0.2Mondi Paper Co. Ltd 3,100 7.5 35 0.7 715 3.8 516 0.5Tongaat Hulett Refineries Ltd2,333 5.6 132 2.6 365 1.9 292 0.3Dunlop SA 754 1.8 302 5.9 141 0.7 113 0.1South African Breweries 574 1.4 209 4.1 103 0.5 82 0.1Sasol Fibers 503 1.2 187 3.6 152 0.8 122 0.1Lever Brothers 521 1.3 208 4.1 98 0.5 78 0.1Illovo sugar (Merebank) 468 1.1 187 3.6 88 0.5 70 0.1AECI 450 1.1 0 0.0 0 0.0 0 0.0NCP Isipingo 34 0.1 2 0.0 12 0.1 4,744 4.4Diesel vehicles 1,002 2.4 1,965 38.2 6,867 36.3 3,554 3.3Ships 850 2.0 108 2.1 1,815 9.6 268 0.2Airport 6 0.0 0 0.0 160 0.8 120 0.1Others 3,460 8.3 1,193 23.2 5,563 29.4 86,555 79.4

Total 41,468 100.0 5,137 100.0 18,942 100.0 108,989 100.0

SO2 PM10 NOx CO

Derived from “South Durban Sulphur Dioxide Management Systems, Steering Committee : Emission Inventory for South Durban, April 2000, Reference : DSEI1_2000, Ecoserv.

11

SO2 Concentrations From ENGEN (ppb)

12

SO2 Concentrations From SAPREF (ppb)

13

SO2 Concentrations From Mondi (ppb)

14

SO2 Concentrations from 11 point sources (ppb)

15

Sources of SO2 and NO2 Gases

Sulfur dioxide gas

Predicted sulfur dioxide concentrations match long term measurements at the Settlers School. This increases confidence in our predictions.

Nearly all of the sulfur dioxide at the School is due to emissions from local industry.

Most of the sulfur dioxide is due to three sources; Engen, SAPREF, and Mondi.

Nitrogen dioxide gas

Local industry accounts for about half (51%) of measured levels of nitrogen dioxide.

The rest is due to cars and trucks.

16

Sources of Particulate Matter

Particulate matter under 10 microns

Relatively little (7%) particulate matter under 10 microns diameter comes from local industry.

Most PM10 is likely to come from vehicles (especially diesel cars and trucks), wind-blown dusts, as well as industry.

17

Sources of Other Pollutants

Carbon monoxide gas

Relatively little (9%) carbon monoxide comes from industry.

Most is due to cars and trucks.

Reduced sulfur gases

These smelly gases appear to come from South Works or Mondi, based on wind rose information.

More information is needed to analyze sources.

Volatile organic compound vapors (solvents, petrol vapors, etc.)

Vehicles are the largest source, followed by refineries.

More information is needed to analyze sources.

18

Wind Direction Specific RelationshipsFigure 43. Percent change in within-day variability1 of peak flow (PF) associated with measured levels of PM102, SO23 and NO24 stratified by wind sector5, at the school grounds on the prior day among all students with persistent asthma6: from logistic regression models using generalized estimating equations (GEE)7

-0.83

-0.05

3.22

0.05

3.29

0.91

5.02

-0.37-0.69

-2

-1

0

1

2

3

4

5

6

NNE SSWSW SENW NNE SSWSW SENW NNE SSWSW SENW

PM10 SO2 NO2

within_PF

What did we learn? Effect of Air Pollution and Wind Direction on Health Status of Participants

19

16 Sectors Around School

20

Within Day Variability of Peak Flow by Wind Sector

Figure 46. Percent change in within-day variability1 of peak flow (PF) associated with measured levels of PM102, SO23 and NO24 stratified by wind sector5, at the school grounds for the prior 48 hours6 among all students with persistent asthma7: from logistic regression models using generalized estimating equations (GEE)8

0.04

-0.73

1.151.16

3.20

-2.38

5.55

3.44

0.30

-4

-2

0

2

4

6

8

NNE SSWSW SENW NNE SSWSW SENW NNE SSWSW SENW

PM10 SO2 NO2

within_PF

21

What Conclusions Did We Reach?

Exposure Assessment Health Status Effect of Air Pollution on Health Status

22

Conclusions – Exposure Assessment

Levels of most pollutants measured at the School during the study were low as compared both to international and South African standards and guidelines. In particular, pollutant levels of sulfur dioxide gas were considerably lower than levels experienced over the past several years.

The wind rose analysis and the dispersion modeling suggest that Engen has been a significant source of sulfur dioxide exposure at the Settlers School. Engen is the only strong source in the NNE direction from the school. Other important sulfur dioxide sources include SAFREF and Mondi.

23

Conclusions – Health Status A very high percent of the participating students had

asthma Based on the symptoms reported by their parents:

52 % of the students in grades 3 and 6 had asthma 26% had persistent asthma (meaning asthma that causes symptoms

more than about 2 times per week) These percents are higher than found in similar studies of children

carried out elsewhere in South Africa and in other countries. The special breathing test for asthma, called the methacholine

challenge test, showed similar results: the percent of students with test results showing asthma were much higher than those found in similar studies in other countries.

24

Comparative Data from Studies Table 22. Percent of participants of current and comparative population-based studies with PC20 less than or equal to specified concentrations of methacholine

Settlers Primary School

Isle of Wight (UK)

Italy

United States

Grade 3

Age 10

Ages 7 - 11

Ages 6 - 8

Urban

Rural

African-

American

White

n

84

784

621

594

79

490

< 2 mg/ml

20.2%

< 4 mg/ml

39.4%

20.0%

14.8%

< 8 mg/ml

59.4%

14.4%

< 10 mg/ml

*

41.7%

22.3%

* not directly measured in current study

25

Conclusions – Effect of Air Pollution on Health Status

The study results suggest that exposures to the air pollutants SO2, PM10, and NO2 are causing the students who already have persistent asthma to have more symptoms and poorer breathing function on the following one to two days. There were strong relationships between exposures to SO2,

PM10, and NO2 and increases in symptoms on the following one to two days including cough, wheezing, chest tightness, and shortness of breath among the students with persistent asthma.

Exposures to SO2, PM10, and NO2 were also strongly related to changes in these students’ breathing function on the following one to two days. The kinds of changes seen are those that usually happen when

someone’s asthma is causing more problems (“acting up”).

26

Conclusions – Effect of Air Pollution on Health Status (continued)

Sources of air pollutants affecting health status For SO2, pollutant reaching the school

from a north-northeast (NNE) wind direction had the strongest relationship to changes in lung function. SO2 from this direction would be expected to come mostly from Engen.

27

Conclusions – Effect of Air Pollution on Health Status (continued)

Sources of air pollutants affecting health status

We still are not certain that the SO2 from Engen is most responsible for effects on breathing function because: strong effects of pollutant coming from the north-northeast

(NNE) were seen also with PM10. However, Engen’s PM10 emissions are expected to be relatively small in comparison to other sources such as motor vehicle exhaust

also, because of typical daily pattern of changing wind directions, it may be that SO2 sources to the southwest (SSWSW), such as SAPREF and Mondi, contribute more to health effects occurring later in the day after school hours

28

Recommendations – Exposure Estimates1. Air quality monitoring at the school should be continued, and

additional monitoring is needed. Monitoring is especially important given the many industries in South Durban, the topography, meteorology, and uncertainties in the emission inventory. Also, monitoring is only way to verify trends in pollutant levels.

2. Monitoring should be improved to provide the following: Continuous monitoring of PM2.5 and SO2 at sites with large or

potentially affected populations, e.g., Settlers School, Merebank and Umlazi.

Periodic monitoring at ‘hotspots’ of SO2 or other pollutants. Every 3rd or 6th day monitoring is suggested.

Periodic monitoring of other pollutants, including volatile organic compounds (VOCs), lead, and reduced sulfur compounds (TRS).

Indoor and personal monitoring in special studies designed to measure total exposure (indoors and outdoors). The use of wood or charcoal indoors can produce very high pollutant levels.

29

Recommendations – Emission InventoryA comprehensive air quality management strategy requires an adequate emission inventory that describes all pollutant sources. The source inventory should be improved by:

Marking it comprehensive, including (spatially disaggregated) information on point, mobile and fugitive emissions.

Include PM10 and PM2.5.

Including VOC information for specific chemical species

Use source measurements, not calculations where practical.

Use a recent year and include temporal changes for big sources.

Include all parameters needed for modeling

Include quality assurance and quality control (QA/QC) plan and an external peer review process. To be useful, inventory estimates must be verified.

30

Recommendations – Dispersion Modeling1. Dispersion modeling is an essential component of an air

quality management strategy. Modeling can be used to (1) apportion sources; (2) assess impacts of new/modified sources; (3) design abatement strategies; (4) estimate concentrations and risks.

2. Existing emission sources should be modeled to understand annual average and worst case impacts.

3. Impacts from new or modified emission sources should be modeled and evaluated prior to construction or operation.

4. Model predictions should be compared to ambient measurements and diagnostic measures used to understand discrepancies.

31

Recommendations – Emission ControlsThe area has been historically impacted by industrial emissions. Based on the health effects and apportionment study, emission controls, better fuels, and/or lower emitting combustion processes that significantly reduce emissions are warranted. Specifically:

1. Sulfur (SO2) emissions from local sources should be reduced.

2. Emission controls for one pollutant can result in substantial and cost-effective reductions for other pollutants. For example, a dry scrubber system would substantially reduce both SO2 and PM emissions. Thus, emission reductions for NOx, PM and other pollutants should also be considered.

3. VOC and TRS emissions from refineries, paper mills and waste water treatment facilities may be significant. These require further investigation and quantification, and possible control.

4. Emission reductions should be verified. Continuous emission monitors at the large point sources are suggested.

32

Recommendations – Further Health Studies & Clinical Follow-Up

A relatively large study in the Durban metropolitan area to characterise geographic and/or ethnic variations in asthma prevalence and severity, which would also assess a host of potential risk factors including ambient air pollution, indoor allergens and pollutants, sensitisation to allergens would assist in: Identification of causative factors Health-effect-driven targets for exposure reduction

Follow-up for those with asthma, both for those who participated in the study and others with asthma in the community. Medical management Education about the disease and how to control symptoms