PM10 AND ACUTE RESPIRATORY
INFECTION (ARI) AMONG CHILDREN
IN KLANG VALLEY : GIS MAPPING
Siti Rahmah A. R.1, Sharifah Norkhadijah S. I. 1, Muhammad Firuz R. 2,
Mohd Talib L. 3, Mazrura S. 4
1Department
of Environmental and Occupational Health, Faculty of Medicine and
Health Sciences, UPM
2School of Environmental and Natural Resource Sciences, Faculty of Science and
Technology, UKM
3Department of Environmental Science, Faculty of Environment Studies, UPM
4Universiti Kebangsaan Malaysia
INTRODUCTION
• Rapid urban population growth and physical
development has given significant
pressure to the
Worsened air
environment.
pollution
Level of Urbanisation in Malaysia by Year
Total Population of Malaysia by
Year
30
80
71
28.3
70
62
25
60
23.3
50.7
15
18.4
(%)
Million
20
50
13.7
40
34.2
30
10
20
5
10
0
0
1980
1991
2000
Year
Source: Department of Statistic, Malaysia 2010
2010
1980
1991
2000
2010
Year
2
Source: Malaysia Air Pollution Index and Environmental Quality Report 2010
3
Source: The Acute Respiratory Infection Atlas, First Edition 2010
4
Source: The Acute Respiratory Infection Atlas, First Edition 2010
5
AIR POLLUTION INDEX
INDEX
COLOR CODE
CATEGORY
0-50
GOOD
51-100
MODERATE
101-200
UNHEALTHY
201-300
VERY UNHEALTHY
301
HAZARDOUS
6
Source of Ozone:
- industrial facilities and
electric utilities, motor
vehicle exhaust, gasoline
vapors, and chemical
Source of SO2:
- Generation of electricity
from coal, oil or gas that
contain sulphur, fuel
combustion
Source of CO:
- incomplete combustion
like cigarette smoking
and car exhausts
Source of PM10:
- bushfires, unpaved
roads, motor vehicles
emission, industrial
process
Source of NO2:
- Motor vehicles exhaust,
electric utilities and
industrial boilers
Source: Environmental Quality Report 2010
7
Particulate Matter (PM10)
Particles, which are
between 2.5 and 10
microns in aerodynamic
diameter (PM2.5-PM10),
Particles smaller than 2.5
microns (PM2.5), can travel
deeper into the lungs.
OBJECTIVE
To determine distribution pattern of PM10 and
ARI among children age between 0 to 14 years
old in Klang Valley.
Data analysis
ARI data with the coordinate will
be input in the GIS software to
build a pattern of ARI cases
Air pollution data with the coordinate
of each monitoring station will be input
in the GIS software to build a pattern
of air pollution
These two pattern will be overlaid to explore the
association between ARI and PM10.
10
RESULTS AND DISCUSSIONS
PM10 concentration with ARI cases in 2007
ARI_cases_2007
Value
High : 64.5843
Low : 32.3775
PM10 concentration with ARI cases in 2008
ARI_cases_2008
Value
High : 64.5843
Low : 32.3775
PM10 concentration with ARI cases in 2009
ARI_cases_2009
Value
High : 64.5843
Low : 32.3775
PM10 concentration with ARI cases in 2010
ARI_cases_2010
Value
High : 64.5843
Low : 32.3775
Annual mean of PM10 concentration and ARI cases
CONCLUSION
• Highest PM10 was observed in Klang.
• High PM10 can increase ARI incidence.
• Integrated usage of geostatistical methods,
and spatial analysis can introduce valuable
information to identify, visualize and explore
the relationship between incidence on ARI
and environmental pollution.
STUDY LIMITATION
• Limited air quality station numbers in Klang
Valley to get more accurate data in certain
places.
• ARI data may not cover other respiratory
registry in some private health sector.
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