Pure app!. geophys. 160 (2003) 265-277 0033-4553/03/020265-13
© Birkhiiuser Verlag, Basel, 2003
I Pure and Applied Geophysics
Visibility and Incidence of Respiratory Diseases During the 1998 Haze Episode in Brunei Darussalam ANIL KUMAR YADAV,I,- KRISHAN KUMAR,! AWG MAKARIMI BIN HJ AWG KASIM,2 M. P. SINGH,3,- S. K. PARIDA,4 and MAITHILI SHARAN 5
Abstract-Air pollution episodes as a result of forest fires in Brunei Darussalam and neighbouring regions have reached hazardous levels in recent years. Such episodes are generally associated with poor visibility and air quality conditions. In the present study, data on PM lO (particulate matter of size less than 10 microns) and CO in Brunei Darussalam have been considered to study the incidence of respiratory diseases whereas data on relative humidity (RH) in addition to PM lO have been used to explain the visibility with a particular emphasis on haze episode during 1998. Initial exploratory analysis indicates significant correlation of visibility with PM lO and RH. An attempt has been made to explain visibility on the basis of PM lO and RH using multiple linear regression analysis. The regression model shows that PM lO and RH are two significant factors affecting the visibility at a given site. Further, canonical correlation, a multivariate method of analysis, has been used to explain the incidence of respiratory diseases as a function of air quality during the haze period. The results indicate that PM lO and CO levels during the haze period have a significant bearing on the incidence of respiratory diseases (Asthma, Acute Respiratory Infections and Influenza (ARB)). Key words: Haze, air pollution, visibility, respiratory diseases, PM lO , canonical correlation.
Introduction Intense forest fires during February-April 1998 in Brunei Darussalam located on the NE part of Borneo Island; SON, 115°E and neighbouring regions led to the emission of unusually high concentration of particulates, resulting in prolonged haze formation over the entire southeast Asian region (see Fig. I). The regional haze in SE Asia is a
recurring air pollution problem (NICHOL,
1997; RADOJEVIC,
1997;
RADOJEVIC and HASSAN, 1999). The resultant haze reduced visibility to hazardous
I Guru Jambheshwar University, Hisar-125 001, Haryana, India. E-mail:
[email protected] - Current affiliation: Ansal Institute of Technology, Gurgaon-122003 India 2 University Brunei Darussalam, Brunei Darussalam. 3 Visiting Consultant, University Brunei Darussalam, Brunei Darussalam. 4 Ministry of Health, Brunei Darussalam. 5 Centre for Atmospheric Sciences, Indian Institute of Technology, Delhi-II 0 016, India.
266
Anil Kumar Yadav el af.
Pure app!. geophys.,
Figure 1 Region in Southeast Asia affected by haze in 1998.
levels and affected the health of the exposed population adversely. A reasonably good background of earlier studies on haze-related aspects such as location of sources, effects on health and general day-to-day life has been provided in a recent study by RADOJEVIC and HASSAN (1999). They have analysed the air quality data of Brunei Darussalam collected in the recent past. Their analysis included overall air quality (S02, NO, N0 2, CO, 0 3 and PM IO), diurnal variation of these pollutants and PSI (Pollution Standards Index) vis-i-vis haze. PSI is an index developed by the US Environmental Protection Agency on the basis of epidemiological studies carried out in several US cities. It provides a simplified system of reporting air quality status of a place to a layman. PSI of a pollutant converts daily measured concentrations to a number on a scale of 0 to 500 through an empirical formulation. Using this technique a nomogram (Fig. 2) is prepared which classifies PSI into five different categories, namely Good, Moderate, Unhealthy, Very Unhealthy and Hazardous. Further information on PSI may be found in SINGH and HASSAN (1998). On the basis of air quality data analysis during the 1998 haze episode, RADOJEVIC and HASSAN (1999) have reported that only particulate matter is a significant pollutant. They have looked at 1 h, 8 hand 24 h average concentrations of PM 10 and reported a number of exceedances with reference to WHO guidelines.
Vol. 160,2003
Visibility of Respiratory Diseases
GOOD
MODERATE
UNHEALTHFUL
,,.
-
~
267
~ :::
""
~
:,
-
,
2!
~
:::
~
N
g
~
.."
~
'''''1. N
~
N
~
N
~
~
N
N
~
:,,,,;,.1'1",,,,1
~
N
~
~
l.J
g
W
W
~ ~
("oJ
(",J
~
~
W
~
W
E
W
~
W.t..1=
W
~ ~
·,,
=~ ';'3
"
VERY UNHEALTHFUL
,
=
N
N
~
N
~
l' I, "" r
N
~
" "''1"''
N
~
N
~
N
~
N
~
w~ g~
I 1"" ,I "'1',..1 ,+,1.. """1 ""1= :::11
73 , .
· ,
HAZARDOUS
Figure 2 Pollution Standards Index (PSI) Nomogram for PM IO (24-hour average) [Based on US EPA Guidelines] (SINGH and HASSAN, 1998),
Though most studies on haze, to the best of our knowledge, have followed a somewhat qualitative approach regarding its effects on visibility and human health, no attempt has been made relative to statistical verification of some of their conclusions. Further, the studies mentioned above have focused only on PM IO as the sole pollutant affecting the general air quality. The present study attempts to bridge this gap by doing a quantitative analysis of haze related hazards. Two vital statistical techniques - multiple linear regression analysis and canonical correlation analysis have been applied to explain the visibility and the incidence of respiratory diseases, respectively.
268
Pure appl. geophys.,
Anil Kumar Yadav et al.
Data Description
In the present study, hourly data on PM IO , RH and visibility from the airport in Brunei Darussalam have been considered for the period April 7 to December 31, 1998, which includes a part of the haze episode of 1998. Though the haze period extended from Feb. to May 1998, PM 10 data for the airport were available only from April 7 onwards. Data on PM IO from another site (BSB Post Office) were also available but have certain drawbacks such as missing values and a value repeating consecutively on some occasions. Therefore, the data from this site have not been considered for the present study. Hourly data of CO were also considered during the haze period. Data on the number of cases reported for various respiratory diseases, namely Asthma (ASTH), Acute Respiratory Infections and Influenza (ARII) in Brunei during this period were also collected from OPD records of Civil Hospitals of Brunei. Time Behaviour of PM iO
PM 10 being the most significant pollutant contributing to haze formation, its time traces must be examined before any further analysis. Figure 3 gives the time series plot ofPM IO for the entire period considered in this study. The trends of PM 10 values 2000 - . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . 1900
Apr 7 -
1800
Dec 31, 1998
1700 1600 1500 1400 ~
"'E
1300
"-- 1200
0' I 1100
o
~ 1000
E
900
o
800
~
:2
Il
700 600 500 400 300 200
10:+-A,......-:~~~~.1~~.¥_I ..... Apr May June
-,......-.....,.~-.....,..,w._ . . . .~Io.I!!>dNov 1.~~~ Aug Sept Oct Dec ....
I.I!L.I!!lrI&J........
I
I
I
July
I
I
I
I
I.
Figure 3 Time series plot of PM 10 at the airport in Brunei Darussalam during April-Dec. 1998.
Vol. 160,2003
Visibility of Respiratory Diseases
269
from Figure 3 indicate clearly the occurrence of unusually high PM IO concentration during the period April-May 1998. Based on the PSI nomogram for PM 10 (Fig. 2), it appears pertinent to focus on PM IO concentrations above 50 J..lgjm 3 . Therefore, in our analysis, we have identified the interval from April 7 to May 15 as a sample of the "haze" period and the remaining portion as "non-haze" period. It may be relevant here to mention that the diurnal behaviour of PM IO concentration for the haze period (Fig. 4a) (i.e., April 7th to May 15th 1998) is quite different from that during the non-haze period (Fig. 4b). In the haze period, hourly PM 10 concentration starts building up at about 2 am onwards and peaks at about 8 am. Thereafter, it starts declining and reaches a steady minimum at about 3 pm. The build-up of PM IO during night in the non-haze months is never so pronounced (very small). The reduced levels of PM 10 during the day can be explained on the basis of diurnal plots of horizontal wind speed and mixing height. A typical plot of diurnal variation of the ventilation coefficient, a product of wind speed and mixing height, shows behaviour complementary to Figure 4b (MAKARIMI et al., 1999). This offers a plausible explanation for the observed diurnal behaviour of PM IO .
Data Analysis Visibility
Initial exploratory analysis indicates significant negative correlation of visibility (km) with PM IO (J..lgjm 3) and relative humidity (RH in percentage) (Table 1). The values of the Pearson's correlation coefficient are -0.31 and -0.58 with PM IO and RH, respectively. This provides the basis to explain visibility (VIS) in terms of PM 10 and RH using a multiple linear regression model of the following form:
(1) where e is the error (residual) term and [30, [31 and [32 are the regression coefficients. The regression model (Table 2) shows that PM 10 and RH are two significant factors affecting visibility at a given site. The equation representing the regression model may be expressed as VIS = 42.28 - .0195 PM 10
-
.323 RH
+e
.
(2)
The results of ANalysis Of VAriance (ANOVA *) (Table 3) for the regression model indicate the goodness of fit for the overall model. The R 2 (adj.) value obtained reveals
* Analysis of variance may be defined as a technique whereby the total variation present in a set of data is partitioned into several components (DANIEL, 1991; MOORE and COBBY, 1998). In regression analysis, ANOVA partitions the total variation present in the data into two components: variation explained by the model and the residual variation.
270
Ani! Kumar Yadav et al.
Pure appl. geophys.,
600,--------------------------------------,
(a) Haze Period 500
400
;:;
