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Urban heat island and air pollution--an emerging role for hospital respiratory admissions in an urban area.

Introduction

One of the well-documented air pollution problems associated with intense anthropogenic activities is the urban heat island (UHI) phenomenon. At present, many studies have established the relationship between convergence and UHI. For example, a stronger convergence is due to stronger heat island intensities, which are in turn associated with anthropogenic heat flux (Khan & Simpson, 2001). A slight change in surface winds with convergence has formed over Paris and Tokyo due to the UHI effect (Fujibe, 2003; Lemonsu & Masson, 2002).

In urban areas, convergence worsens air quality. The convergence zone persists over the urbanized area, finally resulting in high concentrations of pollutants (Yoshikado & Tsuchida, 1996). Moreover, many epidemiological studies have shown an association between air pollution and various health issues (Lin et al., 2001; Llorca, Salas, Prieto-Salceda, Chinchon-Bengoechea, & Delgado-Rodriguez, 2005). Numerous studies have focused on the association between UHI and convergence, as well as the relationship between air pollution and human health. Associations among air pollution, hospital respiratory admissions, and convergence due to the UHI effect in urban settings, however, remain unclear.

According to data analysis, the air quality is worse in Dali than in other areas; in Dali, respiratory admission counts are higher than in other areas and many clear UHIs have appeared, especially in autumn. This county, however, is not near a major stationary air pollutant source, and its population count is not the largest in metropolitan Taichung. Hence, we suspect that the worsened air pollution is probably related to the UHI effect, and has resulted in higher hospital respiratory admission counts in Dali.

The study described here attempts to clarify the aforementioned ambiguous--or otherwise unknown--associations among the three parameters, by way of statistical analysis and observations of one experimental campaign.

Study Area

The geographical location of Taiwan is on the border between the Eurasian continent and the Pacific Ocean; as such, it serves as a boundary between the earth's largest land and water masses, and it includes both temperate and tropical zones.

The Taichung metropolis, with nearly 2.5 million residents, is located in the Taichung Basin in central Taiwan (Figure 1: http:// www.envsci.thu.edu.tw/teacher/wlcheng/ fig1_5.pdf). Its UHI phenomenon has already been reported (Lin et al., 1999). Dali, a UHI center of the Taichung metropolis, has a population of 220,000 and serves active commercial and manufacturing functions.

In this study, Wufong was treated as a reference station, because it represents an isolated rural area in the Taichung metropolis. The balloon-borne measurements were collected at Tsaoton, a rural town near Dali and Wufong that is away from airplane routes, to obtain the vertical profiles of the wind field.

Materials and Methods

Data Collection

Data regarding the daily hospital respiratory admissions in the 29 political districts of the Taichung metropolis were obtained from the Taiwan Bureau of National Health Insurance (TBNHI) for between September 1 and November 30, 2003, as well as for 2004 (hereafter referred to as the "examined period"). All afflicted groups in the data were classified according to the International Classification of Disease, Ninth Revision (ICD-9; World Health Organization, 1998). To properly reflect the admission data in the events of poor air quality in the Taichung metropolis, only the data for hospital respiratory admissions (ICD-9 codes 460-519) were used for analysis. The admission data for influenza (ICD-9 code 487) were excluded, because they were treated as part of a flu epidemic. Four age groups, namely, 0-4 years (preschoolers), 5-14 years (children), 15-64 years (adults), and over 65 years (elderly), were categorized to account for different responses to poor air quality during UHI episodes.

Hourly air pollution data (i.e., concentrations of ozone [[O.sub.3]], sulfur dioxide [S[O.sub.2]], nitrogen oxides [N[O.sub.x]], carbon monoxide [CO], particulate matter [[PM.sub.10]], and the Pollutant Standards Index [PSI]), as well as daily meteorological data (i.e., air temperature, wind direction, and wind speed) for the examined period were obtained from 11 stations belonging to the Taiwan Environmental Protection Administration (TEPA) air quality monitoring network. Four of these stations, the Jhongming, Situn, Dali, and Wufong stations, were chosen for further analysis. The intensities of UHI were divided into three groups, namely "Level 1," with a UHI between 0[degrees]C and 2[degrees]C; "Level 2," with a UHI between 2[degrees]C and 3[degrees]C; and "Level 3," with a UHI equal to or greater than 3[degrees]C.

To avoid the "weekend effect" when industrial activities are reduced and most regional hospitals and clinics are less busy, which may lead to an underestimation of UHI effect, admission data and hourly air pollution data for Saturdays and Sundays during the examined period were removed from consideration.

Air quality data from the monitoring stations were compared to respiratory admissions in the hospitals and clinics in the 29 districts. GIS was used in order to calculate the districts' geographical centers and determine the spatial variation between air quality patterns and the hospital respiratory admissions.

The tethersonde, supported by a spherical hydrogen balloon, was tethered on a Kevlar line and controlled by an electric capstan. It consisted of a balloon-borne rawinsonde for efficiently gathering vertical meteorological data (Cheng, 2000). In our study, a tethered balloon was released every three hours from the surface to an altitude of about 1,000 meters at Tsaoton during the experimental period, October 21-30, 2004. Detailed descriptions of the instrumentation and the methodologies used to monitor the vertical profile data sets in several similar Central Taiwan Air-Quality Management Program (CTAMP) experiments have been provided elsewhere (Cheng, 2000; Cheng, Pai, Tsuang, & Chen, 2001).

The Air Pollution Model (TAPM), a viable tool for year-long simulations developed by Australia's Commonwealth Scientific and Industrial Research Organization (CSIRO), is a PC-based, prognostic meteorological and air pollution model driven by a Graphical User Interface (GUI) (Hurley, Physick, & Luhar, 2005). In this study, TAPM was used to simulate the convergence phenomenon due to the UHI in metropolitan Taichung. The observed vertical wind speed and wind direction were used as the reference parameters for testing whether TAPM simulation was reliable; the accuracy of TAPM simulation was estimated with the Index of Agreement (IOA), whose scale ranges from 0 to 1, with a higher score representing greater accuracy (Hurley et al., 2003).

Comparison Analysis

Two comparisons were determined by Duncan's Multiple Range test (Cody & Smith, 2006) provided by SAS software. First, we tested whether the air pollutants accumulate in Dali and worsen the residents' health. Second, we tested whether air quality and residents' health varied with UHI intensity.

Results and Discussion

Air Quality and Hospital Respiratory Admission Counts Under Varying UHI Levels

In the autumn season in the Taichung metropolis, the center of the UHI is in Dali, as well as the area with poor air quality. As indicated in Tables 1a and 1b, the UHI intensity in Dali was significantly greater than in other areas (p < .05), regardless of UHI intensity during the examined period. For example, at all levels, the nitrogen dioxide (N[O.sub.2]) and CO concentrations in Dali were greater than those in other areas. As for PSI, the value in Dali was larger than in Jhongming only at Level 3 intensity. In principle, with the UHI intensity increasing (particularly at Level 3), the poor quality of the air became much more pronounced.

The mean daily hospital respiratory admission counts for young people in Dali were higher than in other areas; at Level 1 and Level 3 intensities, they were higher than those in Jhongming and Wufong, but at Level 2 intensity, they were larger than only that in Wufong. In comparison to its effect on air quality, the effect of increases in UHI intensity on hospital respiratory admissions counts was not as obvious.

Comparison of UHI Intensities with Air Quality and Hospital Respiratory Admission Counts

UHI intensity is not a confounding variable in determining the relationship between air pollutant concentrations and the hospital respiratory admission counts. Hence, while analyzing hospital respiratory admission counts, we need not further adjust air pollutant concentrations.

In Dali, the air quality worsens and hospital respiratory admissions increase significantly when UHI intensity is high enough. Tables 1a and 1b indicate that when UHI intensity was at Level 3, the air quality deteriorated significantly (p < .05), and the mean daily counts of hospital respiratory admissions of preschoolers and children significantly increased (p < .05). These facts indicate that the UHI effect may influence air pollutant concentrations, which is in line with the observations of Yoshikado & Tsuchida (1996) and Devara and co-authors (2002). The worsened air quality indirectly affected the residents' health--especially that of young children--although not clearly. This finding is similar to the results that suggest that hospital respiratory admissions are related to concentrations of S[O.sub.2], CO, N[O.sub.2], and [PM.sub.10] (Buckeridge et al., 2002; Chen, Xirasagar, & Lin, 2006).

Experimental Campaign

Synoptic Pattern

The experimental campaign belonged to coupled Type III and Type VII (Figure 2: http:// www.envsci.thu.edu.tw/teacher/wlcheng/ fig1_5.pdf). Figure 2 shows weather surface maps of the campaign at 8:00 a.m. on October 29, 2004. The campaign involves the northern extent of the tropical depression migrating to the vicinity of Taiwan, which weakens the easterly winds. The area is conducive to the UHI phenomena, and its strong solar radiation with low humidity is the most favorable for air pollution episodes (Cheng, 2001).

UHI and Convergence Phenomena

During this campaign, the strongest UHI phenomenon occurred in Dali, as did the highest air pollutant concentrations. The surface air temperature distributions in the Taichung metropolis at 8:00 p.m. on October 29, 2004--as shown in Figure 3 (http://www. envsci.thu.edu.tw/html/teacher/wlcheng/ fig1_5.pdf)--represented the strongest UHI phenomenon of the experimental period. Figure 3 shows that the heat island intensity in Dali, the warm center, was 5.62[degrees]C. At the same time, evidently the air pollutant concentrations in Dali were either at the contour peak or were approaching its peak.

These results show that the air quality was poorest when the strongest UHI phenomenon occurred in Dali. The dangerous "hotspot" of air pollution during the UHI episodes appeared to be within or near the Dali area.

In the center of the UHI, where the convergence is generated as the UHI phenomenon occurs, wind speed and direction vary, causing the accumulation of air pollutants. TAPM simulations showed the vertical wind field for the X-cross section at the strongest UHI phenomenon; it was observed that the wind direction changed and the wind speed reduced at different heights in the areas near Dali (Figure 4: http://www.envsci.thu.edu. tw/teacher/wlcheng/fig1_5.pdf). Presumably, during the examined period, Dali and its surrounding area was a center of convergence where the hotter air moved upward and the cooler air from the rural areas moved to the center of the UHI, due to the rapidly rising air temperature in Dali. The wind directions of the horizontal low-speed wind field changed near Dali, indicating that the air flow might have been disturbed by the UHI.

The manifest observations and the simulations showed that the air quality became worse after the wind strength weakened and its direction changed; these are conditions similar to those witnessed in metropolitan Tokyo (Yoshikado & Tsuchida, 1996), where a convergence zone persisting over an urbanized area caused very high concentrations of pollutants.

Unfortunately, cooler air moving from the suburban or rural areas to Dali may carry air pollutants with it, thereby affecting hospital respiratory admissions counts. Dali still represented one of the districts whose admission count was large similarly to the distributions of hospital respiratory admissions in the Taichung metropolis on the specific dates shown in Figure 5 (http:// www.envsci.thu.edu.tw/teacher/wlcheng/fig1_5. pdf). The largest hospital respiratory admissions count did not occur in Dali, however.

Conclusion

Our study shows that during the examined period in Dali when the UHI intensity became Level 3, the air quality significantly worsened (p < .05). The air pollutants clearly accumulated in the county, where the air quality was worse than that of other districts (p < .05). The corresponding increase in hospital respiratory admissions counts in the county--with the exception of those in the elderly group--was also more pronounced than those in other districts. Further, that the center of the UHI appeared in the county was confirmed from observations of surface air temperature and TAPM simulations of vertical air flow for the strongest UHI phenomenon. It was clear that the convergence was generated in Dali, and that the wind direction of air flow near Dali was disturbed. In principle, the UHI phenomenon generates convergence, transports air pollutants to urban settings, and consequently raises the risk of an increase in hospital respiratory admissions in the center of the UHI.

Acknowledgements: This research was funded by the National Science Council of Taiwan (NSC 95-2211-E-029-012). The authors are grateful to their colleagues, Professors Walter Den and David Newquist, for providing additional comments on the manuscript.

Pre-published digitally October 2009, National Environmental Health Association

References

Buckeridge, D.L., Glazier, R., Harvey, B.J., Escobar, M., Amrhein, C., & Frank, J. (2002). Effect of motor vehicle emissions on respiratory health in an urban area. Environmental Health Perspectives, 110(3), 293-300.

Chen, C.H., Xirasagar, S., & Lin, H.C. (2006). Seasonality in adult asthma admissions, air pollutant levels, and climate: A population-based study. The Journal of Asthma, 43(4), 287-292.

Cheng, W.L. (2000). A vertical profile of ozone concentration in the atmospheric boundary layer over central Taiwan. Meteorology and Atmospheric Physics, 75(3-4), 251-258.

Cheng, W.L. (2001). Synoptic weather patterns and their relationship to high ozone concentration in the Taichung Basin. Atmospheric Environment, 35(29), 4971-4994.

Cheng, W.L., Pai, J.L., Tsuang, B.J., & Chen, C.L. (2001). Synoptic patterns in relation to ozone concentrations in west-central Taiwan. Meteorology and Atmospheric Physics, 78(1-2), 11-12.

Cody, R.P., & Smith, J.K. (2006). Applied statistics and the SAS programming language (5th ed.). Upper Saddle River, NJ: Prentice-Hall.

Devara, P.C.S., Maheskumar, R.S., Raj, P.E., Pandithurai, G., & Dani, K.K. (2002). Recent trends in aerosol climatology and air pollution as inferred from multi-year lidar observations over a tropical urban station. International Journal of Climatology, 22(4), 435-449.

Fujibe, F. (2003). Long-term surface wind changes in the Tokyo metropolitan area in the afternoon of sunny days in the warm season. Journal of the Meteorological Society of Japan, 81(1), 141-149.

Hurley, P., Manins, P., Lee, S., Boyle, R., Ng, Y.L., & Dewundege, P. (2003). Year-long, high-resolution, urban airshed modelling: Verification of TAPM predictions of smog and particles in Melbourne, Australia. Atmospheric Environment, 42(38), 1899-1910.

Hurley, P.J., Physick, W.L., & Luhar, A.K. (2005). TAPM: A practical approach to prognostic meteorological and air pollution modelling. Environmental Modeling & Software, 20(6), 737-752.

Khan, S.M., & Simpson, R.W. (2001). Effect of a heat island on the meteorology of a complex urban airshed. Boundary-layer Meteorology, 100(3), 487-506.

Lemonsu, A., & Masson, V. (2002). Simulation of a summer urban breeze over Paris. Boundary-layer Meteorology, 104(3), 463-490.

Lin, H.T., Lee, K.P., Chen, K.T., Lin, L.J., Kuo, H.C., & Chen, T.C. (1999). Experimental analyses of urban heat island effects of the four metropolitan cities in Taiwan (I): A comparison of the heat island intensities between Taiwan and the world cities. Journal of Architecture, 31, 51-73 (in Chinese, with English abstract).

Lin, R.S., Sung, F.C., Huang, S.L, Gou, Y.L., Ko, Y.C., Gou, H.W., & Shaw, C.K. (2001). Role of urbanization and air pollution in adolescent asthma: A mass screening in Taiwan. Journal of Formosan Medical Association, 100(10), 649-655.

Llorca, J., Salas, A., Prieto-Salceda, D., Chinchon-Bengoechea, V., & Delgado-Rodriguez, M. (2005). Nitrogen dioxide increases cardiohospital respiratory admissions in Torrelavega (Spain). Journal of Environmental Health, 68(2), 30-35.

World Health Organization. (1998). International classification of disease, ninth revision. Geneva: Author.

Yoshikado, H., & Tsuchida, M. (1996). High levels of winter air pollution under the influence of the urban heat island along the shore of Tokyo Bay. Journal of Applied Meteorology, 35(10), 1804-1813.

LI-WEI LAI, PHD

WAN-LI CHENG, PHD

Corresponding Author: Li-Wei Lai, Assistant Professor of Environmental Science, Center of General Education, National Taipei College of Business, Taipei 100, Taiwan ROC. E-mail: d89228001@ntu.edu.tw.
TABLE 1a
A Comparison of Four Districts in the Taichung Metropolis
During the Examined Period, Levels 1 and 2

UHI                                      Level 1
Intensities

Districts               Jhongming                      Situn
                        (n = 56)                      (n = 56)

[PM.sub.10]
  ([micro]g/
  [m.sup.3])   75.32 [+ or -] 31.856 (b,c)   64.19 [+ or -] 33.63 (c)
[O.sub.3]
  (ppb)        26.29 [+ or -] 9.71 (b)       30.57 [+ or -] 9.30 (a)
N[O.sub.2]
  (ppb)        25.33 [+ or -] 6.26 (b)       15.59 [+ or -] 6.49 (c)
S[O.sub.2]
  (PPb)         4.88 [+ or -] 1.88 (a)        3.34 [+ or -] 2.04 (b)
CO (ppm)        0.73 [+ or -] 0.14 (b)        0.67 [+ or -] 0.21 (b)
PSI            67.64 [+ or -] 18.47 (a)      67.93 [+ or -] 22.69 (a)
Preschoolers    0.32 [+ or -] 0.72 (b)        0.71 [+ or -] 0.73 (a)
Children        1.27 [+ or -] 1.12 (a)        1.57 [+ or -] 1.19 (a)
Adults          2.59 [+ or -] 1.56 (a)        3.14 [+ or -] 1.95 (a)
Elderly         0.20 [+ or -] 0.40 (a,b)      0.38 [+ or -] 0.59 (a)
Total           4.38 [+ or -] 1.97 (b)        5.80 [+ or -] 2.58 (a)

UHI                                      Level 1
Intensities

Districts                Wufong                         Dali
                        (n = 56)                      (n = 56)

[PM.sub.10]
  ([micro]g/
  [m.sup.3])    90.62 [+ or -] 27.94 (a)     74.96 [+ or -] 28.49 (a)
[O.sub.3]
  (ppb)         24.96 [+ or -] 10.57 (b)     25.33 [+ or -] 7.75 (b)
N[O.sub.2]
  (ppb)          20.82 [+ or -] 5.16 (c)     28.29 [+ or -] 8.94 (b)
S[O.sub.2]
  (PPb)           4.54 [+ or -] 1.56 a)       2.69 [+ or -] 1.51 (b)
CO (ppm)                   --                 0.90 [+ or -] 0.19 (a,b)
PSI                        --                 72.0 [+ or -] 21.53 (b)
Preschoolers     0.20 [+ or -] 0.40 (b)       0.64 [+ or -] 0.77 (b)
Children         0.54 [+ or -] 0.71 (b)       1.50 [+ or -] 1.28 (a)
Adults           0.88 [+ or -] 0.95 (b)       2.70 [+ or -] 1.62 (a)
Elderly          0.11 [+ or -] 0.31 (b)       0.38 [+ or -] 0.56 (a)
Total            1.71 [+ or -] 1.38 (c)       5.21 [+ or -] 2.57 (a,b)

UHI                                      Level 2
Intensities

Districts               Jhongming                      Situn
                        (n = 14)                      (n = 14)

[PM.sub.10]
  ([micro]g/
  [m.sup.3])   59.52 [+ or -] 24.75 (a)      58.61 [+ or -] 17.65 (a)
[O.sub.3]
  (ppb)        26.39 [+ or -] 11.37 (a)      32.94 [+ or -] 12.10 (a)
N[O.sub.2]
  (ppb)        20.93 [+ or -] 7.68 (b)       19.51 [+ or -] 5.40 (b)
S[O.sub.2]
  (PPb)         3.49 [+ or -] 2.01 (a,b)      3.32 [+ or -] 1.51 (a,b)
CO (ppm)        0.54 [+ or -] 0.17 (b)        0.54 [+ or -] 0.20 (b)
PSI             54.7 [+ or -] 18.0 (a)       65.43 [+ or -] 22.4 (a)
Preschoolers    0.57 [+ or -] 1.02 (a,b)      1.21 [+ or -] 1.19 (a)
Children        1.21 [+ or -] 1.48 (a)        0.86 [+ or -] 0.86 (a)
Adults          1.71 [+ or -] 1.20 (b)        3.00 [+ or -] 0.99 (a)
Elderly         0.07 [+ or -] 0.27 (a)        0.14 [+ or -] 0.36 (a)
Total           3.57 [+ or -] 2.44 (a)        5.21 [+ or -] 2.15 (a)

UHI                                      Level 2
Intensities

Districts                Wufong                         Dali
                        (n = 14)                      (n = 14)

[PM.sub.10]
  ([micro]g/
  [m.sup.3])   66.55 [+ or -] 24.66 (a)      58.55 [+ or -] 24.14 (b)
[O.sub.3]
  (ppb)        31.96 [+ or -] 7.34 (a)       30.12 [+ or -] 9.82 (a)
N[O.sub.2]
  (ppb)        18.40 [+ or -] 5.08 (b)       26.49 [+ or -] 8.45 (b)
S[O.sub.2]
  (PPb)         4.37 [+ or -] 1.07 (a)        2.91 [+ or -] 0.80 (b)
CO (ppm)                   --                 0.80 [+ or -] 0.19 (b)
PSI                        --                 61.8 [+ or -] 16.1 (b)
Preschoolers    0.21 [+ or -] 0.58 (c)        0.79 [+ or -] 0.70 (a,b)
Children        0.29 [+ or -] 0.47 (a)        0.57 [+ or -] 0.76 (b)
Adults          0.71 [+ or -] 1.54 (c)        2.29 [+ or -] 1.54 (a)
Elderly         0.14 [+ or -] 0.36 (a)        0.36 [+ or -] 0.63 (a)
Total           1.36 [+ or -] 1.45 (b)        4.00 [+ or -] 2.29 (b)

Note. Means with the same letter are not significantly
different at the .05 level. "=" indicates the data is absent.
For instance, at Level 3, the CO concentration in Dali is
significantly larger than that in Situn (p < .05), but the CO
concentration in Situn is not significantly different from
that in Jhongming. In Dali at Level 1, Level 2, and Level 3,
means with the same underline are not significantly different
at the .05 level.

TABLE 1b
A Comparison of Four Districts in the Taichung Metropolis
During the Examined Period, Level 3

UHI                                    Level 3
Intensities

Districts              Jhongming                      Situn
                        (n = 44)                     (n = 44)

[PM.sub.10]
  ([micro]g/
  [m.sup.3])    89.50 [+ or -] 56.29 (a)    92.05 [+ or -] 58.73 (a)
[O.sub.3]
  (ppb)         23.97 [+ or -] 7.54 (b)     35.01 [+ or -] 10.11 (a)
N[O.sub.2]
  (ppb)         29.37 [+ or -] 10.41 (b)    22.98 [+ or -] 11.53 (c)
S[O.sub.2]
  (PPb)          6.24 [+ or -] 4.18 (a)      3.48 [+ or -] 2.11 (c)
CO (ppm)         0.70 [+ or -] 0.32 (b)      0.65 [+ or -] 0.34 (b)
PSI              72.6 [+ or -] 28.5 (b)      74.7 [+ or -] 29.O (a,b)
Preschoolers     1.05 [+ or -] 1.06 (a)      1.32 [+ or -] 1.16 (a)
Children         1.02 [+ or -] 1.15 (b)      1.55 [+ or -] 1.32 (a)
Adults           2.30 [+ or -] 1.52 (b)      3.50 [+ or -] 1.90 (a)
Elderly          0.34 [+ or -] 0.68 (a)      0.30 [+ or -] 0.46 (a)
Total            4.70 [+ or -] 1.91 (b)      6.66 [+ or -] 2.67 (a)

UHI                                    Level 3
Intensities

Districts                Wufong                        Dali
                        (n = 44)                     (n = 44)

[PM.sub.10]
  ([micro]g/
  [m.sup.3])    94.56 [+ or -] 37.11 (a)     90.17 [+ or -] 44.16 (a)
[O.sub.3]
  (ppb)         33.64 [+ or -] 8.10 (a)      32.14 [+ or -] 8.59 (a)
N[O.sub.2]
  (ppb)         24.09 [+ or -] 7.41 (c)      34.29 [+ or -] 9.00 (a)
S[O.sub.2]
  (PPb)          4.86 [+ or -] 0.97 (b)       5.39 [+ or -] 2.64 (a)
CO (ppm)                   --                 1.05 [+ or -] 0.32 (a)
PSI                        --                 85.8 [+ or -] 25.8 (a)
Preschoolers      0.4 [+ or -] 0.62 (b)       1.27 [+ or -] 1.26 (a)
Children         0.34 [+ or -] 0.64 (c)       1.59 [+ or -] 1.24 (a)
Adults           1.20 [+ or -] 1.13 (c)       3.23 [+ or -] 2.07 (a)
Elderly          0.16 [+ or -] 0.43 (a)       0.41 [+ or -] 0.69 (a)
Total            2.14 [+ or -] 1.36 (c)       6.50 [+ or -] 2.83 (a)

Note. Means with the same letter are not significantly
different at the .05 level. "=" indicates the data is absent.
For instance, at Level 3, the CO concentration in Dali is
significantly larger than that in Situn (p < .05), but the CO
concentration in Situn is not significantly different from
that in Jhongming. In Dali at Level 1, Level 2, and Level 3,
means with the same underline are not significantly different
at the .05 level.
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Title Annotation:INTERNATIONAL PERSPECTIVES
Author:Lai, Li-Wei; Cheng, Wan-Li
Publication:Journal of Environmental Health
Article Type:Report
Geographic Code:1USA
Date:Jan 1, 2010
Words:3923
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