The urban heat island and its impact on heat waves and human health in Shanghai. Int J Biometeorol 54: 75-84

Article (PDF Available)inInternational Journal of Biometeorology 54(1):75-84 · October 2009with218 Reads
DOI: 10.1007/s00484-009-0256-x · Source: PubMed
Abstract
With global warming forecast to continue into the foreseeable future, heat waves are very likely to increase in both frequency and intensity. In urban regions, these future heat waves will be exacerbated by the urban heat island effect, and will have the potential to negatively influence the health and welfare of urban residents. In order to investigate the health effects of the urban heat island (UHI) in Shanghai, China, 30 years of meteorological records (1975-2004) were examined for 11 first- and second-order weather stations in and around Shanghai. Additionally, automatic weather observation data recorded in recent years as well as daily all-cause summer mortality counts in 11 urban, suburban, and exurban regions (1998-2004) in Shanghai have been used. The results show that different sites (city center or surroundings) have experienced different degrees of warming as a result of increasing urbanization. In turn, this has resulted in a more extensive urban heat island effect, causing additional hot days and heat waves in urban regions compared to rural locales. An examination of summer mortality rates in and around Shanghai yields heightened heat-related mortality in urban regions, and we conclude that the UHI is directly responsible, acting to worsen the adverse health effects from exposure to extreme thermal conditions.
ORIGINAL PAPER
The urban heat island and its impact on heat waves
and human health in Shanghai
Jianguo Tan & Youfei Zheng & Xu Tang & Changyi Guo & Liping Li & Guixiang Song &
Xinrong Zhen & Dong Yuan & Adam J. Kalkstein & Furong Li & Heng Chen
Received: 17 December 2008 / Revised: 29 July 2009 / Accepted: 3 August 2009 / Published online: 1 September 2009
#
ISB 2009
Abstract With global warming forecast to continue into
the foreseeable future, heat waves are very likely to
increase in both freque ncy and intensity. In urban regions,
these future heat waves will be exacerbated by the urban
heat island effect, and will have the potential to negatively
influence the health and welfare of urban residents. In order
to investigate the health effects of the urban heat island
(UHI) in Sha nghai, China, 30 years of meteorological
records (197 52004) were e xamined for 11 first- and
second-order weather stations in and around Shanghai.
Additionally, automatic weather observation data recorded
in recent years as well as daily all-cause summer mortality
counts in 11 urban, suburban, and exurban regions (1998
2004) in Shanghai have been used. The results show that
different sites (city center or surroundings) have experi-
enced different degrees of warming as a result of increasing
urbanization. In turn, this has resulted in a more extensive
urban heat island effect, causing additional hot days and
heat waves in urban regions compared to rural locales. An
examination of summer mortality rates in and around
Shanghai yields heightened heat-related mortality in urban
regions, and we conclude that the UHI is dire ctly
responsible, acting to worsen the adverse health effects
from exposure to extreme thermal conditions.
Keywords Global warming
.
Urban heat island
.
Heat wave
.
Human health
Introduction
In recent years, the impact of weather on human health has
become an issue of increased significance, especially
considering the potential impacts of global warming and
an increased urban heat island effect due to urbanization
(Kunst et al. 1993; Kalkstein and Greene 1997; Guest et al.
1999; Smoyer et al. 2000). Warming of the climate system
is unequivocal. The IPCC Fourth Assessment Report (AR4)
clearly indicates that the update d 100-year linear trend
(19062005) of global surface temperature is 0.74 K. The
warming trend over the last 50 years has averaged 0.13 K
per decade and 11 of the last 12 years (19952006) rank
among the 12 warmest years since 1850 (IPCC 2007). A
J. Tan (*)
:
X. Zhen
Shanghai Urban Environmental Meteorology Center,
951 Jinxiu Road, Pudong,
Shanghai 200135, China
e-mail: jianguot@21cn.com
Y. Zheng
Key Laboratory of Meteorological Disaster of Ministry of Education,
Nanjing University of Information Science &Technology,
Nanjing 210044, China
X. Tang
Shanghai Meteorological Bureau,
166 Puxi Road,
Shanghai 200030, China
C. Guo
:
G. Song
:
D. Yuan
Shanghai Municipal Center for Disease Control & Prevention,
1380 ZhongShan West Road,
Shanghai 200336, China
L. Li
:
F. Li
:
H. Chen
Injury Prevention Research Centre,
Medical College of Shantou University,
22 Xinling Road,
Shantou City 515041, Guangdong Province, China
A. J. Kalkstein
Department of Geography and Environmental Engineering,
United States Military Academy,
West Point, NY, USA
Int J Biometeorol (2010) 54:7584
DOI 10.1007/s00484-009-0256-x
warming climate will likely result in an increase in the
frequency and intensity of heat waves (McMichael et al.
1996; Meehl et al. 2001; Patz and Khaliq 2002).
The urban heat island (UHI) has become one of the largest
problems associated with the urbanization and industrializa-
tion of human civilization, as the increased temperatures
associated with the UHI tend to exacerbate the threats to
human health posed by thermal stress. As a result, the UHI
has been a centr al theme among climatologists, and it is well
documented in many metropolitan areas around the world
(Oke 1973; Katsoulis and Theoharatos 1985; Balling and
Cerveny 1987; Lee 1992; Saitoh et al. 1996; Yamashita
1996; Böhm 1998; Figuerola and Mazzeo 1998; Klysik and
Fortuniak 1999; Kim and Baik 2002; Wilby 2003). The
UHI experienced by many cities is larger at night than
during the day, more pronounced in winter than in summer,
and is most apparent when winds are weak. For example, in
Beijing, the difference in mean air temperature between the
city center and surrounding fields can be as much as 4.6 K
(Zhang et al. 2002; Song and Zhang 2003). This results in
additional hot days in urban locales, which can directly
influence the health and welfare of city residents.
As UHIs are characterized by increased temperature,
they can potentially increase the magnitude and duration of
heat waves within cities. Scientists have also discovered
that the impacts of heat waves on humans vary among
different regions within a city. As early as 1972, Buechley
et al. (1972) investigated the relationship between the heat
island and death island and found that the mortality rate
during a heat wave in creases exponent ially with th e
maximum temperature, an effect that is enhanced by the
UHI. Clarke (1972) revealed that the nighttime effect of
UHIs can be particularly harmful during a heat wave, as it
deprives urban residents of the cool relief found in rural
areas during the night. Thus, during heat waves, death rates
are often much higher in cities than in outlying environs
(Henschel et al. 1969; Buechley et al. 1972; Clarke 1972;
Jones et al. 1982; Smoyer 1998). An epidemiologic study
of mortality during the summer 2003 heat wave in Italy also
illustrated that those liv ing in urban regions have an
elevated risk of death compared to those living in suburban
or rural areas as a result of heightened urban temperatures
(Conti et al. 2005).
Unlike purely tropical regions that remain war m all year
round, Shanghai experiences a subtropical climate with
cold, dry winters and wet, hot summers, as well as a
pronounced UHI (Ding et al. 2002; Zhou et al. 2002).
Shanghai has been found to be prone to heat-related
mortality (Tan et al. 2004, 2007), although few studies
have quantitatively or qualitatively examined the impact of
the UHI on the frequency or the intensity of heat waves
along with its corresponding impact on heat-related
mortality among the urban and suburban populations. Thus,
the goal of this paper is to determine the influence of the
Shanghai UHI on heat waves and human health wi thin both
urban and rural locales.
Materials and methods
The study was carried out over the region of Shanghai,
China, whi ch encompasses approximately 6,300 km
2
, and
contains a population listed as slightly over 18 million in
2006. In order to capture the effects of urban areas on local
climate, 30 years (19752004) of dail y maximum temper-
ature were compiled covering only the summer months,
defined here as May through October. These data were
examined for 11 first- and second-order weather stations
(Fig. 1) and were obtained from the Shanghai Meteorological
Bureau. The specific sites in this study are: the urban site
(XuHui-58367), suburban sites (MingHang-58361, BaoShan-
58362, PuDong-58470, JiaDing-58365), and exurban sites
(ChongMing-58366, NanHui-58369, JinShan-58460, QinPu-
58461, SongJiang-58462, FengXian-58463). For each year
throughout the 30-year research period, we first examined the
yearly extreme maximum temperature (the single hottest day
in each year), the mean daily maximum temperature in mid-
summer (defined as July through August), and the number of
hot days (defined as days exceeding 35°C in T
max
) for each of
the 11 stations. Simple linear regression was used to discern
overall trends in the data, and the statistical significance of
these trends was assessed (Table 1). The number of hot days,
as well as heat wave duration at urban, suburban, and
exurban sites, are listed in Table 2.
The UHI intensity is typi cally defined as the temperature
difference (ΔT) between the urban (u), suburban (s), and
exurban (e) locations. This is described in terms of the
difference in daily maximum temperatur e between the
urban center and suburban sites (ΔT
u-s
), and that between
urban cen ter and the exurban s tations ( ΔT
u-e
). The
observed values of urban, suburban, and exurban sites were
represented by the temperature from the urban site
(XuHui station), the average of four suburban stations
(MinHang, BaoShan, PuDong, JiaDing), and the average
temperature from the exurban stations (ChongMing,
NanHui, JinShan, QingPu, SongJiang and FengXian),
respectively. The UHI intensity of each site (ΔT
i
)is
calculated by the temperature difference between the urban
site (XuHui station) and each suburban or exurban site as
follows:
$T
i
¼ Tmax
0
Tmax
i
While Tmax
0
is the daily maximum temperature at the
urban site, Tmax
i
is the daily maximum temperature at the
suburban or exurban site. In order to investigate the diurnal
76 Int J Biometeorol (2010) 54:7584
variation of the UHI intensity, the temperature difference
between the urban (XuHui), suburban (JiaDing), and exurban
(ChongMing, FengXian, JinShan, SongJiang) sites are calcu-
lated from automatic weather stations from June through
August, 20052007. The observed variations in the urban
heat island effect have been plotted in Figs. 2, 3,and4.
Here, a hot day is defined as a day with a daily
maximum temperature exceeding 35°C in at least 1 of the
11 sites in Shanghai. Days below this threshold were
categorized as non-heat days. Additionally, a heat wave is
defined as a period with at least three consecutive hot days.
Although this definition is somewhat arbitrary, it was
chosen to correspond with the Chinese Meteorological
Administration heat warnings, which are issued when
maximum temperatures are forecast to exceed 35°C.
Furthermore, with the assumption that each meteorological
Fig. 1 Shanghai within China and the spatial distribution of 11 weather stations across Shanghai
Table 1 The rates of increase and linear regression results by year for annual extreme maximum temperature, mean maximum temperature in
mid-summer (JulAug), and hot days at urban, suburban, and exurban sites
Sites Yearly extreme maximum
temperature
Mean maximum temperature
in mid-summer (JulAug)
Hot days
Rate of increase
(K / year)
R
2
p Rate of increase
(K / year)
R
2
p Rate of increase
(days / year)
R
2
p
Urban XuHui 0.085 0.389 0.0001 0.073 0.240 0.0044 0.64 0.388 0.0001
Suburban MinHang 0.049 0.172 0.0181 0.051 0.150 0.0282 0.29 0.168 0.0197
BaoShan 0.066 0.271 0.0022 0.054 0.136 0.0376 0.40 0.278 0.0019
PuDong 0.067 0.204 0.0095 0.054 0.158 0.0240 0.34 0.279 0.0018
JiaDing 0.062 0.241 0.0043 0.049 0.128 0.0448 0.41 0.272 0.0021
Exurban QingPu 0.051 0.158 0.0244 0.045 0.112 0.0609 0.28 0.161 0.0229
ChongMing 0.035 0.090 0.0918 0.038 0.082 0.1138 0.10 0.070 0.1427
NanHui 0.029 0.053 0.2053 0.028 0.064 0.1623 0.09 0.074 0.1305
JinShan 0.013 0.013 0.5409 0.024 0.042 0.2603 0.07 0.026 0.3817
SongJiang 0.034 0.076 0.1276 0.034 0.070 0.1442 0.20 0.090 0.0952
FengXian 0.009 0.004 0.7196 0.020 0.030 0.3408 0.08 0.036 0.2950
Statistically significant slopes at 95% confidence level (p0.05) are in bold
Int J Biometeorol (2010) 54:7584 77
observation site represents its entire area or district, we
classify days in which more than eight of the s ites
experienced maximum temperatures above 35°C as large-
scale hot days, thus covering 59.682.6% of the total area
of Shanghai. The consistency of hot day occurrence among
the 11 sites has been plotted in Fig. 5.
All deaths recorded between 1998 and 2004 for all
regions of Shanghai were obtained from the Shanghai
Municipal Center for Disease Control and Prevention. These
data consist of the daily mortality totals of each district for all
causes of death and cover the summer study period.
Excess deaths are calculated by subtracting a baseline
death rate from the observed daily mortality value.
Numerous methods have been identified in the literature
for calculating the baseline mortality (Gosling et al. 2009),
and here, we adopt a 30-day moving average for the same
year (Rooney et al. 1998; Dessai 2002, 2003; Gosling et al.
2007).
Results
Warming trends at the urban, suburban and exurban sites
As demonstrated in Table 1, there are different linear
warming trends in the different areas (city center, suburban,
and exurban areas) of Shanghai over the last 30 years
(19752004), covering the yearly extreme maximum
temperature, the average maxi mum temperature from July
through August, and the number of hot days during the
y = 2E-05x
2
+ 0.0411x + 0.147
R
2
= 0.7704
y = -0.001x
2
+ 0.0523x + 0.1132
R
2
= 0.6951
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
1975 1979 1983 1987 1991 1995 1999 2003
Year
Heat Island Intensity (K)
Tu-s Tu-e
Fig. 2 The variation of urban heat island intensity [in terms of the
difference of daily maximum temperature between the urban center
and suburban sites (ΔT
u-s
), and that between urban and exurban
(ΔT
u-e
) sites] from 1975 to 2004
Sites Hot days
(days / year)
Heat wave duration
3 days 5 days 7 days >10 days
Urban XuHui 11.2 39 18 9 5
Suburban MinHang 7.4 25 12 4 1
BaoShan 7.5 22 11 8 1
PuDong 5.2 18 8 1 0
JiaDing 7.6 27 9 5 1
Exurban QingPu 7.7 26 9 4 0
ChongMing 3.1 9520
NanHui 2.7 7210
JinShan 5.2 14 6 3 0
SongJiang 6.4 21 8 4 0
FengXian 3.7 8220
Table 2 The average number
of hot days and the occurrence
of different heat wave durations
at urban, suburban, and
exurban sites in Shanghai
(19752004)
Tu-s
-0.5
0
0.5
1
1.5
2
May June July August September October
Month
Heat Island Intensity ( K )
-0.50
0.00
0.50
1.00
1.50
2.00
May June July August September October
Month
Heat Island Intensity ( K )
Tu-e
Fig. 3 The mean heat island intensity [in terms of the difference of
daily maximum temperature between the urban center and suburban
sites (ΔT
u-s
), and that between urban and exurban stations (ΔT
u-e
)] by
month from 1975 through 2004. Error bars indicate ±1 SD
78 Int J Biometeorol (2010) 54:7584
summer. Significant trends, using a 95% confidence level
(p<0.05), are observed at the city center, all suburban sites,
and one exurban location (QingPu).
The average mid-summer (July and August) maximum
temperature in the urban center is rising at a rate of 0.073 K
per year (p =0.0044), with a 0.085 K per year (p =0.0001)
increase in yearly extreme maximum temperature. Similarly,
in the city center, the number of hot days is increasing by a
rate of 0.64 days per year (p =0.0001), while more modest
increases varying from 0.29 (p =0.0197) to 0.41 (p =0.0021)
days per year are observed at the suburban sites. There are no
significant upward trends in exurban areas, with one single
exception (QingPu). Clearly, urban regions in Shanghai are
warming at a faster rate than those in the surrounding areas.
Variations in the characteristics of the urban heat island
effect
The intensity of the urban heat island is measured in terms
of the difference in daily maximum temperature between
the urban center and the suburban sites (ΔT
u-s
), and that
between the urban center and the exurban sites (ΔT
u-e
)
(Fig. 2). From the 1970s to the mid-1980s, the UHI was
much less pronounced, with an average difference in daily
maximum summer temperature of 0.20.4 K between the
city center and its surroundings. However, these temperature
differences increased during the period of study, particularly
between the city center and the exurban locations. In fact,
beginning in the mid-1980s, there is a distinct deviation
between the UHI intensities of the exurban and the suburban
sites. While the temperature difference of urban-exurban
areas rose further to 1.6 K, differences between the urban and
suburban sites remaine d at approximatel y 0.8 K. This
disparity is likely due to the rapid expansion of Shanghai
into the suburban regions beginning in the mid-1980s.
The UHI intensity was strongest in July during the
summer months, where the average UHI intensity reached
0.9 K between urban and exurban areas (ΔT
u-e
), and 0.6 K
between urban and suburban areas (ΔT
u-s
)(Fig.3).
Furthermore, the diurnal variation of the heat island
intensity derived from the six automatic weather stations
located in the urban (XuHui), suburban (JiaDing), and
exurban sites (ChongMing, FengXian, JinShan, SongJiang)
in summer (June through August), 20052007, shows that
the heat island intensity is more pronounced in the daytime
than that in the night (Fig. 4). The highest value in the
region of 0.52.0 K occurs at noon or in the afternoon,
corresponding approximately to the time in which the daily
maximum temperature is reached.
The urban heat island and heat waves
As a result of increased temperatures within the urban
locales, the UHI may affect the number of hot days as well
as the duration of heat waves, potentially increasing the risk
of mortality from heat stress. The yearly average number of
hot days and the total number of heat waves with different
durations over the research period (19752004) at different
locations in Shanghai are listed in Table 2. Not surprisingly,
the largest average value of annual hot days is 11.2 days per
year in the urban site (XuHui), whi le fewer hot days occur
in the exurban sites such as ChongMing, NanHui, or
FengXian. Similarly, heat wave duration is also impacted
by the UHI, so that the longest duration heat waves (for
example, a heat wave with at least 10 consecutive hot days)
usually occurred in the urban area. There were five such events
at the urban location (XuHui) with only one event recorded
at the suburban stations (MinXing, BaoShan, JiaDing).
In order to discern whether increasing numbers of hot
days are attributable to a regional climate warming or to an
expanding UHI, we examined the five hottest years (1978,
1983, 1988, 1998, and 2003) and analyzed the consistency
of hot day occurrence among the 11 sites. This was done to
0
5
10
15
20
25
30
35
40
45
50
1978 1983 1988 1998 2003
Year
Number of hot days
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Proportions of large-scale hot days
Hot days
proportions of large-scale hot days
Fig. 5 The number of hot days (>35°C) and the proportion of large-
scale hot days (>35°C at eight or more stations) during the five hottest
years on record
Fig. 4 The diurnal variation of the temperature difference between the
city center (XuHui) and suburban(JiaDing), and various exurban sites
(ChongMing, FengXian, JinShan, SongJiang) over 24 h in summer
(JuneAugust, 20052007)
Int J Biometeorol (2010) 54:7584 79
determine the frequency of large-scale hot days in the
investigation area during these y ears. Figure 5 illustrates a
decreasing trend of the proportion of the large-scale hot
days corresponding with an increasing number of hot days.
For example, at least 1 of the 11 stations in Shanghai
reported a hot day 16 times in 1983, and among these there
were 13 large-scale hot days, accounting for 81.3%. In
2003, however, there were 45 hot days reported but only
29.5% of these were large-scale hot days. Thus, it seems
that the growing UHI increases the number of hot days
around the city center, but large-scale hot days are not
increasing. This provides strong evidence that the warming
is local in nature, caused alm ost entirely by the UHI, and
not as a result of a larger, regional warming pattern.
The urban heat island and excess death
The relationships between hea t and hum an health are
summarized in Tab le 3, which illustra tes the excess
mortality rate, the number of heat waves, and the average
maximum temperature for each heat wave from 1998 to
2004 in each region. Population-adjusted excess mortality
in each region, along with UHI intensity, has been plotted
for each year in Fig. 6. The excess deaths in the central
urban region are higher than those in the suburban and
exurban sites, which coincide well with heat isl and
intensity, especiall y in the two severe heat waves in 1998
and 2003 (Tan et al. 2004, 2007). For example, with the
1998 heat wave, the excess mortality rate in the urban area
is about 27.3/100,000, compared to only 7/100,000 in the
exurban districts.
Furthermore, a comparison between excess deaths and
the spatial coverage of the two heat waves in 1998 and
2003 (Fig. 7) shows that the extent of high temperatures
played an important role in the number of excess deaths. In
general, the more stations that reported hot days, the higher
the number of excess deaths. In 1998, Shanghai experi-
enced long duration, large-scale hot days with more than
nine districts experi encing temperatures above 35°C for
nine consecutive days from August 8 to 16. As a result,
excess deaths increased sharply with a maximum value of
453 deaths observed on August 16. On the other hand, in
2003, there were frequent hot days, often with a large
number of consecutive days, but these heat waves were not
often experienced by a large number of stations. Thus, the
spatial coverage of the 2003 event was much smaller than
that observed in 1998, resulting in fewer deaths.
Discussion
The urban heat island effect is among the most well-
documented impacts of human activity on local climate. As
large-scale climate change continues, the UHI is very likely
to exacerbate the warming, resulting in more frequent and
more intense heat waves (Wilby 2003). Research on the
UHI has typically focused on tropical or mid-latitude cities
for the dual purposes of understanding the dynamics of the
energy balance in the urban boundary layer and its
application to issues related to urban pollution, energy
conservation, and the prevention of heat-related health
problems or deaths (Buechley et al. 1972; Smoyer 1998).
Here, the comparison between meteorological monitor-
ing stations both inside and around the city of Shanghai
revealed the large impact of the urban heat island effect on
temperature, heat waves, and human health. The results
demonstrate that the meteorological sites (city center and its
surroundings) have experienced different degrees of warm-
ing over the period of record as a direct resul t of increasing
urbanization and a more pronounced heat island. Addition-
ally, we find that the hottest days (above 35°C), as well as
prolonged heat waves, are more likely to occur in urban
locales.
The UHI is often referred to as a nighttime phenomenon
with the highest values of the UHI intensity occurring
between midnight and early morning, especially in winter.
This has been documented in the United States, Italy, and
beyond (Basu and Samet 2002;deDonato et al. 2008),
highlighting that the major differences between urban and
rural areas were measured during the night. However, for
Shanghai, our results show that the heat island is often
more pronounced in the daytime during the summer, with
the highest urbanrural differences ranging from 0.5 to
2.0 K at noon or in the afternoon, coinciding with the
timing of maximum daily temperature.
The incre ased thermal loads found in urban areas may be
a direct factor for heightened levels of human mortality
(Clarke and Bach 1971; Jones et al. 1982; Conti et al.
2005
). Additionally, previous studi es note that virtually all
causes of mortality increase during extreme heat waves,
including respiratory failure and circulatory system failure
from heart atta ck or stroke. The results of this study
demonstrate that heat-related mortality (all-cause deaths
above the baseline) is often much higher in the inner city
than in outlying environs during heat waves, coinciding
with heat island intensity. Inhabitants of urban areas may
experience sustained thermal stress both day and night as
city surfaces often heat up quickly during the day but are
slow to cool at night (Sheridan and Dolney 2003). There is
emerging evidence that the urban population shows greater
sensitivity to heat compared to those in rural regions. For
example, analyses of the 1995 Chicago heat wave have
shown that the relative risk for a heat-related hospital
admission in the city was nearly two times higher compared
to the suburbs (Rydman et al. 1999). Similar results were
found in 2003, where heat wave mortality was greater in
80 Int J Biometeorol (2010) 54:7584
Table 3 Summary statistics of excess mortality rate and mean maximum temperature in heat waves, broken down by region and year
Year Item Urban MinHang BaoShan PuDong JiaDing ChongMing NanHui JinShan QingPu SongJiang FengXian
1998 Heat waves 3 2 2 1 1 1 2 1 2 1 2
Longest duration 7/817/8 8/8 17/8 7/8 15/8 8/8 16/8 8/8 16/8 8/8 15/8 10/8 16/8 8/8 17/8 7/8 16/8 8/8 17/8 9/8 16/8
Tmax(°C) 36.8 36.9 36.4 37 36.4 35.9 36.2 36.3 36.5 36.4 35.8
Excess mortality rate (1/100,000) 27.30 18.20 18.99 15.82 13.08 9.21 12.81 8.01 12.51 18.15 7.00
1999 Heat waves 0 0 1 0 0 0 0 0 0 0 0
Longest duration 9/9 11/9
Tmax(°C) 35.3
Excess mortality rate (1/100,000) 0.40
2000 Heat waves 2 2 1 2 1 0 0 1 1 1 0
Longest duration 20/7 24/7 20/7 24/7 20/7 23/7 20/7 24/7 20/7 23/7 21/7 24/7 21/7 23/7 21/7 24/7
Tmax(°C) 36.1 35.3 36.8 35.7 36 35.4 35.9 35.8
Excess mortality rate (1/100,000) 2.51 2.29 0.25 0.91 0.41 0.94 1.09 0.20
2001 Heat waves 2 3 1 2 3 0 0 1 2 1 0
Longest duration 19/7 31/7 25/7 29/7 28/6 2/7 28/6 2/7 28/6 2/7 29/6 2/7 28/6 3/7 29/6 1/7
Tmax(°C) 36.5 35.7 36.1 36.1 36.2 36.1 36.4 36.1
Excess mortality rate (1/100,000) 0.93 0.89 2.29 0.95 4.82 1.89 2.85 3.82
2002 Heat waves 4 0 0 1 0 0 0 0 0 0 0
Longest duration 22/8 26/8 14/7 16/7
Tmax(°C) 36.1 36.4
Excess mortality rate (1/100,000) 2.57 0.41
2003 Heat waves 4 4 2 4 4 1 0 2 4 3 1
Longest duration 19/7 6/8 28/7 3/8 21/7 29/7 19/7 25/7 19/7 4/8 25/7 29/7 28/7 30/7 28/7
3/8 28/7 4/8 27/8 30/8
Tmax(°C) 36.6 36.1 36.9 36 36.3 35.7 36.2 36.6 36.2 35.9
Excess mortality rate (1/100,000) 4.32 6.39 5.85 1.64 17.39 1.42 3.41 5.89 3.16 0.00
2004 Heat waves 2 2 3 3 3 2 0 0 2 2 1
Longest duration 16/7 31/7 19/7 31/7 17/7 7/30 20/7 25/7 17/7 1/8 20/7 25/7 17/7 31/7 17/7 31/7 23/7 25/7
Tmax(°C) 36.2 36 35.8 35.9 36.2 35.8 36 36.2 36.5
Excess mortality rate (1/100,000) 3.33 5.60 0.23 1.00 2.89 0.57 0.22 1.56 0.39
Int J Biometeorol (2010) 54:7584 81
urban regions compared to suburban areas in Switzerland
(Grize et al. 2005).
Our previous investigation revealed that observed differ-
ences in heat-related mortality between two severe heat
waves in 1998 and 2003 could be traced to the longevity of
the heat; prolonged exposure to heat is more stressful to
human health than isolated hot days (Tan et al. 2007). Here,
we confirm that the UHI serves to enhance the prolonged
exposure to heat in the city center, resulting in elevated
levels of heat-related mortality in urban regions.
This study was subject to several limitations. First, many
approaches such as absolute threshold temperature (Huynen
et al. 2001), relative threshold temperature (Hajat et al.
2002), and synoptic climatological approaches (Sheridan
2002; Sheridan and Kalkstein 2004) can also be used to
define heat waves. Although our definition is somewhat
arbitrary, it was chosen to correspond with the Chinese
Meteorological Administrations heat warnings, which are
issued when maximum temperatures are forecast to exceed
35°C. Thus, Chinese residents are more familiar with the
definition used here. Second, the effects of the UHI on
heat-related mortality are multifaceted, and we did not
examine data measuring air pollution, other meteorological
factors such as cloud cover or humidity, or the potential
impacts of socioeconomic status or other social variables.
Therefore, no confounding effects were evaluated. Previous
research indicates that human mortality is impacted by both
ambient meteorological conditions and atmospheric pollut-
ant levels. The stagnant atmospheric condit ions common
during heat waves can trap pollutants in urban areas,
exacerbating the negative impacts of the heat wave
-5
0
5
10
15
20
25
30
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
Urban Heat Island Intensity(K)
excess mortality(1/100000)
1998
2000
2001
2003
2004
Fig. 6 The excess mortality rate and the heat island intensity for heat
waves in Shanghai
(a) 1998
-8
-4
0
4
8
12
16
20
6-16
6-20
6-24
6-28
7-2
7-6
7-10
7-14
7-18
7-22
7-26
7-30
8-3
8-7
8-11
8-15
8-19
8-23
8-27
8-31
9-4
9-8
9-12
Date
The number of the sites with
Tmax
35
°
C
-200
-100
0
100
200
300
400
500
excess deaths
The number of the sites with Tmax
35
°
C
excess deaths
(b) 2003
-8
-4
0
4
8
12
16
20
6-16
6-20
6-24
6-28
7-2
7-6
7-10
7-14
7-18
7-22
7-26
7-30
8-3
8-7
8-11
8-15
8-19
8-23
8-27
8-31
9-4
9-8
9-12
Date
The number of the sites with
Tmax
35
°
C
-200
-100
0
100
200
300
400
500
excess deaths
The number of the sites with Tmax
35
°
C
excess deaths
Fig. 7 The number of excess
deaths versus the number of
stations reporting hot days dur-
ing the summers of 1998 (a) and
2003 (b)
82 Int J Biometeorol (2010) 54:7584
(Anderson et al. 1996; Piver et al. 1999; Johnson et al.
2005). Air pollution such as ozone and PM10 compound
the heatmortality relationship, and previous research
suggests that between 21 and 38% of the excess deaths
observed during the summer 2003 European heat wave
were attributable to these pollutants (Stedman 2004).
However, it remains difficult to separate the impacts of
heat and pollution on human health, and it is possible that
some of the heightened urban mortality totals in this study
were partially a resul t of elevated concentrations of airborne
pollutants found in the city center.
Conclusion
There is no doubt that the urban heat island (UHI) has a
profound impact on human health. The UHI serves to
enhance the intensity of heat waves, which in turn
adversely affects human health due to an increased
exposure to extreme thermal conditions. As a result, heat-
related mortality is found to be higher in the city center
compared to suburban locales. This research provides
evidence that Shanghai local officials should be cognizant
of the increased thermal loads experienced in urban regions
and take appropriate action to help reduce the impact of
heat on the population.
Acknowledgements This material is based upon work supported by
The Natural Science Foundation of China (No. 30771846), Jiangsu
Key Laboratory of Meteorological Disaster (No. KLME05005),
National Scientific and Technical supporting Programs, Ministry of
Science and Technology of China (No. 2006BAK13B06), and the
Gong-Yi Program of China Meteorological Administration (No.
GY200706019). Two anonymous reviewers are thanked for their
comments on an earlier version of the manuscript.
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