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BUILT ENVIRONMENT AND HEALTH (MJ NIEUWENHUIJSEN AND AJ DE NAZELLE, SECTION EDITORS)
The Urban Heat Island: Implications for Health
in a Changing Environment
Clare Heaviside
1,2,3
&Helen Macintyre
1
&Sotiris Vardoulakis
2,3,4
#Springer International Publishing AG 2017
Abstract
Purpose of Review The Urban Heat Island (UHI) is a well-
studied phenomenon, whereby urban areas are generally
warmer than surrounding suburban and rural areas. The most
direct effect on health from the UHI is due to heat risk, which
is exacerbated in urban areas, particularly during heat waves.
However, there may be health benefits from warming during
colder months. This review highlights recent attempts to quan-
titatively estimate the health impacts of the UHI and estima-
tions of the health benefits of UHI mitigation measures.
Recent Findings Climate change, increasing urbanisation and
an ageing population in much of the world, is likely to in-
crease the risks to health from the UHI, particularly from heat
exposure. Studies have shown increased health risks in urban
populations compared with rural or suburban populations in
hot weather and a disproportionate impact on more vulnerable
social groups. Estimations ofthe impacts ofvarious mitigation
techniques suggest that a range of measures could reduce
health impacts from heat and bring other benefits to health
and wellbeing.
Summary The impact of the UHI on heat-related health is
significant, although often overlooked, particularly when con-
sidering future impacts associated with climate change.
Multiple factors should be considered when designing mitiga-
tion measures in urban environments in order to maximise
health benefits and avoid unintended negative effects.
Keywords Temp erature .Heat .Built environment .
Mitigation .Adaptation .Mortality .Cities
Introduction
People living in cities worldwide face a variety of risks to
health, due to pollution of the air, water and soil from industry
and traffic, from noise and from over-crowding and poor
housing [1]. This is of particular concern to the public health
community, as 2007 marked the tipping point whereby more
people lived in urban than rural areas, globally [2]. Increasing
urbanisation, climate change and ageing populations mean
that health risks for urban populations will continue to in-
crease in the future [3], particularly in the developing world
[4,5]. The Urban Heat Island (UHI) effect, which describes
the observation that temperatures in towns and cities are gen-
erally higher than in surrounding rural or suburban areas [6],
represents one mechanism by which the health of urban pop-
ulations can be compromised. The UHI effect can exacerbate
health impacts by affecting rainfall patterns [7], interacting
with and worsening air pollution [8], increasing flood risk
and decreasing water quality [9]. However, the most direct
impact of the UHI on human health is through exposure to
increased temperature, which can be particularly problematic
during heat waves.
There is a large body of research which associates exposure
to high or low temperatures to increased illness,
This article is part of the Topical Collection on Built Environment and
Health
*Clare Heaviside
clare.heaviside@phe.gov.uk
1
Environmental Change Department, Public Health England,
Harwell, Oxon OX11 0RQ, UK
2
School of Geography Earth and Environmental Sciences, University
of Birmingham, Birmingham B15 2TT, UK
3
Department of Social and Environmental Health Research, London
School of Hygiene and Tropical Medicine, 15-17 Tavistock Place,
London WC1H 9SH, UK
4
Institute of Occupational Medicine, Edinburgh EH14 4AP, UK
Curr Envir Health Rpt
DOI 10.1007/s40572-017-0150-3
hospitalisation and mortality, globally [10–13]. Events such as
heat waves can lead to peaks in heat-related mortality over the
space of a few days, for example the European heat wave of
2003 was associated with thousands of excess deaths [14].
City populations are especially at risk due to the additional
higher temperature associated with the UHI effect during heat
waves, which can exacerbate health impacts from heat. For
example, Paris and other French cities were particularly affect-
ed by the 2003 heat wave [15,16].
We reviewed recent studies which characterised and
quantified health impacts relating to the UHI, primarily
throughexposuretoheat,andthosewhichassessedthe
potential impacts on health of UHI mitigation measures.
We did not review studies on measurements or the physics
of the UHI, subjects which are well covered elsewhere
[17,18]. Where possible we focused on studies which
provided quantitative estimates of the health impacts of
the UHI effect. Figure 1illustrates the main topics cov-
ered by this review.
Characterising and Measuring the Urban Heat
Island
The phenomenon of higher ambient temperatures in urban,
rather than rural or suburban environments, is largely ex-
plained by the differences between land surface materials
and building geometry in urban and rural areas, which influ-
ence the surface energy balance. In cities, urban materials such
as concrete and paving absorb energy from the sun during the
day, and slowly release this energy into the air as heat, mostly
at nighttime, which is when the temperature difference be-
tween urban and rural areas, and hence the UHI intensity, is
usually largest. The lack of moisture in urban areas and in-
creased anthropogenic heating also contribute to the UHI ef-
fect. The effect was first recorded in 1833 in London, using
observations [19]. Since then, the magnitude of the UHI effect
has been recognised and estimated in many cities around the
world.
The UHI effect can occur in any urbanised area, although it
is usually more noticeable in larger cities. UHI ‘intensity’,
usually defined and measured as the difference in temperature
between the centre of an urban area and the temperature of a
rural reference point outside of the city, scales approximately
with population size [20]. In extreme cases, usually at night-
time, temperatures can be up to 5–10 °C higher in the centre of
cities like New York, London, Manchester and Birmingham
than in the surrounding countryside; although on average, the
UHI intensity is usually around 2 to 4 °C [21–24]. Even
though there is less incoming solar energy in winter than sum-
mer, the UHI effect can be large throughout the year. Most
UHI research focuses on summertime, since this is when most
of the potential harmful effects occur, and peak temperatures
are reached. Less research investigates the wintertime UHI
and potential benefits to health which may exist from winter
heating in urban areas. The conditions most favourable for a
large UHI effect are when skies are clear, due to the increased
solar heating in the daytime, and when winds are light so there
is a lack of atmospheric mixing and therefore dispersal of the
warm air. These conditions often coincide with heat waves,
where populations are particularly at risk from the effects of
heat.
Challenges When Assessing the Extent of the UHI Effect
Since the existence of the UHI has been acknowledged for so
long, methods to quantify its intensity have evolved over time.
These can be broadly classified by the use of (a) ground ob-
servations (either fixed or mobile), (b) satellite images or (c)
modelling using regional climate or meteorological models.
Traditionally, data from pairs of observational sites were
used to measure the UHI intensity, although the position and
local environment of the observational sites can vary by loca-
tion, which limits comparability between cities, and point
Fig. 1 Summary of topics covered in this review. Examples of relevant
publications on methods to assess health impacts ofthe Urban Heat Island
and on mitigation methods to reduce health impacts are indicated by
square brackets
Curr Envir Health Rpt
measurements provide little information on spatial variation in
temperature across a city. Additionally, temperature monitor-
ing stations have historically been sited outside of city centres
to reduce the potential for urban infrastructure influencing
ambient temperature measurements. Whilst this siting is use-
ful for analysis of long-term temperature trends without arti-
ficial influence, it can limit the availability of urban reference
temperature data points. Moving transects taken across a city
using vehicles may give more spatial information, and high-
density observational networks within cities have occasionally
been used [25], but these are difficult and costly to set up and
maintain. In recent years, satellite imagery has been used to
give an indication of the spatial variation in temperature across
a city, although the satellite images represent ‘skin’or surface
temperature, which is less relevant for human exposure than
air temperature at the surface, and images are limited to dis-
crete snapshots in time and only when there is no cloud cover.
These limitations mean that although the intensity of the
UHI can be estimated, there is a lack of high-quality informa-
tion on the variation of risk and population exposure to heat
across a city. This fact is highlighted by members of the public
health community, who outline the requirements for spatial
information on the UHI effect in order to identify areas, where
health impacts are likely to be larger, and in order to better
protect the public from harmful temperature effects [26].
Modelling studies using high-resolution regional weather
and climate models can provide an effective way to quantify
the UHI intensity, characterise spatial variations in tempera-
ture and, in theory, can be applied to any city in the world. In
order to be effective, relevant parameters representing urban
characteristics need to be included as inputs to the models, and
the unique nature of individual cities and local meteorology
should be observed [18]. The effects of urban parameters rel-
evant to the UHI, such as height, shape, three-dimensional
area and spatial distribution of buildings and other infrastruc-
ture can be determined using field and laboratory studies [27].
This information is then incorporated into building parameter
schemes, when running regional models, to improve surface
energy exchange in urban areas, e.g. [28]. In addition, by
varying model parameters, the range of effects of urban infra-
structure and the potential benefits of mitigation measures can
be investigated and quantified. Although modelled simula-
tions address some of the shortcomings of traditional measure-
ment techniques, they cannot replace the requirement for reli-
able observations which are essential for effective model
evaluation.
Health Implications of the UHI
Exposure to heat is associated with a range of adverse health
effects, ranging from exacerbation of minor existing condi-
tions to increased risk of hospitalisation and death [11]. Heat
stroke is not usually the sole cause of death; rather, heat is
often a contributory factor to deaths and morbidity from other
causes, such as respiratory illness [29]. This risk has been
shown to be significant at even moderately high temperatures
[12], although health effects are most severe during periods of
extremely high temperatures or heat waves. The enhancement
of temperatures due to the UHI effect therefore increases heat-
related mortality risk in urban areas, and this is likely to further
increase in future, due to climate change [30,31].
Temperatures during heat wave events generally reach a max-
imum during daytime hours, although high nighttime mini-
mum temperatures, which can keep indoor temperatures high,
are also likely to affect health, especially if a heat wave per-
sists over several days. For example, high nighttime tempera-
tures, a key characteristic of the UHI effect, were associated
with increased mortality during the 2003 heat wave in Paris
[32]. The populations most likely to be adversely affected by
heat are generally those in the older age groups and those with
existing health conditions.
Several studies have projected the potential impacts of heat
on mortality due to climate change [33,34], and some have
shown that although an increase in temperature may lead to
decreases in cold-related mortality in future, any benefits are
likely to be outweighed by the increase in heat-related deaths
due to the combined effects from projected increased mean
temperature and heat wave frequency and an ageing, growing
population [13,30]. Since there is less research on the poten-
tial health benefits of the UHI in preventing cold-related mor-
tality in winter months, interventions such as modifications to
building design to protect against the effects of heat should not
exacerbate the risks from cold, and vice versa [35]. Most stud-
ies based on climate projections do not explicitly include the
UHI effect due to the computational difficulty in resolving
features at the urban scale in global climate models, and this
may lead to underestimation of health impacts in urban areas
[36•]. When urban schemes are included in models, the future
impact of the UHI is often discussed, but this is not always
related to a health burden [37]. In the following sections, we
focus on work which has sought to identify and quantify the
heat-related health impacts directly associated with the UHI.
Assessing Heat Risk in Urban Areas
Variations in land surface type mean that temperature varies
across a city resulting in similar variations in the potential for
population exposure to heat. Higher UHI intensities tend to
occur in centrally located parts of the city, where people are
often more likely to be socially disadvantaged. In turn, these
socio-economic factors may modify how harmful the UHI
effect can be and increase vulnerability to the UHI in urban
populations [1].There is evidence that vegetated and therefore
cooler neighbourhoods are home to more affluent populations
and that heat-related health risks are lower in these areas [38].
Curr Envir Health Rpt
In addition, poorer neighbourhoods often lack critical physical
and social resources to cope with extreme heat [39]. Studies in
the USA also suggest strong relationships between land cover,
neighbourhood social conditions and surface temperatures
[40]. In particular, surface temperature is statistically higher
in areas characterised by poverty, ethnic minority groups, lack
of education, elderly populations and increased crime due in
part to high population density and therefore abundance of
manmade surfaces in these areas [41].
Dwelling type and building characteristics play fundamen-
tal roles in determining health risks from heat, and are likely to
be linked to social factors. For example, air conditioning can
protect against heat-related impacts by reducing indoor tem-
perature, but is not always available to more vulnerable pop-
ulation groups, despite becoming more affordable. Air condi-
tioning can lead to increased energy consumption and green-
house gas emissions (when not powered by renewable energy
sources) and can exacerbate the UHI by dissipating heat out-
doors. Some evidence suggests that air conditioning needs to
be available in the whole house to be effective, and there is
also a risk that constant use can increase physiological depen-
dence upon it [42]. Building design to prevent overheating in
homes is a key factor determining the vulnerability of the
population and a research topic in itself [43].
Spatial Mapping to Identify Heat Risk
Mapping techniques to identify population risk from exposure
to heat across a city make use of highly spatially resolved
information from climate or meteorological modelling, satel-
lite imagery [44] or interpolated observations [45]tocharac-
terise variations in urban temperature. Other factors which
modify the effects of heat on health, such as age or socio-
economic distribution, can also be mapped at the same time.
Attempts have been made to combine maps of hazards, in-
cluding the UHI effect as well as environmental, demographic
or physical factors, to give indications of risk variability across
a city, in the form of heat risk models [46–49]. In some cases,
this has resulted in creating an index of risk.
In the UK, the creation of a heat vulnerability index for the
city of London was based on nine proxy measures of heat risk,
selected following a literature search, and used principal com-
ponent analysis, weighted according to health impact [50].
The nine variables included information about housing,
socio-economic status, population density, access to heating
and air conditioning, occupant age and underlying health con-
dition. Results showed strong statistical evidence of clustering
of areas of high vulnerability, e.g. high population density in
central London and poor health statusand welfare dependency
in the east. Although satellite data and monitoring sites were
used to estimate the UHI intensity, there was a lack of consis-
tent highly spatially and temporally resolved temperature
information, and air pollution (often a significant risk factor
in urban areas) was not included as a risk factor [50].
Another London study highlighted the ‘triple jeopardy’of
age, UHI intensity and dwelling type (although not socio-
economic status) on heat risk [51•]. High-resolution modelled
temperature for a single hot day was included in the study, and
the analysis was carried out using GIS techniques. Exposure
to daily mean maximum temperature was derived from out-
door temperature, UHI anomaly per dwelling (outdoor tem-
perature compared with the average outdoor temperature for
all dwellings) and indoor temperature. Results showed that
UHI intensity and particularly dwelling type were the main
factors contributing to heat mortality risk [51•].
Quantification of the Health Burden Associated With
the UHI
Mapping studies go some way to identifying areas of heat
vulnerability, particularly when combined with demographic
and socio-economic data. Some mapping studies are linked
with recorded health data such as hospital admissions or mor-
tality figures, for example an analysis based on satellite data of
temperature for Philadelphia in the USA detected that the
spatial distribution of heat wave deaths in 1993 was co-
located with the urban poor as well as with higher UHI inten-
sity [52]. In Brisbane, hospital admissions data were analysed
using Bayesian modelling, and it was found there were signif-
icant increases in emergency, non-accidental hospitalizations
with increasing daily maximum temperature in summer for a
number of areas in the city, particularly those with high pop-
ulation density and low income [53]. An investigation of mor-
tality based on apparent temperature derived by spatial inter-
polation (using kriging) of sparse observation sites for
Massachusetts, USA, in urban and rural areas suggested that
demographic factors, such as ethnicity and age, may be more
important than level of urbanisation, at least for this particular
study area [54]. A US impact assessment for mortality and
energy use for cold and warm seasons [55] showed that the
impact of the UHI on heat-related deaths was estimated at an
increase of 1.1 deaths per million population, and the impact
of the UHI on cold-related deaths was a decrease of 4.0 deaths
per million. The author highlighted the importance of taking
the potential health benefits of the UHI into account as well as
costs. However, the results were derived simply by relating
information from death certificates on the underlying probable
cause of death (e.g. heat, cold) to urbanisation level in various
cities.
Epidemiological methods (cross sectional or longitudinal)
can be employed to investigate the risk of mortality depending
on the heat exposure experienced in different parts of a city,
often using satellite imagery. The analysis can be carried out
by (a) stratifying the data based on local temperature (or UHI
intensity), and calculating the temperature-mortality
Curr Envir Health Rpt
relationship separately for regions of different temperature,
e.g. [56–58], or (b) by comparing results for urban and rural/
suburban areas [59]. Case-control epidemiological studies
may also be employed, based on urban and rural population
samples [32]. Analyses may include cold effects, as well as
heat, and morbidity as well as mortality, such as a study in the
Czech Republic which focused on cardiovascular outcomes
and found some evidence to suggest that the UHI was one
possible risk factor for heat stress, along with demographic
factors and exposure to air pollution [60]. A recent study for
London went further by seeking to investigate whether there
were differences in the susceptibility to heat and cold experi-
enced by populations in urban and rural regions using case-
crossover epidemiological analyses, and whether adaptation
to heat and cold could be detected [61•]. The study used
modelled temperature for London at a resolution of 1 km
2
to
derive an UHI anomaly, defined here as the difference be-
tween local temperature and London mean temperature for
each day, and investigated different zones around London.
There was some evidence for acclimatisation or adaptation
to heat in London, although this was not clear for cold effects
[61•].
Health impact assessment methods can be employed to
estimate the health burden of the UHI in terms of the heat-
related mortality associated with the excess temperature due to
the UHI effect. Such studies use epidemiologically derived
relationships between temperature and mortality, along with
highly spatially resolved modelled temperature exposure data
and baseline health data to estimate the impact of the UHI
intensity on heat-related mortality. For example, the spatial
study [51•] described above went on to combine modelled
urban temperatures at 1 km
2
resolutionandanexisting
temperature-mortality relationship to determine how heat-
related mortality was affected by various factors in London.
The modelled temperature in this case was used to derive an
UHI anomaly based on building location compared with the
London average, rather than compared with a rural or subur-
ban reference, and the impact analysis was based on indoor air
temperatures, which are heavily modified by dwelling charac-
teristics [51•].
Another London-based analysis included projected temper-
atures and population to calculate the effects ofclimate change
on heat mortality [62]. They used a Climate Projections
Weather Generator (UCKP09) for future decades, which sim-
ulates temperature projections for each 5 km
2
grid cell, and
included downscaled information on the UHI based on de-
rived relationships between land use and anthropogenic heat
flux [62]. A sensitivity analysis for adaptation to the order of 1
or 2 °C is included to demonstrate that heat-related mortality
may be reduced by 32 to 69% in the future, although this 1–
2 °C degree of adaptation is not based on empirical evidence
of the scale of adaptation we might expect in future, and which
is uncertain [63].
To directly estimate the impact on health that can be attrib-
uted to the UHI, modelling techniques can be employed to
estimate the impact of land use on temperature, and hence
on heat mortality. In a recent modelling experiment, tempera-
tures were simulated by regional climate models at high reso-
lution, with and without urban surfaces in the West Midlands,
a region of the UK, for the 2003 heat wave, and for projected
temperatures in future decades [36•]. A health impact assess-
ment was carried out for the two modelled simulations, with
and without urban land use, and the mortality results were
compared in order to quantify the role of urban surfaces in
relation to heat mortality. The experiment showed that around
half of the heat-related mortality during the heat wave period
in August 2003 in the West Midlands could be attributed to the
UHI effect, i.e. the excess heat mortality as a result of the
excess temperature due to the UHI [36•]. Projections for the
future suggested that a similar heat wave event in 2080, under
a medium climate change emission scenario, could lead to a
threefold increase in heat-related mortality [36•]. Another
study, this time based in the USA analysed the relationship
between temperature and mortality and included climate and
urbanisation projections for the future to calculate mortality
[64•]. They found that increases in minimum and mean tem-
peratures were responsible for projected increases in annual
heat-related mortality of around 50% and up to 300% by the
2050s.These types of study make a case for consideration of
the enhancement of temperature from urban surfaces when
calculating health impacts under climate change conditions
using global climate models; otherwise, the potential effects
of the UHI on health will not be fully captured.
Mitigation Techniques for Reducing the Harmful
Effects of the UHI
There are two broad types of mitigation technique for reduc-
ing the UHI effect at the city scale:those whichaim to increase
solar reflectivity, using ‘cool’or reflective materials for build-
ings and surfaces, and those which aim to increase evapotrans-
piration through increased greening and water availability.
The harmful effects of excess heat associated with the UHI
may also be mitigated through behavioural change, improved
building design and reduced anthropogenic heat emissions in
urban areas.The adoptionof heat-health warning systems [65]
tailored to urban environments could be considered to be an
alternative mitigation measure [66]. Detailed reviews on the
various techniques employed to counteract the UHI effect in
terms of temperature reduction are covered elsewhere, e.g.
[67]. Here we consider mitigation measures in the context of
reduction of negative health impacts.
Reflective or cool roofs are characterised by their ability to
reflect solar energy, and, as such, can be used as a counter-
measure to reduce the impacts of the UHI effect [68,69]. The
Curr Envir Health Rpt
heat-related health benefits from the implementation of cool or
reflective roofs and pavements can therefore be considered to
be a direct effect resulting from a reduction in local tempera-
ture. The health benefits relating to increasing urban green
space or blue space (water), however, are more complex. It
is widely understood that urban greening can have a positive
effect on reducing the UHI effect [70–72], but there may be
additional benefits of urban greening on health, through re-
duced temperature exposure, increased access to green space
(which may improve mental health and wellbeing), reductions
to air pollution and more [73•]. In Lisbon, Portugal, proximity
to urban green and blue spaces was associated with decreased
mortality for elderly populations, after adjusting for confound-
ing factors, and in the case of water bodies, the health benefit
was still seen several kilometres away [74]. The authors ac-
knowledge that it was not possible to determine whether the
health benefits resulted from reduced temperature, improved
health status of populations near green and blue spaces or from
reduced stress. Similarly, a protective effect of green space on
mortality was found for areas with low socio-economic status
in Spain [75]. Literature reviews of the evidence for the health
benefits of urban green spaces conclude that although they are
generally found to be good for health, a causal relationship is
difficult to determine, given the complexity of the relation-
ships involved [76,77•].
Green roofs are another method employed to mitigate UHI
intensity by introducing vegetation at roof level to increase
evapotranspiration. Vertical ‘green walls’can also carry out
a similar function [78]. Unlike cool roofs, which are fairly
simple in their function of reflecting solar radiation, a number
of factors determine the effectiveness of green roofs in reduc-
ing UHI intensity. The cooling potential depends on local
climate, vegetation type, density, soil depth, irrigation and
maintenance, and in some cases, the reflectivity (albedo) of
green roofs may be lower than the reflectivity of the original
roofing material [79]. A further consideration is that since the
vegetation is at roof height, there is less benefit from the
greening to be felt at ground level. There are, however, likely
to be benefits of green roofs in terms of CO
2
uptake, air pol-
lution reduction, run-off reduction, biodiversity and in insu-
lating effects in winter [80,81].
Cool roofs are considered to be a more practical, cheaper
method of UHI mitigation than green roofs [82], although
green roofs and walls can make useful contributions to a range
of health improvements. The reported health benefits of well-
designed and maintained urban green spaces make them de-
sirable to include within urban environments, whilst taking
care to minimise any potential risks, for example from urban
vectors or pollen emissions [83•]. It is worth noting that al-
though many studies investigate the potential effects of
“greening”of cities, in practice, trees and green spaces are
more often lost to urban development and infrastructure.
Whilst it is useful to quantify the benefits of adding green
space, particularly when developing and urbanising existing
green areas, we should be realistic as to the practicality of
greening large areas of our existing cities.
In this review, we do not cover the topics of building design
and modification, for example the use of external shutters or
shading to mitigate the UHI and minimise overheating im-
pacts. It is worth noting that one mitigation measure for
minimising heat-related health impacts from the UHI which
does not require physical changes to infrastructure is the im-
plementation of heat-health warning systems such as heat
wave plans [65,84,85]. These plans should acknowledge that
heat effects are likely to be more pronounced in city centres,
where residents may experience adverse health effects due to
higher temperatures compared to surrounding rural areas.
Assessing the Health Benefits of UHI Mitigation
Modelling can be used to estimate potential health benefits
and costs relating to various mitigation measures through im-
pact assessment methods. For example, benefits from reduc-
tions in UHI intensity from reflective roofs may have unin-
tended consequences in terms of increasing concentrations of
some air pollutants, depending on the method employed, for
example changes in solar reflectivity can affect local chemical
production of ozone [69]. This highlights the need for inte-
grated modelling techniques and the use of multi-criteria de-
cision analysis when considering planning and policy imple-
mentation [86]. Spatial mapping techniques may provide in-
formation on any disparity of the effectiveness of strategies
based on various demographic and socio-economic factors
[87] and make the case for actions at the local level [88].
Recent work investigating heat-related health risks and the
potential for countermeasures to the UHI highlights the im-
portance of considering the indoor environment, when many
studies focus only on reduction of outdoor temperatures [89].
Results showed that reductions in outdoor temperature do not
always reduce the indoor heat risk and that for the indoor
environment, trees, green and cool (reflective) roofs and pav-
ing may have some benefits to health, but passive cooling and
air conditioning should also be considered for risk reduction
[89]. However, the hazard reduction potential is presented
qualitatively and data on the effectiveness of air conditioning
is sparse. Air conditioning may be beneficial to health in hot
weather, but it is problematic in terms of increasing unwanted
anthropogenic heating, energy consumption and emissions of
greenhouse gases. Reliance on air conditioning may become
challenging in the event of power outages, so passive mea-
sures to provide cooling in buildings are more desirable [42].
Quantitative methods have been employed to estimate the
future health effects of climate change alongside various mit-
igation measures, e.g. using spatial and risk assessment
methods quantitatively, to show that increasing vegetation
(tree coverage) could reduce heat stress effects through
Curr Envir Health Rpt
increased evapotranspiration in a US study [90]. The use of
trees has multiple co-benefits, such as social improvements
and protection from urban flooding, although a potential
downside is increased water demand and energy demand for
maintenance. Street trees can be considered to provide ‘eco-
system services’in terms of improved human health, and are
linked with wider co-benefits, as well as potential unintended
negative effects [83•]. To maximise the benefits, care needs to
be given to design of the tree canopy, choice of species and the
need for maintenance.
Parameters in urban climate models can be adapted to sim-
ulate the effects on changes in local temperature from, for
example a change in reflectivity (albedo) of roofs [48], and
to calculate the potential number of ‘deaths avoided’by var-
ious UHI mitigation methods. This technique was carried out
for New York to investigate the impacts of mitigation on the
UHI, energy use and atmospheric chemistry, and applied to a
hybrid model to investigate the potential benefits to health
[91]. The author suggests that in mid-latitudes, cool roofs do
not modify the winter UHI, and will therefore not lead to an
increase in cold-related mortality. An increased rooftop albedo
from 0.32 to 0.90 related to around 45 avoided heat-related
deaths per year in New York City.
A study based on US metropolitan areas estimated changes
in heat-related deaths up to 2050 resulting from changes in
vegetative cover and surface albedo, and found that combina-
tions of these measures could offset 40–99% of the projected
increases due to climate change [92•]. In a related study, four
different mitigation strategies were assessed as to their impact
on emergency service calls, with increased albedo being
highlighted as the most effective strategy in a model for
Arizona, USA [93]. In Melbourne, Australia, urban climate
modelling of ten urban vegetation schemes for current and
future climates was carried out to investigate the effect on
heat-related mortality. The study found decreased temperature
and related mortality with greening simulations; however, the
scale of greening in the central business district would have to
be reasonably substantial to achieve the desired health benefits
(reductions in mortality from 5 to 28% with an increase in
vegetation cover from 15 to 33%) [94].
Impact modelling, incorporating environmental, social and
demographic information, is essential as a tool for assessing
potential benefits of UHI interventions, but it is difficult to
validate the estimated impacts against observed impacts. A
system-based approach may be necessary to examine the full
range of impacts, benefits and costs [73•]. A US case study
highlights the complexity of designing effective UHI mitiga-
tion policies, and provides recommendations on how policy
makers can optimise performance by clearly identifying an
endpoint and integrating scientific and location specific infor-
mation to overcome existing limitations [95•]. Specific end-
points should be determined from the start (e.g. reduce heat-
related mortality) rather than be related to the intervention
(e.g. plant a certain number of trees) so that success can be
driven by a better understanding of the desired goal.
Conclusions
There is a wealth of existing research on the UHI phenome-
non, the impact of heat and climate change on health and the
use of building and urban planning to make our cities more
healthy and sustainable. This review has only focused on re-
cent literature which aims to quantitatively assess the heat-
related health impacts of the UHI effect, and how these im-
pacts may be avoided through various mitigation techniques.
We identified numerous spatial mapping studies which are
intended to help local authorities and public health practi-
tioners to identify vulnerable populations. However, in order
for this type of work to prove useful, close collaboration be-
tween researchers and policy-makers is essential [96].
Quantification of the UHI impact on health is necessary to
increase the understanding of policy makers of the present
and future risks to health of urban populations, particularly
in the context of climate change. Care should be taken to
consider multiple exposures in urban environments, which
may compound or modify the direct impacts of heat on health;
air pollution is a problem in many cities, and should be con-
sidered alongside the UHI effect as a hazard to urban health.
The work presented here shows that when projecting future
heat impacts, omitting the additional temperature increase as-
sociated with the UHI—not often characterised in global
models—may lead to underestimations of health effects. We
have mainly focused on heat-related health impacts, but more
research on the winter-time UHI is required to ensure that
implementation of planning policy minimises risks in both
cold and warm seasons.
We reviewed the most commonly implemented mitigation
measures and studies which aimed to quantify the potential
health benefits of a range of interventions. This has highlight-
ed again the multiple factors at play, and the need to consider
unintended consequences and benefits to health of policies
designed to protect against the UHI. The assessment of im-
pacts of mitigation measures should also highlight risks, so as
to prevent unintended negative effects, particularly in rapidly
urbanising countries.
The current quantity of research on the link between envi-
ronment and health and wellbeing can provide fundamental
evidence of the health benefits we may experience through
careful planning and design of our urban spaces. The public
health and environmental community should continue to work
together to promote measures which provide co-benefits in
terms of health, the environment and the economy, for exam-
ple through cleaner energy, active travel or centralised trans-
port initiatives, all of which are particularly relevant to urban
environments. With a growing, ageing and more urbanised
Curr Envir Health Rpt
population expected in most parts of the world, the develop-
ment of healthy, sustainable cities, based on sound scientific
evidence, should be considered a priority for improved public
health and wellbeing.
Acknowledgements The research was partly funded by the National
Institute for Health Research Health Protection Research Unit (NIHR
HPRU) in Environmental Change and Health at the London School of
Hygiene and Tropical Medicine in partnership with Public Health
England (PHE) and in collaboration with the University of Exeter,
University College London and the Met Office. The views expressed
are those of the author(s) and not necessarily those of the NHS, the
NIHR, the Department of Health or Public Health England.
Compliance with Ethical Standards
Conflict of Interest Clare Heaviside, Helen Macintyre and Sotiris
Vardoulakis declare that they have no conflict of interest.
Human and Animal Rights and Informed Consent This article does
not contain any studies with human or animal subjects performed by any
of the authors.
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