Abstract-The rapid development in urban areas, especially in
the central business district can result a number of consequences related to urbanheatisland (UHI), as it increases both the surface albedo and anthropogenic heat which lead to rise the temperature in the certain areas. This research aims to investigate existing actions and determine possible strategies for mitigating UHI, a case study of Surabaya, Indonesia. Qualitative method using triangulation analysis was used, as well as document review and stakeholder interview to recommend strategies for mitigating the UHI effect. The city development document is being used as document review. Furthermore, Department of Public Works, Planning and Development Agency and experts in urban environment and urban development were the stakeholders. The results of this research can be used as a baseline study for more understanding and addressing the UHI effects in Surabaya and other cities. The result shows that despite lack of understanding to the concept of UHI, municipality of Surabaya has been implemented several strategies for mitigating UHI effects, such as increasing provision of green space, reducing electricity consumption and replacing asphalt with cool pavement. Comprehensive approaches to the integration of stakeholders are needed to contrive and implement the strategies, as well as developing more plans and programs for mitigating the UHI effects. The strategies should be incorporated with the urban environmental issues, since it`s all substantial aspect of sustainable city development and related to UHI.
Abstract A shift in development towards the outskirts of urban areas changes the characteristics of the region and can ultimately lead to urban disparities in economic and social terms. The current study has tried to divide the study area covers the areas of surrounding Surabaya as urban, peri urban and rural areas with reference to three time periods (2008, 2009 and 2010) and shows that the typology in the study area changes each year. Furthermore, based on the theil index analysis, using a number of pre-prosperous household for social disparity and per capita GDP (Gross Domestic Product) for economic disparity shows that urban and peri urban areas have medium and high level of social and economic disparity compare with rural area which have low levels of disparity. Through multivariate correlation analysis can be seen that the health center distance, electricity and water users effecting the social disparity. Moreover, the financial, industrial, electricity, trade, construction, transportation, agriculture, and mining sector's productivity have a significant relationship with the economic disparity. Health facilities, water and electricity improvement strategies to be followed for reducing the social disparity. Electricity improvement, water, services sector, transportation infrastructure, and industrial development to reduce the economic disparity .
A number of studies, including observational, modelling, or both, focusing on the micro to the meso-scale, have investigated the e ﬀ ec- tiveness of using diﬀerent mitigation strategies to reduce the UHI in various cities. These strategies include increasing urban vegetation (Bowler et al., 2010; Coutts et al., 2016; Fallmann et al., 2013; Oliveira et al., 2011; Rizwan et al., 2008); use of water bodies (Hathway and Sharples, 2012; Theeuwes et al., 2013; Žuvela-Aloise et al., 2016) and changing the size and geometry of urban infrastructures (Ali-Toudert and Mayer, 2007; Middel et al., 2014). Adding more urban trees, parks, gardens, wetlands, and green roofs within urban areas, is generally referred to as the implementation of Green Infrastructure. The GI strategy is generally regarded as a sustainable strategy in mitigating UHI eﬀects due to their multiple functionality and beneﬁts for the urban environment such as increasing biodiversity and improving air quality in urban areas (Akbari et al., 2001). Initially, GI was de ﬁ ned as ﬂoodways, wetlands and parks, which provide water inﬁltration and ﬂood control facilities (McMahon and Benedict, 2000). More recently, the de ﬁ nition has been expanded to include a variety of environmental and sustainability goals through a network of natural and planted ve- getation such as street trees, parklands, rain gardens, community gar- dens, wetlands, green and cool roofs, and green walls (Foster et al., 2011). However, there is limited information about the potential of GI in mitigating UHI eﬀects particularly during heatwaves when diﬀerent GI scenarios are applied at the city scale. In addition, there is a pressing need to examine to what extent these mitigation strategies should be implemented to obtain substantial cooling beneﬁts to mitigate UHI ef- fects during heatwaves.
The rapid urbanization of Chinese cities has resulted in significant effects to the urban environment and to urban ecological networks. Zhengzhou city, the capital city of Henan province in central China, is characterized by a warm climate and four distinctive seasons, with a dry spring, and a hot and rainy summer. Based on satellite images, we analyzed land surface temperature (LST) and prepared a further assessment. Using LST data, we analyzed the urbanheatisland (UHI) and its relationship to green space, in order to make suggestions for future urban planning. The results show that urbanheatisland exists in Zhengzhou city Central Urban area. The mean land surface temperature (MLST) difference between urban and non-urban is significant. In addition, the urban green space reveals a negative relationship with LST. To conclude, we discuss the role of green space in mitigatingurbanheatisland, and propose some greenway related strategies for urban landscape planning in Zhengzhou city.
List of Tables
List of Tables
Tab. 1: Percentage of urban population exposed to air pollutants from 2001-2011 (Guerreiro, de Leeuw, & Foltescu 2013) ............................................................................. 26 Tab. 2: Initial concentrations as used within the box model ............................................... 38 Tab. 3: Urban parameter table for input to the urban parameterization scheme. Parameters are derived for the three CORINE based urban classes: commercial (33), high density (32) and low density residential (31). The lower part of the table is only valid for the BEP by representing the distribution of the buildings in height and street characteristics for each class (changed from Chen 2011) ......................................................................................... 54 Tab. 4: Sky View Factors calculated from building height H and road width W according to the formula of Oke (1982) ............................................................................................... 55 Tab. 5: Modelling setup used for meteorological part according to Skamarock et al. (2005) ............................................................................................................................................. 58 Tab. 6: Most important parameters and schemes added to the modelling setup for WRF- Chem .................................................................................................................................... 63 Tab. 7: SNAP level 1 source categories 1 to 10 classified by the emission source ............ 68 Tab. 8: Measurement stations used for evaluation of the urbanized WRF-Chem run ........ 72 Tab. 9 Important meteorological features of urban and rural environments, presented as an average for the modelling period Aug 11 to Aug 17 2003 .................................................. 84 Tab. 10 Atmospheric composition of urban and rural
Our study in Hanoi, Vietnam focuses on the urban tree species African mahogany (Khaya senegalensis) and its current and past growth in urban and rural areas. Af- rican mahogany was introduced to Hanoi; it is native in Africa and occurs along a broad range from Western Af- rica to Central Africa to Eastern Africa. It is one of the most important timber species in Africa, used e.g. for furniture, railroads and boats. Trees are growing to a maximum height of 30 m (Gaoue and Ticktin 2007). Due to its origin, African mahogany is adapted to moist regions with high rainfall though due to its deep root system it is very drought resistant. African mahogany is a common urban tree species worldwide, especially in tropical and subtropical regions such as Vietnam. Hanoi, with a population of 6.5 million inhabitants the second largest city of Vietnam, will also be affected most se- verely by climate change due to increased temperatures and precipitation levels (IPCC 2001; Schmidt-Thomé et al. 2015). This study analyzed the growth of a common urban and forest tree species in a subtropical city, highly affected by climate change. The results show how urban trees will be influenced by the urbanheatisland effect and climate change, helping to find common and prac- tical solutions for mitigation measures to climate change with vital and benefitting green infrastructure. The underlying research questions of this study are:
With this aim, a complete three-dimensional atmospheric modelling of the 2003 heat wave (see Step 2 in Fig. 1) is carried out with the Meso-NH non-hydrostatic model (Lafore et al., 1998). The 10th of August 2003 is selected as a reference real case, this being a sunny day with low winds of the 2003 heat wave according to the previous modelling exercises performed by Kounkou-Arnaud et al. (2013) and de Munck et al. (2013). The numerical set-up is time-computing consuming but makes possible to take into account explicitly the retroactions of surface fluxes on the low atmosphere. This reference day of heat wave is consequently run for the today city as well as for each urban expansion scenario. Indeed, the low atmosphere is influ- enced in different way according to the size, shape, and other characteristics of the city coming from the studied scenarios. The Meso-NH outputs, required to force TEB, are extracted and stored with a one-hour time step. One single atmospheric level is needed; it is taken 30 m above the top of the urban canopy. These meteorological conditions are then modified and adapted to correspond to different intensities of heat waves. First, the temperature fields provided by Meso-NH are linearly corrected in order to fit the middle value of T X of each intensity class, i.e. 34, 38, 42, and 46 ° C, respectively (see Step 3 in
San Antonio, Texas
San Antonio is an excellent choice to study the UHI, because it is “one of the fastest growing metropolitan areas in the USA” (Kreuter et al. 2001). The growth of the San Antonio urban area has been mainly symmetrical over the past 70 years. However, there has been a slight favor of growth on the north and northwest sides seen in figure 1 when compared to the original city limits. Consequently, stations on both the north and south side of the city were chosen to observe changes caused by the varying spread of urbanization. If there is a major difference, the northern station, San Antonio International Airport, should have a stronger UHI signal than the southern airport.
In most developing countries, capital city has been facing environmental problem such as urbanization, in which infrastructure development has been very fast that replaced open space area. The objectives of the research were to analysis land use/land cover and surface temperature changes of Jakarta for the period of 2000 - 2012. Result showed that during 12 years, 49.7% of green open space was converted into other land uses, especially build-up areas. This caused the increase of surface temperature and created UrbanHeatIsland (UHI) phenomenon in Jakarta. Almost all of Jakarta area has high surface temperature, however, some areas with green open space indicated has lower surface temperature. In comparison to build-up areas, surface temperature of green open space was lower of about 3.2ͼC. This fact revealed the effectiveness of urban forest in lowering surface temperature. Other mitigation action of UHI is an idea to reduce air stagnation of air masses by developing corridors that can throw and dilute air pollutants into the coastal and sea area.
Jenerette GD, Harlan SL, Stefanov WL, Martin CA. 2011. Ecosystem services and urbanheat riskscape
moderation: water, green spaces, and social inequality in Phoenix, USA. Ecological Applications 21:2637- ode a o : wa e , g ee spaces, a d soc a equa y oe , US . cological pplications : 637 2651.
Due to the expected increase in the number of hot days and heat waves, it is anticipated that demand for air conditioning will increase. However, an increase in the use of air conditioners produces additional heat outside buildings and generates more greenhouse gases. Therefore, passive measures to provide cool spaces should be considered first – building designs that keep rooms cool via insulation (thick and well- designed walls, small windows, double glazing and the correct choice of materials) or blends and public space providing shade and natural ventilation. However, in the event that active cooling of building continues to be necessary, the most energy efficient air condition systems should be used and promoted through the Eco labeling Directive (EC, 2009)
The seasonal variation of the UHI as well as the NDVI is shown in Figure 8 . The UHI is positive for most of the year, implying a higher temperature in the urban core than the surrounding. UHI with a maximum amplitude of 3.1 C during the month of June (DOY 129). During winter days, however, the urban core becomes cooler than the rural zone form- ing thus an UHS. This reversal in the sign of the UHI is due in large part to 2 physical phenomena—albedo and evaporation. During the winter, in addition to high albedo in the urban core, the soils are exposed and precipitation water evaporates at potential rates, thus exacerbating the cooling compared to rural zones, in which transpiration is limited by low tem- peratures, thus shunting most of the absorbed energy into sensible heating. These results are consistent with previous urban studies over other arid and semi-arid regions, which showed that urban areas exhibit a rela- tively weak UHI (Bounoua et al. 2009 ), and some- times even a heat sink when evaporation is important (Shepherd 2006 ). On the other hand, the seasonal variation of NDVI is negative year-around, implying that the rural zone is always greener than the urban core. However, within this paradigm the increase in vegetation density in the rural zone during the grow- ing season results in largest NDVI differences and
complex geometric structure of urban areas [ 19 ].
4. Recent studies
Both deterministic and stochastic models are broadly devel- oped to implement the mentioned UHI study aims. These models are mainly supported with large datasets obtained from local weather stations, mobile measurement stations, and satellite thermal imagery. Airﬂow (i.e. Meso and micro-scale CFD) and energy balanced (i.e. UCM and BEM) models applied in different scales are amongst deterministic approaches. In many scenarios, a multi-scale model combined with airﬂow and energy balanced models is developed to enhance the accuracy of the simulation. On the other hand, statistical models such as artiﬁcial neural network (ANN) and regression methods are widely implemented to correlate the complex and large scale characteristic of a city to the UHI.
After running simulations for Oxford Street canyons previously identified, results were extracted from ENVI-met in the form of graphical illustrations and numerical excel files from the Receptors within both canyons. Street 2 (S2) represents Oxford Street while Street 1 (S1) represents Regent’s Street which intersects S1. The different vegetation and albedo strategies were applied to determine which intervention(s) are more appropriate to be used within the case study canyons to improve pedestrians’ thermal comfort. Thus, PET, PMV, Predicted Percentage of Dissatisfied (PPD) have been the focus of the study. Further analysis is undertaken to explore how Ta, Tmrt, Surface Temperature (Ts) Wind Speed (Ws) and Relative Humidity (RH) influence pedestrians’ thermal comfort (PTC).
Climatic data provide information on the atmospheric characteristics of a given area and their effects on human activities. On attempting to conduct reliable climate studies, the first requirement is to obtain homogeneous data series. A climatic time series is said to be homogeneous if the na- ture of the changes occurring in it is only meteorological or climatic (Conrad and Pollack, 1962). The inhomogeneities shown by time series may be of two types: sharp, caused especially by the relocation of measuring instruments or weather stations, and gradual, such as the progressive changes occurring around the weather station that generates the data. In this case, an outstanding feature is urban heating since, among other factors, the growth of any city leads to alterations in the measurement of a series of climatic variables, among them temperature.
Scholars have conducted numerous studies on the relationship of temperature and respiratory diseases. The admission rate of patients (>75 years old) with respiratory diseases increased by 3% with every 1 °C above the threshold temperature (the maximum daily average temperature = 29.5 °C) (7). The daily average air temperature is in a V-shaped correlation with the emergency visits for respiratory diseases. When the daily average air temperature is lower/higher than the optimal temperature, the excess risk of emergency visits for respiratory diseases is 3.75%/1.54% of the total population with every 1 °C above/below the daily average air temperature, respectively (8). However, high temperature and heat waves have the most serious impact on human health. The incidence of upper respiratory infection at the Summer Solstice reaches 56.3 people/d (9).
heat flux, Q E is the turbulent latent heat flux, and ∆Q S is the net heat storage flux associated with heating/cooling
of this mass. So, in principle, urban climate is driven by the urban SEB and radiation balance. Each energy balance term will be altered in the urban environment and contribute to the formation of the UrbanHeatIsland effect (UHI). Urban surfaces, compared to vegetation and other natural ground cover, reflect less radiation back to the atmosphere. They instead absorb and store more of it, which raises the area's temperature. Thermal storage increases in cities in part due to the lower solar reflectance of urban surfaces, but it is also influenced by the thermal properties of construction materials and urban geometry. Urban geometry can cause some short-wave radiation - particularly within an urban canyon - to be reflected on nearby surfaces, such as building walls, where it is absorbed rather than escaping into the atmosphere. Similarly, urban geometry can impede the release of long-wave, or infrared, radiation into the atmosphere at night. Particularly densely built areas, with a low sky view factor, cannot easily release long-wave radiation to the cooler, open sky, and this trapped heat contributes to the urbanheatisland. Urban areas tend to have less evapotranspiration relative to natural landscapes, because cities retain little moisture. This reduced moisture in built up areas leads to dry, impervious urban infrastructure reaching very high surface temperatures, which contributes to higher air temperatures. An additional term that must be considered in the urban setting is the heat added by human activities. It can come from a variety of sources and is estimated by totaling all the energy used for heating and cooling, running appliances, transportation, and industrial processes.
Climate Science and Urban Design – a Historical and Comparative Study funded by the ESRC under grant RES 062 23 2134
Within the Dutch Climate changes Spatial Planning Programme and the Knowledge for Climate Research Programme, a start was made with data gathering and exploration of these to estimate urban meteorology and climatology in the Netherlands (Van Hove et al, 2010, 2011). An up-to-date assessment of the magnitude of the current UHI-intensity in urban areas in the Netherlands has been made. The underlying question is whether thermal comfort already is or will become a critical issue in the next decades. The assessment was based on results from meteorological observations reported in the literature with particular focus on assessed relationships between maximum nocturnal UHI intensity (UHI max ) and city features, such as city size and urban configuration and structure. Also results from recent meteorological observations in the urban canopy in Rotterdam and Arnhem have been used. Furthermore, historical datasets for 19 towns and cities provided by hobby meteorologists have been analyzed to obtain a more nationwide coverage. The results of these pilot studies resulted also into the initiation of the Dutch national research programme ‘Climate-Proof Cities’’ (Theme 4, KfC, 2010- 2014), which main aim is to develop effective adaptation strategies and measures to mitigate future climate impacts on the urban environment.
Assistant Professor, Dept. of Civil Engineering, Viswajyothi College of Engineering and Technology, Kerala, India ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Urbanisation is taking place at a faster rate in Kerala. As per the demographic studies, Trivandrum is one of the high density districts when compared to the neighboring districts within the State. One of the most general consequences of urbanisation is the change in micro climatic variables such as temperature, humidity, near surface winds. The present study deals with the identification of urbanized area using landuse map and estimation of land surface temperature in Trivandrum district, Kerala using Landsat-7 ETM+ satellite data for years 1990, 2005. The urban areas showed a higher temperature when compared to adjacent rural areas thus establishing urbanheatisland in Trivandrum. Satellite imageries can be used as a good source to find the temperature at all the points on the land surface rather than interpolating the temperature of an area from datas available from limited number of monitoring stations.
Trenberth KE, Jones PD, Ambenje P, Bojariu R, Easterling D, Klein Tank A, Parker D, Rahimzadeh F, Renwick JA, Rusticucci M, Soden B, Zhai P. 2007. Observations: Surface and atmospheric climate change. In Climate Change 2007: The Physics Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds). Cambridge University Press: Cambridge, New York.IPCC 2007, pág.8 Lowry, W.P., 1977: Empirical estimation of urbaneffects on climate: A problem analysis.