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Methods and Techniques for Integrated Mesoscale and Microscale Analysis of Urban Thermal Behavior:

The Case of Bari (Italy)

Claudia Ceppi1, Mariella De Fino1, Giovanna Mangialardi2, Simona Erario3, and Francesco Selicato2

1 DICATECh-Technical University of Bari, Italy {mariella.defino,claudia.ceppi}@poliba.it

2 DICAR- Technical University of Bari, Italy ing.mangialardi@gmail.com, francesco.selicato@poliba.it

3 Independent Researcher erariosimona@libero.it

Abstract. Within the general study of urban heat islands, some specific aspects were investigated in the city of Bari, South Italy, where the analyzes were car-ried out at two different scales, in order to explore the thermal patterns of all the areas including public housing complexes. In fact, it was considered that those are among the most vulnerable to urban and building decay, also due to poor original environmental and constructional quality, so that improvement actions at different decision-making levels are highly desirable. Specifically, starting from a GIS-based analysis of the overall urban area at the mesoscale, through some representative parameters and their relationships with the land surface temperatures, the assessment was further carried out at the microscale, which suggested retrofitting strategies on the buildings, in order to address both district heat mitigation and envelope energy efficiency.

Keywords: urban climate alteration, surface temperature, multi-scale approach, building energy saving.

1 Introduction

The urban heat island (UHI) and the climate anomalies in urban areas result from climate modification, climate change and urban growth. In particular, the UHI de-scribes the influence of urban surfaces on temperature patterns in urban areas as op-posed to surrounding areas [1, 2]. In general, the main effects of climate alteration are: damaging for the health of the inhabitants, worsening of outdoor and indoor comfort conditions and increase of global energy consumptions [3].

In literature, two main layers have been recognized to address the study of the at-mospheric urban heat island and, thus, of the thermal behaviour: the Urban Canopy Layer (UCL) and the Urban Boundary Layer (UBL). The UCL concerns the urban atmosphere extending upwards from the surface to approximately the mean building height, while the UBL is the layer above the UCL that is influenced by the underlying urban surface [4]. Similarly, the thermal behaviour under canopy can and should be

Methods and Techniques for Integrated Mesoscale and Microscale Analysis 415

broken down into different scales of analysis, that, according to Oke (2004), have been taking into account herein: the mesoscale and the microscale.

The mesoscale is commonly opposed to regional scales and it concerns the study of the whole urban area. Differently, the microscale, namely the district scale, is referred to specific objects, i.e. a building, a road, with dimension ranging from one meter to hundreds of meters, which can influence the microclimate due to their proper thermal properties (emissivity, reflectivity, thermal inertia, ...).

The choice of the multi-scale approach is motivated by the strict interrelation be-tween the different levels of analysis, although they require different approaches and different methods. In fact, the environmental conditions can affect the thermal beha-viour of the buildings, whereas building characteristics, namely envelope surfaces rather than shape and structure, can affect the local thermal behaviour (the terms mesoscale, local and microscale scale are used according to[5]).

It is acknowledged that there are close relationships among global climate, local climate, urban planning, urban morphology and building typology. Both global and local climates affect urban planning and morphology and, thus, outdoor and indoor comfort and building energy consumption, since climatic variables such as solar ra-diation, air temperature and wind, combined with surface/volume ratio, height/distance ratio, natural shading distribution, are vital psychological and func-tional components of a place. Similarly, the interaction of the building thermal behav-iour, due to surface characteristics, construction components and technological facili-ties with the local climate is relevant. For instance, it is recognized that a major threat to urban heat island and climate anomalies within the urban area is constituted by heat waves. Besides, the cooling loads of the buildings, which are strictly connected to the optical properties of the finishing materials and to the thermal performances of the envelope, is considered one of the primary causes of higher energy consumption and, thus, one of the factors that most influence the climate behavior at the microscale.

The urban environment is therefore faced with a challenge that requires two levels of sensitivity to understand the individual parts and the whole system [6]. On the one hand, the urban planning at the mesoscale can determine the morphology and, on the other hand, the building design of technical and construction characteristics at the microscale can affect the urban climate. Both levels interact and combine to deter-mine the regional climate and relative global consequences, besides affecting the fulfilment of residents’ needs. Therefore, in order to analyze those phenomena, the residential complexes of public housing have been taken into account, within the city. Those are considered the most vulnerable to the phenomenon of heat waves, also due to poor original environmental and constructional quality. Moreover, since they are generally owned and managed by public bodies, they might more easily undergo coordinated and integrated improvement measures.

1.1 Methodology

To assess the thermal behaviour at the urban scale, remote sensing data is used de-rived by ASTER VNIR (Advanced Spaceborne Thermal Emission and Reflection Radiometer- Visible and Near Infrared) images [7]. In particular, the land surface temperature (LST) is considered as derived data. Despite the surface temperature and the air temperature are distinct, in terms of investigated areas and characteristics,

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these are related. The term surface UHI is used to distinguish the measurements obtained by the remote sensor in alternative to air temperature.

The advantage of using such data is the ability to study large areas, which allows to analyse the emission characteristics of the surfaces diversified by materials, namely colours and finishing, and thus to identify heterogeneous thermal behavioural patterns in the urban area [2].

Based on the preliminary assessment, a representative neighbourhood was further analysed at the urban and building scales. Specifically, urban materials/surfaces were mapped, in terms of solar reflectivity and thermal emissivity, and investigated by infrared thermography, in order to detect the temperature distribution and identify the most critical situations with regard to the heat island effect. Then, building envelope components were assessed, in terms of thermal transmittance compared with norma-tive thresholds, in order to define their influence on the heating and cooling energy demand.

Based on the overall results, some retrofitting strategies were proposed for those cases, where both surface properties and component performances were found poor, in order to merge heat island mitigation strategies and energy saving solutions, according to a multi-scale approach.

1.2 The Case Study

The case study is the city of Bari, Apulia Region, located in Southern Italy. The city has been thoroughly analyzed within a three-year strategic research

project, funded by Apulia Region and European Union and concluded in 2013. The ECOURB project could achieve some interesting results about the assessment of thermal patterns of the city. The present work moves from those results in order to integrate them according to the abovementioned different scales and approaches.

2 The Meso-Scale (Urban) Framework

The meso-scale analysis allows to investigate the relationship between the land sur-face temperature and the features of the urban settlement. The use of the LST is wide-ly recognize as indicator of the overall thermal pattern and used in conjunction with indicators, such as land cover, land use, vegetation index, urban morphology and others [2, 6, 8-12]. In fact, the LST is an indicator to assess the effects of surface ra-diative proprieties, energy exchange, internal climate of buildings and human comfort in the cities [11, 13].

Thirty-two areas within the metropolitan area of Bari have been examined in order to recognize their thermal pattern. These areas consist of residential complexes of social housing with public ownership and variously distributed within the city.

Those complexes are hubs, with variable extension, that feature most Italian cities and that might be integrated, on the boundaries or isolated from the consolidated ur-ban area. They show very peculiar morphological configuration with clear settlement connotation, particularly in the applications of the early XX century, compared with the 50’s and 60’s and, even more, with the recent cases. They give evidence of specif-ic construction and technical traditions throughout the years. They have social and

Methods and Techniques for Integrated Mesoscale and Microscale Analysis 417

political relevance, as they were designed and built as whole neighborhoods (“167 areas”, as designated by the law n.167/1962 before, and “PEEP areas”, so defined by the law n. 865/72 afterwards) to meet the housing needs – not without contradictions and failures. Finally, the debate about public housing is challenging within the current policies of urban development, for the fulfillment of the diffuse housing demand of a wide social class and the current use and management requirement of the built heritage.

In the light of the abovementioned aspects, social housing complexes were selected for the present study, also considering their vulnerability to the heat island phenome-non [23]and the possibility to implement their improvement policies directly by the government bodies, owning either/or managing the heritage, with relative positive impacts on the urban areas.

The areas mainly vary for year of construction, ranging from 1903 and 2007, and urban morphology of the districts, in which they are included.

The urban morphology represents an indicator of some key features of the urban space, such as geometry, density, building typology and functions. Moreover, its rela-tion to the spatial pattern of surface temperature within the urban area has been prov-en [4, 9, 14]. According to the classification of the city of Bari in nine morphology classes [7], the relationship between the district and the urban morphology has been assessed in a GIS environment.

Fig. 1. Thermal image of the city of Bari acquired on 07.06.2001, which has been superim-posed on the distribution of public housing complex

The urban morphology that characterizes most of the areas can be identified as “open tissue”, as the various complexes of buildings are mostly localized in the peri-pheral areas of the city centre. It is worth mention that, for the above mentioned

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purposes of investigation, the in-depth analysis of those areas is particularly interest-ing, since they represent the border areas with respect to the phenomenon of heat islands, forming a boundary between heavily urbanized areas and suburban areas. Through spatial representation in GIS, four indicators, that are considered particular-ly descriptive of the districts in relation to their thermal behaviour, are determined. In detail, the thermal data, processed by the ASTER level 1B through the ENVI soft-ware, is related to satellite in summer period acquired on 07.06.2001.The other para-meters are the Normalized Difference Vegetation Index (NDVI), processed from the same thermal image with a resolution of 15 m, the morphometric protection index and the Sky View Factor (SVF).

The morphometric protection index is a dimensionless parameter that expresses the level of protection from the surrounding areas. With reference to urban areas, it defines the most protected areas inside the buildings and then synthesizes information such as the distance between the buildings and their relative height. It is therefore used, in the present study, as a proxy to determine the effects of sunshine on structures.

The SVF is considered a measure of the radiation geometry of a given site. It ranges from zero to one, representing totally obstructed and free spaces, respectively [15]. The different data were resampled at a resolution of 10 m and were intersected with the data related to digital mapping of the city. In particular, in order to study the parameters related to the context of the buildings, a buffer of 50 m in the surroundings of the considered buildings, belonging to various districts, was created. Following the analysis of the distribution of the various parameters in a GIS environment, it was carried out a descriptive analysis of the data obtained for each building and weighted according to the area of intersection between grid and vector data relating to individu-al buildings. Fig. 1 shows the distribution of the thermal data for the whole city of Bari.

The bivariate correlation analysis between the factors shows that the SVF is the factor best correlated with the surface temperature, reaching a value of about 0.6, while the NDVI shows an almost negligible correlation with the LST, probably due to the general lack of vegetated surfaces, replaced by impermeable surfaces. On the contrary, the morphometric protection index shows, as expected, a good inverse cor-relation with the SVF, with a well explained relatively low surface temperature report. Among the districts that have a higher variability of this parameter are the districts of Japigia and the two belonging to the neighbourhood of San Paolo

Both the sub district (named “Comparto A” and “Comparto B and C”) of San Paolo, are also those that show a greater variability of land surface temperature (ranges between 307.32-316.61 K) and a greater variability in the values of SVF and PI (ranging respectively between 0,37 and about 1 the SVF, and between 0,39 to 1,3 the PI). [Fig.2][Fig.3].This variability linked to the wider range of surface tempera-tures within the same district, and the morphological type (open tissue) has lead to the choice of the case study for microscale analysis on San Paolo area, as will be illustrated in the following paragraphs.

Methods and Techniques for Integrated Mesoscale and Microscale Analysis 419

Fig. 2. Scatter plot of the distribution of SVF for the various districts

Fig. 3. Scatter plot of the distribution of LST for the various districts

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3 The Microscale (District and Building) Framework

The microscale thermal assessment was developed for the case study of San Paolo neighborhood, in the north-west suburbs of Bari. The neighborhood is a residential area with social housing buildings that were realized since the 50’s. Specifically, two main historical construction phases occurred, resulting in the compartments CEP and PEEP, named after their funding programmes [Fig.4].

The CEP compartment, designed between 1955 and 1958, is composed of blocks of three/four storey buildings, with variable orientation. The structure is mixed, with masonry solid walls and reinforced concrete/ hollow brick slabs.

The PEEP compartment, designed from 1963, shows less fragmented layout, fea-tured by two main orientation axes. The five/six storey buildings have reinforced concrete pillars/beams/slabs structure.

Fig. 4. CEP (A) and PEEP (B-C) compartments in San Paolo neighborhood

3.1 Thermal Performances at the Urban Scale

San Paolo neighborhood was firstly investigated at the local scale. Specifically, within a selected representative area [Fig. 5], including both compartments, thematic maps were developed for albedo [Fig. 7] and emissivity [Fig. 6] of the horizontal surfaces, according to experimental values found in literature [16][17]. High albedo expresses the ability of the materials of reflecting most of the incident solar radiation during daytime and keeping the surfaces cooler, whereas high thermal emissivity allows the materials to radiate away the heat stored in the underlying structure, mainly during night time. Thus, high albedo and high thermal emissivity allow the surfaces to show high solar reflectance index (SRI) and reduce the heat transfer to the built environment.

Methods and Techniques for Integrated Mesoscale and Microscale Analysis 421

Within the case study, the emissivity is quite high, ranging from 0.9 to 0.98, whe-reas albedo varies from 0.08 to 0.3. Particularly, lowest albedo values feature the roofs that are generally finished by asphalt waterproofing membrane.

Fig. 5. Materials of horizontal surfaces

Fig. 6. Albedo of horizontal surfaces

Furthermore, IR thermography mapping of the surfaces was carried out in order to assess their thermal behaviour. IR thermography is a non destructive technique to detect the temperature distribution on a surface, based on the emitted infrared radia-tion, according to the well known equation:

q = σ ε T4 (1)

422 C. Ceppi et al.

Fig. 7. Emissivity of horizontal surfaces

where q is the hemispherical total emissive power (radiated energy per unit area, W/ m2), σ the Stefan-Boltzmann constant (5.67051 x 10-8 W/m2K4), ε the total hemis-pherical emissivity of the surface (0 < ε < 1) and T the surface absolute temperature (K). It follows that the hemispherical total emissive power q is directly related to the temperature T, once the emissivity ε is known.

Specifically, several typologies of surfaces/materials were analyzed by Avio Neo-thermo TVS-700 camera (8-14μm) in September 2012, including plastered building facades, roofs with asphalt, roads with asphalt, trees and bare soil. Thermograms were preliminary elaborated, using an average value of ε = 0,95, in order to get qualitative thermal maps [Fig.8][Fig.9].

Fig. 8. Thermal map, including plastered building facades and roofs with asphalt

Methods and Techniques for Integrated Mesoscale and Microscale Analysis 423

Fig. 9. Thermal map including roads with asphalt, trees and bare soil

Then, quantitative assessment of the surface temperatures was achieved by itera-tively correcting the emissivity for all the different materials [Tab.1]. It is worth men-tion that the correction of emissivity would generally result in a slight temperature variation of 1-2°C on average.

Table 1. Surface/Material versus Emissivity [1]

Surface/Material Emissivity (8-13 μm) Trees 0,990

Dark bare soil 0,898 Roads with asphalt 0,965 Roof with asphalt 0,897 Plastered facades 0,950

As an example, for the thermograms showed above, a grid of 10 measurement points was used for each surface/material [Tab. 2].

Table 2. Temperature values

Tmax (°C) Tmin (°C) Taverage (°C) Fig. 2 Plastered facade 26,40 25,42 25,81 Roof with asphalt 41,54 40,37 41,02 Fig. 3

Road with asphalt 38,28 35,10 36,90 Tree 28,28 24,57 26,38 Bare soil 29,50 26,28 27,76

424 C. Ceppi et al.

Results confirmed that roofs are the most critical surfaces, as they are finished by poorly reflective materials. At about 12 a.m. in a summer day, their temperature is on average up to 4°C higher that the roads and 16°C higher than close facades. The inci-dent solar radiation plays a key role in the process, as well, considering that roofs are the most exposed surfaces, typically not shaded by surrounding elements. As a refer-ence, a simulation by Ecotect of a group of 25 buildings in the area shows that, throughout the summer season, horizontal surfaces are exposed to about 475 kWh/m2 incident solar radiation against 143,203 kWh/m2 of vertical surfaces.

Thermography was also used to assess energy performances of buildings. As ex-pected, most structures show missing thermal insulation, resulting in thermal bridges, due to unprotected concrete framework mainly in PEEP compartment, as well as re-duction of wall section where heating radiators are located, both in CEP and PEEP compartments [Fig. 10].

Fig. 10. Thermal bridges due to unprotected concrete framework and heating radiators

3.2 Thermal Performances at the Building Scale

The CEP compartment was built according to the common criteria featuring the social housing complexes by INA Casa Institute in Italy, as thoroughly documented in bibli-ographic and archivist records, including the four “Handbooks of INA Casa”. Particu-larly, the handbooks were released to support design and construction of buildings belonging to the Institute and comprise guidelines and recommendations from urban planning to technical detailing.

As a consequence, with specific reference to that compartment and based on the available information and the direct investigation of the buildings, the materials and construction techniques were defined and the energy performances of building com-ponents were assessed. In detail:

Solid walls were generally made out of plastered calcarenite stone, locally called “tufo”. The thickness varied: 60cm at the ground floor, 55cm at the first floor, 50cm at the second floor, 45cm for the third floor. Sometimes, they could be composed of two outer leaves and an inner air cavity, with 43cm total thickness. Plaster was usually made out of cement or lime based mortar with stone powder added.

Basement floors were separated from the ground by a 15-20 cm thick layer of un-shaped stone blocks, with cross ventilation by ducts, and finished by concrete/gravel slab, cement mortar and cement tiles.

Methods and Techniques for Integrated Mesoscale and Microscale Analysis 425

Roofs were made out of 20-25cm slab with reinforced concrete beams and hollow clay bricks, light concrete 15% slope layer, 7-10 mm asphalt waterproof membrane and eventually cement mortar and cement tiles.

Windows were generally single glazed, with wooden frame and wooden shutters. Most frames are currently made out of aluminum, steel and PVC. A summary of construction details for the most representative components is shown in Tab.3, along with the calculated thermal transmittance - and relative threshold val-ues according to Italian codes - as well as the attenuation ratio and delay time due to the thermal inertia. The information for all the buildings of the compartment, includ-ing photographic documentation, technical drawings and envelope/plant performance details, were stored and managed by GIS platform [Fig.12].

Table 3. Thermal performances of representative envelope components

Envelope opaque components

Component Thickness

(cm) Ucalculated (W/m2K)

Uthreshold

(W/m2K) Delay

time (h) Attenuation

ratio Solid wall 50 0,99 0,4 8,89 0,1

Cavity walls 43 0,84 0,4 9,06 0,41 Roof 43 1,45 0,38 8,31 0,34

Envelope transparent components

Component Ucalculated (W/m2K)

Uthreshold

(W/m2K) Single glazed window with wooden frame and outer

wooden shutters 2,33 2,6

Single glazed window with aluminum frame and outer PVC shutters

5,8 2,6

Results show that the replacement of wooden frames with aluminum ones doubled

the thermal transmittance of the original windows. Moreover, all the traditional envelope components do not accomplish the normative thresholds. The roofs show the poorest performances, requiring a transmittance reduction of 74%, against 60% and 52% of solid and cavity walls respectively.

4 Energy Retrofitting Strategies

Based on the abovementioned assessment, some retrofitting strategies have been evaluated, with specific focus on roof components, that showed the most critical be-haviour, in terms of both surface solar reflection index and thermal component transmittance. Specifically, green roofs and cool roofs were assessed by Design Builder and Energy Plus simulations on a building-type, based on the most recurring construction envelope characteristics.

The solutions are widely acknowledged by the scientific community as highly per-forming, both for mitigation of the urban island effect [17,18,19] and for reduction of

426 C. Ceppi et al.

building energy consumptions and peak cooling demand [20,21,22]. Specifically, green roofs exploit the capability of the vegetation to absorb the solar radiation for supporting its life-cycle, including photosynthesis, evapotranspiration and respiration. Moreover, the soil layer gives an added insulation to the building roof and the water content increases the thermal inertia of the structure. Differently, cool roofs limit the heat transfer to the underlying structure, due to high reflective/ low absorbing materials, whose high thermal emissivity also allows heat dissipation when the environmental temperature drops.

The building-type is north-south oriented. It is a four storey housing complex, in-cluding 3 staircases and 24 apartments, with 70 m2 net surface. The load bearing structure is composed of 50 cm thick solid masonry walls and 25 cm thick reinforced concrete/ hollow brick slabs. Windows are single glazed and wooden framed with outer wooden shutters. HVACs include gas heating and electricity cooling. Simula-tions compared the annual heating and cooling demand before and after the interven-tions, particularly for the apartments at the upper floor, that are supposed to undergo the most significant retrofitting benefit.

Tab. 4 summarizes the simulated scenarios and relative thermal transmittance val-ues. It is worth mention that cool roof and green roof were designed to equally ac-complish the normative threshold.

Table 4. Simulation roof scenarios

Component Layers (from inside to outside) Thickness

(mm) U

(W/m2K)

Original roof

Cement plaster 15

1,45 Cast concrete (beam + slab) 300

Lightweight sloped cast concrete 100 Asphalt waterproof membrane 10

Cool roof

Cement plaster 15

0,27

Cast concrete (beam + slab) 300 Aerogel insulating board 40

Lightweight sloped cast concrete 100 Asphalt waterproof membrane 10

Lime sand render 20 White cement tiles (ρ=0,8) 30

Green roof

Cement plaster 15

0,28

Cast concrete (beam + slab) 300 EPS insulating board 20

Lightweight sloped cast concrete 100 Asphalt waterproof membrane 10

Daku FSD 80 Vegetation soil 180

Methods and Techniques for Integrated Mesoscale and Microscale Analysis 427

Table 5. summarizes the annual heating and cooling demand

Component Heating demand (kWh/m2) Cooling demand (kWh/m2) Original roof 114,24 32,78

Cool roof 101,45 21,96 Green roof 98,00 21,62

Results show that cool roof and green roof similarly address cooling energy de-

crease, about 33% saving, whereas the green roof perform slightly better, in terms of heating energy reduction, about 14% against of the cool roof. Although both solutions were designed with same thermal transmittance, it is reasonable that the green roof exploits its thermal inertia during the winter time, too.

5 Conclusion

The paper meant to highlight how meso-scale and micro-scale should interact to ad-dress mitigation strategies for climate anomalies within the city and their relative impacts on the comfort of the citizens.

Specifically, the assessment at the district level, based on the outcome of the urban relationship analyses and further specified through the qualification of the buildings, in terms of optical and thermal properties of external surfaces and energy perfor-mances of envelope components, enabled the identification of some relevant critical issues for the heat island phenomenon, namely the solar gain of the urban areas and the consumptions/emissions due to the construction and technological systems. As a result, retrofitting strategies and solutions were proposed that were validated at the building level, but can be easily replicated for a variety of cases at the compartment level, toward the sustainable requalification of the built heritage as urban planning target, with positive environmental and energy impacts both at the micro-scale and the meso-scale.

In all, along with building retrofitting, urban requalification should be based on energy quality. Since that requalification mainly concerns the government bodies, public housing complexes, which were mainly examined in the present work, can offer a valuable chance for integrated and coordinated intervention. Nevertheless, such an approach is certainly consistent with the current legislation, e.g. the Land-scape Plan of Apulia Region, where it is higly recommended and awarded by Green Certificates the development of green zones in peri-urban areas, as compensation for the consumption of soil and the contribution to the pollution increase.

Acknowledgments. The authors would like to acknowledge Rocco Rubino, Frances-co Mancini and Pasquale Balena, Technical University of Bari. Their contribution for supporting data acquisition and elaboration is much appreciated.

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