Performance Evaluation of Built Environment in Local Climate Zones

The thermal performance of a building is significantly influenced by the climate around it. It is observed that the microclimate of an urban area is notably different from that of the surrounding regions. This difference is mainly due to the variations in anthropogenic heat, built morphology and surface characteristics. The Local Climate Zone (LCZ) system, effectively classifies the urban areas concerning these climatic variations. This study comprises two sections; the first section explores the climatic differences across LCZs and the impact of urban built morphology on microclimate. For this, three different LCZs – LCZ-2, LCZ-5 and LCZ-9 (high, medium and low density respectively) were modelled within the range of values prescribed in the LCZ system and an analytical study was carried out with the help of the CFD tool – ENVIMET. To understand the influence of urban morphology features on microclimate, LCZ-2, a representative LCZ was chosen and a parametric study of variations in morphology variables was carried out. It was observed that incidence angle, surface characteristics and H/W greatly influence the microclimate. The second section of the study explores the thermal performance of the built environment across the LCZs. A typical 3-bedroom residential building was considered and thermal performance evaluation of the same in three different local climatic conditions was carried out through field measurements. It was observed that heat flux in LCZ-5 (65.5 W/m 2 ) is high compared to that of LCZ-2 (16.6 W/m 2 ) and LCZ-9 (6.04 W/m 2 ). The study points to the significance of location-specific building performance studies and design criteria.


Introduction
Considering the facts that buildings are one among the largest energy consumers (Mahdavinejad & Javanroodi, 2014) and the alarming energy crisis (Li et al., 2021), thermal performance regulation of the built environment becomes at most important.Design criteria and climatic context are the prime influencing factors of building thermal performance.The impact of climatic context on the thermal performance of buildings was been studied extensively over the last decade (Janjai & Deeyai, 2009).
Apart from the macroclimate of a region, microclimatic conditions of the region also impact the convective and radiative thermal exchanges between the building and the surrounding (Moazami et al., 2019).This study focuses on the thermal performance of the built environment in different microclimatic conditions.The study is limited to the ventilation availability (Sushanth SJ, 2019) and the solar exposure aspects of the microclimate.
The observed variations in the microclimate of urban areas are mainly due to the anthropogenic heat, built morphology and surface characteristics (Dimoudi et al., 2013).The Local Climate Zone (LCZ) system-a land classification system developed by Steward &Oke (Stewart & Oke, 2012), effectively classifies the urban areas concerning these climatic variations.In the LCZ system, regions of uniform surface cover, structure, material and human activity, are classified into 17 zones.In addition, it is observed that the urban morphology features significantly alter the microclimate (Hargreaves et al., 2017).Urban morphology features such as H/W ratio, Surface characteristics (emissivity), Built Surface Fraction (BSF), Wind incidence angle and Block staggering (the percentage area of the façade not being blocked by the neighbouring building) are studied and their influence on urban microclimate is explored.Most of the LCZ related studies are satellite-based studies or macro-level studies (Alexander & Mills, 2014;Ng, 2015;Xu et al., 2017).In this study a more precise, location-specific thermal environment in LCZ is explored, using ENVIMET which is three-dimensional microclimatic modelling software with computational fluid dynamics (CFD).The ENVIMET model has been widely accepted and validated for assessing built environments (Berardi et al., 2020;Forouzandeh, 2021).On-site field measurements were taken using calibrated HFP01 heat flux sensor.
In the case of non-commercial buildings, most of the heating happens due to solar exposure and the ventilation availability helps in cooling.This study helps in understanding the particular solar exposure and ventilation availability experienced in different zones of the urban area and the level of influence of each of the urban morphology features on them.In addition, the understanding of the thermal performance of buildings in each zone along with the microclimate experienced helps in deriving more location-specific urban and building level design criteria.

Objectives and Methodology
The study intends to explore the variations in urban microclimate and their impact on the thermal performance of the built environment.The following are the major objectives addressed.
o To evaluate microclimatic variations across Local Climate Zones.o To understand the impact of urban morphology variables on microclimate.o To evaluate the thermal performance of the built environment across Local Climate Zones.The study comprises two sections; the first section explores the climatic differences across LCZs and the impact of urban built morphology on microclimate.For this, three different LCZs -LCZ-2, LCZ-5 and LCZ-9 (high, medium and low density respectively) were modelled within the range of values prescribed in the LCZ system (Table 1) and an analytical study was carried out with the help of the CFD tool -ENVIMET.
In this paper, ENVIMET simulations were performed for a typical summer week (September 9 th to September 16 th ).The simulations were carried out for 24 hours with one hour time step for a week.The base case where simulated with (1) Wind speed at 10m was set to 0.7m/s, according to IMD, (2) Air temperature and relative humidity hourly values were obtained from the nearby meteorological station of Dehradun, (3) ENVIMET default values were used for roughness length and specific humidity.Building walls and roofs albedo were set to 0.4 and 0.3 respectively while the model"s numerical stability and the minimization of boundary effects which may affect the output data were assured by placing 10 nesting grids around the main model area.
Table 1 presents the characteristics of the chosen LCZs, where building surface fraction refers to the ratio of the building plan area to total plan area and pervious surface fraction refers to the proportion of ground surface with pervious cover which affects the surface reflectivity.To understand the influence of urban morphology features on microclimate, LCZ-2, a representative LCZ was chosen and a parametric study of variations in morphology variables (H/W ratio, Built Surface Fraction (BSF), Incidence angle, Emissivity, Block staggering) was carried out with the widely used statistical method, Response Surface Method.The second section of the study explores the thermal performance of the built environment across the LCZs.A typical 3-bedroom residential building (located on the first floor of the apartment) was considered and thermal performance evaluation of the same in three different local climatic conditions was carried out through field measurements using HFP01 heat flux sensor.The instrument, heat flux plate was setup one per wall and measurements were taken for all four directions.The sensors were placed at 5m height from ground level.This study focuses only on the heat transmission on the southern façade (brick wall with U Value 0.31).Figure 2 depicts the instrumental setup used for the thermal performance assessment.A comparative study of the thermal performance assessment is carried out to establish the impact of microclimate on the thermal performance of the built environment.Figure 1 outlines the methodology adopted for this study.

Study location
Dehradun, the state capital city of Uttarakhand, India, which lies between 78°00" to 78°10" East longitude and 30°15" to 30°25" North latitude, was chosen as the study location.Based on the "Energy conservation and building code" the city climate is classified as a composite climate (ECBC, 2017).The region experiences both extreme winters and extreme summers.The temperature of the region varies from 6 0 C to 42 0 C, average humidity 68% and wind speed 0-4.5 m/s.Hence the building design criteria should consider both the extreme conditions.This study presents the summer-time data only and the seasonal variations shall be presented in future works.

Experimental design
The first section of the paper deals with the zone variations in microclimate within the same urban area.Local Climate Zones 2, 5 and 9 representing the high, medium and low-density urban setup were considered for the microclimate analysis.Considering the mean values of the range of characteristics mentioned in Table 1, urban areas were modelled and simulated in CFD tool ENVIMET (Appendix 1).Analysis was carried out for an experimental area of 200m X 200m and with a precision of 1m grid size.The energy plus weather file for the Dehradun region was used and the analysis was carried out for the summer solstice.The microclimatic dataventilation availability and solar exposure were recorded for a time period of one week.The analysis model considered for the study is presented in figure 3.

Figure 3: LCZ morphology considered for the analytical study
The next section of the study deals with the impact of urban morphology features on urban microclimate with the help of Design of Experiments (DOE).A representative Local climate zone -LCZ-2 was considered for the same.Keeping every property of LCZ-2 within the prescribed limits, a parametric analysis of urban morphological variables is carried out using Response Surface Method (RSM) to examine their impact on microclimate (ventilation availability and solar exposure).Among the two designs available in RSM, Central Composite Design (CCD) and Box-Behnken Design (BBD), CCD is used in the present study since it has a wider scope in the application.Five independent variables of urban morphology, H/W ratio (ranging from 0.75 to 2), Emissivity (ranging from 0.3 to 0.9), Wind incidence angle (0 0 to 90 0 ), BSF (ranging from 40-70), Block staggering (ranging from 0-20) have been considered.Considering the number of factors, by using CCD, the total experiment run has been reduced from 243 to 33, saving considerable time and effort.Each of the combinations is simulated (with conditions the same as in the previous case) for ventilation availability and solar exposure in the ENVIMET tool (Appendix 2).Later, statistical analysis was carried out to understand the relative impact of each of the variables on microclimate.
The last section deals with the thermal performance of the built environment across LCZs.Similar residential buildings on the first floor of the apartment, one each in LCZ-2.LCZ-5 and LCZ-9 were considered for the analysis.Field measurements using HFP01 heat flux sensor were carried out for one week in summer.Figure 2 shows the instrumental setup used for the same.The heat flux data obtained were compared to understand the variations in thermal performance of buildings across LCZs.

Microclimatic variations across LCZs
The study focuses on the ventilation availability and the solar exposure aspects of the microclimate.The ventilation availability analysis shows that there are considerable variations in wind velocity across LCZs.The results of the analysis are presented in Table 2.The observations are made at three levels-3m, 12m and 21m representing low, mid and high levels respectively.An increase in ventilation availability is observed with respect to the increase in height of observation.The inter LCZs variations in ventilation availability show that, the higher the built density, the lower is the ventilation availability.The height-wise variations in ventilation availability show a similar trend across the LCZs.The results point to the fact that, in addition to the different design criteria adopted in each climate zone, LCZs based design criteria are required to make use of the maximum ventilation potential.LCZ-9 0.8 0.9 0.9 The solar exposure was analysed for the modelled building clusters for a typical summer week.It was observed that the LCZ-5 receives the maximum shortwave radiation compared to LCZ-2 and LCZ-9.The peak exposure was experienced around 2pm throughout the week.LCZ-9 experiences low shortwave radiations in comparison to other LCZs except for a few morning hours.When the whole week is considered, LCZ-5 experiences maximum shortwave radiation and LCZ-9 experience the least.Single day data is represented in Appendix 3 for clear understanding.The observed solar exposure data are presented in figure 4. When the long wave radiations are considered, LCZ-2 receives the maximum, followed by LCZ-5 and LCZ-9.The time of experiencing peak long wave radiation also varies with LCZs.The mutual shading effect, the surface properties and built density are a few of the major contributing parameters to the variations in solar exposure.The study further investigates the impact of urban morphology features on solar exposure and ventilation availability.

Impact of morphology features on microclimate
A parametric analysis using RSM was carried out to analyse the impact of urban morphology variables on microclimate.The coefficient of determination (R2) and percentage of variation in response (R2 adj) are used to determine the fitness of the model.A relatively high value (>90 %) is observed, confirming the model"s applicability.Figure 7 depicts microclimate variation with respect to urban morphology.It can be clearly seen that increase in incidence angle and Emissivity has a positive effect on the summer radiation, whereas increasing BSF and block staggering decreases the radiation.An interesting observation is the radiation trend with respect to the H/W ratio, which is an inverted parabola.After attaining a stable maximum value, a downward trend follows an initial positive trend.The effect of BSF, Block staggering, and incidence angle on wind speed (Figure 8) is similar to the observation in radiation.Wind speed increases linearly with respect to incidence angle, whereas a negative trend is observed for BSF and block staggering.Unlike radiation, an upward parabola is seen in the wind speed (Figure 8) for Emissivity and H/W change.Here an initial downward trend is observed and after reaching a stable minimum value, an upward trend is observed.Also from Figure 7, it can be seen that the maximum variation in the radiation is caused by block staggering and incidence angle in the studied range.The H/W ratio, block staggering and incidence angle provide a significant impact on the wind speed (Figure 8).
In order to analyse the relative effect of each parameter and their interactions on the microclimate, Pareto charts are used in the present study (Figures 5 and 6).The interaction terms which are obtained as significant to the microclimate are taken for the analysis.From figure 5, it is evident that the interaction of block staggering and Incidence angle has the most significant effect on radiation.Also, Emissivity appears to be the least influencing factor in the radiation, followed by BSF and Incidence angle interaction.Similarly, the Incidence angle has a strong impact, whereas Emissivity has an almost negligible effect on the wind speed.As it can be seen from the Pareto chart of wind speed, Figure 6, there is a considerable variation in the magnitude of the impact between each morphological feature and their interaction term.For instance, the magnitude of the interaction term of block staggering and the incidence angle factor, which has the maximum effect, has a difference of 14, with the factor having the minimum effect, the incidence angle.Whereas observing Figure 5, the standardized effect of the various parameters in radiation varies in a small range (varies from 2-6) with a very little difference.This slight difference indicates that the impact of the studied morphological features on wind speed can be more or less the same.Even though Emissivity and BSF have little effect on the wind speed, it is evident that both Emissivity and BSF interact with the incidence angle and H/W ratio, respectively.Thus a considerable impact is contributed by these variables on the wind speed.This interaction effect shows that these parameters shouldn"t be ignored while considering wind speed as a design parameter.

Thermal performance of built environment in local climate zones
Thermal performance analysis of the built environment in LCZs was carried out with the help of the HFP01 heat flux sensor.The heat flux data of the building were recorded for one week in summer.It was observed that heat flux in LCZ-5 (65.5 W/m 2 ) is high compared to that of LCZ-2 (16.6 W/m 2 ) and LCZ-9 (6.04 W/m 2 ).It is important to note that the variation trend of heat flux in different LCZs is similar to that of solar exposure.In LCZ-2 due to the high density, mutual shading happens and hence the solar exposure is reduced, this, in turn, impacts the thermal performance as well.In the case of LCZ-5, though the ventilation availability is more than that of LCZ-2, the solar exposure is too high and the heat flux is higher compared to LCZ-2 and LCZ-9.Whereas in the case of LCZ-9, the ventilation availability is high (in addition to the other morphology features) and thus cooling is higher, hence the heat flux is observed to be low.The time of experiencing peak heat flux is also similar to that of solar exposure.In the summer season, the built environment in LCZ-2 and LCZ-9 performs better thermally than LCZ-5.

Conclusion
Performance evaluation of the built environment shows considerable variations across LCZs.Microclimate plays a key role in this difference.Controlling the microclimate can help in regulating the building thermal performance or regulating the design criteria according to microclimate can improve the thermal performance.Further research in this regard is much needed.The parametric study on the impact of urban morphology variables on microclimate shows that incidence angle, surface characteristics and H/W ratio greatly influence the microclimate.This indicates that regulating these morphology variables helps in improving microclimate and building thermal performance.Further, the impact of seasonal variations as well needs to be addressed.

Figure 5 :Figure 6 :
Figure 5: Relative impact of morphology variables on solar exposure

Figure 7 :Figure 8 :
Figure 7: Impact of morphology variables on radiation exposure