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Simulating the CO2 reduction caused by decreasing the air conditioning load in an urban area
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Simulating the CO2 reduction caused by decreasing the air conditioning load in an urban area Yujiro Hirano ∗ , Tsuyoshi Fujita Center for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, Japan
a r t i c l e
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Article history: Received 28 February 2015 Received in revised form 30 May 2015 Accepted 11 June 2015 Available online xxx Keywords: Urban heat island Energy saving Air-conditioning load simulation Urban thermal environment CO2 reduction
a b s t r a c t In this paper, measures such as planting urban greenery and using high-albedo paint to mitigate the urban heat-island effect, conserve energy, and reduce CO2 emissions were assessed. As a typical energy-saving method for buildings, reducing the internal heat sources and increasing the insulation are also assessed. We used a coupled urban canopy and building energy model to predict the heat loads of buildings in city districts, the effects of air-conditioning on energy consumption, and air temperature changes. In this model, a vertical one-dimensional local atmospheric model is coupled with an air-conditioning load calculation model for buildings, making it possible to assess the interaction between anthropogenic heat release due to air-conditioning usage and the outside thermal environment. In this study, we selected a target study region in the city of Kawasaki, Japan. When typical city districts were assessed, planting greenery or increasing albedo achieved temperature reductions of 0.6–1.0 ◦ C and 0.1–0.5 ◦ C, respectively, and energy savings of 40–80 and 70–90 kJ/m2 /day (per unit floor area) on a typical summer day. The results from the large-scale assessment show that urban greening or albedo increases achieved the highest energy savings, of up to 400 t-CO2 /day, in the entire target study region. © 2015 Elsevier B.V. All rights reserved.
1. Introduction The conservation of energy to mitigate global warming is an important topic of study. Of particular concern is the need to offset the ever-increasing amounts of energy used for air-conditioning purposes in urban regions. In urban areas, a significant impact of urbanization is the rise in temperature due to artificial land cover, anthropogenic heat, and so on (i.e., urban heat islands) [1–3]. A worsening urban heat-island effect not only makes city living less comfortable during the summer, but is also implicated in higher peak electrical loads and energy consumed for air-conditioning purposes [2–7]. Consequently, improving the thermal environment of urban regions is important for countering both global warming and the urban heat-island effect. Various studies have evaluated the effects of a heat island on the energy consumption of a number of cities, including Tokyo [8], Athens [9–11], London [12–14], and Taipei [15]. In recent years, sufficient knowledge of urban heat islands has been accumulated, with the next step being to mitigate their negative impacts. In fact, in recent years, proposals for mitigation measures such as urban greening, urban albedo increases, and permeable pavement,
∗ Corresponding author. E-mail address: [email protected] (Y. Hirano).
as well as reports on the investigation of their mitigation effects, are becoming more common. In particular, many studies evaluating the mitigation of heat-island effects have been conducted in the United States and Canada [16–24]. However, since the results of these studies depend on various factors, such as local climatic conditions, building styles, and lifestyles, their results are still insufficient for widespread application. More specifically, few studies have evaluated cases in Japan, where the summers are hot and humid. Hirano and Fujita [8] developed a new method to evaluate the heat-island impact on energy consumption by taking into consideration spatial and temporal distributions of both energy consumption and air temperature. However, since this method is based on the sensitivity of energy consumption to ambient temperatures, the interaction effects between anthropogenic heat release due to air-conditioning use, and the outside thermal environment cannot be expressed. In addition, only the effects of changes in outdoor temperature were estimated, and it was not possible to accurately evaluate the effects of countermeasures accompanying changes in building surface temperatures (e.g., cool roofs [25–34]). In recent years, many studies have reported the effects of urban geometry on temperature, air-flow, and radiation conditions inside the urban canopies [35–40]. However, because Hirano and Fujita [8] used mesoscale meteorological model that assumes the urban land to be a flat surface with a large roughness length and small albedo,
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Please cite this article in press as: Y. Hirano, T. Fujita, Simulating the CO2 reduction caused by decreasing the air conditioning load in an urban area, Energy Buildings (2015), http://dx.doi.org/10.1016/j.enbuild.2015.06.033
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Fig. 1. Overview of the coupled urban canopy and building energy model [44].
the effect of urban canopy cannot be expressed. Therefore, a more realistic approach for estimating the effects of countermeasures on air-conditioning energy consumption is a simulation-based evaluation using air-conditioning load calculations. Moreover, in order to express the interaction effects between energy consumption and outside air temperature, as well as the effects of changes in building surface temperatures, physical variables such as air-conditioning load, air temperature, the heat balance on building surfaces, heat conduction trough roofs, and walls have to be calculated simultaneously. This report assesses the effects of cooling load reduction measures (e.g., planting greenery or painting urban surfaces with high-albedo paint, internal heat reduction, and increasing insulation) on heat-island mitigation and CO2 reduction using a coupled urban canopy and building energy model [41–45]. In this paper, based on the simulations used by the model, the extent of airconditioning load changes due to the aforementioned measures is considered in detail. Moreover, a spatial calculation method is
established and CO2 reduction effects at an entire city scale are estimated.
2. Calculation conditions A coupled urban canopy and building energy model was used to predict the heat loads of buildings and changes in air temperature and energy consumption caused by air-conditioning use in urban districts (Fig. 1). The urban canopy model was developed by Kondo and Liu [46] and improved by Kikegawa et al. [41], Kondo et al. [42], and Kikegawa et al. [43]. This model was a local atmospheric model that parameterized the urban districts using the average building width, interval between buildings, and vertical density of buildings in order to express the area in a horizontally continuous homogeneous state as multiple one-dimensional vertical layers. This model assumes a vertically multilayered atmosphere and calculates the
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Fig. 2. Study area and typical districts.
meteorological elements, such as air temperature, humidity, and wind velocity, one-dimensionally. This model assumes that the buildings are uniform, of rectangular parallelepiped shape, and placed at regular intervals. The distribution of building heights are expressed by the building density at each vertical layer. Shortwave and long-wave radiations in the canopy are calculated in a three-dimensional way, and the surface heat balance and surface temperatures on building roofs, ground surfaces, and side walls in each direction are calculated for each layer. The building energy model was developed by Kikegawa et al. [41] and Kikegawa et al. [43]. This model was used for calculating the air-conditioning loads and was capable of calculating the city block-scale air-conditioning loads that included interactions with the outdoor atmosphere when incorporated into the urban canopy model. This model calculates the heat balance in a single-room based on the assumption that each building is one box, and the amount of sensible/latent heat removed is calculated by air-conditioners (i.e., air-conditioning loads) using parameters for air-conditioning, such as temperature setting, operation schedule, proportion of air-conditioned space, and so on. The coefficients of performance (COP) of air-conditioners are also calculated based on the calculation of heat balance in the room, considering the dependence of COP on air-conditioning loads. From the calculated air-conditioning loads and COP of air-conditioners, the energy consumption by air-conditioners and anthropogenic heat are calculated, which reflects the outdoor air-temperature calculation by the urban canopy model again. For the model used in this research, the temperature sensitivity of electric power for an office-building district had already been verified through a comparison with power supply data [41], and reproducibility was verified through a comparison with general air-conditioning load calculation software for residential buildings [43]. In addition, for the weather conditions of this study, we have conducted meteorological observations in urban districts, and the reproducibility of outdoor weather elements was verified [44]. Moreover, we have verified the temperature sensitivity of cooling energy consumption through a cross-comparison of various estimation methods concerning the sensitivity of energy consumption to ambient temperature [47]. This study targeted a region that included the city of Kawasaki, Japan (Fig. 2). The city of Kawasaki is a business- and industryfocused city, adjacent to the Tokyo metropolitan area in which the clear presence of a heat island was previously reported [4,8,48–52]. The city of Kawasaki has a narrow shape which is orientated from the southeast to the northwest. The southeast side verge is a landfill area, and is adjacent to the Tokyo Bay. A dense urban district is located in the central to southeast areas, and the northwest inland
areas are mainly residential in nature. This area was divided into a 500 m grid (see Fig. 2), and simulations were run based on these grid units. The investigation classified each grid cell into one of three typical districts using the method devised by Kikegawa et al. [43]: office district, residential district with fire-resistant construction, and residential district with wooden construction. Table 1 summarizes geometric parameters for each district-type. The CO2 emissions intensity was set at 0.371 kg-CO2 /kWh for electric power and 2.08 kg-CO2 /m3 for city gas based on the Order for Enforcement of the Act on Promotion of Global Warming Countermeasures [53]. Heat production per unit volume was set to 44.8 MJ/m3 based on the Comprehensive Energy Statistics [54]. To simulate typical summer days, we selected the date range of 27–29 July 2002, which represented a slightly overcast period with occasional clear-sky conditions, during which Japan was subject to a Pacific anticyclone. In order to validate the simulation, we have conducted meteorological observations made within the urban districts, and compared them with the calculation results of this model [44]. Since the simulation reproducibility during this period was confirmed using atmospheric observation data, this study used initial values and upper boundary conditions that were identical to calculations by Ohashi et al. [44]. Results from the third day of study were used in the evaluation, with the first two days providing a period for preliminary calculation runs. A standard case to compare with each countermeasure case was determined according to the conditions of Kikegawa et al. [41,43]. Table 2 summarizes the standard case and Table 3 indicates the sites that were modified for countermeasures. It was assumed that up to 60% of the rooftop and wall surfaces could be treated using planted greenery and increased-albedo countermeasures. At ground level, however, while high-albedo paint can be applied to road and parking surfaces, the planting of greenery on these surfaces is more difficult. Although further research is required to assess the extent to which each countermeasure can be implemented on these surfaces, this study examined scenarios in which planting greenery and albedo increases were possible on 20% and 60% of the ground surface, respectively. In this model, the conductance for water vapor transfer at the
Table 1 Geometric parameters for each district-type.
b: Average building width (m) w: Interval between buildings (m) h: Average building height (m)
Office districts
Residential (fire-resistant)
Residential (wooden)
14.6 12.7 17.3
11.4 10.5 12.5
9.2 11.2 7.0
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Table 2 Summary of the parameters used for the standard testing conditions.
Surface covering and albedo
Residential (fire-resistant)
Residential (wooden)
26.0 50.0 0.3 3.0
27.0 60.0 0.5 4.0
27.0 60.0 0.5 4.0
Each floor/roof top 10.0 0.75
Each floor 25.9 0.40
Each floor 25.9 0.40
226.0 196.7 196.7 192.6 230.2 230.2 4.0 4.0 4.0 Rooftop: 1.35 Rooftop: 1.54 Rooftop: 0.68 Walls: 0.68 Walls: 1.94 Walls: 1.65 Rooftop: Surface albedo 0.2. Walls: Surface albedo (other than windows) 0.2, total surface ratio 32%, no wall greenery. Ground: Surface albedo (non-vegetated portion) 0.2, proportion with green coverage 27%.
vegetation surface is set as a constant value, and evaporation efficiency is calculated from this set value and atmospheric conditions, among other variables. The albedo increases, based on the author’s observations of high-albedo paint [55], was 0.83 for rooftops and 0.64 for walls and ground surfaces. Here, 0.83 is the value for highalbedo white paint and 0.64 is the value for pale colored paint. We used a radiometer by applying paints on the concrete surface, and derived these albedo values from the ratio of the standard white board. These values were selected because building rooftops may be suitable for white paint, but consideration is required for glare and esthetic issues when dealing with walls, the ground level, and road spaces. Two other energy-conservation techniques outlined in Table 3 were also assessed: reducing internal heat sources and increasing insulation. The reduced internal heat case assumed that energy-conservation practices within a building would reduce heat generated by lights and equipment. This scenario only assessed the impact of a lesser amount of machine-generated heat on reduced air-conditioning loads, ignoring the savings in energy that was actually consumed by lights and equipment. An increase in the insulation case implied that the insulation of roof and outer walls increased based on the conditions of Kikegawa et al. [43]. 3. Results for typical districts 3.1. Standard case Fig. 3 shows the calculation results of air temperatures for three typical districts at ground level for the standard case. There was a Table 3 Summary of cases for each countermeasure. Urban greening
Increasing albedo
Internal heat reduction Insulation increased
Rooftop: Greenery on 60% of the rooftop area Walls: Greenery on 60% of the wall area (excluding windows) Ground: Ground level greenery increased by 20% Rooftop: Change 60% of the rooftop surface albedo to 0.83 Walls: Change 60% of the wall albedo to 0.64 Ground: Change 60% of the ground level albedo to 0.64 Reduce heat generated internally (from lights and equipment other than air conditioning) by 20% Rooftop of office districts: 0.38 (W/m2 /K), fire-resistant residential: 0.39 (W/m2 /K), wooden residential: 0.23 (W/m2 /K), respectively Walls of office districts: 0.38 (W/m2 /K), fire-resistant residential: 0.72 (W/m2 /K), wooden residential: 0.56 (W/m2 /K), respectively
smaller temperature change in the office and fire-resistant residential districts than in the wooden residential districts, with higher nighttime temperatures. This was either due to the higher heat capacity of the buildings, or the reduced radiant cooling caused by less available open sky over the districts. In any case, the urban canopy effect appeared to be obvious. Fig. 4 shows the calculated heat balance within buildings for the standard case, indicating the differences between each city district type. The double peak pattern of the window-transmitted insolation values can be explained by sunlight infiltrating with more easiness when the sun is at lower altitudes. However, since this model assumes that the buildings were rectangular solids aligned regularly in a virtual space, the possibility that shading from southern-orientated buildings around noontime may influence window-transmitted insolation, requires further verification. The peak in the window-transmitted insolation for office district is small with respect to the residential districts. The first reason for this is because the office district consists of large buildings with wide floor areas, and consequently, the window-transmitted insolation per floor area becomes relatively small. The second reason is the setting of the rate of the total insolation transmitted through the window is lower for the office district than that for the residential districts (see Table 2) to correspond to the setting for the windows with blinds according to Kikegawa et al. [41]. The conductive heat transfer values from the rooftops and walls of buildings in the fire-resistant residential districts were negative during the daytime. This is because the operation rates during the daytime are lower in a residential air-conditioning schedule, and thus, the average room temperatures at the non-air-conditioned areas were higher than the outdoor temperatures due to radiation from windows. Although the lack of sufficient onsite data requires further investigation in the future, each of these calculation results can be considered as relatively valid on a qualitative basis.
Office districts Air temperature [oC]
Temperature set for air conditioning (◦ C) Humidity set for air conditioning (%) Rate of total insolation transmitted through window surfaces (–) Amount of outside air introduced per unit building floor area during the air-conditioning period (m3 /m2 /h) Location of ventilation opening (for introducing outside air) Occupied floor area per occupant (m2 /person) Proportion of air conditioned space that makes up the total building floor area (–) Human body heat (sensible heat) (kJ/person/h) Human body heat (latent heat) (kJ/person/h) Floor height of building (m/floor) Coefficient of heat transmission (W/m2 /K)
Office districts
Residential (fire-resistant)
32 30 28 26
Residential (wooden)
24 0
2
4
6
8
11
14
17
20
23
Fig. 3. Air temperature by district type for standard case.
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3.2. Examining countermeasure locations
Fig. 4. Indoor heat balance by district types for a standard case (per unit floor area).
Table 3 summarizes the various settings used when installing greenery or high-albedo paint on rooftops, walls, or ground spaces. The results depended on the utilized countermeasures, and cases with seven countermeasure combinations were simulated. Fig. 5 compares the daily average differences in the indoor heat balance between the standard and countermeasure cases (Fig. 4). Fig. 5 shows how each greening case resulted in a lower heat load, with a pronounced reduction in the conductive heat load when rooftops and walls were covered with greenery. Even when greenery was installed only on the ground surface, a drop in temperature caused conductive heat to decrease slightly, but at relatively low levels. Conversely, adding greenery increased heat infiltration through air ventilation. This was primarily because the rise in the latent heat load from the added humidity exceeded the reduction in the sensible heat load from the decrease in temperature. In the increased-albedo cases, the reductions in the conductive heat load were significant when paint was applied to rooftops and walls. Conductive heat rose slightly when the albedo was increased at ground level only for office districts, but this could be attributed to ground-reflected radiation entering the walls. The windowtransmitted insolation values increased in every case. When the albedo was increased only at ground level, the window-transmitted insolation was sufficiently large to contribute to an increase in the heat load. However, from only a small change in heat load via air ventilation, the reduction in the air-conditioning load due to a decrease in the outside air temperature was relatively minor. Ventilation heat infiltration was found to increase slightly in several
Fig. 5. Changes in heat load elements after greenery was installed or albedo was increased.
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Residential (fire-resistant)
Office district 0.0
A B C D
0.0
A B C D
Residential (wooden) 0.0
-0.2
-0.2
-0.2
-0.4
-0.4
-0.4
-0.6
-0.6
-0.6
-0.8
-0.8
-0.8
-1.0
-1.0
Countermeasure cases
Residential (fire-resistant)
Office district
A B C D
0
A: Urban greening B: Increasing albedo C: Internal heat reduction D: Higher insulation
-1.0
Standard case [oC]
A B C D
0
A B C D
Residential (wooden) 0
-20
-20
-20
-40
-40
-40
-60
-60
-60
-80
-80
-80
Countermeasure cases
A B C D
A: Urban greening B: Increasing albedo C: Internal heat reduction D: Higher insulation
Standard case [kJ/m2/day] (per unit floor area)
Fig. 6. Differences in the daily average air temperatures at the ground level.
Fig. 7. Differences in energy consumption (per unit floor area).
cases when albedo was increased in wooden residential districts, but this was due to decreases in room temperature associated with lower conductive heat loads. These results are a consequence of greater variation in daytime room temperatures due to airconditioning schedules that lowered operation rates during the daytime in residential areas.
depending on the conditions. However, the internal heat reduction case and the increased insulation case had an impact on temperature conditions of less than 0.1 ◦ C on the daily mean. Fig. 7 compares energy-conservation outcomes for the various countermeasures, using greenery scenarios represented by the rooftop, wall, and ground surface cases, and albedo scenarios represented by the rooftop and wall cases. Under the conditions used in the study, planting greenery and increasing albedo resulted in significant energy savings. For the residential districts, though the temperature reduction effects are higher in installing a greenery case than in increasing an albedo case (see Fig. 6), the energy-saving effects are higher in increasing the albedo case than in installing the greenery case. This is primarily because the direct effects due to decreased surface temperatures appear to be larger than the indirect effects due to the decreased outdoor air temperatures. For the office district, though the temperature reduction effects in installing the greenery case and increasing the albedo case are relatively small (see Fig. 6), the energy-saving effects are not small as compared to the residential districts. This is because, according to the air-conditioning operation schedule, the energy consumption for cooling in the office building district are higher in daytime, and are easy to be affected by the surface heat balance change. Since the scenarios outlined in Table 3 did not allow each countermeasure to be compared equally, this study did not attempt to compare the relative merits of each technique to determine which was more useful. Reducing internally generated heat had little effect in residential districts, but had a substantial impact in office districts. Since internally generated heat is a significant contributor to airconditioning loads in energy-intensive offices (Fig. 4), conserving
3.3. Implications for energy conservation and heat-island mitigation The air temperature reductions using various heat-islandmitigation and energy-saving strategies are compared in Fig. 6. In this study, greenery on the rooftops, walls, and ground, as well as high-albedo paint applied to the rooftops and walls, was used. Because installing the greenery and increasing the albedo change the outdoor heat balances on a building and the ground surface, temperature reduction effects appear to be higher than other energy saving measures, such as internal heat reduction case and increased insulation case. Besides, Fig. 6 shows air temperature differences at the ground level, because of which the influence of the heat balance change on the ground surface became relatively large. However, increasing the albedo case assumes to apply high-albedo paint only on the rooftops and walls, the temperature reduction effects appeared to be lower than installing the greenery case. Therefore, installing greenery for a wooden residential district, which has the smallest building-to-land ratio resulted in the highest temperature reduction effect. For the office district, temperature reduction effects of installing the greenery and increasing the albedo are relatively small with respect to the residential districts. This is mainly because the building ratio is high in the office district, and the influence of the heat balance change on the ground surface became relatively small. Besides, the heat balance change is easily affected by the shadow effects of the surrounding buildings. Based on these results, the planting of greenery achieved the largest reductions in temperature, with daily average reductions of 0.6–1.0 ◦ C. Temperatures dropped by 0.1–0.5 ◦ C in the scenarios with increased albedo, which would aid the amelioration of the thermal environments. The complexity of the interactions between the effects of anthropogenic heat reduction and changes in the heat flux at building surfaces makes it difficult to clearly identify trends in the other cases. In comparison with installing greenery or increasing albedo, however, each of the other cases resulted in relatively minor changes. In the internal heat reduction case, the temperature decreased slightly in each district type. This is due to the reduction in anthropogenic heat by energy saving. In the increased insulation case, the temperature increased slightly in the wooden residential district. In this case, the heat capacity of building surfaces decreases due to insulation, and thus, the range of variation of the surface temperature becomes large, resulting in impacts that vary
Fig. 8. Cooling energy consumption in Kawasaki (standard case, per unit land area, kJ/m2 /day).
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Fig. 9. Differences in energy consumption.
4. Large-scale assessment of the city of Kawasaki Potential energy-consumption reductions for each countermeasure when implemented on a large scale were investigated next. The same simulation was run for each grid in the target study area (Fig. 2). This calculation applies the urban-greening scenarios represented by the rooftop, walls, and ground surface cases, and high-albedo scenarios represented by the cases of rooftops and walls. In order to express the mixing of different district-types when using a grid size of 500 m, energy consumption per unit floor area for the 3 district types (i.e., the office, fire-resistant residential, and wooden residential districts) included in each 500 m grid cell were calculated separately, and multiplied by each districts’ floor area. Therefore, this calculation does not express the atmospheric interactions between buildings of different district types existing in the same grid cell. Fig. 8 shows the standard case for energy consumption and Fig. 9 indicates the energy savings when greenery was planted or albedo increased. Higher energy savings can be observed in denser urban areas. While energy consumption reductions are pronounced on a per unit floor area basis in residential districts as well as office districts (see Fig. 7), in terms of per unit land area, significantly higher energy savings can be realized in dense urban areas because of the increased floor area. Although the fact that higher energy savings can be obtained in denser urban areas may be an intuitive conclusion, it is significant that these energy saving effects were quantified. CO2 reductions were calculated when the four countermeasure scenarios described in Table 3 were implemented over the entire study region (Fig. 10). Fig. 10 contains an additional axis indicating the proportion of total air conditioning reductions in the standard case. This study found that increasing albedo or planting greenery achieved relatively significant CO2 reductions, which approached 300–400 t-CO2 /day over the entire study region, or around 15–20% of the total. At values of just over 100 t-CO2 /day
0 CO2 reduction
energy indoors was important for reducing air-conditioning loads in the office district. Although the temperature increased in the increased insulation case in the wooden residential district (see Fig. 6), energy consumption for the air-conditioning decreased. This is because the temperature setting for air conditioning is further lower than the outdoor temperature and the insulation prevents heat transfer from the outdoor air.
A
B
C
D
0
-100
-5
-200
-10
Office district Residential (fire-resistant) Residential (wooden)
-300
-15 [%]
-400 Countermeasure cases
Standard case [t-CO2/day]
A: Urban greening B: Increasing albedo C: Internal heat reduction D: Higher insulation Fig. 10. Differences in total CO2 emissions.
(7%) and 60 t-CO2 /day (3%), higher insulation and internal heat reduction levels were also found to significantly conserve energy. However, these scenarios did not allow an equal comparison of each countermeasure. Therefore, this study did not attempt to compare these countermeasures to determine which was most effective. In addition, these percentages possibly understate true CO2 reductions, because only midsummer days were used in the analysis. In many cases, percentage values calculated only for midsummer days tended to be smaller because the denominators of total air conditioning values were large. For the future, a regular assessment and a year-round evaluation is necessary for a more comprehensive understanding of the effects on energy savings. 5. Conclusions In this study, we have assessed the cooling and CO2 reduction effects for the mitigation of urban heat islands and for energy saving, e.g., urban greening and high-albedo painting. As a typical energy-saving method for buildings, reducing the internal heat sources, and increasing the insulation have also been assessed. In order to simulate the city-block-scale air-conditioning loads and cooling energy demands, we used a coupled urban-canopy and building-energy model. This model includes a vertical onedimensional local atmospheric model and a box-type building model for calculating the air-conditioning loads, and it predicts the
Please cite this article in press as: Y. Hirano, T. Fujita, Simulating the CO2 reduction caused by decreasing the air conditioning load in an urban area, Energy Buildings (2015), http://dx.doi.org/10.1016/j.enbuild.2015.06.033
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heat loads of buildings and the effects of air conditioning operation on the energy consumption and air temperature changes. This coupled model made it possible to express the effects of interaction of the anthropogenic heat release due to the use of air-conditioning with the outdoor thermal environment. For the purpose of our investigation, we have selected three typical districts, which consisted of office districts, residential districts of fire-resistant construction, and residential districts of wooden construction. The investigation based on these three typical districts showed that the urban greening and increased albedo can be effective in mitigating the urban thermal environments. Each of the other scenarios (i.e., internal heat reduction, higher insulation) showed relatively less change when compared to the greening or increasing the albedo. The investigation on the energy savings based on three typical districts showed that the greening and increasing the albedo resulted in a significant degree of energy conservation. The investigation also suggested that applying a high-albedo paint on the ground surface might increase the airconditioning load due to an increase in the window-transmitted insolation. Given the testing conditions used in this study, planting greenery or increasing albedo achieved respective temperature reductions of 0.6–1.0 ◦ C and 0.1–0.5 ◦ C, and energy savings in residential areas on a per unit floor area basis of 40–50 kJ/m2 /day and 70–90 kJ/m2 /day. In order to conduct a large-scale evaluation on the outcome of the implementation of these countermeasures, we have applied the same calculation to each grid contained in the city of Kawasaki. This approach made it possible to clarify the potential of each countermeasure to reduce the CO2 emission over the entire target area, and visualized the spatial distribution of CO2 emissions and reduction effects; this can be expected to contribute to the actual planning of a global warming countermeasure by the local governments. The results of the large-scale assessment showed that increasing the albedo achieved the highest CO2 reductions of up to 400 t-CO2 /day throughout Kawasaki. However, this measure might give rise to higher CO2 emissions during the winter in Japan by reducing the heat-island effect and increasing heating demands [8]. Since we did not include energy-efficiency parameters for heating, we only considered the effects during the summer. A year-round evaluation is required in the future. Additionally, more realistic studies that consider the feasibility of executing each countermeasure, and assess each countermeasure over a period of several years (including during wintertime) are planned. Another future research direction is to conduct an evaluation while distinguishing between direct effects due to decreased rooftop surface temperatures and indirect effects from the outside air. Fig. 5 suggests that the main factor of the heat load reductions by urban greening is the reduction of conductive heat from the roof and wall surfaces. However, since the air temperature is changed by urban greening due to the change in sensible heat flux from the building surfaces, the changes in air temperatures should be smaller than the changes in surface temperatures. Therefore, for conductive heat from roof and wall surfaces, the indirect effects are considered to be smaller than the direct effects. On the other hand, for heat infiltration through air ventilation, the results were obtained suggesting that the urban greening increased the heat load (see Fig. 5). This is because, for the heat infiltration through air ventilation, the increase in the latent heat load due to increased humidity was greater than the decrease in sensible heat load due to the reduced temperatures in the urban greening case under the calculation conditions in the study. This is an important result which suggests that if greenery is planted at a particular building, there is a possibility that air-conditioning loads in surrounding buildings will increase rather than decrease. In reality, it is difficult to adopt similar rooftop greening techniques for all buildings in a district, and
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Simulating the CO2 reduction caused by decreasing the air conditioning load in an urban area Yujiro Hirano ∗ , Tsuyoshi Fujita Center for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, Japan
a r t i c l e
i n f o
Article history: Received 28 February 2015 Received in revised form 30 May 2015 Accepted 11 June 2015 Available online xxx Keywords: Urban heat island Energy saving Air-conditioning load simulation Urban thermal environment CO2 reduction
a b s t r a c t In this paper, measures such as planting urban greenery and using high-albedo paint to mitigate the urban heat-island effect, conserve energy, and reduce CO2 emissions were assessed. As a typical energy-saving method for buildings, reducing the internal heat sources and increasing the insulation are also assessed. We used a coupled urban canopy and building energy model to predict the heat loads of buildings in city districts, the effects of air-conditioning on energy consumption, and air temperature changes. In this model, a vertical one-dimensional local atmospheric model is coupled with an air-conditioning load calculation model for buildings, making it possible to assess the interaction between anthropogenic heat release due to air-conditioning usage and the outside thermal environment. In this study, we selected a target study region in the city of Kawasaki, Japan. When typical city districts were assessed, planting greenery or increasing albedo achieved temperature reductions of 0.6–1.0 ◦ C and 0.1–0.5 ◦ C, respectively, and energy savings of 40–80 and 70–90 kJ/m2 /day (per unit floor area) on a typical summer day. The results from the large-scale assessment show that urban greening or albedo increases achieved the highest energy savings, of up to 400 t-CO2 /day, in the entire target study region. © 2015 Elsevier B.V. All rights reserved.
1. Introduction The conservation of energy to mitigate global warming is an important topic of study. Of particular concern is the need to offset the ever-increasing amounts of energy used for air-conditioning purposes in urban regions. In urban areas, a significant impact of urbanization is the rise in temperature due to artificial land cover, anthropogenic heat, and so on (i.e., urban heat islands) [1–3]. A worsening urban heat-island effect not only makes city living less comfortable during the summer, but is also implicated in higher peak electrical loads and energy consumed for air-conditioning purposes [2–7]. Consequently, improving the thermal environment of urban regions is important for countering both global warming and the urban heat-island effect. Various studies have evaluated the effects of a heat island on the energy consumption of a number of cities, including Tokyo [8], Athens [9–11], London [12–14], and Taipei [15]. In recent years, sufficient knowledge of urban heat islands has been accumulated, with the next step being to mitigate their negative impacts. In fact, in recent years, proposals for mitigation measures such as urban greening, urban albedo increases, and permeable pavement,
∗ Corresponding author. E-mail address: [email protected] (Y. Hirano).
as well as reports on the investigation of their mitigation effects, are becoming more common. In particular, many studies evaluating the mitigation of heat-island effects have been conducted in the United States and Canada [16–24]. However, since the results of these studies depend on various factors, such as local climatic conditions, building styles, and lifestyles, their results are still insufficient for widespread application. More specifically, few studies have evaluated cases in Japan, where the summers are hot and humid. Hirano and Fujita [8] developed a new method to evaluate the heat-island impact on energy consumption by taking into consideration spatial and temporal distributions of both energy consumption and air temperature. However, since this method is based on the sensitivity of energy consumption to ambient temperatures, the interaction effects between anthropogenic heat release due to air-conditioning use, and the outside thermal environment cannot be expressed. In addition, only the effects of changes in outdoor temperature were estimated, and it was not possible to accurately evaluate the effects of countermeasures accompanying changes in building surface temperatures (e.g., cool roofs [25–34]). In recent years, many studies have reported the effects of urban geometry on temperature, air-flow, and radiation conditions inside the urban canopies [35–40]. However, because Hirano and Fujita [8] used mesoscale meteorological model that assumes the urban land to be a flat surface with a large roughness length and small albedo,
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Fig. 1. Overview of the coupled urban canopy and building energy model [44].
the effect of urban canopy cannot be expressed. Therefore, a more realistic approach for estimating the effects of countermeasures on air-conditioning energy consumption is a simulation-based evaluation using air-conditioning load calculations. Moreover, in order to express the interaction effects between energy consumption and outside air temperature, as well as the effects of changes in building surface temperatures, physical variables such as air-conditioning load, air temperature, the heat balance on building surfaces, heat conduction trough roofs, and walls have to be calculated simultaneously. This report assesses the effects of cooling load reduction measures (e.g., planting greenery or painting urban surfaces with high-albedo paint, internal heat reduction, and increasing insulation) on heat-island mitigation and CO2 reduction using a coupled urban canopy and building energy model [41–45]. In this paper, based on the simulations used by the model, the extent of airconditioning load changes due to the aforementioned measures is considered in detail. Moreover, a spatial calculation method is
established and CO2 reduction effects at an entire city scale are estimated.
2. Calculation conditions A coupled urban canopy and building energy model was used to predict the heat loads of buildings and changes in air temperature and energy consumption caused by air-conditioning use in urban districts (Fig. 1). The urban canopy model was developed by Kondo and Liu [46] and improved by Kikegawa et al. [41], Kondo et al. [42], and Kikegawa et al. [43]. This model was a local atmospheric model that parameterized the urban districts using the average building width, interval between buildings, and vertical density of buildings in order to express the area in a horizontally continuous homogeneous state as multiple one-dimensional vertical layers. This model assumes a vertically multilayered atmosphere and calculates the
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Fig. 2. Study area and typical districts.
meteorological elements, such as air temperature, humidity, and wind velocity, one-dimensionally. This model assumes that the buildings are uniform, of rectangular parallelepiped shape, and placed at regular intervals. The distribution of building heights are expressed by the building density at each vertical layer. Shortwave and long-wave radiations in the canopy are calculated in a three-dimensional way, and the surface heat balance and surface temperatures on building roofs, ground surfaces, and side walls in each direction are calculated for each layer. The building energy model was developed by Kikegawa et al. [41] and Kikegawa et al. [43]. This model was used for calculating the air-conditioning loads and was capable of calculating the city block-scale air-conditioning loads that included interactions with the outdoor atmosphere when incorporated into the urban canopy model. This model calculates the heat balance in a single-room based on the assumption that each building is one box, and the amount of sensible/latent heat removed is calculated by air-conditioners (i.e., air-conditioning loads) using parameters for air-conditioning, such as temperature setting, operation schedule, proportion of air-conditioned space, and so on. The coefficients of performance (COP) of air-conditioners are also calculated based on the calculation of heat balance in the room, considering the dependence of COP on air-conditioning loads. From the calculated air-conditioning loads and COP of air-conditioners, the energy consumption by air-conditioners and anthropogenic heat are calculated, which reflects the outdoor air-temperature calculation by the urban canopy model again. For the model used in this research, the temperature sensitivity of electric power for an office-building district had already been verified through a comparison with power supply data [41], and reproducibility was verified through a comparison with general air-conditioning load calculation software for residential buildings [43]. In addition, for the weather conditions of this study, we have conducted meteorological observations in urban districts, and the reproducibility of outdoor weather elements was verified [44]. Moreover, we have verified the temperature sensitivity of cooling energy consumption through a cross-comparison of various estimation methods concerning the sensitivity of energy consumption to ambient temperature [47]. This study targeted a region that included the city of Kawasaki, Japan (Fig. 2). The city of Kawasaki is a business- and industryfocused city, adjacent to the Tokyo metropolitan area in which the clear presence of a heat island was previously reported [4,8,48–52]. The city of Kawasaki has a narrow shape which is orientated from the southeast to the northwest. The southeast side verge is a landfill area, and is adjacent to the Tokyo Bay. A dense urban district is located in the central to southeast areas, and the northwest inland
areas are mainly residential in nature. This area was divided into a 500 m grid (see Fig. 2), and simulations were run based on these grid units. The investigation classified each grid cell into one of three typical districts using the method devised by Kikegawa et al. [43]: office district, residential district with fire-resistant construction, and residential district with wooden construction. Table 1 summarizes geometric parameters for each district-type. The CO2 emissions intensity was set at 0.371 kg-CO2 /kWh for electric power and 2.08 kg-CO2 /m3 for city gas based on the Order for Enforcement of the Act on Promotion of Global Warming Countermeasures [53]. Heat production per unit volume was set to 44.8 MJ/m3 based on the Comprehensive Energy Statistics [54]. To simulate typical summer days, we selected the date range of 27–29 July 2002, which represented a slightly overcast period with occasional clear-sky conditions, during which Japan was subject to a Pacific anticyclone. In order to validate the simulation, we have conducted meteorological observations made within the urban districts, and compared them with the calculation results of this model [44]. Since the simulation reproducibility during this period was confirmed using atmospheric observation data, this study used initial values and upper boundary conditions that were identical to calculations by Ohashi et al. [44]. Results from the third day of study were used in the evaluation, with the first two days providing a period for preliminary calculation runs. A standard case to compare with each countermeasure case was determined according to the conditions of Kikegawa et al. [41,43]. Table 2 summarizes the standard case and Table 3 indicates the sites that were modified for countermeasures. It was assumed that up to 60% of the rooftop and wall surfaces could be treated using planted greenery and increased-albedo countermeasures. At ground level, however, while high-albedo paint can be applied to road and parking surfaces, the planting of greenery on these surfaces is more difficult. Although further research is required to assess the extent to which each countermeasure can be implemented on these surfaces, this study examined scenarios in which planting greenery and albedo increases were possible on 20% and 60% of the ground surface, respectively. In this model, the conductance for water vapor transfer at the
Table 1 Geometric parameters for each district-type.
b: Average building width (m) w: Interval between buildings (m) h: Average building height (m)
Office districts
Residential (fire-resistant)
Residential (wooden)
14.6 12.7 17.3
11.4 10.5 12.5
9.2 11.2 7.0
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Table 2 Summary of the parameters used for the standard testing conditions.
Surface covering and albedo
Residential (fire-resistant)
Residential (wooden)
26.0 50.0 0.3 3.0
27.0 60.0 0.5 4.0
27.0 60.0 0.5 4.0
Each floor/roof top 10.0 0.75
Each floor 25.9 0.40
Each floor 25.9 0.40
226.0 196.7 196.7 192.6 230.2 230.2 4.0 4.0 4.0 Rooftop: 1.35 Rooftop: 1.54 Rooftop: 0.68 Walls: 0.68 Walls: 1.94 Walls: 1.65 Rooftop: Surface albedo 0.2. Walls: Surface albedo (other than windows) 0.2, total surface ratio 32%, no wall greenery. Ground: Surface albedo (non-vegetated portion) 0.2, proportion with green coverage 27%.
vegetation surface is set as a constant value, and evaporation efficiency is calculated from this set value and atmospheric conditions, among other variables. The albedo increases, based on the author’s observations of high-albedo paint [55], was 0.83 for rooftops and 0.64 for walls and ground surfaces. Here, 0.83 is the value for highalbedo white paint and 0.64 is the value for pale colored paint. We used a radiometer by applying paints on the concrete surface, and derived these albedo values from the ratio of the standard white board. These values were selected because building rooftops may be suitable for white paint, but consideration is required for glare and esthetic issues when dealing with walls, the ground level, and road spaces. Two other energy-conservation techniques outlined in Table 3 were also assessed: reducing internal heat sources and increasing insulation. The reduced internal heat case assumed that energy-conservation practices within a building would reduce heat generated by lights and equipment. This scenario only assessed the impact of a lesser amount of machine-generated heat on reduced air-conditioning loads, ignoring the savings in energy that was actually consumed by lights and equipment. An increase in the insulation case implied that the insulation of roof and outer walls increased based on the conditions of Kikegawa et al. [43]. 3. Results for typical districts 3.1. Standard case Fig. 3 shows the calculation results of air temperatures for three typical districts at ground level for the standard case. There was a Table 3 Summary of cases for each countermeasure. Urban greening
Increasing albedo
Internal heat reduction Insulation increased
Rooftop: Greenery on 60% of the rooftop area Walls: Greenery on 60% of the wall area (excluding windows) Ground: Ground level greenery increased by 20% Rooftop: Change 60% of the rooftop surface albedo to 0.83 Walls: Change 60% of the wall albedo to 0.64 Ground: Change 60% of the ground level albedo to 0.64 Reduce heat generated internally (from lights and equipment other than air conditioning) by 20% Rooftop of office districts: 0.38 (W/m2 /K), fire-resistant residential: 0.39 (W/m2 /K), wooden residential: 0.23 (W/m2 /K), respectively Walls of office districts: 0.38 (W/m2 /K), fire-resistant residential: 0.72 (W/m2 /K), wooden residential: 0.56 (W/m2 /K), respectively
smaller temperature change in the office and fire-resistant residential districts than in the wooden residential districts, with higher nighttime temperatures. This was either due to the higher heat capacity of the buildings, or the reduced radiant cooling caused by less available open sky over the districts. In any case, the urban canopy effect appeared to be obvious. Fig. 4 shows the calculated heat balance within buildings for the standard case, indicating the differences between each city district type. The double peak pattern of the window-transmitted insolation values can be explained by sunlight infiltrating with more easiness when the sun is at lower altitudes. However, since this model assumes that the buildings were rectangular solids aligned regularly in a virtual space, the possibility that shading from southern-orientated buildings around noontime may influence window-transmitted insolation, requires further verification. The peak in the window-transmitted insolation for office district is small with respect to the residential districts. The first reason for this is because the office district consists of large buildings with wide floor areas, and consequently, the window-transmitted insolation per floor area becomes relatively small. The second reason is the setting of the rate of the total insolation transmitted through the window is lower for the office district than that for the residential districts (see Table 2) to correspond to the setting for the windows with blinds according to Kikegawa et al. [41]. The conductive heat transfer values from the rooftops and walls of buildings in the fire-resistant residential districts were negative during the daytime. This is because the operation rates during the daytime are lower in a residential air-conditioning schedule, and thus, the average room temperatures at the non-air-conditioned areas were higher than the outdoor temperatures due to radiation from windows. Although the lack of sufficient onsite data requires further investigation in the future, each of these calculation results can be considered as relatively valid on a qualitative basis.
Office districts Air temperature [oC]
Temperature set for air conditioning (◦ C) Humidity set for air conditioning (%) Rate of total insolation transmitted through window surfaces (–) Amount of outside air introduced per unit building floor area during the air-conditioning period (m3 /m2 /h) Location of ventilation opening (for introducing outside air) Occupied floor area per occupant (m2 /person) Proportion of air conditioned space that makes up the total building floor area (–) Human body heat (sensible heat) (kJ/person/h) Human body heat (latent heat) (kJ/person/h) Floor height of building (m/floor) Coefficient of heat transmission (W/m2 /K)
Office districts
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32 30 28 26
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2
4
6
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11
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Fig. 3. Air temperature by district type for standard case.
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3.2. Examining countermeasure locations
Fig. 4. Indoor heat balance by district types for a standard case (per unit floor area).
Table 3 summarizes the various settings used when installing greenery or high-albedo paint on rooftops, walls, or ground spaces. The results depended on the utilized countermeasures, and cases with seven countermeasure combinations were simulated. Fig. 5 compares the daily average differences in the indoor heat balance between the standard and countermeasure cases (Fig. 4). Fig. 5 shows how each greening case resulted in a lower heat load, with a pronounced reduction in the conductive heat load when rooftops and walls were covered with greenery. Even when greenery was installed only on the ground surface, a drop in temperature caused conductive heat to decrease slightly, but at relatively low levels. Conversely, adding greenery increased heat infiltration through air ventilation. This was primarily because the rise in the latent heat load from the added humidity exceeded the reduction in the sensible heat load from the decrease in temperature. In the increased-albedo cases, the reductions in the conductive heat load were significant when paint was applied to rooftops and walls. Conductive heat rose slightly when the albedo was increased at ground level only for office districts, but this could be attributed to ground-reflected radiation entering the walls. The windowtransmitted insolation values increased in every case. When the albedo was increased only at ground level, the window-transmitted insolation was sufficiently large to contribute to an increase in the heat load. However, from only a small change in heat load via air ventilation, the reduction in the air-conditioning load due to a decrease in the outside air temperature was relatively minor. Ventilation heat infiltration was found to increase slightly in several
Fig. 5. Changes in heat load elements after greenery was installed or albedo was increased.
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Fig. 6. Differences in the daily average air temperatures at the ground level.
Fig. 7. Differences in energy consumption (per unit floor area).
cases when albedo was increased in wooden residential districts, but this was due to decreases in room temperature associated with lower conductive heat loads. These results are a consequence of greater variation in daytime room temperatures due to airconditioning schedules that lowered operation rates during the daytime in residential areas.
depending on the conditions. However, the internal heat reduction case and the increased insulation case had an impact on temperature conditions of less than 0.1 ◦ C on the daily mean. Fig. 7 compares energy-conservation outcomes for the various countermeasures, using greenery scenarios represented by the rooftop, wall, and ground surface cases, and albedo scenarios represented by the rooftop and wall cases. Under the conditions used in the study, planting greenery and increasing albedo resulted in significant energy savings. For the residential districts, though the temperature reduction effects are higher in installing a greenery case than in increasing an albedo case (see Fig. 6), the energy-saving effects are higher in increasing the albedo case than in installing the greenery case. This is primarily because the direct effects due to decreased surface temperatures appear to be larger than the indirect effects due to the decreased outdoor air temperatures. For the office district, though the temperature reduction effects in installing the greenery case and increasing the albedo case are relatively small (see Fig. 6), the energy-saving effects are not small as compared to the residential districts. This is because, according to the air-conditioning operation schedule, the energy consumption for cooling in the office building district are higher in daytime, and are easy to be affected by the surface heat balance change. Since the scenarios outlined in Table 3 did not allow each countermeasure to be compared equally, this study did not attempt to compare the relative merits of each technique to determine which was more useful. Reducing internally generated heat had little effect in residential districts, but had a substantial impact in office districts. Since internally generated heat is a significant contributor to airconditioning loads in energy-intensive offices (Fig. 4), conserving
3.3. Implications for energy conservation and heat-island mitigation The air temperature reductions using various heat-islandmitigation and energy-saving strategies are compared in Fig. 6. In this study, greenery on the rooftops, walls, and ground, as well as high-albedo paint applied to the rooftops and walls, was used. Because installing the greenery and increasing the albedo change the outdoor heat balances on a building and the ground surface, temperature reduction effects appear to be higher than other energy saving measures, such as internal heat reduction case and increased insulation case. Besides, Fig. 6 shows air temperature differences at the ground level, because of which the influence of the heat balance change on the ground surface became relatively large. However, increasing the albedo case assumes to apply high-albedo paint only on the rooftops and walls, the temperature reduction effects appeared to be lower than installing the greenery case. Therefore, installing greenery for a wooden residential district, which has the smallest building-to-land ratio resulted in the highest temperature reduction effect. For the office district, temperature reduction effects of installing the greenery and increasing the albedo are relatively small with respect to the residential districts. This is mainly because the building ratio is high in the office district, and the influence of the heat balance change on the ground surface became relatively small. Besides, the heat balance change is easily affected by the shadow effects of the surrounding buildings. Based on these results, the planting of greenery achieved the largest reductions in temperature, with daily average reductions of 0.6–1.0 ◦ C. Temperatures dropped by 0.1–0.5 ◦ C in the scenarios with increased albedo, which would aid the amelioration of the thermal environments. The complexity of the interactions between the effects of anthropogenic heat reduction and changes in the heat flux at building surfaces makes it difficult to clearly identify trends in the other cases. In comparison with installing greenery or increasing albedo, however, each of the other cases resulted in relatively minor changes. In the internal heat reduction case, the temperature decreased slightly in each district type. This is due to the reduction in anthropogenic heat by energy saving. In the increased insulation case, the temperature increased slightly in the wooden residential district. In this case, the heat capacity of building surfaces decreases due to insulation, and thus, the range of variation of the surface temperature becomes large, resulting in impacts that vary
Fig. 8. Cooling energy consumption in Kawasaki (standard case, per unit land area, kJ/m2 /day).
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Fig. 9. Differences in energy consumption.
4. Large-scale assessment of the city of Kawasaki Potential energy-consumption reductions for each countermeasure when implemented on a large scale were investigated next. The same simulation was run for each grid in the target study area (Fig. 2). This calculation applies the urban-greening scenarios represented by the rooftop, walls, and ground surface cases, and high-albedo scenarios represented by the cases of rooftops and walls. In order to express the mixing of different district-types when using a grid size of 500 m, energy consumption per unit floor area for the 3 district types (i.e., the office, fire-resistant residential, and wooden residential districts) included in each 500 m grid cell were calculated separately, and multiplied by each districts’ floor area. Therefore, this calculation does not express the atmospheric interactions between buildings of different district types existing in the same grid cell. Fig. 8 shows the standard case for energy consumption and Fig. 9 indicates the energy savings when greenery was planted or albedo increased. Higher energy savings can be observed in denser urban areas. While energy consumption reductions are pronounced on a per unit floor area basis in residential districts as well as office districts (see Fig. 7), in terms of per unit land area, significantly higher energy savings can be realized in dense urban areas because of the increased floor area. Although the fact that higher energy savings can be obtained in denser urban areas may be an intuitive conclusion, it is significant that these energy saving effects were quantified. CO2 reductions were calculated when the four countermeasure scenarios described in Table 3 were implemented over the entire study region (Fig. 10). Fig. 10 contains an additional axis indicating the proportion of total air conditioning reductions in the standard case. This study found that increasing albedo or planting greenery achieved relatively significant CO2 reductions, which approached 300–400 t-CO2 /day over the entire study region, or around 15–20% of the total. At values of just over 100 t-CO2 /day
0 CO2 reduction
energy indoors was important for reducing air-conditioning loads in the office district. Although the temperature increased in the increased insulation case in the wooden residential district (see Fig. 6), energy consumption for the air-conditioning decreased. This is because the temperature setting for air conditioning is further lower than the outdoor temperature and the insulation prevents heat transfer from the outdoor air.
A
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(7%) and 60 t-CO2 /day (3%), higher insulation and internal heat reduction levels were also found to significantly conserve energy. However, these scenarios did not allow an equal comparison of each countermeasure. Therefore, this study did not attempt to compare these countermeasures to determine which was most effective. In addition, these percentages possibly understate true CO2 reductions, because only midsummer days were used in the analysis. In many cases, percentage values calculated only for midsummer days tended to be smaller because the denominators of total air conditioning values were large. For the future, a regular assessment and a year-round evaluation is necessary for a more comprehensive understanding of the effects on energy savings. 5. Conclusions In this study, we have assessed the cooling and CO2 reduction effects for the mitigation of urban heat islands and for energy saving, e.g., urban greening and high-albedo painting. As a typical energy-saving method for buildings, reducing the internal heat sources, and increasing the insulation have also been assessed. In order to simulate the city-block-scale air-conditioning loads and cooling energy demands, we used a coupled urban-canopy and building-energy model. This model includes a vertical onedimensional local atmospheric model and a box-type building model for calculating the air-conditioning loads, and it predicts the
Please cite this article in press as: Y. Hirano, T. Fujita, Simulating the CO2 reduction caused by decreasing the air conditioning load in an urban area, Energy Buildings (2015), http://dx.doi.org/10.1016/j.enbuild.2015.06.033
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heat loads of buildings and the effects of air conditioning operation on the energy consumption and air temperature changes. This coupled model made it possible to express the effects of interaction of the anthropogenic heat release due to the use of air-conditioning with the outdoor thermal environment. For the purpose of our investigation, we have selected three typical districts, which consisted of office districts, residential districts of fire-resistant construction, and residential districts of wooden construction. The investigation based on these three typical districts showed that the urban greening and increased albedo can be effective in mitigating the urban thermal environments. Each of the other scenarios (i.e., internal heat reduction, higher insulation) showed relatively less change when compared to the greening or increasing the albedo. The investigation on the energy savings based on three typical districts showed that the greening and increasing the albedo resulted in a significant degree of energy conservation. The investigation also suggested that applying a high-albedo paint on the ground surface might increase the airconditioning load due to an increase in the window-transmitted insolation. Given the testing conditions used in this study, planting greenery or increasing albedo achieved respective temperature reductions of 0.6–1.0 ◦ C and 0.1–0.5 ◦ C, and energy savings in residential areas on a per unit floor area basis of 40–50 kJ/m2 /day and 70–90 kJ/m2 /day. In order to conduct a large-scale evaluation on the outcome of the implementation of these countermeasures, we have applied the same calculation to each grid contained in the city of Kawasaki. This approach made it possible to clarify the potential of each countermeasure to reduce the CO2 emission over the entire target area, and visualized the spatial distribution of CO2 emissions and reduction effects; this can be expected to contribute to the actual planning of a global warming countermeasure by the local governments. The results of the large-scale assessment showed that increasing the albedo achieved the highest CO2 reductions of up to 400 t-CO2 /day throughout Kawasaki. However, this measure might give rise to higher CO2 emissions during the winter in Japan by reducing the heat-island effect and increasing heating demands [8]. Since we did not include energy-efficiency parameters for heating, we only considered the effects during the summer. A year-round evaluation is required in the future. Additionally, more realistic studies that consider the feasibility of executing each countermeasure, and assess each countermeasure over a period of several years (including during wintertime) are planned. Another future research direction is to conduct an evaluation while distinguishing between direct effects due to decreased rooftop surface temperatures and indirect effects from the outside air. Fig. 5 suggests that the main factor of the heat load reductions by urban greening is the reduction of conductive heat from the roof and wall surfaces. However, since the air temperature is changed by urban greening due to the change in sensible heat flux from the building surfaces, the changes in air temperatures should be smaller than the changes in surface temperatures. Therefore, for conductive heat from roof and wall surfaces, the indirect effects are considered to be smaller than the direct effects. On the other hand, for heat infiltration through air ventilation, the results were obtained suggesting that the urban greening increased the heat load (see Fig. 5). This is because, for the heat infiltration through air ventilation, the increase in the latent heat load due to increased humidity was greater than the decrease in sensible heat load due to the reduced temperatures in the urban greening case under the calculation conditions in the study. This is an important result which suggests that if greenery is planted at a particular building, there is a possibility that air-conditioning loads in surrounding buildings will increase rather than decrease. In reality, it is difficult to adopt similar rooftop greening techniques for all buildings in a district, and
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Please cite this article in press as: Y. Hirano, T. Fujita, Simulating the CO2 reduction caused by decreasing the air conditioning load in an urban area, Energy Buildings (2015), http://dx.doi.org/10.1016/j.enbuild.2015.06.033