Policies for Building Low-Carbon Cities and Evaluating Them in Asia:

Academic Article

Journal of Heat Island Institute International Vol.7-2 (2012)

Policies for Building Low-Carbon Cities and Evaluating Them in Asia:

The Effect of Mitigation around Buildings

Yukiko YOSHIDA*

¹

Toshiaki ICHINOSE*

¹

*¹National Institute for Environmental Studies Tsukuba, Japan

Corresponding author email: [email protected] ABSTRACT

When planning and building low-carbon cities, architectural methods that take into account global environmental conservation generally involve a reduction in the effect of the heat load of a building. Therefore, we evaluated the reduction in energy consumption that can be achieved by improving models for efficient heating, ventilation, and air conditioning (HVAC) technologies in office buildings. We attempted to develop an information system for building blocks and used it to develop a system called Environment and Energy around Building Blocks (EEBB). The information about energy saving will be available to residents and energy managers.

Introduction

In urban areas, the high population density creates heat islands and causes anthropogenic heat. As Figure 1 shows, we must develop an Asian strategy instead of adopting European Union logic, which focuses on reducing heating to realize low-carbon cities. As Asia becomes increasingly urbanized, it needs a cooling method that limits the problem of environmental impact. This report presents part of the results from the research project entitled Study on the Strategic Urban Planning and Assessment of Low-Carbon Cities, supported by The Global Environment Research Fund (Hc-086: FY2008), Ministry of

Environment (Head investigator: Prof. Hidefumi Imura, Nagoya University).

Concept of Environment and Energy around Building Blocks (EEBB)

First, we evaluated the reduction of energy consumption that can be achieved by improving heating, ventilation, and air conditioning (HVAC) technologies in office buildings (Yoshida 2006). We are developing a building-block information system called Environment and Energy around Building Blocks (EEBB).

The logic of this system is based on the optimal control of air conditioning (Yoshida et al. 2008). Based on our experimental

Figure 1. (a) GDP(PPP) per capita and heating-cooling degree month (b) Population density and heating-cooling degree month 0080

6040 2000 8060 40200 2040 6080 00

Paris

Moscow

Tokyo Shanghai

San Francisco Nagoya

London Berlin

Bangkok Seoul

Beijing New York

Abu Dhabi Manila

Only cooling degree month Cooling degree month Heating degree month Only heating degree month

▲

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Paris

Moscow

Tokyo Shanghai

San Francisco Nagoya

London Berlin

Bangkok

Seoul Beijing

New York

Abu Dhabi Manila

Only cooling degree month Cooling degree month Heating degree month Only heating degree month

▲

※Bangkok: From the central part to 10km

data, we composed a low-energy optimal control model for each season, and we developed an environmental information system to help the occupants of buildings to decide their behavior for the reduction of energy consumption.

Additionally, we are now attempting to extend EEBB on an urban scale. We think the emission density of anthropogenic heat is proportional to the population density in the case of no improvement of heat-source equipment, buildings, and occupant’s behavior. Feedback is a key way to connect buildings in urban evaluations. Wisely chosen countermeasures when applying EEBB can improve the thermal environment and realize a low-carbon society (Figure 2). Publicly available remote-sensing and statistical data helped us evaluate the simulation’s accuracy. Appropriate energy-savings information should be provided for residents and energy managers (e.g., making use data from Automated Meteorological Data Acquisition System [AMeDAS, JMA] measurements delivered in real time).

We therefore developed a research flow (Figure 3) that classifies types of cities in terms of the sky-view factor and weather data. In this study, we calculated the energy consumption by considering specific window types and building-block characteristics.

Possibility of Energy Reduction

With respect to energy consumption in Japanese office buildings, air conditioning accounts for about 50%, and lighting and electrical outlets for about 30% (Murakami et al. 2006). At the National Institute for Environmental Studies (NIES), we constructed a three-story ferroconcrete office building called the Climate Change Research Hall (CCRH), with a total floor space of 4900 m². When this office building was designed, the possible energy reduction was calculated. The study found that the effect of window type on cooling was about 10%, natural ventilation reduced the need for cooling by about 40%, and roof planting had little effect (Chikada et al. 2001). In office buildings, generally speaking, air handling units (AHU) use chilled water in summer and fan coil units (FCU) use hot water in winter (Yoshida 2006). We collected a large quantity of data on energy consumption, HVAC, and the weather, using the Building and Energy Monitoring System (BEMS).

In an office building, a reduction in energy consumption was achieved by improving the HVAC technologies and by using natural ventilation (Figure 4). The maximum energy consumption for this building was designed to provide for the needs of the residents. The calculations were based on the system running for 24 hours a day for 1 year. However, subsequently, the energy consumption was found to be about

Figure 2. Concept for the development of EEBB Source: Yoshida et al. 2008; Ichinose et al. 2008

60% of the designed value. After improving the air conditioning, the energy consumption of the building was reduced and we determined the maximum level for energy reduction with optimal control plus natural ventilation.

The results of monitoring showed good potential for seasonal energy minimization in this building. This condition required the residents’ indoor temperature be set at 27° C in summer and 22° C in winter. The project’s goal was achieved, including the resolution of mechanical problems, with these optimal settings (Yoshida 2009).

Case Study through EEBB in Nagoya

We used laser-point data provided by Kokusai Kogyo Corp. to construct a three-dimensional model (Figure 5) that used building blocks with seven-story buildings (i.e., floor

height 3.2 m). The average building height was 21.5 m. Inside the building blocks we set a sky-view factor (SVF) of 20% using CanopOn2 tool (Takenaka 2006), and the road width was 8 m (Figure 5).

As Figure 6 shows, the higher the buildings are, the more anthropogenic heat is emitted.

When generating blocks using the three-dimensional model, which was made by RayMan (Matzarakis et al. 2006), we set five values for the predicted mean vote (PMV) index, for five values of wind velocity, which were 0, 0.5, 1, 1.5, and 2 m/s (Figure 7). When the wind velocity decreased, the PMV value also decreased, thus reducing the thermal stress. When we changed the road width to 4 m, the effect of a change in wind velocity was not significantly different.

Figure 4. Change in cooling load by changing HVAC settings Figure 3. Building blocks (research flow)

Source: Yoshida et al. 2009 Analysis of local characteristics

⑥Population density of a block

⑦Heat island effects of quantitive evaluation

EEBB-model （1km×1km）

①Block form extracted

②Average block model value computed

③Indoor configuration (population, lighting, electric outlets)

⑤Air conditioning level calculated (day/hour)

④Amount of heat inflow computed from weather data

0 100 200 300 400 500 600 700 800

When designed

Chilled-and-hot water: Change in energy consumption by changing HVAC settings

FY2004 weekdays 10：00-18：00 4 Jul.:FCU chilled water change 1 Dec.:FCU hot water change

（Saturdays and Sundays and public holiday suspension）

*1 hour data

FCU chilled water

AHU chilled water FCU hot water

FCU chilled water AHU chilled water

FCU hot water

FCU chilled water AHU chilled water

FCU hot water

FCU/AHU　chilled-and-hot water [MJ/m2 ・Year]

FY2004 measurements

Ideal values after HVAC system improvements with

optimal control Summer:27℃

Winter:20℃

Ideal values after HVAC system improvements with

optimal control + natural ventilation

Figure 6. Heat load versus building height Nagoya）

Source: Urban Climate Simulation System (UCSS) developed by Dr. Ashie, Japan.

MOE developed a simple calculation tool, March 2002.

Figure 5. 3D-CAD model of Nagoya in 2005 and SVF on a 3D-model of the canopy Building blocks: Average building height 21.5m

Number of stories：7F (floor height 3.2m) Daytime population: About 20,000 people Day-and-night population ratio: About 500%

Tree cover ratio: 16%, Bare land ratio: 18%

Road width: 8ｍ B ildi h i h 20

0.0 130.1

34.5

0.0 117.2

69.0

1.4 109.2 102.9

1.9 99.8 137.2

15.7 94.3 169.3

-50 0 50 100 150 200 250 300

H eat lo ad （ W / ㎡ ）

2 4 6 8 10

Building height (Floor)

人工顕熱

対流顕熱

人工潜熱

蒸発潜熱

Anthropogenic heat

Anthropogenic latent heat Evaporative latent heat Convected sensible heat

Figure 7. PMV and wind velocity in Nagoya 1.5

2.0 2.5 3.0 3.5

0 0.5 1 1.5 2

Wind Velocity〔m/s〕

PM V 〔 - 〕

Road width 4m

Road width 8m

AM10：00, September 12, 2008 Outside temperature：28℃

Humidity：50％（Japan Meteorological Agency）

Nagoya

Building height 20ｍ

The situation was compared with the SET* for a general indicator adjusted to the human condition in Figure 8. We found that we needed a wind velocity of 1.0 m/s or more to keep the SET* at 28° C or below. An outside temperature of 28° C is the limit of human comfort according to ASHRAE standard 55 (ASHRAE 2004). Therefore, when the outside temperature is higher than 28° C, we need air conditioning inside buildings, and the outside environment requires the shade of buildings or trees. The effects of wind are also needed between buildings.

In terms of building-block types, it is easy to set an indicator using SVF. When increasing the road width, the SVF becomes larger and PMV exceeds 3.0 (Figure 9), reaching the level of extreme physiological thermal stress (Fanger 1972).

If we are to build low-carbon cities, we need to reach a level of comfort with respect to wind values. When planning the building blocks in Nagoya, we found that SVF values of less than 50% were appropriate.

Next, we analyzed the air-temperature distribution in average blocks using Computational Fluid Dynamics software (CFD2000). The parameters were as follows: we set a westerly

wind direction, a wind velocity of 2.0 m/s, an outside air temperature of 35 ℃, a wall-surface temperature of 35° C, a roof-surface temperature of 45° C, and a road-surface temperature of 45° C. The building height was set at 20 m. The standard k- ε model with X: 200 m × Y: 200 m × Z: 100 m accounted for the effect of turbulence. Depending on road width, the model provided different turbulence parameters for different monitoring points. Table 1 shows predicted air temperatures inside building blocks, using a CFD simulation for different road widths and monitoring point heights.

When we set the road width at 4 m and the monitoring point height at 1.2 m, the CFD simulation of the air temperature inside the blocks resulted in temperatures of 40° C on the windward side and 48° C on the leeward side of the buildings.

Increasing the height of the monitoring points from 1.2 to 20 m resulted in an increase in the air temperature of 6° C on the leeward side of the buildings. On the other hand, on the windward side, the temperature dropped slightly at monitoring points set 5 and 10 m above the road. Therefore, each building had a different condition with regard to the effective use of

Figure 8. SET* and wind velocity in Nagoya

25 27 29 31 33

0 0.5 1 1.5 2

Wind Velocity〔m/s〕

SET* 〔 ℃〕

Road width 4m Road width 8m

Building height 20ｍ

AM10：00, September 12, 2008 Outside temperature：28℃

Humidity：50％（Japan Meteorological Agency）

Nagoya

Figure 9. PMV and SVF in Nagoya 0.0

1.0 2.0 3.0 4.0 5.0

0% 10% 20% 30% 40% 50% 60% 70% 80%

Sky view factor[%]

PMV [-]

Road width 10m Road width 4m

Road width 8m

Nagoya

AM10:00, Semptember 12, 2009 Outside temperature：28℃

Humidity：50％

Wind velocity：0m/s

natural ventilation, depending on the wind direction.

When we changed the road width to 8 m, the influence of the outside environment was similar to that in the example of a 4 m road width. This model showed that building blocks with an 8 m road width can use outside air effectively when the building height is 5 m or 10 m.

As described below, when we increased the road width to 10 m, we observed a higher air temperature than in the two previous examples. Around monitoring points set at heights of 5 m and 10 m, we could use the outside air to effectively cool the air inside the buildings. When the monitoring points were at roof level (20 m), we found hot zones, which were probably the result of the heat transfer from roads and roofs. Therefore, this model should not be used for exploring natural ventilation.

The results provided an idea for how to reduce the energy consumption needed for cooling by using natural ventilation.

The settings were optimized and can be used for planning further studies.

In accordance with differences in window types, the FCU operation times were calculated for each side these building blocks (Figure 10) in Nagoya. In this analysis, we took into account the perimeter load for cooling in direct sunlight and kept the indoor environment comfortable for human beings for each building block. The results show that the southern perimeter zone had a beneficial effect on high-specification windows. The north, west, and east sides of buildings had little effect on cooling with the high-specification windows in the Nagoya building blocks (road width 8 m, building height 20 m).

Finally, we found the maximum energy reduction level

with regard to cooling load when the design conformed with Japanese building law for high-specification windows in Nagoya (road width 8 m, building height 20 m), as shown in Figure 11.

When buildings cast shadows, the cooling load decreases and people in the street feel more comfortable. This is the best way to develop low-carbon cities in Asia. As Figure 12 shows, real-time weather data help us measure energy effects accurately.

This will probably lead to the practical implementation of measures designed to combat climate change and heat islands in Asia, which is our primary goal.

Conclusion

To realize low-carbon cities, Asia must reduce the energy needed for cooling. According to our results, which revealed the dependence of the cooling requirement on the weather data and building arrangement, we can control HVAC efficiently. For example, in a case study in Nagoya, the sky-view factor was set at 50% or less. Using CFD simulations of air temperature around the buildings, we were able to achieve a comfortable temperature level by setting the building height at 5 m or 10 m.

Moreover, in Nagoya, the high-specification windows had a beneficial effect on the south side of buildings.

We focused on achieving a heat balance for cooling reduction, which we investigated to determine whether natural ventilation could be used in each building situation. Our research revealed an energy-savings potential we can calculate as basic data for each building-block type in different parts of Asia.

Table 1. Air temperatures inside building blocks predicted using CFD Road width Building’s side Monitoring point heights

1.2m 5m 10m 20m

4m Windward 40℃ 38℃ 38℃ 40℃

Leeward 48℃ 50℃ 52℃ 54℃

8m Windward 39℃ 38℃ 38℃ 39℃

Leeward 52℃ 53℃ 54℃ 55℃

10m Windward 40℃ 38℃ 38℃ 38℃

Leeward 48℃ 52℃ 54℃ 56℃

Figure 10. FCU operation time for cooling load in each perimeter zone

References

ASHRAE Standard 55-2004. Thermal environment conditions for human occupancy. ASHRAE

Chikada, M., Inoue. T, et al., 2001, Evaluation of Energy Saving Methods in a Research

Institute Building, CCRH, PLEA2001-The 18th Conference on Passive and Low Energy Architecture, Florianopolis-BRAZIL:

883-888.

Fanger, P.O., 1972, Thermal Comfort, New York, McGraw Hill Book Company.

Ichinose, Toshiaki et al., 2008, Counteracting Urban Heat Islands in Japan, Urban Energy Transition: From Fossil Fuels to Renewable Power, Elsevier Science Ltd, ISBN-13978-0080453415

Matzarakis, A., Rutz F. and Mayer H., 2006, Modeling the Figure 12. Image of demographic system EEBB using Google MAP (Nagoya)

Figure 11. Annual heating and cooling load for air conditioning 20

10 0 10 20 30 40

H ea ti ng /C ool ing loa d〔W /㎡〕

37%

19%

19% 25%

Cooling load for interior

（ summer ）

Standard weather data in Nagoya (FY2000)

Cooling load for perimeter Heating load for perimeter

Cooling load for interior

（ winter ）

Office

233_{MJ/㎡・year}

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

1 hour data

Cooling load for perimeter

Cooling load for

interior (winter) Cooling load for interior

（summer） Heating load

for perimeter

City name

Population

- 48 -

Area Population ratio

Area ratio

My SQL5.04 PHP5.1.6 Apache2.2.3

Air-conditioning mode

thermal bioclimate in urban areas with the RayMan model, PLEA2006-The 23th Conference on Passive and Low Energy Architecture

Murakami. S, Levine D. M, H. Yoshino. H, Inoue. T, Ikaga. T, Shimoda. Y, Miura. S, et al., 2006, Energy Consumption, Efficiency, Conservation, and Greenhouse Gas Mitigation in Japan's Building Sector,

http://repositories.cdlib.org/lbnl/LBNL-60424/

Takenaka, A., 2009, CanopOn2, http://takenaka-akio.cool.ne.jp/

etc/canopon2/, 449-453

Yoshida, Yukiko et al., 2006, Development and testing air conditioning and lighting technologies to reduce CO2

emissions in the commercial sector, First International Conference Carbon on Management at Urban and Regional Levels, Connection Development Decisions to Global Issues, Mexico City: Global Carbon Project

Yoshida, Yukiko, 2006, Development of air conditioning technologies to reduce CO2 emissions in the commercial sector, Carbon Balance and Management, 1:12; doi:

10.1186/1750-0680-1-12.

Yoshida, Yukiko et al., 2008, Development of environmental information system to reduce energy consumption in buildings using BAC-net, Proceedings of the 2008 World Sustainable Building Conference, Volume 2, SB08-ISBN978-0-646-50372-1, Melbourne

Yoshida, Yukiko and Toshiaki Ichinose, 2009, Towards low carbon cities in rapidly urbanizing Asia: climatic change mitigation strategy in building sector, Second International Conference Carbon on Management at Urban and Regional Levels, Connection Development Decisions to Global Issues, Nagoya: Global Carbon Project

Yoshida, Yukiko and Toshiaki Ichinose, 2009, Planning low-carbon society based on building- urban environmental evaluation in Asia, 7th International Science Conference on the Human Dimensions of Global Environmental Change, IHDP Open Meeting 2009, Bonn

Yoshida, Yukiko and Toshiaki Ichinose, 2009, Research and development of the information system for building-blocks environmental evaluation, The 7th International Conference on Urban Climate ICUC-7, Yokohama

Yoshida, Y., 2009, Development of Air Conditioning Technologies, Cooling India, Chary Publications Pvt. Ltd., Mar-Apr ’09, 58-62

(Received Feb 9, 2012, Accepted Oct 10, 2012)