D

Journal of Energy and Power Engineering 8 (2014) 1933-1941

DAVID

PUBLISHING

A Novel Concept of AI-EV (Air-Conditioner Integrated Electric Vehicle) for the Advanced Smart Community Yu Notoji and Tsuguhiko Nakagawa Department of Thermal Engineering, Graduate School of Okayama Prefectural University, Kuboki 111, Japan Received: August 03, 2014 / Accepted: September 04, 2014 / Published: November 30, 2014. Abstract: In order to expand the natural energy and the energy conservation, “the smart PV (photovoltaic power generation) & EV (electric vehicle) system” has been proposed and the effect has been clarified. In the smart PV & EV system, it is important that electric vehicles become popular. Therefore, the AI-EV (air-conditioner integrated electric vehicle) has been proposed. In this paper, the AI-EV is designed based on the required car air-conditioner capacity. And, the value of AI-EV is compared with a gasoline vehicle, HV (hybrid vehicle) and EV using the mathematical simulation model. As a result, it is clarified that the minimum displacement of the small-engine is 120 cc for AI-EV. In the smart PV & EV system, AI-EV can reduce CO2 emissions by 20% almost the same as EV. Additionally, AI-EV is able to gain the cruising range more than twice as long as EV. Key words: Electric vehicle, air-conditioner, CO2 emissions, smart community.

1. Introduction After the Great East Japan Earthquake, it has become necessary to reduce nuclear power dependence and CO2 emissions. In one of the solutions, a smart PV (photovoltaic power generation) & EV (electric vehicle) system has been proposed [1]. In the system, it is not only to improve the energy efficiency of a car, but also to reduce the CO2 emissions from the total energy consumption of homes, vehicles and the working places. As a concrete method, PV power is charged directly to the EV battery, and EV is used as energy storage, energy transportation and levelling of PV output fluctuations. In the smart PV & EV system, it is important that electric vehicles become popular. In order to spread and expand electric vehicles, it should solve the issues of short cruising range, the high cost of storage battery and the risk of dead battery. Therefore, the authors have proposed AI-EV (air-conditioner integrated electric vehicle). In this paper, a car air-conditioner capacity is

Corresponding author: Yu Notoji, reseacher, research field: thermal engineering. E-mail: [email protected].

determined based on the heat transfer between inside and outside of the car. A mathematical simulation model which evaluates for the AI-EV energy consumption has been developed based on the thermodynamics that is the difference of the thermal efficiency between the power plant and the small-engine. And then, the value of the AI-EV is compared with conventional vehicles. The reduction of CO2 emissions and the vehicles’ performance are compared and the evaluation includes the home and working place.

2. Innovative Changes of the Energy System 2.1 Future Two-Way Energy System Fig. 1 shows comparison between “conventional system” and “future energy system”. The conventional system is adjusted supply quantity of fuel and electric power to consumption by fuel and electric company. Therefore, energy flow is in one direction from supplier to consumer. In order to introduce PV in the conventional system as shown in Fig. 2, PV power which is DC (direct current power) has to be converted to AC (alternating

A Novel Concept of AI-EV (Air-Conditioner Integrated Electric Vehicle) for the Advanced Smart Community

1934

Supply

Conventional system Gas stations Gasoline vehicles Houses

Factories Gasoline vehicles

Electric power

Public facilities

Future energy system New energy flow

Natural energy Houses

Factories

Electric vehicles

Electric power

Electric vehicles Public facilities

Natural energy Fig. 1 Future energy system.

Power plant

PV PCS Transformer

Power system

Transformer

Transformer DC AC

Home

EV AC/DC

Working place (University) DC/AC

Fig. 2 Conventional PV & EV system.

current power) into the current power system. In addition, PV power is converted from AC to DC when it charges the EV. On the other hand, PV generated

power, which depends on the weather, has a wide fluctuation. For this reason, supplying the PV power directly into the current power system causes fluctuations in the system frequency. Therefore, it is necessary to install a large secondary battery for levelling of PV output fluctuations when the supplied PV power will be increased into the power system. In this case, the total PV power utilization efficiency which is defined as “electric power consumption/amount of PV power generation” approximately 59% when PV power is supplied to a home through the use of a storage EV battery. This value is low. If the total PV power utilization efficiency is low, installation area and cost for PV are increased. Therefore, the system cost performance is deteriorated. The total PV power utilization efficiency can be calculated using the conversion efficiencies which are shown in Table 1 [2]. 2.2 Smart PV & EV System As shown in Fig. 3, the smart PV & EV system has been proposed to solve these issues which are described above. In the system, PV power is charged directly to the EV battery as DC. In the future system, it is considered to combine with a commuter EV and PV. The commuter EV is parked at an office or factory during the daytime on weekdays. So, PV is installed at the office or factory side of the working place, but is not installed at home. The generated PV power charges the EV storage battery directly in DC. When the EV battery level is full, generated PV power is supplied into the power source for the working place after being converted from DC to AC. And, if the charging level of the EV storage battery has some surplus power which is not including the necessary power for the next commute, the surplus power can be supplied directly to the home. So, this system is possible to minimize the number of conversions between DC and AC involving energy losses. When PV power is consumed only by EV driving, the total PV power utilization efficiency, which is calculated by the conditions of Table 1, is

A Novel Concept of AI-EV (Air-Conditioner Integrated Electric Vehicle) for the Advanced Smart Community

2.3 Issues of EV

Table 1 Conversion efficiency. Conversion efficiency PCS execution efficiency Transformer efficiency From charge to discharge efficiency Motor efficiency AC/DC converter efficiency (charging to EV) DC/AC inverter efficiency (supplying from EV) DC/AC converter (supplying from EV)

0.88 0.97 0.94 0.90 0.90 0.85 0.94

Power plant

Power system Transformer

Transformer

AC/DC Home DC/DC

DC AC EV

In the smart PV & EV system, it is important to spread and effectively utilize electric vehicles as shown before. Table 2 shows a performance estimation of gasoline vehicle, HV (hybrid vehicle) and EV. In Table 2, grey-zones show that EV is inferior to the gasoline vehicle and HV in some respects. In order to spread and expand electric vehicles, it should solve the issues of short cruising range, high cost of storage battery and the risk of dead battery. For solving these issues, a new concept vehicle is proposed.

3. Air-Conditioner Integrated Electric Vehicle 3.1 Basic Design of AI-EV

Working place (University)

The new concept vehicle is utilized as not only an PCS PV

Fig. 3 Smart PV & EV System. Table 2 Performance estimation of each vehicle. Gasoline HV vehicle Energy consumption × ○ Accelerating ○ ○ performance Cruising range ○ ◎ Quitness × ○ Conventional Eco-friendly × △ Running cost × △ Vehicles cost ○ △ Risk of losing energy ○ ○ Energy transport × △ Future Disaster response × △ CO2 emissions × △ ◎

1935

EV ◎ ◎ × ◎ ◎ ○ × × ○ ○ ○

= Excellent; ○ = good; △ = fair; × = poor.

85%. When PV power, which has been converted to AC, is supplied to home through the use of EV, the efficiency is 80%. On the other hand, the efficiency of 88% is achieved when PV power is supplied into DC to power electrical appliances, such as LED lights. In addition, the new system reduces the electric load of the current cable networks without the reverse power flow.

apparatus for locomotion, but also electricity transportation and a storage medium of electricity. The new concept vehicle is called AI-EV, which is integrated car driving power system, power storage system, power generation system and air-conditioning power system. A simplified image of AI-EV is shown in Fig. 4. As shown in the Fig. 4, AI-EV has a novel hybrid system which drives the air-conditioning system and generates electric power in the case of a low air-conditioning load through the use of a small-engine less than 200 cc displacement. The generated power is charged to the AI-EV battery. For this reason, AI-EV has a great possibility to solve three issues which are held by conventional EV. These issues are a short cruising range, the high cost of storage battery and the risk of the dead battery. At the same time, it is possible to reduce the initial cost of EV largely. AI-EV, as mentioned above, is a novel concept vehicle. PHEV (plug-in hybrid electric vehicle) has a typical traveling drive system which is combined an engine with a motor [3]. In contrast, the traveling drive system of AI-EV is a motor. So, both traveling drive systems are different. EV-REX (electric vehicle with range extender) has an engine power generation device,

A Novel Concept of AI-EV (Air-Conditioner Integrated Electric Vehicle) for the Advanced Smart Community

1936

Electric motor

Small engine Air conditioner

Compressor

Battery

Generator

q2  U 2  A2  T2  T4  　 t  q3 T  M 3  c pl  3 t t q4 T  V 4  c pa  4 t t q5   u 5  A5  c pa  T5 t q3  U 3  A3  T3  T4  t Constraint conditions are shown as follows:

Gas fuel

Photovoltaic power Fig. 4 A simplified image of AI-EV.

q2 q1

q5

q4

so it looks like AI-EV. However, a compressor of air-conditioner mounted EV-REX is driven by a motor. In contrast, a compressor of air-conditioner mounted AI-EV is driven by an engine. BEV (battery electric vehicle) is not mounted any engine. Therefore, AI-EV is different with all of the conventional types of vehicles. 3.2 Heat Balance Model in the Car Inside A car air-conditioner capacity is determined based on the heat balance model between the inside and outside of the car. As shown in Fig. 5, the inside of the car is heated or cooled depending on the weather conditions outside. This is shown by the heat balance equation which is defined as follow [4]:

0

 t

5

q

k 1

k

(1)

Each amount of heat transferred is defined as follows:

q1  u1  A1  c pa  T1 t

(2)

(5) (6) (7)

(8)

A1  A5

(9)

T5  T4

(10)

T4 t  0  T4(0) Fig. 5 The heat balance model with cooling.

(4)

u1  u 5

T3 t  0  T3(0)

q3

(3)

(11) (12)

where, t: elapsed time (sec); q1: enthalpy of air-conditioner output air (kJ/sec); q2: amount of heat transferred from outside (kJ/sec); q3: amount of heat reserving material (kJ/sec); q4: amount of heat reserving inside (kJ/sec); q5: enthalpy of discharged air to outside (kJ/sec); T1: air-conditioner output air temperature (K); T2: outside air temperature (K); T3: material temperature (K); T4: inside temperature (K); T5: discharged air temperature to outside (K); A1: air conditioner outlet area (m2); A2: surface area (m2); A3: material area (m2); A5: exhaust port area (m2); M3: mass of the material (kg); U2: total heat transfer coefficient of the car (W/(m2·K)); U3: total heat transfer coefficient of the material (W/(m2·K)); V4: inside volume (m3); u1: velocity of air-conditioner output air (m/sec); u5: velocity of discharged air to outside (m/sec);

A Novel Concept of AI-EV (Air-Conditioner Integrated Electric Vehicle) for the Advanced Smart Community

3.3 The Experiment U2 can be obtained by T2, T4, A2, and using Eq. (3). In this method, solar radiation is disturbance factor to calculate the total heat transfer coefficient U2. For this reason, T2 and T4 were measured at night while there is nothing solar radiation. The measured result is shown in Fig. 6. From Fig. 6, it is obtained that U2 is 30 W/(m2·K)). As the result, the required capacity of air-conditioner is able to calculate using the equation which is defined as follow:

q n  q 0－ q1

(13)

In this study, it is necessary to evaluate the performance of an actual vehicle, so an air-conditioner which was mounted on 2,000 model “Mira” was used. The refrigerating cycle of the air-conditioner is shown in Fig. 7. The performance of the air-conditioner is evaluated through the COP (coefficiency of performance). The COPC (cooling) and the COPH (heating) are given as follows [6]: h － h4 (14)    COPC  1 h2－ h1

Measured value /(m22・K) ·K) U2=20 W/(m U2=30 W/(m /(m22・K) ·K) /(m22・K) ·K) U2=40 W/(m

40 35 30 25 20

Measured Condition (night time) Temperature 5.3 ℃ Relative humidity 76.5 % Temperature 22.5 ℃ Inside air Relative humidity 35.9 %

15

Outside air

10 5 0

10 Pressure (Mpa)

condition has a temperature of 10 C and relative humidity of 100%. In this case, the required capacity of air-conditioner for cooling is 6 kW.

400

1200

Cooling Heating 3

1

4 h 3 , h4

0.1

200

2

Condenser

Expansion valve

3.4 Required Power of a Car Air-Conditioner The required compressor power of a car air-conditioner can be calculated based on the obtained air-conditioner capacity.

800 Time [sec] Time (sec)

Fig. 6 A comparison result of a measure and calculation about total heat transfer coefficient U2.

the use of an air-conditioner. For example, the outside condition has a temperature of 32 C, relative humidity of 60% and solar radiation of 0.8 (kW/m2). The target

(15)

where, COPC: coefficiency of performance of cooling;

where, q0: enthalpy of outside air (kJ/sec); qn: required capacity of air-conditioner (kJ/sec). Eq. (13) is shown as cooling (q0 > q1). In the case of heating (q0 < q1), positive and negative signs are reversed. That is to say, the required capacity for cooling is calculated based on the capacity to cool outside air to a target condition of car inside through

h2－ h3    h2－ h1

COPH 

Inside temperature (oC) Inside temperature [℃]

cpa: specific heat of the air (kJ/(kg·K)); cpl: specific heat of the material (kJ/(kg·K)). In Eq. (7), q3 is heat transfer due to the temperature difference between the inside air of the car and material. In order to calculate the heat transfer rate due to the temperature difference between the inside and the outside, Eq. (3) can be used. For that, it is necessary to know the total heat transfer coefficient U2. So, U2 is obtained through the following experiment [5].

1937

Evaporator

Compressor

1 h1

h2

300 400 Specific enthalpy (kJ/kg)

Fig. 7 Refrigerating cycle of Mira mounted air-conditioner.

1938

A Novel Concept of AI-EV (Air-Conditioner Integrated Electric Vehicle) for the Advanced Smart Community

COPH: coefficiency of performance of heating; h1: enthalpy of refrigerant at compressor (kJ/kg); h2: enthalpy of refrigerant at condenser (kJ/kg); h3: enthalpy of refrigerant at expansion valve (kJ/kg); h4: enthalpy of refrigerant at evaporation (kJ/kg); ηα: the efficiency of mechanical; ηβ: the efficiency of adiabatic compression of the gas. It is obtained that the COPC is 2.8 and the COPH is 3.1 under the condition of Table 3. The required small-engine displacement to drive the air-conditioner compressor was calculated by COPC, COPH, the required capacity of air-conditioner and the engine output characteristics. Specifically, the engines output characteristics were used of EX13-premium (displacement of 126 cc), EX17-premium (displacement of 169 cc) and EX21-premium (displacement of 211 cc) manufactured by FUJI Heavy Industries, Ltd. as general purpose. The result is shown in Fig. 8. Fig. 8 is shown an example of the cooling case. As the result, it is clarified that the required engine output is obtained by the required capacity of air-conditioner and COPC. And then, the engine displacement can be determined by the engines output characteristics. In this case, the required engine output is found to be 2.2 kW and the engine displacement is found to be 120 cc when the engine drives at 3,600 rpm.

Table 3 The condition of measured air-conditioner capacity

4. Evaluation of Smart PV & EV System

the evaluation was performed based on the HEX model

As the above results, it is clarified that the required Required Power(kW) [kW] RequiredCompressor compressor power

Temperature (oC)

Relative humidity (%) 60.0 o

COPH

Temperature ( C)

5.0

Relative humidity (%) 80.0

Output of air-conditioner 10.0 100.0 50.0 5.6

engine displacement of AI-EV is less than one-fifth of that of conventional gasoline vehicles. However, AI-EV is concerned to increase CO2 emissions compared with conventional EV, because AI-EV should consume fossil fuels in a small-engine. Accordingly, the value of the AI-EV has been evaluated for the reduction of CO2 emissions and the level of economic efficiency in the smart PV & EV system. 4.1 Evaluation of New Energy System (HEX Model) In a future energy system, which has been expected by the authors, PV generating electricity in an arbitrary place and electricity is transported and stored by EV. Therefore, it is necessary to calculate energy balance in each area. Additionally, unitary evaluation of the different energies, such as electricity, city gas, gasoline, etc., is very important. So, it is extremely difficult to evaluate by the “network type model”. For this reason, which is novel simulation model dividing the study area by hexagons. This model has been developed refers to numerical analysis method of the flow

3600[rpm] 3,600 rpm

4

COPC

Outside condition 32.0

analysis method and the heat transfer analysis using the control volume. The image of HEX model is shown in

3

Fig. 9 [7]. According to the energy balance of every HEX

2

(hexagon), it is necessary to calculate the energy

1

variation with energy outflow and inflow between adjacent HEXs. Additionally, the type of energy

2 4 6 8 Requiredcapacity capacity of Required air-conditioner (kW) Air-Conditioner [kW]

80 120 160 200

outflow and inflow into the HEX is different such as

Engine [cc] Enginedisplacement displacement (cc)

electricity, city gas and gasoline. Therefore, in HEX

Fig. 8 Determination logic displacement mounted on AI-EV.

of

the

small-engine

position (i, j), the basical equation of energy outflow and inflow from a boundary is defined as follow:

A Novel Concept of AI-EV (Air-Conditioner Integrated Electric Vehicle) for the Advanced Smart Community

1939

Table 4 PV data. PV data Output unit area PV area Total power

190.0 W/m2 12.5 m2/unit 2.4 kW

Table 5 AI-EV data.

Fig. 9 HEX model.

eijkmt 

n5

e r 1

ijrt

(16)

The energy variation of HEX with energy outflow and inflow in calendar time γt is defined as follow: n3

EFijmt   t  eijkmt

(17)

k1

where, i: HEX position of study area in a x-axis direction; j: HEX position of study area in a y-axis direction; k: boundary of HEX; m: kind of energy; r: method of energy transportation; γt: calendar time; n5: the number of energy transportation; n3: the number of boundary; et: the particular energy variation with time γt; EFijmt: the energy variation of HEX with outflow, inflow energy. 4.2 Calculated Condition In this case study, four different types of vehicles were simulated, a gasoline engine vehicle, a HV, an EV, and an AI-EV. The vehicles were simulated driving for a commuting between home and OPU (Okayama Prefectural University) once a day for a year. The PV data is shown in Table 4. Amount of PV power generation is calculated based on an annual weather database which has hourly solar radiation data and reflected PV power fluctuations caused by the weather, the season and the time [8]. And, the AI-EV data is shown in Table 5.

AI-EV data Electricity consumption (AI-EV) Available capacity of the battery The capacity of the battery Commuting distance Commute day Displacement of engine

9.1 km/kWh 20%-100% 24.0 kWh/unit 28.0 km/day 242.0 day/year 120.0 cc

AI-EV uses LPG (liquefied petroleum gas) to drive a small-engine. The average commuting distance of workers in OPU is 28 km/d and the average running speed is 30 km/h. Additionally, the CO2 emission coefficient of gasoline is 2.62 kg-CO2/ℓ, the CO2 emission coefficient of electricity is 0.657 kg-CO2/kWh (2011 The Chugoku Electric Power Company, Inc.), the CO2 emission coefficient of LPG is 3.48 kg-CO2/kg [9].

5. Analysis Result 5.1 CO2 Emissions A comparison result of the annual CO2 emissions through the use of each vehicle in this system is shown in Fig. 10. Reduction rate of CO2 emissions based on the gasoline vehicle is also shown in Fig. 10. In Fig. 10, in the smart PV & EV system, AI-EV is expected to reduce CO2 emissions of 20% compared with gasoline engine vehicle. The effect is almost the same as EV. The reduction value of CO2 emissions is three times as the value of HV. The reason is that the difference of energy conversion efficiency which is changed from fuels to using a car air-conditioning power. In the AI-EV, small-engine efficiency is 37.0%. When it is considered the driving and mechanical losses, the total efficiency from fuels to using a car air-conditioning power is 35.2%. On the other hand, EV has to be charged

A Novel Concept of AI-EV (Air-Conditioner Integrated Electric Vehicle) for the Advanced Smart Community

12

11.9

Gasoline

CO emission (t-CO /year) CO2 2emissions [t-CO22/year]

1.4 10 Electricity 8 6 4

of Home

3.6

11.2

0.7 3.6

6%

250

21%

20% 9.5

9.4

LPG 0.3

3.1

2.9

Electricity of Workplace

6.9

6.9

6.3

6.3

2 0

Gasoline Vehicle

HV

Smart PV & EV SMART PV(EV) & EV (EV)

Smart PV & SMART PV &EV EV (AI-EV) (AI-EV)

Fig. 10 A comparison of annual CO2 emission.

electricity from the conventional power system when the weather is bad such as rain. In the conventional power system, power generation efficiency is 36.8% at receiving terminal (2010 result in Japan). When it is considered that the AC ⇔ DC conversion and charge   discharge losses, the total efficiency from fuels to using a car air-conditioning power is 26.6%. Therefore, the total reduction of CO2 emissions in the smart PV & EV system using by AI-EV is almost the same as the Smart PV & EV System. 5.2 Performance of AI-EV as a Vehicle The maximum cruising range of EV and AI-EV in summer season is shown in Fig. 11. In Fig. 11, the limit cruising range of EV is 100 km in the case of driving in a city area (in other words, average speed 32 km/h) in the summer seasons. On the other hand, the maximum cruising range of AI-EV which is mounted a 120 cc displacement engine is more than 200 km under the same condition as above mentioned EV. Consequently, AI-EV is able to gain the maximum cruising range approximately twice as long as EV in a city area. The reason for this is that the AI-EV cruising range is extended by the effect of the hybrid system which drives the air-conditioning system and generates electric power in the case of a low air-conditioning load. As the results show, it is clarified that AI-EV is able to solve the issues of conventional EV. Therefore, it is considered that the smart PV & EV system using by

Cruising range (km) Cruising range [km]

1940

AI-EV (120cc) EV

200 150 100 Outside temperature Relative humidity Solar radiation

50 0

20

30 30

32.0 ℃ 60.0 % 0.8 kW/m2

40 50 50 60 60 70 70 80 80 90 90 40 Average running running speed Average speed[km/h] (km/h)

100 100

Fig. 11 Extend of the maximum cruising range.

AI-EV can be adapted for Europe and America where commuting distances are often over 50 km for one way.

6. Conclusions A car air-conditioner capacity is determined based on the heat transfer between inside and outside of the car. A mathematical simulation model which evaluates for the AI-EV energy consumption has been developed based on the thermodynamics that is the difference of the thermal efficiency between the power plant and the small-engine. And then, the value of the AI-EV is compared with conventional vehicles. The reduction of CO2 emissions and the vehicles’ performance are compared and the evaluation includes the home and working place. The following conclusions are obtained: A novel concept car of AI-EV has been proposed and verified the effects based on the heat transfer and thermodynamics; In the smart PV & EV system, AI-EV is expected to reduce CO2 emissions of 20% which is compared with a gasoline vehicle. The effect is almost the same as that of EV; The AI-EV’s performance as a vehicle in a city area, AI-EV is able to gain the maximum cruising range approximately twice as long as EV. Therefore, AI-EV can solve the issues of conventional EV; Therefore, it is considered that the smart PV & EV

A Novel Concept of AI-EV (Air-Conditioner Integrated Electric Vehicle) for the Advanced Smart Community

system using by AI-EV can be adapted for Europe and America where commuting distances are often over 50 km for one way.

[4]

Acknowledgments

[5]

We would like to express our gratitude to JST (Japan Science and Technology Agency) for their financial support.

[6]

References [1]

[2]

[3]

Kose, N., Nakagawa, T., and Shinohara, K. 2012. “Design Method of PV and EV Combined System Using a HEX Model.” Journal of Chemical Engineering of Japan 38 (6): 415-23. Mitsumoto, Y., and Nakagawa, T. 2013. “High Rate Interactive Energy System through the Use of PV & EV.” Presented at ASME 2013 Power Conference, Boston, United States. Hori, M. 2007. “Plug-in Hybrid Vehicles for Energy and Environment.” Society of Automotive Engineers of Japan

[7]

[8]

[9]

1941

38 (2): 265-9. Shimono, K., Shibata, S., and Nakagawa, T. 2013. “Air-Conditioner Integrated Electric Vehicle.” Presented at 2013 Japan Society of Mechanical Engineers Thermal Engineering Conference, Hirosaki, Japan. Fujiwara, K. 2009. Automotive Air-Conditioner, Automotive Air Conditioner Society of Engineers. Tokyo: Tokyo Denki University Press, 43-7. Dong, J., Chen, J., Chen, Z., Zhang, W., and Zhou, Y. 2007. “Heat Transfer and Pressure Drop Correlations for the Multi-louvered Fin Compact Heat Exchanger.” Energy Conversion and Management 48 (5): 1506-15. Kose, N., and Nakagawa, T. 2013. “Effective Method of Renewable Energy by Using Electric Vehicles and Evaluation by the HEX Model.” Journal of Japan Society of Energy and Resources 34 (4): 18-26. Japan Meteorological Agency. 2010. “Climate Statistics.” Accessed March 2, 2014. http://www.data.jma.go.jp/ obd/stats/etrn/index.php. Ministry of the Environment. 2012. “Publication of Electric Power Companies-Specific Emission Factors at 2011.” Accessed May 16, 2013. http://www.env.go.jp/ press/press.php?serial=15912.