The first commitment period (2008-2012) under the Kyoto protocol has expired. This paper evaluated factors of GHG emissions in major countries under Annex I of the Kyoto Protocol and in the industries of the Keidanren’s Voluntary Action Plan on the Environment through decomposition analysis. The energy intensity improvement rate can be often observed to have a strong relationship with the economic growth rate. It is important to achieve stable improvement of energy and CO₂ intensity without economic conditions. This paper analyzed the correlation between annual changes in per-capita GDP and energy intensity of GDP as well as the intensity improvement rate. The energy intensity of Japan was not been improved greatly after 1990 compared with the improvements of many other Annex I countries. However, the improvements of Japan were achieved without strong correlation with per-capita GDP, while large improvements in some countries were induced by the improvement of per-capita GDP. The energy intensity of some of the business associations participating in the Keidanren’s Action Plan was worsened between 1997 and 2010/2012. According to the analyses of this study, the worsening of the intensity in the most of the associations were strongly affected by the decrease in economic activities.

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In order to expand the natural energy and the energy conservation, "The Smart Photovoltaic power generation (hereinafter referred to as PV) and Electric Vehicle (hereinafter referred to as EV) system" has been proposed and the effect has been clarified. However, the Smart PV and EV system has some problems to become common. It’s necessary to solve EVs problems which are short cruising range, high cost of storage battery and risk of dead battery. Therefore, Air-conditioner Integrated Electric Vehicle (hereinafter referred to as AI-EV) which has a greatly improving the mentioned above three performances has been proposed.
In this paper, the authors have studied the total energy consumption of the Smart PV and EV system in the case of using Gasoline Engine Vehicle, Hybrid Vehicle, EV and AI-EV. As a result, AI-EV can reduce CO₂ emissions by 20% almost the same as EV in the Smart PV and EV system. In addition, AI-EV is able to gain the cruising range more than twice as long as EV with the same battery capacity.

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The objective of this paper is to develop a method to evaluate the effect of the diffusion of photovoltaic systems on energy consumption in detached-houses in terms of cities, towns and villages. Household composition and residential conditions were divided into 156 categories, and a model was formulated for the calculation of differences in energy consumption between regions based on the number of households in each category and meteorological conditions. The results of estimations using this model for 50 areas throughout the country were subjected to statistical regression analysis, which derived correlated formulas that would make it possible to calculate the rate of reduction in electricity consumption in cities, towns and villages as well as the payback years for recouping the initial investment in a PV system. The formulas employed the average number of people in households, average floor space, temperature in an average year and hours of sunshine in an average year as explanatory variables. The formulas were applied to 1,055 cities, towns and villages throughout the nation, and the results suggest the relationship between the diffusion of PV systems and the payback years, and regional characteristics with regard to the effect of subsidies.

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