In welfare facilities for the elderly, from the viewpoint of hygiene, a lot of attention is paid to ventilation and humidification. However, excessive ventilation in winter promotes the inflow of outdoor air with low temperature and humidity, and brings low humidity, cold draft, and increase in heating load. Furthermore, the airflow route in a facility should be designed to minimize infection or odor diffusion. It is important to grasp the airflow distribution of whole the building quantitatively. However, it is not easy to clarify it by measurements, especially for building with a large scale. In this study, measurements of indoor environment on site along with the multiple interzonal airflow analysis were conducted for a welfare facility for the elderly in Hokkaido. The distributions of air temperature, humidity and CO₂ concentration in the building were measured through a winter. As the results, it was shown that the indoor absolute humidity and CO₂ concentration became decreased during the operation of an exhaust fan in the kitchen with a large capacity. The decrease occurred even in a room far from the kitchen, and thus it was suggested that the exhausting air from the kitchen predominated the indoor environment of the whole building, and that the air from various spaces in the facility was gathered to the dayroom located next to the kitchen. In addition, an interzonal airflow analysis was performed for this whole building to calculate airflow distribution for a representative day in winter, considering the estimated opening areas, the operating time and airflow rate of all the exhaust fans including kitchen, toilet, bathroom, and the other rooms in the facility, with the air temperature distribution determined based on measured values. The CO₂ concentration and absolute humidity balance equations were solved simultaneously, by determining generation rate from persons (CO₂ and moisture) and humidifier and bathroom (moisture). The calculated results of distributions of CO₂ concentration and absolute humidity were shown to agree well with the measure values. Based on the calculated results of this validated model, it was shown that the air quality of each bedroom satisfied a proper level. The air in the day service center significantly flow into the dayroom of the inhabitants of the facility, which was not proper from the viewpoint of infection control. On the other hand, during nighttime when the exhaust fan in the kitchen was stopped, the airflow was balanced within several blocks dominated by exhaust fans of toilet operated continuously. At last, analysis for two improved cases in ventilation operation were performed; a case of operating the kitchen fan intermittently and a case introducing direct air supply into kitchen equivalent with the exhaust airflow rate of the kitchen fan. As the results, it was shown that the increase in humidity, and saving in heat load are possible within an acceptable levels of increase in CO₂ concentration by intermittent operation in the kitchen and introducing direct air supply to the kitchen. Furthermore, in the latter case, although decrease in heat loss by air infiltration into building will be cancelled by heating the air supplied to kitchen, the airflow was balanced within several blocks in the building, which is a merit from the viewpoint of controls of infection or odor diffusion in the facility.

 To realize a Net-Zero Energy Building, it is necessary to reduce the amount of energy used for air-conditioning. To achieve this, one important factor is to reduce the outdoor air load. Extensive studies on this topic using cooling or heating pits have been carried out. However, when compared with the surface temperature of a cooling pit, the dew point temperature of outdoor air is high in the summer, and this leads to dew condensation inside the pit. In such cases, there is a higher likelihood of microbial contamination.

 In this study, bacterial communities from the air and surface of a pit, and from two offices, were collected during the summer of 2018 and the winter of 2019. For each sample, variable region 4 (V4) of the bacterial 16S ribosomal RNA (rRNA) gene was amplified by a polymerase chain reaction (PCR) using the primer set 5’-acactctttccctacacgacgctcttccgatct-GTGCCAGCMGCCGCGGTAA-3’(515F) and 5’-gtgactggagttcagacgtgtgctcttccgatct-GGACTACHVGGGTWTCTAAT-3’ (806R). The 16S rRNA amplification protocol version 4_13 was used as a pretreatment with the Next-Generation Sequencer (NGS, Illumina MiSeq system). DNA quality was checked using the Agilent 2200 TapeStation. All samples with the necessary quality and quantity of nucleic acid for analysis were then analyzed. The produced sequence library was mixed, and to improve its quality, a refining process using the AMPureXP PCR purification system (Beckman Coulter, Inc.) was carried out.

 The main results obtained by this study were as follows.

 (1) A total of 20 phyla were detected in the summer and winter. The major phyla accounting for 96.4% of those detected were phylum Proteobacteria (41.0%), Firmicutes (20.2%), Actinobacteria (11.4%), Bacteroidetes (9.1%), Cyanobacteria (7.2%), [Thermi] (3.8%), Fusobacteria (3.7%). As these phyla were detected in other buildings in a previous study, they are apparently the main bacterial phyla in the general environment.

 (2) On the surface of the pit, genus Nesterenkonia, which was detected at ≥1% only in the summer, decreased remarkably over the course of one year during the completion of the building. Moreover, a principal coordinate analysis suggested that bacteria flora change depending on human activity or the progression of time.

 (3) Although the office influenced the bacteria in the pit, the original bacterial flora formed over time and under the influence of the building occupants.

 (4) In the pit, as airborne bacteria downstream might affect the indoor bacteria, it is important to control microbial contamination.

 Information and communication technologies such as artificial intelligence and internet of things have developed significantly in recent years, and the concept of “Digital-Twin” that imitate actual world in a cyber space has been created. It is expected that new value will be created by connecting actual world and cyber space seamlessly. Effort to save energy using ICT have been conducted for building facilities, and among them, building automation systems, central monitoring systems, building energy management systems and simulations are representative. Simulations have important parts for planning and design as WHITE-BOX models. On the other hand, ANN models are expected accurate reproduction performance as BLACK-BOX models. We aim building "Digital-Twin", and evaluated the building method of ANN models based on operation data.

 In this report, the target of ANN models is absorption chiller heater utilizing waste heat, it is evaluated that the parameters such as mini-batch size, construction of hidden layers and number of output nodes influence predictive accuracy and calculation time. The heat source system has a micro cogeneration system, solar collectors, a cooling tower and a heat exchanger as peripheral equipment, chilled and hot water which is generated by them is used in air handling units.

 The influence of mini-batch size are shown below, the details are in Chapter 3. Increasing the mini-batch size increased the learning times for convergence, however the calculation time for 20,000 epochs was reduced up to 60%, on the other hand, the predictive accuracy improved as decreasing the mini-batch size. Therefore it is suggested that the mini-batch size with well-balance of predictive accuracy and calculation time is 64.

 There are two composition parameters of ANN models, one is composition of hidden layers, and the other is composition of output layer. The result of evaluation is shown below, and the details are in chapter 4. However, considering the preceding result, the composition of ANN models which mini-batch size is 64 is evaluated. The number of nodes in the output layer part of ANN models has less influence on predictive accuracy than the composition of the hidden layer. When the nodes of hidden layers had 50-50 or more, the influence by the number of nodes in output layer could be ignore, there was no difference in predictive accuracy, moreover the coefficient of determine were as high as about 0.99 for outlet temperature and about 0.97 for gas and power consumption.

 As a conclusion, in order to imitate a heat source system with hourly data for one year using ANN, it is well-balance that the ANN model has 50-50 of hidden layers, 5 of output nodes and 64 mini-batch size. In general heat source equipment, the types and number of input and output information are mostly same, therefore this method can be applied to a lot of heat source equipment. However, more complex ANN models are needed to improve the predictive accuracy for gas and power consumption.

 This study proposes operational strategies for combinations of equipment, including an electric vehicle (EV), in a house using self-consumption. The aim of this is to attain both comfort and efficient energy management under several household and regional conditions, focusing on the frequency of the EV’s use as well as the residents’ schedules. As operational strategies for self-consumption of surplus power, storage battery (BT) charging, EV charging and daytime operation of heat pump water heater (EC) was assumed. The effect of introducing each piece of equipment was compared using an evaluation index based on the storage battery capacity equivalent. Moreover, the amount of self-consumption, CO₂ emissions, and the cost-effectiveness of different equipment combinations were calculated and compared. These effects were shown to be different depending on household conditions.

 The following observations are reported in this article.

 1) The amount of self-consumption in case of EV introduction was high when the EV is used infrequently, with a maximum equivalent amount of 12.5 kWh BT capacity. However, when the EV was used frequently, the amount of self-consumption in case of an EV alone was small.

 2) The amount of self-consumption in case of EC daytime operation was high (at a maximum equivalent amount of 3.6 kWh BT capacity) when the residents were absent for a long daytime period, and there was a plentiful hot water supply.

 3) The increase in CO₂ emissions in homes due to the increased frequency of EV use and the decrease in self-consumption was greater than the CO₂ emission reduction of an EV.

 4) By using the BT and the EC daytime operation in combination with the EV, it was possible to reduce the CO₂ emission and use the EV storage capacity effectively while increasing the self-consumption rate. In addition, it is shown that investing 1,200,000 to 600,000 yen in the introduction of EVs would carry the same economic burden as that under gas vehicle conditions with a similar self-consumption rate (80% or more).

 To achieve 1.5°C targets, it has been reported that it is necessary to reduce the net-CO₂ emission to zero. The most feasible zero-emissions scenario is the scenario that minimizes the energy demand to the lowest amount and not depends on the negative emission technology like Carbon Capture and Storage (CCS). However, it is not realistic to simply reducing energy demand by drastically improving efficiency of appliances or reducing the number of appliances to zero. It is necessary to express the change in efficiency in appliance stock by taking into account the time required for the dissemination of measures appropriately. In addition, reducing the number of appliances changes service level that occupants receive, so it must be done within the allowable range. In 2050, it is possible to not only improve the efficiency of appliances, equipment and building, but also to reduce energy consumption by the change of macro-frame and land-use. In this paper, considering these points, we analyzed the possibility of zero emission in the Japanese residential sector in 2050 through energy-saving measures and residential solar power generation, using a bottom-up simulation model. This model can reproduce the diversity of household energy consumption caused by their characteristics in region and national scale households, compare changes in energy consumption due to changes in equipment, behavior, and number of households on the same evaluation axis, and quantify the change in power demand by time.

 As the simulation result, without any measures added, the primary energy consumption in the Japanese household sector in 2013 and 2050 are 3080PJ and 1615PJ. Net energy consumption in 2050 is 532PJ. This indicates that to realize zero-emission in 2050, the current measure is not enough and more stringent measures need to be implemented.

 In this paper, three types of measures were added to create zero-emission in 2050 as follows: Improvement of equipment and housing energy efficiency, reduction of equipment number, and operation of macro-frame. By implementing these measures and installing solar cells in all detached houses, it is possible to realize zero-emission from the net annual energy consumption in 2050. Especially, the energy saving effect of the heating and hot water is large. From 2013 to 2050, energy consumption of other home appliances account for a relatively large proportion of overall household energy consumption. Further, it is suggested that as energy consumption reduced significantly, the energy consumption will be less affected by changes in macro frames. This indicates that a certain “minimum energy” exists.

 As the result of the load curve, most power generation deficiency days and power generation excess days occur on different seasons. Since it is impossible to store electricity in the residential batteries across seasons, only a small amount of electricity generated by solar cells is available to be used in the residential sector. For better use of the energy from the solar cell, it is needed to transfer the energy to other sectors or to develop an energy storage system that able to store energy for a long time.