## 3 Results
### Calculation of \(CO_{2}\) Emissions
In the present study, it was assumed that the impact of power infrastructures for EV charging has already been accounted for in the analysis of the EV life cycle and was therefore excluded from the following calculations. Emissions due to the installation and operation of large-scale telecommunications, control, automation, processing, and data storage infrastructures. On the one hand, it is necessary to take into account the impact of infrastructure manufacturing (specific in time), and on the other hand, it is necessary to take into account the impact over time due to the flow of energy for charging EVs, and for their possible control. As stated [26], regarding the provision of EV charging: \"In order to enable these functionalities, however, additional equipment has to be installed, which, on the other hand, will lead to increased electricity consumption and more e-waste\". As the profile and quantity of infrastructure depends on the way EVs are interconnected in the network, it is necessary to analyze each of the modes proposed in the literature. As such, the information contained in Table 1 was used, which summarizes the theoretical characteristics of each of the integration modes referred to in point 1: NC, WCNC, V2G, and G2V. But, even excluding distribution network infrastructures (which will be dealt with separately in the next point), to make EV charging possible, new infrastructures will have to be installed in any case:  
* At least with cables, chargers, and meters for NC or WCNC mode. These components are almost all passive, meaning they have low active energy consumption. However, they cause additional Joule losses. It was considered that these were already included in the analysis of the life cycle of an EV. * In G2V mode, in addition to cables, chargers, and meters, it is also necessary to install cables and communications equipment and a certain level of processing with artificial intelligence (AI) to make decisions about the most appropriate option for the network, managing loads and priorities. Thus, in this mode, there is active consumption of some equipment (communications and processing), and losses in cables and equipment. * In V2G mode, there is a large increase in the necessary infrastructure [19] On the one hand, all EVs must be connected to the grid whenever they are parked, which implies having more grid connection infrastructures than the number of EVs, so that each EV can be connected at different locations. Vehicles are parked most of the time, but in different locations (e.g., at home at night, and at the workplace during the day or in a commercial area) [17]. This mode needs many more cables, chargers, and meters; it is also necessary to install many more cables and much more communication equipment and equipment dedicated to processing with AI and IOT to make decisions about the most suitable option for the network, for the loads and the priorities, as well as for large-scale data storage. Because there is more infrastructure and communication, in V2G mode, there will be more losses in cables and more active energy consumption in communication, processing, and storage equipment. Only in the cases of NC and WCNC modes is no relevant communications infrastructure required. For G2V and V2G modes, it is necessary to create a smart grid with a communications component, which will be larger in V2G mode. To study emissions due to communications, counting, and data processing infrastructures, it was considered that in G2V mode, the needs are equivalent to those required to implement a smart grid/smart metering. According to [26], the environmental impact of communication and information technologies to implement smart metering infrastructures (considering the entire life cycle and excluding infrastructures in homes) will be a loss of 6.8 to 14.3 PJ of exergy for 20 years, considering the city of Vienna (Austria). Around 33% of these values correspond to electrical energy consumption over time of use.