Method for monitoring consumer-specific operational costs of at least one component of an HVAC system Field of the invention The present invention relates to a method for monitoring consumer-specific operational costs of at least one component of a heating, ventilation and air conditioning (HVAC) system. Background of the invention For efficiently controlling an HVAC and correctly allocating the costs for operating the HVAC, the building supplied by the HVAC is divided into zones that can be associated to different tenants. Exemplary buildings are residential homes, apartments, hotels, office buildings, schools, factories, and work shops. The zones can be separated spaces such as for example different rooms of a home or they can be areas of a large enclosed space such as an airport or an open-space office. The building, or sometimes each zone, has at least one inlet for the supply of an air flow and generally at least one outlet for removal or return of the air flow. Usually, sensors are used to detect the air flow into and out of the respective zone. The costs for the supply of conditioned air into the zones are usually calculated using the information of the detected air flow. The sensors observe different parameters such as an air flow, air pressure, , air temperature, and air humidity in order to find out which zone is contributing to what extend to the total costs of operating the HVAC. To correctly monitor all the data in a building, a vast amount of sensors must be installed. Due to a considerable likelihood of failure of such sensors, the maintenance requirements are quite significant. Moreover, integrating the sensors in the duct system or components such as inlets and outlets has a negative impact on the HVACs performance. For example, dust or dirt may build up on the sensors or on their carriers, which may compromise the flow characteristics. Despite a decrease in measurement accuracy of the sensors, repair or exchange of the sensor is expensive as well. Furthermore, a pure input/output observation is not always reflecting reality because what happens in between is fully neglected. A new holistic approach in determining a consumer- specific cost share for operating a multi-zone HVAC is needed. Object of the invention It is thus an object of the present invention to provide an improved method for monitoring consumer-specific operational costs of at least one component of an HVAC system, which HVAC system supplies at least a first zone and a second zone of a building with conditioned air. The solution proposed by the invention is specified by the features of the independent claims. The method according to the invention is specifically allowing a lean, efficient, and yet accurate determination of a fair allocation of HVAC costs. Especially, the inventive method then allows for optimally reflecting reality because different usages and conditions in different zones can be taken into account with any desired degree of precision, even with a reduced number of sensors. Summary of the invention The invention relates to a method for monitoring consumer-specific operational costs of at least one component of an HVAC system, which HVAC system supplies at least a first zone and a second zone of a building with conditioned air, wherein the method comprises the following steps for each of n time intervals with n ^ 1, wherein i = 1,…,n and wherein i and n א ^: determining i-th first usage data characterizing a usage of the first zone during an i-th time interval, especially characterizing a use-related change in air properties in the first zone during the i-th time interval, determining i-th second usage data characterizing a usage of the second zone during the i- th time interval, especially characterizing a use-related change in air properties in the second zone during the i-th time interval, determining an i-th first cost sharing coefficient based at least on the i-th first usage data, said i-th first cost sharing coefficient associated with the first zone, and determining an i-th second cost sharing coefficient based at least on the i-th second usage data, said i-th second cost sharing coefficient associated with the second zone. In particular, in such an HVAC system, a heat exchanger is connected to a primary flow path with a supply line and a return line, wherein a heat transfer medium, e.g. water, enters the heat exchanger through the supply line with an inlet temperature and exits the heat exchanger with an outlet temperature via the return line, and wherein the heat exchanger transmits a heat flow to the air flowing through an air flow path, which enters the heat exchanger with a supply air temperature and a supply air humidity und which exits the heat exchanger with a conditioned air temperature and a conditioned air humidity. In particular, one exemplary HVAC component, of which the consumer-specific operational costs are monitored, is the heat exchanger. The operational costs of the heat exchanger are, for example, determined based on a difference between the inlet temperature and the outlet temperature of the heat transfer medium. Additionally maintenance costs, and replacement costs of the heat exchanger can be considered. In particular, a further HVAC component would be a respective valve in the supply line and/or return line of the heat exchanger for regulating the flow of the heat transfer medium, in particular also for measuring said inlet temperature and said outlet temperature of the heat transfer medium. Operational costs of these valves would comprise at least one of costs caused by the electricity for controlling them, maintenance costs, and replacement costs. In particular, the operational costs of at least one component of an HVAC system include costs for the provision of a hot and/or cold fluid, especially water and/or air. For example, these costs include cost, especially electricity costs, for operating an electrically operated heating and/or cooling device, e.g. an electric heater. Additionally, maintenance costs and/or replacement costs associated with the provision of a hot and/or cold fluid can be considered as well. In particular, determining the i-th first cost sharing coefficient is further based on the i-th second usage data. In particular, determining the i-th second cost sharing coefficient is further based on the i- th first usage data. In particular, said i-th first cost sharing coefficient associated with the first zone is relating to or applicable to i-th operational costs of the at least one component of the HVAC system. In particular, said i-th second cost sharing coefficient associated with the second zone is relating to or applicable to i-th operational costs of the at least one component of the HVAC system. In particular, the i-th operational costs are operational costs of the at least one component of the HVAC system incurring during the i-th time interval. In particular, the i-th first usage data comprise data relating to occupation. In particular, the i-th first usage data comprise at least one of an amount of occupants in the first zone, a duration of occupation of the first zone, a frequency of occupation of the first zone, and a chronological pattern of occupation of the first zone. In particular, the i-th second usage data comprise at least one of an amount of occupants in the first zone, a duration of occupation of the first zone, a frequency of occupation of the first zone, and a chronological pattern of occupation of the first zone. In particular, said occupants/occupation can be understood as referring to human occupants/occupation of at least one of a work desk, a work machine, and a manufacturing machine. In particular, the i-th first usage data comprise at least one of a seating distribution, a seating density, and locations of single seats. In particular, said occupants/occupation can however also be understood as referring to object occupants/occupation, i.e. to presence of one or more objects that act as heat sink or heat source. For example, the usage data may reflect usage of electronic devices that may cause influence on the air quality in the respective zone. In particular, the i-th second usage data comprise at least one of a seating distribution, a seating density, and locations of single seats. In particular, at least part of the i-th first usage data are selected, determined, received, or measured. In particular, at least part of the i-th second usage data are selected, determined, received, or measured. In particular, at least part of the i-th first usage data are collected (i.e. received and/or measured) by sensors, e.g. comprised by at least one of a seat, a work desk, a ceiling, a wall, a work machine, and a manufacturing machine. In particular, at least part of the i-th second usage data are collected (i.e. received and/or measured) by sensors, e.g. comprised by at least one of a seat, a work desk, a ceiling, a wall, a work machine, and a manufacturing machine. In particular, at least part of the i-th first usage data are selected or determined by a human user. In particular, at least part of the i-th second usage data are selected or determined by a human user. In particular, the i-th first cost sharing coefficient and the i-th second cost sharing coefficient relate to the operational costs of at least one component of an HVAC system. Therefore, the i-th first cost sharing coefficient and the i-th second cost sharing coefficient are configured to split these operational costs of at least one component of an HVAC system in accordance with a usage intensity of the first zone and second zone and potentially further zones. In some embodiments, the method further comprises the following steps for each of the n time intervals: determining i-th first inflow data characterizing a first conditioned air supplied by the HVAC system and flowing into the first zone during the i-th time interval, wherein the i-th first usage data comprise the i-th first inflow data, and determining i-th second inflow data characterizing a second conditioned air supplied by the HVAC system and flowing into the second zone during the i-th time interval, wherein the i- th second usage data comprise the i-th second inflow data, in particular wherein the i-th first inflow data are collected by a first conditioned air sensor, in particular a first conditioned air ultrasonic flow sensor, and the i-th second inflow data are collected by a second conditioned air sensor, in particular a second conditioned air ultrasonic flow sensor. In particular, a conditioned air sensor for example is selected from a flow sensor, air temperature sensor, a humidity sensor, a pollution sensor, an organic compounds (VOCs) sensor, a nitrogen oxide (NOx) sensor, a carbon-dioxide sensor, a particle matter sensor, a dust sensor, a virus sensor, a pollen sensor, an odorant molecule sensor and an encoder of a ventilation flap. In particular, a conditioned air ultrasonic flow sensor is a type of flow meter that measures the velocity of a fluid with ultrasound to calculate volume flow. Using ultrasonic transducers, the flow meter can for example measure the average velocity along the path of an emitted beam of ultrasound, by averaging the difference in measured transit time between the pulses of ultrasound propagating into and against the direction of the flow or by measuring the frequency shift from the Doppler effect. Also, there are flow sensors that measure the transit times of surface acoustic waves between ultrasonic transducers (SAW sensors). Although such sensors are known per se, they have been shown to be especially suitable for the method according to the invention. In particular, the i-th first inflow data are collected in proximity to a first conditioned air inlet, in particular to a first conditioned air ventilation flap, located in or at least leading to the first zone. In particular, the i-th second inflow data are collected in proximity to a second conditioned air inlet, in particular to a second conditioned air ventilation flap, located in or at least leading to the second zone. In particular, the first conditioned air sensor is configured for detecting at least one air property of the first conditioned air. In particular, the second conditioned air sensor is configured for detecting at least one air property of the second conditioned air. In some embodiments, the method further comprises the following steps for each of the n time intervals: determining i-th first outflow data characterizing a first exhaust air flowing out of the first zone during the i-th time interval, wherein the i-th first usage data comprise the i-th first outflow data, and determining i-th second outflow data characterizing a second exhaust air flowing out of the second zone during the i-th time interval, wherein the i-th second usage data comprise the i-th second outflow data, in particular wherein the i-th first outflow data are collected by a first exhaust air sensor, in particular a first exhaust air ultrasonic flow sensor, and the i-th second outflow data are collected by a second exhaust air sensor, in particular a second exhaust air ultrasonic flow sensor. In particular, similar to the conditioned air sensor described above, an exhaust air sensor is for example selected from a flow sensor, air temperature sensor, a humidity sensor, a pollution sensor, an organic compounds (VOCs) sensor, a nitrogen oxide (NOx) sensor, a carbon-dioxide sensor, a dust sensor, a particle matter sensor, a virus sensor, a pollen sensor, an odorant molecule sensor and an encoder of a ventilation flap. In particular, the i-th first outflow data are collected in proximity to a first exhaust air outlet, in particular to a first exhaust air ventilation flap, located in or at least leading away from the first zone. In particular, the i-th second outflow data are collected in proximity to a second exhaust air outlet, in particular to a second exhaust air ventilation flap, located in or at least leading away from the second zone. In particular, the first exhaust air sensor is configured for detecting at least one air property of the first exhaust air. In particular, the second exhaust air sensor is configured for detecting at least one air property of the second exhaust air. In particular, the different zones will accordingly participate in the total costs according to the contamination level of the exhaust air flowing out of them. In some embodiments, the first exhaust air flowing out of the first zone is returned back to the HVAC system and the second exhaust air flowing out of the second zone is returned back to the HVAC system. In particular, at least one of the returned first exhaust air and the returned second exhaust air is recycled or reprocessed in the HVAC. For example, the respective exhaust air is at least one of: cleaned, tempered, humidified, dehumidified, sterilized, and mixed with fresh outside air. In some embodiments, the zones are separated rooms or comprise separated rooms. In particular, the term “separated” may mean that the rooms are separated at least by a wall. In particular, said wall may comprise at least one door allowing for accessing the respective room and/or at least one window allowing for exchanging the air in the respective room. In particular, the term “separated” does not necessarily mean that the rooms are hermetically sealed from one another, but there may be gaps and/or clearances in the wall. In particular, the zones are separable rooms in that a separation element separating the rooms from one another is removable or adjustable. For example, the zones are office cubes or booths in an open-space office. In some embodiments, the zones are parts of a single room. In particular, said single room may be an open-space office, a warehouse, or a shop floor. The single room can be segmented in zones wherein each zone is e.g. associated with a different tenant, division, or department. In particular, the i-th first usage data are based on a person occupation of the first zone and the i-th second usage data are based on a person occupation of the second zone. In some embodiments, the method further comprises, for each of the n time intervals, determining i-th first occupation data characterizing a first person occupation of the first zone during the i-th time interval, wherein the i-th first usage data comprise the i-th first occupation data, and determining i-th second occupation data characterizing a second person occupation of the second zone during the i-th time interval, wherein the i-th second usage data comprise the i-th second occupation data, in particular wherein the i-th first occupation data are collected by a first occupation sensor, in particular a first occupation smart plug, a first occupation smart meter, a first occupation motion sensor, a first occupation thermal sensor, a first occupation optical sensor, a first occupation ultrasonic sensor, a first occupation microwave sensor, a first occupation infrared sensor and a first attendance recorder and the i-th second occupation data are collected by a second occupation sensor, in particular a second occupation smart plug, a second occupation smart meter, a second occupation motion sensor, a second occupation thermal sensor, and a second occupation optical sensor, and a second attendance recorder. In some embodiments, the HVAC system comprises, as a component, a heat exchanger, in particular incorporated in an air duct of the HVAC system, wherein the heat exchanger is configured, using a heat transfer medium, for dissipating thermal energy from or transferring thermal energy to supply air flowing through the heat exchanger, which is then flowing as conditioned air to the first zone and second zone. In some embodiments, the method further comprises, for each of the n time intervals, determining i-th first absolute costs based on i-th operational costs of the at least one component of the HVAC system and the i-th first cost sharing coefficient. In particular, the i-th first absolute costs are determined by multiplying the i-th operational costs of the at least one component of the HVAC system with the i-th first cost sharing coefficient. In particular, the method further comprises, for each of the n time intervals, determining i- th second absolute costs based on i-th operational costs of the at least one component of the HVAC system and the i-th second cost sharing coefficient. In particular, the i-th second absolute costs are determined by multiplying the i-th operational costs of the at least one component of the HVAC system with the i-th second cost sharing coefficient. In some embodiments, wherein n ^ 2, the method comprises, for each of the n time intervals, determining i-th first action data characterizing a status of each of at least one first action undertaken in the first zone during the i-th time interval, said at least one first action targeting an influence on at least one air property in the first zone, in particular wherein the i-th first action data are collected by a first action data sensor, in particular a first action smart plug, a first action smart meter, a first action motion sensor, and a first action optical sensor. In particular, the i-th first usage data comprise the i-th first action data. In particular, the at least one first action comprises a measure taken in the first zone in the i-th time interval to influence the at least one air property. In some embodiments, the method further comprises identifying a correlation of a first action with the first absolute costs. In particular, identifying the correlation is based on an analysis of a respective chronological sequence of the n first action data and the n first absolute costs. In particular, said chronological sequences may be differentiated, wherein a correlation is identified if a peak in the derivation of the first action data and a peak in the derivation of the first absolute costs occur within a predefined distance of time. In some embodiments, the method further comprises, based on the identified correlation, determining a cost-saving or a cost-increase caused by a given first action identified as correlating with the first absolute costs. In particular, the cost-saving or the cost-increase is determined based on a comparison of first absolute costs during a given first interval in which the given first action falls with first absolute costs during an interval after or before the given first interval. In some embodiments, the method further comprises generating recommendation data based on the determined cost-saving or the determined cost-increase, said recommendation data indicating that the given first action is associated with said determined cost-saving or said recommendation data indicating that avoidance of the given first action is associated with avoidance of said determined cost-increase. In particular, the method may comprise generating recommendation data based on the determined cost-saving or the determined cost-increase, said recommendation data indicating that the given first action should be taken at a different time. In some embodiments, each of the at least one first action undertaken in the first zone is one of a group comprising: an adjustment of a window position, an adjustment of a door position, an adjustment of an air inlet, an activation of a separate thermal device, and an adjustment of a separate thermal device. In particular, when n ^ 2, the method comprises, for each of the n time intervals, determining i-th second action data characterizing a status of each of at least one second action undertaken in the second zone during the i-th time interval, said at least one second action targeting an influence on at least one air property in the second zone. In particular, the i-th second usage data comprise the i-th second action data. In particular, the at least one second action comprises a measure taken in the second zone in the i-th time interval to influence the at least one air property. In particular, the method further comprises identifying a correlation of a second action with the second absolute costs. In particular, identifying the correlation is based on an analysis of a respective chronological sequence of the n second action data and the n second absolute costs. In particular, said chronological sequences may be differentiated, wherein a correlation is identified if a peak in the derivation of the second action data and a peak in the derivation of the second absolute costs occur within a predefined distance of time. In particular, the method further comprises, based on the identified correlation, determining a cost-saving or a cost-increase caused by a given second action identified as correlating with the second absolute costs. In particular, the cost-saving or the cost-increase is determined based on a comparison of second absolute costs during a given second interval in which the given second action falls with second absolute costs during an interval after or before the given second interval. In particular, the method further comprises generating recommendation data based on the determined cost-saving or the determined cost-increase, said recommendation data indicating that the given second action is associated with said determined cost-saving or said recommendation data indicating that avoidance of the given second action is associated with avoidance of said determined cost-increase. In particular, each of the at least one second action undertaken in the second zone is one of a group comprising: an adjustment of a window position, an adjustment of a door position, an adjustment of an air inlet, an activation of a separate thermal device, and an adjustment of a separate thermal device. In some embodiments, the i-th first inflow data comprise at least one of an i-th first conditioned air quantity, an i-th first conditioned air temperature, an i-th first conditioned air humidity, an i-th first conditioned air degree of pollution, an i-th first conditioned air carbon- dioxide concentration, an i-th first conditioned air viral contamination, an i-th first conditioned air pollen concentration, an i-th first conditioned air odorant molecule concentration, and an i-th first conditioned air ventilation flap position. In some embodiments, the i-th first outflow data comprise at least one of an i-th first exhaust air quantity, an i-th first exhaust air temperature, an i-th first exhaust air humidity, an i-th first exhaust air degree of pollution, an i-th first exhaust air carbon-dioxide concentration, an i-th first exhaust air viral contamination, an i-th first exhaust air pollen concentration, an i-th first exhaust air odorant molecule concentration, and an i-th first exhaust air ventilation flap position. In some embodiments, the i-th second inflow data comprise at least one of an i-th second conditioned air quantity, an i-th second conditioned air temperature, an i-th second conditioned air humidity, an i-th second conditioned air degree of pollution, an i-th second conditioned air carbon-dioxide concentration, an i-th second conditioned air viral contamination, an i-th second conditioned air pollen concentration, an i-th second conditioned air odorant molecule concentration, and an i-th second conditioned air ventilation flap position. In some embodiments, the i-th second outflow data comprise at least one of an i-th second exhaust air quantity, an i-th second exhaust air temperature, an i-th second exhaust air humidity, an i-th second exhaust air degree of pollution, an i-th second exhaust air carbon- dioxide concentration, an i-th second exhaust air viral contamination, an i-th second exhaust air pollen concentration, an i-th second exhaust air odorant molecule concentration, and an i-th second exhaust air ventilation flap position. In particular, it has been mentioned that there are first and second exhaust air ventilation flaps, the positions of which may monitored to be part of the inflow/outflow data. Such exhaust air ventilation flaps are typically used to balance a room, i.e. to control the inflow vs. the outflow. For example, this may also be used to pressurize a zone, i.e. when inflow does not equal outflow, so that the excessive air must leave the respective zone through a leak area or leak spot. In some embodiments, the i-th operational costs of the at least one component of the HVAC system comprise at least one of i-th electricity costs, i-th maintenance costs, and i-th spare part costs, in particular wherein the i-th spare part costs comprise at least one of i-th filter replacement costs and i-th UV lamp replacement costs. The invention further relates to a method for monitoring consumer-specific energy costs of at least one component of an HVAC system and consumer-specific maintenance costs of the at least one component of the HVAC system, which HVAC system supplies at least a first zone and a second zone of a building with conditioned air, wherein the method comprises the following steps for each of n time intervals with n ^^1, wherein i = 1,…, n and wherein i and n א ^: determining i-th first inflow data characterizing a first conditioned air flowing from the HVAC system into the first zone during an i-th time interval, determining i-th first outflow data characterizing a first exhaust air flowing out of the first zone and back to the HVAC system during the i-th time interval, determining i-th second inflow data characterizing a second conditioned air flowing from the HVAC system into the second zone during the i-th time interval, determining i-th second outflow data characterizing a second exhaust air flowing out of the second zone and back to the HVAC system during the i-th time interval, determining i-th HVAC outflow data characterizing a conditioned air leaving the HVAC system, determining i-th HVAC inflow data characterizing an exhaust air arriving back at the HVAC system, determining i-th first energy costs associated with the first zone based at least on i-th total energy costs of the at least one component of the HVAC system, the i-th HVAC outflow data, and the i-th first inflow data, determining i-th first maintenance costs associated with the first zone based at least on i-th total maintenance costs of the at least one component of the HVAC system, the i-th HVAC inflow data, and the i-th first outflow data, determining i-th second energy costs associated with the second zone based at least on the i-th total energy costs of the at least one component of the HVAC system, the i-th HVAC outflow data, and the i-th second inflow data, and determining i-th second maintenance costs associated with the second zone based at least on the i-th total maintenance costs of the at least one component of the HVAC system, the i-th HVAC inflow data, and the i-th second outflow data. In particular, the i-th HVAC outflow data comprise i-th HVAC outflow air pressure data and the i-th first inflow data comprise i-th first inflow air pressure data, wherein the i-th first energy costs are at least based on a deviation of the i-th HVAC outflow air pressure data and the i-th first inflow air pressure data. In particular, the i-th HVAC outflow data comprise i-th HVAC outflow air pressure data and the i-th second inflow data comprise i-th second inflow air pressure data, wherein the i-th second energy costs are at least based on a deviation of the i-th HVAC outflow air pressure data and the i-th second inflow air pressure data. This way, it can be determined to what extent each zone is exacerbating the transport of conditioned air to the respective zone. In particular, the i-th HVAC inflow data comprise i-th HVAC inflow air pressure data and the i-th first outflow data comprise i-th first outflow air pressure data, wherein the i-th first maintenance costs are at least based on a deviation of the i-th HVAC inflow air pressure data and the i-th first outflow air pressure data. In particular, the i-th HVAC inflow data comprise i-th HVAC inflow air pressure data and the i-th second outflow data comprise i-th second outflow air pressure data, wherein the i-th second maintenance costs are at least based on a deviation of the i-th HVAC inflow air pressure data and the i-th second outflow air pressure data. This way, it can be determined to what extent each zone is exacerbating the transport of exhaust air back to the HVAC. In particular, the i-th first inflow data are collected in proximity to a first conditioned air inlet located in or at least leading to the first zone. In particular, the i-th second inflow data are collected in proximity to a second conditioned air inlet located in or at least leading to the second zone. In particular, the i-th first inflow data are collected with a first conditioned air sensor configured for detecting at least one air property of the first conditioned air. In particular, the i-th second inflow data are collected with a second conditioned air sensor configured for detecting at least one air property of the second conditioned air. In some embodiments, the i-th first outflow data are collected in proximity to a first exhaust air outlet located in or at least leading away from the first zone. In some embodiments, the i-th second outflow data are collected in proximity to a second exhaust air outlet located in or at least leading away from the second zone. In particular, the i-th first outflow data are collected with a first exhaust air sensor configured for detecting at least one air property of the first exhaust air. In particular, the i-th second outflow data are collected with a second exhaust air sensor configured for detecting at least one air property of the second exhaust air. In particular, the i-th HVAC outflow data are collected in proximity to a conditioned air outlet located in or at least leading away from the HVAC system. In particular, the i-th HVAC outflow data are collected with an HVAC outflow air sensor configured for detecting at least one air property of the conditioned air leaving the HVAC system. In particular, the i-th HVAC inflow data are collected in proximity to an exhaust air inlet located in or at least leading to the HVAC system. In particular, the i-th HVAC inflow data are collected with an HVAC inflow air sensor configured for detecting at least one air property of the arriving back at the HVAC system. The invention further relates to an HVAC system that is configured for performing the above described methods. In particular, the HVAC system comprises a control unit, especially a computer, as well as suitable interfaces for reading and outputting data. The invention further relates to a computer program comprising instructions which, when the program is executed by a control unit, especially by a computer, cause the control unit to carry out the above described methods. Brief description of the drawings By way of example only, preferred embodiments of the invention will be described more fully hereinafter with reference to the accompanying figures, wherein: Figure 1 shows, in a top view, an open-space office which is separated into a first zone, a second zone, and a shared zone; Figure 2 shows the open-space office of figure 1 in a side view; Figure 3 shows an alternative HVAC configuration for the open-space office of figure 1; Figure 4 shows a chart qualitatively plotting the occupation of the first zone and the occupation of the second zone over a working week; Figure 5 shows a chart qualitatively plotting an electricity consumption of the first zone and an electricity consumption of the second zone; Figure 6 shows another chart with a curve representing the first zone and a curve representing the second zone; Figure 7 shows an office floor that has five closed rooms in it; Figure 8 shows a chart qualitatively plotting absolute costs and action data of a given zone; and Figure 9 shows one example of how to determine a correlation between absolute costs and action data. Detailed description of the drawings Figure 1 shows, in a top view and neglecting any arrangement on its ceiling, an open-space office 1 which is separated into a first zone 2, a second zone 3, and a shared zone 4, and which is supplied by an HVAC system. The first zone 2 is rented out to a first tenant and the second zone 3 is rented out to a second tenant, wherein the shared zone 4 is used by both the first tenant and the second tenant. In the shared zone, a first hallway 5, a second hallway 6, a kitchen 7, a computer 19, attendance recorders 20 and 21, and an eating area 8 are located. The borders defining the first zone 2 and the second zone 3 are in this case intangible, i.e. there are not walls, room dividers, or glass panels separating the zones. A software start-up is renting the first zone 2 in the office 1. In the first zone 2, a group 9 of eight work desks is located, wherein on each side of the first zone 2, there are four desks in a row. A group 10 of six desk lamps is positioned between pairs of work desks for illuminating their top surface, and wherein a group 11 of six fan heaters is positioned between pairs of work desks for tempering a space underneath the work desks on demand. The occupation today is six out of a group 12 of eight employees because one employee is on sick leave and one is remote working. The second zone 3 is rented by an architecture firm. In the second zone 3, a group13 of four work desks are located, wherein there are two pairs of work desks arranged in the center of the second zone 3. A group 14 of two uplighters is positioned at two corners of the second zone 3 for indirectly illuminating the second zone 3, and a group 15 of desk lamps is positioned between each of the desk pairs for illuminating their top surface. A cooling fan 16 is currently positioned between the pairs of work desks on one side of the second zone 3 for locally lowering the perceived temperature on demand, and a fan heater 17 is currently positioned between the pairs of work desks on the other side of the second zone 3 for locally increasing the temperature on demand. The occupation today is three out of a group 18 of four employees because one employee is on a business trip. The electrical assets 10, 11, 14, 15, 16, and 17 are connected to the grid via smart plugs connected to the computer 19 so that the usage and energy consumption of said assets can be monitored in real-time. The computer 19 is also connected to the attendance recorders 20 and 21 so that the occupation of the zones 2 and 3 can be monitored in real- time. As an embodiment, the invention provides a method for monitoring consumer-specific operational costs of at least one component of an HVAC system (not shown in figure 1), which HVAC system supplies at least the first zone 2 and the second zone 3 with conditioned air, wherein the method comprises the following steps, which are carried out each day: (a) determining first usage data characterizing a usage of the first zone 2 during the current day, (b) determining second usage data characterizing a usage of the second zone 3 during the current day, (c) determining a current day’s first cost sharing coefficient based at least on the current day’s first usage data, said current day’s first cost sharing coefficient associated with the first zone 2, and (d) determining a current day’s second cost sharing coefficient based at least on the current day’s second usage data, said current day’s second cost sharing coefficient associated with the second zone 3. These steps a) - d) are carried out every day of the year in order find a fair distribution of the costs of the at least one component of the HVAC system. That is, current day’s operational costs of the at least one component of the HVAC system are also recorded, and, to find out current day’s first absolute costs associated with the tenant of the first zone 2 and current day’s second absolute costs associated with the tenant of the second zone 3, the current day’s first operational costs are multiplied with the respective current day’s cost sharing coefficient. The first and second usage data characterizing the usage of the respective zone during the current day may relate to one or more of a plurality of different aspects. For example, in a very simple embodiment, usage of the zones can be characterized merely by occupation. Accordingly, the cost sharing coefficients are determined based on how many employees are present in the zones in the relevant interval. The occupation can be monitored by attendance recorders 20 and 21 collecting occupation data and providing the occupation data to the computer 19. In other embodiments, e.g. occupation of employees can be determined by sensors detecting the presence of humans which might be considered if not only employees are visiting the zone or if an attendance recorder is not available. In a straightforward embodiment, the maximum amount of individual employees determined as being present in the respective zone during the current day is used for determining the respective cost sharing coefficient. Given that the occupation as shown in figure 1 is the “peak” occupation for the day, the operational costs of the at least one component of the HVAC system are split in a ratio 6:3 or 2:1. In more sophisticated embodiments, data relating to further aspects can influence the cost sharing coefficients, either as alternative to the occupation data or in addition to the occupation data. For example, usage of the electrical assets 10, 11, 14, 15, 16, and 17 can be recorded and a usage of the respective zone can be derived from the usage of the electrical assets. Activation status and/or energy consumption of the devices can be used for that. As an example, it is a early autumn day and convention among employees about a comfortable room temperature cannot easily be achieved. Thus, in the first zone 2, some employees in the group 12 wish a window to be open whereas other employees feel cold and activate four of the six fan heaters. It is a cloudy day and all six lamps of the group 10 are activated. Optionally, the activation status and/or energy consumption of other devices may also monitored, such as personal computers, charging adapters, and printers. In total, zone 2 consumes 18 kWh of electricity on the current day. In the second zone 3, two employees of the group 18 suffer from the opened window in zone 2 and start the fan heater 17. The third employee activates the cooling fan 16 for a couple of hours where the sun comes out. As the group 18 is smaller and they do not need the background light 14, the total energy consumption of the current day is only 6 kWh. Thus, the operational costs of the at least one component of the HVAC system can be split in a ratio 18:6 or 3:1 in case usage of the zone is only to be derived from how the mentioned devices are used. For this, it is assumed that the more heavily a zone is used with regards to electric devices, the more it should participate in the costs of fresh air supply and air tempering. In case, the cost sharing coefficients should be derived from both occupation and energy consumption, the costs should be split in a ration 5:2 when considering equal weightings, wherein individual weightings can be assigned to potential aspects such as occupation and energy consumption. Shared zone 4 has so far been neglected, i.e. it was assumed that both zones 2 and 3 are responsible for the operational costs of the at least one component of the HVAC system caused by supplying the shared zone 4 with conditioned air in the same ratio as according to the determined cost sharing coefficients. The costs for supplying zone 4 with fresh air can however also just be shared equally or in accordance to a ratio of the area of zone 2 and the area of zone 3 in case they are differently sized. In other embodiments, the shared zone 4 may further be used by more parties that do not rent a zone in the office 1, wherein the costs of zone 4 may be split in different ways. Figure 2 shows the office 1 in a side view, wherein the supply of conditioned air by the HVAC system 22 can be seen as a duct system 23 leads from the HVAC system 22 to a group 24 of five inlets that distribute the conditioned air into the shared zone 4, the first zone 2 and the second zone 3. The inlets 24 are not dedicated to any zone but supply the open-space office 1 as a whole. An outlet 25 is installed in the shared zone 4 for returning exhaust air through the duct system 23 back to the HVAC system 22 where it can be recycled. Figure 3 shows an alternative HVAC configuration for the office 1. The HVAC system 22 supplies via the duct system 26 the first zone 2 with a dedicated inlet 27 and the second zone 3 with a dedicated inlet 28. Exhaust air transported back to the HVAC system 22 via the duct system 26 is drained from the first zone 2 by a dedicated outlet 29 and from the second zone 3 by a dedicated outlet 30. To stick to the example as described in context of figure 1, the first and second usage data may comprise, respectively, first and second inflow data. That is, over the current day, respective inflow data are determined which are characterizing a respective conditioned air supplied by the HVAC system 22 and flowing into the respective zone during the current day. The current day’s first inflow data are collected in proximity to the first conditioned air inlet 27 and the current day’s second inflow data are collected in proximity to the second conditioned air inlet 28. For example, this can be achieved through respective conditioned air sensors which are detecting at least one air property of the first conditioned air, in particular one or more of: a quantity, a temperature, a humidity, a degree of pollution, a carbon-dioxide concentration, a viral contamination, a pollen concentration, and an odorant molecule concentration. Also, the usage data may comprise outflow data characterizing the respective exhaust air flowing out of the respective zone during the current day. In particular, the first outflow data are collected in proximity to the first exhaust air outlet 29 located in or at least leading away from the first zone 2 and the second outflow data are collected in proximity to the second exhaust air outlet 30 located in or at least leading away from the second zone 3. If the respective inflow and outflow data correspond, then a deviation could be determined in accordance to which the different zones will participate in the total costs for running the HVAC. In other embodiments, the different zones will participate in the total costs only according to the contamination level of the exhaust air flowing out of them, i.e. the usage data comprise only the outflow data, or at least: the usage data do not comprise the inflow data. Again, the respective outflow data can be collected with respective exhaust air sensors configured for detecting at least one air property of the first exhaust air, in particular one or more of: a quantity, a temperature, a humidity, a degree of pollution, a carbon-dioxide concentration, a viral contamination, a pollen concentration, and an odorant molecule concentration. In an alternative interpretation of figure 3, a method for monitoring consumer-specific energy costs of at least one component of an HVAC system and consumer-specific maintenance costs of the at least one component of the HVAC system could work like this: The HVAC system 22 supplies the first zone 2 and the second zone 3 with conditioned air, wherein, for example in daily intervals, first inflow data at the inlet 27 and second inflow data at the inlet 28 are determined. These inflow data are again characterizing the conditioned air arriving at the respective zones. Also, again, outflow data are collected daily, characterizing the exhaust air at the outlets 29 and 30. As well, HVAC outflow data are determined for every interval, which HVAC outflow data are characterizing the conditioned air leaving the HVAC system, and HVAC inflow data are determined for every interval, which HVAC inflow data are characterizing the exhaust air arriving back at the HVAC system. Eventually, respective energy costs associated with the respective zones are determined based at least total energy costs of the at least one component of the HVAC system 22, the HVAC outflow data, and the respective inflow data. Analogously, respective maintenance costs associated with the respective zones are determined based at least on total maintenance costs of the at least one component of the HVAC system 22, the HVAC inflow data, and the respective outflow data. This approach achieves a fair distribution of energy and maintenance costs according to the cost-by-cause principle. For example, if a comparison of the conditioned air exiting the HVAC system 22 with the conditioned air arriving at the single zones finds that the conditioned air is not arriving at each zone with the same quality, the energy costs must be distributed so as to make a tenant pay more than the others for it, where the conditioned air arrives in a worse quality. This could happen if the given zone is very remote from the HVAC system 22 or if the tenant of the given zone took any action that exacerbate transport of conditioned air into the given zone (e.g. blocking an outlet so as to increase the air pressure in the given zone which is why the HVAC system would need to increase the supply pressure). Analogously, maintenance costs can be distributed based on the exhaust air of all zones arriving back at the HVAC system 22 and the exhaust air measured at each zone outlet 29, 30. The costs for reusing the air are thus shifted more towards those tenants who are polluting the air more intensively, e.g. hair cutters or perfume shops. The more polluted the exhaust air is that arrives back at the HVAC system 22, the more wear will occur to the components of the HVAC, e.g. the filters must be replaced sooner, a technical service must be conducted sooner, ventilators supplying fresh air from outside must be repaired sooner, etc. Figure 4 shows a chart qualitatively plotting the occupation 31 of the first zone 2 and the occupation 32 of the second zone 3 over the days of one week, i.e. the differently colored areas are Monday, Tuesday, Wednesday, Thursday, and Friday. It is only on Wednesday that the first zone 2, as shown in figure 1, is occupied by six employees and the rest of the week it is fully occupied with eight employees. The second zone 3 is occupied by three employees today (Wednesday), as shown in figure 1. On Monday, zone 3 was fully occupied by four employees, and Friday, only two people were present. On Thursday, two business partners visited zone 3 which was detected by cameras. Even though the two visitors were only present for 2 hours, the maximum occupation on Thursday hit five so that this number is determining the usage data which leads to a higher cost sharing coefficient for the second zone 3. Accordingly, the costs related to at least one component of the HVAC system are split 8:4 on Monday, 8:3 on Tuesday, 6:3 on Wednesday, 8:5 on Thursday, and 8:2 on Friday. Of course in other embodiments, the values plotted in the chart for each weekday may be average values which considers the single attendance times of the individual persons. Figure 5 shows a chart qualitatively plotting an electricity consumption 33 of the first zone 2 and an electricity consumption 34 of the second zone 3. The consumption is influenced by the occupation but also by sensibilities and needs of the individual occupants 12 and 18. The electricity consumption is a good indicator for the usage of the zones and one can derive the applicable cost sharing coefficients based on the ratio of the single zones’ electricity consumption. Also, the occupation ratio as shown in figure 4 or other aspects can additionally be incorporated into the cost sharing coefficient determination. Figure 6 shows another chart with a curve 35 representing the first zone 2 and a curve 36 representing the second zone 3. The curves, for example, plot an electricity consumption (e.g. detected by smart plugs or smart meters), an activity (e.g. detected by a motion sensor), or a heat emission (e.g. detected by a thermal camera) over one day, i.e. every interval is one hour of the day, wherein the records begin at 6 am and end at 9 pm. The drop at 12 am is significant because many employees leave for lunch. In case of a plotted electricity consumption, the slightly rising behavior in the evening can be explained by extra light sources, brighter light settings, and/or activation of heating devices. Also, it is possible to establish a correlation between the cooling/heating activity in one of the zones and the presence of a person or the number of persons being present in that zone, e.g. as detected by a presence sensor. This correlation can be used to set and/or control the cooling/heating activity or strategy of the given zone. Figure 7 shows, in a similar top view as figure 1, an office floor 37 that has five closed rooms in it, which can be accessed by respective doors. The walls are raised up to the ceiling and are made of glass. Similar as in figure 1, there is a first zone 38 rented by a first tenant and comprising four similar-sized small rooms, and there is a second zone 39 rented by a second tenant and consisting of one big room. There is, again, a shared zone 40 with a kitchen and an eating area. A computer 41 is collecting action data. Action data are characterizing measures that have been taken by occupants. These actions or measures are aimed at influencing the ambient air properties (e.g. in its temperature). For example, each of a plurality 42 of windows can be equipped with a sensor that determines a position status (open/closed). As well, each of the group 43 of doors can be equipped with a sensor for the same data. The electronic devices 44 can also be equipped e.g. with a smart plug for monitoring a state of activation (on/off) or even a state of adjustment (e.g. high/mid/low), in particular this can be the same smart plug that may monitor the energy consumption as explained in context of the previous figures. Furthermore, action data can relate to an adjustment of an air inlet (of the HVAC). When at the same time, absolute costs 45 for the given zone are recorded as shown in figure 8, i.e. by applying the determined cost sharing coefficient to the operational costs, a correlation of corresponding action data 46 with the absolute costs 45 is searched. Specifically, where a change in status of a given action is detected, an algorithm would search for consequences of the status change in the costs data. Figure 8 is again a daily chart with 15 working hours e.g. plotting an opening status 46 of the windows 42 as well as determined absolute costs 45 assigned to the given zone. Between eleven in the morning and 5 in the afternoon, at least one window was opened to let outside air enter the given zone. One can see the effect in the costs curve in that there is a sharp increase and a sharp decrease following the window status changes. Figure 9 shows one example of how to determine such a correlation. The curves 46 and 45 from figure 8 can be derived and plotted as curves 47 and 48. Now the algorithm is searching for peaks in the derivation curve 48 of the action data, and, upon detection of a peak, is searching for peaks in the derivation curve 47 of the absolute costs. The search for respective peaks can be defined so that only peaks are detected that are larger than a certain threshold value. The subsequent search for a peak in the curve 47 potentially correlated to a detected peak in the curve 48 can further be defined so that peaks are detected only within a predefined distance of time, which is here illustrated by the time frames 49 and 50. In response to the identification of these correlations, a computer 19 or 41 can provide recommendation data, e.g. displayed on a tablet GUI, indicating that avoidance of the given action (opening the window(s)) is associated with the determined cost-increase. While this is a very straightforward example of a recommendation, there might be recommendations which are more sophisticated. For example, while monitoring the temperature over the course of the day, the computer 19 or 41 may output recommendation data indicating that a specific action, e.g. opening of the windows, should be undertaken at a specific day time, e.g. in the morning or in the evening, in order to avoid air coming in from outside that have a high temperature or high dust pollution and that needs to be cooled down or cleaned. Although the invention is illustrated above, partly with reference to some preferred embodiments, it must be understood that numerous modifications and combinations of different features of the embodiments can be made. All of these modifications lie within the scope of the appended claims.

List of reference signs 24 Inlets 49 Time frame 25 Outlet 50 Time frame