This present disclosure is related generally to the field of emissions management, such as greenhouse gas (GHG) emissions management, and more specifically to a centralized emission management system that estimates resource consumption at facilities.
“Emissions” refer to the introduction of chemicals, particulate matter, or biological materials into the atmosphere, ground, or water system that potentially can cause harm or discomfort to humans or other living organisms, or may damage the natural environment.
GHG is a collective term for gases such as carbon dioxide, methane, HFCs, SF6, and nitrous oxide that trap heat in the atmosphere and contribute to climate change. GHG accounting and reporting is the discipline of tracking GHGs produced as a result of executing business processes, including manufacturing, travel, keeping of livestock, etc.
The term “carbon dioxide equivalent” (CO2e) is a common normalized unit of measurement, such as expressed in tonnes of CO2e, that is used to compare the relative climate impact of the different GHGs. The CO2e quantity of any GHG is the amount of carbon dioxide that would produce the equivalent global warming potential. There are publicly accepted factors that are used to convert an entity's emissions, usage of resources (e.g., electricity, gas, oil, coal, etc.), or waste products, among other things, into a CO2e emission.
A company or other entity may want to, or be required to, reduce their CO2e emissions or energy usage. For example, a company's CO2e emissions may be capped by a governmental or industrial organization within an established time frame. However, the company may not have all the resource consumption data necessary to calculate its CO2e emissions at all of its facilities. Thus what is needed is a technique to estimate resource consumption at a facility when data from that facility is not available.
In one or more embodiments of the present disclosure, a centralized emission management system is implemented via a server that is accessible to a large number of entities. An entity uploads information about demographic data and resource consumption data of its organizational units, such as facilities, to determine measures of environmental impact, such as CO2e emissions. When resource consumption of a target organizational unit is not available, the entity can request the server to estimate the resource consumption based on private information about comparable organizational units within the entity or public information about comparable organizational units outside of the entity. The server determines the comparable organizational units based on the demographic data, such as facility area (e.g., square footage), revenue, produced units, facility type (e.g., office, manufacturing, etc.), facility age, facility operating hours, employee count, HVAC type, facility location, and other demographic data. The entity can select a resource consumption item of a comparable organizational unit from which the server determines an estimated resource consumption of the target organizational unit, generates an audit trail of the estimate, and determines a measure of environmental impact from the estimate. Any report listing the estimated resource consumption or the measure of environmental impact clearly designates the value as an estimate.
In the drawings:
Use of the same reference numbers in different figures indicates similar or identical elements.
Although server 112 has many functions, and there may be a plurality of servers, only one server and its emission management software related to the present disclosure are illustrated. The emission management software includes algorithms 118, 120, and 122, which are stored along with their data in a non-transitory computer-readable medium. Algorithms 118 are for generating the web-based GUI and related functions. Algorithms 120 are for storing the clients' entered data into a database 124 and converting the clients' resource consumptions and other relevant information into CO2e emissions, wastewater production, and other measures of environmental impact. Algorithms 122 are for estimating resource consumption at an organizational unit, such as a facility, based on demographic data and resource consumption data in database 124 or a public database 126, recording the estimated resource consumption in database 124, and creating an audit trail for the estimated resource consumption.
A client initially sets up its account in the emission management software by providing a company model 128 with a hierarchy of its organizational units via the web-based GUI or an upload of a compatible file with such information. The hierarchical levels of the organizational units may include geographical areas such as continents, regions such as countries in a geographical area, and facilities such as cities in a region. The client then inputs information for each organizational unit using the web-based GUI or an upload of a compatible file with such information. The emission management software is able to present processed information to the client on a per facility basis or aggregated for different hierarchical levels of the company.
The client provides information for each organizational unit relevant to environmental impact. Some of the information may be related to resource consumption of an organizational unit, such as types of energy used (e.g., electricity, natural gas, diesel, oil, coal, etc.), quantities of energy used (e.g., kwh, gallons, etc.), dates of energy used, costs of energy used, airline travel, lighting usage, types/amounts of products manufactured and types/amounts of emissions, efficiencies, waste products, water usage, raw input product usage (e.g., paper, metals, etc.), costs of various pertinent resources, and other types of data pertinent to resource consumption. Server 112 may save the individual resource consumption entries as resource consumption items for the organizational unit in database 124. Some of the information may be related to demographics of the organizational unit, such as facility area (e.g., square footage), facility revenue, facility produced units, facility type (e.g., office, manufacturing, etc.), facility age, facility operating hours, facility employee count, facility HVAC type, facility location, and other types of data pertinent to demographics.
Each input resource and/or output product, assuming a certain usage efficiency, is applied to an appropriate algorithm to determine its corresponding CO2e emission quantity or other unit of measurement. Many of the algorithms 120 correlating resources, outputs, or activities to an equivalent CO2e emission are based on publicly known standards, such as the Emissions & Generation Resource Integrated Database (eGRID) conversion factors used by the Environmental Protection Agency (EPA).
The raw data, e.g. in terms of natural gas or gallons of gasoline, is periodically input by the clients, such as at the end of each accounting period, which may be yearly. The client's data may also include information that is automatically uploaded to the server 112 through any interface, such as a utility meter for electricity, water, etc. Server 112 stores the past data in database 124. Server 112 processes the data and presents the processed data to the client in a suitable presentation on the web-based GUI, upon the client requesting the presentation.
When resource consumption of a target organizational unit/facility is not available, the client can request server 112 to estimate the resource consumption based on comparable organizational units/facilities within the entity or public information about comparable organizational units/facilities outside of the entity. Server 112, executing algorithms 122, determines the comparable facilities based on their demographic data in database 124 and presents them to the client. The client can select a comparable facility, and in response server 112 determines resource consumption items of the selected comparable facility from database 124. The client can select a resource consumption item, and in response server 112 determines an estimated resource consumption of the target facility, generates an audit trail of the estimate, and determines a measure of environmental impact from the estimate. Any report listing the estimated resource consumption or the measure of environmental impact clearly designates the value as an estimate.
Method 200 may begin in block 202 after the client has set up its company model. In block 202, server 112 receives a transmission of demographic data and resource consumption data of other organizational units (hereafter “facilities B”) that are part of the client. The types of demographic data may include but are not limited to facility area, facility revenue, facility produced units, facility type, facility age, facility operating hours, facility employee count, facility HVAC type, and facility location. The types of resource consumption data may include but are not limited to resource consumption types, resource consumption amounts, dates of consumption, indications if information for each resource consumption item is estimated by the client, and resource consumption prices. Server 112 stores the data in database 124. Block 202 may be followed by block 204.
In block 204, server 112 receives a transmission of demographic data of facility A that is part of the client. Server 112 stores the data in database 124. Block 204 may be followed by block 206.
In block 206, server 112 receives a transmission of a request to estimate resource consumption of facility A. The request includes an estimation approach, a resource consumption type, and an estimation period. Depending on the estimation approach, the request includes other information specific to the estimation approach. For example, when a comparable facility estimation approach is selected, the request further includes a normalization factor and demographic filters for determining comparable facilities.
Assuming the comparable facility estimation approach has been selected, a menu 309 allows the client to select a normalization factor. The normalization factor may be any of the demographic data, such as facility floor area, facility revenue, facility produced units. As described later, server 112 determines the resource consumption per day per unit of the normalization factor of a comparable facility, i.e., resource consumption during reporting period/(reporting period×normalization factor).
A button 310 allows the client to add a demographic filter for searching comparable facilities. Each demographic filter includes an editable field that may be automatically filled with its value from the demographic information in database 124. The selected normalization factor may appear as a demographic filter by default. An editable field 312 may be filled with the floor area value from of the demographic data of facility A in database 124. In case server 112 has not received a transmission of the demographic data for facility A, the client may fill editable field 312 with the floor area value. The client may also edit the value in editable field 312 to see how that impacts the estimated resource consumption. The new or edited value in editable field 312 may be saved into database 124 after the client selects a save button 337. An auto fill button 314 causes field 312 to revert back to the floor area value from database 124. A delete button 316 causes the corresponding demographic filter to be removed.
Assuming facility building type have been added as a demographic filter, an editable field 318 may be filled with the building type value from the demographic data of facility A in database 124. In case server 112 has not received a transmission of the demographic data for facility A, the client may fill editable field 318 with the building type value. The client may also edit the value in editable field 318 to see how that impacts the estimated resource consumption. The new or edited value in editable field 318 may be saved into database 124 after the client selects save button 337. An auto fill button 320 causes field 318 to revert back to the floor area value from the demographic data in database 124. A delete button 322 causes the corresponding demographic filter to be removed. As described later, server 112 determines comparable facilities based on the demographic filters.
The client may select a leased space estimation approach when the client occupies less than all the building space and the client has access to the total building consumption from its landlord. When a leased space estimation approach is selected, the request includes a resource consumption type, an estimation period, a total building area, a total building occupancy rate, a leased space area, and a total building consumption. The client may provide the information using menus similar to those shown in
Referring back to
In block 208, in response to block 206, server 112 determines facilities B that are comparable to facility A based on their demographic data. When server 112 cannot find any comparable facility B, server 112 may access demographic data and resource consumption data of additional organizational units (hereafter “facilities C”) that are not part of the client's organizational hierarchy. The data may be located in a public database 126 (
In block 210, server 112 transmits a list of the comparable facilities B or C to the client. Referring to
In block 212, server 112 receives a selection of a comparable facility (e.g., the San Francisco facility) from the list. Block 212 may be followed by block 214.
In block 214, in response to block 212, server 112 determines resource consumption items of the selected comparable facility from database 124. The resource consumption items may be limited to the consumption type specified for facility A. Block 214 may be followed by block 216.
In block 216, server 112 transmits a list of the resource consumption items to the client. Block 216 may be followed by block 218.
In block 218, server 112 receives a selection of a resource consumption item and estimation parameters. Referring to
The estimation parameters include a base period for the data of the selected comparable facility to be used in the estimation, and the normalization factor value (e.g., facility floor area) of the selected comparable facility. A menu 328 allows the client to select the base period for the data of the selected comparable facility. An editable field 330 may be filled with the normalization factor value from the demographic data of the selected comparable facility in database 124. The client may also edit the value in editable field 330 to see how that impacts the estimated resource consumption. The new or edited value in editable field 330 may be saved into database 124 after the client selects save button 337. An auto fill button 332 causes field 300 to revert back to the floor area value from database 124. Table 326 and field 330 are automatically updated when the client switches between comparable facilities in menu 324.
Referring to
In block 220, in response to block 218, server 112 determines an estimated resource consumption of facility A based on the selected resource consumption item and the estimation parameters. Server 112 determines the resource consumption per day per unit of the normalization factor of the selected resource item, i.e., resource consumption during reporting period/(reporting period×normalization factor during reporting period). For example, the normalization factor may be facility floor area or any other demographic data selected as the normalization factor including production units and revenue. Server 112 then determines the estimated resource consumption of facility A by multiplying the consumption per day per unit of the normalization factor of the selected comparable facility by the estimation period and the normalization factor of facility A. Block 220 may be followed by block 222.
In block 221, server 112 determines an estimated resource consumption of facility A based on the total building consumption, the building occupancy rate, the leased space area, and the total building area. Specifically, server 112 determines a product of (1) a first quotient of the total building consumption and the total building occupancy rate and (2) a quotient of the leased space area and the total building area, i.e., (total building consumption/total building occupancy rate)×(leased space/total building area). The division of the building occupancy rate ensures that the client only accounts for a portion of the consumption from the occupied spaces. Block 221 may be followed by block 222.
In block 222, server 112 transmits the estimated resource consumption of facility A to the client. Referring to
In block 224, server 112 receives an approval of the estimated resource consumption of facility A from the client. Referring to
In block 226, in response to block 224, server 112 derives a measure of environmental impact from the estimated resource consumption. Server 112 records, in database 124, the measure of environmental impact with a system estimation flag, the estimated resource consumption with a system estimation flag, and an audit trail for the estimated resource consumption. The system estimation flag indicates that a value is based on a system estimate. Referring to
In block 228, server 112 then indicates, in any subsequently generated GUI (e.g., report) transmitted to the client, that the estimated resource consumption and/or the measure of environmental impact are estimated values.
Various other adaptations and combinations of features of the embodiments disclosed are within the scope of the invention. Numerous embodiments are encompassed by the following claims.