Data Management Guide
This section is under development. So the content may be incomplete and subject to change.
This guide provides comprehensive data validation schemas for all modules in the CO2 Calculator. These specifications help data managers prepare and upload data correctly.
General Notes
- module_data.csv: data uploaded by the backmanagement office. Here it is important to always have the info of the unit_institutional_id.
- factors.csv: factors that are necessary for the calculation. (emission factors and/or other factors)
- module_template.csv: file that has the names of the columns, and a line of example. Users can download it by clicking on "Download CSV Template".
- module_test.csv: file that is uploaded via the button "Upload CSV". In this CSV, we have the same columns as in the CSV "template", (and there is no unit_institutional_id since the user is already inside the unit).
- unit_institutional_id: For institutional data where relevant, this field contains the unit identifier (e.g., for EPFL: cf_id as 4-digit numbers).
- kg_co2eq: When this optional field is provided with a value, no calculation is performed for that line - the value is used directly.
- note: Available across all modules to add any relevant comments or explanations for specific entries.
- Template and Test files: Used for data entry by unit managers, while data files are typically pre-filled by the back-office.
- Factors files: Contain emission factors and conversion coefficients required for calculations.
- Order of upload from the configuration back-office: first upload factors, then references, then data. The factors.csv file needs to be uploaded before the reference.csv files, and the reference.csv file needs to be uploaded before data.csv file, this allows certain validation rules to be checked properly.
- Rows that don't meet mandatory field requirements or value constraints will be ignored during upload.
- Warning messages will be displayed when data doesn't match factor files.
- Date formats must follow ISO standard (YYYY-MM-DD).
- For research facilities only, a button 'compute missing factors' needs to be pushed in order to calculate the factors for all research facilities for which the info is not given via the .csv. This needs to be done after the rest of the modules are completed. If not done, the contribution to co2 emissions of these research facilities will be 0. The modules contributing to research facilities carbon footprint are: process emissions, buildings, equipment and purchases. If some of the input data, reference or factors for these modules is updated, the button needs to be pushed again in order to update the results for research facilities accordingly.
Headcount
headcount_data.csv
| field |
type |
mandatory |
values constraints |
description |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-digits numbers only) |
| name |
string |
✅ |
non-empty string |
e.g. First and second name |
| sius_code |
string |
✅ |
within 51, 52, 53, 54, 56, 57, 58, 59 |
SIUS function code. Used to build the FTE-per-function chart. |
| user_institutional_id |
string |
✅ |
numbers only |
for EPFL: sciper |
| fte |
float |
✅ |
0 ≤ float ≤ 1 |
Full-time equivalent e.g. 1.0, 0.8, 0.05, 0.75 |
| note |
string |
❌ |
- |
contains the note if needed |
Note
fte can be completed directly in the table if not provided in the file, and must be filled to validate the module.
SIUS code reference
| Code |
FR |
EN |
| 51 |
Enseignant·e·s habilité·e·s à diriger une unité organisationnelle |
Professors |
| 52 |
Autres enseignant·e·s |
Other teaching staff |
| 53 |
Collaborateur·trices scientifiques |
Scientific collaborators |
| 54 |
Assistant·e·s et/ou doctorant·e·s |
Scientific and doctoral assistants |
| 56 |
Personnel de direction de la haute école |
Managerial staff |
| 57 |
Personnel administratif |
Administrative staff |
| 58 |
Personnel de soutien |
Support staff |
| 59 |
Personnel d'exploitation |
Operational staff |
headcount_template.csv and headcount_test.csv
| field |
type |
mandatory |
values constraints |
description |
| name |
string |
✅ |
non-empty string |
e.g. First and second name |
| sius_code |
string |
✅ |
within 51, 52, 53, 54, 56, 57, 58, 59 |
SIUS function code. Used to build the FTE-per-function chart. |
| user_institutional_id |
string |
✅ |
numbers only |
for EPFL: sciper |
| fte |
float |
✅ |
0 ≤ float ≤ 1 |
Full-time equivalent e.g. 1.0, 0.8 |
| note |
string |
❌ |
- |
contains the note if needed |
Process Emissions
processemissions_data.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-digits, numbers only) |
| category |
string |
✅ |
within processes_factors.csv |
e.g. Refrigerant |
| subcategory |
string |
❌ |
within processes_factors.csv, can be None. |
If the category is Refrigerants the subcategory needs to be specified to choose the corresponding factor. e.g. R145 |
| quantity_kg |
float |
✅ |
in kg, float >=0 |
e.g. 34 |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given no calculation is performed for the line |
processemissions_test.csv and processemissions_template.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| category |
string |
✅ |
within processes_factors.csv |
e.g. Refrigerant |
| subcategory |
string |
❌ |
within processes_factors.csv, can be None. |
If the category is Refrigerants the subcategory needs to be specified to choose the corresponding factor. e.g. R145 |
| quantity_kg |
float |
✅ |
in kg, float >=0 |
e.g. 34 |
| note |
string |
❌ |
- |
contains the note if needed |
processemissions_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| category |
string |
✅ |
- |
for EPFL: Refrigerants, CH4, N2O, CO2 |
| subcategory |
string |
❌ |
- |
If the category is Refrigerants the subcategory is always specified in the factors used at EPFL. |
| unit |
string |
✅ |
- |
eg kg |
| ef_kg_co2eq_per_unit |
float |
✅ |
0 ≤ float |
e.g. 23'500 (kg CO2 eq / kg for SF6) |
test calculation processemissions_factors
| category |
subcategory |
quantity_kg |
kg_co2eq |
note |
expected_result |
| Carbon dioxide (CO2) |
|
100 |
|
|
100 |
| Methane (CH4) |
|
50 |
|
|
1350 |
| Nitrous oxide (N2O) |
|
10 |
|
|
2730 |
| Hydrofluorocarbons (HFCs) |
HFC-23 (CHF3) |
5 |
|
|
73000 |
| Hydrofluorocarbons (HFCs) |
HFC-125 (CHF2CF3) |
10 |
|
|
37400 |
| Hydrofluorocarbons (HFCs) |
HFC-134a (CH2FCF3) |
2 |
|
|
3060 |
| Sulfur hexafluoride (SF6) |
|
0.5 |
|
|
12150 |
| Nitrogen trifluoride (NF3) |
|
1 |
|
|
17400 |
| Perfluorinated compounds |
PFC-14 (CF4) |
3 |
|
|
22140 |
| Fluorinated ethers |
HFE-134 (CHF2OCHF2) |
1.5 |
|
|
9945 |
| Carbon dioxide (CO2) |
|
50 |
75 |
Override test: given kg_co2eq differs from calculation |
75 |
Buildings
building_energycombustions_data.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-digits, numbers only) |
| name |
string |
✅ |
within building_combustions_factors.csv |
e.g. "natural_gas" |
| unit |
string |
✅ |
in SI format |
eg kg, kWh , if couple "unit" "name" not found in building_energycombustions_factors.csv row ignore with warning message |
| quantity |
float |
✅ |
0 ≤ float |
e.g. 34 |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given no calculation is performed for the line |
building_energycombustions_test.csv & building_energycombustions_template.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| name |
string |
✅ |
within building_combustions_factors.csv |
e.g. "natural_gas" |
| unit |
string |
✅ |
in SI format |
eg kg, kWh , if couple "unit" "name" not found in building_energycombustions_factors.csv row ignore with warning message |
| quantity |
float |
✅ |
0 ≤ float |
e.g. 34 |
| note |
string |
❌ |
- |
contains the note if needed |
building_energycombustions_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit |
string |
✅ |
in SI format |
e.g. kWh, kg |
| name |
string |
✅ |
has to be unique, see table below |
e.g. natural_gas |
| ef_kg_co2eq_per_unit |
float |
✅ |
0 ≤ float |
e.g. 0.05 |
name reference table
| name |
FR |
EN |
| natural_gas |
Gaz naturel |
Natural gas |
| heating_oil |
Mazout |
Heating oil |
| biomethane |
Biométhane |
Biomethane |
| propane |
Propane |
Propane |
| pellets |
Granulés de bois |
Pellets |
| forest_chips |
Plaquettes forestières |
Forest chips |
| wood_logs |
Bois bûche |
Wood logs |
test calculation building_energycombustion
| name |
unit |
quantity |
kgco2eq |
note |
expected_result |
| natural_gas |
kWh |
100 |
|
|
24 |
| heating_oil |
kWh |
50 |
|
|
16.22 |
| biomethane |
kWh |
200 |
|
|
8.88 |
| propane |
kWh |
75 |
|
|
20.38 |
| pellets |
kg |
500 |
|
|
55.40 |
| forest_chips |
kg |
1000 |
|
|
50.30 |
| wood_logs |
kg |
250 |
|
|
28.45 |
| natural_gas |
kWh |
150 |
40 |
Override test: given kgco2eq differs from calculation |
40 |
building_rooms_data.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-digits, numbers only) |
| building_name |
string |
✅ |
within building_rooms_factors.csv |
e.g. GC |
| room_name |
string |
✅ |
i.e. AI0122 |
If the correspondence (building_name, room_name) is not found in the reference, the row is ignored with a warning message (we do not have the info on squared meters without the name, and so we cannot do the calculation). |
| room_type |
string |
✅ |
within office, miscellaneous, laboratories, archives, libraries, auditoriums, see table below |
e.g. "office". it can be modified in the table by the user. If different from buildings_room_reference.csv it overwrites it. This is the information that is used for the calculation. |
| room_allocation_ratio |
float |
❌ |
0 ≤ float ≤ 1.0 |
Describe the allocation of a room for a sinle unit, in case of shared rooms etc... e.g. 0.8. If not given, default to 1 |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given no calculation is performed for the line. For EPFL, this must be filled for SCITAS, RCP, etc |
building_rooms_test.csv and building_rooms_template.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| building_location |
string |
❌ |
can be None |
e.g. "ECUBLENS" |
| building_name |
string |
✅ |
within building_rooms_factors.csv |
e.g. GC |
| room_name |
string |
✅ |
i.e. AI0122 |
If the correspondence (building_name, room_name) is not found in the reference, the row is ignored with a warning message (we do not have the info on squared meters without the name, and so we cannot do the calculation). |
| room_type |
string |
✅ |
within office, miscellaneous, laboratories, archives, libraries, auditoriums, see table below |
e.g. "office". it can be modified in the table by the user. If different from buildings_room_reference.csv it overwrites it. This is the information that is used for the calculation. If the correspondence building, room_name, room_type does not exist, use the kwh_per_square_meter for the building, room_type (the room_name does not influence the consumption). |
| note |
string |
❌ |
- |
contains the note if needed |
building_rooms_reference.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| building_location |
string |
❌ |
can be None |
e.g. "ECUBLENS" |
| building_name |
string |
✅ |
within building_rooms_factors.csv |
e.g. GC |
| room_name |
string |
✅ |
digit or name |
i.e. AI0122 |
| room_type |
string |
✅ |
within office, miscellaneous, laboratories, archives, libraries, auditoriums, see table below |
The type in this file is the one that is used by default when adding a new line. However, it can be changed by the user, and if changed, the chosen type is used to pair with the corresponding factors in building_rooms_factors.csv (only type and building are taken to compute co2_eq). |
| room_surface_square_meter |
float |
✅ |
0 ≤ float |
e.g. 12 |
building_rooms_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| building_name |
string |
✅ |
- |
for EPFL: BCH,BS... |
| room_type |
string |
✅ |
within office, miscellaneous, laboratories, archives, libraries, auditoriums, see table below |
e.g. "office" |
| heating_kwh_per_square_meter |
float |
✅ |
0 ≤ float |
e.g. 2.3. These are the consumption hypotheses in squared meters for the given building and type of room. This column gives the hypotheses for all buildings, which are used for the calculation also when the data are input by the users (via the upload .csv) |
| cooling_kwh_per_square_meter |
float |
✅ |
0 ≤ float |
e.g. 2.3. These are the consumption hypotheses in squared meters for the given building and type of room. This column gives the hypotheses for all buildings, which are used for the calculation also when the data are input by the users (via the upload .csv) |
| ventilation_kwh_per_square_meter |
float |
✅ |
0 ≤ float |
e.g. 2.3. These are the consumption hypotheses in squared meters for the given building and type of room. This column gives the hypotheses for all buildings, which are used for the calculation also when the data are input by the users (via the upload .csv) |
| lighting_kwh_per_square_meter |
float |
✅ |
0 ≤ float |
e.g. 2.3. These are the consumption hypotheses in squared meters for the given building and type of room. This column gives the hypotheses for all buildings, which are used for the calculation also when the data are input by the users (via the upload .csv) |
| ef_kg_co2eq_per_kwh |
float |
✅ |
0 ≤ float |
e.g. 0.125 |
| energy_type |
string |
✅ |
electric, thermal, etc |
It specifies the type of heating: if electric,the heating is classified as heating (electric), if thermal, it is classified as centralized heating. |
| conversion_factor |
float |
❌ |
can be None |
e.g. 4 , if None consider as 1. To be applied to heating (only, and not to the other three categories) heating_kwh_per_square_meter * ef_kg_co2eq_per_kwh * conversion_factor. This is an adjustement factor needed because the emission factor or heating can be very different if the heating is not electric. So it needs to be adjusted to respect the nature of the thermal heating (gas, etc). Also pay attention to the fact that in some cases the kwh for heating are elec, in other thermique, etc. And we need to bring it to right type to use the emission factors properly. |
room_type reference table
| name |
FR |
EN |
| office |
Bureau |
Office |
| miscellaneous |
Divers |
Miscellaneous |
| laboratories |
Laboratoires |
Laboratories |
| archives |
Archives |
Archives |
| libraries |
Bibliothèques |
Libraries |
| auditoriums |
Auditoires |
Auditoriums |
test calculation building_rooms
| building_name |
room_name |
room_type |
room_allocation_ratio |
kg_co2eq |
note |
expected_result |
| AAB |
AAB 0 05 |
office |
1.0 |
|
17.7 * (5.189 + 5.866 + 0.748 + 2.293 * 1.0) * 1.0 * 0.097 |
24.2 |
| AAB |
AAB 0 32 |
miscellaneous |
1.0 |
|
26.99 * (5.339 + 17.798 + 1.033 + 3.257 * 1.0) * 1.0 * 0.097 |
71.80 |
| AAB |
AAB 0 47 |
office |
0.5 |
|
18.76 * (5.189 + 5.866 + 0.748 + 2.293 * 1.0) * 0.5 * 0.097 |
12.83 |
| CSV |
CSV 0 32 |
libraries |
1.0 |
|
34.51 * (3.952 + 5.104 + 0.069 + 35.594 * 2.8297) * 1.0 * 0.097 |
367.7 |
| SOS1 |
SOS1 0 32 |
archives |
0.75 |
|
13.94 * (0.857 + 1.404 + 0.094 + 1.154 * 2.8297) * 0.75 * 0.097 |
5.7 |
| AAB |
AAB 0 92.1 |
miscellaneous |
1.0 |
50 |
Override test: given kg_co2eq differs from calculation |
50 |
| CCT |
CCT 0 01 |
office |
1.0 |
|
36.62 * (381.421 + 431.142 + 54.965 + 168.571 * 1.0) * 1.0 * 0.097 |
3680.37 |
Equipment
equipment_data.csv
| field |
type |
mandatory |
values constraints |
description |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-digits numbers only) |
| equipment_id |
string |
✅ |
letters and numbers |
This info is used to deal with the updates between one year and the other, in particular for usage hours information. for EPFL: Inventory number |
| name |
string |
✅ |
non-empty string |
e.g. name of the equipment "GoPro" |
| equipment_class |
string |
✅ |
within equipments_factors.csv |
e.g. "Evaporator" is used to get power in equipments_factors.csv, for EPFL these are the standard inventory classes in ENG. If equipment_class is not empty but the value is not listed to equipments_factors.csv, the row is ignored. A warning message is displayed in loading. |
| sub_class |
string |
❌ |
within equipments_factors.csv, can be None |
e.g. "Vacuum evaporators". The sub_class is filled by the user. Must be in the tuples equipment_class/sub_class within equipments_factors.csv else row ignored - (Warning message in loading if data uploaded with the wrong subclass) |
| active_usage_hours_per_week |
int |
❌ |
0 ≤ int ≤ 168 |
e.g. 23. The sum of active + passive must be ≤ 168 |
| standby_usage_hours_per_week |
int |
❌ |
0 ≤ int ≤ 168 |
e.g. 23. The sum of active + passive must be ≤ 168 |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given, no calculation is performed on this line |
equipment_template.csv and equipment_test.csv
| field |
type |
mandatory |
values constraints |
description |
| equipment_id |
string |
✅ |
letters and numbers |
This info is used to deal with the updates between one year and the other, in particular for usage hours information. for EPFL: Inventory number |
| name |
string |
✅ |
non-empty string |
e.g. name of the equipment "GoPro" |
| equipment_class |
string |
✅ |
within equipments_factors.csv |
e.g. "Evaporator" is used to get power in equipments_factors.csv, for EPFL these are the standard inventory classes in ENG. If equipment_class is not empty but the value is not listed to equipments_factors.csv, the row is ignored. A warning message is displayed in loading. |
| sub_class |
string |
❌ |
within equipments_factors.csv, can be None |
e.g. "Vacuum evaporators". The sub_class is filled by the user. Must be in the tuples equipment_class/sub_class within equipments_factors.csv else row ignored - (Warning message in loading if data uploaded with the wrong subclass) |
| active_usage_hours_per_week |
int |
❌ |
0 ≤ int ≤ 168 |
e.g. 23. The sum of active + passive must be ≤ 168 |
| standby_usage_hours_per_week |
int |
❌ |
0 ≤ int ≤ 168 |
e.g. 23. The sum of active + passive must be ≤ 168 |
| note |
string |
❌ |
- |
contains the note if needed |
equipment_factors.csv
| field |
type |
mandatory |
values constraints |
description |
| equipment_category |
string |
✅ |
non-empty string within : {scientific,it,other} |
e.g. scientific. Case-sensitive |
| equipment_class |
string |
✅ |
not empty string |
e.g. "Evaporator". For EPFL these are the standard inventory classes in ENG |
| sub_class |
string |
❌ |
can be None |
e.g. "Vacuum evaporators" |
| active_usage_hours_per_week |
int |
✅ |
0 ≤ int ≤ 168 |
e.g. 23. The sum of active + passive must be ≤ 168 |
| standby_usage_hours_per_week |
int |
✅ |
0 ≤ int ≤ 168 |
e.g. 23. The sum of active + passive must be ≤ 168 |
| active_power_w |
float |
✅ |
≥ 0 |
e.g. 23 |
| standby_power_w |
float |
✅ |
≥ 0 |
e.g. 23 |
| ef_kg_co2eq_per_kwh |
float |
✅ |
≥ 0 |
e.g. swiss mix 0.125 |
test calculation equipment
| equipment_id |
name |
equipment_class |
sub_class |
active_usage_hours_per_week |
standby_usage_hours_per_week |
kgco2eq |
note |
expected_result |
| EQ001 |
Power supplies |
Power supplies |
|
24 |
144 |
|
(100.0 * 24 + 0.0 * 144) / 1000 * 47 * 0.097 |
10.94 |
| EQ002 |
Amplifiers |
Amplifiers |
|
24 |
144 |
|
(20.0 * 24 + 10.0 * 144) / 1000 * 47 * 0.097 |
8.75 |
| EQ003 |
Large Motor |
Moteurs |
Large Motor/Generator |
24 |
144 |
|
(64000.0 * 24 + 100.0 * 144) / 1000 * 47 * 0.097 |
7068.27 |
| EQ004 |
Milling machine |
Milling machine |
|
24 |
144 |
|
(2300.0 * 24 + 30.0 * 144) / 1000 * 47 * 0.097 |
271.35 |
| EQ005 |
Arc Welding |
Press |
Arc Welding Power Sources |
24 |
144 |
|
(3500.0 * 24 + 30.0 * 144) / 1000 * 47 * 0.097 |
402.65 |
| EQ006 |
Old -80C freezer |
Lab Freezer / Frigde |
Old -80°C freezers (>12yo) |
168 |
0 |
900 |
Override test: given kgco2eq differs from calculation |
900 |
| EQ007 |
Servers |
Servers |
|
70 |
98 |
|
(500.0 * 70 + 100.0 * 98) / 1000 * 47 * 0.097 |
204.24 |
Purchases
purchases_common_data.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-digits, numbers only) |
| name |
string |
✅ |
non-empty string |
e.g. "HP Novobook" |
| supplier |
string |
❌ |
- |
e.g. "Bentley Systems International Ltd" |
| quantity |
float |
❌ |
0 ≤ float |
e.g. 3 |
| total_spent_amount |
float |
✅ |
0 ≤ float |
e.g. 3567 |
| currency |
string |
❌ |
in chf, eur, usd, gbp, aud, etc format. If not given, chf is used by default. |
e.g. eur |
| purchase_institutional_code |
string |
✅ |
within purchases_common_factors.csv |
e.g. UNSPSC code, as to within purchases_common_factors.csv |
| purchase_institutional_description |
string |
❌ |
- |
e.g. UNSPSC description, if not given compute with purchases_common_factors.csv |
| purchase_additional_code |
string |
❌ |
within purchases_common_factors.csv |
e.g. NACRES code, this column is used for the co2 emission calculations. For EPFL: data uploaded from the data manager will always have this column filled. But users can add purchases without this code and a static mapping (contained in the factors) is used for UNSPCS -> NACRES. |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given no calculation is performed for the line |
purchases_common_test.csv and purchases_common_template.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| name |
string |
✅ |
non-empty string |
e.g. "HP Novobook" |
| supplier |
string |
❌ |
- |
e.g. "Bentley Systems International Ltd" |
| quantity |
float |
❌ |
0 ≤ float |
e.g. 3 |
| total_spent_amount |
float |
✅ |
0 ≤ float |
e.g. 3567 |
| currency |
string |
❌ |
in chf, eur, usd, gbp, aud, etc format. If not given, chf is used by default. |
e.g. eur |
| purchase_institutional_code |
string |
✅ |
within purchases_factors.csv |
e.g. UNSPSC code |
| purchase_institutional_description |
string |
❌ |
- |
e.g. UNSPSC description, if not given compute with purchases_common_factors.csv |
| purchase_additional_code |
string |
❌ |
within purchases_factors.csv |
e.g. NACRES code |
| note |
string |
❌ |
- |
contains the note if needed |
purchases_common_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| currency |
string |
✅ |
in chf, eur, usd, gbp, aud, etc format. |
for labo1point5 is eur |
| purchase_category |
string |
✅ |
within it_equipment,other_purchases,scientific_equipment,services,vehicles,consumable_accessories,biological_chemical_gaseous_product |
e.g. vehicle. This columns is used to split the purchases into the subsections in the module. |
| purchase_institutional_code |
string |
✅ |
- |
e.g. UNSPSC code |
| purchase_institutional_description |
string |
❌ |
- |
e.g. UNSPSC description, in english |
| purchase_additional_code |
string |
❌ |
- |
e.g. NACRES code, optional because for EPFL we add a line per UNSPSC with the average to be used for purchases added by the user |
| ef_kg_co2eq_per_currency |
float |
✅ |
0 ≤ float |
e.g. 0.1 |
test calculation purchases_common
| name |
supplier |
quantity |
total_spent_amount |
currency |
purchase_institutional_code |
purchase_institutional_description |
purchase_additional_code |
note |
kg_co2eq |
expected_result |
| name 1 |
supplier 1 |
1 |
168.639 |
chf |
27112800 |
|
VA03 |
|
|
0.061372 |
| name 2 |
supplier 2 |
1 |
537.190 |
chf |
B |
|
KC01 |
|
|
0.151509 |
| name 3 |
supplier 1 |
3.2 |
7.86 |
chf |
31162800 |
|
KE31 |
|
|
0.002574 |
| name 4 |
supplier 2 |
1 |
100 |
chf |
10121700 |
|
|
here we use the UNSPSC factor, 100 * 1.067 / 1.173 * 0.88 |
|
0.088 |
| name 5 |
supplier 1 |
1.3 |
585 |
eur |
B |
|
NA12 |
|
|
0.797953964194373 |
| name 6 |
supplier 2 |
2.7 |
63.46 |
eur |
41120000 |
|
OA21 |
override test |
10 |
10 |
purchases_centralized_data.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-dits, numbers only) |
| name |
string |
✅ |
non-empty string |
e.g. "Liquid nitrogen" |
| unit |
string |
✅ |
- |
e.g. liter |
| annual_consumption |
float |
✅ |
- |
e.g. 45.05 |
| coef_to_kg |
float |
✅ |
non negative |
e.g. 3.05 |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given no calculation is performed for the line |
purchases_centralized_test.csv and purchases_centralized_template.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| name |
string |
✅ |
non-empty string |
e.g. "Liquid nitrogen" |
| unit |
string |
✅ |
- |
e.g. liter |
| annual_consumption |
float |
✅ |
- |
e.g. 45.05 |
| coef_to_kg |
float |
✅ |
non negative |
e.g. 3.05 |
| note |
string |
❌ |
no constraints |
contains the note if needed |
purchases_centralized_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| name |
string |
✅ |
non-empty string |
e.g. "Liquid nitrogen" |
| ef_kg_co2eq_per_kg |
float |
✅ |
0 ≤ float |
e.g. 0.1 |
test calculation purchases_centralized
| name |
unit |
annual_consumption |
coef_to_kg |
note |
kg_co2eq |
expected_result |
| liquid nitrogen |
liters |
500 |
0.808 |
500 * 0.808 * 0.1 |
|
40.40 |
| liquid nitrogen |
liters |
250 |
0.808 |
250 * 0.808 * 0.1 |
|
20.20 |
| liquid nitrogen |
kg |
100 |
1.0 |
100 * 1.0 * 0.1 |
|
10.00 |
| liquid nitrogen |
liters |
750 |
0.808 |
750 * 0.808 * 0.1 |
|
60.60 |
| liquid nitrogen |
kg |
80 |
1.0 |
80 * 1.0 * 0.1 |
|
8.00 |
| liquid nitrogen |
liters |
200 |
0.808 |
override test |
15 |
15 |
External Clouds & AI
external_ai_data.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-digits numbers only) |
| provider |
string |
✅ |
within external_ai_factors.csv |
e.g. name of the firm "Google" |
| usage_type |
string |
✅ |
within external_ai_factors.csv |
e.g. "text,video,image", tuple provider/usage_type within external_ai_factors. If not in provided tuple, the raw is ignored with a Warning message. |
| requests_per_user_per_day |
string |
✅ |
within "1-5 times per day", "5-20 times per day", "20-100 times per day", ">100 times per day" |
e.g. 1-5 times per day |
| fte_count |
float |
✅ |
1 ≤ float |
e.g. 2. By default the numbers shown is the total headcount of the unit. |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given no calculation is performed |
external_ai_test.csv and external_ai_template.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| provider |
string |
✅ |
have to be in external_ai_factors.csv |
e.g. name of the firm "Google" |
| usage_type |
string |
✅ |
have to be in external_ai_factors.csv |
e.g. "text,video,image" |
| requests_per_user_per_day |
string |
✅ |
within "1-5 times per day", "5-20 times per day", "20-100 times per day", ">100 times per day" |
e.g. 1-5 times per day |
| fte_count |
float |
✅ |
1 ≤ float |
e.g. 2. By default the numbers shown is the total headcount of the unit. |
| note |
string |
❌ |
- |
contains the note if needed |
external_ai_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| provider |
string |
✅ |
- |
e.g. name of the firm "Google" |
| usage_type |
string |
✅ |
- |
e.g. type of use "text,video,image" |
| ef_kg_co2eq_per_request |
float |
✅ |
0 ≤ float |
e.g. "0.05" |
test calculation external_ai
| provider |
usage_type |
requests_per_user_per_day |
fte_count |
note |
kg_co2eq |
expected_result |
| Claude (Anthropic) |
text |
10 |
5 |
5 * 10 * 235 * 0.0075 |
|
88.1250 |
| ChatGPT (OpenAI) |
image |
2 |
3 |
3 * 2 * 235 * 0.3 |
|
423.0000 |
| Mistral AI |
code |
15 |
2 |
2 * 15 * 235 * 0.15 |
|
1057.5000 |
| Gemini (Google) |
text |
5 |
4 |
4 * 5 * 235 * 0.0075 |
|
35.2500 |
| Copilot (Microsoft) |
image |
8 |
1 |
1 * 8 * 235 * 0.3 |
|
564.0000 |
| Claude (Anthropic) |
code |
20 |
2 |
2 * 20 * 235 * 0.15 |
|
1410.0000 |
| Other |
text |
3 |
3 |
3 * 3 * 235 * 0.0075 |
override test |
100 |
external_clouds_data.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-digits numbers only) |
| service_type |
string |
✅ |
within external_clouds_factors.csv |
e.g. one of storage,compute |
| provider |
string |
✅ |
within external_clouds_factors.csv |
e.g."AWS" |
| spent_amount |
float |
✅ |
0 ≤ float |
e.g. 299 |
| currency |
string |
❌ |
in chf, eur, usd format. If not given, eur is used by default. |
e.g. eur |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given no calculation is performed |
external_clouds_test.csv and external_clouds_template.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| service_type |
string |
✅ |
within external_clouds_factors.csv |
e.g. one of storage,compute |
| provider |
string |
✅ |
within external_clouds_factors.csv |
e.g."AWS" |
| spent_amount |
float |
✅ |
0 ≤ float |
e.g. 299 |
| currency |
string |
❌ |
in chf, eur, usd format. If not given, eur is used by default. |
e.g. eur |
| note |
string |
❌ |
- |
contains the note if need |
external_clouds_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| service_type |
string |
✅ |
not empty |
e.g. storage,compute |
| provider |
string |
✅ |
not empty |
e.g. firm |
| currency |
string |
✅ |
in chf, eur, usd format, not None. |
for EPFL -> eur |
| ef_kg_co2eq_per_currency |
float |
✅ |
0 ≤ float |
e.g. 0.8 |
test calculation external_clouds
| service_type |
provider |
spent_amount |
currency |
note |
kg_co2eq |
expected_result |
| storage |
AWS |
100 |
eur |
100 * 0.259 |
|
25.90 |
| compute |
GCP |
500 |
eur |
500 * 0.259 |
|
129.50 |
| storage |
Azure |
250 |
chf |
250 * 1.0672 * 0.259 |
|
69.10 |
| compute |
OVH |
300 |
chf |
300 * 1.0672 * 0.259 |
|
82.92 |
| storage |
AWS |
1000 |
usd |
1000 * 0.8849 * 0.259 (USD to EUR conversion) |
|
229.19 |
| compute |
GCP |
150 |
eur |
150 * 0.259 |
|
38.85 |
| storage |
OVH |
200 |
chf |
200 * 1.0672 * 0.259, override test |
50 |
50 |
| --- |
|
|
|
|
|
|
Travel
travel_planes_data.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (numbers only) |
| origin_iata |
string |
✅ |
IATA code |
e.g. "GVA". |
| destination_iata |
string |
✅ |
IATA code |
e.g. "JFK". |
| user_institutional_id |
string |
❌ |
- |
e.g. EPFL: SCIPER. It is not mandatory so that users can add travels also for external people, people outside the unit, etc. Data from the backoffice however should have a SCIPER. |
| departure_date |
string |
❌ |
ISO format YYYY-MM-DD |
e.g. "2025-05-15" if date format not recognized ignore row, id date not in the carbon report year ignore row. If None the row is considered. |
| number_of_trips |
int |
✅ |
1 ≤ int |
e.g. 2 |
| cabin_class |
string |
✅ |
within first,business,economy |
e.g. business. For EPFL when taken from API, premium economy needs to be classifed as eco. |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given no calculation is performed for the line. |
travel_planes_test.csv and travel_planes_template.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| origin_iata |
string |
✅ |
IATA code |
e.g. "GVA" |
| destination_iata |
string |
✅ |
IATA code |
e.g. "JFK" |
| user_institutional_id |
string |
❌ |
- |
e.g. EPFL: SCIPER |
| departure_date |
string |
❌ |
ISO format YYYY-MM-DD |
e.g. "2025-05-15 if date format not recognized ignore row, id date not in the carbon report year ignore row. If None the row is considered. |
| number_of_trips |
int |
✅ |
1 ≤ int |
e.g. 2 |
| cabin_class |
string |
✅ |
within first,business,economy |
e.g. business |
| note |
string |
❌ |
- |
contains the note if needed |
travel_planes_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| category |
string |
✅ |
within short_to_medium_haul, medium_to_long_haul |
e.g. "medium_to_long_haul" |
| cabin_class |
string |
✅ |
business, economy, first |
flight class to choose the corresponding factor. for EPFL: Premium economy is treated as economy, first class and business class have the same factor for short to mediul haul |
| ef_kg_co2eq_per_km |
float |
✅ |
0 ≤ float |
e.g. "0.345" |
| rfi_adjustment |
float |
✅ |
0 ≤ float |
The RFI (Radiative Forcing Index) for the methodology should be specified here, e.g. 2, 2.7, 3, etc. This is used to account for the total warming impact of flying. for EPFL: 1.35, which corresponds to transforming mobitool factors to 2.7 RFI as in atmosfair |
| min_distance |
float |
✅ |
in km, unique value |
e.g. "300" min distance of the category |
| max_distance |
float |
✅ |
in km, unique value |
e.g. "1200" max distance of the category |
travel_planes_locations_reference.csv
Data source
Airport location reference data is sourced from GeoNames, a geographical database covering all countries.
| field |
type |
mandatory |
values constraints |
example / notes |
| name |
string |
✅ |
- |
name of the location, typically the city or train station |
| airport_size |
string |
❌ |
within medium_airport,large_airport |
e.g. "medium_airport" |
| latitude |
float |
✅ |
- |
e.g. 46.2044 |
| longitude |
float |
✅ |
- |
e.g. 6.1432 |
| continent |
string |
❌ |
within EU,NA,SA,AF,AS,OC |
e.g. "EU" |
| country_code |
string |
❌ |
in ISO 3166-1 alpha-2 format or use RoW for rest of the world |
e.g. "CH" |
| iata_code |
string |
✅ |
IATA code of the airport |
e.g. "GVA" |
| municipality |
string |
❌ |
- |
e.g. "Geneva" |
| keywords |
string |
❌ |
- |
keywords to link the location with the possible different names in the data |
test calculation travel_planes
| origin_iata |
destination_iata |
user_institutional_id |
departure_date |
number_of_trips |
cabin_class |
note |
kg_co2eq |
expected_result |
| GVA |
CDG |
|
|
1 |
economy |
(407.6 + 95) km * 0.2906 * 1.35 * 1 |
|
197.18 |
| GVA |
LHR |
|
|
2 |
business |
(753.7 + 95) km * 0.4471 * 1.35 * 2 |
|
1024.57 |
| GVA |
FRA |
|
|
1 |
economy |
(459.2 + 95) km * 0.2906 * 1.35 * 1 |
|
217.41 |
| GVA |
JFK |
|
|
1 |
business |
(6201.1 + 95) km * 0.393 * 1.35 * 1 |
|
3340.39 |
| GVA |
LAX |
|
|
1 |
economy |
(9509.4 + 95) km * 0.1902 * 1.35 * 1 |
|
2466.12 |
| LHR |
JFK |
|
|
3 |
business |
(5540.0 + 95) km * 0.393 * 1.35 * 3 |
|
8968.97 |
| GVA |
CDG |
|
|
1 |
economy |
override test |
150 |
150 |
travel_trains_data.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-digits,numbers only) |
| origin_name |
string |
✅ |
train station name |
e.g. "Geneve Cornavin" TBD it accepts error in naming |
| origin_country_code |
string |
✅ |
ISO2 for the country |
e.g. CH for switzerland |
| destination_name |
string |
✅ |
train station name |
e.g. "Geneve Cornavin" TBD it accepts error in naming |
| destination_country_code |
string |
✅ |
ISO2 for the country |
e.g. CH for switzerland |
| user_institutional_id |
string |
❌ |
only number |
e.g. EPFL: SCIPER. It is not mandatory so that users can add travels also for external people, people outside the unit, etc. |
| departure_date |
string |
❌ |
ISO format YYYY-MM-DD |
e.g. "2025-05-15 if date format not recognized ignore row, id date not in the carbon report year ignore row. If None the row is considered. |
| number_of_trips |
int |
✅ |
1 ≤ int |
e.g. 2 |
| cabin_class |
string |
✅ |
within first,second |
e.g. second |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given no calculation is performed for the line |
Note
Traveler name is obtained with headcount
travel_trains_test.csv , travel_trains_template.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| origin_name |
string |
✅ |
train station name |
e.g. "Geneve Cornavin" TBD it accepts error in naming |
| origin_country_code |
string |
✅ |
ISO2 for the country |
e.g. CH for switzerland |
| destination_name |
string |
✅ |
train station name |
e.g. "Geneve Cornavin" TBD it accepts error in naming |
| destination_country_code |
string |
✅ |
ISO2 for the country |
e.g. CH for switzerland |
| user_institutional_id |
string |
❌ |
only number |
e.g. EPFL: SCIPER. It is not mandatory so that users can add travels also for external people, people outside the unit, etc. |
| departure_date |
string |
❌ |
ISO format YYYY-MM-DD |
e.g. "2025-05-15 if date format not recognized ignore row, id date not in the carbon report year ignore row. If None the row is considered. |
| number_of_trips |
int |
✅ |
1 ≤ int |
e.g. 2 |
| cabin_class |
string |
✅ |
within first,second |
e.g. second |
| note |
string |
❌ |
- |
contains the note if needed |
travel_trains_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| country_code |
string |
✅ |
in ISO 3166-1 alpha-2 format or use RoW for rest of the world |
e.g. "CH" |
| ef_kg_co2eq_per_km |
float |
✅ |
0 ≤ float |
e.g. "0.125" |
travel_trains_locations_reference.csv
Data source
Train station location reference data is sourced from GeoNames, a geographical database covering all countries.
| field |
type |
mandatory |
values constraints |
example / notes |
| name |
string |
✅ |
- |
name of the location, typically the city or train station |
| latitude |
float |
✅ |
- |
e.g. 46.2044 |
| longitude |
float |
✅ |
- |
e.g. 6.1432 |
| continent |
string |
❌ |
within EU,NA,SA,AF,AS,OC |
e.g. "EU" |
| country_code |
string |
✅ |
in ISO 3166-1 alpha-2 format or use RoW for rest of the world |
e.g. "CH" |
| municipality |
string |
❌ |
- |
e.g. "Geneva" |
| keywords |
string |
❌ |
- |
keywords to link the location with the possible different names in the data |
test calculation travel_trains
| origin_name |
origin_country_code |
destination_name |
destination_country_code |
user_institutional_id |
departure_date |
number_of_trips |
cabin_class |
note |
kg_co2eq |
expected_result |
| Genève |
CH |
Basel SBB |
CH |
|
|
1 |
|
(184.9 × 1.2) km × 0.00979 (CH) × 1 |
|
2.17 |
| Basel SBB |
CH |
Aachen Hbf |
DE |
|
|
2 |
|
(374.3 × 1.2) km × 0.0719 (DE) × 2 |
|
64.59 |
| Genève |
CH |
Paris |
FR |
|
|
1 |
|
(410.6 × 1.2) km × 0.0269 (FR) × 1 |
|
13.26 |
| Milano |
IT |
Aachen Hbf |
DE |
|
|
1 |
|
(630.6 × 1.2) km × 0.0719 (DE) × 1 |
|
54.41 |
| Genève |
CH |
Lyon |
FR |
|
|
3 |
|
(113.0 × 1.2) km × 0.0269 (FR) × 3 |
|
10.95 |
| Basel SBB |
CH |
Milano |
IT |
|
|
2 |
|
(260.0 × 1.2) km × 0.0491 (IT) × 2 |
|
30.64 |
| Genève |
CH |
Aachen Hbf |
DE |
|
|
1 |
|
(506.9 × 1.2) km × 0.0719 (DE) × 1, override test |
40 |
40 |
| Genève |
CH |
London |
GB |
|
|
1 |
|
(980.0 × 1.2) km × 0.0775 (RoW) × 1 |
|
90.78 |
Research Facilities
researchfacilities_common_data.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-digits, numbers only) |
| researchfacility_id |
string |
✅ |
within researchfacilities_common_factors.csv |
e.g. for EPFL: cf of research facilities |
| researchfacility_name |
string |
✅ |
within researchfacilities_common_factors.csv |
e.g. CIBM-GE |
| use |
float |
✅ |
0 ≤ float, in format of use_unit |
e.g. 34 |
| use_unit |
string |
✅ |
within researchfacilities_common_factors.csv |
e.g. chf, hours... if correspondence is not found in factors, the row is ignored with a warning message |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given no calculation is performed for the line. in this case this would correspond to the co2 generated by the unit use of the facility |
researchfacilities_common_test.csv and researchfacilities_common_template.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| researchfacility_id |
string |
✅ |
within researchfacilities_common_factors.csv |
e.g. for EPFL: cf of research facilities |
| researchfacility_name |
string |
✅ |
within researchfacilities_common_factors.csv |
e.g. CIBM-GE |
| use |
float |
✅ |
0 ≤ float, in format of use_unit |
e.g. 34 |
| use_unit |
string |
✅ |
within researchfacilities_common_factors.csv |
e.g. chf, hours... if correspondence is not found in factors, the row is ignored with a warning message |
| note |
string |
❌ |
- |
contains the note if needed |
researchfacilities_common_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| researchfacility_id |
string |
✅ |
|
e.g. for EPFL: cf of research facilities |
| researchfacility_name |
string |
✅ |
|
e.g. CIBM-GE |
| kg_co2eq_sum |
float |
❌ |
0 ≤ float |
e.g. 3555, not mandatory because the calculator is used to compute these results. however if this quantity is given here, it is taken instead of the calculator computation. It corresponds to the co2 for the research facility coming from purchases, equipment, buildings, process emissions and combustion emissions. |
| total_use |
float |
✅ |
0 ≤ float, in the unit of "use_unit" |
e.g. 34 |
| use_unit |
string |
✅ |
- |
typically currency, time or count : chf if total_use calculated by billing, or time in hrs or other. This info appears in the table for the users. |
Note
Important to push on the button 'compute missing factor' to calculate the kg_co2eq_sum for research facilities where this info was not known, through the calculator computation. If not done, the contribution of these research facilities will be 0.
researchfacilities_animals_data.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| unit_institutional_id |
string |
✅ |
numbers only |
for EPFL: cf_id (4-digits, numbers only) |
| researchfacility_id |
string |
✅ |
within researchfacilities_animals_factors.csv |
e.g. for EPFL: cf of research facilities |
| researchfacility_name |
string |
✅ |
within researchfacilities_animals_factors.csv |
e.g. CIBM-GE |
| researchfacility_type |
string |
✅ |
within researchfacilities_animals_factors.csv |
e.g. mice |
| use |
float |
✅ |
0 ≤ float, in format of use_unit |
e.g. 34 |
| use_unit |
string |
✅ |
within researchfacilities_animals_factors.csv |
e.g. housing |
| note |
string |
❌ |
- |
contains the note if needed |
| kg_co2eq |
float |
❌ |
- |
if given no calculation is performed for the line |
researchfacilities_animals_test.csv and researchfacilities_animals_template.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| researchfacility_id |
string |
✅ |
within researchfacilities_animals_factors.csv |
e.g. for EPFL: cf of research facilities |
| researchfacility_name |
string |
✅ |
within researchfacilities_animals_factors.csv |
e.g. CIBM-GE |
| researchfacility_type |
string |
✅ |
within researchfacilities_animals_factors.csv |
e.g. mice |
| use |
float |
✅ |
0 ≤ float, in format of use_unit |
e.g. 34 |
| use_unit |
string |
✅ |
within researchfacilities_animals_factors.csv |
e.g. housings |
| note |
string |
❌ |
- |
contains the note if needed |
researchfacilities_animals_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| researchfacility_id |
string |
✅ |
|
e.g. for EPFL: cf of research facilities |
| researchfacility_name |
string |
✅ |
|
e.g. CIBM-GE |
| processemissions_share |
float |
✅ |
0 ≤ float ≤ 1 |
e.g. 0.3, this is the share of process emissions in the total co2eq of the research facility. This is used to split the total co2eq into the different parts of the research facility (for animal facility, mice vs fish). |
| building_energycombustions_share |
float |
✅ |
0 ≤ float ≤ 1 |
e.g. 0.3, this is the share of building energy combustion emissions in the total co2eq of the research facility. This is used to split the total co2eq into the different parts of the research facility (for animal facility, mice vs fish). |
| building_rooms_share |
float |
✅ |
0 ≤ float ≤ 1 |
e.g. 0.1, this is the share of building rooms emissions in the total co2eq of the research facility. This is used to split the total co2eq into the different parts of the research facility (for animal facility, mice vs fish). |
| purchases_common_share |
float |
✅ |
0 ≤ float ≤ 1 |
e.g. 0.2, this is the share of purchases common emissions in the total co2eq of the research facility. This is used to split the total co2eq into the different parts of the research facility (for animal facility, mice vs fish). |
| purchases_additional_share |
float |
✅ |
0 ≤ float ≤ 1 |
e.g. 0.05, this is the share of purchases additional emissions in the total co2eq of the research facility. This is used to split the total co2eq into the different parts of the research facility (for animal facility, mice vs fish). |
| equipments_share |
float |
✅ |
0 ≤ float ≤ 1 |
e.g. 0.15, this is the share of equipments emissions in the total co2eq of the research facility. This is used to split the total co2eq into the different parts of the research facility (for animal facility, mice vs fish). |
| kg_co2eq_sum_processemissions |
float |
❌ |
0 ≤ float |
e.g. 3555, not mandatory because the calculator is used to compute these results. however if this quantity is given here, it is taken instead of the calculator computation. It corresponds to the co2 for the research facility coming from process emissions |
| kg_co2eq_sum_building_energycombustions |
float |
❌ |
0 ≤ float |
e.g. 3555, not mandatory because the calculator is used to compute these results. however if this quantity is given here, it is taken instead of the calculator computation. It corresponds to the co2 for the research facility coming from buidlings energy combustion |
| kg_co2eq_sum_building_rooms |
float |
❌ |
0 ≤ float |
e.g. 3555, not mandatory because the calculator is used to compute these results. however if this quantity is given here, it is taken instead of the calculator computation. It corresponds to the co2 for the research facility coming from building rooms |
| kg_co2eq_sum_purchases_common |
float |
❌ |
0 ≤ float |
e.g. 3555, not mandatory because the calculator is used to compute these results. however if this quantity is given here, it is taken instead of the calculator computation. It corresponds to the co2 for the research facility coming from purchases common |
| kg_co2eq_sum_purchases_additional |
float |
❌ |
0 ≤ float |
e.g. 3555, not mandatory because the calculator is used to compute these results. however if this quantity is given here, it is taken instead of the calculator computation. It corresponds to the co2 for the research facility coming from purchases additional |
| kg_co2eq_sum_equipments |
float |
❌ |
0 ≤ float |
e.g. 3555, not mandatory because the calculator is used to compute these results. however if this quantity is given here, it is taken instead of the calculator computation. It corresponds to the co2 for the research facility coming from equipments |
| researchfacility_type |
string |
✅ |
- |
e.g. mice |
| total_use |
float |
✅ |
0 ≤ float, in the unit of "use_unit" |
e.g. 34 |
| use_unit |
string |
✅ |
- |
e.g. housing |
Note
Important to push on the button 'compute missing factor' to calculate the kg_co2eq_sum_module_submodule where this info was not known, through the calculator computation. If not done, the contribution of these modules/submodules will be 0.
Additional Categories
Food, commuting and waste
These categories are related to the headcount. The total FTE is used to compute the values. For the logic of the calculation, all three categories - food, commuting, waste - are in the same files. A difference is made between student and members of staff, but waste has no difference in values.
headcount_members_factors.csv" & "headcount_students_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| headcount_category |
string |
✅ |
within food, commuting, waste |
e.g. food |
| headcount_class |
string |
✅ |
within the class of the categories, food: vegetarian, non_vegetarian , commuting: walking, cycling, powered_two_wheeler, public_transport, car, waste: incineration, composting, biogas, recycling |
the class of the category |
| headcount_subclass |
string |
❌ |
none |
the subclass of the category if needed |
| number_of_unit_per_fte |
float |
✅ |
0 ≤ float |
e.g. for food, this is the kg of food per FTE, for commuting this is the total km per FTE for the reference year, for waste this is the total kg of waste per FTE for the reference year |
| ef_kg_co2eq_per_unit |
float |
✅ |
0 ≤ float |
e.g. for food, this is the kg of co2eq per kg of food, for commuting this is the kg of co2eq per km, for waste this is the kg of co2eq per kg of waste |
| unit |
string |
✅ |
- |
e.g. for food, this is kg, for commuting this is km, for waste this is kg |
Note
No test and template files
Building grey energy
building_construction_renovation_factors.csv
| field |
type |
mandatory |
values constraints |
example / notes |
| building_name |
string |
✅ |
within building_rooms_reference.csv |
e.g. BCH |
| category |
string |
✅ |
within the class of the categories new-tech, new-env,ren-tech,ren-env,demolition |
the category of the specified category of grey energy |
| ef_kgco2eq_per_m2 |
float |
✅ |
0 ≤ float |
the kg of co2eq per m2 attributes to a specified category of grey energy |