Carbon Emission Calculation API

API ID 13723

Carbon footprint estimation for business travel, global hotel stays, vehicles usage, freight, eCommerce, shipments, fuel and electricity with supplementary APIs on airports and clustering results.

API Documentation

Endpoints

Request
# Emissions from Business Flight Travel Returns estimated greenhouse gas emissions (CO2e) in multiple units (grams, kilograms, metric tons, pounds) for business travel through flights/air, based on airport codes of arrival and departure, class of flight and number of passengers. This calculation is used for reporting Scope 3 emissions for individuals flying for work purposes. The footprint of a flight travel is calculated based on the distance between airports and the travelling class of the passenger. operationId: calculate_emissions_from_business_flight_travel ## Notes - If there are two passengers in the same flight, but sitting in different classes then two separate API calls are suggested, one for each passenger. - As the ICAO does not apply the radiative forcing (RF) multiplier (accounting for the wider climate effect of emissions arising from aircraft transport at altitude) or distance uplift factor to account for delays/circling and non-direct routes (i.e., not along the straight-line/great-circle between destinations), we have added an option for you to factor it in the calculation. Use the "add_rf" field to add this factor. - WTT (well-to-tank) emissions consist of all processes between the source of the fuel (the well) through the extraction, processing (refining), storage and delivery phases up until the point of use (the tank) in the plane before take-off. Using the "include_wtt" field will add the upstream emission associated with this flight in the estimation.
Endpoint ID: 31396
POST https://zylalabs.com/api/13723/carbon+emission+calculation+api/31396/flight+travel+estimates
INPUT PARAMETERS

Flight Travel Estimates — Endpoint Features

Object Description
number_of_passengers Required Default: 1. If a NULL or <0 is entered, it is set to 1
cluster_name Optional Identifier to log and aggregate these results under using the Cluster Data API
include_wtt Required The default value of "Y" includes the Well-to-Tank (WTT) factors while "N" bypasses it
cluster_name Optional Identifier to log and aggregate these results under using the Cluster Data API
cluster_name Optional Identifier to log and aggregate these results under using the Cluster Data API
add_rf Required The default value of "Y" adds the radiative forcing multiplier factor in the footprint calculation; "N" bypasses it
include_wtt Required The default value of "Y" includes the Well-to-Tank (WTT) factors while "N" bypasses it
number_of_passengers Required Default: 1. If a NULL or <0 is entered, it is set to 1
include_wtt Required The default value of "Y" includes the Well-to-Tank (WTT) factors while "N" bypasses it
add_rf Required The default value of "Y" adds the radiative forcing multiplier factor in the footprint calculation; "N" bypasses it
add_rf Required The default value of "Y" adds the radiative forcing multiplier factor in the footprint calculation; "N" bypasses it
round_trip Required The default value of "Y" means that the traveller has taken the flight from origin to destination and then back to the same origin in the same class, while a "N" means a one-way journey.
Request Body Required Json
flight_class Required The class in which the passenger is travelling. Allowed: [Economy, Premium, Business, First]. It is optional. For NULL or undefined values, an Average factor is used.
number_of_passengers Required Default: 1. If a NULL or <0 is entered, it is set to 1
round_trip Required The default value of "Y" means that the traveller has taken the flight from origin to destination and then back to the same origin in the same class, while a "N" means a one-way journey.
iata_airport_to Required The arrival airport's IATA airport code (The unique 3 digit geocode, also known as IATA location identifier, IATA station code, or location identifier)
round_trip Required The default value of "Y" means that the traveller has taken the flight from origin to destination and then back to the same origin in the same class, while a "N" means a one-way journey.
flight_class Required The class in which the passenger is travelling. Allowed: [Economy, Premium, Business, First]. It is optional. For NULL or undefined values, an Average factor is used.
iata_airport_from Required The departing airport's IATA airport code (The unique 3 digit geocode, also known as IATA location identifier, IATA station code, or location identifier)
flight_class Required The class in which the passenger is travelling. Allowed: [Economy, Premium, Business, First]. It is optional. For NULL or undefined values, an Average factor is used.
iata_airport_to Required The arrival airport's IATA airport code (The unique 3 digit geocode, also known as IATA location identifier, IATA station code, or location identifier)
iata_airport_to Required The arrival airport's IATA airport code (The unique 3 digit geocode, also known as IATA location identifier, IATA station code, or location identifier)

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

number_of_passengers
cluster_name
include_wtt
cluster_name
cluster_name
add_rf
include_wtt
number_of_passengers
include_wtt
add_rf
add_rf
round_trip
flight_class
number_of_passengers
round_trip
iata_airport_to
round_trip
flight_class
iata_airport_from
flight_class
iata_airport_to
iata_airport_to
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "type": "estimate-travel-flight",
        "iata_airport_from": "SFO",
        "airport_from": "San Francisco International Airport",
        "iata_airport_to": "KUL",
        "airport_to": "Kuala Lumpur International Airport",
        "flight_class": "Economy",
        "round_trip": "Y",
        "add_rf": "Y",
        "include_wtt": "Y",
        "number_of_passengers": 3,
        "co2e_gm": 10284950,
        "co2e_kg": 10284.95,
        "co2e_mt": 10.28,
        "co2e_lb": 22674.41,
        "explanation": "This emission profile is computed using the UK Government's 2026 conversion factors for greenhouse gas (GHG) reporting. The calculation is for 3 passengers travelling in Economy class between San Francisco International Airport(SFO) and Kuala Lumpur International Airport(KUL). The distance between these airports is estimated at 13,635 km, utilizing the Haversine equation for Great-Circle Distance (GCD). Since it is a round trip, the distance is doubled to 27,269 km. Radiative forcing uplift is included and indirect/WTT factors are added, as per inputs. Based on these operational parameters, the total footprint evaluates to 10,284,950 grams of CO2e. Standardized metric conversions render this as 10284.95 kg (rounded to two decimal places) or 10.28 metric tons. Scaled against imperial baselines using the conversion factor of 2.20462 (source: GHG conversion factors, 2026), the final metric is expressed as 22674.41 lbs."
    },
    "success": true,
    "status": 200
}
Flight Travel Estimates — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31396/flight+travel+estimates?number_of_passengers=3&include_wtt=Y&add_rf=Y&include_wtt=Y&number_of_passengers=3&include_wtt=Y&add_rf=Y&add_rf=Y&round_trip=Y&flight_class=Economy&number_of_passengers=3&round_trip=Y&iata_airport_to=KUL&round_trip=Y&flight_class=Economy&iata_airport_from=SFO&flight_class=Economy&iata_airport_to=KUL&iata_airport_to=KUL' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
    "cluster_name":"KrugerBrent-ConferenceLAX_Jun26",
    "iata_airport_from":"DXB",
    "iata_airport_to":"LAX",
    "flight_class":"Business",
    "round_trip":"Y",
    "add_rf":"Y",
    "include_wtt":"Y",
    "number_of_passengers":1
}'

    
Request
# Emissions from Hotel Stay Returns estimated greenhouse gas emissions (CO2e) in multiple units (grams, kilograms, metric tons, pounds) based on country of hotel, length of stay, room count, and hotel star rating. CarbonSutra's approach for calculating the carbon footprint of hotel stays is based on Cornell Hotel Sustainability Benchmark Index and UK government's GHG conversion factors published in 2026. operationId: calculate_emissions_from_hotel_stay
Endpoint ID: 31397
POST https://zylalabs.com/api/13723/carbon+emission+calculation+api/31397/hotel+stay+emission+estimates
INPUT PARAMETERS

Hotel Stay Emission Estimates — Endpoint Features

Object Description
Request Body Required Json
number_of_rooms Required Number of rooms booked, irrespective of count of persons per room. Default: 1
country_code Required Two digit ISO 3166-1 alpha-2 country code
cluster_name Optional Identifier to log and aggregate results under Cluster Data API
city_name Required City of hotel within the country
hotel_rating Required Expedia star classification rating of the hotel. Allowed: [2-5], Default: 4
number_of_nights Required Length of stay in nights. Default: 1
number_of_rooms Required Number of rooms booked, irrespective of count of persons per room. Default: 1
cluster_name Optional Identifier to log and aggregate results under Cluster Data API

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

number_of_rooms
country_code
cluster_name
city_name
hotel_rating
number_of_nights
number_of_rooms
cluster_name
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "type": "estimate-hotel-stay",
        "country": "Japan",
        "city_name": "Kyoto",
        "hotel_rating": 4,
        "number_of_nights": 5,
        "number_of_rooms": 1,
        "co2e_gm": 208850,
        "co2e_kg": 208.85,
        "co2e_mt": 0.21,
        "co2e_lb": 460.43,
        "explanation": "CarbonSutra uses the Cornell Hotel Sustainability Benchmarking Index 2026 (CHSB2026) for this calculation, specifically leveraging the mean value from the CHSB validity test for Measure 1 - HCMI Room Night Emission (Carbon Category). Because specific emission factors for Kyoto are unlisted in CHSB2026, fallback data for Japan has been applied to this calculation of one room and 5 nights. This methodology relies on the Expedia Star Rating classification system. Where regional data gaps exist, proxy assignments are made according to the transparent governance rules published on carbonsutra.com. For the hotel rating of four stars, an emission factor of 41.77 kgCO2e per room night is used. This footprint evaluates to 208,850 grams of CO2e. Standardized unit conversions render this as 208.85 kg (rounded to two decimal places) or 0.21 metric tons. Scaled against imperial baselines using the conversion factor of 2.20462 (source: GHG conversion factors, 2026), the final metric is expressed as 460.43 lbs."
    },
    "success": true,
    "status": 200
}
Hotel Stay Emission Estimates — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31397/hotel+stay+emission+estimates?number_of_rooms=1&country_code=JP&city_name=Kyoto&hotel_rating=4&number_of_nights=5&number_of_rooms=1' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
  "cluster_name": "KrugerBrent-Jun26",
  "country_code": "GB",
  "city_name": "Manchester",
  "hotel_rating": "5",
  "number_of_nights": 4,
  "number_of_rooms": 1
}'

    
Request
# Emissions from Vehicle Usage based on its type Returns estimated greenhouse gas emissions (CO2e) in multiple units (grams, kilograms, metric tons, pounds) for travel in vehicles based on its type. operationId: calculate_emissions_from_vehicle_usage_based_on_type
Endpoint ID: 31398
POST https://zylalabs.com/api/13723/carbon+emission+calculation+api/31398/vehicles+estimates+by+type
INPUT PARAMETERS

Vehicles Estimates by Type — Endpoint Features

Object Description
distance_value Required Distance travelled. If an undefined value is passed, it will be set to 1.00
fuel_type Required Applicable for cars, these 5 values are allowed: ["Diesel", "Petrol", "PHEV", "BEV", "Unknown"]. If unsure then use "Unknown", which is the default value.
include_wtt Optional The default value of "Y" includes the Well-to-Tank (WTT) factors while "N" bypasses it.
cluster_name Optional Identifier to log and aggregate results under the Cluster Data API
Request Body Required Json
vehicle_type Required Type of vehicle
distance_unit Required Enter "km" for kilometers and "mi" for miles. Default is "km"

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

distance_value
fuel_type
include_wtt
cluster_name
vehicle_type
distance_unit
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "type": "estimate-vehicle-usage",
        "vehicle_type": "Car-Type-Executive",
        "fuel_type": "Petrol",
        "distance_value": 4800,
        "distance_unit": "km",
        "include_wtt": "Y",
        "co2e_gm": 1232352,
        "co2e_kg": 1232.35,
        "co2e_mt": 1.23,
        "co2e_lb": 2716.86,
        "explanation": "CarbonSutra computed this emission profile using the UK Government's 2026 conversion factors for greenhouse gas (GHG) reporting. The car is an Executive type, running on petrol. For a transit distance of 4,800 kilometers and with indirect/WTT factors added, the total footprint evaluates to 1,232,352 grams of CO2e. Standardized metric conversions render this as 1232.35 kg (rounded to two decimal places) or 1.23 metric tons. Scaled against imperial baselines using the conversion factor of 2.20462 (source: GHG conversion factors, 2026), the final metric is expressed as 2716.86 lbs."
    },
    "success": true,
    "status": 200
}
Vehicles Estimates by Type — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31398/vehicles+estimates+by+type?distance_value=4800&fuel_type=petrol&vehicle_type=Car-Type-Executive&distance_unit=km' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
    "cluster_name":"KrugerBrent-Exhibition-2025",
    "vehicle_type":"Car-Type-Supermini",
    "fuel_type":"petrol",
    "distance_value":8800,
    "distance_unit":"km",
    "include_wtt":"N"
}'

    
Request
# Emissions from Vehicle Usage based on its Make/Model Returns estimated greenhouse gas emissions (CO2e) in multiple units (grams, kilograms, metric tons, pounds) for travel in vehicles based on its make and model. 145 Makes and 5,000 models are covered. To get the specific name of make and model, use the supplementary APIs. ## Notes - If you do not know the make and model of vehicle, we suggest to use the API which calculates emissions by Vehicle Type. - For dual fuel vehicles, the average of emissions from its conventional and alternative fuels is used. - If a model is released across multiple years by the same maker, then the emissions for that model are averaged.
Endpoint ID: 31399
POST https://zylalabs.com/api/13723/carbon+emission+calculation+api/31399/vehicles+estimates+by+model
INPUT PARAMETERS

Vehicles Estimates by Model — Endpoint Features

Object Description
vehicle_model Required Name of Vehicle Model. Retrieve it from Supplementary API or documentation
distance_unit Required Enter "km" for kilometers and "mi" for miles. Default is "mi".
distance_value Required Distance travelled. If an undefined value is passed, it will be set to 1.00
cluster_name Optional Identifier to log and aggregate these results under using the Cluster Data API
Request Body Required Json
vehicle_make Required Name of Vehicle Make. Retrieve it from Supplementary API or documentation

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

vehicle_model
distance_unit
distance_value
cluster_name
vehicle_make
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "type": "estimate-vehicle",
        "distance_unit": "km",
        "distance_value": 2100,
        "vehicle_make": "Lexus",
        "vehicle_model": "RX 300",
        "co2e_gm": 630686,
        "co2e_kg": 630.69,
        "co2e_mt": 0.63,
        "co2e_lb": 1390.43
    },
    "success": true,
    "status": 200
}
Vehicles Estimates by Model — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31399/vehicles+estimates+by+model?vehicle_model=rx 300&distance_unit=km&distance_value=2100&vehicle_make=lexus' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
    "cluster_name":"KB-Oct-2025",
    "distance_unit":"km",
    "distance_value":9500,
    "vehicle_make":"Lexus",
    "vehicle_model":"RX 300"
}'

    
Request
# Emissions from Electricity Usage Returns estimated greenhouse gas emissions (CO2e) in multiple units (grams, kilograms, metric tons, pounds) from electricity usage based on coutnry name and units of electricity consumed. Data from nearly 90 countries for years 2020, 2024 and 2026, from multiple sources has been compiled. operationId: calculate_emissions_from_electricity_usage
Endpoint ID: 31400
POST https://zylalabs.com/api/13723/carbon+emission+calculation+api/31400/electricity+usage+estimates
INPUT PARAMETERS

Electricity Usage Estimates — Endpoint Features

Object Description
Request Body Required Json
country_name Required Name of the country for which the emission is being measured.
electricity_unit Required Electricity unit of consumption. Allowed values: [KWh, MWh]. Default: MWh
electricity_value Required Number of units of electricity consumed. If an undefined value is passed, it will be set to 1.00
cluster_name Optional Identifier to log and aggregate results under Cluster Data API

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

country_name
electricity_unit
electricity_value
cluster_name
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "type": "estimate-electricity",
        "electricity_unit": "MWh",
        "electricity_value": 4000,
        "country_name": "France",
        "co2e_gm": 172000000,
        "co2e_kg": 172000,
        "co2e_mt": 172,
        "co2e_lb": 379194.64
    },
    "success": true,
    "status": 200
}
Electricity Usage Estimates — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31400/electricity+usage+estimates?country_name=france&electricity_unit=MWH&electricity_value=4000' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
  "country_name":"Germany",  
  "electricity_unit":"mwh",
  "electricity_value":1100
}'

    
Request
# Emissions from Fuel Consumption Returns estimated greenhouse gas emissions (CO2e) in multiple units (grams, kilograms, metric tons, pounds) based on usage, fuel name and its value in tonnes. CarbonSutra computes the emissions from stationary combustion fuels which are burnt in a fixed unit or asset owned or controlled by the reporting organization, and usually reported as a Scope 1 direct emission. The source of data and methodology of emission factor calculation are from UK government's GHG conversion factors of 2026. operationId: calculate_emissions_from_fuel_consumption
Endpoint ID: 31401
POST https://zylalabs.com/api/13723/carbon+emission+calculation+api/31401/fuel+combustion+estimates
INPUT PARAMETERS

Fuel Combustion Estimates — Endpoint Features

Object Description
fuel_usage Required Fuel usage or activity. Allowed: ["Gas", "Liquid", "Solid"]
Request Body Required Json
fuel_usage Required Fuel usage or activity. Allowed: ["Gas", "Liquid", "Solid"]
fuel_name Required The fuel name is based on value of fuel usage field. Only the following values are allowed: - For fuel_usage = ""gas"", the allowed values for fuel_name are: [Butane, CNG, LNG, LPG, Natural gas, Natural gas (100% mineral blend), Other petroleum gas, Propane]- For fuel_usage = ""liquid"", the allowed values for fuel_name are: [Aviation spirit, Aviation turbine fuel, Burning oil, Diesel (100% mineral diesel), Diesel (average biofuel blend), Fuel oil, Gas oil, Lubricants, Marine fuel oil, Marine gas oil, Naphtha, Petrol (100% mineral petrol), Petrol (average biofuel blend), Processed fuel oils - distillate oil, Processed fuel oils - residual oil, Refinery miscellaneous, Waste oils]- For fuel_usage = ""solid"", the allowed values for fuel_name are: [Coal (domestic), Coal (electricity generation - home produced coal only), Coal (electricity generation), Coal (industrial), Coking coal, Petroleum coke]
fuel_name Required The fuel name is based on value of fuel usage field. Only the following values are allowed: - For fuel_usage = ""gas"", the allowed values for fuel_name are: [Butane, CNG, LNG, LPG, Natural gas, Natural gas (100% mineral blend), Other petroleum gas, Propane]- For fuel_usage = ""liquid"", the allowed values for fuel_name are: [Aviation spirit, Aviation turbine fuel, Burning oil, Diesel (100% mineral diesel), Diesel (average biofuel blend), Fuel oil, Gas oil, Lubricants, Marine fuel oil, Marine gas oil, Naphtha, Petrol (100% mineral petrol), Petrol (average biofuel blend), Processed fuel oils - distillate oil, Processed fuel oils - residual oil, Refinery miscellaneous, Waste oils]- For fuel_usage = ""solid"", the allowed values for fuel_name are: [Coal (domestic), Coal (electricity generation - home produced coal only), Coal (electricity generation), Coal (industrial), Coking coal, Petroleum coke]
fuel_value Required The amount of fuel that is consumed in number of tonnes. Default is 1.00
fuel_value Required The amount of fuel that is consumed in number of tonnes. Default is 1.00
cluster_name Optional Identifier to log and aggregate results under Cluster Data API
cluster_name Optional Identifier to log and aggregate results under Cluster Data API

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

fuel_usage
fuel_usage
fuel_name
fuel_name
fuel_value
fuel_value
cluster_name
cluster_name
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "type": "estimate-fuel",
        "fuel_usage": "gas",
        "fuel_name": "CNG",
        "fuel_unit": "tonnes",
        "fuel_value": "4500",
        "co2e_gm": 11284759845,
        "co2e_kg": 11284759.85,
        "co2e_mt": 11284.76,
        "co2e_lb": 24878607.26
    },
    "success": true,
    "status": 200
}
Fuel Combustion Estimates — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31401/fuel+combustion+estimates?fuel_usage=gas&fuel_usage=gas&fuel_name=CNG&fuel_name=CNG&fuel_value=4500&fuel_value=4500' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
    "cluster_name":"KrugerBrent-Plant3A-May26",
    "fuel_usage":"liquid",
    "fuel_name":"Gas oil",
    "fuel_value":7800
}'

    
Request
# Emissions from Freight Shipping Returns estimated greenhouse gas emissions (CO2e) in multiple units (grams, kilograms, metric tons, pounds) for freight shipments through Road, Rail, Air and Sea (categorized into Short Sea and Deep Sea). Two additional calculations for Intermodal shipping are available: 1) Road with Rail and 2) Road with Short Sea. In both cases, the road distance is assumed to be 10% of the entire journey. operationId: calculate_emissions_from_shipment_of_freight
Endpoint ID: 31402
POST https://zylalabs.com/api/13723/carbon+emission+calculation+api/31402/freight+shipping+estimates
INPUT PARAMETERS

Freight Shipping Estimates — Endpoint Features

Object Description
freight_weight Required Weight of freight in kilograms. If a NULL or <=0 is entered, it is set to 1.00
Request Body Required Json
distance_value Required Distance of journey in kilometers (KM). If a NULL or <=0 is entered, it is set to 1.00
transport_mode Required The mode of shipment of freight. Deep sea (value: DeepSea) shipping refers to the maritime transport of goods on intercontinental routes, crossing oceans as opposed to short sea (value: ShortSea) shipping over relatively short distances.​ For Intermodal shipping of 1) Road with Rail and 2) Road with Short Sea, the road distance is assumed to be at 10% of the entire journey.
cluster_name Optional Identifier to log and aggregate results under the Cluster Data API
freight_weight Required Weight of freight in kilograms. If a NULL or <=0 is entered, it is set to 1.00
distance_value Required Distance of journey in kilometers (KM). If a NULL or <=0 is entered, it is set to 1.00
cluster_name Optional Identifier to log and aggregate results under the Cluster Data API

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

freight_weight
distance_value
transport_mode
cluster_name
freight_weight
distance_value
cluster_name
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "type": "estimate-freight",
        "distance_value": 2000,
        "transport_mode": "rail",
        "freight_weight": 2235,
        "co2e_gm": 98340,
        "co2e_kg": 98.34,
        "co2e_mt": 0.1,
        "co2e_lb": 216.8
    },
    "success": true,
    "status": 200
}
Freight Shipping Estimates — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31402/freight+shipping+estimates?freight_weight=2235&distance_value=2000&transport_mode=rail&freight_weight=2235&distance_value=2000' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
    "cluster_name":"KrugerBrent-PO72-Feb26",
    "transport_mode":"Rail",
    "distance_value":1500,
    "freight_weight":19000
}'

    
Request
# Emissions from eCommerce Shipments Returns estimated greenhouse gas emissions (CO2e) in multiple units (grams, kilograms, metric tons, pounds) for eCommerce shipments. This is an advanced algorithm to estimate the emissions of a package's journey from its shipment location to the collection point. If the distance between two postal codes is above a threshold, we find the nearest airports from the origin and then from the destination location. The final distance of journey is then a sum of the distance between the origin postal code and nearest airport by land, air travel between the airports closest to the origin and the destination and finally, land travel between destination airport and postal code of collection point by land. The final calculation follows ECTA/Cefic and BEIS/DEFRA's recommended conversion factors and works on a database of over 1.5 million postal codes across 95 countries and 9,000 global airports. operationId: calculate_emissions_from_ecommerce_shipment
Endpoint ID: 31403
POST https://zylalabs.com/api/13723/carbon+emission+calculation+api/31403/ecommerce+shipment+estimates
INPUT PARAMETERS

eCommerce Shipment Estimates — Endpoint Features

Object Description
Request Body Required Json
origin_country_code Required Two letter ISO country code of the origin, ie from where the package is being sent
origin_postal_code Required The postal code within the origin country from where the package is being shipped
destination_country_code Required Two letter ISO country code of the destination, ie to where the package is being sent
destination_postal_code Required The postal code within the destination country to where the package is being shipped
package_weight Required Weight of package in kilograms. If a NULL or <=0 is entered, it is set to 1.00
add_rf Optional The default value of "Y" adds the radiative forcing multiplier factor in the footprint calculation; "N" bypasses it
include_wtt Optional The default value of "Y" includes the Well-to-Tank (WTT) factors while "N" bypasses it
cluster_name Optional Identifier to log and aggregate results under the Cluster Data API

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

origin_country_code
origin_postal_code
destination_country_code
destination_postal_code
package_weight
add_rf
include_wtt
cluster_name
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "type": "estimate-ecommerce",
        "origin_country_code": "SG",
        "origin_postal_code": "436915",
        "destination_country_code": "IN",
        "destination_postal_code": "248001",
        "package_weight": 3.5,
        "add_rf": "Y",
        "include_wtt": "Y",
        "co2e_gm": 15,
        "co2e_kg": 0.02,
        "co2e_mt": 0,
        "co2e_lb": 0.04
    },
    "success": true,
    "status": 200
}
ECommerce Shipment Estimates — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31403/ecommerce+shipment+estimates?origin_country_code=SG&origin_postal_code=436915&destination_country_code=IN&destination_postal_code=248001&package_weight=3.5&add_rf=Y&include_wtt=Y' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
    "cluster_name": "KrugerBrent_Marketing_Oct25",
    "origin_country_code": "IN",
    "origin_postal_code": "604407",
    "destination_country_code": "SG",
    "destination_postal_code": "436915",
    "package_weight":24.40,
    "add_rf": "Y",
    "include_wtt": "Y"
}'

    
Request
# Airport to Nearest Airport Returns the distance in kilometers of the closest airport from a given airport code, along with name and IATA code, using Haversine function. operationId: find_nearest_airport_from_another_airport
Endpoint ID: 31404
GET https://zylalabs.com/api/13723/carbon+emission+calculation+api/31404/airport+to+nearest+airport
INPUT PARAMETERS

Airport to Nearest Airport — Endpoint Features

Object Description
iata_airport_code Required An IATA airport code is unique 3 digit geocode (also known as IATA location identifier, IATA station code, or location identifier)
same_country Required A value of "Y" will result in closest airport with the same country of IATA Code, else the country borders will be ignored and the nearest airport will be found.

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

iata_airport_code
same_country
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "airport_from": "San Francisco International Airport",
        "closest_airport_code": "SQL",
        "closest_airport_name": "San Carlos Airport",
        "distance": "16.13"
    },
    "success": true,
    "status": 200
}
Airport to Nearest Airport — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31404/airport+to+nearest+airport?iata_airport_code=SFO&same_country=Y' --header 'Authorization: Bearer YOUR_API_KEY' 


    
Request
# Postal Code to Nearest Airport Returns the distance in kilometers bewteen a postal code and the nearlest airport to it, using Haversine function. This is an advanced algorithm which takes a postal code and country code as input and returns the nearest airport its latitude/longitude value. The distance between the coordinates of postal code and its airport is measured using Haversine function and the returned value is in kilometers. The data has instances of multiple addresses with different values of latitude/longitude associated with the same postal code. For such cases, an array of all addresses and their distance with nearest airport for the same postal code is returned. The source of 1.5 million postal code data is taken as it is from https://public.opendatasoft.com/explore/dataset/geonames-postal-code/. For airports, the publicly available database of IATA codes and airport names is used. operationId: find_nearest_airport_from_postal_code
Endpoint ID: 31405
GET https://zylalabs.com/api/13723/carbon+emission+calculation+api/31405/postal+code+to+nearest+airport
INPUT PARAMETERS

Postal Code to Nearest Airport — Endpoint Features

Object Description
country_code Required Two digit ISO 3166-1 alpha-2 country code.
postal_code Required A valid postal code of a location

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

country_code
postal_code
API EXAMPLE RESPONSE
JSON
{
    "data": [
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Dehradun City Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Kanwali Road Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Patel Nagar (Dehradun) Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "CDA(A.F) Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Hathi Barkala Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Neshvilla Road Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Sachivalaya Parisar Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Dalanwala Dehradun Uttarakhand",
            "distance": "18.14",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Arahat Bazar Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Dehradun IBC Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Rispana Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Nivh Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Karanpur Dehradun Uttarakhand",
            "distance": "18.82",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Govindgarh (Dehradun) Dehradun Uttarakhand",
            "distance": "21.5",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Dehradun G.P.O. Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Kanwali Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Dilaram Bazar Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Araghar Dehradun Uttarakhand",
            "distance": "17.58",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Dehradun Kty Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Sayedwala Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Cannaught Place Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Mothrowala Dehradun Uttarakhand",
            "distance": "19.69",
            "unit": "km"
        },
        {
            "airport_name": "Dehradun Jolly Grant Airport",
            "iata_code": "DED",
            "postal_code": "248001",
            "address": "Ballupur Dehradun Uttarakhand",
            "distance": "22.64",
            "unit": "km"
        }
    ],
    "success": true,
    "status": 200
}
Postal Code to Nearest Airport — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31405/postal+code+to+nearest+airport?country_code=IN&postal_code=248001' --header 'Authorization: Bearer YOUR_API_KEY' 


    
Request
# Distance between Two Airports Returns the distance between two IATA airport codes in kilometers, using Haversine function. operationId: find_distance_between_two_airports
Endpoint ID: 31406
GET https://zylalabs.com/api/13723/carbon+emission+calculation+api/31406/distance+between+two+airports
INPUT PARAMETERS

Distance between Two Airports — Endpoint Features

Object Description
iata_airport_from Required The first (or from) IATA airport code is unique 3 digit geocode (also known as IATA location identifier, IATA station code or location identifier)
iata_airport_to Required The second (or to) IATA airport code is unique 3 digit geocode (also known as IATA location identifier, IATA station code or location identifier)

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

iata_airport_from
iata_airport_to
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "airport_from": "Ninoy Aquino International Airport",
        "airport_to": "Tokyo Haneda International Airport",
        "distance": 2996.08
    },
    "success": true,
    "status": 200
}
Distance between Two Airports — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31406/distance+between+two+airports?iata_airport_from=MNL&iata_airport_to=HND' --header 'Authorization: Bearer YOUR_API_KEY' 


    
Request
# Airports Keywords Search Returns the lists of airport names and Airport IATA code which matches the keyword. The algorithm searches through airport names, IATA code, names of state and information from other sources. operationId: search_airports_based_on_keywords
Endpoint ID: 31407
GET https://zylalabs.com/api/13723/carbon+emission+calculation+api/31407/airports+keyword+search
INPUT PARAMETERS

Airports Keyword Search — Endpoint Features

Object Description
keyword Required A keyword to search for the airport records

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

keyword
API EXAMPLE RESPONSE
JSON
{
    "data": [
        {
            "iata_code": "DEL",
            "airport_name": "Indira Gandhi International Airport"
        }
    ],
    "success": true,
    "status": 200
}
Airports Keyword Search — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31407/airports+keyword+search?keyword=delhi' --header 'Authorization: Bearer YOUR_API_KEY' 


    
Request
## List of all Vehicle Makes Returns a list of all vehicle makers and their number of models, which can be used in getting list of models and then estimating footprints. This API is primarily used by application developers.
Endpoint ID: 31408
GET https://zylalabs.com/api/13723/carbon+emission+calculation+api/31408/vehicle+makes
INPUT PARAMETERS

Free test requests remaining: 3 of 3.

This endpoint does not require any input parameters.

API EXAMPLE RESPONSE
JSON
{
    "data": [
        {
            "make": "Acura",
            "number_of_models": 51
        },
        {
            "make": "Alfa Romeo",
            "number_of_models": 13
        },
        {
            "make": "AM General",
            "number_of_models": 4
        },
        {
            "make": "American Motors Corporation",
            "number_of_models": 4
        },
        {
            "make": "ASC Incorporated",
            "number_of_models": 1
        },
        {
            "make": "Aston Martin",
            "number_of_models": 42
        },
        {
            "make": "Audi",
            "number_of_models": 170
        },
        {
            "make": "Aurora Cars Ltd",
            "number_of_models": 1
        },
        {
            "make": "Autokraft Limited",
            "number_of_models": 2
        },
        {
            "make": "Avanti Motor Corporation",
            "number_of_models": 1
        },
        {
            "make": "Azure Dynamics",
            "number_of_models": 1
        },
        {
            "make": "Bentley",
            "number_of_models": 30
        },
        {
            "make": "Bertone",
            "number_of_models": 1
        },
        {
            "make": "Bill Dovell Motor Car Company",
            "number_of_models": 2
        },
        {
            "make": "Bitter Gmbh and Co. Kg",
            "number_of_models": 2
        },
        {
            "make": "BMW",
            "number_of_models": 434
        },
        {
            "make": "BMW Alpina",
            "number_of_models": 2
        },
        {
            "make": "Bugatti",
            "number_of_models": 5
        },
        {
            "make": "Buick",
            "number_of_models": 50
        },
        {
            "make": "BYD",
            "number_of_models": 1
        },
        {
            "make": "Cadillac",
            "number_of_models": 84
        },
        {
            "make": "CCC Engineering",
            "number_of_models": 1
        },
        {
            "make": "Chevrolet",
            "number_of_models": 277
        },
        {
            "make": "Chrysler",
            "number_of_models": 64
        },
        {
            "make": "CODA Automotive",
            "number_of_models": 1
        },
        {
            "make": "Consulier Industries Inc",
            "number_of_models": 1
        },
        {
            "make": "CX Automotive",
            "number_of_models": 7
        },
        {
            "make": "Dabryan Coach Builders Inc",
            "number_of_models": 1
        },
        {
            "make": "Dacia",
            "number_of_models": 3
        },
        {
            "make": "Daewoo",
            "number_of_models": 8
        },
        {
            "make": "Daihatsu",
            "number_of_models": 3
        },
        {
            "make": "Dodge",
            "number_of_models": 124
        },
        {
            "make": "E. P. Dutton, Inc.",
            "number_of_models": 1
        },
        {
            "make": "Eagle",
            "number_of_models": 10
        },
        {
            "make": "Environmental Rsch and Devp Corp",
            "number_of_models": 1
        },
        {
            "make": "Evans Automobiles",
            "number_of_models": 2
        },
        {
            "make": "Excalibur Autos",
            "number_of_models": 1
        },
        {
            "make": "Federal Coach",
            "number_of_models": 14
        },
        {
            "make": "Ferrari",
            "number_of_models": 82
        },
        {
            "make": "Fiat",
            "number_of_models": 10
        },
        {
            "make": "Fisker",
            "number_of_models": 2
        },
        {
            "make": "Ford",
            "number_of_models": 266
        },
        {
            "make": "General Motors",
            "number_of_models": 1
        },
        {
            "make": "Genesis",
            "number_of_models": 17
        },
        {
            "make": "Geo",
            "number_of_models": 15
        },
        {
            "make": "GMC",
            "number_of_models": 173
        },
        {
            "make": "Goldacre",
            "number_of_models": 1
        },
        {
            "make": "Grumman Allied Industries",
            "number_of_models": 1
        },
        {
            "make": "Grumman Olson",
            "number_of_models": 1
        },
        {
            "make": "Honda",
            "number_of_models": 74
        },
        {
            "make": "Hummer",
            "number_of_models": 2
        },
        {
            "make": "Hyundai",
            "number_of_models": 112
        },
        {
            "make": "Import Foreign Auto Sales Inc",
            "number_of_models": 1
        },
        {
            "make": "Import Trade Services",
            "number_of_models": 11
        },
        {
            "make": "INEOS Automotive",
            "number_of_models": 2
        },
        {
            "make": "Infiniti",
            "number_of_models": 87
        },
        {
            "make": "Isis Imports Ltd",
            "number_of_models": 1
        },
        {
            "make": "Isuzu",
            "number_of_models": 36
        },
        {
            "make": "J.K. Motors",
            "number_of_models": 21
        },
        {
            "make": "Jaguar",
            "number_of_models": 105
        },
        {
            "make": "JBA Motorcars, Inc.",
            "number_of_models": 1
        },
        {
            "make": "Jeep",
            "number_of_models": 78
        },
        {
            "make": "Kandi",
            "number_of_models": 1
        },
        {
            "make": "Karma",
            "number_of_models": 4
        },
        {
            "make": "Kenyon Corporation Of America",
            "number_of_models": 4
        },
        {
            "make": "Kia",
            "number_of_models": 81
        },
        {
            "make": "Koenigsegg",
            "number_of_models": 2
        },
        {
            "make": "Laforza Automobile Inc",
            "number_of_models": 1
        },
        {
            "make": "Lambda Control Systems",
            "number_of_models": 1
        },
        {
            "make": "Lamborghini",
            "number_of_models": 39
        },
        {
            "make": "Land Rover",
            "number_of_models": 76
        },
        {
            "make": "Lexus",
            "number_of_models": 112
        },
        {
            "make": "Lincoln",
            "number_of_models": 46
        },
        {
            "make": "London Coach Co Inc",
            "number_of_models": 1
        },
        {
            "make": "London Taxi",
            "number_of_models": 1
        },
        {
            "make": "Lordstown",
            "number_of_models": 1
        },
        {
            "make": "Lotus",
            "number_of_models": 10
        },
        {
            "make": "Lucid",
            "number_of_models": 20
        },
        {
            "make": "Mahindra",
            "number_of_models": 1
        },
        {
            "make": "Maserati",
            "number_of_models": 59
        },
        {
            "make": "Maybach",
            "number_of_models": 6
        },
        {
            "make": "Mazda",
            "number_of_models": 83
        },
        {
            "make": "Mcevoy Motors",
            "number_of_models": 4
        },
        {
            "make": "McLaren Automotive",
            "number_of_models": 27
        },
        {
            "make": "Mercedes-Benz",
            "number_of_models": 435
        },
        {
            "make": "Mercury",
            "number_of_models": 51
        },
        {
            "make": "Merkur",
            "number_of_models": 2
        },
        {
            "make": "MINI",
            "number_of_models": 51
        },
        {
            "make": "Mitsubishi",
            "number_of_models": 56
        },
        {
            "make": "Mobility Ventures LLC",
            "number_of_models": 2
        },
        {
            "make": "Morgan",
            "number_of_models": 1
        },
        {
            "make": "Nissan",
            "number_of_models": 140
        },
        {
            "make": "Oldsmobile",
            "number_of_models": 35
        },
        {
            "make": "Pagani",
            "number_of_models": 3
        },
        {
            "make": "Panos",
            "number_of_models": 1
        },
        {
            "make": "Panoz Auto-Development",
            "number_of_models": 1
        },
        {
            "make": "Panther Car Company Limited",
            "number_of_models": 1
        },
        {
            "make": "PAS Inc - GMC",
            "number_of_models": 2
        },
        {
            "make": "PAS, Inc",
            "number_of_models": 2
        },
        {
            "make": "Peugeot",
            "number_of_models": 8
        },
        {
            "make": "Pininfarina",
            "number_of_models": 1
        },
        {
            "make": "Plymouth",
            "number_of_models": 23
        },
        {
            "make": "Polestar",
            "number_of_models": 11
        },
        {
            "make": "Pontiac",
            "number_of_models": 60
        }
    ],
    "_note": "Response truncated for documentation purposes"
}
Vehicle Makes — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31408/vehicle+makes' --header 'Authorization: Bearer YOUR_API_KEY' 


    
Request
## List of all Models for a specific Vehicle Make Returns a list of all models for a specific vehicle maker's name.
Endpoint ID: 31409
GET https://zylalabs.com/api/13723/carbon+emission+calculation+api/31409/vehicle+models
INPUT PARAMETERS

Vehicle Models — Endpoint Features

Object Description
Request Body Required Json
vehicle_make Required

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

API EXAMPLE RESPONSE
JSON
{
    "data": [
        {
            "model": "CT 200h"
        },
        {
            "model": "ES 250"
        },
        {
            "model": "ES 250 AWD"
        },
        {
            "model": "ES 300"
        },
        {
            "model": "ES 300h"
        },
        {
            "model": "ES 330"
        },
        {
            "model": "ES 350"
        },
        {
            "model": "ES 350 F Sport"
        },
        {
            "model": "GS 200t"
        },
        {
            "model": "GS 200t F Sport"
        },
        {
            "model": "GS 300"
        },
        {
            "model": "GS 300 4WD"
        },
        {
            "model": "GS 300 F Sport"
        },
        {
            "model": "GS 300/GS 400"
        },
        {
            "model": "GS 300/GS 430"
        },
        {
            "model": "GS 350"
        },
        {
            "model": "GS 350 AWD"
        },
        {
            "model": "GS 350 F Sport"
        },
        {
            "model": "GS 430"
        },
        {
            "model": "GS 450h"
        },
        {
            "model": "GS 460"
        },
        {
            "model": "GS F"
        },
        {
            "model": "GS300"
        },
        {
            "model": "GX 460"
        },
        {
            "model": "GX 470"
        },
        {
            "model": "GX 550"
        },
        {
            "model": "HS 250h"
        },
        {
            "model": "IS 200t"
        },
        {
            "model": "IS 250"
        },
        {
            "model": "IS 250 AWD"
        },
        {
            "model": "IS 250 C"
        },
        {
            "model": "IS 250/IS 250C"
        },
        {
            "model": "IS 300"
        },
        {
            "model": "IS 300 AWD"
        },
        {
            "model": "IS 350"
        },
        {
            "model": "IS 350 AWD"
        },
        {
            "model": "IS 350 C"
        },
        {
            "model": "IS 350/IS 350C"
        },
        {
            "model": "IS 500"
        },
        {
            "model": "IS F"
        },
        {
            "model": "LC 500"
        },
        {
            "model": "LC 500 Convertible"
        },
        {
            "model": "LC 500h"
        },
        {
            "model": "LFA"
        },
        {
            "model": "LS 400"
        },
        {
            "model": "LS 430"
        },
        {
            "model": "LS 460"
        },
        {
            "model": "LS 460 AWD"
        },
        {
            "model": "LS 460 L"
        },
        {
            "model": "LS 460 L AWD"
        },
        {
            "model": "LS 500"
        },
        {
            "model": "LS 500 AWD"
        },
        {
            "model": "LS 500h"
        },
        {
            "model": "LS 500h AWD"
        },
        {
            "model": "LS 600h L"
        },
        {
            "model": "LX 450"
        },
        {
            "model": "LX 470"
        },
        {
            "model": "LX 570"
        },
        {
            "model": "LX 600"
        },
        {
            "model": "NX 200t"
        },
        {
            "model": "NX 200t AWD"
        },
        {
            "model": "NX 200t AWD F Sport"
        },
        {
            "model": "NX 250"
        },
        {
            "model": "NX 250 AWD"
        },
        {
            "model": "NX 300"
        },
        {
            "model": "NX 300 AWD"
        },
        {
            "model": "NX 300 AWD F Sport"
        },
        {
            "model": "NX 300h"
        },
        {
            "model": "NX 300h AWD"
        },
        {
            "model": "NX 350 AWD"
        },
        {
            "model": "NX 350 AWD F Sport"
        },
        {
            "model": "NX 350h AWD"
        },
        {
            "model": "NX 450h Plus AWD"
        },
        {
            "model": "RC 200t"
        },
        {
            "model": "RC 300"
        },
        {
            "model": "RC 300 AWD"
        },
        {
            "model": "RC 350"
        },
        {
            "model": "RC 350 AWD"
        },
        {
            "model": "RC F"
        },
        {
            "model": "RX 300"
        },
        {
            "model": "RX 300 4WD"
        },
        {
            "model": "RX 330 2WD"
        },
        {
            "model": "RX 330 4WD"
        },
        {
            "model": "RX 350"
        },
        {
            "model": "RX 350 2WD"
        },
        {
            "model": "RX 350 4WD"
        },
        {
            "model": "RX 350 AWD"
        },
        {
            "model": "RX 350 L"
        },
        {
            "model": "RX 350 L AWD"
        },
        {
            "model": "RX 350h AWD"
        },
        {
            "model": "RX 400h 2WD"
        },
        {
            "model": "RX 400h 4WD"
        },
        {
            "model": "RX 450h"
        },
        {
            "model": "RX 450h AWD"
        },
        {
            "model": "RX 450h L AWD"
        },
        {
            "model": "RX 500h AWD"
        },
        {
            "model": "RZ 300e (18 inch wheels)"
        },
        {
            "model": "RZ 300e (20 inch wheels)"
        },
        {
            "model": "RZ 450e AWD (18 inch wheels)"
        },
        {
            "model": "RZ 450e AWD (20 inch Wheels)"
        },
        {
            "model": "SC"
        },
        {
            "model": "SC 300/SC 400"
        },
        {
            "model": "SC 300/SC 430"
        },
        {
            "model": "SC 430"
        },
        {
            "model": "TX 350"
        },
        {
            "model": "TX 350 AWD"
        },
        {
            "model": "TX 500h AWD"
        },
        {
            "model": "UX 200"
        },
        {
            "model": "UX 250h"
        },
        {
            "model": "UX 250h AWD"
        },
        {
            "model": "UX 300h"
        },
        {
            "model": "UX 300h AWD"
        }
    ],
    "success": true,
    "status": 200
}
Vehicle Models — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31409/vehicle+models&vehicle_make=Required' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{}'

    
Request
# Estimated Flight Times between Airports Returns the estimated travel time through flight between two airports. operationId: estimate_flight_time_between_airports
Endpoint ID: 31410
GET https://zylalabs.com/api/13723/carbon+emission+calculation+api/31410/estimated+flight+time+between+airports
INPUT PARAMETERS

Estimated Flight Time between Airports — Endpoint Features

Object Description
iata_airport_from Required The departing (or from) IATA airport code is unique 3 digit geocode (also known as IATA location identifier or IATA station code)
iata_airport_to Required The landing (or to) IATA airport code is unique 3 digit geocode (also known as IATA location identifier or IATA station code)
iata_airport_to Required The landing (or to) IATA airport code is unique 3 digit geocode (also known as IATA location identifier or IATA station code)

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

iata_airport_from
iata_airport_to
iata_airport_to
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "airport_from": "Los Angeles International Airport",
        "airport_to": "Singapore Changi Airport",
        "estimated_formatted": "17 hours 27 minutes",
        "hours": 17,
        "minutes": 27,
        "totalMinutes": 1047
    },
    "success": true,
    "status": 200
}
Estimated Flight Time between Airports — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/13723/carbon+emission+calculation+api/31410/estimated+flight+time+between+airports?iata_airport_from=LAX&iata_airport_to=SIN&iata_airport_to=SIN' --header 'Authorization: Bearer YOUR_API_KEY' 


    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Carbon Emission Calculation API simply include your bearer token in the Authorization header.

Headers
Header Description
Authorization Required Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

No long-term commitment. Upgrade, downgrade, or cancel anytime. Free Trial includes up to 50 requests.

(Save 2 months with annual billing 🎉)

🚀 Enterprise Plan

Starts at
$ 10,000/Year


  • Custom Volume
  • Custom Rate Limit
  • Specialized Customer Support
  • Real-Time API Monitoring

Overview

Carbon footprint estimation for business travel, global hotel stays, vehicles usage, freight, eCommerce, shipments, fuel and electricity with supplementary APIs on airports and clustering results.

Carbon Emission Calculation API FAQs

Each endpoint returns estimated greenhouse gas emissions (CO2e) in multiple units (grams, kilograms, metric tons, pounds) based on specific parameters like flight details, hotel stays, vehicle types, and electricity usage. For example, the Flight Travel Estimates endpoint provides emissions based on airport codes, flight class, and passenger count.

Key fields in the response data include "co2e_gm," "co2e_kg," "co2e_mt," and "co2e_lb," which represent emissions in different units. Other fields may include details like "airport_from," "airport_to," "hotel_rating," and "vehicle_type," depending on the endpoint used.

Parameters vary by endpoint but generally include inputs like "airport codes," "flight class," "number of passengers," "country name," "fuel type," and "distance value." For instance, the Hotel Stay Estimates endpoint requires "country," "number of nights," and "hotel rating."

The response data is structured in a JSON format, with a "data" object containing specific attributes related to the emission estimate. Each estimate type has its own structure, detailing the parameters used and the calculated emissions, making it easy to parse and utilize.

Data sources include government publications and standards such as the UK Government's GHG conversion factors, Cornell Hotel Sustainability Benchmark Index, and various environmental agencies. This ensures that the emissions calculations are based on reliable and up-to-date information.

Typical use cases include corporate sustainability reporting, compliance with environmental regulations, and analysis of carbon footprints for travel, accommodation, and logistics. Organizations can use this data to identify areas for emissions reduction and improve their sustainability strategies.

Users can customize requests by specifying parameters relevant to their needs, such as selecting different vehicle makes/models, adjusting flight classes, or choosing specific countries for hotel stays. This flexibility allows for tailored emissions calculations based on unique organizational activities.

Users can utilize the returned data for reporting and analysis by integrating it into sustainability dashboards, compliance reports, or decision-making tools. The structured format allows for easy extraction of key metrics, enabling organizations to track and manage their carbon emissions effectively.

General FAQs

To obtain your API key, first sign in to your account and navigate to the API you want to use. From the API's Pricing section, choose a plan and complete the subscription process. Once subscribed, return to the API page and you will see your API Access Key displayed at the top of the documentation page. You can use this key to authenticate your requests.

You can’t switch APIs during the free trial. If you subscribe to a different API, your trial will end and the new subscription will start as a paid plan.

The free trial lasts for 7 days and allows you to make up to 50 API requests.

No, the free trial is available only once, so we recommend using it on the API that interests you the most. Most of our APIs offer a free trial, but some may not include this option.

Yes. If the API offers a free trial, you will see a "Free 7-Day Trial" option in its Pricing section. The trial lasts for 7 days and allows up to 50 API requests, enabling you to evaluate the API before subscribing to a paid plan.

Zyla API Hub is like a big store for APIs, where you can find thousands of them all in one place. We also offer dedicated support and real-time monitoring of all APIs. Once you sign up, you can pick and choose which APIs you want to use. Just remember, each API needs its own subscription. But if you subscribe to multiple ones, you'll use the same key for all of them, making things easier for you.

Prices are listed in USD (United States Dollar), EUR (Euro), CAD (Canadian Dollar), AUD (Australian Dollar), and GBP (British Pound). We accept all major debit and credit cards. Our payment system uses the latest security technology and is powered by Stripe, one of the world's most reliable payment companies. If you have any trouble paying by card, just contact us at [email protected]

Additionally, if you already have an active subscription in any of these currencies (USD, EUR, CAD, AUD, GBP), that currency will remain for subsequent subscriptions. You can change the currency at any time as long as you don't have any active subscriptions.
The local currency shown on the pricing page is based on the country of your IP address and is provided for reference only. The actual prices are in USD (United States Dollar). When you make a payment, the charge will appear on your card statement in USD, even if you see the equivalent amount in your local currency on our website. This means you cannot pay directly with your local currency.
Occasionally, a bank may decline the charge due to its fraud protection settings. We suggest reaching out to your bank initially to check if they are blocking our charges. Also, you can access the Billing Portal and change the card associated to make the payment. If these does not work and you need further assistance, please contact our team at [email protected]
Prices are determined by a recurring monthly or yearly subscription, depending on the chosen plan.
API calls are deducted from your plan based on successful requests. Each plan comes with a specific number of calls that you can make per month. Only successful calls, indicated by a Status 200 response, will be counted against your total. This ensures that failed or incomplete requests do not impact your monthly quota.
Zyla API Hub works on a recurring monthly subscription system. Your billing cycle will start the day you purchase one of the paid plans, and it will renew the same day of the next month. So be aware to cancel your subscription beforehand if you want to avoid future charges.
To upgrade your current subscription plan, simply go to the pricing page of the API and select the plan you want to upgrade to. The upgrade will be instant, allowing you to immediately enjoy the features of the new plan. Please note that any remaining calls from your previous plan will not be carried over to the new plan, so be aware of this when upgrading. You will be charged the full amount of the new plan.
To check how many API calls you have left for the current month, refer to the 'X-Zyla-API-Calls-Monthly-Remaining' field in the response header. For example, if your plan allows 1,000 requests per month and you've used 100, this field in the response header will indicate 900 remaining calls.

You can monitor your API usage through the response headers included with every request:

x-zyla-api-calls-monthly-used: Shows the total number of API requests you have used during the current billing period.
x-zyla-api-calls-monthly-remaining: Shows the number of API requests you have remaining for the current billing period.

The 'X-Zyla-RateLimit-Reset' header shows the number of seconds until your rate limit resets. This tells you when your request count will start fresh. For example, if it displays 3,600, it means 3,600 seconds are left until the limit resets.

Yes, you can cancel your subscription at any time. Simply go to the Pricing section of the API you're subscribed to and click the "Unsubscribe" button.

Please note that upgrades, downgrades, and cancellations take effect immediately. Once your subscription is canceled, access to the service will end immediately, regardless of any remaining API calls in your quota.

After 7 days, you will be charged the full amount for the plan you were subscribed to during the trial. Therefore, it's important to cancel before the trial period ends. Refund requests for forgetting to cancel on time are not accepted.
When you subscribe to an API free trial, you can make up to 50 API calls. If you wish to make additional API calls beyond this limit, the API will prompt you to perform an "Start Your Paid Plan." You can find the "Start Your Paid Plan" button in your profile under Subscription -> Choose the API you are subscribed to -> Pricing tab.
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Please have a look at our Refund Policy: https://zylalabs.com/terms#refund


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