# Search for Nigeria VKT / mileage / vehicle utilization data Search terms: vehicle kilometres travelled, vehicle kilometers traveled, vehicle-kilometre, vehicle-kilometer, vkt, annual mileage, annual km, km per vehicle, km/vehicle, average distance travelled per vehicle, average distance traveled per vehicle, vehicle utilisation, vehicle utilization, utilisation rate, utilization rate, vehicle km, vehicle-km, kilometres travelled, kilometers traveled, mileage ## C:\Users\HP\palmgrove\NEFDB\datasets\transport_aviation\road_vkt\TSDK_Nigeria.xlsx - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\datasets\transport_aviation\road_vkt\TSDK_Nigeria.pdf - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\datasets\transport_aviation\derived\fleet_registration_summary.csv - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\icct_soot_free_transport_nigeria.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\world_bank_lagos_air_quality_management.md - Contains VKT/mileage/utilization mentions: **Yes** - Term `vehicle-kilometer`: > | 19,69,756 | 20,29,669 | 8,65,683 | 4,32,540 | 30,22,125 | 2,45,42,923 | \\mathbf{c O}\_{2} \\mathbf{c H\_{4}} \\mathbf{c O}\_{2} \\mathbf{c O}\_{2}\\mathbf\\mathbf{e q} Note: a. Other than open burning. Includes emissions from dumpsites and wastewater. expressed in terms of outputs such as vehicle-kilometers traveled or inputs such as tons of fuel consumed or tons of trash burned. For many of the source types considered in this inventory, reliable data for estimating the output values were not available for Lagos State, so crude estimates or national-level statistics had to be applied. The missing dat - Term `vehicle-kilometer`: > -level statistics had to be applied. The missing data included information on amounts of trash and biomass burned, industrial production and energy consumption, and the numbers and utilization of small generators for electricity. Details of these estimates are expressed in terms of outputs such as vehicle-kilometers traveled or inputs such as tons of fuel consumed or tons of trash burned. For many of the source types considered in this inventory, reliable data for estimating the output values were not available for Lagos State, so crude estimates or national-level statistics had to be applied. The missing dat - Term `mileage`: > , and delivery trucks (Mufson and Kaplan 2021). * * * 4.1.3.4.1 Minibuses/danfos According to Lagos State Metropolitan Transport Agency (LAMATA), as recently as 2015, the small passenger vans known as danfos accounted for about 45 percent of all motorized passenger trips in Lagos. Given the high mileage of danfos—reportedly as much as 80,000 km per year—and the relatively old average age of the fleet (two-thirds may be over 17 years old), they would be logical targets for replacement. The government’s 2018 plan for reducing short-lived GHGs (Government of Nigeria 2018) calls for phasing out the da ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\lagos_transport_statistics_2020.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\road_vkt\LAMATA_WB_ICR.md - Contains VKT/mileage/utilization mentions: **Yes** - Term `vehicle-kilometer`: > /impact indicators identified in PAD were (Please see Table 1 for outcome and output indicators): ## Key outcome/impact indicators (i) Reduction of time and money (as a portion of the overall income) spent by poor households for personal travel activities; (ii) Reduction of accidents (relative to vehicle-kilometers driven), and particularly of those involving pedestrians; and (iii)Number of person-days of labor created (by the road rehabilitation and maintenance program). **1.3 Revised PDO (as approved by original approving authority) and Key Indicators, and** **reasons/justification** The Project was restru - Term `VKT`: > 3\. \| General traffic \| - Reduced congestion in corridor, allowing time and cost savings - Reduced accident rate \| \| 4\. \| Population along corridor \| - Improved quality of life - Improved public transport access opportunities - Reduced pollution, as a result of reduced congestion and lower VKT \| \| 5\. \| Bus transport operators/associations \| - Improved access to finance - \| \| 6\. \| Bus drivers/owners \| - Better work environment - Better organized - Improved revenue \| * * * | 7. | Vendors and commerce along corridors | - | | --- | --- | --- | | 8. | Bus suppliers | - | | 9. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\road_vkt\TSDK_Nigeria.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\road_vkt\Lagos_Transport_Statistics_2020.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\alternatives_log.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\download_log.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\epa_ghg_emission_factors_hub_2024.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\fleet_efficiency\FRSC_Stats_Digest_Q1_2024.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\fleet_efficiency\FRSC_Stats_Digest_Q2_2023.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\fleet_efficiency\FRSC_Stats_Digest_Q4_2022.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\fleet_efficiency\NADDC_NAIDP_2023.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\frsc_annual_report_2020.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\frsc_annual_report_2021.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\frsc_annual_report_2022.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\frsc_annual_report_2023.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\ghg_protocol_scope3_calculation_guidance.md - Contains VKT/mileage/utilization mentions: **Yes** - Term `mileage`: > measure representing one tonne of goods transported over 1 kilometer. TEU-kilometer is a unit of measure representing one twenty-foot container equivalent of goods transported over 1 kilometer. The distance-based method is especially useful for an organization that does not have access to fuel or mileage records from the transport vehicles, or has shipments smaller than those that would consume an entire vehicle or vessel. If sub-contractor fuel data cannot be easily obtained in order to use the fuel-based method, then the distance-based method should be used. Distance can be tracked using interna - Term `vehicle-kilometer`: > l (as shown in the distance-based method below) to the fuel-based method in category 4 (Upstream transport and distribution). Distance-based method If data on fuel use is unavailable, companies may use the distance-based method. The distance-based method involves multiplying activity data (i.e., vehicle-kilometers or person-kilometers travelled by vehicle type) by emission factors (typically default national emission factors by vehicle type). Vehicle types include all categories of aircraft, rail, subway, bus, automobile, etc. Companies should collect data on: •• Total distance travelled by each mode of t - Term `vehicle-km`: > nnual distance travelled by each mode of transport (aggregated across all employees), apply the formula below to calculate emissions. ## Calculation formula \[6.1\] Distance-based method ## CO2e emissions from business travel = ## sum across vehicle types: ∑ (distance travelled by vehicle type (vehicle-km or passenger-km) × vehicle specific emission factor (kg CO2e/vehicle-km or kg CO2e/passenger-km)) + **(optional)** ∑ (annual number of hotel nights (nights) × hotel emission factor (kg CO2e/night)) _Technical Guidance for Calculating Scope 3 Emissions_ \[84\] * * * Example \[6.1\] Calculating em - Term `vehicle-km`: > l employees), apply the formula below to calculate emissions. ## Calculation formula \[6.1\] Distance-based method ## CO2e emissions from business travel = ## sum across vehicle types: ∑ (distance travelled by vehicle type (vehicle-km or passenger-km) × vehicle specific emission factor (kg CO2e/vehicle-km or kg CO2e/passenger-km)) + **(optional)** ∑ (annual number of hotel nights (nights) × hotel emission factor (kg CO2e/night)) _Technical Guidance for Calculating Scope 3 Emissions_ \[84\] * * * Example \[6.1\] Calculating emissions from business travel using the distance-based method Company A - Term `vehicle-km`: > each member of the group travelled the same amount in the same business trip. | Road Travel | | | | | | | | --- | --- | --- | --- | --- | --- | --- | | Employee Group | Number of employees in group | Car type | Average employees per vehicle | Location | Distance(km) | Emission factor(kg CO2e/vehicle-km) | | Group 1 | 10 | Hybrid | 2 | United States | 50 | 1 | | Group 2 | 20 | Average gasoline car | 2 | Australia | 200 | 2 | | Group 3 | 100 | Four wheel drive | 3 | United States | 100 | 4 | | Air Travel | | | | | | --- | --- | --- | --- | --- | | Employee Group | Number of employees in group - Term `vehicle-km`: > haul – flights 3-6 hours in length \*\*••\*\*Long haul – journeys made by wide-bodied aircrafts that fly long distance, typically more than 6.5 hours. ## total business travel emissions of Company A can be calculated as follows: emissions from road travel = ∑ (distance travelled by vehicle type (vehicle-km or passenger-km) × vehicle specific emission factor (kg CO2e/vehicle-km or kg CO2e/passenger-km)) = (10/2 × 50 × 1) + (20/2 × 200 × 2) + (100/3 × 100 × 4) = 17,583.33 kg CO2e emissions from air travel = ∑ (distance travelled by vehicle type (vehicle-km or passenger-km) × vehicle specific emission - Term `vehicle-km`: > by wide-bodied aircrafts that fly long distance, typically more than 6.5 hours. ## total business travel emissions of Company A can be calculated as follows: emissions from road travel = ∑ (distance travelled by vehicle type (vehicle-km or passenger-km) × vehicle specific emission factor (kg CO2e/vehicle-km or kg CO2e/passenger-km)) = (10/2 × 50 × 1) + (20/2 × 200 × 2) + (100/3 × 100 × 4) = 17,583.33 kg CO2e emissions from air travel = ∑ (distance travelled by vehicle type (vehicle-km or passenger-km) × vehicle specific emission factor (kg CO2e/vehicle-km or kg CO2e/passenger-km)) = (10 × 10,000 × 5) - Term `vehicle-km`: > avel = ∑ (distance travelled by vehicle type (vehicle-km or passenger-km) × vehicle specific emission factor (kg CO2e/vehicle-km or kg CO2e/passenger-km)) = (10/2 × 50 × 1) + (20/2 × 200 × 2) + (100/3 × 100 × 4) = 17,583.33 kg CO2e emissions from air travel = ∑ (distance travelled by vehicle type (vehicle-km or passenger-km) × vehicle specific emission factor (kg CO2e/vehicle-km or kg CO2e/passenger-km)) = (10 × 10,000 × 5) + (20 × 15,000 × 6) + (100 × 12,000 × 5) = 8,300,000 kg CO2e total emissions from employee travel = emissions from road travel + emissions from air travel = 17,583.33 + 8,300,000 = - Term `vehicle-km`: > ) × vehicle specific emission factor (kg CO2e/vehicle-km or kg CO2e/passenger-km)) = (10/2 × 50 × 1) + (20/2 × 200 × 2) + (100/3 × 100 × 4) = 17,583.33 kg CO2e emissions from air travel = ∑ (distance travelled by vehicle type (vehicle-km or passenger-km) × vehicle specific emission factor (kg CO2e/vehicle-km or kg CO2e/passenger-km)) = (10 × 10,000 × 5) + (20 × 15,000 × 6) + (100 × 12,000 × 5) = 8,300,000 kg CO2e total emissions from employee travel = emissions from road travel + emissions from air travel = 17,583.33 + 8,300,000 = 8,317,583.33 kg CO2e ## Spend-based method If it is not possible to u - Term `vehicle-km`: > the total commuting of all employees. See Appendix A for more information on sampling. CO2e emissions from employee travel = then, sum across vehicle types to determine total emissions: kg CO2e from employee commuting kg CO2e from employee commuting = ∑ (total distance travelled by vehicle type (vehicle-km or passenger-km) \\mathrm{C O\_{2}e} total distance travelled by vehicle type (vehicle-km or passenger-km) = ∑ (daily one-way distance between home and work (km) × 2 × number of commuting days per year) (optionally) for each energy source used in teleworking: ∑ (quantities of energy consumed (kW - Term `vehicle-km`: > emissions from employee travel = then, sum across vehicle types to determine total emissions: kg CO2e from employee commuting kg CO2e from employee commuting = ∑ (total distance travelled by vehicle type (vehicle-km or passenger-km) \\mathrm{C O\_{2}e} total distance travelled by vehicle type (vehicle-km or passenger-km) = ∑ (daily one-way distance between home and work (km) × 2 × number of commuting days per year) (optionally) for each energy source used in teleworking: ∑ (quantities of energy consumed (kWh) × emission factor for energy source (kg CO2 ∑ (quantities of energy consumed (kWh) × emi - Term `vehicle-kilometer`: > each employee. Each employee completes a questionnaire the results of which are summarized in the following table: | Employee | Rail commute(times per week) | One way distance by rail(km) | Rail emission factor(kgCO2e/passenger-kilometer) | Car commute(times per week) | Car emission factor(kgCO2e/vehicle-kilometer) | One way distance by car(km) | | --- | --- | --- | --- | --- | --- | --- | | A | 5 | 10 | 0.1 | 0 | 0.2 | N/A | | B | 4 | 10 | 0.1 | 1 | 0.2 | 15 | | C | 0 | N/A | 0.1 | 5 | 0.2 | 20 | Note: The activity data and emissions factors are illustrative only, and do not refer to actual data. total em - Term `vehicle-km`: > | 4 | 10 | 0.1 | 1 | 0.2 | 15 | | C | 0 | N/A | 0.1 | 5 | 0.2 | 20 | Note: The activity data and emissions factors are illustrative only, and do not refer to actual data. total emissions from employee commuting for the reporting year is calculated as: ∑ (total distance travelled by vehicle type (vehicle-km or passenger-km) ∑ (daily one way distance between home and work (km) × 2 × 5 × number of commuting weeks per year) = (15 × 2 × 1 × 48) + (20 × 2 × 5 × 48) = 11,040 km =(10\\times2\\times5\\times48)+(10\\times2\\times4\\times48)=8,640\ mathsf k r r * * * Average-data method If company specific - Term `vehicle-km`: > /](http://www2.dft.gov.uk/pgr/sustainable/greenhousegasemissions/). * * * Calculation formula \[7.2\] Average-data method CO2e emissions from employee commuting = sum across each transport mode: ∑ (total number of employees × % of employees using mode of transport × one way commuting distance (vehicle-km or passenger-km) × 2 × working days per year × emission factor of transport mode (kg CO2e/vehicle-km or kg CO2e/passenger-km)) Companies should convert average daily commuting distance into annual average commuting distance by multiplying the one-way distance by two for the daily return trip and b - Term `vehicle-km`: > \] Average-data method CO2e emissions from employee commuting = sum across each transport mode: ∑ (total number of employees × % of employees using mode of transport × one way commuting distance (vehicle-km or passenger-km) × 2 × working days per year × emission factor of transport mode (kg CO2e/vehicle-km or kg CO2e/passenger-km)) Companies should convert average daily commuting distance into annual average commuting distance by multiplying the one-way distance by two for the daily return trip and by the average number of days worked per year (i.e., excluding weekends and days spent on business tra - Term `vehicle-km`: > \[7.2\] Calculating emissions from employee travel using the average data method (continued) ## CO2e emissions by mode of transport can be calculated as follows: emissions from employee commuting = ∑ (total number of employees × % of employees using mode of transport × one way commuting distance (vehicle-km or passenger-km) × 2 × working days per year × emission factor of transport mode (kg CO2e/vehicle-km or kg CO2e/passenger-km)) ## rail commuters: (10,000 × 50% × 10 × 2 × 235 × 0.1) = 2,350,000 kg CO2e **car commuters:** (10,000 × 30% × 15 × 2 × 235 × 0.2) = 4,230,000 kg CO2e **foot commuters:** - Term `vehicle-km`: > emissions by mode of transport can be calculated as follows: emissions from employee commuting = ∑ (total number of employees × % of employees using mode of transport × one way commuting distance (vehicle-km or passenger-km) × 2 × working days per year × emission factor of transport mode (kg CO2e/vehicle-km or kg CO2e/passenger-km)) ## rail commuters: (10,000 × 50% × 10 × 2 × 235 × 0.1) = 2,350,000 kg CO2e **car commuters:** (10,000 × 30% × 15 × 2 × 235 × 0.2) = 4,230,000 kg CO2e **foot commuters:** (10,000 × 15% × 1 × 2 × 235 × 0) = 0 kg CO2e **bus commuters:** (10,000 × 5% × 5 × 2 × 235 × 0.1) = 1 - Term `mileage`: > sions from leased assets Downstream leased assets differ from upstream leased assets in that the leased assets are owned by the reporting company. The availability and access to information depends on the type of asset leased. For example, a company that leases vehicles may need to request fuel or mileage data from lessees in order to calculate emissions. The calculation methods for upstream and downstream leased assets do not differ. For guidance on calculating emissions from category 13 (Downstream leased assets), refer to the guidance for category 8 (Upstream leased assets). Companies requestin - Term `vehicle-km`: > s per unit of electricity consumed(e.g.,kgCO2e/kWh) | | | | | Fugitive emission factors, expressed in units of emissions per unit of fugitive emission(e.g.,kgCO2e/kg refrigerant leakage) | | | | | Distance-based method | sum across vehicle types: | | | | Σ(distance travelled by vehicle type(vehicle-km or passenger-km) | | | | | × vehicle specific emission factor(kgCO2e/vehicle-km or kgCO2e/passenger-km)) | | | | | (optional) | | | | | Σ(annual number of hotel nights(nights)×hotel emission factor(kgCO2e/night)) | Total distance travelled by each mode of transport(air,train,bus,car,etc.)f - Term `vehicle-km`: > factors, expressed in units of emissions per unit of fugitive emission(e.g.,kgCO2e/kg refrigerant leakage) | | | | | Distance-based method | sum across vehicle types: | | | | Σ(distance travelled by vehicle type(vehicle-km or passenger-km) | | | | | × vehicle specific emission factor(kgCO2e/vehicle-km or kgCO2e/passenger-km)) | | | | | (optional) | | | | | Σ(annual number of hotel nights(nights)×hotel emission factor(kgCO2e/night)) | Total distance travelled by each mode of transport(air,train,bus,car,etc.)for all employees in the reporting year. | | | | Countries of travel(since transpo - ... and 5 additional matches omitted. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\glec_framework_v3_dec2024.md - Contains VKT/mileage/utilization mentions: **Yes** - Term `vehicle km`: > ns | tonne |\ | Wagon | tonne |\ | Wagons capacity | tonne |\ | Max gross weight | tonne |\ | Cargo capacity | tonne |\ | Gross weight empty | tonne |\ | Load factor | % |\ | Cargo weight | tonne |\ | Gross weight | tonne |\ | Electric distribution losses | % |\ | Measured electric consumptions per vehicle km vkm, including distribution losses | kWh/vkm |\ | CO2wtw European average | g/kWh |\ | Electric consumption per net-t km, including distribution losses | kWh/tkm |\ | GHG(CO2per vehicle km) | g/vkm |\ | Distance | km |\ | GHG emissions wtw | kg |\ | Transport activity | |\ | GHG(CO2ewtw per tkm) | - Term `vehicle km`: > tonne |\ | Gross weight | tonne |\ | Electric distribution losses | % |\ | Measured electric consumptions per vehicle km vkm, including distribution losses | kWh/vkm |\ | CO2wtw European average | g/kWh |\ | Electric consumption per net-t km, including distribution losses | kWh/tkm |\ | GHG(CO2per vehicle km) | g/vkm |\ | Distance | km |\ | GHG emissions wtw | kg |\ | Transport activity | |\ | GHG(CO2ewtw per tkm) | g/tkm |\ \ | | South | North | Roundtrip average |\ | --- | --- | --- | --- |\ | | 630 | 630 | 630 |\ | | 1 | 1 | 1 |\ | | 78 | 78 | 78 |\ | | 22 | 22 | 22 |\ | | 30 | 30 | 30 |\ | ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\icao_icec_methodology_v13_1.md - Contains VKT/mileage/utilization mentions: **Yes** - Term `VKT`: > WGA | WGA | | VHV | VHV | WGP | WGP | | VHZ | VHZ | WHK | WHK | | VIE | VIE | WIC | WIC | | VIG | VIG | WIL | NBO | | VII | VII | WIN | WIN | | VIL | VIL | WJR | WJR | | VIR | VIR | WJU | WJU | | VIS | VIS | WKJ | WKJ | | VIX | VIX | WLE | WLE | | VKG | VKG | WLG | WLG | | VKO | MOW | WLH | WLH | | VKT | VKT | WLK | WLK | | VLC | VLC | WLP | WLP | | VLD | VLD | WLS | WLS | | VLG | VLG | WMI | WMI | | VLI | VLI | WMN | WMN | | VLL | VLL | WMO | WMO | | VLN | VLN | WMR | WMR | | VLY | VLY | WMX | WMX | | VNO | VNO | WNH | WNH | | VNS | VNS | WNN | WNN | | VNX | VNX | WNP | WNP | | VOG | VOG | WNZ | - Term `VKT`: > WGA | | VHV | VHV | WGP | WGP | | VHZ | VHZ | WHK | WHK | | VIE | VIE | WIC | WIC | | VIG | VIG | WIL | NBO | | VII | VII | WIN | WIN | | VIL | VIL | WJR | WJR | | VIR | VIR | WJU | WJU | | VIS | VIS | WKJ | WKJ | | VIX | VIX | WLE | WLE | | VKG | VKG | WLG | WLG | | VKO | MOW | WLH | WLH | | VKT | VKT | WLK | WLK | | VLC | VLC | WLP | WLP | | VLD | VLD | WLS | WLS | | VLG | VLG | WMI | WMI | | VLI | VLI | WMN | WMN | | VLL | VLL | WMO | WMO | | VLN | VLN | WMR | WMR | | VLY | VLY | WMX | WMX | | VNO | VNO | WNH | WNH | | VNS | VNS | WNN | WNN | | VNX | VNX | WNP | WNP | | VOG | VOG | WNZ | WNZ | ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\ipcc_2006_vol2_ch3_mobile_combustion.md - Contains VKT/mileage/utilization mentions: **Yes** - Term `vehicle kilometres travelled`: > ld choose the method on the basis of the existence and quality of data. The tiers are defined in the corresponding equations 3.2.3 to 3.2.5, below. $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ Three alternative approaches can be used to estimate CH4 and N2O emissions from road vehicles: one is based on vehicle kilometres travelled (VKT) and two are based on fuel sold. The Tier 3 approach requires detailed, country-specific data to generate activity-based emission factors for vehicle subcategories and may involve national models. Tier 3 calculates emissions by multiplying emission factors by vehicle activity levels (e.g., VKT - Term `VKT`: > sis of the existence and quality of data. The tiers are defined in the corresponding equations 3.2.3 to 3.2.5, below. $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ Three alternative approaches can be used to estimate CH4 and N2O emissions from road vehicles: one is based on vehicle kilometres travelled (VKT) and two are based on fuel sold. The Tier 3 approach requires detailed, country-specific data to generate activity-based emission factors for vehicle subcategories and may involve national models. Tier 3 calculates emissions by multiplying emission factors by vehicle activity levels (e.g., VKT) for - Term `VKT`: > led (VKT) and two are based on fuel sold. The Tier 3 approach requires detailed, country-specific data to generate activity-based emission factors for vehicle subcategories and may involve national models. Tier 3 calculates emissions by multiplying emission factors by vehicle activity levels (e.g., VKT) for each vehicle subcategory and possible road type. Vehicle subcategories are based on vehicle type, age, and emissions control technology. The Tier 2 approach uses fuel-based emission factors specific to vehicle subcategories. Tier 1, which uses fuel-based emission factors, may be used if it is - Term `VKT`: > {a, b, c, d} $$ Emission = emission or CH4 or N2O (kg) $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} (\\mathrm {k g}) $$ EFa,b,c,d = emission factor (kg/km) $$ \\mathrm {E F} \_ {\\mathrm {a}, \\mathrm {b}, \\mathrm {c}, \\mathrm {d}} $$ Distancea,b,c,d = distance travelled (VKT) during thermally stabilized engine operation phase for a given mobile source activity (km) $$ \\mathrm {D i s t a n c e} \_ {\\mathrm {a}, \\mathrm {b}, \\mathrm {c}, \\mathrm {d}} $$ Ca,b,c,d = emissions during warm-up phase (cold start) (kg) $$ \\mathrm {C} \_ {\\mathrm {a}, \\mathrm {b}, \\m - Term `VKT`: > emission models such as the USEPA MOVES or MOBILE models, or the EEA’s COPERT model will be used (USEPA 2005a, USEPA 2005b, EEA 2005, respectively). These include detailed fleet models that enable a range of vehicle types and control technologies to be considered as well as fleet models to estimate VKT driven by these vehicle types. Emission models can help to ensure consistency and transparency because the calculation procedures may be fixed in software packages that may be used. It is good practice to clearly document any modifications to standardised models. It may not be possible to split by - Term `VKT`: > emission models such as the USEPA MOVES or MOBILE models, or the EEA’s COPERT model will be used (USEPA 2005a, USEPA 2005b, EEA 2005, respectively). These include detailed fleet models that enable a range of vehicle types and control technologies to be considered as well as fleet models to estimate VKT driven by these vehicle types. Emission models can help to ensure consistency and transparency because the calculation procedures may be fixed in software packages that may be used. It is good practice to clearly document any modifications to Additional emissions occur when the engines are cold, a - Term `VKT`: > nd 3.2.5 for Tier 2 and 3 methods involves the following steps: • Step 1: Obtain or estimate the amount of fuel consumed by fuel type for road transportation using national data (all values should be reported in terajoules; please also refer to Section 3.2.1.3.) • Step 2: Ensure that fuel data or VKT is split into the vehicle and fuel categories required. It should be taken into consideration that, typically, emissions and distance travelled each year vary according to the age of the vehicle; the older vehicles tend to travel less but may emit more CH4 per unit of activity. Some vehicles may ha - Term `mileage`: > onverters (e.g., typical catalysts convert nitrogen oxides to N₂ and CH₄ into CO₂). Dia¹ et al (2001) reports catalyst conversion efficiency needed for total hydrocarbons (THCs) of which CH₄ is correlated with 92% (-6%) in a 1933-1995 test. Considerable deformation of catalysts with relatively high mileage accumulation; specifically, THC levels remained steady until approximately 60 000 kilometers, then increased by 33 percent to between 60 000 to 100 000 kilometres. • The impact of operating conditions (e.g., speed, road conditions, and driving patterns, which all affect fuel economy and vehicle sy - Term `annual mileage`: > s associated with existing studies¹. The following section provides a method for developing CH₄ emission factors from THC values. Well conducted and documented inspection and maintenance (I/M) programmes may provide a source of national data for emission factors by fuel, model, and year as well as annual mileage accumulation rates. Although some I/M programmes may only have available emission factors for new vehicles and local air pollutants (sometimes called regulated pollutants, e.g., NO₃, PM, AMVOCs, THC₅), it may be possible to derive CH₄ or NO₃ emission factors from these data. A CH₄ emission factor m - Term `mileage`: > g without a functioning catalytic converter. Consequently, N₂O emissions may be low and CH₄ may be high when catalytic converters are not present or operating improperly. Diaz et al (2001) provides information on THC values for Mexico City and catalytic converter efficiency as a function of age and mileage, and this also chapter provides guidance on developing CH₄ factors from THC data. • Engine loading - Due to traffic density or challenging topography, the number of accelerations and decelerations that a local vehicle encounters may be significantly greater than that for corresponding travel in co - Term `Mileage`: > PORT N₂O and CH₄ DEFAULT EMISSION FACTORS AND UNCERTAINTY RANGES⁽ᵃ⁾ Fuel Type/Representative Vehicle Category CH₄ (kg/TL) Default Lower Upper Default Lower Upper Motor Gasoline -Uncontrolled⁽ᶜ⁾ 33 9.6 110 3.2 0.96 11 Motor Gasoline -Oxidation Catalyst⁽ᶜ⁾ 25 7.5 86 8.0 2.6 24 Motor Gasoline -Low Mileage Light Duty Vehicle Vintage 1995 or Later⁽ᶜ⁾ 2.5 1.1 16 5.7 1.9 17 Gas / Diesel Oil⁽ᶜ⁾ 3.9 1.6 9.5 3.9 1.3 12 Natural Gas⁽ᶜ⁾ 92 50 1 540 3 1 77 Liquified petroleum gas⁽ᶜ⁾ 62 na na 0.2 na 13 123 Ethanol, trucks, US⁽ᶜ⁾ 260 77 880 41 13 123 Ethanol, cars, Brazil⁽ᶜ⁾ 18 13 84 na na na Sources: USEP - Term `annual mileage`: > iachristos, L., and Samaras, Z., (2005), LAT (2005) and TNO (2002). 2 The urban emission factor is distinguished into cold and hot for passenger cars and light duty trucks. The cold emission factor is relevant for trips which start with the engine at ambient temperature. A typical allocation of the annual mileage of a passenger car into different driving conditions could be 0:30, 10:30, 10:40 for urban cold, urban hot, road and highway respectively. 3 Passenger car emission factors are also proposed for light duty vehicles when no more detailed information exists. 4 The sulphur content of gasoline has both - Term `mileage`: > e detailed information exists. 4 The sulphur content of gasoline has both a cumulative and an immediate effect on N₂O emissions. The emission factors for gasoline passenger cars correspond to fuels at the period of registration of the different technologies and a vehicle fleet of >50,000 km average mileage. 5 N₂O and CH₄ emission factors from heavy duty vehicles and power two wheels are also expected to depend on vehicle technology. There is no adequate experimental information though to quantify this effect. 6 N₂O emission factors from diesel and LPG passenger cars are proposed by TNO (2002). Increa - Term `vehicle kilometres travelled`: > e in diesel N₂O emissions as technology improves may be quite uncertain but is also consistent with the developments in the after treatment systems used in diesel engines (new analysis, SC4 DNO). * * * 3.2.1.3 CHOICE OF ACTIVITY DATA Activity data may be provided either by fuel consumption or by vehicle kilometres travelled VKT. Use of adequate VKT data can be used to check top-down inventories. FUEL CONSUMPTION Emissions from road vehicles should be attributed to the country where the fuel is sold; therefore fuel consumption data should reflect fuel that is sold within the country’s territories. Such energy data ar - Term `VKT`: > technology improves may be quite uncertain but is also consistent with the developments in the after treatment systems used in diesel engines (new analysis, SC4 DNO). * * * 3.2.1.3 CHOICE OF ACTIVITY DATA Activity data may be provided either by fuel consumption or by vehicle kilometres travelled VKT. Use of adequate VKT data can be used to check top-down inventories. FUEL CONSUMPTION Emissions from road vehicles should be attributed to the country where the fuel is sold; therefore fuel consumption data should reflect fuel that is sold within the country’s territories. Such energy data are ty - Term `VKT`: > ay be quite uncertain but is also consistent with the developments in the after treatment systems used in diesel engines (new analysis, SC4 DNO). * * * 3.2.1.3 CHOICE OF ACTIVITY DATA Activity data may be provided either by fuel consumption or by vehicle kilometres travelled VKT. Use of adequate VKT data can be used to check top-down inventories. FUEL CONSUMPTION Emissions from road vehicles should be attributed to the country where the fuel is sold; therefore fuel consumption data should reflect fuel that is sold within the country’s territories. Such energy data are typically available fro - Term `vehicle kilometres travelled`: > with the other appropriate sectors to ensure that any fuel removed from on-road statistics is added to the appropriate sector, or vice versa. Two alternative approaches are suggested to separate non-road and on-road fuel use: As validation, and if distance travelled data are available (see below vehicle kilometres travelled), it is good practice to estimate fuel use from the distance travelled data. The first step (Equation 3.2.6) is to estimate fuel consumed by vehicle type i and fuel type j. * * * \| EQUATION 3.2.6 VALIDATING FUEL CONSUMPTION | Estimated Fuel = $\\sum\_{i,j,t}$\[Vehicles $ \_{i,j,t} $ Distance $ - Term `VKT`: > t} $ \] | | | --- | --- | $$ \\text {E s t i m a t e d F u e l} = \\sum\_ {i, j, t} \\left\[ V e h i c l e s \_ {i, j, t} \\cdot D i s t a n c e \_ {i, j, t} \\cdot C o n s u m p t i o n \_ {i, j, t} \\right\] $$ Where: Estimated Fuel =total estimated fuel use estimated from distance travelled (VKT) data (l) $$ \\mathrm {V e h i c l e s} \_ {\\mathrm {i}, \\mathrm {j}, \\mathrm {t}} $$ $$ \\mathrm {D i s t a n c e} \_ {\\mathrm {i}, \\mathrm {j}, \\mathrm {t}} $$ $$ \\text{Consumption}\_{\\mathrm{i,j,t}} = \\text{average fuel consumption (l/km)} \\text{ by vehicles of type i and using fuel - Term `VEHICLE KILOMETRES TRAVELLED`: > ehicle travelled on major highways is believed to be reasonably well known and on the other hand rural traffic is poorly measured. In any case, the adjustments made for reasons of the choice of adjustment factor and background data as well as any other checks should be well documented and reviewed. VEHICLE KILOMETRES TRAVELLED (VKT) $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O}. $$ VEHICLE KILOMETRES TRAVELLED (VKT) While fuel data can be used at Tier 1 for CH4 and N2O, higher tiers also need vehicle kilometres travelled (VKT) by v - Term `VKT`: > ways is believed to be reasonably well known and on the other hand rural traffic is poorly measured. In any case, the adjustments made for reasons of the choice of adjustment factor and background data as well as any other checks should be well documented and reviewed. VEHICLE KILOMETRES TRAVELLED (VKT) $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O}. $$ VEHICLE KILOMETRES TRAVELLED (VKT) While fuel data can be used at Tier 1 for CH4 and N2O, higher tiers also need vehicle kilometres travelled (VKT) by vehicl - ... and 21 additional matches omitted. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\lee_et_al_2021_aviation_rf.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\nbs_road_transport_data_q4_2018.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\nesrea_vehicular_emission_regulations_2011.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\road_vkt\NBS_Road_Transport_Report_Q2_2024.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\road_vkt\NBS_Road_Transport_Report_Q3_2024.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\road_vkt\NBS_Road_Transport_Report_Q4_2023.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\road_vkt\WorldBank_Lagos_BRI_2pgs.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\route_data\BASL_MMA2_busiest_routes_2026.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\route_data\BusinessDay_lucrative_routes_plane_shortage_2024.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\route_data\TBI_domestic_aircraft_grounded_fleet_types_2024.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\route_data\THISDAY_2023_domestic_airline_passengers.md - Contains VKT/mileage/utilization mentions: **No** - No relevant VKT / mileage / utilization mentions found. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\uk_defra_2024_methodology.md - Contains VKT/mileage/utilization mentions: **Yes** - Term `vehicle kilometres travelled`: > _ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ * * * Table 29: Typical van freight capacities and estimated average payload.......................................82 Table 30: Utilisation of vehicle capacity by company-owned LGVs: annual average 2003 – 2005 (proportion of total vehicle kilometres travelled).............................................................82 Table 31: Related worksheets to sea transport emission factors...................................................85 Table 32: Assumptions used in the calculation of ferry emission factors........................................86 Table - Term `mileage`: > | | RW uplift(%) | 38.00 | 31.50 | 31.50 | 31.50 | 21.67 | 21.75 | 22.24 | 22.31 | | 5.17. The above uplifts have been applied to the ANPR weighted SMMT gCO2/km to give the ‘Real-World’ 2024 GHG Conversion factors. The average car conversion factors were calculated by weighting with the relative mileage of the different categories. This calculation utilised data from the UK GHG Inventory on the relative % total mileage by petrol and diesel cars. Overall, for petrol and diesel, this split in total annual mileage was 55.8% petrol and 44.2% diesel, and can be compared to the respective total registra - Term `mileage`: > een applied to the ANPR weighted SMMT gCO2/km to give the ‘Real-World’ 2024 GHG Conversion factors. The average car conversion factors were calculated by weighting with the relative mileage of the different categories. This calculation utilised data from the UK GHG Inventory on the relative % total mileage by petrol and diesel cars. Overall, for petrol and diesel, this split in total annual mileage was 55.8% petrol and 44.2% diesel, and can be compared to the respective total registrations of the different vehicle types for 2006-2023, which were 58.9% petrol and 41.1% diesel. 5.18. An adjustment fac - Term `annual mileage`: > ion factors. The average car conversion factors were calculated by weighting with the relative mileage of the different categories. This calculation utilised data from the UK GHG Inventory on the relative % total mileage by petrol and diesel cars. Overall, for petrol and diesel, this split in total annual mileage was 55.8% petrol and 44.2% diesel, and can be compared to the respective total registrations of the different vehicle types for 2006-2023, which were 58.9% petrol and 41.1% diesel. 5.18. An adjustment factor is applied to account for the biofuel content of transportation fuels. 5.19. Conversion f - Term `vehicle km`: > itions to average car use), plus an assumed average passenger occupancy of 1.4 (L.E.K. Consulting, 2002). 5.42. Conversion factors per passenger km for taxis and black cabs are presented in the 'Business travel-land' worksheet of the 2024 GHG Conversion factors set. The base conversion factors per vehicle km are also presented in the 'Business travel-land' worksheet of the 2024 GHG Conversion factors set. 5.43. Conversion factors for CH₄ and N₂O are based on the conversion factors for diesel cars from the UK GHGI 2019 (Ricardo Energy & Environment, 2021), updated to align with AR5 GWP values and are p - Term `vehicle km`: > in Table 21 and in the "Delivery vehicles" worksheet of the 2024 GHG Conversion factors set. 23 The data was provided by TfL in a personal communication and is not available in a public TfL source. * * * 5.46. Conversion factors for petrol and diesel vans/LGVs are based upon emission factors and vehicle km for average sized LGVs from the UK GHGI for 2022. The factors for each class are then calculated relative to the average from quantitative analysis of regulatory data across the years 2012-2022. For the years 2012-2020 CO2 emissions factors for different size classes were derived from analysis of t - Term `vehicle km`: > for the latest year. In the 2024 update, CO2 conversion factors for CNG and LPG vans are calculated from the conversion factors for conventionally fuelled vans using the same methodology as for passenger cars (section ). The average van conversion factor is calculated based on the relative UK GHGI vehicle km for petrol and diesel vans for 2022, as presented in Table 21. $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C O} \_ {2} $$ * * * 5.49. As a final additional step, an accounting for biofuel use has been included in the calculation of the final vans/LGVs emissi - Term `vehicle km`: > the UK fleet up to the end of 2022 5.54. All other methodological details are as already outlined for xEV passenger cars. Direct Emissions from Buses 5.55. The 2015 and earlier updates used data from DfT from the Bus Service Operators Grant (BSOG) in combination with DfT bus activity statistics (vehicle km, passenger km, average passenger occupancy) to estimate conversion factors for local buses. DfT holds very accurate data on the total amount of money provided to bus service operators under the scheme, which provides a fixed amount of financial support per unit of fuel consumed. Therefore, the tota - Term `vehicle km`: > al amount of money provided to bus service operators under the scheme, which provides a fixed amount of financial support per unit of fuel consumed. Therefore, the total amount of fuel consumed (and hence CO2 emissions) could be calculated from this, which when combined with DfT statistics on total vehicle km, bus occupancy and passenger km allow the calculation of emission factors25. * * * 5.56. From the 2016 update onwards, it was necessary to make some methodological changes to the calculations due to changes in the Scope/coverage of the underlying DfT datasets, which include: a) BSOG data are now - Term `vehicle km`: > of HGV and, if known, the extent of loading. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ each weight class of rigid and articulated HGVs, for all rigid and for all articulated, and aggregated for all HGVs. These are derived from the fleet average gCO2 per vehicle km factors in the “Delivery vehicles” worksheet. The average tonnes of freight lifted figures are derived from the tkm and vehicle km (vkm) figures given for each class of HGVs in Tables RFS0113 and RFS0110, respectively (DfT, 2023a). Dividing the tkm by the vkm figures gives the average tonnes of fre - Term `vehicle km`: > $ each weight class of rigid and articulated HGVs, for all rigid and for all articulated, and aggregated for all HGVs. These are derived from the fleet average gCO2 per vehicle km factors in the “Delivery vehicles” worksheet. The average tonnes of freight lifted figures are derived from the tkm and vehicle km (vkm) figures given for each class of HGVs in Tables RFS0113 and RFS0110, respectively (DfT, 2023a). Dividing the tkm by the vkm figures gives the average tonnes of freight lifted by each HGV class. The 2024 GHG Conversion factors include factors in tonne km (tkm) for all loads (0%, 50%, 100% and a - Term `vehicle-km`: > uses” section. $$ \\mathrm {N O} \_ {\\mathrm {x}} $$ $$ \\mathrm {C O} \_ {2} $$ Direct Emissions from Vans/Light Goods Vehicles (LGVs) 6.17. Conversion factors for light good vehicles (LGVs, vans up to 3.5 tonnes gross vehicle weight - GVW), were calculated based on the conversion factors per vehicle-km in the earlier section on “Direct Emissions from Vans/Light Goods Vehicles (LGVs)”. 6.18. The typical / average capacities and average payloads that are used in the calculation of van conversion factors per tonne km are presented in Table 29. The average payload capacity values are based on the qu - Term `vehicle-km`: > ns for diesel vans. $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ * * * 6.21. Conversion factors per tonne km are calculated from the average load factors for the different weight classes in combination with the average freight capacities of the different vans in Table 29 and the conversion factors per vehicle-km in the “Delivery vehicles” and “Freighting goods” worksheets of the 2024 GHG Conversion factors set. Direct Emissions from Rail Freight 6.22. Rail freight conversion factors remain constant since the publish of 2021 GHG Conversion factors, but have been updated from AR4 to AR5 GWP values. 6.23. ## C:\Users\HP\palmgrove\NEFDB\docs\transport_aviation\vkt_gap_verdict.md - Contains VKT/mileage/utilization mentions: **Yes** - Term `VKT`: > # Nigeria road VKT gap — verdict ## Direct vehicle-kilometres data found? **No.** None of the NEFDB sources — TSDK Nigeria, ICCT, World Bank Lagos Air Quality, NBS/FRSC vehicle reports, or Lagos transport statistics — publish **annual vehicle-kilometres travelled (VKT)** by road vehicle type for Nigeria. They cont - Term `vehicle-kilometre`: > # Nigeria road VKT gap — verdict ## Direct vehicle-kilometres data found? **No.** None of the NEFDB sources — TSDK Nigeria, ICCT, World Bank Lagos Air Quality, NBS/FRSC vehicle reports, or Lagos transport statistics — publish **annual vehicle-kilometres travelled (VKT)** by road vehicle type for Nigeria. They contain: | Source | What it has | What it lack - Term `vehicle-kilometre`: > # Nigeria road VKT gap — verdict ## Direct vehicle-kilometres data found? **No.** None of the NEFDB sources — TSDK Nigeria, ICCT, World Bank Lagos Air Quality, NBS/FRSC vehicle reports, or Lagos transport statistics — publish **annual vehicle-kilometres travelled (VKT)** by road vehicle type for Nigeria. They contain: | Source | What it has | What it lacks | |---|---|---| | TSDK Nigeria (Zenodo) | Vehicle stock, passenger-km, freight ton-km, load factors (sparse), energy intensity | VKT by vehicle type; consistent year/definition set | | ICCT so - Term `VKT`: > # Nigeria road VKT gap — verdict ## Direct vehicle-kilometres data found? **No.** None of the NEFDB sources — TSDK Nigeria, ICCT, World Bank Lagos Air Quality, NBS/FRSC vehicle reports, or Lagos transport statistics — publish **annual vehicle-kilometres travelled (VKT)** by road vehicle type for Nigeria. They contain: | Source | What it has | What it lacks | |---|---|---| | TSDK Nigeria (Zenodo) | Vehicle stock, passenger-km, freight ton-km, load factors (sparse), energy intensity | VKT by vehicle type; consistent year/definition set | | ICCT soot-free transpor - Term `VKT`: > Lagos transport statistics — publish **annual vehicle-kilometres travelled (VKT)** by road vehicle type for Nigeria. They contain: | Source | What it has | What it lacks | |---|---|---| | TSDK Nigeria (Zenodo) | Vehicle stock, passenger-km, freight ton-km, load factors (sparse), energy intensity | VKT by vehicle type; consistent year/definition set | | ICCT soot-free transport | In-use stock estimates, fuel quality, fleet projections | Mileage or VKT | | World Bank Lagos AQM | Emission inventory, mode share, policy scenarios | Vehicle-type VKT | | NBS / FRSC | Total/private/commercial stocks, nu - Term `Mileage`: > | What it has | What it lacks | |---|---|---| | TSDK Nigeria (Zenodo) | Vehicle stock, passenger-km, freight ton-km, load factors (sparse), energy intensity | VKT by vehicle type; consistent year/definition set | | ICCT soot-free transport | In-use stock estimates, fuel quality, fleet projections | Mileage or VKT | | World Bank Lagos AQM | Emission inventory, mode share, policy scenarios | Vehicle-type VKT | | NBS / FRSC | Total/private/commercial stocks, number plates, crash-involved vehicles | VKT or annual distance | Web search (SSATP, Climate Action Transparency, academic studies) also found **L - Term `VKT`: > as | What it lacks | |---|---|---| | TSDK Nigeria (Zenodo) | Vehicle stock, passenger-km, freight ton-km, load factors (sparse), energy intensity | VKT by vehicle type; consistent year/definition set | | ICCT soot-free transport | In-use stock estimates, fuel quality, fleet projections | Mileage or VKT | | World Bank Lagos AQM | Emission inventory, mode share, policy scenarios | Vehicle-type VKT | | NBS / FRSC | Total/private/commercial stocks, number plates, crash-involved vehicles | VKT or annual distance | Web search (SSATP, Climate Action Transparency, academic studies) also found **Lagos-sp - Term `VKT`: > ht ton-km, load factors (sparse), energy intensity | VKT by vehicle type; consistent year/definition set | | ICCT soot-free transport | In-use stock estimates, fuel quality, fleet projections | Mileage or VKT | | World Bank Lagos AQM | Emission inventory, mode share, policy scenarios | Vehicle-type VKT | | NBS / FRSC | Total/private/commercial stocks, number plates, crash-involved vehicles | VKT or annual distance | Web search (SSATP, Climate Action Transparency, academic studies) also found **Lagos-specific mileage assumptions** and activity descriptions, but no national VKT table. ## Proposed - Term `VKT`: > ition set | | ICCT soot-free transport | In-use stock estimates, fuel quality, fleet projections | Mileage or VKT | | World Bank Lagos AQM | Emission inventory, mode share, policy scenarios | Vehicle-type VKT | | NBS / FRSC | Total/private/commercial stocks, number plates, crash-involved vehicles | VKT or annual distance | Web search (SSATP, Climate Action Transparency, academic studies) also found **Lagos-specific mileage assumptions** and activity descriptions, but no national VKT table. ## Proposed derivation (interim only) If a VKT-based estimate is unavoidable, derive it as: ``` VKT_vehi - Term `mileage`: > rld Bank Lagos AQM | Emission inventory, mode share, policy scenarios | Vehicle-type VKT | | NBS / FRSC | Total/private/commercial stocks, number plates, crash-involved vehicles | VKT or annual distance | Web search (SSATP, Climate Action Transparency, academic studies) also found **Lagos-specific mileage assumptions** and activity descriptions, but no national VKT table. ## Proposed derivation (interim only) If a VKT-based estimate is unavoidable, derive it as: ``` VKT_vehicle_type = passenger-km_or_freight-ton-km / load_factor / stock ``` - Use **TSDK Nigeria** for passenger-km, freight ton-km - Term `VKT`: > rios | Vehicle-type VKT | | NBS / FRSC | Total/private/commercial stocks, number plates, crash-involved vehicles | VKT or annual distance | Web search (SSATP, Climate Action Transparency, academic studies) also found **Lagos-specific mileage assumptions** and activity descriptions, but no national VKT table. ## Proposed derivation (interim only) If a VKT-based estimate is unavoidable, derive it as: ``` VKT_vehicle_type = passenger-km_or_freight-ton-km / load_factor / stock ``` - Use **TSDK Nigeria** for passenger-km, freight ton-km, and vehicle stock. - Apply TSDK load factors where availabl - Term `VKT`: > ommercial stocks, number plates, crash-involved vehicles | VKT or annual distance | Web search (SSATP, Climate Action Transparency, academic studies) also found **Lagos-specific mileage assumptions** and activity descriptions, but no national VKT table. ## Proposed derivation (interim only) If a VKT-based estimate is unavoidable, derive it as: ``` VKT_vehicle_type = passenger-km_or_freight-ton-km / load_factor / stock ``` - Use **TSDK Nigeria** for passenger-km, freight ton-km, and vehicle stock. - Apply TSDK load factors where available; use default ranges where missing. - Cross-check priva - Term `VKT`: > es | VKT or annual distance | Web search (SSATP, Climate Action Transparency, academic studies) also found **Lagos-specific mileage assumptions** and activity descriptions, but no national VKT table. ## Proposed derivation (interim only) If a VKT-based estimate is unavoidable, derive it as: ``` VKT_vehicle_type = passenger-km_or_freight-ton-km / load_factor / stock ``` - Use **TSDK Nigeria** for passenger-km, freight ton-km, and vehicle stock. - Apply TSDK load factors where available; use default ranges where missing. - Cross-check private/commercial car assumptions against Lagos-only estim - Term `VKT`: > **TSDK Nigeria** for passenger-km, freight ton-km, and vehicle stock. - Apply TSDK load factors where available; use default ranges where missing. - Cross-check private/commercial car assumptions against Lagos-only estimates from Haruna et al. (2025). This is a **stop-gap**, not a robust national VKT dataset. ## Annual mileage table by vehicle type | Vehicle type | Central km/veh/yr | Range (±) | Basis / source | |---|---:|---:|---| | Motorcycle | 10,000 | 7,000 – 14,000 | TSDK passenger-km ÷ TSDK motorcycle stock; assumed occupancy 1.0–1.5 passengers/vehicle. | | Car / taxi | 25,000 | 8,000 - Term `Annual mileage`: > for passenger-km, freight ton-km, and vehicle stock. - Apply TSDK load factors where available; use default ranges where missing. - Cross-check private/commercial car assumptions against Lagos-only estimates from Haruna et al. (2025). This is a **stop-gap**, not a robust national VKT dataset. ## Annual mileage table by vehicle type | Vehicle type | Central km/veh/yr | Range (±) | Basis / source | |---|---:|---:|---| | Motorcycle | 10,000 | 7,000 – 14,000 | TSDK passenger-km ÷ TSDK motorcycle stock; assumed occupancy 1.0–1.5 passengers/vehicle. | | Car / taxi | 25,000 | 8,000 – 55,000 | TSDK car passenge - Term `vehicle-km`: > i. & Tech., DOI:10.64290/bima.v9i3A.1356 Confidence: **Low**. The ranges are wide because activity and stock come from different years/methodologies, load factors are sparse, and key categories (HDV payload, LDV occupancy, bus stock) rely on assumptions. ## Recommended action for NEFDB v1 **Drop vehicle-km emission factors and keep fuel-based factors only for v1.** Rationale: - Fuel-based factors (kg CO₂e per litre from IPCC/Defra/EPA) can be applied directly to fuel-consumption data, which is more available and more reliable. - A derived VKT table would propagate large, poorly bounded uncertainty i - Term `VKT`: > tions. ## Recommended action for NEFDB v1 **Drop vehicle-km emission factors and keep fuel-based factors only for v1.** Rationale: - Fuel-based factors (kg CO₂e per litre from IPCC/Defra/EPA) can be applied directly to fuel-consumption data, which is more available and more reliable. - A derived VKT table would propagate large, poorly bounded uncertainty into Scope 1/2/3 calculations. - NEFDB’s credibility for listed-company reports is better served by transparently flagging the gap than by publishing weak VKT numbers. If a downstream Scope 3 or transport module must have VKT, store the table - Term `VKT`: > tly to fuel-consumption data, which is more available and more reliable. - A derived VKT table would propagate large, poorly bounded uncertainty into Scope 1/2/3 calculations. - NEFDB’s credibility for listed-company reports is better served by transparently flagging the gap than by publishing weak VKT numbers. If a downstream Scope 3 or transport module must have VKT, store the table above as an **interim `derived/road_vkt_interim.csv`** with explicit `confidence=low` and `derived=assumption` flags for every row. ## Follow-up to close the gap 1. Acquire the TSDK Nigeria `.xlsx` into `NEFDB/da - Term `VKT`: > ble. - A derived VKT table would propagate large, poorly bounded uncertainty into Scope 1/2/3 calculations. - NEFDB’s credibility for listed-company reports is better served by transparently flagging the gap than by publishing weak VKT numbers. If a downstream Scope 3 or transport module must have VKT, store the table above as an **interim `derived/road_vkt_interim.csv`** with explicit `confidence=low` and `derived=assumption` flags for every row. ## Follow-up to close the gap 1. Acquire the TSDK Nigeria `.xlsx` into `NEFDB/datasets/transport_aviation/road_vkt/` so the derivation is reproducib - Term `vkt`: > bounded uncertainty into Scope 1/2/3 calculations. - NEFDB’s credibility for listed-company reports is better served by transparently flagging the gap than by publishing weak VKT numbers. If a downstream Scope 3 or transport module must have VKT, store the table above as an **interim `derived/road_vkt_interim.csv`** with explicit `confidence=low` and `derived=assumption` flags for every row. ## Follow-up to close the gap 1. Acquire the TSDK Nigeria `.xlsx` into `NEFDB/datasets/transport_aviation/road_vkt/` so the derivation is reproducible. 2. Request official mileage/odometer data from FRSC, - ... and 5 additional matches omitted. ## Conclusion - **No** — none of the downloaded source files contains **usable Nigeria VKT data disaggregated by road vehicle type**. - Relevant mentions are only methodological or generic: - `world_bank_lagos_air_quality_management.md` mentions vehicle-kilometres as a general output measure and a high-level danfo mileage estimate (up to 80,000 km/year) for Lagos. - `LAMATA_WB_ICR.md` uses VKT/vehicle-kilometres as a project indicator language, not as a Nigeria VKT dataset. - `ghg_protocol_scope3_calculation_guidance.md`, `glec_framework_v3_dec2024.md`, `uk_defra_2024_methodology.md`, and `ipcc_2006_vol2_ch3_mobile_combustion.md` are global methodology documents that define vehicle-km / VKT / annual mileage concepts. - `icao_icec_methodology_v13_1.md` matched only airport codes that contain the letters “VKT”. - `vkt_gap_verdict.md` documents the same gap and contains an **interim, derived** annual-mileage-by-vehicle-type table based on assumptions; it is not a downloaded Nigeria VKT source. - The downloads explicitly searched (`TSDK_Nigeria.xlsx`, `TSDK_Nigeria.pdf`, `fleet_registration_summary.csv`, ICCT, NBS/FRSC markdowns, Lagos transport statistics) contain **no VKT, annual mileage, or vehicle utilization data**.