Road-Transport CO₂ Emissions and Decarbonization Pathways in Pakistan

Description

This dataset supports the research article "Explaining the Motorization–Emission Paradox: Road-Transport CO₂ Emissions and Decarbonization Pathways in Pakistan," submitted to Sustainable Environment Research. The dataset contains 25 annual observations (2000–2024) for Pakistan's road-transport sector, compiled from four primary sources: the Pakistan Bureau of Statistics (PBS) Statistical Yearbook, the Hydrocarbon Development Institute of Pakistan (HDIP) Energy Yearbook, the World Bank World Development Indicators (WDI), and the National Electric Power Regulatory Authority (NEPRA) State of Industry Reports. The dataset includes the following variable categories: (1) Transport CO₂ emissions: Vehicle-disaggregated carbon dioxide emissions (Mt CO₂e) calculated using IPCC Tier 1 default emission factors for motor gasoline, gas/diesel oil, and compressed natural gas (CNG), following the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (Volume 2: Energy). (2) Vehicle registration data: Annual registered vehicle counts disaggregated by vehicle type — motorcycles, cars/jeeps/light commercial vehicles, buses, trucks, and three-wheelers/taxis — sourced from PBS. (3) Fuel consumption data: Annual consumption of motor gasoline (petrol), high-speed diesel (HSD), and compressed natural gas (CNG) allocated to the road-transport sector, sourced from HDIP Energy Yearbooks. Fuel-to-vehicle allocation was performed using a bottom-up approach based on fleet composition, average annual mileage, and type-specific fuel economy estimates, documented in Additional file 5 of the manuscript. (4) Macroeconomic and demographic indicators: Real GDP (constant 2015 USD), total population, urbanization rate (% urban), and GDP per capita, sourced from the World Bank WDI. (5) Energy and structural variables: Transport energy intensity (toe per million USD GDP), transport share of total energy consumption, per-vehicle fuel consumption by vehicle type, and fleet composition shares used in the LMDI decomposition analysis. (6) ARDL model variables: Natural logarithms of transport CO₂ emissions (lnTCO2), real GDP (lnGDP), population (lnPOP), vehicle registrations (lnVEH), energy intensity (lnEI), and urbanization (lnURB). (7) Scenario assumption parameters: IEA STEPS-calibrated parameters for electric vehicle penetration rates, CNG transition shares, fleet turnover rates, and grid emission factor trajectories used in the 2025–2050 forecasting scenarios. All monetary values are in constant 2015 USD. Energy quantities are in tonnes of oil equivalent (toe) or thousand tonnes of oil equivalent (ktoe). Emissions are in million tonnes of CO₂ equivalent (Mt CO₂e).

Institutions

• Chang'an University

  Shaanxi, Xi'an

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