Electrifying passenger road transport in India requires near-term electricity grid decarbonisation

The study addresses how electrification of India’s passenger road transport affects life cycle greenhouse gas (GHG) emissions and under what conditions BEVs provide climate benefits. Transport accounts for a quarter of global CO2 emissions from fuel combustion, with light-duty passenger road vehicles responsible for around 40% of transport emissions. Policy responses are often technology-centric, with many NDCs prioritising electrification. BEV use shifts emissions from vehicle tailpipes to the electricity sector, making grid carbon intensity decisive for net GHG outcomes. Owing to regional diversity in generation mixes, ambient temperatures, and charging patterns, BEV benefits cannot be generalized across countries or within India. India’s transport sector contributed about 13% of energy-related GHG emissions in 2019, with rapid growth in vehicle stock dominated by two-wheelers and relatively low but rising car ownership. The paper models life cycle emissions for over 600 commercially available 2W and 4W vehicles (FY 2018/19), accounting for energy production, vehicle manufacturing (including batteries), use, and end-of-life, to quantify how time of day/year and regional charging conditions influence BEV emissions and to identify technology pathways for near-term mitigation.

The authors developed a cradle-to-grave life cycle assessment (LCA) for more than 600 passenger light-duty vehicles (2W and 4W) sold in India in FY2018/19. Emissions include CO2, CH4, and N2O from energy production (fuels and electricity), vehicle use-phase, manufacturing (including battery production), and end-of-life recycling. Key calculations: LCE (gCO2e/ton-km) = Eme (tailpipe, zero for BEVs) + Ep (energy production) + Exp (manufacturing) − Ecol (end-of-life recycling credit), normalized by vehicle curb mass. Energy production emissions Ep are the product of the carbon intensity of energy (gCO2e/MJ for fuels, gCO2/kWh for electricity) and real-world energy consumption (MJ/km or kWh/km).

• Electricity carbon intensity (CI): Derived from Central Electricity Authority (CEA) data for FY2018/19, disaggregated into five regions (north, west, south, east, north-east) and hourly profiles for typical winter and summer days, with India-average transmission and distribution losses applied. Static generation mix is assumed over vehicle lifetimes. For 2018/19 and 2029/30, average CI values are 927 and 676 gCO2/kWh, respectively. Future mix (2029/30) follows CEA’s optimal generation mix projection considering demand growth (to 2517 TWh), capacity additions, costs, and intermittency; coal is projected to supply 54% of electricity, wind/solar 31% of generation with increased installed capacity and 27 GW of storage.
• Fuel production CI: Well-to-tank intensities for gasoline and diesel reflect India’s crude mix and refinery operations using Masnadi et al. and Jing et al., giving 17.3 gCO2e/MJ (gasoline) and 16.4 gCO2e/MJ (diesel), with combustion emissions based on certified tailpipe values.
• Vehicle energy use and tailpipe emissions: Type-approved consumption and emissions (ARAI, MIDC/NEDC-based) from SIAM and other sources are adjusted to reflect real-world use. Consistent with literature and Argonne National Laboratory analyses, penalties of +20% energy/fuel for ICEV/HEV and +40% for BEV are applied to NEDC values. Temperature adjustment factors account for ambient temperature effects (HVAC and battery performance): India-average penalties of ~4% (ICE), 5% (HEV), and 6% (BEV) based on monthly mean temperatures. Hourly/seasonal electricity profiles are used to map charging time emissions.
• Vehicle manufacturing and end-of-life: 4W production and recycling emissions are derived using Sphera GaBi 9.2 databases (2020). Battery manufacturing and recycling data are replaced with primary-data-based LCA for NCM batteries, yielding 124.5 kgCO2e/kWh for manufacturing and 93.6 kgCO2e/kWh net after recycling. For Indian BEVs (20–30 kWh batteries; 1200–1600 kg curb weight), production emissions are ~8–10 tCO2, with 3–4 tCO2e recycling credit, netting ~5–6 tCO2e over life. 2W production/recycling are estimated by scaling from 4W (component resizing) and literature cross-check: for a class-1 2W (~109 kg), net production/recycling ~1.1 tCO2, overall life-cycle ~73.8 gCO2e/km; for electric 2W (1.0–3.3 kWh, 68–118 kg), net manufacturing/recycling ~1.0–1.2 tCO2e. Lifetime distances are 200,000 km (4W; ~12,500 km/year over 16 years) and 80,000 km (2W).
• Scenario and sensitivity analyses: Regional and temporal charging profiles (hourly, seasonal), regional electricity mixes, and “static vs dynamic” grid mix sensitivities (0.5–1.5% annual CI reductions) are tested. Future (2030) scenarios assess BEV benefits against cleaner grid and varying BEV efficiencies (100–200 Wh/km) and fuel economy baselines (4–6 L/100 km). Real-world correction factor alternatives (e.g., 30% BEV range loss; 34% ICE real-world increase) are explored. Policy-related calculations include gasoline-equivalent fuel consumption for BEVs vs India’s Phase-2 corporate-average fuel consumption standard (from 2022/23) for a representative curb weight of 1237 kg.

• Regional and temporal dependency of BEV benefits: In 2018/19, life-cycle GHG outcomes for 4W BEVs vary markedly by region and charging time. North-eastern India (gas and hydro-dominant) enables large BEV benefits (~40–47% vs gasoline; ~37–42% vs diesel), while eastern and western regions (coal-heavy: 89% and 84% coal share) can lead to higher BEV life-cycle emissions (increases exceeding 15%) relative to ICE baselines. Northern and southern regions show moderate benefits (often positive vs gasoline, diminished vs diesel).
• Time-of-day and season: Due to the “duck-curve” and higher overnight grid CI, charging off-peak at night raises BEV life-cycle emissions by about 3–9% versus daytime charging; summer conditions further elevate emissions compared to winter.
• Current power mix constraints: India’s grid was >70% coal in 2018/19; wind+solar generation totaled 101 TWh (~7% of 1376 TWh demand). Intermittency drives hourly and seasonal variability, directly influencing BEV life-cycle emissions.
• 2030 cleaner grid scenario: With projected 27% lower average grid CI in 2029/30 (to ~676 gCO2/kWh), BEV life-cycle emissions fall by ~23–25% versus 2018/19 BEVs. BEV benefit in 2030 depends strongly on BEV Wh/km and ICE baseline L/100 km. Under India’s Phase-2 standard (4.95 L/100 km at 1237 kg), a BEV at ~142 Wh/km has comparable life-cycle GHG to a gasoline vehicle; less efficient BEVs can be worse, while more efficient ones deliver clearer benefits.
• BEV vs diesel: Diesel vehicles (~25% lower fuel use than gasoline counterparts) erode BEV relative advantages under current grid conditions; BEV mitigation potential is diminished when compared to diesel ICEs in many regions.
• Hybrids as near-term mitigation: Compared to gasoline 4W, diesel, diesel-hybrid, and gasoline-hybrid reduce life-cycle GHG by ~21%, ~25%, and ~33%, respectively, requiring no charging infrastructure and less battery material, offering robust near-term mitigation.
• Two-wheelers: 2W dominate sales (>80% of 26.2 million vehicles in 2018/19) and are ~70% less GHG-intensive per km than 4W. Electric 2W already offer about 20% GHG reduction relative to gasoline 2W due to superior efficiency and small batteries, with small manufacturing penalties.
• Charging behavior and policy levers: Night-time home charging preferences observed internationally could worsen BEV emissions unless managed; time-differentiated tariffs could encourage lower-emission daytime charging.
• Regulatory accounting gap: India’s tailpipe-only fuel consumption standard assigns BEVs very low gasoline-equivalent consumption (e.g., 1.0 L/100 km for 100 Wh/km), but life-cycle accounting shows this understates true emissions by factors of ~3.5 (2030) to ~4.7 (2019). To justify 1.0 L/100 km equivalence, grid CI would need to be ≤150 gCO2e/kWh (about 78% below 2030 forecast), illustrating a GHG loophole.
• Scale and materials: India’s EV30@30 ambitions imply up to 125 GWh/year of battery capacity by 2030 (nearly 10% of projected world output). Global trends toward larger BEV batteries (e.g., China average 37 kWh in 2018; B-segment ~60 kWh) and rising SUV share heighten battery/material demands; hybrids require far less critical materials.
• Quantitative examples: Off-peak BEV charging increases life-cycle emissions by 3–9%; 2030 grid CI ~676 gCO2/kWh; renewables/wind+solar generation was 101 TWh (~7%) in 2018/19; Phase-2 standard threshold 4.95 L/100 km at 1237 kg; diesel has ~25% lower fuel use than gasoline variants.

The findings demonstrate that BEV climate benefits in India are highly contingent on electricity grid decarbonisation, spatial heterogeneity in power mixes, and charging timing. Under today’s coal-dominated grid, BEVs can underperform efficient ICEs in coal-heavy regions and when charged overnight or in summer. As the grid transitions toward lower carbon intensity, BEVs’ life-cycle emissions decline substantially, but achieving robust benefits also requires efficient BEV designs (low Wh/km) and improvements in ICE baselines. In contrast, self-charging hybrids deliver immediate and consistent GHG reductions (21–33%) without reliance on charging infrastructure or clean electricity, providing a practical bridge technology that eases materials constraints. Given India’s overwhelming 2W market share and the high relative efficiency of 2W, prioritizing electrification of 2W yields near-term, scalable mitigation with smaller batteries and lower manufacturing penalties. Policy implications include: accelerating grid decarbonisation (especially phasing down coal), aligning transport electrification with progress on reliable, affordable power access, and using time-of-use tariffs to shift charging to lower-emission periods. The current tailpipe-only fuel economy framework creates GHG accounting loopholes that over-credit BEVs; integrating life-cycle emissions into vehicle and fuel standards would better align regulations with climate goals. A balanced ‘avoid-shift-improve’ strategy—supporting active mobility and public transit, improving urban design, encouraging telework, and deploying a mosaic of technologies (efficient ICEs, hybrids, BEVs, and sustainable low-carbon fuels)—is essential to meet mitigation targets while accounting for regional diversity and grid realities.

Electrification can reduce passenger transport GHGs in India, but its effectiveness hinges on near-term grid decarbonisation, spatial charging context, and BEV efficiency. Today, 4W BEV benefits are strong in the north-east and mixed to negative in coal-heavy regions, especially with night-time charging. By 2030, a cleaner grid enables larger BEV benefits, provided BEVs remain energy-efficient relative to evolving ICE baselines. Hybrids offer immediate, sizable reductions with lower materials demand, and electrifying the dominant 2W segment provides meaningful near-term mitigation. India’s EV strategy should be phased: prioritize 2W electrification, accelerate hybrids and stringent fuel-efficiency/low-carbon fuel standards for 4W, and commit to a clear coal phase-down to unlock full BEV benefits. Regulatory reforms should close tailpipe-only loopholes by adopting life-cycle-based accounting. Future research should refine dynamic grid modeling, incorporate detailed fleet evolution and real-world usage/charging behavior, and assess supply-chain sustainability and recycling to support a circular battery/materials economy.

Key limitations include: (1) Assuming a static electricity generation mix over vehicle lifetimes, whereas real-world grids evolve; sensitivity analyses with dynamic decarbonisation rates slightly lower BEV emissions but the main conclusions remain. (2) Real-world driving and energy use differ from type-approval cycles (NEDC/MIDC), especially for highly electrified vehicles; the study applies literature-based correction factors and temperature adjustments but acknowledges uncertainty in penalties and their regional variability. (3) Lack of explicit fleet dynamics (sales mix shifts, scrappage, segment trends) may influence aggregate emissions trajectories. Additional uncertainties arise from battery manufacturing/recycling inventories, regional charging accessibility/behavior, and future technology shifts (vehicle mass, aerodynamics, HVAC loads).