Solutions for decarbonising urban bus transport: a life cycle case study in Saudi Arabia

Greenhouse gas (GHG) reduction in non-OECD countries is critical due to faster annual GHG growth and slower uptake of decarbonisation technologies. Saudi Arabia, aiming for net zero by 2060 with Vision 2030 as a mid-term target, has transport emissions contributing 22% of national GHGs and seeks to reduce private vehicle dependence by enhancing urban bus transport. Hydrogen fuel cell vehicles (FCVs) and battery electric vehicles (BEVs) offer zero tailpipe emissions, but life-cycle impacts depend on feedstock production, electricity generation sources, fuel production efficiency, battery manufacturing, fuel cell stack performance, battery technology, and operational efficiency. A comprehensive life-cycle assessment (LCA) is needed to evaluate decarbonisation potential. Hydrogen is classified by production method: green (electrolysis with renewables), blue (steam methane reforming (SMR) with carbon capture and storage (CCS)), and grey (SMR without CCS). In 2021, 4% of global H2 used renewables vs 48% from natural gas; Saudi Arabia’s substantial NG reserves make grey/blue hydrogen more feasible in the near term. Literature on FCVs/BEVs LCA for urban buses—especially PEM fuel cell buses—is sparse, often omitting infrastructure (charging and hydrogen refuelling stations) and lacking a Saudi context. This study fills these gaps with a full life-cycle analysis of fuel cell buses (FCBs), battery electric buses (BEBs), and internal combustion engine buses (ICEBs), including shipping, AC loads, and infrastructure, for a Makkah bus fleet in 2022 and 2030 scenarios. Practical transitional strategies—blue/grey hydrogen for FCBs and grid-powered BEBs—are evaluated, alongside hypothetical all-renewable BEBs and a 2030 hydrogen mix, and sensitivity analyses. A globally applicable LCA model tailored for non-OECD conditions is developed, expanding GREET to include bus-specific life-cycle phases and AC energy demands.

The study notes significant research gaps in LCAs of urban buses, particularly PEM fuel cell buses, with existing work often limited to powertrain analysis and lacking inclusion of infrastructure for charging and hydrogen refuelling. There is little to no research contextualised for Saudi Arabia. Prior LCAs identify the need to account for feedstock production, energy sources, battery manufacturing impacts, and operational factors. Hydrogen production pathways (green, blue, grey) and their varying environmental profiles are established in literature, but comparative, full life-cycle analyses for urban buses in non-OECD contexts remain sparse.

The study follows a bottom-up LCA compliant with ISO 14040/14044 to quantify life-cycle energy use and emissions for FCBs (PEM), BEBs, and ICEBs in a Makkah, Saudi Arabia urban bus fleet. Functional unit: 1 km travelled by a bus under general operation, assuming 30 passengers per bus to neutralize load variability. Scope includes both vehicle cycle (materials, components, assembly, disposal, recycling (ADR), shipping) and fuel cycle (feedstock production, fuel production, distribution, refuelling/charging infrastructure, and operation). Fleet and operation: 20 buses (18 active, 2 reserve), 10-year life, 508,080 km per bus, two 2-hour rounds/day with 3-hour rests, service every 20 minutes from 08:00–22:00 on a defined Makkah route. Models and data: GREET 2022 used for core LC coefficients; original sub-models developed for hydrogen refuelling stations (RFS), super-fast charging stations (SFCS), roll-on/roll-off shipping, and bus AC energy/cooling loads; H2A used for grey/blue hydrogen SMR production simulation; Python-based geospatial model (GIS shapefiles, Haversine distances) to estimate average transport distances of electricity feedstocks and fuels. Life-cycle inventory (LCI): Combined primary/secondary sources, company consultations, literature, GREET, and ecoinvent 3.9.1. Vehicle specifications: Three bus models represent each technology—Toyota Sora (FCB), BYD K9 (BEB), Volvo B8RLE (ICEB). Material bills of materials compiled (Fig. 2). Vehicle cycle scaling: In ADR phase, bus energy and emissions assumed proportional to vehicle weight based on GREET passenger vehicle relationships. Shipping: Roll-on/roll-off vessel model using ICCT method. Assumptions include 8-cylinder main engine (2360 kW/cyl), SFC 217 g/kWh, average speed 19.8 knots, auxiliary/boiler powers 1518/225 kW. Estimated shipping distances: FCB 8036 nautical miles (from Japan), BEB 6500 nm (from China), ICEB 6009 nm (from Sweden). Air conditioning (AC) load model: Detailed heat balance for cabin cooling load (metabolic, solar, ventilation, ambient exchange, heating system, and drivetrain-specific terms). Comfort temperature set to 25 °C; Makkah average outdoor 39 °C; COP of AC compressor 1.6. Solar geometry and irradiance (Global Solar Atlas) used to compute solar heat gains; convection coefficients derived for assumed bus speed; SHGF 172.5 W/m², shading coefficient 0.81. AC cooling load found to be ~32.2 kW with roof contributing ~55% of thermal load; AC energy included in operation across all bus types. Operation energy baselines (excluding AC/aux): FCB 5.5 kg H2/100 km, BEB 0.9 kWh/km, ICEB 30 L diesel/100 km; temperature assumed not to affect FCB/BEB baseline efficiency under Makkah conditions. Hydrogen cycle (2022): Blue hydrogen from Jubail (SMR with CCS, 90% CCS efficiency); grey hydrogen from Yanbu (SMR without CCS). NG sources/pipelines: Blue uses NG from Fadhili (pipeline 74.9 km); grey uses east-west pipeline from Abqaiq to Yanbu (1193 km). Methane leakage: Upstream default 0.05% (Aramco 2022), processing 0.03% (GREET), transmission/compression 0.18% per 1000 km (ecoinvent), distribution 0.09% (US EPA). Hydrogen production efficiencies (LHV): blue 69%, grey 76% (KAPSARC). H2A used to estimate consumption: NG use 0.1635 mmBTU/kg H2 (blue), 0.1483 mmBTU/kg H2 (grey); electricity 0.5 kWh/kg H2, water 10 L/kg H2. Steam co-production scenarios considered: surplus steam can feed CCS or be exported to chemical plants; five cases compare blue/grey, locations (Jubail/Yanbu), and steam use/export. Hydrogen transport: pipelines to bulk terminals, then tube trailers to stations; loss factors and compression efficiency from GREET; SMR plant construction excluded. Hydrogen RFS: Inventory based on HydroStatoil model (Reykjavik) BOM; FCB tanks 600 L (~23.46 kg H2), consumption ~9.7 kg/100 km with AC; station sized at 259 kg/day to meet 245 kg/day for fleet; component lifetimes ≥10 years. Electricity cycle: 2022 energy mix assumed as 60.6% NG, 39.2% oil, 0.2% solar; 2030 target: 50% renewables (34.4% solar, 13.6% wind) and 50% NG. Power plant technology shares and efficiencies set from literature/GREET. Grid losses 7% (sensitivity 4–10%). Emission factors per technology from ecoinvent/literature (Table 2). Feedstock transport distances computed: oil refineries to plants 742 km; NG fields to plants 577 km. SFCS: Station with six 350 kW chargers (operated at 150 kW for safety), three power units, one control unit; material composition from literature and GREET emission factors. Diesel cycle: Steps include crude extraction (recovery 99.1%), processing at Abqaiq, pipeline to Yanbu (1193 km at 260 BTU/ton-mile), refining at SAMREF/YASREF (assumed equal diesel supply; refinery efficiency 90.4% from average API 30.5 and sulfur 2.325%), pipeline to Jeddah bulk (303 km), trucking to Makkah retail (96 km). Well-to-pump energy use 16.6% of diesel energy (166,466 BTU/mmBTU), CO2 11,178 g/mmBTU (2022 grid). Vehicle end-of-life and recycling: 2022 recycling rates in KSA assumed 33.9% aluminium, 10% steel; no LFP battery recycling facilities in KSA (assume 30% Li2CO3 recycling by 2030 via hydrometallurgy). Battery/stack replacements: Within 10 years, BEB LFP and FCB PEM stacks not replaced; ICEB lead-acid likely 3 replacements; NiMH in ICEBs one replacement (per assumptions). 2030 scenario: Increased grid renewables, CCS efficiency from 90% to 96.2%, 9.7% shale gas in NG mix, vehicle light-weighting (30% steel replaced by aluminium), local assembly in Saudi Arabia (eliminating shipping), higher recycled content in manufacturing (73.6% steel, 64.9% aluminium), LFP recycling 30%, and PEM FC stack efficiency increased from 52% to 61%. Also evaluates BEBs powered entirely by renewable electricity (PV infrastructure excluded) and a mixed hydrogen scenario (98% blue, 2% grey). Sensitivity analysis: Nearly all impact factors varied ±10% (exceptions: grid losses 4–10%, methane leakage 0–1%), defining “worse” and “better” cases by direction of GWP100 change. LCIA: CML2001 for GWP100, GWP20, acidification potential (AP), eutrophication potential (EP), photochemical oxidation potential (POP).

- 2022 life-cycle GHG emissions (kg CO2-eq/km): blue FCB 0.84; grey FCB 1.29; BEB (grid) 1.51; ICEB 1.81. Vehicle-cycle contributes 12–24% of emissions; fuel-cycle dominates others. - 2022 life-cycle energy consumption (MJ/km): blue FCB 28.59 (highest due to CCS energy); ICEB second-highest (operation-dominated); BEB second-lowest overall despite highest vehicle-cycle energy; grey FCB lowest total energy. - Compared to ICEB, blue FCB reduces GHG emissions by 53.6% but increases energy use by 19.5% (due to CCS). BEB reduces emissions by 16.9% and reduces energy use by 6.1% vs ICEB. - Fuel-cycle GHG (2022) (kg CO2-eq/km): blue H2 0.64 (lowest); grey H2 1.09; grid electricity 1.25; diesel 1.60 (operation 87% of diesel emissions). Fuel production contributes 90–93% for H2/electricity options. Methane leakage assumed low (0.38% cumulative), helping lower fuel-cycle GHG. - Operation phase energy: BEB lowest at 1.60 kWh/km; FCB next; ICEB much higher due to ~30% powertrain efficiency. AC accounts for 38–44% of operational energy; roof contributes ~55% of AC cooling load. - Hydrogen production scenarios: Blue H2 (Jubail) vs grey H2 (Yanbu) – blue reduces GHG by 0.45 kg/km but increases energy by 7.4 MJ/km (CCS energy). Grey with steam export (case 3) reduces GHG by 0.20 kg/km and energy by 3.36 MJ/km vs stand-alone grey (case 5). Producing blue H2 at Yanbu (case 4) vs grey at Yanbu (case 3) reduces GHG by 0.61 kg/km and energy by 5.2 MJ/km. Blue at Yanbu vs blue at Jubail reduces transport-related GHG and energy by 0.15 kg/km and 2.27 MJ/km. - 2030 scenario: BEB sees largest declines—GHG −51% and energy −35% vs 2022—becoming least energy-consuming and second-lowest emitting; reductions predominantly from fuel cycle due to grid decarbonisation. Blue FCB remains lowest-emitting, though advantage over BEB shrinks; reductions from improved CCS and cleaner power. Grey FCB: GHG −19%, energy −15%; loses least-energy status to BEB. ICEB remains most emitting; marginal declines mainly from vehicle-cycle improvements. - 2030 mixed hydrogen (98% blue, 2% grey) FCB: 0.57 kg CO2-eq/km and 24.74 MJ/km, similar to pure blue hydrogen. - Hypothetical all-renewable BEBs: 2022 case would achieve 9.82 MJ/km energy and 0.26 kg CO2-eq/km (−54% energy vs grey FCB; −69% GHG vs blue FCB). In 2030, 100% green BEBs are the most GHG-efficient, 79% lower than grid BEBs and 72% lower than blue FCBs, and 40% better energy efficiency than grid BEBs. - Other environmental impacts (2022, CML2001): BEBs perform worst for AP, EP, and POP due to NOx from fossil-based electricity; grey FCBs best. GWP20 vs GWP100 similar, with slightly higher feedstock contributions in GWP20. - Sensitivity (GWP100, ±10% unless noted): Blue FCB most sensitive to CCS efficiency (±10.8%); also sensitive (1–4%) to PEM stack efficiency, H2 production efficiency, vehicle weight, outdoor temperature, grid renewables share. Grey FCB most sensitive to H2 production efficiency, then PEM stack efficiency and outdoor temperature. BEB most sensitive to grid renewable share (±6.95%); grid losses, temperature, vehicle weight smaller effects; battery-related factors minor as no replacement within life-cycle. ICEB dominated by diesel fuel carbon footprint (±7.69%); engine/refinery efficiency and temperature smaller effects.

The study demonstrates that full life-cycle assessments materially affect the ranking of decarbonisation options for urban buses in Saudi Arabia. Under current (2022) conditions, blue hydrogen FCBs deliver the greatest GHG reductions relative to diesel, despite higher energy use from CCS. BEBs’ benefits are constrained by the fossil-dominated grid and high battery manufacturing burdens, and they exhibit higher acidification, eutrophication, and photochemical ozone formation impacts. The findings emphasize that decarbonisation effectiveness for BEBs is highly contingent on grid renewable penetration, while FCB performance hinges on CCS efficiency, hydrogen production efficiency, and logistics. Incorporating AC loads—significant in hot climates—shows substantial operational energy shares (38–44%) without changing the relative rankings, underscoring the necessity to include HVAC in LCAs for hot regions. By 2030, with projected grid decarbonisation, enhanced CCS, and vehicle light-weighting, BEBs become competitive on energy use and approach blue FCBs on GHGs, while 100% renewable BEBs become the most GHG- and energy-efficient in theoretical scenarios. Overall, replacing diesel with low-carbon fuels (blue hydrogen or renewable electricity) is key; fuel-cycle decarbonisation dominates total impacts for FCBs and BEBs, whereas diesel remains operation-dominated. The results inform technology choices and infrastructure planning in non-OECD contexts, highlighting how energy system evolution dictates optimal bus propulsion strategies.

Blue hydrogen fuel cell buses are identified as the leading near- to medium-term solution for decarbonising Saudi urban bus transport given feasible fuel supplies, cutting life-cycle GHG emissions by roughly half versus diesel even with higher energy consumption. Anticipated advancements by 2030—grid renewable expansion, improved CCS efficiency, vehicle light-weighting, and better FC stack efficiency—enable deeper cuts for both FCBs and BEBs, with mixed-hydrogen FCBs performing similarly to pure blue hydrogen. In 2022 conditions, grid-powered BEBs offer limited GHG reductions and perform worse on several non-GHG impacts due to fossil-based electricity and battery manufacturing, but by 2030 they achieve substantial life-cycle GHG and energy reductions as the grid decarbonises. In a theoretical scenario, 100% renewable-powered BEBs provide the greatest GHG and energy benefits, though practical deployment depends on renewable availability and allocation to transport, and requires inclusion of renewable infrastructure impacts in future LCAs. The study underscores the importance of broad LCA scope (including shipping, infrastructure, and HVAC loads) and recommends complementary economic analyses, assessments of CCS effectiveness, and exploration of low-carbon fuels such as e-fuels, alongside comprehensive energy efficiency evaluations.

- Geographical and temporal specificity: The case study is tailored to Makkah, Saudi Arabia, with 2022 baseline and 2030 projected parameters; generalisability may vary with local energy mixes, logistics, and climate. - Scope exclusions: Construction of SMR plants for hydrogen production is excluded; environmental impacts of photovoltaic infrastructure are excluded in the 100% renewable BEB scenarios. - Model assumptions and proxies: GREET lacks bus-specific ADR parameters, so ADR energy/emissions are scaled by vehicle weight from passenger vehicles; AC load and shipping models use literature-based parameters; certain distances and efficiencies rely on estimated averages and public databases. - Data constraints: Limited availability of PEM FCB bill of materials and Saudi-specific infrastructure inventories required integrating literature, consultations, and assumptions; 2030 scenario incorporates hypothesised improvements (CCS efficiency, recycled content, vehicle weights, assembly location). - Recycling and replacements: Battery recycling infrastructure is assumed (30% Li2CO3 by 2030) and no LFP/PEM stack replacements within 10 years; deviations would alter results. - Hydrogen scenarios: Steam co-production allocations and plant locations (Jubail/Yanbu) are scenario-based; results sensitive to these system boundary choices and methane leakage rates.