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Review examines renewable natural gas growth in North America, indicating challenges and opportunities for expansion.
Renewable natural gas (RNG), or upgraded biomethane, is an increasingly important low-carbon fuel that converts organic wastes into pipeline-quality gas while advancing circular-economy objectives. This review examines the rapidly growing North American RNG sector in a global context, focusing on feedstock resources, anaerobic digestion, gas-upgrading technologies, lifecycle carbon intensity, economics, policy drivers, and commercialization challenges. North America possesses one of the world’s largest biomethane resource bases, including agricultural residues, landfill gas, wastewater sludge, and organic wastes, supported by extensive natural gas infrastructure. Market growth has been driven primarily by U.S. Renewable Fuel Standard (RFS) and Low Carbon Fuel Standard (LCFS) incentives, while deployment in Canada and Mexico remains constrained by infrastructure, financing, regulatory, and policy limitations. Major upgrading technologies, including water scrubbing, pressure swing adsorption, membrane separation, amine absorption, biological methanation, and cryogenic upgrading, are evaluated in terms of methane recovery, energy consumption, methane slip, and end use suitability. Although cryogenic systems achieve the highest methane purity, membrane separation and pressure swing adsorption currently offer greater commercial maturity and scalability. While RNG production costs generally exceed those of fossil natural gas, project economics are enhanced by carbon credits, avoided methane emissions, waste management benefits, and digestate valorization. Emerging opportunities include modular upgrading systems, artificial intelligence-assisted process optimization, hydrogen integration, and carbon utilization pathways. Key challenges remain in methane leakage quantification, lifecycle assessment harmonization, rural deployment scalability, digestate management, and integrated carbon management strategies required for cost-effective large-scale RNG expansion.
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Patil et al. (2026) studied this question.
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