Objective As a vital liquid hydrogen-based energy carrier, green methanol increasingly requires large-scale, cross-regional transportation. Batch transportation of methanol and gasoline via existing refined-oil pipelines is an important technical pathway to reduce transportation costs and improve oil-gas pipeline network utilization. However, the resulting transmix exhibits sharp polarity differences of constituent media, condition-sensitive miscibility, and strict quality limits — posing new requirements for more precise interface detection and cutting.

Methods This study combines literature review and technical analysis to examine the methanol-gasoline batch transportation process and the formation and properties of the resulting transmix. This paper summarizes the fundamental principles and technical characteristics of established detection technologies (density-based, optical, ultrasonic, electrical, tracer labeling, and near-infrared spectroscopy) and advanced techniques (surface plasmon resonance and terahertz time-domain spectroscopy), and it compares their applicability to methanol-gasoline batch transportation. Multi-stage cutting methods (two- to five-stage) and requirements for online collaborative station control are discussed.

Results Compared with conventional batch transportation of refined petroleum products, properties of methanol-gasoline transmix are significantly more sensitive to water content, temperature, and gasoline composition, potentially exhibiting turbidity or partial phase separation. Density-based, optical, and ultrasonic methods possess sound engineering foundations. Near-infrared spectroscopy enables simultaneous monitoring of quality metrics and transmix concentration, representing a key direction for online detection. Three-stage cutting can serve as a basic scheme, whereas four- and five-stage cutting applies to stations with dedicated storage and downstream processing capacity.

Conclusion To address the interface detection and precision cutting challenges in methanol-gasoline batch transportation, we need to transition from single-property empirical methods to multi-parameter collaborative sensing, quality-metric verification, and intelligence-assisted cutting. Future research should establish a tailored evaluation system for methanol-gasoline interface detection while advancing multi-sensor fusion, online dynamic cutting, and station-level collaborative control, which will provide vital technical support for the safe, efficient, and cost-effective pipeline transportation of green methanol.