Headspace (HS) colorimetric sensing is rapidly emerging as a practical alternative for determining volatile and semi-volatile compounds, combining gas-phase isolation with simple visual or smartphone-based readout to deliver fast, low-cost, and matrix-resistant analysis. This review synthesizes recent progress in the field over the past seven years (2019-2025), highlighting how innovations in chromogenic reagents, nano-enabled transducers, paper and microfluidic architectures, and digital image analysis have transformed HS colorimetry from qualitative vapor indicators into quantitative, application-ready platforms. We organize recent work through a unified methodological lens, showing how tailored HS sampling modes-static exposure, purge-and-trap enrichment, microdrop extraction, and chemical vapor/hydride generation-are strategically paired with selective dyes or cross-reactive arrays to tackle targets spanning food aroma and spoilage markers, inorganic gases, toxic metals/metalloids, and hybrid analyte systems. Beyond summarizing representative devices, the review distills the key design principles that govern successful HS-colorimetric performance and compares how different platforms achieve sensitivity, selectivity, and portability in real samples. We also critically discuss the main bottlenecks that still shape the field, and conclude with future perspectives for next-generation HS-colorimetric technologies aimed at improving robustness, scalability, and field deployment across food quality control, environmental monitoring, and point-of-care diagnostics.
El-tahlawy et al. (Sun,) studied this question.