SIFT-MS: Comprehensive, Real-time Fenceline Monitoring of Volatile Pollutants

Volatile organic compounds (VOCs) are implicated in the formation of ozone and secondary organic aerosols (SOAs). Some of these VOCs are toxic and can cause nuisance odors, impacting human health, quality of life, and the environment. The chemical production industry is a significant source of VOC pollution and ensuring that emissions are minimized is crucial, as well as the ability to trace these events back to the responsible facility. Tracing the pollutant back to its source can be non-trivial in large industrial complexes.

Conventional analytical approaches for monitoring industrial emissions at the fenceline include time-averaged, automated thermal desorption-gas chromatography–flame ionization detection (TD-GC–FID) and grab sampling (using bags or canisters) followed by laboratory-based gas chromatography–mass spectrometry (GC–MS) analysis. These, however, are impractical for detecting and responding to transient pollution events in a timely manner (1).

In contrast, selected ion flow tube mass spectrometry (SIFT-MS) is a laboratory-grade analytical technique that analyzes air directly and continuously with high specificity and sensitivity for a wide range of VOCs. SIFT-MS combines the required analytical performance with robustness that enables the instrumentation to be rapidly deployed during a pollution event, in addition to routine fenceline monitoring (for example, in an air monitoring shed). VOC data can even be acquired spatially with the instrument operating in a moving mobile laboratory, enabling detection of pollution hot spots in real time.

This article provides an overview of the enhanced fenceline monitoring that mobile SIFT-MS laboratories provide on-site, especially when coupled with drone sampling to identify pollution sources. Figure 1 summarizes workflows for both characterizing pollutant distribution at an industrial complex and effectively responding to pollution incidents. The sections below highlight the synergistic benefits of using mobile SIFT-MS laboratories and drone sampling.

Instrumentation

The SIFT-MS Technique: SIFT‑MS directly analyzes air by using soft chemical ionization (CI) to generate mass-selected reagent ions (2) that can rapidly react with and quantify VOCs down to part-per-trillion concentrations (by volume, pptV). Up to eight reagent ions (H₃O⁺, NO⁺, O₂⁺, O⁻, OH⁻, O₂⁻, NO₂⁻, and NO₃⁻) obtained from a microwave discharge in air are applied in modern SIFT-MS instruments (2). These reagent ions react with VOCs and other trace analytes in well-controlled ion‑molecule reactions, but they do not react with the major components of air (N₂, O₂, and Ar). This enables direct, real‑time analysis of air samples to be achieved at trace and ultra-trace levels without pre-concentration. Real‑time switching between reagent ions with no hardware change provides high selectivity because the multiple reaction mechanisms give independent measurements of each analyte (Figure 2). The use of multiple reagent ion-product ion pairs in real-time data acquisition frequently resolves isobaric overlaps due to different ionization mechanisms (3). Analytical results compare well with GC (3,4).

Mobile SIFT-MS Laboratory:A typical mobile SIFT-MS laboratory comprises: (i) a suitable van with modified electrical system to power the instrumentation and air conditioning, (ii) a SIFT-MS instrument operating on nitrogen carrier gas, (iii) a supply of carrier gas and calibration standard, (iv) a sample inlet system configured for flow-past sampling at the SIFT-MS instrument (which samples at 25 standard cubic centimeters per minute; sccm),(v) a weather measurement system, (vi) a global positioning system (GPS), (vii) a cellular internet connection for continuous streaming of data, and (viii) mapping software that integrates SIFT-MS, position, and weather data (5). With this integrated, real-time measurement and reporting system, instant detection of pollution events enables instant decisions to be made by remote management or field operators, as appropriate.

Drone Sampling:A commercial drone with associated sampler for filling gas sample bags is commonly utilized to “grab” air samples at low altitude and at a short distance from the mobile laboratory. This greatly simplifies sampling of suspected pollution sources such as industrial stacks. Inflight detection of air containing elevated VOC concentrations is achieved with user-selectable sensors. Data can be monitored in real time through communication with ground receivers, and sample collection triggered (into the sample bag) if elevated concentrations are detected. The filled sample bag is analyzed immediately at the collection location using the mobile SIFT‑MS laboratory. On-site SIFT-MS analysis eliminates sample degradation and gives immediate, quantitative feedback on pollutants.

Fenceline Monitoring

Conventional fenceline monitoring typically has either a field-based analyzer or samplers (such as thermal desorption tubes or canisters) deployed at fixed locations on the boundary. For the latter, samplers are analyzed offline at a laboratory using GC–FID or GC–MS. For VOCs, conventional approaches are typically time-averaged from one hour to a day, week, or month, making it difficult to capture transient pollution incidents.

Alternatively, utilization of direct, real-time SIFT-MS analysis enables immediate incident detection with high selectivity, facilitating effective resolution of the cause of pollution. Although SIFT-MS instruments are readily installed in traditional air monitoring sheds (Figure 2), the mobile SIFT-MS laboratory provides greater flexibility both in routine monitoring—since anywhere on the boundary can become a monitoring point—and for rapid incident response. This application, and the related ambient monitoring application has been widely used in South Korea (1), as well as in China (6), Vietnam (7), and the UK (8).

Spatial Mapping

The durability of modern SIFT-MS instruments enables them to be operated in a mobile laboratory while the vehicle is moving, supporting spatial mapping of VOCs. This provides a deeper understanding of the variation in pollutant concentrations across a geographic area and reveals hotspots that can be investigated in more detail using fenceline monitoring.

Figure 3 shows benzene, toluene, ethanol, and NO₂ measurements made by researchers from the Wolfson Atmospheric Chemistry Laboratory (WACL; University of York) along a measurement route in York, United Kingdom (9). Higher concentrations of pollutants were measured in the city center (top left) compared to the more suburban areas at bottom right.

Identification of Pollution Sources Using Drones and SIFT-MS

Volatile pollutants from industry can disperse far beyond the fenceline, but their landing distance depends on the height of the emission source, ambient temperature and pressure, and wind direction. Drones can simplify identification of pollution sources, but because of the transient nature of pollution incidents this is generally efficient only once the “hot spot” has been identified, whether following a complaint or detection during routine monitoring. Within the “hot spot,” the drone can move from plume to plume until high total VOC readings are detected using the onboard sensor. Sampling into the bag can be triggered and the collected sample brought to
the mobile SIFT-MS laboratory for immediate on-site analysis. If required, the drone can resample the plume for subsequent regulatory analysis at an accredited laboratory. In the meantime, practical steps can be taken by the company responsible to mitigate pollutant release.

The combined approach utilizing mobile SIFT-MS laboratories and drone sampling has been pioneered by South Korea (1). For example, Shin et al. (10) investigated suspected emission sources at nine “hot spots” in the Banwol National Industrial Complex in Ansan, South Korea. Three areas (1, 2, and 3) with higher pollutant concentrations were subjected to a more intensive survey, followed by drone sampling to identify pollutants in very defined spots (A, B, C) within area 1, 2, and 3. Figure 4 shows comparative results obtained for fenceline and drone sampling, with concentrations of toluene, xylene, hydrogen sulfide, and methyl ethyl ketone much higher than background measurements at these sites. Based on the general agreement between the fenceline and drone samples, Shin et al. (10) concluded that the use of drone and real-time SIFT-MS monitoring enables rapid identification of pollutant sources.

Conclusion

SIFT-MS is an orthogonal technique to regulatory methods that use GC, providing real-time, onsite, laboratory‑grade analysis of air pollutants. In South Korea these benefits, together with drone sampling, have led to SIFT-MS finding widespread application in air pollution monitoring, from the fenceline to incident response (1). Integrated with location and meteorological measurement technologies for real-time data reporting, SIFT-MS complements incumbent global regulatory methods by being able to address pollution events more rapidly, supporting improved human and environmental health.

Acknowledgment

We gratefully acknowledge Dr Shin and his colleagues for permission to reproduce Figure 4.

References

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Vaughan Langford is senior principal scientist at Syft Technologies in New Zealand. He joined Syft in late 2002 after completing his PhD in physical chemistry at the University of Canterbury, and post-doctoral fellowships at the Universities of Geneva, Western Australia, and Canterbury. He has 43 peer-reviewed publications on a wide range of SIFT-MS applications, and is co-author of the textbook SIFT-MS: From Method Concept to Routine Analysis, published in 2025.

Leslie Silva is applications team lead at Syft Technologies, Inc. in the USA. She joined Syft in 2020 after completing her PhD in biochemistry and molecular biology at the University of Calgary, a postdoctoral fellowship at MD Anderson Cancer Center, and research positions at Lawrence Berkeley National Laboratory and a food and beverage start-up, Endless West. She has 23 peer-reviewed publications and numerous patents, application notes, and conference papers.