High-Throughput Semiquantitative Screening of Ambient Air Samples by ORS-ICP-MS and Integrated Sample Introduction System (ISIS)

Importance of the Topic

High-throughput semiquantitative screening of trace metals in ambient air is essential for environmental compliance, pollution source identification, and rapid risk assessment. Traditional semiquantitative ICP-MS workflows face challenges from polyatomic interferences, limited calibration flexibility, and long sample cycle times. A streamlined method capable of analyzing thousands of samples with minimal matrix knowledge and without extensive calibration reduces time and cost in large-scale air quality surveys.

Objectives and Study Overview

The primary objective was to implement a rapid semiquantitative ICP-MS method using an Agilent 7500c with an octopole reaction system operating in helium collision mode and an integrated sample introduction system. The study targeted the analysis of 2,500 wet-collector air samples in under one month, generating both dissolved and extractable element data. Key goals included maximizing sample throughput, ensuring acceptable data quality via NIST standard reference material checks, and minimizing analysis cycle times through custom ISIS programming.

Methodology

The semiquantitative ICP-MS approach scanned the full mass range in 40 s per analysis under uniform conditions to allow interpolation of response factors. Helium collision mode reduced most polyatomic interferences without generating new ones. Air samples were collected at 450 L/min using a SpinCon Advanced Air Sampler directly into 10 mL of proprietary solution. Each sample yielded two fractions:

• Dissolved element fraction: centrifuged supernatant diluted into 1 % HNO₃.
• Extractable element fraction: treated with reagents, shaken 10 min, diluted and centrifuged.

Custom ISIS stream-selection programming eliminated delays associated with pump tubing stabilization and spray-chamber rinse, reducing the total cycle time to approximately 70 s per sample versus 120 s with standard high-throughput setups. Automated macros exported results for statistical analysis.

Used Instrumentation

• Agilent 7500c ORS-ICP-MS with octopole reaction system in He collision mode
• Agilent Integrated Sample Introduction System with stream-selection configuration
• SpinCon Advanced Air Sampler (wet concentrator)
• CETAC ASX-510 autosampler
• Cyclonic spray chamber

Main Results and Discussion

NIST SRM 1643e (10× dilution) was analyzed 72 times, yielding recoveries of 81–110 % and RSDs below 25 % across low to high-abundance elements. The optimized stream-selection ISIS reduced signal stabilization to ~20 s and achieved 10³ signal reduction in ~20 s rinse, enabling ~540 samples per 8 h shift. Over ~10 days, 2,500 ambient air samples (5,000 analyses) were completed. Major mineral elements (Na, K, Ca, Mg) accounted for >98 % of total composition, while urban particulate tracers (Al, Fe, Zn) appeared at moderate to high levels. Extractable fractions consistently showed higher metal concentrations than dissolved fractions due to particulate release.

Benefits and Practical Applications

• Enables large-scale air quality surveys with unknown matrices without extensive calibration
• Improves laboratory efficiency by reducing per-sample analysis time by ~40 %
• Maintains data quality suitable for screening via NIST CRM recoveries and RSDs
• Applicable to urban environmental monitoring, emergency response, and regulatory screening

Future Trends and Potential Applications

Future developments may integrate advanced autosamplers and robotics for unattended operation, incorporate machine-learning algorithms for pattern recognition in semiquantitative datasets, extend the methodology to fully quantitative analyses using novel cell technologies, and adapt portable or field-deployable ICP-MS platforms for on-site ambient air screening.

Conclusion

The combined use of semiquantitative ORS-ICP-MS in helium collision mode and a custom stream-selection ISIS program provides a rapid, reliable screening tool for trace metal analysis of ambient air samples. The method achieved project goals of high throughput and acceptable data quality in an automated workflow, demonstrating its utility in large-scale environmental surveys.