# Intelligent Wearable Analyzer for Vapor Exposure (iWAVE) in Transportation Sector

> **NIH ALLCDC R01** · VIRGINIA POLYTECHNIC INST AND ST UNIV · 2022 · $623,010

## Abstract

Intelligent Wearable Analyzer for Vapor Exposure (iWAVE) in Transportation Sector
Exposure to hazardous air pollutants (HAPs) has been linked to a variety of health effects, such as cancer,
asthma, autism, reduced fertility, and lower intelligence. Development of effective strategies for reducing
occupational exposure to HAPs requires accurate, time-resolved measurement of exposure. Current practice
typically requires collection of a sample in the field using a canister or sorbent tube, transport to the lab, and
then application of gas chromatography with a detector to identify and quantify the species present in the
environment. A small, unobtrusive, wearable, direct-read device with 5-min time resolution for exposure
assessment would enhance worker exposure monitoring and advance our capabilities for exposure-response
epidemiologic study. The proposed project will employ microelectromechanical systems (MEMS) technology,
advanced microelectronics components and systems, and state-of-the-art micro gas chromatography (µGC)
and telecommunication techniques to develop an intelligent wearable analyzer for vapor exposure (iWAVE) for
use in the Transportation, Warehousing, and Utilities (TWU) sector and in others where workers are
exposed to similar chemical hazards (Exposure Assessment cross-sector). iWAVE allows to better assess
on a real-time basis the effects of workplace conditions and activities on HAP generation and subsequent
exposure. This capability has three major outcomes: (1) to allow identification of specific activities that are
associated with elevated exposures so that mitigation efforts might be applied most effectively; (2) to enable
greatly improved monitoring of personal occupational exposure in health effects studies; and (3) to provide a
platform for a real-time detection system that can alert workers to hazardous conditions. Three specific aims
for the proposed project are: 1) implementation and characterization of iWAVE MEMS modules including air
sampling, preconcentration, and injection (ASPI) and multi-dimensional separation and detection (GC Matrix or
GCM) modules, 2) iWAVE implementation and evaluation under simulated occupational environments, and 3)
iWAVE validation and utilization for exposure analysis in the transportation sector through the assistance of
Virginia Tech Transportation Institute (R2P). Thirty experienced heavy-vehicle workers performing diesel re-
fueling and maintenance tasks will wear both conventional industrial hygiene sampling trains and iWAVE for
breathing zone sample collection within a 0.4m radius of the nose/mouth. iWAVE superiority in terms of the
total analysis time (<5min) for HAP identification even in low-concentration (ppbv) environments will be
demonstrated. While focused on exposure monitoring, the scientific and technological impacts of this project
may extend to other applications if this research is accomplished successfully.

## Key facts

- **NIH application ID:** 10418601
- **Project number:** 5R01OH011350-04
- **Recipient organization:** VIRGINIA POLYTECHNIC INST AND ST UNIV
- **Principal Investigator:** Masoud Agah
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** ALLCDC
- **Fiscal year:** 2022
- **Award amount:** $623,010
- **Award type:** 5
- **Project period:** 2019-06-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10418601

## Citation

> US National Institutes of Health, RePORTER application 10418601, Intelligent Wearable Analyzer for Vapor Exposure (iWAVE) in Transportation Sector (5R01OH011350-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10418601. Licensed CC0.

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