Grantee Research Project Results

VOC Sensors for ppb-level Detection and Speciation

EPA Grant Number: SU840167
Title: VOC Sensors for ppb-level Detection and Speciation
Investigators: Presto, Albert
Institution: Carnegie Mellon University
EPA Project Officer: Page, Angela
Phase: I
Project Period: December 1, 2020 through November 30, 2021
Project Amount: $25,000
RFA: P3 Awards: A National Student Design Competition Focusing on People, Prosperity and the Planet (2020) RFA Text |  Recipients Lists
Research Category: P3 Awards , P3 Challenge Area - Air Quality

Description:

• The goal of this proposal is to develop a reliable and cost-effective VOC sensor suite for ambient and residential deployment with rough speciation, which will enable human exposure estimation and benefit pollution control. Five metal oxide semiconductor sensors, one electrochemical sensor, and two photoionization detectors will be combined as a sensor suite. Taking advantage of their different selectivity, numerical algorithms and machine learning algorithms will be established from laboratory and field calibration data to realize ppb-level detection and rough speciation. The developed sensor suites will be deployed indoors and outdoors to evaluate their performance. The purpose of this project is to reduce human exposure and VOC emissions, which is closely related to the P3 goals. Such portable and cost-effective personal devices will be useful tools to help people identify VOC emission sources and be aware of surrounded air pollution. This sensor suite will be especially beneficial to rural and disadvantaged communities who have limited access to public resources.

Objective:

Volatile organic compounds (VOCs) have significant harmful effects on human health and the environment. Exposure-driven measurements are essential to quantify the harmful impact of VOCs. Current VOC measurement techniques are expensive and complicated, leading to a lack of sufficient monitoring stations, which prohibits exposure-driven measurements. A low-cost and portable sampling technique that can be deployed indoors will be favored for exposure-driven measurements. Low-cost VOC sensors suggest a promising future to provide additional and complementary information to conventional VOC measurement techniques. Although these sensors have been widely used for industrial purposes, there are limited studies deploying these sensors for residential or ambient measurement because of a high limit of detection (LOD) and non-selectivity. LOD can be decreased by signal conditioning and advanced calibration algorithms. The non-selectivity can be addressed by synergizing the results from multiple VOC sensors. In our preliminary study, VOC sensors operating on different working principles responded differently to the same pollution event, which is likely due to their different selectivity. Hence, we plan to fabricate a suite of VOC sensors and establish an advanced algorithm, aiming to realize ppb-level measurement with rough speciation. The ppb-level detection can ensure robust measurements for ambient concentrations and residential exposures. Rough speciation can identify groups of compounds (e.g., BTEX) that are more impactful to human health, and therefore benefit future epidemiological studies. 

Expected Results:

• Unlike other particulate and gas sensors whose functionality has been tested in field measurements, research into low-cost VOC sensors is still mainly focused on laboratory and field calibration. The high LOD and non-selectivity are large concerns that hamper the application of low-cost VOC sensors. In this work, we will address these two problems at the same time, aiming for a practical VOC sensor suite that can be used indoors and outdoors. From this work, we will design a reliable and cost-effective VOC sensor suite with ppb-level LOD and rough speciation function. The LOD will be extended to ppb-level, which enables ambient and residential measurements. The rough speciation feature can identify groups of compounds harmful to human health (e.g., BTEX) and environments (e.g., biogenic VOCs). Distinguishing these compounds can provide more reliable data for analyzing the environmental and health impacts of VOCs. The developed VOC sensor suites will be readily integrated into our existing network of Real-Time Multi-Pollutant Sensors (RAMP) monitors to provide a comprehensive air quality measurement, including PM_2.5, O₃, CO, CO₂, SO₂, NO_x, and VOC concentrations.

Supplemental Keywords:

Low-cost VOC sensor, ambient and residential measurement, speciation, air pollution control

Progress and Final Reports:

Final Report