Compact Multi-Pollutant Mid-Infrared Laser Spectroscopic Trace-Gas SensorEPA Grant Number: R835137
Title: Compact Multi-Pollutant Mid-Infrared Laser Spectroscopic Trace-Gas Sensor
Investigators: Wysocki, Gerard
Institution: Princeton University
EPA Project Officer: Chung, Serena
Project Period: February 1, 2012 through January 31, 2016
Project Amount: $250,000
RFA: Developing the Next Generation of Air Quality Measurement Technology (2011) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Air
Sensing of airborne chemicals is of importance in a number of atmospheric monitoring applications and will play a major role in further improvement of emissions inventories. Recent studies indicate that industrial emissions may be 10-20 times greater than the amount estimated using current standard emission factors. Development of new, sensitive, multi-species sensing technologies, which can be configured into wireless sensor networks to create dynamic pollutant maps, identify emission sources and measure the actual emission rates, is a critical step towards improvement of the emission control and monitoring.
Laser technology offers a unique set of capabilities that enable ultra-sensitive and selective chemical detection in a compact and power-efficient instrument. Most chemical compounds in gas phase (including volatile organic compounds, or hydrocarbons) have their strongest fundamental ro-vibrational absorption features in the mid-infrared spectral region (~3-16 μm). This strong molecular fingerprint makes this part of electromagnetic spectrum ideal for measuring numerous gases with the highest sensitivities. In this project we focus on development of a new, compact, sensor node for spectroscopic chemical sensing of multiple compounds. Two major innovations are proposed: 1) Multicomponent chemical analysis will be enabled thorough application of novel mid-IR widely tunable excternal cavity quantum cascade lasers with mode-hop-free high resolution wavelength tuning capability, and 2) ultracompact broadband sensor system will be developed as a compact wireless sensor node suitable for deployments in large-area wireless sensor networks. The new technology will provide significant improvements with respect to methods currently used by providing agile detection of multiple compounds in vapor phase including those with broad absorption features while enabling sensor network deployments.
Detection of Benzene, one of the highly toxic (carcinogenic) atmospheric pollutants, will be the main focus of this project. At the current stage of laser technology the absorption feature of Benzene at 9.63μm (1038cm-1) is optimal for laser spectroscopic sensing in the atmosphere. This is the only absorption band located within so called atmospheric transparency spectral window with a minimum interference from other atmospheric constituents e.g. water vapor. The proposed sensor node will operate at center frequency of 1038 cm-1 with a total tuning range of >150cm-1. The high resolution broadband spectral scan capable of resolving the entire (>50cm-1 wide) spectral feature of Benzene will assure high detection specificity. Ultimately the proposed system will enable detection of multiple compounds including those with overlapped broad absorption bands. Within the target spectral range, simultaneous monitoring of multiple molecules (including important emission targets: butadiene, ammonia, ozone or ethylene) with sensitivities relevant to emission inventorying and pollution prevention will be enabled. As a proof-of-concept for multispecies detection, sensing of ammonia will be performed and fully characterized. This secondary molecular target, that is a small molecule with well resolved spectral lines, will serve as an example of high-resolution spectroscopic sensing capabilities of the developed detection system. The proposed sensor node with capability of multiple chemical species detection in a wireless sensor network configuration is expected to have significant impact on improvement of the spatial and temporal coverage of air pollution measurement data as requested in the project solicitation.