Use of a gas chromatography-mass spectrometry organic aerosol monitor for in-field detection of fine particulate organic compounds in source apportionment

Formation of secondary organic material from gaseous precursors in wood smoke

The apportionment of the contribution of wood smoke emitted particles to the total concentration of particulate matter in a region has been greatly aided by the development of new analytical methods. These analytical methods quantitatively determine organic marker compounds unique to wood combustion such as levoglucosan and dehydroabietic acid. These markers have generally been determined in 24-hour averaged samples. We have developed an instrument based on the collection of particles on an inert filter, desorption of the organic material in an inert atmosphere with subsequent GC separation and MS detection of the desorbed compounds. The GC-MS Organic Aerosol Monitor (OAM) instrument has been used in three field studies. An unexpected finding from these studies was the quantification of the contribution of secondary organic aerosols from gases present in wood smoke in addition to primary wood smoke emitted particles. The identification of this secondary material was made possible by the collection of hourly averaged data that allowed for the time patterns of black carbon, organic material, and wood smoke marker compounds to be included and compared in a Positive Matrix Factorization (PMF) analysis. Most of the organic markers associated with wood smoke (levoglucosan, stearic acid and dehydroabietic acid) are associated with primary wood smoke emissions, but a fraction of the levoglucosan and stearic acid are also associated with secondary organic material formed from gaseous precursors in wood smoke. Additionally, this secondary material was shown to be present in each in of the three urban area where wood smoke burning occurs. There is a need for additional studies to better understand the contribution of secondary particulate formation from both urban and wildfires.Implications: This paper presents results from three field studies which show that in addition to the formation of primary particulate matter from the combustion of wood smoke and secondary particulate matter is also formed from the gaseous compounds emitted with the wood smoke. This material is identified in the studies of wood combustion reported here by the identification and quantification of specific organic marker compounds related to wood combustion and is shown to and represents a contributor nearly as large as the primary emitted material and better quantifying the impact of wood combustion on airborne fine particulate matter.

Apportionment of PM2.5 adjacent to the I-710 Harbor Freeway in Long Beach, CA

During August and September 2012, a study was conducted to determine the sources of PM2.5 adjacent to the I-710 Long Beach Freeway. The site is directly affected by the emissions from heavy diesel traffic flowing from major container ports about 10 km south of the sampling site. Hourly average data were obtained for particulate species including PM2.5, black carbon and UV absorbing carbon, EC, fine particulate nonvolatile and semi-volatile organic material (NVOM and SVOM), sulfate, nitrate, chloride, ammonium ion, and Na ion, and for related factors including O3, CO, NOX, SO2, and total traffic flow on the I-710. A total of 520 hourly averaged data sets with 15 measured variables were analyzed by EPA-PMF v5.0. The data were best described by a 10-factor solution. Based on the composition and diurnal patterns of the factors, they were assigned to three diesel-related factors (two of which appeared to represent traffic from the ports and one general freeway diesel factor), a light-duty, spark-ignition vehicle-related factor, three secondary factors (one of which was associated with O3 formation processes), and three factors dominated by sulfate, SO2, and chloride, respectively. The diurnal patterns for these last three factors are strongly correlated. Meteorological and refinery upset data indicate that they are associated with emissions from a nearby refinery. The results of the PMF analysis were combined with nephelometer light scattering, corrected for coarse particle scattering and estimated aerosol water content in a multilinear regression analysis to identify visibility degradation sources. Major contributors were the aerosol water content, and the secondary PMF factors associated with either Nitrate and NVOM or NVOM and SVOM. The use of hourly average data made possible the identification of factors associated with gasoline vehicle emissions and both port and non-port diesel emissions.Implications: Hourly averaged data were obtained for PM_2.5, its components and factors related to primary emissions and the formation of secondary material at a near freeway sampling location adjacent to the I-710 freeway just south of the Long Beach Boulevard entrance and 10 km north of the Ports of Long Beach and Los Angeles. The major objective of the study was to determine the impact of traffic from the ports at the monitoring site. This manuscript reports on the PMF analysis of the data set. Factors related to both diesel traffic originating from the ports and diesel traffic from non-port origins were identified. The diesel traffic originating from the ports was responsible for 9% of the total traffic and 95% of the BC measured at the sampling site. The non-port diesel traffic was responsible for 15% of the total traffic and 5% of the BC. While the Port 1 diesel traffic coming from the ports contributed a large fraction of the BC, this source contributed only 2% of the CO and 5% of the NO_X at the sampling site. The impact of these traffic sources on light scattering was also small. Analysis of sources of sulfate and SO₂ at the sampling site indicated that these species did not come from port activities of ships at or approaching the port, but rather from upset flare events at a nearby oil refinery.

Mid-infrared supercontinuum-based upconversion detection for trace gas sensing

Recent advancements of mid-infrared (MIR) supercontinuum light sources have opened up new possibilities in laser-based trace gas sensing. While the supercontinuum sources inherently support wide spectral coverage, the detection of broadband absorption signals with high speed and low cost is traditionally limited by the MIR detector arrays. In this work, we demonstrate that this limitation can be circumvented by upconverting the MIR signal into the near-infrared (NIR) region, where cost-effective silicon-based detector arrays can be utilized to measure broadband absorption. We also show that, by combining a MIR supercontinuum source with a MIR-to-NIR upconverter and an astigmatic multipass cell, fast detection (~20 ms) of ethane with sub-ppmv sensitivity can be achieved at room temperature. For multi-species detection, a least-square global fitting method is presented, showing a promising potential for applications such as environmental monitoring and biomedical research.

A Broadband Mid-Infrared Trace Gas Sensor Using Supercontinuum Light Source: Applications for Real-Time Quality Control for Fruit Storage

We present a fully integrated and transportable multi-species trace gas sensor based on a mid-infrared (MIR) supercontinuum light source. The high brightness (surpassing synchrotron) and ultra-broad spectral bandwidth (2-4 μm) of this light source allows simultaneous detection of multiple broadband absorbing gas species. High sensitivity in the sub-ppmv level has been achieved by utilizing an astigmatic multipass cell. A grating-based spectrometer at a scanning rate of 20 Hz is developed employing a balanced detection scheme. A multi-component global fitting algorithm is implemented into a central LabVIEW program to perform real-time data analysis. The obtained concentration values are validated by the standard gas chromatography mass spectrometry (GC-MS) method. Field application of the sensor for quality control of stored fruits at a small scale is demonstrated, involving the detection of ethylene, ethanol, ethyl acetate, acetaldehyde, methanol, acetone, and water simultaneously. The sensor also shows promising potentials for other applications, such as environmental monitoring and biomedical research.