Determining aerosol type using a multichannel DustTrak DRX. (December 2018)

• Record Type: Journal Article
• Authors: Chang, Lisa Tzu-Chi; Leys, John; Heidenreich, Stephan; Koen, Terry
• Is Part Of: Journal of aerosol science. Volume 126(2018)
• Page Start: 68
• Page End: 84
• Publication Date: 2018-12
• Subjects: PM10 -- PM2.5 -- Particle characterization -- Air quality monitoring network -- DustTrak DRX; Aerosols -- Periodicals; Aerosols -- Periodicals; Aérosols -- Périodiques; 541.34515
• DOI: 10.1016/j.jaerosci.2018.08.009
• Languages: English
• ISSNs: 0021-8502

Abstract

Abstract: The aerosol monitoring provides air quality information to the community. Policy and community groups often want to know more than the level of mass concentration, that is, a description of what type of aerosols are being reported. There is a need to more objectively and efficiently, that is, in near real time, classify aerosols. Different instruments are used in different networks, raising the issue of comparability. In New South Wales, Australia, the Air Quality monitoring network uses Tapered Element Oscillating Microbalances (TEOM). The Community DustWatch network uses DustTrak® and subjectively classifies its data into dust, smoke and fog. To understand the instrument measurement differences and the aerosols types in Wagga Wagga (New South Wales, Australia), this paper compares paired continuous PM10 measurements from two instruments, the multi-channel DustTrak DRX model 8532 and the TEOM for the period of August 2011 to December 2014. The Reduced Major Axis (RMA) regression was conducted between TEOM PM10 measurements against subjectively classified DustTrak PM10 for different aerosol types. Two methods namely, a single variable DustTrak PM2.5 /PM10 ratio (DTPR) method and the Classification and Regression Trees (CART) method were developed to classify the aerosol type into dust, fog and smoke by their particle size distribution (PSD). Based on the thresholds proposed by a single variable DTPR method, the objective classification was conducted on DustTrak data and the RMA regression was rerun. The major finding is that the multi-channel DustTrak DRX model 8532 can be used to classify aerosol type by their average PSD at Wagga Wagga. The aerosol types were classified by two methods: 1) a single variable DTPR is proposed of ≤ 0.55 as a threshold for dust aerosol; 0.55 <DTPR ≤ 0.96 for smoke and DTPR of > 0.96 for fog. And 2) the CART analysis that uses two variables PM4–10 and DTPR. The initial cut-off of PM4–10 of < 0.95 µg/m 3 which separates fog from other aerosols, then the next cut point is for DTPR of < 0.53 which separates dust from smoke. The PM10 data measured with TEOM and DustTrak have a poor level of agreement no matter if we use the subjectively or objectively classified data. However, the DustTrak PM10 to the TEOM PM10 ratio improves from 0.38 to 0.76 with objectively classified dust data; the ratio of 0.98 gets closer to 1 with objectively classified smoke data; DustTrak PM10 higher by a factor of 2.4 with objectively classified fog data. We were not expecting a good relationship between the two instruments for fog due to the heated inlet on the TEOM. To improve the characterization of aerosol type in the current DustWatch network (or Rural Air Quality Network since 2018), instruments are suggested to be upgraded to multi-channel instruments. Highlights: Multi-channel DustTrak DRX was used to classify aerosol type objectively by their particle size distribution. DustTrak PM2.5 /PM10 ratio (DTPR) method and Classification and Regression Trees (CART) method were developed. DTPR is proposed of ≤ 0.55 as a threshold for dust aerosol; 0.55 <DTPR ≤ 0.96 for smoke and DTPR of > 0.96 for fog. CART uses initial cut-off of PM4–10 of < 0.95 µg/m 3 separates fog from others, then the DTPR of < 0.53 separates dust from smoke. The DustTrak DRX PM10 and TEOM PM10 ratio improved with objectively classified aerosol data.