Analysis of black carbon on filters by image-based reflectance. (15th February 2020)

• Record Type: Journal Article
• Authors: Jeronimo, Matthew; Stewart, Quinn; Weakley, Andrew T.; Giacomo, Jason; Zhang, Xiaolu; Hyslop, Nicole; Dillner, Ann M.; Shupler, Matthew; Brauer, Michael
• Is Part Of: Atmospheric environment. Volume 223(2020)
• Publication Date: 2020-02-15
• Subjects: Black carbon -- Particulate matter -- Optical methods -- Reflectance measurement -- Rapid analysis; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2020.117300
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: Black carbon (BC) is an important contributor to global particulate matter emissions. BC is associated with adverse health effects, and an important short-lived climate pollutant. Here, we describe a low cost method of analysis that utilizes images of PTFE filters taken with a digital camera to estimate BC content on filters. This method is compared with two existing optical methods for analyzing BC (Smokestain Reflectance and Hybrid Integrating Plate and Sphere System) as well as the standard chemical analysis method for determining elemental carbon (Thermal-Optical Reflectance). In comparisons of aerosol generated under controlled conditions (using an inverted diffusion flame burner to cover a range of mass loading and reflectance levels) (N = 12) and in field samples collected from residential solid fuel combustion in China and India (N = 50), the image-based method was found to correlate well (normalized RMSE <10% for all comparisons) with existing methods. A correlational analysis of field samples between the optical methods and Fourier-transform infrared spectroscopy indicated that the same functional groups were predominantly responsible for light attenuation in each optical method. This method offers reduced equipment cost, rapid analysis time, and is available at no cost, which may facilitate more measurement of BC where PM2.5 mass concentrations are already measured, especially in low income countries or other sampling efforts with limited resources. Highlights: Current black carbon analysis techniques are expensive, destructive, or time-consuming. Image-based reflectance is a viable solution for on-site resource-limited sampling efforts. A digital camera was used to assess black carbon on filters.