Organic Aerosol Concentration, Composition, and Sources Analysis at Pretoria, South Africa Employing Fourier-transform Infrared Spectroscopy (FT-IR) and Positive Matrix Factorization (PMF)
MUHAMMAD NAVEED ANWAR, Satoshi Takahama, Christopher Oxford, Randall Martin, Adele L. Igel, Ann Dillner,
University of California, Davis Abstract Number: 229
Working Group: Source Apportionment
AbstractWorld Health Organization (WHO) estimates that about 91% global population live in polluted air – resulting in approximately 7 million premature deaths annually mostly attributed to Low and Middle Income Countries (LMICs). 98% LMICs’ cities, having population >100,000, are non-compliant to WHO air quality guidelines contrary to 56% cities in high income countries. Organic Matter (OM) often dominates PM2.5 mass, sometimes even up to 9/10th of total mass, warranting the need of its quantification particularly in LMICs having limited PM measurements. Unfortunately, the molecular complexity of OM makes quantification challenging and often requires expensive and time-consuming methods. In this study, we demonstrate the capability of Fourier-transform Infrared Spectroscopy (FT-IR) method for providing OM quantification and characterization as a sum of organic functional groups: alcohol, alkane, carbonyl, and carboxyl groups, in the Pretoria, South Africa at a Surface Particulate Matter Network (SPARTAN) site. South Africa falls in the category of LMICs and Pretoria has a 3.3 million population. Polytetrafluoroethylene (PTFE) filters (MTL Corp., PT25DMCAN-PF03A) used for gravimetric, black carbon, FT-IR, ionic and elemental analysis were collected with an AirPhoton SS5 Sampler over 24 hour intervals from April 2021 to April 2022 (71 samples). The mean concentration of PM2.5 was 16 ug/m3 with winter being the most polluted season with remaining seasons appearing in following order: autumn > spring > summer. We present the daily, seasonal, and overall variation of organic composition and OM/ PM2.5 ratios. Source classes and their geographical origins are determined through Positive Matrix Factorization (PMF) of inorganic and organic speciated data and back trajectory analysis. In the future, using the knowledge about these sources and their locations, the appropriate policy measures will be proposed to curb PM2.5 pollution at Pretoria considering the ground based limiting factors and existing mitigation policies.