Secondary organic carbon (SOC) estimation using several indirect techniques and the evaluation of their uncertainties

Knowledge of the relative contribution of primary and secondary organic aerosol fractions is important in formulating effective control measurements for ambient particulate matter (PM), and the main part of Organic Aerosol (OA) in urban and rural atmospheres is found to be of secondary origin. However, its exact contribution still remains uncertain despite intensive efforts undertaken during the last decades to characterize and understand the chemistry leading to Secondary Organic Aerosol (SOA). Indeed, there is still no direct way to separate secondary to primary organic aerosol fractions. Quantification of Secondary Organic Carbon (SOC) is furthermore difficult because of our limited understanding of the molecular composition of SOC and because of the presence of a large, but unknown, number of secondary organic products. This study has been purposely carried out to estimate the contribution of SOC fraction to OA content, by using various semi-direct and indirect methodologies and evaluate associated uncertainties involved in the following outcomes. Measurements were conducted at SIRTA-LSCE, a well arranged atmospheric site in the vicinity of Paris (France), over a period from 6 to 24 March 2015. This was accomplished by utilizing information obtained from intensive filter measurements conducted at every 4 hours. SOC estimations were proposed using Positive Matrix Factorization applied to Aerosol Chemical Speciation Monitor (ACSM) measurements as well as using off-line data analyses, such as EC-, WSOC-, and SOA tracer-based methods. Results might also assert the photochemical origin of SOA, although the relative contribution to the OC and the SOA formation may differ during the chosen period. Large discrepancies were accounted for in the SOC estimations furnished using different techniques. Results imply that cautions should be taken while estimating SOC. Discussion will lead to profound information about the limitations and challenges associated to SOC estimations using different techniques.