Estimation Of Secondary Organic Carbon Research Articles

Molecular characteristics, sources and influencing factors of isoprene and monoterpenes secondary organic aerosol tracers in the marine atmosphere over the Arctic Ocean

Biogenic secondary organic aerosols (BSOA) are important components of the remote marine atmosphere. However, the response of BSOA changes to sea ice reduction over the Arctic Ocean remains unclear. Here we investigated isoprene and monoterpenes secondary organic aerosol (SOAI and SOAM) tracers in three years of summer aerosol samples collected from the Arctic Ocean atmosphere. The results indicated that methyltetrols were the most abundant SOAI tracers, while the main oxidation products of monoterpenes varied over the years owing to different aerosol aging. The results of the principal component analysis (PCA)-generalized additive model (GAM) combined with correlation analysis suggested that SOAI tracers were mainly generated by the oxidation of isoprene from marine emissions, while SOAM tracers were probably more influenced by terrestrial transport. Estimation of secondary organic carbon (SOC) indicated that monoterpenes oxidation contributed more than isoprene and that sea ice changes had a relatively small effect on biogenic SOC concentration levels. Our study quantified the contribution of influencing factors to the atmospheric concentration of BSOA tracers in the Arctic Ocean, and showed that there were differences in the sources of precursors for different BSOA. Hence, our findings have contributed to a better understanding of the characteristics, sources and formation of SOA in the atmosphere of the Arctic Ocean.

Validation of SOC Estimation Using OC and EC Concentration in PM2.5 Measured at Seoul

The organic carbon in the ambient particulate matter (PM) is divided into primary organic carbon (POC) and secondary organic carbon (SOC) by their formation way. To regulate PM effectively, the estimation of the amount of POC and SOC separately is one of the important consideration. Since SOC cannot be measured directly, previous studies have evaluated the determination of SOC by the Elemental Carbon (EC) tracer method. The EC tracer method is a method of estimating the SOC value from calculating the POC by determining (OC/EC)pri which is the ratio of the measured values of OC and EC from the primary combustion source. In this study, three different approaches were applied to OC and EC concentrations in PM2.5 measured at Seoul for determining (OC/EC)pri: 1) the minimum value of OC/EC ratio during the measurement period; 2) regression analysis of OC vs. EC to select the lower 5-20% OC/EC ratio; 3) determining the OC/EC ratio which has lowest correlation coefficient value (R2) between EC and SOC which is reported as minimum R squared method (MRS). Each (OC/EC)pri ratio of three approaches are 0.35, 1.34, and 1.77, respectively from the 1-h data. We compared the (OC/EC)pri ratio from 1-h data with 24-h data and revealed that (OC/EC)pri estimated from 24-h data had twice larger than 1-h data due to the low time resolution of sampling. We finally confirmed that the most appropriate value of (OC/EC)pri is that calculated by a regression analysis of 1-h data and estimated SOC values at PM2.5 of the Seoul atmosphere.

Two-year record of carbonaceous fraction in ambient PM2.5 over a forested location in central India: temporal characteristics and estimation of secondary organic carbon

Fine particles (PM2.5), collected on multiple filter substrates, were measured over Van Vihar National Park in Bhopal, central India, for 2 years (01 January 2012–31 December 2013). A thermal-optical carbon analyser (DRI 2001A) was used to measure carbon fractions on punches of quartz fibre filters. Total carbon contributed 38% to PM2.5 mass, of which pyrolysis corrected OC and EC contributed 27% and 11%, respectively. The seasonal averages of OC during the study duration were 22.5 ± 12.3 μg m−3 (post-monsoon) > 20 ± 12.3 μg m−3 (winter) > 8.3 ± 5.6 μg m−3 (pre-monsoon) > 6.4 ± 4.0 μg m−3 (monsoon). Daytime and nighttime OC and EC concentrations were not statistically different from one another, suggesting that local sources like traffic and diurnal meteorology driven effects did not influence these concentrations much. The value of mean OC/EC ratio was 4.2 ± 3.3 during the study period and was highest (6.1 ± 3.4) during the monsoon season. OC and EC concentrations were strongly correlated (r = 0.9), suggesting common primary sources for these species. SOC (secondary organic carbon) estimated by the EC tracer method constituted 31% of the total OC mass. Although SOC concentrations were low during the monsoons, its contribution to OC was maximum during this season (41% and 53% on average during 2012 and 2013, respectively), suggesting aqueous phase heterogeneous processing of SOC. Meteorological parameters and SOC exhibited no association, while only a weak correlation was observed between SO42− and SOC (r = 0.36), providing no clear indication on the likely role of SO42−-catalysed SOC formation.

Evaluation of factors influencing secondary organic carbon (SOC) estimation by CO and EC tracer methods

Secondary organic carbon (SOC) is known to account for a substantial fraction of fine-mode carbonaceous aerosol. Owing to a limited understanding of SOC formation processes and the absence of direct measurement methods, SOC concentrations are mostly estimated using a tracer-based method utilizing either elemental carbon (EC) or carbon monoxide (CO) as tracers. The performance of these tracer-based methods depends heavily on accurate determination of the (OC/Tracer)pri value. The minimum R squared (MRS) method is currently recognized as a relatively reasonable tool to determine (OC/Tracer)pri. This study estimated SOC based on the MRS method with EC and CO as tracers, followed by the Monte Carlo method to analyze quantitatively the effects of measurement uncertainty, emission scenario and sample size on SOC estimates. We report here four major findings: i) the concentration of O3 was used as an indicator to atmospheric secondary reaction potential, and it was found that the mass proportion of SOC in total OC estimated by CO as the tracer is more consistent with the seasonality of actual secondary reaction potential; ii) the estimation results are highly sensitive to the measurement uncertainty in different emission scenarios, which leads us to conclude that the CO tracer method is more robust than the EC tracer method due to large inherent uncertainties in current EC measurements; iii) oversimplification of emission scenarios has substantial impacts on the estimated SOC value, and careful evaluation of the interdependence between sources should be performed to minimize this bias; and iv) the estimation bias of SOC can be reduced by increasing the sample size, and the tracer method can be expected to generate robust results for sample sizes over 1000. These findings are important in terms of providing a reference to choose appropriate tracers, emission scenarios and sample sizes for robust estimation of SOC in future studies.

Estimation and Uncertainty Analysis of Secondary Organic Carbon Using 1 Year of Hourly Organic and Elemental Carbon Data

AbstractHourly particulate matter 2.5 organic carbon (OC) and elemental carbon (EC) ambient concentrations were measured from February 2012 to January 2013 at a suburban site in the city of Guangzhou, China. The major primary OC and EC sources at this site are vehicular exhaust and regional combustion sources. The annual average OC and EC concentrations (±1SD) were 7.30 ± 5.68 and 2.67 ± 2.28 μgC/m3, respectively. Taking advantage of this large data set of more than 7,000 measurements, we examined the diurnal variation dynamics of the primary OC‐to‐EC ratio ([OC/EC]pri), derived using the minimum R squared (MRS) method, which deploys an algorithm that calculates (OC/EC)pri by exploring the assumed independency between EC and secondary OC (SOC). The MRS‐derived hour‐by‐hour (OC/EC)pri was the lowest (1.8–2.0) for the morning hours while higher (2.4–3.0) for the afternoon and evening hours. Cumulative evidence from other pollutant measurements suggests that the increase in MRS‐derived (OC/EC)pri in the afternoon and evening was a result of SOC formation from photooxidation of precursors that covary with EC (e.g., vehicular exhaust) and thereby inflate (OC/EC)pri. We subsequently separate SOC into two categories based on their correlations with EC, that is, SOCa that covary with EC and SOCb that is unassociated with EC variations. SOCa and SOCb make comparable contributions to SOC, demonstrating that their separation is essential for a more accurate SOC estimation. Otherwise, SOCa would be mistakenly accounted as primary OC. This approach in estimating SOC may underestimate SOCa and subject to bias stemming from OC emissions from cooking and biomass burning.

Inter-comparison of NIOSH and IMPROVE protocols for OC and EC determination: implications for inter-protocol data conversion

Abstract. Organic carbon (OC) and elemental carbon (EC) are operationally defined by analytical methods. As a result, OC and EC measurements are protocol dependent, leading to uncertainties in their quantification. In this study, more than 1300 Hong Kong samples were analyzed using both National Institute for Occupational Safety and Health (NIOSH) thermal optical transmittance (TOT) and Interagency Monitoring of Protected Visual Environment (IMPROVE) thermal optical reflectance (TOR) protocols to explore the cause of EC disagreement between the two protocols. EC discrepancy mainly (83 %) arises from a difference in peak inert mode temperature, which determines the allocation of OC4NSH, while the rest (17 %) is attributed to a difference in the optical method (transmittance vs. reflectance) applied for the charring correction. Evidence shows that the magnitude of the EC discrepancy is positively correlated with the intensity of the biomass burning signal, whereby biomass burning increases the fraction of OC4NSH and widens the disagreement in the inter-protocol EC determination. It is also found that the EC discrepancy is positively correlated with the abundance of metal oxide in the samples. Two approaches (M1 and M2) that translate NIOSH TOT OC and EC data into IMPROVE TOR OC and EC data are proposed. M1 uses direct relationship between ECNSH_TOT and ECIMP_TOR for reconstruction: M1 : ECIMP_TOR = a × ECNSH_TOT + b; while M2 deconstructs ECIMP_TOR into several terms based on analysis principles and applies regression only on the unknown terms: M2 : ECIMP_TOR = AECNSH + OC4NSH − (a × PCNSH_TOR + b), where AECNSH, apparent EC by the NIOSH protocol, is the carbon that evolves in the He–O2 analysis stage, OC4NSH is the carbon that evolves at the fourth temperature step of the pure helium analysis stage of NIOSH, and PCNSH_TOR is the pyrolyzed carbon as determined by the NIOSH protocol. The implementation of M1 to all urban site data (without considering seasonal specificity) yields the following equation: M1(urban data) : ECIMP_TOR = 2.20 × ECNSH_TOT − 0.05. While both M1 and M2 are acceptable, M2 with site-specific parameters provides the best reconstruction performance. Secondary OC (SOC) estimation using OC and EC by the two protocols is compared. An analysis of the usability of reconstructed ECIMP_TOR and OCIMP_TOR suggests that the reconstructed values are not suitable for SOC estimation due to the poor reconstruction of the OC / EC ratio.

Determination of primary combustion source organic carbon-to-elemental carbon (OC / EC) ratio using ambient OC and EC measurements: secondary OC-EC correlation minimization method

Abstract. Elemental carbon (EC) has been widely used as a tracer to track the portion of co-emitted primary organic carbon (OC) and, by extension, to estimate secondary OC (SOC) from ambient observations of EC and OC. Key to this EC tracer method is to determine an appropriate OC / EC ratio that represents primary combustion emission sources (i.e., (OC / EC)pri) at the observation site. The conventional approaches include regressing OC against EC within a fixed percentile of the lowest (OC / EC) ratio data (usually 5–20 %) or relying on a subset of sampling days with low photochemical activity and dominated by local emissions. The drawback of these approaches is rooted in its empirical nature, i.e., a lack of clear quantitative criteria in the selection of data subsets for the (OC / EC)pri determination. We examine here a method that derives (OC / EC)pri through calculating a hypothetical set of (OC / EC)pri and SOC followed by seeking the minimum of the coefficient of correlation (R2) between SOC and EC. The hypothetical (OC / EC)pri that generates the minimum R2(SOC,EC) then represents the actual (OC / EC)pri ratio if variations of EC and SOC are independent and (OC / EC)pri is relatively constant in the study period. This Minimum R Squared (MRS) method has a clear quantitative criterion for the (OC / EC)pri calculation. This work uses numerically simulated data to evaluate the accuracy of SOC estimation by the MRS method and to compare with two commonly used methods: minimum OC / EC (OC / ECmin) and OC / EC percentile (OC / EC10 %). Log-normally distributed EC and OC concentrations with known proportion of SOC are numerically produced through a pseudorandom number generator. Three scenarios are considered, including a single primary source, two independent primary sources, and two correlated primary sources. The MRS method consistently yields the most accurate SOC estimation. Unbiased SOC estimation by OC / ECmin and OC / EC10 % only occurs when the left tail of OC / EC distribution is aligned with the peak of the (OC / EC)pri distribution, which is fortuitous rather than norm. In contrast, MRS provides an unbiased SOC estimation when measurement uncertainty is small. MRS results are sensitive to the magnitude of measurement uncertainty but the bias would not exceed 23 % if the uncertainty is within 20 %.

Assessing the Influence of Seasonal and Spatial Variations on the Estimation of Secondary Organic Carbon in Urban Particulate Matter by Applying the EC-Tracer Method

The elemental carbon (EC)-tracer method was applied to PM10 and PM1 data of three sampling sites in the City of Berlin from February to October 2010. The sites were characterized by differing exposure to traffic and vegetation. The aim was to determine the secondary organic carbon (SOC) concentration and to describe the parameters influencing the application of the EC-tracer method. The evaluation was based on comparisons with results obtained from positive matrix factorization (PMF) applied to the same samples. To obtain site- and seasonal representative primary OC/EC-ratios ([OC/EC]p), the EC-tracer method was performed separately for each station, and additionally discrete for samples with high and low contribution of biomass burning. Estimated SOC-concentrations for all stations were between 11% and 33% of total OC. SOC-concentrations obtained with PMF exceeded EC-tracer results more than 100% at the park in the period with low biomass burning emissions in PM10. The deviations were besides others attributed to the high ratio of biogenic to combustion emissions and to direct exposure to vegetation. The occurrences of biomass burning emissions in contrast lead to increased SOC-concentrations compared to PMF in PM10. The obtained results distinguish that the EC-tracer-method provides well comparable results with PMF if sites are strongly influenced by one characteristic primary combustion source, but was found to be adversely influenced by direct and relatively high biogenic emissions.

Ambient organic carbon to elemental carbon ratios: Influence of the thermal–optical temperature protocol and implications

Ambient organic carbon (OC) to elemental carbon (EC) ratios are strongly associated with not only the radiative forcing due to aerosols but also the extent of secondary organic aerosol (SOA) formation. An inter-comparison study was conducted based on fine particulate matter samples collected during summer in Beijing to investigate the influence of the thermal–optical temperature protocol on the OC to EC ratio. Five temperature protocols were used such that the NIOSH (National Institute for Occupational Safety and Health) and EUSAAR (European Supersites for Atmospheric Aerosol Research) protocols were run by the Sunset carbon analyzer while the IMPROVE (the Interagency Monitoring of Protected Visual Environments network)-A protocol and two alternative protocols designed based on NIOSH and EUSAAR were run by the DRI analyzer. The optical attenuation measured by the Sunset carbon analyzer was more easily biased by the shadowing effect, whereas total carbon agreed well between the Sunset and DRI analyzers. The ECIMPROVE-A (EC measured by the IMPROVE-A protocol; similar hereinafter) to ECNIOSH ratio and the ECIMPROVE-A to ECEUSAAR ratio averaged 1.36±0.21 and 0.91±0.10, respectively, both of which exhibited little dependence on the biomass burning contribution. Though the temperature protocol had substantial influence on the OC to EC ratio, the contributions of secondary organic carbon (SOC) to OC, which were predicted by the EC-tracer method, did not differ significantly among the five protocols. Moreover, the SOC contributions obtained in this study were comparable with previous results based on field observation (typically between 45 and 65%), but were substantially higher than the estimation provided by an air quality model (only 18%). The comparison of SOC and WSOC suggests that when using the transmittance charring correction, all of the three common protocols (i.e., IMPROVE-A, NIOSH and EUSAAR) could be reliable for the estimation of SOC by the EC-tracer method.

Secondary Organic Carbon Estimations with Hourly Monitoring Data and the OC/EC Primary Ratio Method

This study examined the hourly monitoring data from 2006 to 2009 collected by the Aerosol Supersite of the Environmental Protection Administration of Taiwan. The OC/EC primary ratio method has been applied to estimate the content of secondary organic carbon (SOC). Results of this study indicated that the monthly concentrations of PM2.5, OC, and EC all remained low in summer but went up in winter. Possible factors were climate-related and influences from continental high pressure systems. The content (24–36%) of SOC in summer was significantly higher than in other seasons, indicating that a great formation of organic carbon in summer. When considering the hourly trend, apparent peaks can be consistently observed in the morning, which may be due to an increase of mobile pollution source and photochemical reactions. (OC/EC)min ratio values were calculated based on both hourly and daily concentrations of OC and EC, then annual values (2006~2009) were 0.20~1.11 and 0.68~2.72 for hourly and daily data base respectively. Content of SOC in PM2.5 and OC were estimated to be 16~23 % and 75~93 % based on (OC/EC)min ratio from hourly data set, and were 11~18 % and 42~77 % based on (OC/EC)min ratio from daily data set. Results from this study, as well as those from other studies, demonstrated that the OC/EC ratio is dependent upon the sampling method as well as the method of analysis. Furthermore, the daily OC/EC ratio may change, and significant variations may be found even within 24 hours. Taken together, when conducting estimation of SOC, it is important to eliminate the consideration on background concentrations but to take a good advantage of the high temporal resolution of hourly monitoring data in order to estimate SOC using a corrective approach.

Tracer‐based estimation of secondary organic carbon in the Pearl River Delta, south China

Fine particles (PM2.5) were collected using filter‐based high‐volume samplers during summer‐winter 2008 at a rural site in the central Pearl River Delta (PRD), south China, to determine typical secondary organic aerosol (SOA) tracers from significant biogenic (isoprene, monoterpenes, and sesquiterpenes) and anthropogenic (aromatics) precursors. Average isoprene SOA tracers were significantly higher during summer (126 ng m−3) than during fall‐winter (25.1 ng m−3), owing largely to the higher isoprene emission and reaction rates in summer. Average monoterpene SOA tracers during summer (11.6 ng m−3) and fall‐winter (16.4 ng m−3) showed much less difference compared to isoprene SOA tracers, probably resulting from the counteracting effects of temperature on the precursor emission/tracer formation and on gas/particle partitioning. The concentrations of the aromatics' SOA tracer (2,3‐dihydroxy‐4‐oxopentanoic acid) ranged from 1.70 to 52.0 ng m−3 with an average of 15.1 ng m−3, which was the highest reported in ambient air. The secondary organic carbon (SOC) estimated by the SOA‐tracer method averaged 3.07 μg C m−3 in summer and 2.00 μg C m−3 in fall‐winter, contributing 38.4% and 8.7% to OC, respectively. During summer, aromatics‐SOC and isoprene‐SOC reached 2.25 ± 1.5 μg C m−3 and 0.64 ± 0.7 μg C m−3 and accounted for 76% and 18% of the estimated SOC, respectively, while during fall‐winter, aromatics‐SOC (1.64 ± 1.4 μg C m−3) was dominant with a share of 79% in total estimated SOC. These results indicated that anthropogenic aromatics were dominant SOC precursors in the highly industrialized and urbanized PRD region. During summer, SOC levels estimated by elemental carbon (EC) tracer method were not only consistent with but also correlated well with those by SOA‐tracer method. During fall‐winter, however, SOC by SOA‐tracer method was only about one third of that by EC‐tracer method. Their gaps were significantly correlated with the biomass burning tracer levoglucosan, indicating that input from biomass burning emission with very high ratios of OC/EC during fall‐winter would result in an overestimate of SOC by EC‐tracer method. Therefore cautions should be taken when estimating SOC by EC‐tracer method, especially when biomass burning exhibits significant influences.

The characteristics and origins of carbonaceous aerosol at a rural site of PRD in summer of 2006

Abstract. Both organic carbon (OC) and elemental carbon (EC) were measured during PRIDE-PRD 2006 summer campaign by using a semi-continuous thermal-optical carbon analyzer at a rural site, Back Garden (BG), which is located 50 km to the northwest of Guangzhou City. Together with the online EC/OC analyzer, various kinds of instruments related to aerosol chemical properties were employed here, which provided a good opportunity to check data quality. The concentrations of OC correlated well with the mass of organic matter (OM) and water soluble organic carbon (WSOC), implying the reliability of the data measured in this campaign. The average OC concentrations in fine particle for three typical periods during the campaign (local emission influence, typhoon and precipitation and normal days) were 28.1 μgC m−3, 4.0 μgC m−3 and 5.7 μgC m−3, respectively; and EC were 11.6 μgC m−3, 1.8 μgC m−3, and 3.3 μgC m−3, respectively. The diurnal patterns of EC and OC during the campaign were higher at night and in early morning than daytime, which was probably caused by the primary emission and accumulation in the occurrence of low boundary layer. Compared with the constant diurnal enhancement ratios of EC, the enhancement ratio of OC (OC versus (CO-CObackground)) kept in a relative high level in the afternoon, with a similar diurnal profile to oxygenated organic aerosol (OOA), due to the strong photochemical formation of OC. Here, a modified EC tracer method was used to estimate the formation of secondary organic carbon (SOC). These results showed that the average SOC concentration (normal days) at BG site was about 2.0 ± 2.3 μgC m−3, and the SOC fraction in OC could reach up to 80% with the average of 47%. The modified approach in this study proved to be effective and reliable for SOC estimation based on good correlations between estimated SOC versus OOA or WSOC, and estimated POC versus hydrocarbon-like organic aerosol (HOA).

Insights into the Origin of Water Soluble Organic Carbon in Atmospheric Fine Particulate Matter

Concentrations of fine carbonaceous aerosols (PM 2.5 ), including elemental carbon (EC), organic carbon (OC), and water-soluble organic carbon (WSOC) were measured from filters collected every 6th day for one year at three urban/industrial sites in the Midwestern United States: Cincinnati, Cleveland, and Mingo Junction, Ohio. The water-soluble fraction of fine particulate OC varied considerably from site to site and monthly averages were between 39–85% at Cincinnati, 35–68% at Cleveland, and 32–65% at Mingo Junction. Average monthly concentrations of WSOC were compared with measurements of organic source tracers, including levoglucosan, to better understand the spatial and temporal distribution and sources of WSOC. Two methods of predicting the non-biomass burning portion of WSOC (WSOC NB ) were compared including estimation of secondary organic carbon (SOC) by the EC-tracer Method and comparison of the unapportioned OC from a chemical mass balance (CMB) source apportionment analysis. Poor correlations be...

Seasonal and diurnal variations of organic carbon in PM2.5 in Beijing and the estimation of secondary organic carbon

Organic carbon (OC) and elemental carbon (EC) in PM2.5 were measured hourly with a semicontinuous thermal‐optical analyzer in Beijing, China, during four seasons from November 2005 to October 2006. The average OC concentrations measured at Peking University (PKU) site in urban Beijing were 20 ± 19, 12 ± 7, 10 ± 5, and 18 ± 11 μgC/m3 in winter, spring, summer, and autumn, respectively. Distinct seasonal and diurnal patterns of OC were observed, and their concentrations were significantly influenced by the seasonal and diurnal changes in sources, emission rates, and mesoscale meteorology. The impacts of meteorological parameters such as wind and precipitation on OC and EC concentrations are also discussed. OC and EC concentrations were found to be well correlated in winter, spring, and autumn, indicating their common origins, while their correlation was poorer in summer, especially in the afternoon, indicating that the influence of secondary organic carbon (SOC) was significant for this period. SOC concentrations were estimated by using the EC‐tracer method as about 2.6 ± 3.1, 2.8 ± 2.4, 4.5 ± 2.9, and 4.1 ± 4.0 μgC/m3, accounting for 19%, 27%, 45%, and 23% of total organic carbon in winter, spring, summer, and autumn, respectively. This result showed that the relative contribution of SOC to OC in PM2.5 at this urban location was only comparable to that of primary organic carbon (POC) to OC in summer, while in the other three seasons, OC was dominated by POC.

Linear regression techniques for use in the EC tracer method of secondary organic aerosol estimation

A variety of linear regression techniques and simple slope estimators are evaluated for use in the elemental carbon (EC) tracer method of secondary organic carbon (OC) estimation. Linear regression techniques based on ordinary least squares are not suitable for situations where measurement uncertainties exist in both regressed variables. In the past, regression based on the method of Deming [1943. Statistical Adjustment of Data. Wiley, London] has been the preferred choice for EC tracer method parameter estimation. In agreement with Chu [2005. Stable estimate of primary OC/EC ratios in the EC tracer method. Atmospheric Environment 39, 1383–1392], we find that in the limited case where primary non-combustion OC (OC non-comb) is assumed to be zero, the ratio of averages (ROA) approach provides a stable and reliable estimate of the primary OC–EC ratio, (OC/EC) pri. In contrast with Chu [2005. Stable estimate of primary OC/EC ratios in the EC tracer method. Atmospheric Environment 39, 1383–1392], however, we find that the optimal use of Deming regression (and the more general York et al. [2004. Unified equations for the slope, intercept, and standard errors of the best straight line. American Journal of Physics 72, 367–375] regression) provides excellent results as well. For the more typical case where OC non-comb is allowed to obtain a non-zero value, we find that regression based on the method of York is the preferred choice for EC tracer method parameter estimation. In the York regression technique, detailed information on uncertainties in the measurement of OC and EC is used to improve the linear best fit to the given data. If only limited information is available on the relative uncertainties of OC and EC, then Deming regression should be used. On the other hand, use of ROA in the estimation of secondary OC, and thus the assumption of a zero OC non-comb value, generally leads to an overestimation of the contribution of secondary OC to total measured OC.