Standardisation of a European measurement method for organic carbon and elemental carbon in ambient air: results of the field trial campaign and the determination of a measurement uncertainty and working range

2017 ◽  
Vol 19 (10) ◽  
pp. 1249-1259 ◽  
Author(s):  
Richard J. C. Brown ◽  
Sonya Beccaceci ◽  
David M. Butterfield ◽  
Paul G. Quincey ◽  
Peter M. Harris ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Measurement Uncertainty ◽  
Standard Method ◽  
Field Trial ◽  
Measurement Method ◽  
Elemental Carbon ◽  
Ambient Air

A standard method for measurements of organic carbon and elemental carbon has been produced.

scholarly journals Standardisation of a European measurement method for the determination of anions and cations in PM2.5: results of field trial campaign and determination of measurement uncertainty

2016 ◽  
Vol 18 (12) ◽  
pp. 1561-1571
Author(s):  
Sonya Beccaceci ◽  
Richard J. C. Brown ◽  
David M. Butterfield ◽  
Peter M. Harris ◽  
René P. Otjes ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Measurement Uncertainty ◽  
Field Trial ◽  
Measurement Method ◽  
Ambient Particulate Matter ◽  
European Standard ◽  
Standard Measurement ◽  
Anions And Cations ◽  
Determination Of Anions

The results of field trial campaign to validate the European standard measurement method for anions and cations in ambient particulate matter are presented.

Methods for determination of elemental carbon in ambient air

1990 ◽  
Vol 14 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Wojciech Mniszek ◽  
Janusz Kolarczyk ◽  
Antoni Hanusik
Keyword(s):  
Elemental Carbon ◽  
Ambient Air

scholarly journals 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

2016 ◽  
Vol 16 (8) ◽  
pp. 5453-5465 ◽  
Author(s):  
Cheng Wu ◽  
Jian Zhen Yu
Keyword(s):  
Organic Carbon ◽  
Measurement Uncertainty ◽  
Elemental Carbon ◽  
Simulated Data ◽  
Primary Source ◽  
Primary Sources ◽  
Pseudorandom Number Generator ◽  
Combustion Source ◽  
Minimization Method ◽  
Soc Estimation

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 %.

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