Correction Methods for Organic Carbon Artifacts When Using Quartz-Fiber Filters in Large Particulate Matter Monitoring Networks: The Regression Method and Other Options

Figures & data

Figure 1. PAQS artifact-corrected OC calculated as Q – QQB (□) and Q – TQB (Δ) and from the denuder sampler (eq 5). Adapted with permission from Subramanian et al.5 First published in Aerosol Science and Technology, 38 (suppl 1), 27-48, 2004. Copyright 2004 Taylor & Francis, Aerosol Science and Technology.

Figure 2. (a) Dynamic blank sampler and (b) denuder system configurations used to estimate OC artifact during PAQS. Filters are labeled as follows: Q = QFF, T = Teflon filter, QQB = quartz quartz backup, TQB, Teflon quartz backup, ADS = CIG adsorbent.

Table 1. OC measurements during the PAQS, the RIOPA study, and the six-site STN/IMPROVE comparison study

	PAQS	RIOPA	Six-Site STN/IMPROVE
Sample duration	24 hr	48 hr	24 hr
OC measurements (see Figure 2)	Q; denuded Q; TQB; QQB (Figure 2, a and b)	Q; TQB daily (Figure 2a)	Q
Face velocity (cm/sec)	29 Pittsburgh	25 Elizabeth Los Angeles Houston	23.6 Beacon Hill Mt Rainer; 9.5 Phoenix Tonto; 10.4 Dolly Sods Haines Point
Quartz filter	Pallflex	Pallflex	Whatman
Notes: Q indicates quartz-fiber filter collection of PM for OC analysis. TQB and QQB indicate that adsorbed OC was measured on a QFF behind a Teflon or behind a QFF, respectively.

Table 2a. PAQS artifacts. Regression of measured QFF OC concentration (μgC/m³) on PM_2.5 (μg/m³) mass by standard LLSR, Deming regression (accounting for measurement uncertainties), and LLSR and Deming regression after outlier removal by robust regression for PAQS

							Measurement-Based Artifact Estimates
RM	Sample Size (N)	Slope (μgC)/(μgPM2.5)	Intercept (μgC/m^3)	r^2	Average Front-Filter OC (μgC/m^3)	Percent Artifact RM	Percent Field Blank	Percent Artifact TQB	Percent Artifact QQB	Percent Artifact Denuder
Standard LLSR	301	0.128 ± 0.006	1.13 ± 0.12	0.56	3.12	36	3 (N=52)	33	15	20 (N=47)
Deming	301	0.128 ± 0.007	1.11 ± 0.12			36
Robust	291	0.136 ± 0.005	0.91 ± 0.09	0.70	3.04	30	3 (N=52)	34	16
Deming robust	291	0.136 ± 0.005	0.90 ± 0.10			30
Notes: Outlier points are determined by robust regression with a cutoff of 3.0. Percent artifact is the net organic artifact on a single QFF (mean) as a percentage of mean front-filter OC for RM (y-intercept) and mean measurement-based methods (field blank, TQB dynamic blank, QQB dynamic blank, and two-channel denuder system). Percent denuder OC (PAQS) was calculated for the 47 days of paired denuder and front-filter OC data.

Table 2b. RIOPA artifacts. Regression of measured QFF OC concentration (μgC/m³) on PM_2.5 (μg/m³) mass by standard LLSR, Deming regression (accounting for measurement uncertainties), and LLSR and Deming regression after outlier removal by robust regression for RIOPA sites

RIOPA Sites	RM	Sample Size (N)	Slope (μgC)/(μgPM2.5)	Intercept (μgC/m^3)	r^2	Average Front-Filter OC (μgC/m^3)	Percent Artifact RM	Percent Field Blank	Percent Artifact TQB
Los Angeles County, CA	Standard LLSR	40	0.046 ± 0.053	5.28 ± 0.98	0.02	6.08	87	4 (N = 75)	31
	Deming	40	0.048 ± 0.056	5.24 ± 1.03			86
	Robust	40	0.046 ± 0.053	5.28 ± 0.98	0.02	6.08	87		31
	Deming robust	40	0.048 ± 0.056	5.24 ± 1.03			86
	Deming without influential points	37	0.209 ± 0.075	2.87 ± 1.25	0.18	6.21	46		31
Elizabeth, NJ	Standard LLSR	44	0.118 ± 0.026	3.08 ± 0.47	0.32	4.97	62		33
	Deming	44	0.120 ± 0.027	3.05 ± 0.48			61
	Robust	44	0.118 ± 0.026	3.08 ± 0.47	0.32	4.97	62		33
	Deming robust	44	0.120 ± 0.027	3.05 ± 0.48			61
Houston, TX	Standard LLSR	61	0.251 ± 0.043	1.41 ± 0.70	0.36	5.15	27		42
	Deming	61	0.265 ± 0.046	1.19 ± 0.74			23
	Robust	60	0.243 ± 0.040	1.41 ± 0.64	0.39	5.03	28		43
	Deming robust	60	0.255 ± 0.042	1.23 ± 0.67			25
Notes: No denuder or QQB measurements were made in RIOPA. Outlier points are determined by robust regression with a cutoff of 3.0. Percent artifact is the net organic artifact on a single QFF (mean) as a percentage of mean front-filter OC for RM (y-intercept) and and mean measurement-based methods (field blank and TQB dynamic blank).

Table 2c. Six-site STN/IMPROVE comparison study. Regression of measured QFF OC concentration (μgC/m³) on PM_2.5 (μg/m³) mass by standard LLSR, Deming regression (accounting for measurement uncertainties), and LLSR and Deming regression after outlier removal by robust regression

STN/IMPROVE Comparison Study	RM	Sample Size (N)	Slope (μgC)/(μgPM2.5)	Intercept (μgC/m^3)	r^2	Average Front-Filter OC (μgC/m^3)	Percent Artifact RM	Percent Field Blank
Haines Point, DC (urban)	Standard LLSR	118	0.209 ± 0.017	1.32 ± 0.30	0.55	4.49	29	29
	Deming	118	0.213 ± 0.018	1.27 ± 0.31			28
	Robust	116	0.199 ± 0.016	1.44 ± 0.26	0.59	4.37	33
	Deming robust	116	0.201 ± 0.016	1.40 ± 0.26			32
Dolly Sods, WV (rural)	Standard LLSR	105	0.140 ± 0.019	1.46 ± 0.25	0.35	3.03	48	43
	Deming	105	0.142 ± 0.019	1.43 ± 0.26			47
	Robust	99	0.120 ± 0.016	1.56 ± 0.19	0.38	2.83	55
	Deming robust	99	0.122 ± 0.016	1.55 ± 0.19			55
Phoenix, AZ (urban)	Standard LLSR	110	0.383 ± 0.030	0.95 ± 0.36	0.60	5.21	18	27
	Deming	110	0.401 ± 0.031	0.75 ± 0.38			14
	Robust	103	0.447 ± 0.025	0.35 ± 0.29	0.76	5.22	7
	Deming robust	103	0.460 ± 0.025	0.21 ± 0.30			4
Tonto, AZ (rural)	Standard LLSR	102	0.393 ± 0.040	0.12 ± 0.29	0.49	2.58	5	54
	Deming	102	0.425 ± 0.044	−0.08 ± 0.31			−3
	Robust	91	0.115 ± 0.022	1.44 ± 0.14	0.24	2.11	68
	Deming robust	91	0.118 ± 0.022	1.43 ± 0.14			67
Beacon Hill, WA (urban)	Standard LLSR	119	0.405 ± 0.014	−0.31 ± 0.12	0.87	2.78	−11	11
	Deming	119	0.410 ± 0.015	−0.35 ± 0.13			−12
	Robust	116	0.413 ± 0.013	−0.31 ± 0.11	0.90	2.80	−11
	Deming robust	116	0.416 ± 0.013	−0.34 ± 0.11			−12
Mount Ranier, WA (rural)	Standard LLSR	99	0.364 ± 0.019	0.10 ± 0.08	0.78	1.40	7	7
	Deming	99	0.370 ± 0.020	0.08 ± 0.08			6
	Robust	95	0.393 ± 0.015	0.04 ± 0.06	0.89	1.39	3
	Deming robust	95	0.397 ± 0.015	0.02 ± 0.06			2
Notes: No denuder, TQB, or QQB measurements were made in the six-site STN/IMPROVE comparison study. Outlier points are determined by robust regression with a cutoff of 3.0. Percent artifact is the net organic artifact on a single QFF (mean) as a percentage of mean front-filter OC for RM (y-intercept) and field blank.

Table 3. OC estimates by denuder (eq 5), by backup filter subtraction (Q-TQB and Q-QQB), by RM (Deming robust regression), and uncorrected front QFF OC for PAQS and RIOPA

	Full Dataset (mean ± SD)	Lower 25th Percentile (mean ± SD)	Upper 25th Percentile (mean ± SD)
PAQS (N = 301)
Denuder (μgC/m^3) (N = 47)	2.36 ± 1.48	1.88 ± 1.27	3.82 ± 1.70
Q-QQB (μgC/m^3)	2.64 ± 1.44	1.74 ± 1.19	4.17 ± 1.41
Q-TQB (μgC/m^3)	2.09 ± 1.32	1.32 ± 1.11	3.48 ± 1.31
RM (Q - 0.90; μgC/m^3)	2.23 ± 1.61	1.18 ± 1.29	3.99 ± 1.51
Front QFF (Q; μgC/m^3)	3.12 ± 1.61	2.06 ± 1.29	4.88 ± 1.51
QQB (μgC/m^3)	0.48 ± 0.23	0.33 ± 0.16	0.71 ± 0.23
TQB (μgC/m^3)	1.03 ± 0.39	0.75 ± 0.26	1.41 ± 0.34
PM2.5 mass (μg/m^3)	15.64 ± 9.45	6.71 ± 1.72	28.72 ± 8.28
California RIOPA (N = 40)
Q-TQB (μgC/m^3)	4.16 ± 1.94	3.49 ± 1.79	4.85 ± 1.95
RM (Q - 5.24; μgC/m^3)	0.84 ± 2.16	0.16 ± 2.13	1.46 ± 2.19
Front QFF (Q; (μgC/m^3)	6.08 ± 2.16	5.40 ± 2.13	6.70 ± 2.19
TQB (μgC/m^3)	1.90 ± 0.64	1.85 ± 0.54	1.91 ± 0.64
PM2.5 mass (μg/m^3)	17.31 ± 6.56	10.66 ± 2.21	27.09 ± 5.36
New Jersey RIOPA (N = 44)
Q-TQB (μgC/m^3)	3.32 ± 1.43	2.24 ± 0.73	4.83 ± 1.36
RM (Q - 3.05; μgC/m^3)	1.92 ± 1.66	0.72 ± 0.82	3.38 ± 1.78
Front QFF (Q; (μgC/m^3)	4.97 ± 1.66	3.77 ± 0.82	6.43 ± 1.78
TQB (μgC/m^3)	1.61 ± 0.53	1.53 ± 0.48	1.65 ± 0.50
PM2.5 mass (μg/m^3)	16.00 ± 8.03	8.35 ± 2.13	26.51 ± 8.51
Texas RIOPA (N = 61)
Q-TQB (μgC/m^3)	2.96 ± 2.44	1.44 ± 1.42	4.60 ± 2.80
RM (Q - 1.23; μgC/m^3)	3.92 ± 2.60	2.06 ± 1.44	5.90 ± 2.83
Front QFF (Q; (μgC/m^3)	5.15 ± 2.60	3.29 ± 1.44	7.13 ± 2.83
TQB (μgC/m^3)	2.18 ± 0.98	1.85 ± 0.63	2.53 ± 0.87
PM2.5 mass (μg/m^3)	14.92 ± 6.23	8.72 ± 1.37	23.65 ± 5.21
Notes: OC measured on the backup filters and the PM2.5 mass concentrations are also shown.

Figure 3. Measured front QFF OC (μgC/m³) and PM_2.5 mass (μg/m³) for (a) PAQS, (b–d) RIOPA sites, and (e–j) the six-site STN/IMPROVE comparison study. Dashed circles are outliers in x or y identified by robust regression. The solid line is the Deming linear regression of y on x performed without outliers. The RM estimate is the Deming regression y-intercept value after outlier removal by the robust regression (Table 2). The dashed line is the RM artifact estimate (y-intercept of regression; see also Table 2). In the RM, this value is subtracted from each sample. Note OC concentrations that fall below this line will be negative after RM artifact correction. Dashed squares indicate points not identified as outliers but with a large influence on the regression.

Figure 4. Measured organic adsorption artifact OC (TQB or QQB) and front-filter OC for (a) PAQS and (b–d) RIOPA sites. The increase in measured organic adsorption artifact with increasing front-filter OC (a measure of the organic pollution level) was significant (linear regression t test, α= 0.05) for PAQS and RIOPA sites. An increase in the actual organic adsorption artifact with organic pollution level violates an assumption of the RM of organic artifact estimation.

Figure 5. LLSR of artifact-corrected OC (Q – QQB or Q – TQB; y-axis) on front QFF OC (measured on Q; x-axis), demonstrating intermittent backup filter collection with every tenth sample for PAQS. The regression lines shown correspond well with their full dataset equivalents (PAQS Q – QQB: y = 0.89x – 0.14, r² = 0.99; PAQS Q – TQB: y = 0.81x – 0.43, r² = 0.97; N = 301). For days without backup filter measurements, particulate OC can be estimated from regression equations such as these.

Subramanian , R. , Khlystov , A.Y. , Cabada , J.C. and Robinson , A.L. 2004 . Positive and Negative Artifacts in Particulate Organic Carbon Measurements with Denuded and Undenuded Sampler Configurations . Aerosol Sci. Technol. , 38 : 27 – 48 .

 Web of Science ®Google Scholar