PM_2.5 and PM₁₀ Mass Measurements in California's San Joaquin Valley

PM _2.5 and PM ₁₀ mass measurements from different sampling systems and locations within California's San Joaquin Valley (SJV) are compared to determine how well mass concentrations from a unified data set can be used to address issues such as compliance with particulate matter (PM) standards, temporal and spatial variations, and model predictions. Pairwise comparisons were conducted among 20 samplers, including four Federal Reference Method (FRM) units, battery-powered MiniVols, sequential filter samplers, dichotomous samplers, Micro-Orifice Uniform Deposit Impactors (MOUDIs), beta attenuation monitors (BAMs), tapered element oscillating microbalances (TEOMs), and nephelometers. The differences between FRM samplers were less than 10 and 20% for 70 and 92% of the pairwise comparisons, respectively. The TEOM, operating at 50°C in this study, measured less than the other samplers, consistent with other comparisons in nitrate-rich atmospheres. PM _2.5 mass measured continuously with the BAM was highly correlated with filter-based PM _2.5 although the absolute bias was greater than 20% in 45% of the cases. Light scattering (B _sp ) was also highly correlated with filter-based PM _2.5 at most sites, with mass scattering efficiencies varying by 10 and 20% for B _sp measured with Radiance Research nephelometers with and without PM _2.5 size-selective inlets, respectively. Collocating continuous monitors with filter samplers was shown to be useful for evaluating short-term variability and identifying outliers in the filter-based measurements. Comparability among different PM samplers used in CRPAQS is sufficient to evaluate spatial gradients larger than about 15% when the data are pooled together for spatial and temporal analysis and comparison with models.

This work was supported by the California Regional PM₁₀/PM_2.5 Air Quality Study (CRPAQS) agency under the management of the California Air Resources Board and by the U.S. Environmental Protection Agency under Contract #R-82805701 for the Fresno Supersite.

Notes

Anchor sites.

^b Selected satellite sites.

^c As part of the California Regional PM₁₀/PM_2.5 Air Quality Study.

^d Operated by the California Air Resources Board.

^e Operated by the Bay Area Air Quality Management District.

^f Operated by the San Joaquin Valley Air Quality Management District.

^g Meters above mean sea level (MSL).

^a Andersen Instruments (Thermo Electron, Waltham, MA); Rupprecht & Patashnick (now Thermo Electron, Albany, NY); Met One Instruments (Grants Pass, OR); Desert Research Institute (DRI, Reno, NV); Airmetrics (Eugene, OR); MSP Corporation (Minneapolis, MN); TSI, Inc. (Shoreview, MN); GreenTek (Atlanta, GA); Radiance Research (Seattle, WA).

^b Federal Reference Method (U.S. EPA 1997).

^c Federal Equivalent Method (Code of Federal Regulations 1988).

*Data available at http://www.arb.gov/airways/ and http://www.arb.ca.gov/aqd/aqdcddld.htm

^a See Table 2 for sampler descriptions.

^b Ordinary least squares method does not weight variables by their precisions (Bevington and Robinson 1992).

^c Number of sample concentration differences between stated precision intervals (s) for the difference.

^d Uncertainty of the average difference between Y and X.

^e Paired-difference T-test.

^f Significant probability: P < 0.05 implies the difference between Y and X is significant.

^g Average error. (i.e., difference between measurements): AE = 1001 N/∑_{i = 1} ^N Y_i − X_i X_i.

^a See Table 1 for site names and Table 2 for sampler descriptions.

^b Ordinary Least Squares method does not weight variables by their precisions (Bevington and Robinson 1992).

^c Number of sample concentration differences between stated precision intervals (s) for the difference.

^d Uncertainty of the average difference between Y and X.

^e Paired-difference T-test.

^f Significant probability: P < 0.05 implies the difference between Y and X is significant.

^g Average error: AE = 1001 N/∑_{i = 1} ^N Y_i − X_i X_i.

^a Slope of B_sp on PM_2.5 (Table 4).

^a See Table 1 for site names and Table 2 for sampler descriptions.

^b Ordinary least squares method does not weight variables by their precisions (Bevington and Robinson, 1992).

^c Number of sample concentration differences between stated precision intervals (s) for the difference.

^d Uncertainty of the average difference between Y and X.

^e Paired-difference T-test.

^f Significant probability: P < 0.05 implies the difference between Y and X is significant.

^g Average error: AE = 1001 N/∑_{i = 1} ^N Y_i − X_i X_i.

^a Slope of B_sp on PM_2.5 (Table 6).

^a See Table 1 for site names and Table 2 for sampler descriptions.

^b R² = squared correlation.

^c Average error: AE = 1001 N/∑_{i = j} ^N Y _i− X _i X

^d Percent of sample pairs with the absolute value of AE < 10%, 10–20%, 20–30%, or > 30%.

^e Five SFS samples from 4/12/00 to 5/6/00 identified in Figure 6 and discussed in the text are excluded.