Continuous and filter-based measurements of PM 2.5 nitrate and sulfate at the Fresno Supersite

Feasibility of coupling a thermal/optical carbon analyzer to a quadrupole mass spectrometer for enhanced PM2.5 speciation

A thermal/optical carbon analyzer (TOA), normally used for quantification of organic carbon (OC) and elemental carbon (EC) in PM_2.5 (fine particulate matter) speciation networks, was adapted to direct thermally evolved gases to an electron impact quadrupole mass spectrometer (QMS), creating a TOA-QMS. This approach produces spectra similar to those obtained by the Aerodyne aerosol mass spectrometer (AMS), but the ratios of the mass to charge (m/z) signals differ and must be remeasured using laboratory-generated standards. Linear relationships are found between TOA-QMS signals and ammonium (NH₄⁺), nitrate (NO₃^-), and sulfate (SO₄^2-) standards. For ambient samples, however, positive deviations are found for SO₄^2-, compensated by negative deviations for NO₃^-, at higher concentrations. This indicates the utility of mixed-compound standards for calibration or separate calibration curves for low and high ion concentrations. The sum of the QMS signals across all m/z after removal of the NH₄⁺, NO₃^-, and SO₄^2- signals was highly correlated with the carbon content of oxalic acid (C₂H₂O₄) standards. For ambient samples, the OC derived from the TOA-QMS method was the same as the OC derived from the standard IMPROVE_A TOA method. This method has the potential to reduce complexity and costs for speciation networks, especially for highly polluted urban areas such as those in Asia and Africa.

IMPLICATIONS

Ammonium, nitrate, and sulfate can be quantified by the same thermal evolution analysis applied to organic and elemental carbon. This holds the potential to replace multiple parallel filter samples and separate laboratory analyses with a single filter and a single analysis to account for a large portion of the PM_2.5 mass concentration.

Air quality measurements-From rubber bands to tapping the rainbow

It is axiomatic that good measurements are integral to good public policy for environmental protection. The generalized term for "measurements" includes sampling and quantitation, data integrity, documentation, network design, sponsorship, operations, archiving, and accessing for applications. Each of these components has evolved and advanced over the last 200 years as knowledge of atmospheric chemistry and physics has matured. Air quality was first detected by what people could see and smell in contaminated air. Gaseous pollutants were found to react with certain materials or chemicals, changing the color of dissolved reagents such that their light absorption at selected wavelengths could be related to both the pollutant chemistry and its concentration. Airborne particles have challenged the development of a variety of sensory devices and laboratory assays for characterization of their enormous range of physical and chemical properties. Advanced electronics made possible the sampling, concentration, and detection of gases and particles, both in situ and in laboratory analysis of collected samples. Accurate and precise measurements by these methods have made possible advanced air quality management practices that led to decreasing concentrations over time. New technologies are leading to smaller and cheaper measurement systems that can further expand and enhance current air pollution monitoring networks.

IMPLICATIONS

Ambient air quality measurement systems have a large influence on air quality management by determining compliance, tracking trends, elucidating pollutant transport and transformation, and relating concentrations to adverse effects. These systems consist of more than just instrumentation, and involve extensive support efforts for siting, maintenance, calibration, auditing, data validation, data management and access, and data interpretation. These requirements have largely been attained for criteria pollutants regulated by National Ambient Air Quality Standards, but they are rarely attained for nonroutine measurements and research studies.

A retrospective comparison of model-based forecasted PM2.5 concentrations with measurements

This study presents an assessment of the performance of the Community Multiscale Air Quality (CMAQ) photochemical model in forecasting daily PM2.5 (particulate matter < or = 2.5 microm in aerodynamic diameter) mass concentrations over most of the eastern United States for a 2-yr period from June 14, 2006 to June 13, 2008. Model predictions were compared with filter-based and continuous measurements of PM2.5 mass and species on a seasonal and regional basis. Results indicate an underprediction of PM2.5 mass in spring and summer, resulting from under-predictions in sulfate and total carbon concentrations. During winter, the model overpredicted mass concentrations, mostly at the urban sites in the northeastern United States because of overpredictions in unspeciated PM2.5 (suggesting possible overestimation of primary emissions) and sulfate. A comparison of observed and predicted diurnal profiles of PM2.5 mass at five sites in the domain showed significant discrepancies. Sulfate diurnal profiles agreed in shape across three sites in the southern portion of the domain but differed at two sites in the northern portion of the domain. Predicted organic carbon (OC) profiles were similar in shape to mass, suggesting that discrepancies in mass profiles probably resulted from the underprediction in OC. The diurnal profiles at a highly urbanized site in New York City suggested that the overpredictions at that site might be resulting from overpredictions during the morning and evening hours, displayed as sharp peaks in predicted profiles. An examination of the predicted planetary boundary layer (PBL) heights also showed possible issues in the modeling of PBL.

Ambient air pollutant measurement error: characterization and impacts in a time-series epidemiologic study in Atlanta

In time-series studies of ambient air pollution and health in large urban areas, measurement errors associated with instrument precision and spatial variability vary widely across pollutants. In this paper, we characterize these errors for selected air pollutants and estimate their impacts on epidemiologic results from an ongoing study of air pollution and emergency department visits in Atlanta. Error was modeled for daily measures of 12 air pollutants using collocated monitor data to characterize instrument precision and data from multiple study area monitors to estimate population-weighted spatial variance. Time-series simulations of instrument and spatial error were generated for each pollutant, added to a reference pollutant time-series, and used in a Poisson generalized linear model of air pollution and cardiovascular emergency department visits. Reductions in risk ratio due to instrument precision error were less than 6%. Error due to spatial variability resulted in average risk ratio reductions of less than 16% for secondary pollutants (O(3), PM(2.5) sulfate, nitrate and ammonium) and between 43% and 68% for primary pollutants (NO(x), NO(2), SO(2), CO, PM(2.5) elemental carbon); pollutants of mixed origin (PM(10), PM(2.5), PM(2.5) organic carbon) had intermediate impacts. Quantifying impacts of measurement error on health effect estimates improves interpretation across ambient pollutants.

Methods to assess carbonaceous aerosol sampling artifacts for IMPROVE and other long-term networks

Volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) adsorb to quartz fiber filters during fine and coarse particulate matter (PM2.5 and PM10, respectively) sampling for thermal/optical carbon analysis that measures organic carbon (OC) and elemental carbon (EC). Particulate SVOCs can evaporate after collection, with a small portion adsorbed within the filter. Adsorbed organic gases are measured as particulate OC, so passive field blanks, backup filters, prefilter organic denuders, and regression methods have been applied to compensate for positive OC artifacts in several long-term chemical speciation networks. Average backup filter OC levels from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network were approximately 19% higher than field blank values. This difference is within the standard deviation of the average and likely results from low SVOC concentrations in the rural to remote environments of most IMPROVE sites. Backup filters from an urban (Fort Meade, MD) site showed twice the OC levels of field blanks. Sectioning backup filters from top to bottom showed nonuniform OC densities within the filter, contrary to the assumption that VOCs and SVOCs on a backup filter equal those on the front filter. This nonuniformity may be partially explained by evaporation and readsorption of vapors in different parts of the front and backup quartz fiber filter owing to temperature, relative humidity, and ambient concentration changes throughout a 24-hr sample duration. OC-PM2.5 regression analysis and organic denuder approaches demonstrate negative sampling artifact from both Teflon membrane and quartz fiber filters.