Aerosol Filtration by Sorbent Beds

Fixed beds of sorbent media are used for the evaluation of poiynuclear aromatic hydrocarbons (PAH) present in air. Twostage sampling and separate extraction and analyses of PAH associated with aerosol particles and those present in the vapor state are usually performed. The ability of commonly used sorbents to retain particulate matter introduces a potential for reducing the time and cost of PAH evaluation procedures.

The filtration efficiency of three sorbent media, Florisil, XAD-2, and polyurethanefoam (PUF), for particles in 0.1 to 1 µm size range was studied using airflow rates from 4 to 2501 /mm through a PS 1 sorbent cartridge. Theoretical considerations were used to identify the principal filtration mechanisms and to assess the predictability of the aerosol filtration performance of sorbent filters. The results of this study indicate XAD-2 to be an efficient filtration medium owing to the electrostatic enhancement of capturing and retaining aerosol particles.

As a result of theoretical considerations, Brownian diffusion and inertial deposition were found to be major filtration mechanisms accompanied by electrostatic effects. While the efficiency of the diffusional deposition mechanism was reasonably well predicted with available theories, modeling of submicron particle impaction at higher fluid velocities appeared to be inadequate. Further developments are suggested to improve our understanding of filtration phenomena in sorbent beds under high flow rate conditions.     

Using Continuous PM2.5 Monitoring Data to Report an Air Quality Index

Abstract

As stated in 40 CFR 58, Appendix G (2000), statistical linear regression models can be applied to relate PM_2.5 continuous monitoring (CM) measurements with federal reference method (FRM) measurements, collocated or otherwise, for the purpose of reporting the air quality index (AQI). The CM measurements can then be transformed via the model to remove any bias relative to FRM measurements. The resulting FRM-like modeled measurements may be used to provide more timely reporting of a metropolitan statistical area’s (MSA’s) AQI.¹ Of considerable importance is the quality of the model used to relate the CM and FRM measurements. The use of a poor model could result in misleading AQI reporting in the form of incorrectly claiming either good or bad air quality.

This paper describes a measure of adequacy for deciding whether a statistical linear regression model that relates FRM and continuous PM_2.5 measurements is sufficient for use in AQI reporting. The approach is the U.S. Environmental Protection Agency’s (EPA’s) data quality objectives (DQO) process, a seven-step strategic planning approach to determine the most appropriate data type, quality, quantity, and synthesis for a given activity.² The chosen measure of model adequacy is r², the square of the correlation coefficient between FRM measurements and their modeled counterparts. The paper concludes by developing regression models that meet this desired level of adequacy for the MSAs of Greensboro/Winston-Salem/High Point, NC; and Davenport/Moline/Rock Island, IA/IL. In both cases, a log transformation of the data appeared most appropriate. For the data from the Greens-boro/Winston-Salem/High Point MSA, a simple linear regression model of the FRM and CM measurements had an r² of 0.96, based on 227 paired observations. For the data from the Davenport/Moline/Rock Island MSA, due to seasonal differences between CM and FRM measurements, the simple linear regression model had to be expanded to include a temperature dependency, resulting in an r² of 0.86, based on 214 paired observations.     

Formation of NO2 in range-top burners

This paper describes results of a study that examined NO and NO₂ formation on range-top burners and in diffusion flames. These flames were characterized by composition and temperature profiles. Range-top burner flames and pilot flames displayed qualitatively similar behavior with respect to the kinds of flame regions in which relatively high NO₂/NO ratios were identified. These regions of high NO₂/NO ratios were consistently either regions of low oxygen concentration or flame surfaces subjected to thermal quenching. A limited series of experiments with modified burners indicated that reduced emissions from both the RTB and pilot flames could be achieved by (1) improved primary aeration, using 50% or greater primary air, and (2) using flame geometries designed to minimize flame surface, e.g., flat-flame burners or other designs having effectively fewer distinct ports. Both NO and NO₂ are readily produced in diffusion and partially premixed Bunsen-type flames, mainly in the vicinity of the hot visible zone. High NO₂/NO ratios are associated with the cooler regions of the flame, as, for example, at the base of the flame in the highly diluted downstream region and in the fuel-rich regions of the flames. A simplified reaction mechanism based on CN and NH radicals being oxidized to NO followed by NO + HO₂ → NO₂ + OH appears to explain the high NO₂/NO ratios observed. A practical implication of the study is that a burner designed with improved aeration and mixing minimization of flame surface should emit less NO₂.     

Using continuous PM2.5 monitoring data to report an air quality index

As stated in 40 CFR 58, Appendix G (2000), statistical linear regression models can be applied to relate PM2.5 continuous monitoring (CM) measurements with federal reference method (FRM) measurements, collocated or otherwise, for the purpose of reporting the air quality index (AQI). The CM measurements can then be transformed via the model to remove any bias relative to FRM measurements. The resulting FRM-like modeled measurements may be used to provide more timely reporting of a metropolitan statistical area's (MSA's) AQI. Of considerable importance is the quality of the model used to relate the CM and FRM measurements. The use of a poor model could result in misleading AQI reporting in the form of incorrectly claiming either good or bad air quality. This paper describes a measure of adequacy for deciding whether a statistical linear regression model that relates FRM and continuous PM2.5 measurements is sufficient for use in AQI reporting. The approach is the U.S. Environmental Protection Agency's (EPA's) data quality objectives (DQO) process, a seven-step strategic planning approach to determine the most appropriate data type, quality, quantity, and synthesis for a given activity. The chosen measure of model adequacy is r2, the square of the correlation coefficient between FRM measurements and their modeled counterparts. The paper concludes by developing regression models that meet this desired level of adequacy for the MSAs of Greensboro/Winston-Salem/High Point, NC; and Davenport/Moline/Rock Island, IA/IL. In both cases, a log transformation of the data appeared most appropriate. For the data from the Greensboro/Winston-Salem/High Point MSA, a simple linear regression model of the FRM and CM measurements had an r2 of 0.96, based on 227 paired observations. For the data from the Davenport/Moline/Rock Island MSA, due to seasonal differences between CM and FRM measurements, the simple linear regression model had to be expanded to include a temperature dependency, resulting in an r2 of 0.86, based on 214 paired observations.