Potential interference bias in ozone standard compliance monitoring

The U.S. Environmental Protection Agency has established a federal reference method (FRM) for ozone (O3) and allowed for designation of federal equivalent methods (FEMs). However, the ethylene-chemiluminescence FRM for O3 has been replaced by the UV photometric FEM by most state and local monitoring agencies because of its relative ease of operation. Accumulating evidence indicates that the FEM is prone to bias under the hot, humid, and stagnant conditions conducive to high O3 formation. This bias may lead to overreporting hourly O3 concentrations by as much as 20-40 ppb. Measurement bias is caused by contamination of the O3 scrubber, a problem that is not detected by dry air calibration. An adequate wet test has not been codified, although a procedure has been proposed for agency consideration. This paper includes documentation of laboratory tests quantifying specific interferant responses, collocated ambient FRM/FEM monitoring results, and smog chamber comparisons of the FRM and FEMs with alternative scrubber designs. As the numbers of reports on monitor interferences have grown, interested parties have called for agency recognition and correction of these biases.     

A Re-Examination of Ambient Air Ozone Monitor Interferences

Abstract

Attaining the National Ambient Air Quality Standard (NAAQS) for ozone (O₃) could cost billions of dollars nationwide. Attainment of the NAAQS is judged on O₃ measurements made by the Federal Reference Method (FRM), ethylene chemiluminescence, or a Federal Equivalent Method (FEM), predominantly ultraviolet (UV) absorption. Starting in the 1980s, FRM monitors were replaced by FEMs so that today virtually all monitoring in the United States uses the UV methodology. This report summarizes a laboratory and collocated ambient air monitoring study of interferences in O₃ monitors. Potential interferences examined in the laboratory included water vapor, mercury, o-nitrophenol, naphthalene, p-tolualdehyde, and mixed reaction products from smog chamber simulations of urban atmospheric photochemistry. UV absorption O₃ monitors modi?ed for humidity equilibration were also collocated with UV FEM O₃ monitors at six sites in Houston, TX, during the 2007 summer O₃ season. The results suggest that humidity and interfering species can positively bias (overestimate) O₃ measured by FEM monitors used to determine compliance with the O₃ standards. The results also suggest that humidity equilibration can mitigate this bias.     

A re-examination of ambient air ozone monitor interferences

Attaining the National Ambient Air Quality Standard (NAAQS) for ozone (O3) could cost billions of dollars nationwide. Attainment of the NAAQS is judged on O3 measurements made by the Federal Reference Method (FRM), ethylene chemiluminescence, or a Federal Equivalent Method (FEM), predominantly ultraviolet (UV) absorption. Starting in the 1980s, FRM monitors were replaced by FEMs so that today virtually all monitoring in the United States uses the UV methodology. This report summarizes a laboratory and collocated ambient air monitoring study of interferences in O3 monitors. Potential interferences examined in the laboratory included water vapor, mercury, o-nitrophenol, naphthalene, p-tolualdehyde, and mixed reaction products from smog chamber simulations of urban atmospheric photochemistry. UV absorption O3 monitors modified for humidity equilibration were also collocated with UV FEM O3 monitors at six sites in Houston, TX, during the 2007 summer O3 season. The results suggest that humidity and interfering species can positively bias (overestimate) O3 measured by FEM monitors used to determine compliance with the O3 standards. The results also suggest that humidity equilibration can mitigate this bias.     

Field evaluations of newly available “interference-free” monitors for nitrogen dioxide and ozone at near-road and conventional National Ambient Air Quality Standards compliance sites

Long-standing measurement techniques for determining ground-level ozone (O₃) and nitrogen dioxide (NO₂) are known to be biased by interfering compounds that result in overestimates of high O₃ and NO₂ ambient concentrations under conducive conditions. An increasing near-ground O₃ gradient (NGOG) with increasing height above ground level is also known to exist. Both the interference bias and NGOG were investigated by comparing data from a conventional Federal Equivalent Method (FEM) O₃ photometer and an identical monitor upgraded with an “interference-free” nitric oxide O₃ scrubber that alternatively sampled at 2 m and 6.2 m inlet heights above ground level (AGL). Intercomparison was also made between a conventional nitrogen oxide (NO_x) chemiluminescence Federal Reference Method (FRM) monitor and a new “direct-measure” NO₂ NO_x 405 nm photometer at a near-road air quality measurement site. Results indicate that the O₃ monitor with the upgraded scrubber recorded lower regulatory-oriented concentrations than the deployed conventional metal oxide–scrubbed monitor and that O₃ concentrations 6.2 m AGL were higher than concentrations 2.0 m AGL, the nominal nose height of outdoor populations. Also, a new direct-measure NO₂ photometer recorded generally lower NO₂ regulatory-oriented concentrations than the conventional FRM chemiluminescence monitor, reporting lower daily maximum hourly average concentrations than the conventional monitor about 3 of every 5 days.

Implications: Employing bias-prone instruments for measurement of ambient ozone or nitrogen dioxide from inlets at inappropriate heights above ground level may result in collection of positively biased data. This paper discusses tests of new regulatory instruments, recent developments in bias-free ozone and nitrogen dioxide measurement technology, and the presence/extent of a near-ground O₃ gradient (NGOG). Collection of unbiased monitor inlet height–appropriate data is crucial for determining accurate design values and meeting National Ambient Air Quality Standards.     

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.     

A Simple Methodology for the Determination of Back Trajectories

Abstract

This study comprehensively characterizes hourly fine particulate matter (PM_2.5) concentrations measured via a tapered element oscillating microbalance (TEOM), β-gauge, and nephelometer from four different monitoring sites in U.S. Environment Protection Agency (EPA) Region 5 (in U.S. states Illinois, Michigan, and Wisconsin) and compares them to the Federal Reference Method (FRM). Hourly characterization uses time series and autocorrelation. Hourly data are compared with FRM by averaging across 24-hr sampling periods and modeling against respective daily FRM concentrations. Modeling uses traditional two-variable linear least-squares regression as well as innovative nonlinear regression involving additional meteorological variables such as temperature and humidity. The TEOM shows a relationship with season and temperature, linear correlation as low as 0.7924 and nonlinear model correlation as high as 0.9370 when modeled with temperature. The β-gauge shows no relationship with season or meteorological variables. It exhibits a linear correlation as low as 0.8505 with the FRM and a nonlinear model correlation as high as 0.9339 when modeled with humidity. The nephelometer shows no relationship with season or temperature but a strong relationship with humidity is observed. A linear correlation as low as 0.3050 and a nonlinear model correlation as high as 0.9508 is observed when modeled with humidity. Nonlinear models have higher correlation than linear models applied to the same dataset. This correlation difference is not always substantial, which may introduce a tradeoff between simplicity of model and degree of statistical association. This project shows that continuous monitor technology produces valid PM_2.5 characterization, with at least partial accounting for variations in concentration from gravimetric reference monitors once appropriate nonlinear adjustments are applied. Although only one regression technically meets new EPA National Ambient Air Quality Standards (NAAQS) Federal Equivalent Method (FEM) correlation coefficient criteria, several others are extremely close, showing optimistic potential for use of this nonlinear adjustment model in garnering EPA NAAQS FEM approval for continuous PM_2.5 sampling methods.     

Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial,California, USA

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R² for converted hourly averaged Dylos mass measurements versus a PM_2.5 BAM was 0.79 and that versus a PM₁₀ BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM_2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R² = 0.35–0.81).

Implications: The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.     

Particulate Matter in California: Part 1—Intercomparison of Several PM2.5, PM10–2.5, and PM10 Monitoring Networks

Abstract

It will be many years before the recently deployed network of fine particulate matter with an aerodynamic diameter less than 2.5 [H9262]m (PM_2.5) Federal Reference Method (FRM) samplers produces information on nonattainment areas, trends, and source impacts. However, data on PM_2.5 and its major constituents have been routinely collected in California for the past 20 years. The California Air Resources Board operated as many as 20 dichotomous (dichot) samplers for PM_2.5 and coarse PM (PM_10–2.5). The California Acid Deposition Monitoring Program (CADMP) collected 12-h-average PM_2.5 and PM₁₀ from 1988 to 1995 at ten urban and rural sites and 24-h-average PM_2.5 at five urban sites since 1995. Beginning in 1994, the Children’s Health Study collected 2-week averages of PM_2.5 in 12 communities in southern California using the Two-Week Sampler (TWS). Comparisons of collocated samples establish relationships between the dichot, CADMP, and TWS samplers and the 82-site network of PM_2.5 FRM samplers deployed since 1999 in California. PM mass data from the different monitoring programs have modest to high correlation to FRM mass data, fairly small systematic biases and negative proportional biases ranging from 7 to 22%. If the biases are taken into account, all of the programs should be considered comparable with the FRM program. Thus, historical data can be used to develop long-term PM trends in California.     

Collocated comparisons of continuous and filter-based PM2.5 measurements at Fort McMurray,Alberta, Canada

Collocated comparisons for three PM_2.5 monitors were conducted from June 2011 to May 2013 at an air monitoring station in the residential area of Fort McMurray, Alberta, Canada, a city located in the Athabasca Oil Sands Region. Extremely cold winters (down to approximately ?40°C) coupled with low PM_2.5 concentrations present a challenge for continuous measurements. Both the tapered element oscillating microbalance (TEOM), operated at 40°C (i.e., TEOM₄₀), and Synchronized Hybrid Ambient Real-time Particulate (SHARP, a Federal Equivalent Method [FEM]), were compared with a Partisol PM_2.5 U.S. Federal Reference Method (FRM) sampler. While hourly TEOM₄₀ PM_2.5 were consistently ~20–50% lower than that of SHARP, no statistically significant differences were found between the 24-hr averages for FRM and SHARP. Orthogonal regression (OR) equations derived from FRM and TEOM₄₀ were used to adjust the TEOM₄₀ (i.e., TEOM_adj) and improve its agreement with FRM, particularly for the cold season. The 12-year-long hourly TEOM_adj measurements from 1999 to 2011 based on the OR equations between SHARP and TEOM₄₀ were derived from the 2-year (2011–2013) collocated measurements. The trend analysis combining both TEOM_adj and SHARP measurements showed a statistically significant decrease in PM_2.5 concentrations with a seasonal slope of ?0.15 μg m^?3 yr^?1 from 1999 to 2014.Implications: Consistency in PM_2.5 measurements are needed for trend analysis. Collocated comparison among the three PM_2.5 monitors demonstrated the difference between FRM and TEOM, as well as between SHARP and TEOM. The orthogonal regressions equations can be applied to correct historical TEOM data to examine long-term trends within the network.     

Product Guide/1982

Abstract

An efficient venturi scrubber system making use of heterogeneous nucleation and condensational growth of particles was designed and tested to remove fine particles from the exhaust of a local scrubber where residual SiH₄ gas was abated and lots of fine SiO₂ particles were generated. In front of the venturi scrubber, normal-temperature fine-water mist mixes with high-temperature exhaust gas to cool it to the saturation temperature, allowing submicron particles to grow into micron sizes. The grown particles are then scrubbed efficiently in the venturi scrubber. Test results show that the present venturi scrubber system is effective for removing submicron particles. For SiO₂ particles greater than 0.1 μm, the removal efficiency is greater than 80–90%, depending on particle concentration. The corresponding pressure drop is relatively low. For example, the pressure drop of the venturi scrubber is ～15.4 ± 2.4 cm H₂O when the liquid-to-gas ratio is 1.50 L/m³. A theoretical calculation has been conducted to simulate particle growth process and the removal efficiency of the venturi scrubber. The theoretical results agree with the experimental data reasonably well when SiO₂ particle diameter is greater than 0.1 μm.     

Field performance of dichotomous sequential PM air samplers

For over one year, the Environmental Protection Commission of Hillsborough County (EPCHC) in Tampa, Florida, operated two dichotomous sequential particulate matter air samplers collocated with a manual Federal Reference Method (FRM) air sampler at a waterfront site on Tampa Bay. The FRM was alternately configured as a PM_2.5, then as a PM₁₀ sampler. For the dichotomous sampler measurements, daily 24-h integrated PM_2.5 and PM_10–2.5 ambient air samples were collected at a total flow rate of 16.7 l min⁻¹. A virtual impactor split the air into flow rates of 1.67 and 15.0 l min⁻¹ onto PM_10–2.5 and PM_2.5 47-mm diameter PTFE^® filters, respectively. Between the two dichotomous air samplers, the average concentration, relative bias and relative precision were 13.3 μg m⁻³, 0.02% and 5.2% for PM_2.5 concentrations (n=282), and 12.3 μg m⁻³, 3.9% and 7.7% for PM_10–2.5 concentrations (n=282). FRM measurements were alternate day 24-h integrated PM_2.5 or PM₁₀ ambient air samples collected onto 47-mm diameter PTFE^® filters at a flow rate of 16.7 l min⁻¹. Between a dichotomous and a PM_2.5 FRM air sampler, the average concentration, relative bias and relative precision were 12.4 μg m⁻³, −5.6% and 8.2% (n=43); and between a dichotomous and a PM₁₀ FRM air sampler, the average concentration, relative bias and relative precision were 25.7 μg m⁻³, −4.0% and 5.8% (n=102). The PM_2.5 concentration measurement standard errors were 0.95, 0.79 and 1.02 μg m⁻³; for PM₁₀ the standard errors were 1.06, 1.59, and 1.70 μg m⁻³ for two dichotomous and one FRM samplers, respectively, which indicate the dichotomous samplers have superior technical merit. These results reveal the potential for the dichotomous sequential air sampler to replace the combination of the PM_2.5 and PM₁₀ FRM air samplers, offering the capability of making simultaneous, self-consistent determinations of these particulate matter fractions in a routine ambient monitoring mode.     

Forecasting Peak Daily Ozone Levels: Part 2—A Regression with Time Series Errors Model Having a Principal Component Trigger to Forecast 1999 and 2002 Ozone Levels

Abstract

A modified time series approach, a Box-Jenkins regression with time series errors (RTSE) model plus a principal component (PC) trigger, has been developed to forecast peak daily 1-hr ozone (O₃) in real time at the University of Wisconsin-Milwaukee North (UWM-N) during 1999 and 2002. The PC trigger acts as a predictor variable in the RTSE model. It tries to answer the question: will the next day be a possible high O₃ day? To answer this question, three PC trigger rules were developed: (1) Hi-Low Checklist, (2) Discriminant Function Approach I, and (3) Discriminant Function Approach II. Also, a pure RTSE model without including the PC trigger and a persistence approach were tested for comparison. The RTSE model with DFA I successfully forecast the only two 1-hr federal exceedances (124 ppb), one in 1999 and one in 2002. In terms of the O₃ 100-ppb exceedances, 60–80% of the incorrect forecasts occurred with incorrect PC decisions. A few others may have been caused by unexpected O_3- weather relations. When the three approaches used UWM-N data to forecast a 100-ppb exceedance somewhere in the Milwaukee, WI, metropolitan area, their performance was dramatically improved: the false alarm rate was reduced from 0.89 to 0.44, and the probability of detection was increased from 0.71 to 0.88.     

Improving the correlations of ambient tapered element oscillating microbalance PM2.5 data and SHARP 5030 Federal Equivalent Method in Ontario: A multiple linear regression analysis

Tapered element oscillating microbalances equipped with sample equilibration system (TEOM-SES) used by the province of Ontario for the ambient monitoring of PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 µm) in its air quality index (AQI) network were collocated with the Synchronized Hybrid Ambient Real-time Particulate monitor (SHARP 5030) at two monitoring sites for a period spanning approximately 2 years to determine the similarities and differences between the measurement outputs of both instrumental systems. Due mainly to mass loss observed with the TEOM-SES in cooler months, the province has recently switched its PM_2.5 instrumentation at all stations in its monitoring network from the TEOM-SES to the SHARP 5030, which has the U.S. Environmental Protection Agency (EPA) Federal Equivalent Method (FEM) Class III designation. Thus, it has become imperative to develop corrections for historical and future TEOM measurements for the purpose of making them more agreeable to the new FEM method. This work details the authors’ multiple linear regression analyses (MLRAs) of particulate matter data from both instrumental monitors, with the inclusion of operational parameters of physicochemical relevance for both cases of transformations of historical TEOM and TEOM measurements to be made in the future. For historical TEOM data, it was observed that the transformations only benefited winter and fall months. Furthermore, comparisons of the transformed historical TEOM data with PM_2.5 concentrations determined from the Federal Reference Method (FRM) sampler at seven locations within the province showed marked improvements over the observed TEOM-FRM comparisons.

Implications:This work provides a path to correcting the historically observed underreporting of particulate mass in winter and fall in Ontario by making the TEOM-based continuous data resemble the new FEM outputs (in this case, more SHARP-like). It is possible that the transformation of mainly winter TEOM data as detailed in this work may potentially lead to revisions in historical annual composite mean PM_2.5 concentrations and total annual number of days PM_2.5 exceeded the Canada-wide Standard (CWS) metric across the province.     

Systematic Development of an Artificial Neural Network Model for Real-Time Prediction of Ground-Level Ozone in Edmonton,Alberta, Canada

Abstract

Ground-level ozone is a secondary pollutant that has recently gained notoriety for its detrimental effects on human and vegetation health. In this paper, a systematic approach is applied to develop artificial neural network (ANN) models for ground-level ozone (O₃) prediction in Edmonton, Alberta, Canada, using ambient monitoring data for input. The intent of these models is to provide regulatory agencies with a tool for addressing data gaps in ambient monitoring information and predicting O₃ events. The models are used to determine the meteorological conditions and precursors that most affect O₃ concentrations. O₃ time-series effects and the efficacy of the systematic approach are also assessed. The developed models showed good predictive success, with coefficient of multiple determination values ranging from 0.75 to 0.94 for forecasts up to 2 hr in advance. The inputs most important for O₃ prediction were temperature and concentrations of nitric oxide, total hydrocarbons, sulfur dioxide, and nitrogen dioxide.     

Evaluating the performance of a turbulent wet scrubber for scrubbing particulate matter

A turbulent wet scrubber was designed and developed to scrub particulate matter (PM) at micrometer and submicrometer levels from the effluent gas stream of an industrial coal furnace. Experiments were conducted to estimate the particle removal efficiency of the turbulent scrubber with different gas flow rates and liquid heads above the nozzle. Particles larger than 1 µm were removed very efficiently, at nearly 100%, depending upon the flow rate, the concentration of the dust-laden air stream, and the water level in the reservoir. Particles smaller than 1 µm were also removed to a greater extent at higher gas flow rates and for greater liquid heads. Pressure-drop studies were also carried out to estimate the energy consumed by the scrubber for the entire range of particle sizes distributed in the carrier gas. A maximum pressure drop of 217 mm H₂O was observed for a liquid head of 36 cm and a gas flow rate of 7 m³/min. The number of transfer units (NTU) analysis for the efficiencies achieved by the turbulent scrubber over the range of particles also reveals that the contacting power achieved by the scrubber is better except for smaller particles. The turbulent scrubber is more competent for scrubbing particulate matter, in particular PM_2.5, than other higher energy or conventional scrubbers, and is comparable to other wet scrubbers of its kind for the amount of energy spent.

Implications: The evaluation of the turbulent scrubber is done to add a novel scrubber in the list of wet scrubbers for industrial applications, yet simple in design, easy to operate, with better compactness, and with high efficiencies at lower energy consumption. Hence the turbulent scrubber can be used to combat particulate from industrial gaseous effluents and also has a scope to absorb gaseous pollutants if the gases are soluble in the medium used for particles capture.     

Laboratory Evaluation of an Aldehyde Scrubber System Specifically for the Detection of Acrolein

Abstract

We demonstrate the use of an aldehyde scrubber system to resolve isobaric aldehyde/alkene interferences in a proton transfer reaction mass spectrometer (PTR-MS) by selectively removing the aldehydes from the gas mixture without loss of quantitative information for the alkene components. The aldehyde scrubber system uses a bisulfite solution, which scrubs carbonyl compounds from the gas stream by forming water-soluble carbonyl bisulfite addition products, and has been evaluated using a synthetic mixture of acrolein and isoprene. Trapping efficiencies of acrolein exceeded 97%, whereas the transmission efficiency of isoprene was better than 92%. Quantification of the PTR-MS response to acrolein was validated through an intercomparison study that included two derivatization methods, dinitrophenylhydrazine (DNPH) and O-(4-cyano-2-ethoxybenzyl)hydroxylamine (CNET), and a spectroscopic method using a quantum cascade laser infrared absorption spectroscopy (QCL) instrument. Finally, using cigarette smoke as a complex matrix, the acrolein content was assessed using the scrubber and compared with direct QCL-based detection.     

Understanding the Effectiveness of Precursor Reductions in Lowering 8-Hr Ozone Concentrations—Part II. The Eastern United States

Abstract

Analyses of ozone (O₃) measurements in conjunction with photochemical modeling were used to assess the feasibility of attaining the federal 8-hr O₃ standard in the eastern United States. Various combinations of volatile organic compound (VOC) and oxides of nitrogen (NO_x) emission reductions were effective in lowering modeled peak 1-hr O₃ concentrations. VOC emissions reductions alone had only a modest impact on modeled peak 8-hr O₃ concentrations. Anthropogenic NO_x emissions reductions of 46–86% of 1996 base case values were needed to reach the level of the 8-hr standard in some areas. As NO_x emissions are reduced, O₃ production efficiency increases, which accounts for the less than proportional response of calculated 8-hr O₃ levels. Such increases in O₃ production efficiency also were noted in previous modeling work for central California. O₃ production in some urban core areas, such as New York City and Chicago, IL, was found to be VOC-limited. In these areas, moderate NO_x emissions reductions may be accompanied by increases in peak 8-hr O₃ levels. The findings help to explain differences in historical trends in 1- and 8-hr O₃ levels and have serious implications for the feasibility of attaining the 8-hr O₃ standard in several areas of the eastern United States.     

Chemical Composition of Fine Particles in the Tennessee Valley Region

ABSTRACT

Fine particles in the atmosphere have elicited new national ambient air quality standards (NAAQS) because of their potential role in health effects and visibility-reducing haze. Since April 1997, Tennessee Valley Authority (TVA) has measured fine particles (PM_2.5) in the Tennessee Valley region using prototype Federal Reference Method (FRM) samplers, and results indicate that the new NAAQS annual standard will be difficult to meet in this region. The composition of many of these fine particle samples has been determined using analytical methods for elements, soluble ions, and organic and elemental carbon. The results indicate that about one-third of the measured mass is SO₄ ^-2, one-third is organic aerosol, and the remainder is other materials. The fraction of SO₄ ^-2 is highest at rural sites and during summer conditions, with greater proportions of organic aerosol in urban areas throughout the year. Additional measurements of fine particle mass and composition have been made to obtain the short-term variability of fine mass as it pertains to human exposure. Measurements to account for semi-volatile constituents of fine mass (nitrates, semi-volatile organics) indicate that the FRM may significantly under-measure organic constituents. The potentially controllable anthropogenic fraction of organic aerosols is still largely unknown.     

Performance and Diagnostic Evaluation of Ozone Predictions by the Eta-Community Multiscale Air Quality Forecast System during the 2002 New England Air Quality Study

Abstract

A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O₃) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O₃ was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O₃ on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O₃ concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O₃ very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within [H11006]20%. The model reproduced 53.3% of the observed hourly O₃ within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites.The comparison of modeled and observed lidar O₃ vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64 –77% of observed NO₂ photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O₃/nitrogen oxide (NO_x) ratios suggests that the site is mainly under strongly NO_x-sensitive conditions (>53%). It was found that the modeled lower limits of the O₃ production efficiency values (inferred from O₃-CO correlation) are close to the observations.