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Biomedical subjects

Armistead G Russell

Publications and source records attributed to Armistead G Russell.

11 recordsLinked to original sources
PubMed2006

Control strategy optimization for attainment and exposure mitigation: case study for ozone in Macon, Georgia.

Implementation of more stringent 8-hour ozone standards has led the U.S. Environmental Protection Agency to designate nonattainment status to 474 counties nationwide, many of which had never previously violated air quality standards. As states select emission control measures to achieve attainment in these regions, their choices pose significant implications to local economies and the health of their citizens. Considering a case study of one such nonattainment region, Macon, Georgia, we develop a menu of potential controls that could be implemented locally or in neighboring parts of the state. The control menu offers the potential to control about 20-35% of ozone precursor emissions in most Georgia regions, but marginal costs increase rapidly beyond 15-20%. We link high-order ozone sensitivities with the control menu to identify cost-optimized strategies for achieving attainment and for alternative goals such as reducing spatially averaged or population-weighted ozone concentrations. Strategies targeted toward attainment of Macon ozone would prioritize local reductions of nitrogen oxides, whereas controls in the more densely populated Atlanta region are shown to be more effective for reducing statewide potential population exposure to ozone. A U.S. EPA-sanctioned approach for demonstrating ozone attainment with photochemical models is shown to be highly dependent on the choice of a baseline period and may not foster optimal strategies for assuring attainment and protecting human health.

Air Pollution↗
PubMed2006

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains: Part II. Fine particulate matter and visibility.

As part of the Southern Appalachian Mountains Initiative, a comprehensive air quality modeling system was developed to evaluate potential emission control strategies to reduce atmospheric pollutant levels at the Class I areas located in the Southern Appalachian Mountains. Six multiday episodes between 1991 and 1995 were simulated, and the skill of the modeling system was evaluated. Two papers comprise various parts of this study. Part I details the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. This paper (part II) addresses issues involved with modeling particulate matter (PM) and its relationship to visibility. For most of the episodes, the fractional error was approximately 50% or less for the major constituents of the fine PM (i.e., sulfate [SO4] and organics) in the region. The mean normalized errors and fractional errors are generally larger for the NO3 and soil components, but these components are relatively small. Variations in modeling bias with pollutant levels were also examined. The model showed a systematic overestimation for low levels and an underestimation for high levels for most PM species. For ammonium, the model showed better performance at lower SO4 concentrations when the measured SO4 was assumed to be completely neutralized (ammonium sulfate) and better performance at higher SO4 concentrations when the partially neutralized (ammonium bisulfate) assumption was made. The contributions of various components of PM to reductions in visibility were also calculated; SO4 was found to be the major contributor.

Air Pollutants↗
PubMed2006

Effects of instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, Georgia.

Data from the U.S. Environmental Protection Agency Air Quality System, the Southeastern Aerosol Research and Characterization database, and the Assessment of Spatial Aerosol Composition in Atlanta database for 1999 through 2002 have been used to characterize error associated with instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, GA. These data are being used in time series epidemiologic studies in which associations of acute respiratory and cardiovascular health outcomes and daily ambient air pollutant levels are assessed. Modified semivariograms are used to quantify the effects of instrument precision and spatial variability on the assessment of daily metrics of ambient gaseous pollutants (SO2, CO, NOx, and O3) and fine particulate matter ([PM2.5] PM2.5 mass, sulfate, nitrate, ammonium, elemental carbon [EC], and organic carbon [OC]). Variation because of instrument imprecision represented 7-40% of the temporal variation in the daily pollutant measures and was largest for the PM2.5 EC and OC. Spatial variability was greatest for primary pollutants (SO2, CO, NOx, and EC). Population-weighted variation in daily ambient air pollutant levels because of both instrument imprecision and spatial variability ranged from 20% of the temporal variation for O3 to 70% of the temporal variation for SO2 and EC. Wind

Air Pollutants↗
PubMed2005

Gaseous and particulate emissions from prescribed burning in Georgia.

Prescribed burning is a significant source of fine particulate matter (PM2.5) in the southeastern United States. However, limited data exist on the emission characteristics from this source. Various organic and inorganic compounds both in the gas and particle phase were measured in the emissions of prescribed burnings conducted at two pine-dominated forest areas in Georgia. The measurements of volatile organic compounds (VOCs) and PM2.5 allowed the determination of emission factors for the flaming and smoldering stages of prescribed burnings. The VOC emission factors from smoldering were distinctly higher than those from flaming except for ethene, ethyne, and organic nitrate compounds. VOC emission factors show that emissions of certain aromatic compounds and terpenes such as alpha and beta-pinenes, which are important precursors for secondary organic aerosol (SOA), are much higher from active prescribed burnings than from fireplace wood and laboratory open burning studies. Levoglucosan is the major particulate organic compound (POC) emitted for all these studies, though its emission relative to total organic carbon (mg/g OC) differs significantly. Furthermore, cholesterol, an important fingerprint for meat cooking, was observed only in our in situ study indicating a significant release from the soil and soil organisms during open burning. Source apportionment of ambient primary fine particulate OC measured at two urban receptor locations 20-25 km downwind yields 74 +/- 11% during and immediately after the burns using our new in situ profile. In comparison with the previous source profile from laboratory simulations, however, this OC contribution is on average 27 +/- 5% lower.

Air Pollutants↗
PubMed2005

Nonlinear response of ozone to emissions: source apportionment and sensitivity analysis.

For secondary air pollutants, precursor emissions may impact concentrations in nonlinear and interdependent manners. We explore the nonlinear responses of one such pollutant, ozone, to emissions of its precursors, nitrogen oxides (NOx) and volatile organic compounds. Modeling is conducted for a high ozone episode in the southeastern United States, applying a second-order direct sensitivity method in a regional air quality model. As applied here, the sensitivity method neglects most aerosol and aqueous chemistry processes. Inclusion of second-order sensitivities is shown to enable accurate characterization of response to large perturbations in emissions. An index is introduced to characterize the nonlinearity of ozone response to NOx emitted from each source region. Nonlinearity is found to increase with the tonnage and emission density of the source region. Interactions among the impacts of emission sources are shown to lead to discrepancies between source contribution attributed to an ensemble of emitters and the sum of the contributions attributed to each component. A method is introduced for applying these "cross-sensitivity" interactions to assess the uncertainty of sensitivity and source apportionment estimates arising from uncertainty in an emissions inventory. For ozone response to NOx, underestimates in emission rates lead to underprediction of total source contribution but overprediction of per-ton sensitivity.

Air Pollutants↗
PubMed2005

Optimization-based source apportionment of PM2.5 incorporating gas-to-particle ratios.

A modified approach to PM2.5 source apportionment is developed, using source indicative SO2/PM2.5, CO/PM2.5, and NOx/PM2.5 ratios as constraints, in addition to the commonly used particulate-phase source profiles. Additional information from using gas-to-particle ratios assists in reducing collinearity between source profiles, a problem that often limits the source-identification capabilities and accuracy of traditional receptor models. This is especially true in the absence of speciated organic carbon measurements. In the approach presented here, the solution is based on a global optimization mechanism, minimizing the weighted error between apportioned and ambient levels of PM2.5 components, while introducing constraints on calculated source contributions that ensure that the ambient gas-phase pollutants (SO2, CO, and NOy) are reasonable. This technique was applied to a 25-month dataset of daily PM2.5 measurements (total mass and composition) at the Atlanta Jefferson Street SEARCH site. Results indicate that this technique was able to split the contributions of mobile sources (gasoline and diesel vehicles) more accurately than particulate-phase source apportionment methods. Furthermore, this technique was able to better quantify the direct contribution (primary PM2.5) of coal-fired power plants to ambient PM2.5 levels.

Air Pollutants↗
PubMed2005

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains. Part I: hourly and seasonal ozone.

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI's assessment.

Appalachian Region↗
PubMed2004

Ozone formation potential of organic compounds in the Eastern United States: a comparison of episodes, inventories, and domains.

Direct sensitivity analysis is applied for 3-D assessment of ozone reactivity (or ozone formation potential) in the Eastern United States. A detailed chemical mechanism (SAPRC-99) is implemented in a multiscale air quality model to calculate the reactivity of 32 explicit and 9 lumped compounds. Simulations are carried out for two different episodes and two different emission scenarios. While absolute reactivities of VOCs show a great deal of spatial variability, relative reactivities (normalized to the reactivity of a base mixture) produce a significantly more homogeneous field. Three types of domain-wide relative reactivity metrics are formed for 1-h and 8-h averaging intervals. In general, ozone reactivity metrics (with the exception of those based on daily peak ozone) are fairly robust and consistent between different episodes or emission scenarios. The 3-D metrics also show fairly similar rankings for VOC reactivity when compared to the box model scales. However, the 3-D metrics have a noticeably narrower range for species reactivities, as they result in lower reactivity for some of the more reactive, radical-producing VOCs (especially aldehydes). As expected, episodes and emission scenarios with less radical availability have higher absolute reactivities for all species and higher relative reactivities for the more radical-producing species. Finally, comparing the results with those from a different domain (central California) shows that relative reactivity metrics are comparable over these two significantly different domains.

Air Pollutants↗
PubMed2003

High-order, direct sensitivity analysis of multidimensional air quality models.

A direct sensitivity analysis technique is extended to calculate higher-order sensitivity coefficients in three-dimensional air quality models. The time evolution of sensitivity coefficients of different order is followed alongside that of the concentrations. Calculation of higher-order sensitivity coefficients requires few modifications to the original (first-order) sensitivity modules and is carried out efficiently and with minimal computational overhead. The modeling results (first-, second-, and third-order sensitivity coefficients) for an ozone episode in central California are shown and discussed. Second-order sensitivity coefficients of ozone concentration with respect to domain-wide NO emissions show reasonable agreement with brute-force results and exhibit less noisy behavior. By using second-order sensitivity coefficients the nonlinear responses are better captured and described. For a Taylor series projection from the base case, including the second-order term improves the accuracy. In general, higher-order sensitivity analysis shows a noticeable improvement in terms of accuracy over the conventional first-order analysis. Of particular interest, second-order sensitivity analysis is better equipped to address the nonlinear behavior around the peak ozone in NO(x)-rich plumes.

Air Pollutants↗
PubMed2003

Evaluation of incremental reactivity and its uncertainty in Southern California.

The incremental reactivity (IR) and relative incremental reactivity (RIR) of carbon monoxide and 30 individual volatile organic compounds (VOC) were estimated for the South Coast Air Basin using two photochemical air quality models: a 3-D, grid-based model and a vertically resolved trajectory model. Both models include an extended version of the SAPRC99 chemical mechanism. For the 3-D modeling, the decoupled direct method (DDM-3D) was used to assess reactivities. The trajectory model was applied to estimate uncertainties in reactivities due to uncertainties in chemical rate parameters, deposition parameters, and emission rates using Monte Carlo analysis with Latin hypercube sampling. For most VOC, RIRs were found to be consistent in rankings with those produced by Carter using a box model. However, 3-D simulations show that coastal regions, upwind of most of the emissions, have comparatively low IR but higher RIR than predicted by box models for C4-C5 alkenes and carbonyls that initiate the production of HOx radicals. Biogenic VOC emissions were found to have a lower RIR than predicted by box model estimates, because emissions of these VOC were mostly downwind of the areas of primary ozone production. Uncertainties in RIR of individual VOC were found to be dominated by uncertainties in the rate parameters of their primary oxidation reactions. The coefficient of variation (COV) of most RIR values ranged from 20% to 30%, whereas the COV of absolute incremental reactivity ranged from about 30% to 40%. In general, uncertainty and variability both decreased when relative rather than absolute reactivity metrics were used.

Air Pollutants↗