Carlos Cardelino

Ozone precursor relationships in the ambient atmosphere

The concentrations of ozone, nitrogen oxides, and nonmethane hydrocarbons measured near the surface in a variety of urban, suburban, rural, and remote locations are analyzed and compared in order to elucidate the relationships between ozone, its photochemical precursors, and the sources of these precursors. While a large gradient is found among remote, rural, and urban/suburban nitrogen oxide concentrations, the total hydrocarbon reactivity in all continental locations is found to be comparable. Apportionment of the observed hydrocarbon species to mobile and stationary anthropogenic sources and biogenic sources suggests that present-day emission inventories for the United States underestimate the size of mobile emissions. The analysis also suggests a significant role for biogenic hydrocarbon emissions in many urban/suburban locations and a dominant role for these sources in rural areas of the eastern United States. As one moves from remote locations to rural locations and then from rural to urban/suburban locations, ozone and nitrogen oxide concentrations tend to increase in a consistent manner while total hydrocarbon reactivity does not.

An Observation-Based Model for Analyzing Ozone Precursor Relationships in the Urban Atmosphere

An Observation-Based Model (OBM) is described, which uses in-situ atmospheric observations to determine the sensitivity of ozone concentrations in an urban atmosphere to changes in the emissions of ozone precursors (i.e., volatile organic compounds and nitrogen oxides). The model is formulated following the concept of Relative Incremental Reactivity (RIR) developed by Carter and Atkinson. In the OBM, however, observed concentrations rather than emission inventories are used to drive the photochemical simulations and thereby ensure that the calculations are carried out for the proper mix of nitrogen oxides and volatile organic compounds. From these calculations, a series of sensitivity factors, or RIRs, are inferred that can be used to (1) determine whether reducing emissions of nitrogen oxide or emissions of hydrocarbons would be most effective in abating ozone in a given urban area, and (2) identify the most critical subset of hydrocarbons present in an urban atmosphere causing ozone exceedances. Because the OBM is relatively easy and inexpensive to operate and makes use of data that are increasingly available, it can be used to analyze a wide array of ozone episodes and, thus, could prove to be a relatively cost-effective tool for the analysis of ozone precursor relationships in an urban atmosphere. On the other hand, because the OBM is diagnostic rather than prognostic, it cannot be used in a predictive mode to estimate exactly how much emission reduction is needed to reduce ozone concentrations. For this reason, the OBM should be viewed as a complement to, rather than a substitute for, more sophisticated gridded, emission-based models. To illustrate the characteristics of the OBM and to demonstrate its applicability, we first compare the results of the OBM to those obtained from a series of simulations of the Atlanta metropolitan area using the Urban Airshed Model (UAM), a three-dimensional Eulerian grid model. The OBM is then used to analyze a dataset obtained from the 1990 Atlanta Ozone Study, an EPA field sampling program conducted during the summer of 1990. Because of limitations and potential flaws in the 1990 Atlanta dataset, the results of this OBM analysis are largely illustrative rather than definitive. Nevertheless, a few important issues are elucidated by the analysis. These include (1) the importance of accounting for biogenic hydrocarbons produced from urban vegetation; (2) the potential flaw in using early-morning VOC-to-NOx ratios to infer whether ozone production is limited by VOC or NOx; (3) the critical need for high-sensitivity nitrogen oxide measurements to quantify the sub-ppbv concentrations of NO during the afternoon hours; and (4) the need to consider a number of individual ozone episodes in studying an urban atmosphere because of the possibility that the degree of VOC- and NOx-limitation may vary from one episode to another.

Geostatistical analysis and visualization of hourly ozone data

Abstract The recent recognition of the detrimental impacts of near-surface ozone concentrations has led to the establishment of regionwide monitoring networks. The size of the collected data sets, as well as the presence of pseudorandom patterns in measured ozone concentrations, has motivated the use of advanced techniques for data analysis and presentation. In this work, a series of geostatistical and visualization procedures are applied to the analysis of hourly ozone measurements collected from 29 stations in the southeastern United States. The exploratory data analysis and variography clearly confirm the diurnal pattern of ozone fluctuations, and suggest that during daytime hours, local factors are dominant over the ozone production process. In contrast; during evening hours, regional factors and small-scale uneven variations become more dominant in the ozone depletion process. Using the geostatistical technique of cross-validation, results are generated in order to evaluate the rural classification of investigated stations. The findings of these studies indicate that: (1) the non-rural status of near-urban or presumably downwind stations is an hour-specific condition; (2) prevailing wind directions on each day can significantly alter the rural status of presumably upwind sites; and (3) local topography of a site can be an important factor in influencing its rural status during different hours of the day. Geostatistical techniques are shown to be not only useful for optimal mapping and network design, but also can be coupled with visualization tools to generate animated pseudocolored sequential maps. These maps are an efficient means for analysing spatial and temporal patterns of ozone concentrations.

On using inverse methods for resolving emissions with large spatial inhomogeneities

We apply an inverse method to estimate the carbon monoxide emissions in Atlanta, Georgia. The resultant carbon monoxide inventory is unrealistically characterized by temporal oscillations on the frequency of 1 hour. We suspect that the difficulty in deducing the emissions is due to inhomogeneities in the spatial distribution of the emissions. In several controlled experiments we reproduce the oscillations by introducing relatively small errors into the spatial distribution of the emission inventory. In similar experiments with isoprene in which the emissions are more homogeneous, we do not find this problem. These results are discussed in the context of previous inverse studies of carbon monoxide and isoprene.

The application of data from photochemical assessment monitoring stations to the observation-based model

Abstract The observation-based model – a diagnostic model designed to estimate ozone sensitivity to changes in the concentration of volatile organic compounds, nitrogen oxides, and CO – was used to analyze data gathered during the summer of 1995 at three photochemical assessment monitoring sites (PAMS). The sites were located in Washington DC, Bronx, New York, and Houston, Texas, with the first two being categorized as urban/cental city commercial and the latter as industrial/suburban. Our analysis indicated that: (i) natural hydrocarbons (primarily isoprene) represented a significant fraction of the total hydrocarbon reactivity at all three sites and significantly degraded the efficacy of VOC emission reductions as an O3 mitigation strategy; and (ii) afternoon NO concentrations at all three sites typically fell to levels at or below the limit of detection of the PAMS instrumentation and, as a result, it was not possible to determine whether O3 at the sites was more sensitive to reductions in anthropogenic hydrocarbons or nitrogen oxides.

Application of the Urban Airshed Model to forecasting next-day peak ozone concentrations in Atlanta, Georgia.

ABSTRACT Twenty-four to forty-eight-hour ozone air quality forecasts are increasingly being used in metropolitan areas to inform the public about potentially harmful air quality conditions. The forecasts are also behind “ozone action day” programs in which the public and private sectors are encouraged or mandated to alter activities that contribute to the formation of ground-level ozone. Presented here is a low-cost application of the Urban Airshed Model (UAM), an Eulerian 3-dimensional photochemical-transport grid model for generating next-day peak ozone concentration forecasts. During the summer of 1997, next-day peak ozone concentrations in Atlanta, GA, were predicted both by a team of eight forecasters and by the Urban Airshed Model in Forecast Mode (UAM-FM). Results are presented that compare the accuracy of the team and the UAM-FM. The results for the summer of 1997 indicate that the UAM-FM may be a better predictor of peak ozone concentrations when concentrations are high (> 0.095 ppmv), and the team may be a better predictor of ozone concentrations when concentrations are low (< 0.095 ppmv). The UAM-FM is also discussed in the context of other forecasting tools, primarily linear regression models and a no-skill, persistence-based technique.

Inverse modeling of biogenic isoprene emissions

Using current biogenic emission estimates, Urban Airshed Model simulations for Atlanta, Georgia substantially underpredict isoprene concentrations relative to observations. In this work, an inverse method is used to determine the biogenic isoprene emissions for Atlanta that minimize the difference between the model-simulated and the observed isoprene concentrations. The resulting isoprene emissions are 2 to 10 times higher than any of the accepted emission estimates. Overall, the concurrent ozone simulation improved when the biogenic isoprene emissions were increased. These higher isoprene emissions significantly increase the concentration of model-simulated ozone within the plumes of nitrogen oxides emitted from large point sources. These results should be considered when developing control strategies for urban ozone.

Daily variability of motor vehicle emissions derived from traffic counter data

This work studied the daily variability of mobile sources in rural and urban areas, in and around the Atlanta Metropolitan Area. Traffic counter data collected during the 1992 Southern Oxidants Study Atlanta Intensive Study were used to analyze the spatial and temporal distribution of traffic volume. A simple method to study the daily variability of mobile emissions from the different types of urban and rural roads is presented. The method is based on hourly traffic volume data and emission factors and it has been generalized to describe the daily variability of mobile emissions for urban and rural areas and for the whole modeling domain. Implications of this study for improving mobile emission inventories are also discussed.

Ozone predictions in Atlanta, Georgia: analysis of the 1999 ozone season.

ABSTRACT Ozone prediction has become an important activity in many U.S. ozone nonattainment areas. In this study, we describe the ozone prediction program in the Atlanta metropolitan area and analyze the performance of this program during the 1999 ozone-forecasting season. From May to September, a team of 10 air quality regulators, meteorologists, and atmospheric scientists made a daily prediction of the next-day maximum 8-hr average ozone concentration. The daily forecast was made aided by two linear regression models, a 3-dimensional air quality model, and the no-skill ozone persistence model. The teams performance is compared with the numerical models using several numerical indicators. Our analysis indicated that (1) the team correctly predicted next-day peak ozone concentrations 84% of the time, (2) the two linear regression models had a better performance than a 3-dimensional air quality model, (3) persistence was a strong predictor of ozone concentrations with a performance of 78%, and (4) about half of the teams wrong predictions could be prevented with improved meteorological predictions.

The use of survey data to investigate ozone sensitivity to point sources

Abstract During the Southern Oxidants Studys 1992 Atlanta Intensive, a survey was conducted to improve the emission estimates from point sources for the Atlanta metropolitan region. The survey consisted of a questionnaire and a daily activity log for the largest point sources in the region. The point source information was used to compare a 1992 typical summer days emissions with a specific days emissions (10 August 1992). Both emission inventories indicate that about 90% of point source nitrogen oxides (NO x ) emissions were from power plants. Furthermore, our results show that the daily variation of point source NO x emissions during the Intensive Study was mostly due to the emissions from the power plants. The daily variation of NO x emissions with respect to a typical summer day was as much as 24%. Although the day-to-day variability in point source VOC emissions was as much as 28%, their contribution to the total VOC was not significant. Finally, we evaluate the impact of NO x emissions from power plants on ozone concentrations. Air quality model simulations show significantly different ozone concentrations depending on power plant location.