Impact of biogenic emission uncertainties on the simulated response of ozone and fine particulate matter to anthropogenic emission reductions.

The role of emissions of volatile organic compounds and nitric oxide from biogenic sources is becoming increasingly important in regulatory air quality modeling as levels of anthropogenic emissions continue to decrease and stricter health-based air quality standards are being adopted. However, considerable uncertainties still exist in the current estimation methodologies for biogenic emissions. The impact of these uncertainties on ozone and fine particulate matter (PM2.5) levels for the eastern United States was studied, focusing on biogenic emissions estimates from two commonly used biogenic emission models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System (BEIS). Photochemical grid modeling simulations were performed for two scenarios: one reflecting present day conditions and the other reflecting a hypothetical future year with reductions in emissions of anthropogenic oxides of nitrogen (NOx). For ozone, the use of MEGAN emissions resulted in a higher ozone response to hypothetical anthropogenic NOx emission reductions compared with BEIS. Applying the current U.S. Environmental Protection Agency guidance on regulatory air quality modeling in conjunction with typical maximum ozone concentrations, the differences in estimated future year ozone design values (DVF) stemming from differences in biogenic emissions estimates were on the order of 4 parts per billion (ppb), corresponding to approximately 5% of the daily maximum 8-hr ozone National Ambient Air Quality Standard (NAAQS) of 75 ppb. For PM2.5, the differences were 0.1-0.25 microg/m3 in the summer total organic mass component of DVFs, corresponding to approximately 1-2% of the value of the annual PM2.5 NAAQS of 15 microg/m3. Spatial variations in the ozone and PM2.5 differences also reveal that the impacts of different biogenic emission estimates on ozone and PM2.5 levels are dependent on ambient levels of anthropogenic emissions.

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.

Rethinking the assessment of photochemical modelin systems in air quality planning applications.

The U.S. Environmental Protection Agency provides guidelines for demonstrating that future 8-hr ozone (O3) design values will be at or below the National Ambient Air Quality Standards on the basis of the application of photochemical modeling systems to simulate the effect of emission reductions. These guidelines also require assessment of the model simulation against observations. In this study, we examined the link between the simulated relative responses to emission reductions and model performance as measured by operational evaluation metrics, a part of the model evaluation required by the guidance, which often is the cornerstone of model evaluation in many practical applications. To this end, summertime O3 concentrations were simulated with two modeling systems for both 2002 and 2009 emission conditions. One of these two modeling systems was applied with two different parameterizations for vertical mixing. Comparison of the simulated base-case 8-hr daily maximum O3 concentrations showed marked model-to-model differences of up to 20 ppb, resulting in significant differences in operational model performance measures. In contrast, only relatively minor differences were detected in the relative response of O3 concentrations to emission reductions, resulting in differences of a few ppb or less in estimated future year design values. These findings imply that operational model evaluation metrics provide little insight into the reliability of the actual model application in the regulatory setting (i.e., the estimation of relative changes). In agreement with the guidance, it is argued that more emphasis should be placed on the diagnostic evaluation of O3-precursor relationships and on the development and application of dynamic and retrospective evaluation approaches in which the response of the model to changes in meteorology and emissions is compared with observed changes. As an example, simulated relative O3 changes between 1995 and 2007 are compared against observed changes. It is suggested that such retrospective studies can serve as the starting point for targeted diagnostic studies in which individual aspects of the modeling system are evaluated and refined to improve the characterization of observed changes.

An assessment of the emissions inventory processing systems EMS-2001 and SMOKE in grid-based air quality models.

In the United States, emission processing models such as Emissions Modeling System-2001 (EMS-2001), Emissions Preprocessor System-Version 2.5 (EPS2.5), and the Sparse Matrix Operator Kernel Emissions (SMOKE) model are currently being used to generate gridded, hourly, speciated emission inputs for urban and regional-scale photochemical models from aggregated pollutant inventories. In this study, two models, EMS-2001 and SMOKE, were applied with their default internal data sets to process a common inventory database for a high ozone (O3) episode over the eastern United States using the Carbon Bond IV (CB4) chemical speciation mechanism. A comparison of the emissions processed by these systems shows differences in all three of the major processing steps performed by the two models (i.e., in temporal allocation, spatial allocation, and chemical speciation). Results from a simulation with a photochemical model using these two sets of emissions indicate differences on the order of +/- 20 ppb in the predicted 1-hr daily maximum O3 concentrations. It is therefore critical to develop and implement more common and synchronized temporal, spatial, and speciation cross-reference systems such that the processes within each emissions model converge toward reasonably similar results. This would also help to increase confidence in the validity of photochemical grid model results by reducing one aspect of modeling uncertainty.

Assessing the effects of transboundary ozone pollution between Ontario, Canada and New York, USA.

We investigated the effects of transboundary pollution between Ontario and New York using both observations and modeling results. Analysis of the spatial scales associated with ozone pollution revealed the regional and international character of this pollutant. A back-trajectory-clustering methodology was used to evaluate the potential for transboundary pollution trading and to identify potential pollution source regions for two sites: CN tower in Toronto and the World Trade Center in New York City. Transboundary pollution transport was evident at both locations. The major pollution source areas for the period examined were the Ohio River Valley and Midwest. Finally, we examined the transboundary impact of emission reductions through photochemical models. We found that emissions from both New York and Ontario were transported across the border and that reductions in predicted O3 levels can be substantial when emissions on both sides of the border are reduced.

An evaluation of the UAM-V predicted concentrations of carbon monoxide and reactive nitrogen compounds over the eastern United States during summer 1995.

While there is a clear need to evaluate a photochemical model's ability in predicting not only the concentrations of O3, but also precursors and other trace species, many previous studies have focused only on the assessment of During the 1995 summer season, in addition to the routine monitoring of criteria pollutants, several research-oriented monitoring campaigns were conducted over the eastern United States, providing an extensive database of reactive nitrogen compounds, CO, and speciated hydrocarbon data. In this study, we examine the ability of a photochemical modeling system, RAMS/ UAM-V, to reproduce the measured concentrations of CO, NO2, and NOy over the region during the summer of 1995. The results demonstrate that there is agreement between modeled and measured seasonal average concentrations of NO2, both at the routine and research monitors. The same is true for NOy, but to a lesser degree. However, the model is found to significantly underpredict CO for the routine monitors in comparison to the research monitors.