Effects of the NO(x) SIP Call program on ozone levels in New York.

This study looks at the effects of the major U.S. Environmental Protection Agency (EPA)-mandated ozone (O3) control program implemented by New York State Department of Environmental Conservation since 2003. The study is based on ozone concentrations from eight sites representative of a range of geographic and land use conditions in the period 1995-2012. All sites show lower sample maximums of daily maximum 8-hr ozone concentrations. For example, in the period 2003-2012 compared to the period 1995-2002, the New York Botanical Gardens site experienced an 81%, 56%, and 25% drop in the number of days with daily maximum 8-hr ozone exceeding 85 ppb, 75 ppb, and 65 ppb respectively. For the same site, the frequency of hot days (with temperatures above 32 degrees C) was about the same in both periods. However, a hot day from the period 1995-2002 was 2.1 times more likely to have daily maximum 8-hr ozone exceeding 75 ppb than a hot day in the period 2003-2012. Other sites showed similar results. A comparison of the underlying distributions of ozone and temperature indicates a broad-based reduction of expected ozone values and variability, confirmed as significant by bootstrap tests. Most of the sites exhibit significant albeit small (30%) increases in expected values of maximum afternoon temperatures, favoring increased ozone production. The contrary actually happened. Consequently, trends in observed concentrations are caused by reduced ozone production rather than by favorable meteorological conditions. The study findings are consistent with previous studies that relied on different data sets and analysis methods. Taken together they demonstrate the effectiveness of the NO(x) emission reduction programs in the New York state.

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 sensitivity and reliability of the relative reduction factor approach in the development of 8-hr ozone attainment plans.

The updated regulatory framework for demonstrating that future 8-hr ozone (O3) design values will be at or below the National Ambient Air Quality Standards (NAAQS) provides guidelines for the development of a State Implementation Plan (SIP) that includes methods based on photochemical modeling and analytical techniques. One of the suggested approaches is the relative reduction factor (RRF) for estimating the efficacy of emission reductions. In this study, the sensitivity of model-predicted responses towards emission reductions to the choice of meteorology and chemical mechanisms was examined. While the different modeling simulations generally were found to be in agreement on whether predicted future-year design values would be above or below the NAAQS for 8-hr O3 at a majority of the monitoring locations in the eastern United States, differences existed for a small percentage of monitors (approximately 6.4%). Another issue investigated was the ability of the attainment demonstration procedure to predict changes in monitored O3 design values. A retrospective analysis was performed by comparing predicted O3 design values from model simulations using emission estimates for 1996 and 2001 with monitored O3 design values for 2001. Results indicated that an average gross error of approximately 5 ppb was present between modeled and observed design values and that, at approximately 27% of all sites, model-predicted and observed design values disagreed as to whether the design value was above or below the NAAQS. Retrospective analyses such as the one presented in this study can provide valuable insights into the strengths and limitations of modeling and analysis techniques used to predict future design values over time periods of a decade or more for the purpose of developing SIPs. Furthermore, such analyses could provide avenues for improvement and added confidence in the use of the RRF approach for addressing attainment of the NAAQS.

Assessing ozone-related health impacts under a changing climate.

Climate change may increase the frequency and intensity of ozone episodes in future summers in the United States. However, only recently have models become available that can assess the impact of climate change on O3 concentrations and health effects at regional and local scales that are relevant to adaptive planning. We developed and applied an integrated modeling framework to assess potential O3-related health impacts in future decades under a changing climate. The National Aeronautics and Space Administration-Goddard Institute for Space Studies global climate model at 4 degrees x 5 degrees resolution was linked to the Penn State/National Center for Atmospheric Research Mesoscale Model 5 and the Community Multiscale Air Quality atmospheric chemistry model at 36 km horizontal grid resolution to simulate hourly regional meteorology and O3 in five summers of the 2050s decade across the 31-county New York metropolitan region. We assessed changes in O3-related impacts on summer mortality resulting from climate change alone and with climate change superimposed on changes in O3 precursor emissions and population growth. Considering climate change alone, there was a median 4.5% increase in O3-related acute mortality across the 31 counties. Incorporating O3 precursor emission increases along with climate change yielded similar results. When population growth was factored into the projections, absolute impacts increased substantially. Counties with the highest percent increases in projected O3 mortality spread beyond the urban core into less densely populated suburban counties. This modeling framework provides a potentially useful new tool for assessing the health risks of climate change.

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.