James M. Godowitch

Modeling analyses of the effects of changes in nitrogen oxides emissions from the electric power sector on ozone levels in the eastern United States.

Abstract In this paper, we examine the changes in ambient ozone concentrations simulated by the Community Multiscale Air Quality (CMAQ) model for summer 2002 under three different nitrogen oxides (NOx) emission scenarios. Two emission scenarios represent best estimates of 2002 and 2004 emissions; they allow assessment of the impact of the NOx emissions reductions imposed on the utility sector by the NOx State Implementation Plan (SIP) Call. The third scenario represents a hypothetical rendering of what NOx emissions would have been in 2002 if no emission controls had been imposed on the utility sector. Examination of the modeled median and 95th percentile daily maximum 8-hr average ozone concentrations reveals that median ozone levels estimated for the 2004 emission scenario were less than those modeled for 2002 in the region most affected by the NOx SIP Call. Comparison of the “no-control” with the “2002” scenario revealed that ozone concentrations would have been much higher in much of the eastern United States if the utility sector had not implemented NOx emission controls; exceptions occurred in the immediate vicinity of major point sources where increased NO titration tends to lower ozone levels.

Relevance of mixed layer scaling for daytime dispersion based on raps and other field programs

Abstract A brief review and assessment of field measurement programs that provide data for mixed layer diffusion research is presented. The majority of programs emphasize either the meteorological aspects of the mixed layer or plume characterization. Few programs are available that provide the complimentary blend of plume and appropriate meteorological measurements needed to adequately validate mixed layer diffusion theory. Three major U.S. EPA (Environmental Protection Agency) field programs that provide databases for model development and validation of mixed layer diffusion processes are described and discussed in more detail. The Regional Air Pollution Study (RAPS) focused on measurements of surface and mixed layer turbulent transport processes in the urban environment. The Tennessee Plume Study (TPS) obtained a database with coincident measurement of boundary layer turbulent structure and plume dispersion for a large coal-fired power plant in nonuniform terrain over the diurnal cycle. The North East Regional Oxidant Study (NEROS) obtained data on transport and dispersion of regional air mass along with supporting documentation on the spatial variations of mixed layer depths, vertical turbulent transport processes, cloud fluxes, energy budget and synoptic conditions. A design feature common throughout these experimental programs, but primarily in the RAPS and TPS, was the provision to study significant land-use scale variations and processes which influence the diffusion process. Current similarity predictions of the relevant turbulent parameters are assessed in this context. Additionally, the role of convective clouds rooted within the mixed layer in pollution dispersion as a consequence of mixed layer processes is briefly described.

Impact of Inherent Meteorology Uncertainty on Air Quality Model Predictions

It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, meteorology and emissions. When using air quality models for decision making, it is important to understand how uncertainties in these inputs affect the simulated concentrations. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. Most studies explore this uncertainty by running different meteorological models or the same model with different physics options and in some cases combinations of different meteorological and air quality models. While these have been shown to be useful techniques in some cases, we present a technique that leverages the initial condition perturbations of a weather forecast ensemble, namely, the Short-Range Ensemble Forecast system to drive the four-dimensional data assimilation in the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) model with a key focus being the response of ozone chemistry and transport. Results confirm that a sizable spread in WRF solutions, including common weather variables of temperature, wind, boundary layer depth, clouds, and radiation, can cause a relatively large range of ozone-mixing ratios. Pollutant transport can be altered by hundreds of kilometers over several days. Ozone-mixing ratios of the ensemble can vary as much as 10–20 ppb or 20–30% in areas that typically have higher pollution levels.

Evaluating Regional-Scale Air Quality Models

Numerical air quality models are being used to understand the complex interplay among emission loading, meteorology, and atmospheric chemistry leading to the formation and accumulation of pollutants in the atmosphere. A model evaluation framework is presented here that considers several types of approaches, referred to here as the operational evaluation, diagnostic evaluation, dynamic evaluation, and probabilistic evaluation. The operational evaluation is used to reveal the overall performance of the model, and diagnostic evaluation approaches are then used to identify what processes and/or inputs significantly influence the predictted concentrations and whether they are simulated correctly. Dynamic evaluation entails assessing a model’s ability to reproduce observed changes in pollutant concentrations stemming from changes in weather and emissions. Probabilistic evaluation approaches will provide the confidence that can be placed on model results for air quality management or forecasting applications. Here, we present example results from several different model evaluation studies that consider questions related to the operational, diagnostic, and dynamic evaluation of a model, and discuss their complementary goals toward model improvements and characterization of model performance.

Chapter 2.10 Modeling assessment of the impact of nitrogen oxides emission reductions on ozone air quality in the Eastern United States: Offsetting increases in energy use

Abstract A photochemical air quality model was used to evaluate the impact of a series of NOx control rules on ozone air quality in the eastern U.S. Thanks to the acid rain program and the NOx SIP Call, emission rates of NOx (mass NOx/energy content of fuel used) from industrial point sources have declined dramatically since 1997. Model simulations were performed with three emission scenarios: 2002 emissions, 2004 emissions, and a ‘no control’ scenario. The latter simulates conditions that would have existed in 2002 had new NOx emission controls not been imposed. All scenarios used 2002 meteorology. Controls lead to reductions of NOx emissions in 2002 and 2004 to roughly two thirds and one third of their 1997 levels, respectively. In response to these emission changes, the model predicted that maximun 8-h average ozone concentrations would have decreased from 3% to 8% between 2002 and 2004 given 2002 meteorolgy. The absence of control would have led to considerably higher ozone levels in most of the eastern U.S., with exceptions occurring in the vicinity of point sources, regions that would have experienced lower ozone levels thanks to a more intense titration process.