Steven D. Reynolds

Mathematical modeling of photochemical air pollution—III. Evaluation of the model

Abstract The formulation of a model for predicting the dynamic behavior of chemically reacting air pollutants in an urban atmosphere is presented. The Los Angeles airshed was chosen as the region for initial application of the model. The model development and validation program is divided into three parts: 1. I—Formulation of the model; 2. II—A model and inventory of pollutant emissions; 3. III—Evaluation of the model. In this paper (Part I) we derive the basic equations governing the model, discuss the treatment of meteorological variables (inversion height, wind field, and turbulent eddy diffusivity), present a kinetic mechanism for photochemical smog, and describe the technique employed for numerical integration of the governing partial differential equations for the mean concentrations of carbon monoxide, hydrocarbons, nitric oxide, nitrogen dioxide, and ozone.

Mathematical modeling of photochemical air pollution. II. A model and inventory of pollutant emissions.

Abstract In Part I a model for predicting the dynamic behavior of photochemical air pollution was formulated. To exercise the model, pollutant emissions must be specified as a function of time and location over the region of interest. In this paper (Part II) we present a general methodology for the compilation of a contaminant emissions inventory for an urban area. Particular attention is given to the description of motor vehicle emissions, which constitute the most important single source of pollutants in the region to which the model is applied, the Los Angeles airshed. The model is used to estimate the spatial and temporal distribution of carbon monoxide, hydrocarbon, and nitrogen oxide emissions in the Los Angeles airshed in Autumn 1969.

The Role of Grid-Based, Reactive Air Quality Modeling in Policy Analysis: Perspectives and Implications, as Drawn from a Case Study

During the 1980s the National Acid Precipitation Assessment Program (NAPAP) supported the development of the Regional Acid Deposition Model (RADM). While sound performance evaluation was to be a part of the development process, concern existed that policy makers may hold overly optimistic expectations of RADM’s performance, and of the time to RADM’s acceptability for unrestricted use. A primary objective of this study is to gain an improved understanding of the role of quality of performance in determining a model’s acceptability and usefulness to the policy maker, and thus to aid in developing soundly-based expectations of the modeling process. The vehicle for pursuing this objective is examining the historical evolution of the Urban Airshed Model (UAM), a grid-based photochemical model that is similar in basic formulation to RADM, and its application to policy analysis in the South Coast Air Basin (SOCAB) of California.

Delineation of the Influence of Major Emissions Regions on the Annual Acidic Deposition at Sensitive Areas

One central question for atmospheric processes research of the National Acid Precipitation Assessment Program (NAPAP) of the United States has been identification of the fraction of species deposition at a sensitive receptor region that is attributable to a particular emissions source region. The concern centers on distinguishing between effects of distant and local sources of emissions on sensitive ecological regions. The prevalent means for distinguishing the effects of sources is to develop source-receptor relationships. However, the debate about the nonlinearity in the atmospheric processes raises doubts about the ability of linear models to realistically portray source-receptor relationships. Also, questions have been raised regarding the loss in precision of describing three-dimensional transport (as compared to use of dynamic models) due to the lack of resolution inherent in interpolation techniques and due to the exclusion of cloud-influenced vertical transport.

A Conceptual Framework for Evaluating the Performance of Grid-Based Photochemical Air Quality Simulation Models

Performance evaluation efforts generally do not adequately challenge photochemical air quality simulation models. Consequently, compensatory (or offsetting) errors in a model may remain undetected even though the model appears to perform acceptably. In this paper we discuss the principles and practice of “stressful testing”, devised to minimize the probability of accepting a flawed model for use.

Estimation of the Annual Contribution of US Sulfur Emissions to Canadian Acidic Deposition and Vice Versa

The determination of a source-receptor relationship for acidic deposition has been one of the major thrusts of the National Acid Precipitation Assessment Program (NAPAP). The specific source-receptor relationship considered here is that showing the relative contribution of U.S. and Canadian sulfur emissions to deposition amounts. The results presented here are from a comprehensive Eulerian mathematical modeling system consisting of a core model, the Regional Acid Deposition Model (RADM) (Chang et al., 1987; Chang et al., 1990), a meteorological processor, MM4, (Seaman, 1989) and several interpretative tools. RADM consists of components which represent various atmospheric processes including: gas-phase photochemical production of ozone, hydrogen peroxide, and other oxidants from emissions of reactive organic compounds and oxides of nitrogen; oxidation of sulfur dioxide in both clear air and within cloud water; three-dimensional transport, mixing by clouds, and wet and dry deposition. The meteorological processor, MM4, which provides the information required as input for RADM is a mesoscale numerical weather prediction model using four-dimensional data assimilation (Seaman et al., 1990). The RADM is used episodically, that is, emissions and meteorological information for a specific weather event of three days duration are used for simulating the air concentration of important photochemical oxidants and other chemical species as well as the accumulated material which is deposited to the surface. The output files are then archived for future analysis using the interpretative tools. For the present discussion, the tool of choice is the Tagged Sulfur Engineering Model (TSEM).