Alan J. Cimorelli

AERMOD: A Dispersion Model for Industrial Source Applications. Part I: General Model Formulation and Boundary Layer Characterization

Abstract The formulation of the American Meteorological Society (AMS) and U.S. Environmental Protection Agency (EPA) Regulatory Model (AERMOD) Improvement Committee’s applied air dispersion model is described. This is the first of two articles describing the model and its performance. Part I includes AERMOD’s characterization of the boundary layer with computation of the Monin–Obukhov length, surface friction velocity, surface roughness length, sensible heat flux, convective scaling velocity, and both the shear- and convection-driven mixing heights. These parameters are used in conjunction with meteorological measurements to characterize the vertical structure of the wind, temperature, and turbulence. AERMOD’s method for considering both the vertical inhomogeneity of the meteorological characteristics and the influence of terrain are explained. The model’s concentration estimates are based on a steady-state plume approach with significant improvements over commonly applied regulatory dispersion models. Co...

AERMOD: A Dispersion Model for Industrial Source Applications. Part II: Model Performance against 17 Field Study Databases

Abstract The performance of the American Meteorological Society (AMS) and U.S. Environmental Protection Agency (EPA) Regulatory Model (AERMOD) Improvement Committee’s applied air dispersion model against 17 field study databases is described. AERMOD is a steady-state plume model with significant improvements over commonly applied regulatory models. The databases are characterized, and the performance measures are described. Emphasis is placed on statistics that demonstrate the model’s abilities to reproduce the upper end of the concentration distribution. This is most important for applied regulatory modeling. The field measurements are characterized by flat and complex terrain, urban and rural conditions, and elevated and surface releases with and without building wake effects. As is indicated by comparisons of modeled and observed concentration distributions, with few exceptions AERMOD’s performance is superior to that of the other applied models tested. This is the second of two articles, with the firs...

A complex terrain dispersion model for regulatory applications

Abstract This paper demonstrates the development of a model designed to estimate concentrations associated with a source situated in complex terrain. The model is designed to provide estimates of concentration distributions and is thus primarily suitable for regulatory applications. The model assumes that the concentration at a receptor is a combination of concentrations caused by two asymptotic states: the plume remains horizontal, and the plume climbs over the hill. The factor that weights the two states is a function of the fractional mass of the plume above the dividing streamline height. The model has been evaluated against data from four complex terrain sites. The evaluation shows that the model performs at least as well as CTDMPLUS (Perry, S.G., 1992. CTDMPLUS, a dispersion model for sources near complex topography. Part I: technical formations. Journal of Applied Meteorology 31, 633–645), a more comprehensive model designed for complex terrain applications.

A New Approach to Environmental Decision Analysis: Multi-Criteria Integrated Resource Assessment (MIRA)

A new approach to environmental policy analysis is introduced that is designed to mitigate the exacerbation of environmental problems, which can result from the application of traditional approaches in environmental decision making. These approaches are problematic because they tend to rely on technical fixes, a single-discipline focus, and optimality. When such traditional approaches are applied, complex environmental problems are simplified beyond recognition, and the solution produced no longer matches the original problem. An alternative approach has been developed at the U.S. Environmental Protection Agency (EPA) that is designed to improve the utilization of scientific research results and data (social, physical, and biological) through a more inclusive problem-solving process aimed particularly at difficult and complex environmental issues. Using a policy application pertaining to the EPA’s 1995 decision to approve a fuel additive, the authors illustrate how integrated environmental policy decision analysis can be made operational using this new approach.

Using Prognostic Model–Generated Meteorological Output in the AERMOD Dispersion Model: An Illustrative Application in Philadelphia, PA

Abstract In this study, we introduce the prospect of using prognostic model–generated meteorological output as input to steady–state dispersion models by identifying possible advantages and disadvantages and by presenting a comparative analysis. Because output from prognostic meteorological models is now routinely available and is used for Eulerian and Lagrangian air quality modeling applications, we explore the possibility of using such data in lieu of traditional National Weather Service (NWS) data for dispersion models. We apply these data in an urban application where comparisons can be made between the two meteorological input data types. Using the U.S. Environment Protection Agency’s American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model (AERMOD) air quality dispersion model, hourly and annual average concentrations of benzene are estimated for the Philadelphia, PA, area using both hourly MM5 model–generated meteorological output and meteorological data taken from the NWS site at the Philadelphia International Airport. Our intent is to stimulate a discussion of the relevant issues and inspire future work that examines many of the questions raised in this paper.

How Much Uncertainty is Too Much and How Do We Know? A Case Example of the Assessment of Ozone Monitor Network Options

Limited time and resources usually characterize environmental decision making at policy organizations such as the U.S. Environmental Protection Agency. In these climates, addressing uncertainty, usually considered a flaw in scientific analyses, is often avoided. However, ignoring uncertainties can result in unpleasant policy surprises. Furthermore, it is important for decisionmakers to know how defensible a chosen policy option is over other options when the uncertainties of the data are considered. The purpose of this article is to suggest an approach that is unique from other approaches in that it considers uncertainty in two specific ways-the uncertainty of stakeholder values within a particular decision context and data uncertainty in the light of the decision-contextual data-values relationship. It is the premise of this article that the interaction between data and stakeholder values is critical to how the decision options are viewed and determines the effect of data uncertainty on the relative acceptability of the decision options, making the understanding of this interaction important to decisionmakers and other stakeholders. This approach utilizes the recently developed decision analysis framework and process, multi-criteria integrated resource assessment (MIRA). This article will specifically address how MIRA can be used to help decisionmakers better understand the importance of uncertainty on the specific (i.e., decision contextual) environmental policy options that they are deliberating.

Tackling the Dilemma of the Science-Policy Interface in Environmental Policy Analysis

Scientifically derived environmental indicators are central to environmental decision analysis. This article examines the interface between science (environmental indicators) and policy, and the dilemma of their integration. In the past, science has been shown to dominate many policy debates, usually with unfavorable results. The issue, therefore, is not whether science can determine policy but how science can be part of a more holistic analysis that incorporates other critical perspectives. This article discusses the importance of considering alternative views (as represented by different scientific indicators) within the policy debate. Six example ozone indicators, constructed from the same raw data, are used to illustrate this point. Two represent newly developed indicators that respond to present-day policy questions at the U.S. Environmental Protection Agency. The article concludes with a brief discussion of how such indicators can be used to better define a policy question, inform the policy debate, and evaluate policy alternatives.

A demonstration of the necessity and feasibility of using a clumsy decision analytic approach on wicked environmental problems

Because controversy, conflict, and lawsuits frequently characterize US Environmental Protection Agency (USEPA) decisions, it is important that USEPA decision makers understand how to evaluate and then make decisions that have simultaneously science-based, social, and political implications. Air quality management is one category of multidimensional decision making at USEPA. The Philadelphia, Pennsylvania metropolitan area experiences unhealthy levels of ozone, fine particulate matter, and air toxics. Many ozone precursors are precursors for particulate matter and certain air toxics. Additionally, some precursors for particulate matter are air toxics. However, air quality management practices have typically evaluated these problems separately. This approach has led to the development of independent (and potentially counterproductive) implementation strategies. This is a methods article about the necessity and feasibility of using a clumsy approach on wicked problems, using an example case study. Air quality management in Philadelphia is a wicked problem. Wicked problems are those where stakeholders define or view the problem differently, there are many different ways to describe the problem (i.e., different dimensions or levels of abstraction), no efficient or optimal solutions exist, and they are often complicated by moral, political, or professional dimensions. The USEPA has developed the multicriteria integrated resource assessment (MIRA) decision analytic approach that engages stakeholder participation through transparency, transdisciplinary learning, and the explicit use of value sets; in other words, a clumsy approach. MIRAs approach to handling technical indicators, expert judgment, and stakeholder values makes it a potentially effective method for tackling wicked environmental problems.

Toward sustainability: a case study demonstrating transdisciplinary learning through the selection and use of indicators in a decision-making process.

The purpose of this article is to use a case study example to demonstrate how a transparent, transdisciplinary approach to decision making allows the US Environmental Protection Agency Region III (USEPA Region III) to fulfill its decision-making responsibilities while taking critical steps toward engaging in sustainability discussions. The case study goals were to use information about environmental condition to inform staff and fiscal resource prioritization and allocation for the federal 2010 fiscal year. This article will use a select group of 3 indicators to show 1) that data are not the same as indicators, 2) the feasibility of using disparate data in the same analysis, and 3) specific discussions about indicators can lead to transdisciplinary learning, supporting more informed decision making. We show that, when used in a transdisciplinary learning process, these indicator lessons provide a stepping stone for organizations like USEPA Region III to consider sustainability as more than just a lofty, ethical concept. Instead, these kinds of organizations can more routinely and substantively address sustainability through a progression of individual decisions. We discuss how sustainability can be linked to decision making through a process that requires stakeholders to articulate and confront their values. In this process, selecting indicators and understanding what those choices imply regarding the issues that are highlighted and the population affected is part of the assessment of environmental condition, which is the focus of the case study.

Codependencies of Reactive Air Toxic and Criteria Pollutants on Emission Reductions

Abstract It is important to understand the effects of emission controls on concentrations of ozone, fine particulate matter (PM2.5), and hazardous air pollutants (HAPs) simultaneously, to evaluate the full range of health, ecosystem, and economic effects. Until recently, the capability to simultaneously evaluate interrelated atmospheric pollutants (“one atmosphere” analysis) was unavailable to air quality managers. In this work, we use an air quality model to examine the potential effect of three emission reductions on concentrations of ozone, PM2.5, and four important HAPs (formaldehyde, acetaldehyde, acrolein, and benzene) over a domain centered on Philadelphia for 12-day episodes in July and January 2001. Although NOx controls are predicted to benefit PM2.5 concentrations and sometimes benefit ozone, they have only a small effect on formaldehyde, slightly increase acetaldehyde and acrolein, and have no effect on benzene in the July episode. Concentrations of all pollutants except benzene increase slightly with NOx controls in the January simulation. Volatile organic compound controls alone are found to have a small effect on ozone and PM2.5, a less than linear effect on decreasing aldehydes, and an approximately linear effect on acrolein and benzene in summer, but a slightly larger than linear effect on aldehydes and acrolein in winter. These simulations indicate the difficulty in assessing how toxic air pollutants might respond to emission reductions aimed at decreasing criteria pollutants such as ozone and PM2.5.