The development and application of a simplified ozone modeling system (SOMS)

This paper describes the development and evaluation of a computationally efficient semi-empirical photochemical model that can be used as a screening tool to obtain quick estimates of the effect of a large number of VOC and NO_x emission control strategies on ozone concentrations. Selected control strategies can subsequently be examined with a more complex model. The model is one component of an ozone management system, the regional ozone decision model (RODM), designed to examine the costs and environmental consequences of alternate ozone abatement strategies.The model was developed by systematic simplification of a detailed photochemical model. At each step of the simplification, the simplified model was tested against observations and against results from the detailed model. The first major simplification was the introduction of a highly parameterized chemistry mechanism, originally developed by Azzi et al. (1992 Proc. 11th Int. Clean Air Conf., 4th Regional IUAPPA Conf.). This modification resulted in a factor of 5 improvement in the computational efficiency of the model. The model with the simplified chemistry was then tested by applying it to a photochemical oxidant episode in the San Joaquin Valley of California. Further improvements in computational speed and efficiency were obtained by uncoupling the chemistry from the transport of VOC and NO_x.     

Near-field dispersion modeling for regulatory applications

This paper evaluates the application of dispersion models to estimate near-field pollutant concentrations in two case studies. The Industrial Source Complex Short-Term Model (ISCST3) was evaluated with hexavalent chromium measurements collected within 100 m of two facilities in Barrio Logan, San Diego, CA. ISCST3 provided reasonable estimates for higher pollutant concentrations but underestimated lower concentrations. To understand the observed distribution of concentrations in Barrio Logan, a recently conducted tracer experiment was analyzed. The tracer, sulfur hexafluoride, was released at ambient temperature from an urban facility at the University of California at Riverside, and concentrations were measured within 20 m of the source. Modeling results indicated that Industrial Source Complex-Plume Rise Model Enhancement and American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model-Plume Rise Model Enhancement overestimated high concentrations and underestimated low concentrations. A diagnostic study with a simple Gaussian dispersion model that incorporated site-specific meteorology was used to evaluate model results. This study found that incorporating lateral meandering for nonbuoyant urban plumes in Gaussian dispersion models could improve concentration estimates even when downwash is not considered. Incorporating a meandering component in ISCST3 resulted in improvements in estimating hexavalent chromium concentrations in Barrio Logan. Credible near-source concentration estimates depend on accurate characterization of emissions, onsite micrometeorology, and a method to account for lateral meandering in the near field.     

The Development of a Model to Examine Source-Receptor Relationships for Visibility on the Colorado Plateau

This paper describes the development and application of the Visibility and Haze in the Western Atmosphere (VISHWA) model to understand the source-receptor relationships that govern chemical species relevant to visibility degradation in the western United States. The model was developed as part of a project referred to as Visibility Assessment for Regional Emission Distributions (VARED), the objective of which is to estimate the contributions of various geographical regions, compounds, and emission

sources to light scattering and absorption by particles on the Colorado Plateau.

The VISHWA model is a modified version of a comprehensive Eulerian model, known as the Acid Deposition and Oxidant Model.1 The modifications were designed to obtain the computational efficiency required to simulate a one-year period at about 1/25th of real time, and at the same time incorporate mechanistic features relevant to realistic modeling of the fate and transport of visibility degrading species. The modifications included use of a condensed chemical mechanism; incorporation of reactions to simulate the formation of secondary organic particles; and use of a semi-Lagrangian advection scheme to preserve concentration peaks during advection.

The model was evaluated with 1992 air quality data from Project MOHAVE (Measurements of Haze and Visual Effects) intensive experiments. An important conclusion of this evaluation is that aqueous-phase oxidation of SO2 to sulfate in nonprecipitating clouds makes a significant contribution to observed sulfate levels during winter as well as summer. Model estimates of ambient sulfate

for the winter intensive were within a factor of 2 of the observations for 75% of the values. The corresponding statistic for the summer intensive was 90%. Model estimates of carbon were within a factor of 2 of the limited set of observations.     

Resolving neighborhood scale in air toxics modeling: a case study in Wilmington, CA

Air quality modeling is useful for characterizing exposures to air pollutants. Whereas models typically provide results on regional scales, new concerns regarding the potential for differential exposures among racial/ethnic populations and income strata within communities are driving the need for increasingly refined modeling approaches. These approaches need to be capable of resolving concentrations on the scale of tens of meters, across modeling domains 10-100 km2 in size. One approach for refined air quality modeling is to combine Gaussian and regional photochemical grid models. In this paper, the authors demonstrate this approach on a case study of Wilmington, CA, focused on diesel exhaust particulate matter. Modeling results suggest that pollutant concentrations in the vicinity of emission sources are elevated, and, therefore, an understanding of local emission sources is necessary to generate credible modeling results. A probabilistic evaluation of the Gaussian model application indicated that spatial allocation, emission rates, and meteorological data are important contributors to input and parameter uncertainty in the model results. This uncertainty can be substantially reduced through the collection and integration of site-specific information about the location of emission sources and the activity and emission rates of key sources affecting model concentrations.     

A study on traffic noise of two campuses of University, Balasore, India

Noise pollution is a significant environmental problem in many rapidly urbanizing areas of Orissa, India. Transportation sector is one of the major contributors to noise in these areas. The present study is an attempt to estimate traffic noise pollution at five places on the way from Vyasa Vihar Campus to Gyan Vigyan Vihar Campus of Fakir Mohan University, Balasore, Orissa. The sources of noise at the studied sites are predominantly attributable to motor vehicular traffic. The noise levels of all the five locations were found to be beyond permissible limit during the day time. The contributions of different types of vehicles to environmental noise were found to ranging from 70.4-94.2, 79.0-96.1, 77.8-110.2, 70.8-90.3, 71.0-87.5, 71.1-84.4, 72.5-86.9 and 74.0-85.4 dB (A) by cargo carrying Trucks, Tractors, Dumpers, Town Buses, Motor cycles, Bolero/Trucker, Pick up and Tempo respectively. The contributions of individual vehicles towards noise pollution were found to be more than the road traffic noise-limit i.e., 70 dB (A). On certain local inhabitants interviewed, the impact of noise was observed in the forms of alterations in their physical, psychological and personal aspects. This study warrants attention from all sections of people to deal with the problem of noise pollution.     

Near-Field Dispersion Modeling for Regulatory Applications

Abstract

This paper evaluates the application of dispersion models to estimate near-field pollutant concentrations in two case studies. The Industrial Source Complex Short-Term Model (ISCST3) was evaluated with hexavalent chromium measurements collected within 100 m of two facilities in Barrio Logan, San Diego, CA. ISCST3 provided reasonable estimates for higher pollutant concentrations but underestimated lower concentrations. To understand the observed distribution of concentrations in Barrio Logan, a recently conducted tracer experiment was analyzed. The tracer, sulfur hexafluoride, was released at ambient temperature from an urban facility at the University of California at Riverside, and concentrations were measured within 20 m of the source. Modeling results indicated that Industrial Source Complex–Plume Rise Model Enhancement and American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model–Plume Rise Model Enhancement overestimated high concentrations and underestimated low concentrations. A diagnostic study with a simple Gaussian dispersion model that incorporated site-specific meteorology was used to evaluate model results. This study found that incorporating lateral meandering for nonbuoyant urban plumes in Gaussian dispersion models could improve concentration estimates even when downwash is not considered. Incorporating a meandering component in ISCST3 resulted in improvements in estimating hexavalent chromium concentrations in Barrio Logan. Credible near-source concentration estimates depend on accurate characterization of emissions, onsite micrometeorology, and a method to account for lateral meandering in the near field.     

Modeling the impacts of traffic emissions on air toxics concentrations near roadways

The dispersion formulation incorporated in the U.S. Environmental Protection Agency's AERMOD regulatory dispersion model is used to estimate the contribution of traffic-generated emissions of select VOCs – benzene, 1,3-butadiene, toluene – to ambient air concentrations at downwind receptors ranging from 10-m to 100-m from the edge of a major highway in Raleigh, North Carolina. The contributions are computed using the following steps: 1) Evaluate dispersion model estimates with 10-min averaged NO data measured at 7 m and 17 m from the edge of the road during a field study conducted in August, 2006; this step determines the uncertainty in model estimates. 2) Use dispersion model estimates and their uncertainties, determined in step 1, to construct pseudo-observations. 3) Fit pseudo-observations to actual observations of VOC concentrations measured during five periods of the field study. This provides estimates of the contributions of traffic emissions to the VOC concentrations at the receptors located from 10 m to 100 m from the road. In addition, it provides estimates of emission factors and background concentrations of the VOCs, which are supported by independent estimates from motor vehicle emissions models and regional air quality measurements. The results presented in the paper demonstrate the suitability of the formulation in AERMOD for estimating concentrations associated with mobile source emissions near roadways. This paper also presents an evaluation of the key emissions and dispersion modeling inputs necessary for conducting assessments of local-scale impacts from traffic emissions.     

The development of the acid deposition and oxidant model (ADOM)

This paper describes the development and testing of the Acid Deposition and Oxidant Model (ADOM), a nine-year project funded by a consortium consisting of Environment Ontario, Environment Canada, the German Umweltbundesamt, and the Electric Power Research Institute. The project consisted of three major phases: a design phase, an implementation phase, and an evaluation phase. In the design phase, the system being modeled was divided into its components-transport, gas phase chemistry, aqueous phase chemistry, dry deposition and cloud processes. The formulation of the modules for each of these processes was guided by the requirement that the modules reflect the state of the art, and at the same time be consistent with the available numerical resources. In the implementation phase, submodels were constructed, and then subjected to several tests, which included mathematical consistency checks, sensitivity studies, and evaluation against field and laboratory data. The modules were then assembled and interfaced with the input data sets. The codes for the modules as well as the overall model were vectorized to take advantage of the capabilities of supercomputers such as the CRAY. The North American and West German versions of the model are being tested against data collected in North America and in Europe. This paper describes the evaluation of ADOM with data associated with a regional ozone episode in Ontario in June 1983, and measurements made during an experiment to study the scavenging characteristics of spring storms in the central and northeastern United States in April 1981.     

Analysis of air quality data near roadways using a dispersion model

We used a dispersion model to analyze measurements made during a field study conducted by the U.S. EPA in July–August 2006, to estimate the impact of traffic emissions on air quality at distances of tens of meters from an eight-lane highway located in Raleigh, NC. The air quality measurements consisted of long path optical measurements of NO at distances of 7 and 17 m from the edge of the highway. Sonic anemometers were used to measure wind speed and turbulent velocities at 6 and 20 m from the highway. Traffic flow rates were monitored using traffic surveillance cameras. The dispersion model [Venkatram, A., 2004. On estimating emissions through horizontal fluxes. Atmospheric Environment 38, 2439–2446] explained over 60% of the variance of the observed path averaged NO concentrations, and over 90% of the observed concentrations were within a factor of two of the model estimates.Sensitivity tests conducted with the model indicated that the traffic flow rate made the largest contribution to the variance of the observed NO concentrations. The meteorological variable that had the largest impact on the near road NO concentrations was the standard deviation of the vertical velocity fluctuations, σ_w. Wind speed had a relatively minor effect on concentrations. Furthermore, as long as the wind direction was within ±45° from the normal to the road, wind direction had little impact on near road concentrations. The measurements did not allow us to draw conclusions on the impact of traffic-induced turbulence on dispersion. The analysis of air quality and meteorological observations resulted in plausible estimates of on-road emission factors for NO.