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Air Quality Impact of Distributed Generation of Electricity

Abstract

This dissertation summarizes the results of a five-year investigation of the impact of distributed generation (DG) of electricity on air quality in urban areas. I focused on the impact of power plants with capacities of less than 50 MW, which is typical of DG units in urban areas. These power plants are modeled as buoyant emissions from stacks less than 10 m situated in the midst of urban buildings. Because existing dispersion models are not designed for such sources, the first step of the study involved the evaluation of AERMOD, USEPA's state-of-the art dispersion model, with data collected in a tracer study conducted in the vicinity of a DG unit. The second step of the study consisted of using AERMOD to compare the impact of DG penetration in the South Coast Air Basin of Los Angeles with the impact of replacing DG generation with expansion of current central power plant capacity. The third topic of my investigation is the development and application of a model to examine the impact of non-power plant sources in a large urban area such as Los Angeles. This model can be used to estimate the air quality impact of DG relative to other sources in an urban area.

The first part of this dissertation describes a tracer study conducted in Palm Springs, CA. Concentrations observed during the nighttime experiments are generally higher than those measured during the daytime experiments. They fall off less rapidly with distance than during the daytime. AERMOD provides an adequate description of concentrations associated with the buoyant releases from the DG during the daytime when turbulence is controlled by convection induced by solar heating. However, AERMOD underestimates concentrations during the night when turbulence is generated by wind shear. Also, AERMOD predicts a decrease in concentrations with distance that is much more rapid than the relatively flat observed decrease. I have suggested modifications to AERMOD to improve the agreement between model estimates and observations during the night.

The second part of this dissertation examines the air quality impact of using DG to satisfy future growth in power demand in the South Coast Air Basin of Los Angeles (SoCAB), relative to the impact when the demand is met by expanding current central generation (CG) capacity. The air quality impacts of these two alternate scenarios are quantified in terms of hourly maximum ground-level and annually-averaged primary NOx concentrations, which are estimated using AERMOD. The shift to DGs has the potential for decreasing maximum hourly impacts of power generation in the vicinity of the DGs. The maximum hourly concentration is reduced from 25 ppb to 6 ppb if DGs rather than CGs are used to generate power. However, the annually-averaged concentrations are likely to be higher than for the scenario in which existing CGs are used to satisfy power demand growth. Future DG penetration will add an annual average of 0.1 ppb to the current basin average, 20 ppb, while expanding existing CGs will add 0.05 ppb.

The third part of my dissertation focused on formulating a model to estimate concentrations of NO2, NOx, and O3 averaged over a spatial scale of the order of a kilometer in a domain extending over tens of kilometers. The model can be used to estimate hourly concentrations of these species over time periods of years. It achieves the required computational efficiency by separating transport and chemistry using the concept of species age. Evaluation with data measured at 21 stations distributed over the Los Angeles air basin indicates that the model provides an adequate description of the spatial and temporal variation of the concentrations of NO2 and NOx. Estimates of maximum hourly O3 concentrations show little bias compared to observations, but the scatter is not small.

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