The Air Quality and Human Health Impacts of Distributed Energy GenerationEPA Grant Number: F6A10633
Title: The Air Quality and Human Health Impacts of Distributed Energy Generation
Investigators: Gilmore, Elisabeth A.
Institution: Carnegie Mellon University
EPA Project Officer: Lee, Sonja
Project Period: September 1, 2006 through September 1, 2008
Project Amount: $111,172
RFA: STAR Graduate Fellowships (2006) RFA Text | Recipients Lists
Research Category: Academic Fellowships , Engineering and Environmental Chemistry , Fellowship - Chemical Engineering , Fellowship - Engineering , Fellowship - Public Policy , Health Effects
Distributed generation (DG), broadly defined as small scale electricity production located close to the point of use, is increasingly attractive to relying on the electricity grid. Depending on the DG technology, its emission characteristics, the type of application and its location, there may be a positive or negative effect on local and regional air quality and the associated human health burden compared to centralized power plants. The objectives of this work are twofold: 1) to evaluate the effect of air emissions for a range of DG applications on ambient air pollutant concentrations, and 2) to quantify the effect of the change in air pollution concentrations on human and ecosystem health as well as the externality cost from these effects.
To determine whether DG is desirable for a given application, the full cost (e.g. the private and the social costs) of various DG technologies that are feasible for a given application are compared to the appropriate status quo or centralized energy generation option. Normally, the decision to operate different technologies is made solely on the private costs. A more comprehensive approach is to evaluate the technologies on a full cost basis where the cost of the environmental externalities of the technology is also included. For energy generation, the main environmental externality is air pollution. A bottom-up approach is used to determine the social cost of the air pollution as follows: 1) characterization of the emissions from the DG technology for a given application; 2) modeling of the ambient concentrations using a comprehensive 3-D grid-based regional air quality model known as PMCAMx (the Comprehensive Air Quality Model with extensions and particulate matter modules); 3) transform the concentrations into their equivalent human health effect using concentration-response functions; and 4) multiply the human health endpoints by their economic value.
To date, I have evaluated using DG in the form of installed backup generators for meeting summer peak electricity demand in New York City. The results show that while uncontrolled diesel engines (which comprise a significant percentage of the installed backup units) has a very high social cost, properly controlled diesel generators using low sulfur fuel and equipped with diesel particulate filters can be operated at social costs comparable to natural gas fueled engines and microturbines. On a full cost basis, the DG units are cost-effective compared to the construction of a new dedicated natural gas turbine for meeting peak electricity demand. Over the next two years, I will evaluate other applications for DG. The results from this work will be useful for identifying opportunities where using DG is consistent with reducing the human health and environmental burden of energy generation.