Regional Health Effects of Demand-Side Energy Management Using Exposure Efficiency
Life cycle impact assessment is usually plagued by the assumptions of site independence and uniform mixing of pollutants in a compartment (e.g., atmosphere), which are not valid for all air pollutants. In this paper we propose using the concept of exposure efficiency to simplify the damage pathway analysis without compromising the consideration of site-dependent characteristics. Our case study of increasing insulation in new homes in the US from the MEC1993 to IECC2000 level yields 6,442 TJ (6,111 GBTU) of energy savings potential in terms of energy content of the fuels. The energy savings are attributed to natural gas (72%), electricity (24%) and heating oil (3%). Using exposure efficiency, the electricity savings potentials correspond to an average ambient concentration reduction of 1.4E-5mg/m3 in PM10, 7.6E-5mg/m3 in ammonium sulfate and 4.5E-4mg/m3 in ammonium nitrate, spread across the US. Similarly, the household energy savings reduce 1.0E-4mg/m3 of PM10, 1.2E-7mg/m3 of ammonium sulfate and 2.5E-4mg/m3 of ammonium nitrate. Using a dose-response coefficient derived from a cohort study, the energy savings from increasing insulation in new homes avoid 7.5 cases of premature death each year due to the reduced population exposure to primary and secondary particulate matter. At the state level, the largest SO2 emission reduction occurs in the state of Texas, followed by Ohio and Illinois. However, if we consider exposure to sulfates, Illinois experiences the largest amount of exposure reduction, followed by Texas and Ohio. This means that a unit of SO2 emission in Illinois has more chance of being inhaled than in Texas, i.e., more chance of causing health damage. From a public health policy perspective, the exposure-based analysis is more relevant than emission-based if demand side energy management is targeted to reduce population health risks. Exposure efficiency and selective atmospheric dispersion modeling that we propose can improve a site-dependent life-cycle impact assessment for local pollutants.