Impacts of temperature-dependent heating demand on wintertime emissions

File(s)
Date
2025Author
Scalpone, Cara
Publisher
University of Wisconsin-Madison
Advisor(s)
Holloway, Tracey
Metadata
Show full item recordAbstract
Most residences are heated by burning fuels, such as natural gas, heating oil, or wood, which emits combustion byproducts into the atmosphere. Space heating demand is dependent on outdoor temperatures, so the impact of residential heating on wintertime pollution covaries with changes in atmospheric dynamics and meteorologically-dependent chemical processes. However, current representations of emissions from non-wood residential fuel combustion (RFC) in atmospheric modeling are based on fixed monthly or seasonal allocations that do not vary with daily temperature. To improve the representation of these emissions, a method for temporally allocating annual residential fuel combustion emissions that reflects temperature-dependent changes in heating demand based on heating degree days (HDDs) was developed. The temperature-dependent daily scaling (DS) approach was applied to create an hourly RFC emissions inventory gridded to a 12 km domain covering the contiguous U.S. The DS approach was compared to a seasonal scaling (SS) approach that had a fixed temporal allocation for winter, spring, summer, and fall. Across all climate regions, the DS approach resulted in a redistribution of emissions toward March and November relative to the SS approach. RFC emissions contributed substantially to the total anthropogenic NOx and SO2 emissions in some grid cells, particularly during the heating season. DS had a greater range in hourly emission rates relative to SS, with higher median peak emission rates across all climate regions. Using a diurnal profile to represent hourly heating demand resulted 18% to 28% more emissions to allocated to nighttime hours compared to the default profile. The temperature-based DS approach offers improvements to the representation of heating demand over fixed temporal allocation methods, enabling future investigation into parsing the co-variable impacts of emissions, meteorology, and chemistry on wintertime air pollution.
Subject
Atmospheric models
Air quality
Permanent Link
http://digital.library.wisc.edu/1793/95811Type
Thesis
