Contents lists available at ScienceDirect Sustainable Energy Technologies and Assessments journal homepage: www.elsevier.com/locate/seta Energy-related emissions from commercial buildings: Comparing methods for quantifying temporal indirect emissions associated with electricity purchases Zahra Fallahi, Kaden Plewe, Amanda D. Smith ⁎ Site-Specifc Energy Systems Laboratory, Department of Mechanical Engineering, 1495 East 100 South, MEK 1550 University of Utah, Salt Lake City, UT 84112, United States ARTICLE INFO Keywords: CO 2 emissions NOx emissions SOx emissions Commercial buildings Building energy modeling ABSTRACT The emissions associated with purchased electricity in a specific location are determined by the emission factors attributed to power generators on the electrical grid serving a facility. Averaged, flat rate emission factors consider a representative fuel mix in a region, usually averaged over many years, and are often used in con- junction with building energy analysis. Time-varying power generation data is needed to determine the effect of power generation dispatch on marginal emission factors, but such data is rarely publicly available. This work provides a critical comparative analysis of two types of temporal emission factors with the goal of understanding how indirect emissions relate to the energy usage of commercial buildings in the U.S. Every building’s con- sumption of electricity also varies temporally, so we use representative electric loads on an hourly basis using stock building model simulations. The methods compared are: (1) regional factors provided by U.S. Environmental Protection Agency (EPA) power generation data and (2) city-specific factors derived from the Locational Emissions Estimation Methodology (LEEM). The emissions resulting from alternate calculation methods are presented for , NO x , and SO x . These locally specified, hourly resolved methods of indirect emissions calculation were found to differ from the simple flat rate emissions calculation method (4%–20%). On an annual basis, the difference in calculated emissions using hourly emission factors versus annually averaged LEEM and EPA factors differed by less than 2%, indicating that they provide similar information on an annual basis. Introduction Atmospheric CO 2 concentrations passed the 400 ppm level in 2016 [1], and anthropogenic emissions from the total built environment con- tinue to rise. Decreasing the rate of emissions production from anthro- pogenic systems is necessary to slow or halt the trend of increasing concentrations of atmospheric CO 2 and other greenhouse gases (GHGs). The main GHGs contributing sectors in the United States are transpor- tation, industrial, residential, and commercial buildings, with the buildings sector contributing to more than 40% of total CO 2 emissions [2]. Worldwide, commercial buildings present many opportunities to reduce CO 2 emissions [3]. Gutierrez-Aliaga and Williams have calculated that changes to thermostat settings in offices and restaurants in the U.S. alone could reduce their CO 2 -equivalent annual emissions by 1% [4]. Building emissions are categorized as direct or indirect based on their discharge location. Direct emissions from on-site combustion can be mitigated using energy efficiency retrofits, [5], or by implementing energy management strategies and sophisticated control systems to optimize operating schedules [6]. The majority of indirect emissions from the buildings sector are associated with regional power generation and are discharged at power plants that supply electricity to the elec- trical grid. Various methods are used to consider the amount of indirect emissions associated with the electricity purchases of buildings [7]. Averaged emission factors are calculated based on the share of different resources in electricity production [8]. In the United States, state-based data is available for calculating emission factors. For ex- ample, in the state of Michigan, monthly electricity production in Au- gust 2017 came primarily from coal (37%), nuclear (31%), natural gas (25%), and renewables (less than 6%); in Indiana, monthly electricity production in August 2017 came from coal (78%), natural gas (18%), and renewables (less than 4%). Although averaged emissions factors are based on the types of power plants generating the electricity in each region, they do not consider the effects of the climate, load patterns, and grid communications and operations. This could reduce the https://doi.org/10.1016/j.seta.2018.09.004 Received 16 December 2017; Received in revised form 25 August 2018; Accepted 5 September 2018 ⁎ Corresponding author. E-mail address: amanda.d.smith@utah.edu (A.D. Smith). Sustainable Energy Technologies and Assessments 30 (2018) 150–163 2213-1388/ © 2018 Elsevier Ltd. All rights reserved. T