Assessments of building energy consumption en masse at city or regional scale are valuable for such purposes as identifying the most or least energy-intensive commercial activities or contemplating alternate land and building use, energy efficiency modifications, or distributed renewable generation scenarios. Energy utilities possess customer consumption data but they generally guard that information very closely due to privacy and business intelligence concerns. Furthermore, it is not always possible, may be impractical, and risks exposure to criminal trespass charges to canvass a region to collect data from buildings’ electric and gas meters. To get past that limitation, the authors describe and demonstrate a method for estimating the annual energy consumption of commercial buildings by using a combination of GIS data describing buildings within a region, degree day maps of that same region, the US Energy Information Administration’s Commercial Building Energy Consumption Survey (CBECS) dataset, and our original decomposition model of energy consumption. The decomposition model is cast in the form of a linear expression that uses as inputs the variables that the GIS and degree day data can be manipulated to reach equivalency with those of the CBECS observations. For each represented PBA, we perform a regression using the CBECS data for that PBA including the total annual energy consumption field to obtain a set of coefficients for the terms in the model expression. We can subsequently run real-world building data through the expressions using those coefficients to obtain annual consumption estimates and assess the correlation between CBECS total consumption and our method’s estimates. As an example, for one PBA, “Enclosed Mall,” and using the 2016 update of the 2012 CBECS release, all such commercial buildings represented by CBECS have annual consumption estimates that lie within an order of magnitude of the corresponding CBECS observations’ published consumption value and 60 percent lie within half or double that value. For buildings of all PBAs represented in CBECS, 81 percent have annual consumption estimates that lie within an order of magnitude of the corresponding CBECS observations’ consumption value and 45 percent lie within half or double that value. Real-world building data thoroughness and quality is a significant problem encountered in utilizing this method; in attempting to estimate consumption for commercial buildings in Georgia’s Fulton County, we found that GIS data supplied by Fulton County contained largely inaccurate or missing values for the number of stories, which is necessary to establish square footage. We therefore performed a spatial join between that data and proprietary data purchased from CoStar Market Analytics that included more accurate values for the number of stories. Additionally, we lacked building data showing whether heating was supplied by heat pump or direct heating; in the former case a different model for heating energy consumption as a function of physical building parameters would have been used and therefore confidence in the heating energy component of our estimates relies on the general prevalence within each PBA of heat pump versus direct heating that is innately embedded in the CBECS data.

Research Background

As a carbon-free fuel with high energy content, hydrogen plays a crucial role in decarbonizing the industrial sector that requires high energy inputs. To incentivize the early commercial-scale implementation of hydrogen, the U.S. Congress enacted the Inflation Reduction Act in August 2022 to provide Production Tax Credits (PTC) for low-emissions hydrogen and tax credits for CO2 capture under Sections 45V and 45Q, respectively.

However, the infrastructure for pure hydrogen storage and transportation is yet to be constructed to accommodate large-scale hydrogen utilization. Therefore, many pilot projects on hydrogen utilization are developed to blend a small ratio of hydrogen in the natural gas pipelines. To assess whether a hydrogen-natural gas blend is a feasible transition strategy to achieve moderate decarbonization, we assessed the total emissions of powering natural gas-based boilers in the U.S. using pure natural gas versus a 15 vol. % hydrogen and 85 vol. % natural gas blend.

Methods

We started with defining the process flow, which includes upstream natural gas processing and transportation, hydrogen production and compression, and fuel combustion. For hydrogen production, we considered various production routes, including steam methane reforming and electrolysis using either natural gas or water as feedstock, respectively. We also considered incorporating carbon capture and sequestration at steam methane reforming facilities. We compiled information regarding the total capacity of natural gas-powered industrial boilers in the U.S., hydrogen production capacity by state, and the emission factors for different process stages. An overlay of the locations of the boilers, hydrogen production sites, and natural gas pipelines was created to examine the feasibility of hydrogen blending. We then calculated the total national annual emissions of powering natural gas-based boilers with a 15 vol. % /85 vol. % hydrogen/natural gas blend.

Results

Our calculations showed the blending of 15% hydrogen for heating natural gas-based boilers can potentially be an intermittent tactic to reduce GHG emissions when carbon capture and sequestration is implemented for hydrogen production from natural gas. Meanwhile, blending 15% hydrogen produced via water electrolysis with the current grid would drastically increase GHG emissions. The major contributors include emissions from grid electricity generation and upstream natural gas transmission and distribution. Regional differences in emissions were also observed, where the Northeast sees the lowest increase in emissions and could potentially benefit more from hydrogen blending. However, the Northeast is also the region with the greatest hydrogen deficiency and requires a rapid ramp-up in hydrogen production.

(1) Background

Universities have a unique position to lead in the implementation of climate actions. In March 2023, the White House and the University of Washington co-hosted a forum on how universities have the capability to deliver climate change solutions to their communities [1].

Over the past 14 years, the University of Pittsburgh has completed eight greenhouse gas inventories. Consistently, one of the largest contributors to the University’s carbon footprint has been emissions associated with the building sector, specifically for electricity and heating. In fiscal year (FY) 2022, purchased electricity accounted for 37% of emissions at the University, and steam was the second largest contributor at 28%. In 2022, the University published its first Climate Action Plan (PittCAP), a document that strategizes how the University will achieve carbon neutrality by 2037. This presentation will identify the PittCAP goals for building-related emissions, and how our greenhouse gas inventories are used to assess the achievement of that goal at both a campus-wide and individual building scale.

(2) Methods

Historical data on steam, electricity, and natural gas used in the greenhouse gas inventories were analyzed to compare the University’s current and previous energy use to building energy goals defined in by PittCAP. This data was collected for FY 2019, 2020, and 2021. Because FY 2019 is the launchpad for the PittCAP, it was chosen as the starting year for this analysis. Building energy use data was paired with emissions factors from the University of New Hampshire’s Sustainability Indicator Management & Analysis Platform (SIMAP) to calculate greenhouse gas emissions at the individual building level.

Once the energy use and corresponding carbon emissions were determined for a building from FY19 to FY21, the next step was to determine how that building will contribute to the University’s carbon neutrality goal by 2037. After defining the 2037 carbon emissions target for an individual building, an emissions target was created for every year from 2019 to 2037. This yearly target indicates whether we are on track to meet the 2037 goal. The process was repeated for the 95 buildings included in the University’s Pittsburgh campus GHG inventories.

(3) Preliminary Results

The analysis showed that each of the 95 buildings analyzed would need to decrease their energy use approximately 14% by 2037 to meet the PittCAP goal, which is less than 1% per year from 2019 to 2037. In examining overall building energy use emissions, building energy use performance in fiscal years 2020 and 2021 was beating targets. For FY21, of the 95 buildings analyzed, 22 buildings had already reached their 2037 emissions goal, 27 are on track or ahead of schedule, and 46 buildings are not on track. This information helps the University target which buildings are underperforming and informs decisions about where to prioritize energy efficiency upgrades. Results have already been used at the University of Pittsburgh to inform building upgrade prioritization (in conjunction with other considerations, including energy use intensity, building square footage, and estimated reduction potential).

References

[1] Readout of the White House Forum on Campus and Community-Scale Climate Change Solutions | OSTP. (2023, March 15). The White House. https://www.whitehouse.gov/ostp/news-updates/2023/03/15/readout-of-the-white-house-forum-on-campus-and-community-scale-climate-change-solutions/

The APEX (“Advanced Practices for Environmental Excellence in Cities”) Green Cities Program is a International Finance Corporation (IFC) initiative that supports cities in emerging economies to accelerate the implementation of ambitious and transformative policy actions and investments that significantly contribute to transitioning to low-carbon and resource-efficient growth pathways. The program leverages the APEX online software, which helps cities to quickly assess the most cost-effective way to incorporate measures into their investment and policy pipelines, in order to achieve targets related to energy, transportation, waste, water, and GHG emissions. IFC is part of the World Bank Group.

APEX helps quantify the future impacts and costs of investment, planning, and policy solutions—referred to as measures. There are over 100 measures preloaded into APEX, as well as the option to create custom measures. Each measure has an engine that quantifies its impacts and costs based on the specific situation in the city. The methodology behind each measure is based on prevailing engineering calculations, existing studies in the literature, and/or case studies from other cities. APEX also incorporates information from global datasets and proxy calculations to support cities in data-scarce environments.

This presentation will introduce the APEX program, overview the online software, and highlight case study examples of where APEX has supported cities in Africa and Asia.