New Tool for Assessing Upfront and Operational Emissions: No Passive House Emissions Backfire Found

The past few years have seen a rapid ramp up in our collective understanding of the impact of embodied carbon (more aptly called “upfront carbon”) on the overall carbon footprint of our buildings. Thought leaders like Kate Simonen, Chris Magwood, Stacey Smedley, Bruce King, and others have alerted the building decarbonization community to this once-underestimated source of emissions and have warned of construction’s “carbon burp” (caused mainly by the upfront emissions of the structural elements of buildings) and its potential to push emissions reductions targets out of reach.

This awareness-raising, along with the recent movement to “electrify everything”, have spurred on an important evolution in how we map the pathway to building decarbonization: deep energy efficiency, plus low embodied carbon and carbon-sequestering building materials, plus building electrification, plus clean energy begins to approach “zero carbon building” (see Figure 1).

figure 1 1677816199

This evolved understanding is to be celebrated. As they say, knowledge is power, and we’ll need lots of both knowledge and power to pull off the rapid decarbonization of buildings that is so vital to our shared climate future. To transform buildings into a climate solution rather than a climate problem we need to retrofit buildings to be all-electric and highly energy efficient, using low-embodied carbon materials and designs. And when we need to build new buildings, we should do the same.

Unfortunately, somewhere during the process of embodied carbon awareness-raising a misperception has taken hold: that if you’re not careful, Passive House practice will do more climate harm than good; that the extra insulation and triple-pane windows on a Passive House can backfire, adding more upfront carbon emissions than the operational carbon emissions that they reduce, particularly if your building is powered by (what are assumed to be) “zero carbon electrons”.

We call this a misperception because, from our vantage point, it is not supported by the emissions data from what we understand to be the best-in-class data sources: (1) the BEAM Estimator[1] (for estimating A1-A3 upfront carbon emissions), (2) the eGRID emissions factors in ASHRAE 189.1: Standard for the Design of Green Buildings[2] (for estimating operational carbon emissions using retrospective electricity emissions factors), and (3) the NREL Cambium Tool[3] (for estimating operational carbon emissions using projections for future electricity emissions factors).

Skylar has created a free, open-source tool, the OCEC (Operational Carbon Embodied Carbon Tool, beta version here) that draws upon these data sources to provide a single-page dashboard for rapid comparison of the operational and embodied emissions of two side-by-side building cases. To our knowledge, it is the first early design tool to integrate the upfront emissions from the building enclosure, mechanical system, PV system, and energy storage of a building with a tally of that building’s operational emissions. It also evaluates the impact of refrigerant leakage on overall building emissions, which varies depending on the size of heat pump necessary for a given building.

What follows is a side-by-side comparison of two all-electric homes in Boise, Idaho—one built to a site Energy Use Intensity of 30 (EUI, measured in kBtu/ft2/yr) and the other to an EUI of 15—in order to examine the upfront and operational carbon emissions for both cases and unpack the implications. But, before we do, we want to ground the discussion in a reminder of the sheer magnitude of the building heating problem (and therefore building efficiency problem) that we face in the upcoming clean energy transition.

figure 2 1677816205

Figure 2, a graph from Saul Griffith’s 2022 book, Electrify: An Optimist’s Playbook for our Clean Energy Future[4], shows modeled seasonal variations in electric load by energy sector if loads were almost completely electrified in the United States. The curves for the industry, commercial, and transportation sectors are mellow over the course of the year: no big spikes in load, so no massive ramp-ups necessary in electricity generation and therefore no need to overbuild generation capacity to power those ramp-ups. One can imagine a mix of new wind and solar generation, combined with existing hydro and nuclear, meeting this relatively flat load in a straightforward manner.

But, the residential sector is something different entirely. Coined the "Falcon Curve”, a massive residential energy load in the winter months creates “wings” of a falcon, swooping up to a peak in January. The cause? Winter heating: over 100 gigawatts worth of extra load caused by thermal energy loss from our homes’ leaky and inefficient building envelopes. While a transition to heat pumps and additional wind power can partially alleviate the problem, this winter load poses a serious challenge to the clean energy transition. The title of a recent paper written by, among others, the director of the Healthy Buildings program at Harvard University’s T.H. Chan School of Public Health summarizes it nicely: “Inefficient Building Electrification Will Require Massive Buildout of Renewable Energy and Seasonal Energy Storage.”[5]

The good news is, as Lisa White discusses in her article, "Facilitating the Renewable Transition: Passive Buildings + Grid-Interactive Capabilities" (coming soon in the Spring 2023 issue of Passive House Accelerator magazine), envelope-first building energy efficiency is uniquely suited to address this winter heat load. Or put another way, maybe the best way to flatten this Falcon Curve caused by building energy inefficiency is by improving building energy efficiency. That seems pretty commonsensical, but do we risk unleashing a big pulse of embodied carbon emissions through our building enclosure improvements? Would that pulse be large enough to undermine our well-intentioned interventions? Will all that insulation and triple-pane glass backfire? Let’s take a look.

Skylar used his new 2,000-ft2 all-electric Phius+ 2018 certified house in Boise, Idaho, with its EUI of 15 kBtu/ft2/yr, as the guinea pig for an experiment using his open-source tool. The design of the experiment was simple: take his house with an EUI of 15, compare it to an all-electric code minimum version of the same house, and look at the upfront emissions (using the BEAM Estimator) and operational carbon emissions (using the eGRID emissions factors in ASHRAE 189.1: Standard for the Design of Green Buildings) for both. To determine what his home’s EUI would be if it were built to code minimum, Skylar modeled it as if it were designed to the 2018 IECC. The code minimum result was an EUI of 36. In order to give the code house the benefit of the doubt (and to give the operational carbon comparisons a very easy 2:1 ratio) Skylar adjusted that down to an EUI of 30. So, EUI of 30 for the theoretical code minimum house (modeled with double-pane windows and 2x6 fiberglass batt walls) and EUI of 15 for his actual Phius+ home (built with triple-pane windows and cellulose double stud walls).

Figure 3   Operational and Emodied Tonnes Year 1

The result? As seen in Figure 3, even at the short time horizon of just one year of operation, total carbon emissions for the code house (left bar graph) are higher than for the Passive House that Skylar built (center bar graph). In fact, both upfront and operational emissions are higher for the code house: the energy efficiency of Skylar’s Passive House means lower operational carbon, and the carbon-sequestering quality of its cellulose insulation means lower upfront carbon. Skylar’s Passive House also has smaller refrigerant leaks and smaller upfront carbon emissions due to its smaller heat pump equipment. Of course, because we are comparing two new houses, there is a significant carbon emissions “burp” from the upfront building emissions of new construction: about 25 tons CO2e (excluding insulation or windows). But that is a “new construction burp”, not a “Passive House burp”.

When we look at data like these, we wonder how this worry about total carbon emissions from Passive House, including a supposed backfire, has taken hold. To try to manufacture a backfire for the Passive House, Skylar modeled the impact of using high embodied carbon materials for the Passive House enclosure: wrapping a code-insulated roof, walls, foundation, and slab with R-30 EPS foam. (NOTE: Skylar modeled EPS for this exercise rather than, for example, XPS foam with a high-GWP spraying agent, because the former is readily available in the marketplace while the latter is being phased out across North America. We see this as progress: it is getting harder to be truly reckless on an upfront emissions basis with insulation choices.) The right bar graph in Figure 3 shows total emissions for that hypothetical version of the Passive House, with upfront emissions from the building’s insulation and windows growing to 16.6 tons CO2e. With this change we do see an emissions “burp” for the foam-wrapped Passive House compared to the code built home, at least in year one; total building emissions (operational plus upfront emissions) for the foam-wrapped Passive House are higher than the code built home for that first year. But as soon you extend the time-horizon of the analysis to two years, as seen in Figure 4, that “burp” disappears, overtaken by the two years of operational carbon emissions and refrigerant leakage of the code home.

Figure 4   Operational and Emodied Tonnes Year 2

We want to emphasize that we would never choose to create excess upfront carbon emissions in the real world. We should do our best to decrease both upfront and operational carbon emissions. We just want to illustrate that, based on the data we are seeing, there is not a tradeoff between the operational carbon benefits of Passive House enclosure improvements and total building emissions, even if we make high embodied carbon choices for those enclosure improvements.

Figure 5   Operational and Emodied Tonnes Year 10

When we extend the time horizon of the analysis out to ten years (see Figure 5), the total carbon emissions for the code house begin to dwarf the emissions for either version of the Passive House. The accumulation of ten years of operational carbon emissions and larger refrigerant leaks from the code house’s larger heat pump are what is salient on a total emissions basis, not the upfront emissions from any of the building enclosures, Passive House or otherwise. Of course, we should do everything practicable to reduce those upfront emissions, but not at the expense of the emissions reductions brought by Passive House design.

We suspect that the culprit behind this myth of a Passive House carbon emissions backfire is a lapse in systems thinking—a tunnel vision—that happens at two scales: the building scale and the grid scale.

At the building scale, this tunnel vision misses the systems implications of the load reduction that Passive House design brings. When you reduce a building’s heating load you reduce the size of the heating equipment necessary for that building. In an all-electric building that means a smaller heat pump than would otherwise be needed. Skylar’s Passive House required a 1-ton heat pump, rather than the 3.5-ton unit necessary to heat the code minimum version of the house.

That 3.5-ton heat pump is filled with 13.25 pounds of R-410A refrigerant, compared to just 3.56 pounds in the 1-ton heat pump. R-410A has a 20-year global warming potential (GWP) of 4,340. So, given that the typical leakage rate of a heat pump’s refrigerant is 5% per year, this difference in refrigerant volume has big implications for the two houses’ total emissions. Tunnel vision might cause one to focus only on the extra upfront emissions of the insulation or the triple-pane glazing in the Passive House, but those enclosure improvements reduced the heating load, which reduced the size of the heat pump and its volume of refrigerant. In just ten years of operation that will help avoid 18.2 tons CO2e of refrigerant leakage (calculated at the GWP20 value) and 1.8 tons CO2e of upfront emissions embodied in the heat pump, not to mention 37.3 tons CO2e of operational carbon emissions (see Figure 6).

Figure 6   Emissions Context Code vs Foam PH LARGER TYPE

At the grid scale, the tunnel vision misses the fact that the grid is a complex, interconnected system. Just because your utility’s electricity generation may come mostly from clean, renewable sources, the electrons that your building uses are not necessarily low carbon. Zack lives in Seattle, home to Seattle City Light which calls itself “The Nation’s Greenest Utility”, ostensibly because it owns a lot of hydroelectric generation. Thanks in part to this messaging, people in Seattle assume that the city’s electricity is nearly 100% decarbonized. However, the emissions factor for Zack’s electricity in Seattle is about the same as Skylar’s electricity in Boise. Why? Because clean energy “islands” do not exist on our grid. The grid, like a Passive House, is an interconnected system. Utilities that own clean generation might prefer that you not know it, but guidance from the likes of EPA and NREL make it clear that we need to look to larger interconnected regions to understand how “clean” or “dirty” our electricity really is, and therefore how significant our buildings’ operational carbon emissions really are.

figure 7 NERC regions

As seen in Figure 7, Seattle and Boise are part of a massive grid system called the Western Interconnection (WECC) that stretches throughout most of the western half of the U.S. and Canada. It is a complex mix of “clean” and “dirty” energy generation that is both consumed and imported across that vast region. Any building that is connected to the grid exists in a big pool fed by lots of sources of energy, some “clean” and others “dirty”. Seattleites might feel good about their utility’s “clean” contribution to that big pool, but the electricity that Seattle’s buildings take from the pool is as dirty as the average of the energy sources that feed it.

Put another way, the energy that Zack saves by making his house in Seattle more energy efficient means that more of Seattle City Light’s “low carbon” electricity can be used elsewhere where it can offset higher carbon energy generation—say, from coal-powered electricity generation in Montana, for example. Likewise, the big energy savings, compared to a code built home, of Skylar’s Passive House in Boise does the same, because by reducing electricity demand it helps keep the highest cost and dirtiest generation offline. As seen in Figure 8, electricity generation resources are deployed to the grid in order of lowest to highest cost, and because dirty electricity generation is the most expensive, lower demand generally means a cleaner grid.

figure 8 resources clear by cost

Given these vast grid interconnections (known as NERC regions) like the Western Interconnection—with their complex webs of generation, consumption, and energy imports and exports—grid experts have given considerable thought to where to draw meaningful boundaries between regions so that we can approximate reasonably accurate emissions factors for the electricity consumed there. To this end, EPA divided the United States into 26 eGRID regions:

“eGRID subregions are identified and defined by EPA and were developed as a compromise between NERC regions (which EPA felt were too big) and balancing authroties (which EPA felt were generally too small). Using NERC regions and balancing authorities as a guide, the subregions were defined to limit the import and export of electricity in order to establish an aggregated area where the determined emissions rates most accurately matched the generation and emissions from the plants within that subregion."[6]

Art Adiem of EPA and Cristina Quiroz of TranSystems explain further:

“Choosing an aggregation level that is too large (for example, the entire U.S.) includes generation that is not relevant to the regional resource mix. Conversely, an aggregation level that is too small (for example, EGC [“electricity generating company”]) may exclude generation that is relevant to the area…The eGRID subregion level data is generally considered the best generation-based aggregation level that minimizes the import/export issues…Most or all of the system power in each eGRID subregion originates from within an eGRID subregion.”[7]

We mentioned previously that electricity in Boise and Seattle have about the same emissions factor. The actual value of that emissions factor, according to the EPA, is 604 pounds of CO2e per MWh; it is the average emissions factor of the eGRID subregion that both Boise and Seattle belong to: the NWPP (see Figure 9).

figure 9 eGRID subregions

According to ASHRAE the actual average carbon intensity of the electricity that buildings use in the NWPP subregion is even higher than that 604 pounds of CO2e per MWh. This is due to (1) upstream emissions from fossil fuel extraction, processing, and delivery, and (2) transmission losses (see Figure 10). According to ASHRAE 189.1: Standard for the Design of High-Performance Green Buildings, the adjusted eGRID emissions factor for the NWPP subregion is 936 pounds of CO2e per MWh. Electricity in the NWPP subregion is far from clean today, and it is one of the lowest carbon eGRID subregions on the map.

Figure 10   Upstream Grid Emissions Graph LARGER TYPE

Given these numbers, the notion that the electricity that powers Zack’s Seattle home is somehow low carbon today seems naïve (hence the fairy signifying magical thinking in Figure 10). We suggest that readers be highly skeptical of any operational carbon calculations that assume low electricity emissions factors based on “clean electrons”, and equally skeptical of any analyses comparing embodied carbon and operational carbon that do the same. We consider ourselves to be among the most optimistic about the clean energy transition and the decarbonization of our grid. But today our grid is far from clean, and there are no energy islands on such an interconnected system. In fact, the Western Interconnection is so connected in part because it was designed to send electricity generated by the Pacific Northwest’s hydroelectric dams to other states, and this interconnectedness is only going to grow as we transition to geographically diverse renewable electricity. Skylar’s open source tool therefore draws on the ASHRAE 189.1: Standard for the Design of High-Performance Green Buildings tables for estimating operational carbon emissions (using retrospective electricity emissions factors).

That said, what about this progression to clean electricity? It will, after all, decrease the operational carbon emissions of (electrified) buildings over time. It will also reduce the upfront carbon emissions caused by future building materials, components, and construction. Advances in materials science and low-embodied carbon product development will do the same. Likewise, the GWP of refrigerants should decrease rapidly in the future. Everything is evolving fast in our world of building decarbonization, and that is heartening.

The most salient evolution for building designers today, however, is that of the relationship between building energy use and operational carbon emissions. Based on the retrospective electricity emissions data of the ASHRAE 189.1 tables, we can calculate the operational carbon emissions for a building of a certain EUI for the next year, even the next several. But how can we project what those emissions will look like in 15 years or 30 years, when the electricity will be less carbon intensive thanks to the clean energy transition? To assist with this kind of planning NREL has developed its Cambium Tool, projecting long-run marginal emissions rates based on various scenarios, including a “Mid-Case” scenario of a modestly-paced transition, a 95% clean energy by 2050 case, and a 95% clean energy by 2035 case. Skylar has incorporated these data into his open source tool to assist in estimating future operational carbon emissions during the ongoing clean energy transition.

figure 11

Returning in Figure 11 to our case study comparing a code house (chart on the left) with Skylar’s Passive House (chart on the right), the top red line shows the straight-line projection of the average emissions factor for the NWPP eGRID subregion from ASHRAE 189.1. The black line shows the Cambium Tool’s output for the Mid-Case scenario, with the lower operational carbon emission curves reflecting the impact of a modestly paced clean energy transition. The dotted line shows the operational carbon emissions for the buildings in the 95% clean energy by 2050 case, and the dash-dot line shows the operational emissions in the 95% clean energy by 2030 case.

What is crucial to note here is that the total cumulative emissions of the Passive House are lower than the cumulative emissions for the code house in every scenario. Moreover, the total emissions of the Passive House under even the modestly paced “Mid-Case” clean energy transition are still lower than the code house under the very aggressively-paced 95% clean energy by 2030 case. Based on data from the NREL Cambium Tool (for operational carbon emissions projections) and the BEAM Estimator (for embodied carbon emissions), investing in a Passive House enclosure now is a good building decarbonization decision regardless of the pace of the coming clean energy transition.

In closing, we appreciate the opportunity to share this data and rationale with readers and hope that you will explore the open source tool that Skylar has developed to do quick assessments of operational, embodied, and total carbon emissions for your building designs and retrofits. In hopes of sparking dialogue and debate we have been deliberately “open book” in outlining what we view as “best in class” data sources for embodied carbon and operational carbon, and our rationale for viewing them as such.

Upfront carbon, the impact of refrigerants on the CO2e footprint of buildings, and assessments of whether electricity in a region is “clean” or “dirty” are all relatively new areas of knowledge for the AEC community, and we are learning alongside all of you. Based on the emissions data we are seeing from Builders for Climate Action, the U.S. EPA, ASHRAE, and NREL, we see no evidence of a Passive House “burp” in total building emissions except at the very shortest of timescales (1 year, for example).

That is not to say that upfront emissions are not important. They clearly are. But the bulk of upfront emissions come from things like concrete, asphalt shingles, flooring, doors, and gypsum.[8] The insulation and windows in Skylar’s Passive House make up just a small sliver of the home’s upfront emissions but leverage massive savings in operational carbon emissions that will continue for decades. By selecting, whenever feasible, bio-based insulations that store carbon, we can minimize any upfront emissions from our Passive House building enclosures. But let's tackle both operational and upfront emissions head-on by focusing on what will make the biggest emissions impact: addressing the major upfront emissions culprits mentioned previously, and dramatically reducing operational emissions through Passive House load reduction. By doing so we will not only be reducing building emissions with maximum impact, we will also be accelerating the clean energy transition by flattening the wings of the Falcon Curve: the winter heat load of inefficient buildings.





4.      The Falcon Curve Source: Griffith, S. (2022). Electrify: An optimist's playbook for our Clean Energy Future. The MIT Press.

5.      Buonocore, J.J., Salimifard, P., Magavi, Z. et al. Inefficient Building Electrification Will Require Massive Buildout of Renewable Energy and Seasonal Energy Storage. Sci Rep 12, 11931 (2022).

6.      US Environmental Protect Agency. The Emissions & Generation Resource Integrated Database: eGRID Technical Guide with Year 2020 Data.

7.      Diem, A., Quiroz, C. How to Use eGRID for Carbon Footprinting Electricity Purchases in Greenhouse Gas Emissions Inventories. Environmental Protection Agency, July 2012.

8.      US Department of Energy Office of Energy Efficiency and Renewable Energy. Carbon Emissions in a Typical New Production Home: A Case Study. February 2023