For all model results shown here, the following building geometry was used. This geometry is based on the drawings/models received on May 1, 2026. The model geometry used for this assessment includes both the building and the local shading context. For details on the context shading see the windows site shading section.

As shown in the results below, in order to assess the building performance we have tested the building in five distinct configurations (variants):

1. Code-Minimum: A version which meets but does not exceed the NYC Energy Code 2025 / Zone 4(A) code minimums for assembly R-values, window U-values, airtightness and equipment efficiencies. This variant assumes a typical residential “extract-only” (bath fan) ventilation system, and that the building uses all-electric appliances and equipment for heating, cooling, hot-water and cooking.

2. Improved Envelope: This variant improves the window U-values, assembly R-values, and total airtightness of the building beyond the “code-minimum” levels, but not quite to full “Passive House” level.

3. Improved HVAC: This variant includes a dedicated fresh-air ventilation system with heat recovery (HRV). This system is assumed to be a “basic” HRV with 70% heat-recovery (unit). This variant shows a slight increase in the overall site-energy, due to the increased fan-energy needed.

4. PHI EnerPHit ‘By Component’ [RECOMMENDED]: A variant which meets the stringent Passive House Institute (PHI) EnerPHit (Energy Retrofit) standard’s prescriptive targets for envelope U-values, airtightness, windows, and equipment efficiencies. This variant also includes a high performance ERV system for fresh-air ventilation.

5. PHI EnerPHit ‘By Demand’ : A version which increases assembly R-values, window U-values, and mechanical system efficiencies to meet the PHI-EnerPHit ‘by Demand’ energy performance certification criteria. Due to the higher level of wall insulation required at the existing brick masonry, this variant is not recommended in this case.

“Site Energy” represents the energy purchased by the building and delivered to the site by the utility. This is the most typical energy use figure assessed when considering a site “Net-Zero” building energy balance, or when considering the annual cost of energy for the building. This site-energy total is made up of 6 main groups: heating, cooling, hot-water, lighting, electric equipment (appliances, electric-vehicles, etc), and pumps / fans.

In order to assess the performance of the home across a range of options, we have simulated 5 distinct variants with different energy efficiency measures (see the Model Variants section for all the details on the specific variant inputs). In this case, compared to the “existing” home any of the variants assessed are likely to provide significant reductions in site energy consumption.

Carbon Dioxide and other types of pollution which results from energy consumption are mainly responsible for the increased warming of the earth’s atmosphere and water. In order to reduce the risk of global climate change it is important to reduce all CO_2e (CO₂ Equivalent) emissions related to the buildings, industry and transportation across all sectors. While there is much debate about the specific targets these reductions should achieve, one useful method suggests that by 2030 each individual will need to meet an annual ‘Carbon Budget’ of roughly 2.3 tons-CO_2e per person for all activities. This would mean that an average individual’s annual carbon emissions might include approximately 1 ton-CO_2e / year related to their housing and building inhabitation, 1 ton-CO_2e / year for their transportation, and another 0.3 tons-CO_2e / year for food. For reference, a single US-to-Europe round trip flight currently releases approximately 4 tons of warming gases into the atmosphere. This 1 ton/person target for building emissions gives us a useful benchmark for this building’s annual CO_2e emissions. Given an average annual occupancy of approximately 4 people, this building should ideally see a total annual CO_2e emissions footprint of less than about 4 tons-CO_2e / year.

Based on the modeled source energy and fuel types for the various energy uses of the building we can approximate the average annual CO_2e emissions which will result. CO_2e emission totals shown below are those which result from fuel usage by the building for heating, cooling, hot-water and all other plug-loads. The total amount of CO_2e emitted as a result of each use-type depends on both the amount of fuel used as well as the type of fuel (gas, electricity, etc.). Although fuel-fired heating systems are permitted by Code, for this evaluation we have modeled all variants with electric-powered heat-pump systems only.

Output Emission Rates used are from the NY (NYCW) Subregion. For more information on these factors see the EPA eGRID Data Explorer. Source Energy Factors for all fuel types are taken from the EPA EnergyStar Portfolio Manager Technical Reference (2023).

In order to evaluate a building’s performance, total annual energy consumption is key, as shown above. However, in addition to this top line figure the ‘Passive House’ framework suggests that the building should also meet additional heating and cooling annual energy demand performance targets. It is also useful to compare the peak-heating and peak-cooling loads to the recommended limits for Passive House buildings. While these limits are not required for certification in all cases, it is still good practice to attempt to meet them where possible. Where the home fails to meet these targets is a clear indication that improvements are possible.

Shown below are results for these assessment metrics, for each of the tested variants.

For all the modeled cases shown in the following sections, climate data from the nearest weather station was used.

The data from this climate set is illustrated here for reference purposes. It should be noted that for the Passive House energy models, monthly average climate data are used and therefore may appear different from the more typical ASHRAE hourly data shown in some other US Energy Modeling programs. The monthly data is all derived from the same sources (local weather stations) as the typical ASHRAE data however.