Technical documentation
Methodology & Assumptions
The equations, variables and engineering assumptions that turn your energy data into a CarbonShift Pro estimate. Every number is traceable.
Carbon footprint
A carbon footprint is the total mass of greenhouse gases attributable to an activity or entity over a defined time period — usually one year. It is an accounting construct, not a physical measurement, and its value depends on the boundary you draw around the activity.
CarbonShift Pro draws a narrow, operational boundary on purpose: the energy you consume directly as electricity, heating fuel and transport. Food, goods, air travel, construction materials and the embodied emissions of equipment are out of scope.
CO2 equivalent (CO2e)
CO2e expresses several greenhouse gases as a single number by weighting each gas by its global warming potential over a 100-year horizon. One kilogram of methane, for example, counts as many kilograms of CO2e because its warming effect is stronger per kilogram over that period.
CarbonShift Pro reports category results in kg CO2e/year and total footprint in tonnes CO2e/year (1 tonne = 1,000 kg).
Electricity emissions
Electricity emissions are calculated by multiplying annual electricity consumption by the grid emission intensity of the selected region. When you enter a monthly value, CarbonShift Pro scales it by 12. This ignores seasonal variation in both consumption and grid mix.
CO2e_electricity [kg CO2e/year] = E [kWh/year] × I_grid [kg CO2e/kWh]
E = annual electricity consumption
(or monthly consumption × 12)
I_grid = regional grid emission intensity- E[kWh/year]
- Annual electricity consumed at the meter. Read from a utility bill or estimated from monthly use.
- I_grid[kg CO2e/kWh]
- Average emissions per kilowatt-hour generated on the regional grid. A location-based average, not a marginal or market-based rate.
- CO2e_electricity[kg CO2e/year]
- Estimated annual greenhouse-gas emissions from electricity use.
Grid intensity is a regional average. It does not capture time-of-use variation, marginal generation, transmission losses beyond what the published factor includes, or a specific retail green-energy contract.
Solar PV
Annual solar generation is estimated from installed DC capacity, average equivalent full-sun hours per day, and a performance ratio that bundles inverter, thermal, soiling and wiring losses.
E_solar [kWh/year] = P [kWp] × H [h/day] × 365 [days/year] × PR P = installed DC capacity of the array H = average equivalent full-sun hours per day PR = performance ratio (system losses)
- E_solar[kWh/year]
- Estimated annual solar energy production.
- P[kWp]
- Installed DC power rating of the photovoltaic array under standard test conditions (1,000 W/m², 25 °C).
- H[h/day]
- Average number of hours per day that the array receives irradiance equivalent to full sun. Strongly dependent on latitude, climate and season.
- PR[ratio]
- Performance ratio: the fraction of theoretical production actually delivered after inverter, thermal, soiling, shading, wiring and mismatch losses.
Why actual production varies
- Weather and clouds reduce irradiance and can cause rapid short-term fluctuations.
- Orientation and tilt determine how directly the array faces the sun across the year.
- Shading from trees, buildings or roof features disproportionately cuts output.
- Temperature reduces module efficiency; hot days lower output even under clear skies.
- System losses include inverter efficiency, soiling, wiring resistance and module mismatch.
- Location sets the available solar resource — latitude, altitude and local climate all matter.
Avoided emissions assume generated solar energy displaces grid electricity at the regional average intensity. In practice, the avoided emissions depend on which generator is at the margin when the array produces.
Wind energy
The power available in wind increases with the cube of wind speed. Small-wind output is estimated from a simplified power relationship, then converted to annual energy using a capacity factor.
P_wind [W] = ½ × ρ [kg/m³] × A [m²] × v³ [m/s] × Cp × η ρ = air density A = swept area of the rotor v = wind speed Cp = power coefficient (Betz-limit ideal ≈ 0.59, real turbines lower) η = combined drivetrain and electrical efficiency
- ρ[kg/m³]
- Air density. Lower at higher altitudes and higher temperatures.
- A[m²]
- Swept rotor area, roughly π × (blade diameter/2)². Doubling the diameter quadruples the swept area.
- v[m/s]
- Wind speed at hub height. Because power scales with v³, a 20% increase in wind speed roughly doubles available power.
- Cp[ratio]
- Power coefficient: the fraction of wind kinetic energy the rotor can extract. The theoretical Betz limit is ~59%; real turbines are typically 35–45%.
- η[ratio]
- Drivetrain, generator and electrical losses combined.
CarbonShift Pro converts this into annual energy using an illustrative capacity factor. Capacity factor is the single most sensitive input: a modest change in mean wind speed changes output substantially because available power scales with the cube of wind speed.
Assumptions
The table below lists the default parameters CarbonShift Pro uses when you do not override them. Every value is currently a placeholder and should be replaced with cited, published data before the results are used for any decision.
| Parameter | Value | Unit | Source | Explanation |
|---|---|---|---|---|
| DEFAULTElectricity | 0.4 | kg CO2e/kWh | Unverified placeholder | Generic fallback used when no regional factor is configured. |
| CA:NSElectricity | 0.6 | kg CO2e/kWh | Unverified placeholder | — |
| CA:ONElectricity | 0.05 | kg CO2e/kWh | Unverified placeholder | — |
| CA:QCElectricity | 0.02 | kg CO2e/kWh | Unverified placeholder | — |
| CA:ABElectricity | 0.5 | kg CO2e/kWh | Unverified placeholder | — |
| CA:BCElectricity | 0.03 | kg CO2e/kWh | Unverified placeholder | — |
| US:CAElectricity | 0.25 | kg CO2e/kWh | Unverified placeholder | — |
| US:NYElectricity | 0.22 | kg CO2e/kWh | Unverified placeholder | — |
| US:TXElectricity | 0.4 | kg CO2e/kWh | Unverified placeholder | — |
| US:WAElectricity | 0.1 | kg CO2e/kWh | Unverified placeholder | — |
| naturalGasHeating | 1.9 | kg CO2e/m³ | Unverified placeholder | — |
| heatingOilHeating | 2.7 | kg CO2e/L | Unverified placeholder | — |
| propaneHeating | 1.5 | kg CO2e/L | Unverified placeholder | — |
| gasolineTransport fuel | 2.3 | kg CO2e/L | Unverified placeholder | — |
| dieselTransport fuel | 2.7 | kg CO2e/L | Unverified placeholder | — |
| gasolineVehicle consumption | 8.9 | L/100 km | Unverified placeholder | Assumed average gasoline car consumption. Your own vehicle may differ substantially. |
| dieselVehicle consumption | 7.2 | L/100 km | Unverified placeholder | Assumed average diesel car consumption. |
| hybridVehicle consumption | 5.2 | L/100 km | Unverified placeholder | Assumed average hybrid consumption, burning gasoline. |
| electricVehicle consumption | 18 | kWh/100 km | Unverified placeholder | Assumed average battery-electric energy use, charged from the regional grid. |
| noneVehicle consumption | 0 | L/100 km | Unverified placeholder | — |
| busTransit | 0.09 | kg CO2e/passenger-km | Unverified placeholder | — |
| railTransit | 0.04 | kg CO2e/passenger-km | Unverified placeholder | — |
| solarSpecificYieldRenewables | 1100 | kWh/kWp/year | Unverified placeholder | Site-specific. Depends on irradiance, tilt, azimuth and shading. |
| solarSunHoursRenewables | 4 | equivalent full-sun hours/day | Unverified placeholder | Annual daily average of peak-sun-equivalent hours. Strongly site-, tilt- and shading-dependent. |
| solarPerformanceRatioRenewables | 0.8 | ratio | Unverified placeholder | Accounts for inverter, temperature, soiling and wiring losses. |
| windCapacityFactorRenewables | 0.25 | ratio | Unverified placeholder | Small-wind capacity factor varies strongly with hub-height wind speed. |
| batteryRoundTripEfficiencyRenewables | 0.9 | ratio | Unverified placeholder | — |
| efficiencyRetrofitSavingRenewables | 0.15 | fraction of annual consumption | Unverified placeholder | — |
| Result uncertainty bandReporting | ±20% | fraction | CarbonShift Pro placeholder | Indicative band applied to totals. Not a propagated uncertainty analysis. |
Limitations
CarbonShift Pro is designed for education and early-stage exploration. It is not a substitute for professional services or official carbon accounting.
Professional energy audits
A full audit inspects equipment, envelope, controls and operational schedules on site.
Engineering design
System sizing, electrical design and interconnection require licensed engineering review.
Electrical assessments
Panel capacity, grounding, protection and code compliance must be verified by a qualified electrician.
Solar-site assessments
Real solar yield depends on shading, roof condition, structural load and local irradiance data.
Official carbon accounting
Regulatory or corporate reporting requires verified factors, audited boundaries and documented uncertainty.
Annual averages only
CarbonShift Pro does not model hourly, seasonal or time-of-use variation in consumption or grid mix.
- Location-based grid intensity is used, not market-based or marginal accounting.
- The operational-energy boundary excludes embodied and consumption-chain emissions.
- Battery storage shifts energy; its emissions benefit depends on grid timing and dispatch.
- The ±20% uncertainty band is illustrative and not a propagated statistical uncertainty analysis.
Data provenance
CarbonShift Pro distinguishes three kinds of data so you can see where each number comes from and how much confidence to place in it.
Values read from an instrument or utility bill. CarbonShift Pro never generates these; you supply them.
Numbers you typed, whether read from a bill or approximated from memory. Accuracy is inherited from your source.
Anything the app derives: emissions totals, solar and wind yield, and reduction potential.
Consumption entered from a utility bill is measured data that becomes user-provided input. Everything CarbonShift Pro returns is an estimate.
Factors are held in a single configuration module so they can be replaced without touching calculation or interface code. Replace the placeholder values with cited, published data, set verified: true, and update the source and year fields.





