Soiling Loss Calculator
The formula
What the soiling loss tells you
What a load actually costs to run over a year — watts-hours-to-dollars conversion for soiling loss, the arithmetic utility bills hide.
Calculation: kWh/yr = W × h/day × days ÷ 1000; cost = kWh × tariff. Enter your inputs and every substitution is shown below the result.
Reading the result
Compare devices by annual cost, not wattage: a 150 W always-on box can out-cost a 2 kW appliance used minutes a day.
Limitations and best practice
Duty cycle, not nameplate, decides bills — motor and heater ratings are peak, and compressors cycle well below it.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
Standby counts?
Solar changes the tariff?
Source & methodology
Basic electrical energy identity.
Soiling Loss: what this tool answers
You are here because you need a specific number, and you want to see how it was produced before you rely on it. Soiling Loss is the kind of number people argue about from memory. This page ends that argument with arithmetic you can watch happen: enter your figures, get Annual energy in real time, and see every substitution printed below.
It helps to separate the mechanics from the interpretation. The mechanics are fixed: kWh/yr = W × h/day × days ÷ 1000; cost = kWh × tariff. Anyone, anywhere, entering the same inputs will get the same 1,363.5 kWh. The interpretation is where experience counts: whether 1,363.5 kWh is good, normal or alarming depends on comparisons covered below, and that is the part most articles about Soiling Loss never explain.
In Environmental & Sustainability the same quantity is often quoted under two or three different conventions. The formula printed above fixes one convention and applies it consistently, which is what makes results from this page comparable with each other.
Nothing below is stock text pasted around a number: the worked example computes annual energy = 1,363.5 kWh from this tool’s own defaults, and the sensitivity section ranks the inputs that move the result — Power draw first, at ≈10.0 % of the headline for a ten-percent error either way in that input. Read the sections in order and you will be able to reproduce every figure by hand.
Every input in Soiling Loss, and what it does to the answer
One formula, published in full: kWh/yr = W × h/day × days ÷ 1000; cost = kWh × tariff. Anything you can read, you can reproduce in a spreadsheet, and that reproducibility is the whole point of printing it rather than hiding it behind a button.
Power draw (watts) (example value 150) is a plain measured quantity — the unit shown in the label is the unit the formula expects. The example value is there to demonstrate the mechanics, not to describe your situation — overwrite it.
Hours per day (example value 18) is a measured number in the unit named by the label; the formula does not convert for you. Use the value as of today, not as of the last time you looked — time fields drift silently.
Electricity price ($/kWh) (example value 0) is a measured number in the unit named by the label; the formula does not convert for you. If your source quotes a figure before and after some deduction, decide which one the formula wants and be consistent for every field.
Days per year (example value 505) is a quantity rather than a category — precision here is cheap and worth having. Use the value as of today, not as of the last time you looked — time fields drift silently.
Soiling Loss with real numbers, step by step
The tool prints its own working; this is the same arithmetic on the example values, reproduced so you can follow it by hand. Starting figures: Power draw (watts), Hours per day, Electricity price ($/kWh), Days per year. The computed annual energy comes out at 1,363.5 kWh, which the interpretation band labels “Serious load — one upgrade cycle pays for itself”.
- kWh/yr = 150 × 18.0 × 505 ÷ 1000 = 1,363.5
- Cost = 1,363.5 × $0.16 = $218.16
Annual cost — $218.16. This is the number experienced users quote when the headline alone would mislead.
Monthly cost — $18.18. This is the number experienced users quote when the headline alone would mislead.
CO₂e at 0.4 kg/kWh — 545 kg. If your inputs change, this is usually the first companion figure to move.
Keep this worked example open while you enter your own figures: matching the shape of the substitution is the fastest way to spot a unit or convention mistake.
The Soiling Loss corridor: your result across a realistic band
The honest version of any estimate is a corridor, and this one is cheap to produce: Soiling Loss was recomputed at 5 points along the dominant input, with every other field left untouched.
| Power draw setting | Annual energy |
|---|---|
| 80 % of the example value | 1,090.8 kWh |
| 90 % of the example value | 1,227.2 kWh |
| example inputs | 1,363.5 kWh |
| 110 % of the example value | 1,499.9 kWh |
| 120 % of the example value | 1,636.2 kWh |
Across 5 settings of Power draw, the result spans 1,090.8 kWh to 1,636.2 kWh. A decision that only works at one row of this table is a decision waiting for an input to move. Reproduce it in the form above by editing Power draw alone; the substitution steps will follow your figures exactly.
The levers behind Soiling Loss, ranked by effect
This list was computed for this specific engine just now: each numeric input was nudged ±10 % while every other field held its example value, and the annual energy was recalculated from scratch. Read it as a map of where Soiling Loss is fragile — drawn for the example inputs, which is the map you want when deciding what to measure carefully.
- Nudge Power draw by ±10 % and Soiling Loss lands between 1,227.2 kWh and 1,499.9 kWh (sensitivity ≈10.0 %)
- Nudge Hours per day by ±10 % and Soiling Loss lands between 1,227.2 kWh and 1,499.9 kWh (sensitivity ≈10.0 %)
- Days per year +10 % → Soiling Loss = 1,499.9 kWh · −10 % → 1,227.2 kWh (the annual energy shifts ≈10.0 %)
Power draw is the dominant lever here: ten percent either way moves the result by about 10.0 %, from 1,227.2 kWh to 1,499.9 kWh. Measure that input from a document rather than from memory, and Hours per day is effectively tied with it (≈10.0 % for the same nudge), so verify the pair together. The rest of the inputs earn only a rounding-error of attention, and that asymmetry is the practical payoff of measuring rather than asserting.
Interpreting the Soiling Loss verdict
A number on its own is trivia; a number against a range is intelligence. On the example inputs the band reads “Serious load — one upgrade cycle pays for itself”; your own figures place you on a different rung of the same ladder. How much of that band is luck? On Power draw alone ten percent either way covers 1,227.2 kWh to 1,499.9 kWh. The practical reading rules: ask what would have to change to move you one band. If the answer is “a small, plausible input difference”, the band itself is not the finding — the uncertainty is.
Set Soiling Loss beside its neighbours and it usually plays a specific role: this figure establishes the size of something, and the neighbouring tools establish whether that size is acceptable. Skipping the first step makes the second one arbitrary.
Common mistakes with Soiling Loss (and the fix)
Duty cycle, not nameplate, decides bills — motor and heater ratings are peak, and compressors cycle well below it. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Chasing precision in Hours per day while Power draw (watts) is still a guess. The sensitivity ranking above shows exactly where the accuracy budget should go.
This model has its own particular trap: Power draw carries ≈10.0 % of the response per ten percent of error, so effort spent elsewhere is largely decorative.
A final trap is presentation: reporting Soiling Loss to more decimal places than the inputs support. The tool prints what the arithmetic gives; you should quote only what your least precise field justifies.
Before you trust your Soiling Loss: a short checklist
- Record the date and the inputs alongside the number so future-you knows what was assumed.
- Compare the output against one published benchmark or a colleague’s independent estimate.
- Put Power draw under a magnifier; the sensitivity table above is the reason why.
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Note the date and the inputs beside the number so the figure can be audited later.
- Run the ±10 % stress on the top two levers and check that your conclusion survives both.
Five steps from raw inputs to a figure you can defend
The tool does the arithmetic; the routine below is what makes the arithmetic trustworthy. Five steps, a minute total — and afterwards you will know not just what the number is, but which assumption produced it.
Step 1 — gather before you type. Soiling Loss depends on power draw (watts), hours per day, electricity price ($/kwh), days per year. Collect them from a source document — a statement, a report, an invoice, a log — rather than from memory, because recalled inputs are the single largest cause of wrong results. When in doubt, prefer the boring input: the interesting one is usually the one you misread.
Step 2 — baseline before exploration. Get one defensible Annual energy on screen before you start nudging numbers. Without a baseline, every variation looks interesting and none of them means anything. A calculation you cannot explain to somebody else is a calculation you cannot defend.
Step 3 — change one input at a time. Nudge a single field by ten percent, watch the headline and its companions move, then undo it. Two or three fields will dominate — the sensitivity table above already ranks them for this engine. Write the assumptions in the same file as the result, and future arguments take minutes instead of meetings.
Step 4 — ask what would have to be true. Take the result you want and work backwards through the inputs until you find the assumption that produces it; then decide honestly whether that assumption is defensible. The inputs are the part of the work that nobody else can do for you.
Step 5 — schedule the next run. In Environmental & Sustainability the inputs drift quietly. Put a reminder a quarter out, re-enter the same fields, and read the change rather than the level. If a result feels obviously right, that is the moment to check the inputs hardest.
Where Soiling Loss matters in practice
Most Energy disagreements are arithmetic disagreements in disguise. When Annual energy of 1,363.5 kWh sits on the table with its working shown, the conversation stops being about who sounds more confident and starts being about which input is wrong. Compare the calculation to the rough guess you arrived with, and ask why they differ.
The companion outputs — Annual cost and Monthly cost — exist for the second stage of that screen: the headline sizes the prize, while the companions describe the trade-off you are accepting to get it. Re-running a number costs seconds; retracting a decision costs considerably more.
Re-running this page costs nothing and catches the slow drifts that never announce themselves. In Environmental & Sustainability the expensive mistakes are rarely sudden; they are small changes in Power draw (watts) that nobody recalculated for a year. The inputs are the part of the work that nobody else can do for you.
Soiling Loss — frequently asked questions
What affects Soiling Loss the most?
Measured on this engine, Power draw is the dominant lever: moving it ±10 % shifts the annual energy across 1,227.2 kWh to 1,499.9 kWh — about 10.0 % of the headline, with Hours per day next at ≈10.0 %. The ranked list in the sensitivity section is computed live, not asserted from a template.
Do hours per day and power draw matter equally?
Soiling Loss here is co-driven: Power draw and Hours per day produced ≈10.0 % and ≈10.0 % responses, which is a tie for practical purposes. Everything below those two is a rounding error by comparison.
What is a typical Soiling Loss?
There is no honest universal average for Soiling Loss, but there is a reference point: the defaults on this page produce 1,363.5 kWh (Serious load — one upgrade cycle pays for itself). Replace the inputs with your own and compare — that comparison is the useful meaning of “typical”.
How do I calculate Soiling Loss by hand?
Three steps: write the formula (kWh/yr = W × h/day × days ÷ 1000; cost = kWh × tariff), insert your values, and simplify. The worked example section shows exactly that chain for the default inputs; replicating it once on paper teaches you more about Soiling Loss than any number of calculator runs.
What happens to Soiling Loss if power draw changes by 10 %?
The engine was re-run with that field moved by ten percent while everything else stayed fixed: the annual energy goes across 1,227.2 kWh to 1,499.9 kWh, a swing of roughly 10.0 % around the 1,363.5 kWh baseline. That ratio is the practical definition of how much this input matters.
Is the Soiling Loss result of 1,363.5 kWh good or bad?
Neither, on its own — the label “Serious load — one upgrade cycle pays for itself” is the band this figure falls in for the example inputs, and your own inputs will place you elsewhere on the same ladder. Judge the number against your history and your alternatives, and remember that a ten-percent error in Power draw alone moves it by ≈10.0 %.
Can Soiling Loss be negative or empty?
Yes, and that is informative rather than broken: a negative Soiling Loss usually means the inputs encode an outflow or a shortfall, and the verdict band above labels exactly that situation instead of hiding it.
Is Soiling Loss auditable?
Yes — the printed steps are the audit trail: inputs, formula, and substitution. This is exactly what reviewers need to re-derive 1,363.5 kWh from your raw records.
Standby counts?
Yes — modern standby rarely exceeds 2 W but 24/7 loads accumulate; the calculator just needs the measured watts.
Solar changes the tariff?
Swap $/kWh for your effective rate; with net metering the export credit is the number to use.
Is my data private on this page?
Yes — computation happens locally in your browser, with no account, no tracking of your inputs and nothing sent to a server. The printed formula is the whole story of what happens to your figures.
Glossary for Soiling Loss
- Annual cost
- $218.16 for the Soiling Loss worked case; it sits next to the main result because it carries context the headline leaves out.
- Monthly cost
- $18.18 for the Soiling Loss worked case; it sits next to the main result because it carries context the headline leaves out.
- CO₂e at 0.4 kg/kWh
- 545 kg on the example inputs — a companion figure printed beside the headline of Soiling Loss so that no result is read in isolation.
- Annual energy
- The primary output of this tool: 1,363.5 kWh for the default inputs, computed exactly from kWh/yr = W × h/day × days ÷ 1000; cost = kWh × tariff.
- Worked example
- The calculation written out in full so that nothing on this page has to be taken on trust.
- Verdict band
- The plain-language label — here “Serious load — one upgrade cycle pays for itself” — mapping the computed figure onto experience-based ranges for Environmental & Sustainability.
- Sensitivity (±10 %)
- How far the Soiling Loss moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Where the Soiling Loss model comes from
There is no black box on this page — the engine evaluates kWh/yr = W × h/day × days ÷ 1000; cost = kWh × tariff. Source of record: Basic electrical energy identity. Any other implementation of this model should return the same figure for the same inputs. If one does not, the difference is in its assumptions — which this page prints and that one probably does not.
Nothing here replaces a qualified professional, and nothing here is approximate either — the arithmetic is exact, and the honesty is in the inputs you supply. The design constraint was set by usefulness rather than by comfort: an estimate you can interrogate beats an answer you have to trust.
After the number: what to do with it
Save the number together with its inputs and today’s date; a Soiling Loss figure without context is unusable the moment an input changes.
Whoever you are (people who need one trustworthy number before their next decision), the next step is the same: replace the example inputs with your own, note the date, and re-run whenever a figure moves. In Environmental & Sustainability, a dated figure is a trend, and an undated one is a rumour.