Understanding CO₂

Viele erwarten exakte Zahlen. In der CO₂-Arbeit gibt es die aber selten. Emissionswerte werden berechnet, nicht gemessen – und hängen davon ab, welche Daten verfügbar sind. Genauigkeit bedeutet hier: sauber gerechnet, nicht „auf die Nachkommastelle perfekt“.

An emission factor condenses many real processes into an average value. This is normal, intentional, and necessary – otherwise no one could calculate emissions in practice. Each company would have to measure every single emission itself. Once you understand this, you no longer expect false precision.

For example: No one measures exactly how much CO₂ was released during the production of this particular sheet of paper. We therefore work with averages – practical, traceable, and entirely sufficient for decision-making.

CO₂e makes different gases comparable.
Methane, nitrous oxide and others affect the climate with varying strength. Converting them into CO₂ equivalents creates a shared language. This allows emissions to be combined meaningfully without ignoring individual gases.

At the same time, CO₂e highlights where the real drivers are inside a company: often not where one would intuitively expect CO₂, but in processes that generate methane or nitrous oxide – for example, certain materials, food products, or chemical processes.
CO₂e helps with calculations and prioritisation: those who understand how strongly these gases act can better identify which decisions have real impact.

An emission factor describes how much CO₂ is released per kilowatt-hour, kilometre, or kilogram of material. These factors vary by source, region, or production method.

They are deliberately expressed as averages so that companies remain able to work. No one can measure each delivery, each kilogram of material, or each litre of fuel individually.

Diesel refined in Europe may have a different factor than diesel from another region – but the number remains a practical guide.
Emission factors help with orientation: high, low, unexpectedly large? Often, that’s all you need to make decisions that truly move a company forward.

Most emissions arise where something is consumed or moved. Electricity bills, heating, business travel, purchased goods – for a first understanding, that’s usually enough. The scope logic helps later for classification but isn’t needed at the beginning.

Many companies realise quickly: The “usual suspects” aren’t always the biggest hotspots.

Relevant emissions often sit in areas people hardly notice in daily work – such as materials or external services.
Starting with this simple perspective helps you identify where it’s worth taking a closer look. The detailed scope classification can follow once the basics are understood and the first Aha moments have appeared.

Whether paper, steel, or packaging: Production usually causes more emissions than transport. That’s why it pays to analyse material flows early.

Many companies assume travel or logistics are the biggest contributors. In reality, the CO₂ backpack is already inside the product long before it reaches your premises.

A single paper product, for example, generates far more emissions in paper production than in transport to the print shop. 

This insight helps with prioritisation. Those who know which materials carry weight can make decisions that have far greater impact than optimising individual journeys.

Climate impact describes how strongly something influences the greenhouse effect. It is not about morality but about physics: How much radiative forcing does a gas cause? How does it contribute to warming?
This simple perspective clears up many misunderstandings.

Once you look at climate impact this way, classification becomes much easier. Different activities produce different gases – not all are equally strong, but all contribute to warming.

This sober view helps shift discussions away from “good” or “bad” and towards what actually matters: the effect, not the judgment.

Not every electricity mix has the same CO₂ value.
Depending on the country, season, or provider, the share of renewables varies. This explains why electricity cannot be labelled simply as “clean” or “dirty.”

The CO₂ value of a kilowatt-hour depends strongly on how it was produced at that moment. With plenty of wind or sun, the value drops. When fossil power plants are running, it rises.

The same kilowatt-hour causes almost no emissions in Norway but significantly more in Poland – because of the local electricity mix.

These differences are normal. They show that electricity is a dynamic product whose climate footprint changes across regions.

Models work with assumptions – and that is both intentional and necessary. Exact data would neither be available nor practical in many areas. Models make complex processes usable and still allow reliable decisions.

In everyday business, it would be impossible to measure every single production step. Supply chains are too large and too complex. Models bridge this gap: they represent typical processes and generate values close enough to reality to base decisions on.

No one knows the exact CO₂ emissions from manufacturing each individual screw – but model values provide estimates that are entirely sufficient for strategy and comparisons.
Perfection is less important than having a direction and a basis for decision-making.

Compensation means: emissions here are balanced by reductions or removals elsewhere.

The idea is purely physical: If emissions cannot be avoided at one point, their effect is reduced at another. It is not about “buying one’s way out” but about offsetting the overall climate impact.

Reduction always comes first; compensation addresses what cannot currently be avoided.
For many companies, this is a pragmatic way to take responsibility while continuing to reduce emissions step by step. Both approaches belong together – simply in the right order.


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natureOffice Perspective

At natureOffice, we look at this with a little more nuance. What is “avoidable” is rarely clear-cut in day-to-day business. Many decisions are not black-and-white but somewhere in between.

Should a client meeting be cancelled or moved online? What if meeting in person builds trust that digital formats cannot replace?

What about production processes that are technologically fixed?

Should a company replace a machine earlier “for the sake of the balance sheet” – or might that be worse for the environment?

What about employees who depend on a car because public transport is not available where they live?

Or materials for which no lower-impact alternative currently exists?

And who decides at what point something becomes “no longer reducible”?

In practice, economic, organisational and social realities often collide with theoretical recommendations. Companies operate within trade-offs, not perfect solutions.

That’s why we see reduction and compensation not as a strict sequence but as two pathways that can run in parallel:
reduce where possible, and be transparent about what remains.

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