Lowering streaming video quality: what impact does it have on CO₂ emissions?

Choosing a lower resolution instead of HD or 4K when streaming a video significantly reduces the amount of data transferred. But what does that actually mean for its carbon footprint?

First, where does the digital sector stand in global emissions?

In 2024, the world emitted 53.2 billion tonnes of CO₂e.

Emissions from the digital sector accounted for around 0.75 billion tonnes, or 1.4% of the total.

That is equivalent to three quarters of the emissions from kerosene used by all civil aviation, or twice the emissions generated within France’s borders.

Understanding what happens when you watch a video on YouTube or Netflix, for example

Before you click

A video is stored in several versions (high quality, medium quality, lower quality, etc.) on YouTube or Netflix servers. These servers are housed in data centers (large buildings filled with computing equipment).

When you click Play

Your device tells YouTube or Netflix: “Send me this video.”

That is when the delivery begins:

  • 1 user watches the video = 1 delivery to make
  • 1 million users watch it = 1 million deliveries

1. The data center: the warehouse

If you choose the 1080p version rather than the 480p version, you simply access one version rather than the other. Choosing the 1080p stream rather than the 480p stream makes relatively little difference to the data center's electricity use.

→ Lowering video quality makes little difference to the data center's electricity use

2. Networks: the delivery route

The video now has to travel from the data center to your device.

That is the role of networks, and this has nothing to do with social networks. Here, we mean fiber-optic lines, cables, routers, home Internet gateways, 4G and 5G antennas… Together, they form something like a road network that allows data to move around.

For networks, the difference is very tangible.

For 1 hour of video:

  • 1080p → 2.25 GB
  • 720p → 1.13 GB
  • 480p → 0.50 GB
  • 360p → 0.32 GB

Going from 1080p to 480p therefore means around 78% less data to transport.

→ Lowering video quality = far less data to transport across networks.

In 2024, ≈ 65% of the data volume carried over networks was video streaming.

3. Your device

The data finally reaches your phone, computer or television.

Your screen stays on throughout the video, whether it is playing in 1080p or 480p.

According to , a device's electricity use depends mainly on factors such as screen size, display technology and brightness.

Displaying a video in 1080p rather than 480p makes little or virtually no difference to the device's own electricity use.

→ Lowering video quality makes little or virtually no difference to the device's electricity use.

In summary

The main benefit of lowering a video's quality is that it reduces the amount of data that networks have to transport.

We saw that the digital sector emitted 0.75 billion tonnes of CO₂e in 2024. According to , networks account for 27% of those emissions:

ℹ️ Networks emit much more than data centers even though they use about the same amount of electricity. Why?

Emissions from manufacturing and maintaining infrastructure are slightly higher for data centers than for networks. And the two use roughly the same amount of electricity in operation.

So why do networks emit much more? Because the electricity used to run them is more carbon-intensive than the electricity used by data centers.

Large data-center operators have more choice over where they locate their infrastructure and what electricity they use. This lets them favor regions and electricity sources with lower carbon intensity. Microsoft, Amazon, Google, Meta and Apple, which together accounted for around 35% of data-center electricity use, reported matching the equivalent of 100% of their consumption with renewable energy.

Networks, by contrast, have to be deployed where users are. They therefore depend more heavily on locally generated electricity, whose carbon intensity varies from country to country. In 2025, generating 1 kWh of electricity emitted an average of around 41 gCO₂e in France, 330 g in Germany, 384 g in the United States and 670 g in India.

This is the main reason networks generate more emissions than data centers despite comparable electricity use.

That could change, however, with the rise of AI: electricity demand from data centers is growing very rapidly. In the United States, some projects already envisage new gas-fired generation capacity, a fossil-fuel source that emits CO₂, to meet that growth.

Sources: ·

78% less data does not mean 78% less energy

Reducing data volume does not reduce electricity use by the same proportion.

Yet one common method is to allocate all the electricity used by networks across the data they carry. Under this approach, the more data-intensive a video is, the more energy is attributed to it. For example, using the energy-intensity formulas adopted by , if you watch over Wi-Fi:

  • 1080p → ≈ 525 Wh → ≈ 233 gCO₂e, equivalent to about 1.4 km by car (about 0.9 miles)
  • 480p → ≈ 136 Wh → ≈ 60 gCO₂e, equivalent to about 0.4 km by car (about 0.2 miles)
ℹ️ See the calculation details and assumptions
Data transferred over 2 h 28 min

Full HD 1080p: 5 Mbit/s × 8,880 s ÷ 8 ÷ 1,000 = 5.55 GB

SD 480p: 1.1 Mbit/s × 8,880 s ÷ 8 ÷ 1,000 = 1.221 GB

The bitrate is multiplied by the duration in seconds. We divide by 8 to convert bits to bytes, then by 1,000 to obtain gigabytes.

Electricity allocated to the session: Fraunhofer model

Annual allocation: Energy Intensity Model

The model allocates to the session a share of each part of the network's annual electricity consumption, based on the volume of data transferred.

Allocated electricity = data transferred × energy intensity

For a fixed Wi-Fi connection. The calculation distinguishes between two parts of the network:

Network core: 0.02 kWh/GB

Fixed access network: 0.07 kWh/GB

This gives:

Electricity allocated to the network core = data transferred × 0.02 kWh/GB

Electricity allocated to the fixed access network = data transferred × 0.07 kWh/GB

The calculation covers the network core and access network, as well as the CDN (“Content Delivery Network”), the network of servers hosted in data centers that delivers the video. For a fixed connection, it also includes the CPE (“Customer Premises Equipment”), the equipment installed at the user's premises, such as an Internet router or gateway.

The end-user device (computer, smartphone or television) is not included because its energy use depends mainly on the screen and generally varies little with video quality. Initial ingest and encoding are not allocated to each viewing session either, since they take place before the video is watched.

The CDN is estimated at 0.5 W per viewer.

For a fixed connection, CPE is estimated at 10 W in the VDSL scenario used here.

In Full HD 1080p

Electricity allocated to the network core: 5.55 GB × 0.02 kWh/GB = 111 Wh

Electricity allocated to the fixed access network: 5.55 GB × 0.07 kWh/GB = 388.5 Wh

CDN: 0.5 W per viewer × 2.47 h = 1.23 Wh

CPE: 10 W in the VDSL scenario used here × 2.47 h = 24.67 Wh

Total: network core + fixed access network + CDN + CPE = 525 Wh

Emissions: 0.5254 kWh × 443.8 gCO₂e/kWh ≈ 233 gCO₂e

In SD 480p

Electricity allocated to the network core: 1.221 GB × 0.02 kWh/GB = 24.42 Wh

Electricity allocated to the fixed access network: 1.221 GB × 0.07 kWh/GB = 85.47 Wh

CDN: 0.5 W per viewer × 2.47 h = 1.23 Wh

CPE: 10 W in the VDSL scenario used here × 2.47 h = 24.67 Wh

Total: network core + fixed access network + CDN + CPE = 136 Wh

Emissions: 0.13579 kWh × 443.8 gCO₂e/kWh ≈ 60 gCO₂e

What about a mobile connection?

The same principle is applied, but with a different energy intensity for the access network:

Network core: 0.02 kWh/GB

Mobile access network: 0.2 kWh/GB

Electricity allocated to the network core = data transferred × 0.02 kWh/GB

Electricity allocated to the mobile access network = data transferred × 0.2 kWh/GB

Equivalent distance by car

The distances shown correspond to the emissions of an average petrol-powered internal-combustion car, estimated by at 170 gCO₂e per kilometer, including manufacturing and use. The calculation divides the session's emissions by 170. This comparison provides an order of magnitude; its scope is not identical to that of the video session.

Carbon factor used

The carbon factor used is 443.8 gCO₂e/kWh, according to (2025 global average). The results are estimates based on the assumptions set out above.

These values describe simplified scenarios and are not universal.

But what these figures mainly answer is: “what share of networks' overall electricity consumption can be allocated to this video?”

They do not tell us how much electricity is actually saved at the moment you lower the quality.

In reality, the network is already consuming electricity before your video starts

Networks are not “virtual”: they are physical infrastructure that exists and consumes electricity continuously.

Of their total emissions, approximately:

  • 15% → manufacturing and maintaining equipment (laying kilometers of fiber-optic cable on land and under the oceans, building and maintaining 4G/5G antennas, installing and replacing routers, manufacturing and launching telecommunications satellites…).
  • 85% → the electricity needed to operate it (much of that electricity is consumed regardless of what happens, even when very little data is being transferred. Worldwide, around one third of electricity is still generated from coal, the fossil fuel that emits the most CO₂).

Networks are sized to carry the large volumes of data that flow during peak periods. But even when they are lightly used, their capacity remains in place, so they continue to consume a great deal of electricity. A large part of that consumption is therefore independent of traffic: carrying more data adds only a relatively small increment.

You can picture it as a train that is already ready to leave. One hour of video in 1080p represents 100 boxes. A 480p video represents only 22. Removing 78 boxes lightens the load, but it does not make the train, tracks, stations or signaling any smaller.

This is what the Power Model captures. It was developed from the work of and later used by .

Returning to our example: suppose you watch the movie Inception over Wi-Fi. Applying Fraunhofer's chosen values from this model, the network's estimated electricity consumption during viewing becomes:

  • 1080p → baseline consumption + a small increment ≈ 42.6 Wh
  • 480p → the same baseline consumption + a smaller increment ≈ 42.1 Wh

That is a difference of 0.5 Wh, despite 78% less data.

ℹ️ See the calculation details and assumptions
Data transferred over 2 h 28 min

Full HD 1080p: 5 Mbit/s × 8,880 s ÷ 8 ÷ 1,000 = 5.55 GB

SD 480p: 1.1 Mbit/s × 8,880 s ÷ 8 ÷ 1,000 = 1.221 GB

The bitrate is multiplied by the duration in seconds. We divide by 8 to convert bits to bytes, then by 1,000 to obtain gigabytes.

Energy consumed during the session: Fraunhofer's Power Model

Unlike the previous model, this calculation estimates electricity consumption over the viewing period. For each part of the network, it adds a baseline power draw to a component that increases with bitrate.

Power = baseline power + (traffic-related coefficient × bitrate)

Energy consumed = power × duration

For a fixed Wi-Fi connection. The calculation distinguishes between two parts of the network:

Energy consumed in the network core = [1.5 W + (0.03 W per Mbit/s × bitrate)] × duration

Energy consumed in the fixed access network = [5 W + (0.02 W per Mbit/s × bitrate)] × duration

As in the previous calculation, the scope also includes the CDN and, for a fixed connection, the CPE. The end-user device, initial ingest and encoding are not included.

The same assumptions are used:

CDN: 0.5 W per viewer

CPE: 10 W in the VDSL scenario used here

In Full HD 1080p

Network core: [1.5 W + (0.03 W per Mbit/s × 5 Mbit/s)] × 2.47 h = 4.07 Wh

Fixed access network: [5 W + (0.02 W per Mbit/s × 5 Mbit/s)] × 2.47 h = 12.58 Wh

CDN: 0.5 W per viewer × 2.47 h = 1.23 Wh

CPE: 10 W in the VDSL scenario used here × 2.47 h = 24.67 Wh

Total: network core + fixed access network + CDN + CPE = 42.6 Wh

In SD 480p

Network core: [1.5 W + (0.03 W per Mbit/s × 1.1 Mbit/s)] × 2.47 h = 3.78 Wh

Fixed access network: [5 W + (0.02 W per Mbit/s × 1.1 Mbit/s)] × 2.47 h = 12.39 Wh

CDN: 0.5 W per viewer × 2.47 h = 1.23 Wh

CPE: 10 W in the VDSL scenario used here × 2.47 h = 24.67 Wh

Total: network core + fixed access network + CDN + CPE = 42.1 Wh

What about a mobile connection?

The same model is applied using the parameters selected for the LTE mobile scenario:

Energy consumed in the network core = [0.2 W + (0.03 W per Mbit/s × bitrate)] × duration

Energy consumed in the mobile access network = [1 W + (1.5 W per Mbit/s × bitrate)] × duration

These values make it possible to repeat the calculation for a mobile connection without adding a second full example.

These values describe simplified scenarios and are not universal.

This does not mean the data volume does not matter. It means the networks are already there, powered on and sized to carry a lot of it.

Despite this small immediate increment, overall network electricity consumption is indeed rising: according to , it increased by around 8% between 2020 and 2024.

Reducing data therefore changes the network's immediate electricity use only slightly, but the issue is still real, and it is mainly over the longer term that the effect can become significant.

The real effect comes over the long term, through infrastructure

The volume of data carried by networks keeps increasing.

As explain, when existing network capacity approaches its limits during traffic peaks, operators have to reinforce the network: adding or replacing equipment, increasing infrastructure density in some areas, or deploying new technologies, as happened in the transition from 4G to 5G.

That new equipment then adds its own baseline electricity consumption, even when it is not being used at full capacity.

Network operation is therefore not simply proportional to the amount of data being carried at any given moment. Capacity tends to increase in steps instead: when the network approaches its limits, capacity is added; the network then has headroom again until the next upgrade is needed.

As show, a lasting reduction in the demand that contributes to traffic peaks can slow network expansion. Existing infrastructure then has more headroom and can absorb traffic growth for longer before it needs to be reinforced.

Over time, where the technology allows it, some equipment can also be put into sleep modes during off-peak periods, further reducing this baseline consumption.

This long-term effect is real, but its magnitude depends on many factors: how traffic evolves, the technologies used, and how operators size and run their networks. It is therefore not quantified in this article.

In summary

Less data does not immediately mean proportionally fewer emissions. The benefits emerge mainly when lower demand helps delay, reduce or avoid the addition of new network capacity.

Reducing video quality collectively and consistently over time → Less data transported → More capacity available during traffic peaks → Less pressure to reinforce the network → Over time, lower baseline electricity use and fewer emissions

ℹ️ If I live in a country with low-carbon electricity, is the impact negligible?

Generating 1 kWh of electricity does not produce the same amount of CO₂ in every country. In France, where nuclear power and renewables play a major role, electricity is far less carbon-intensive than in countries that rely more heavily on coal or gas.

These are the average emissions from generating 1 kWh of electricity in 2025:

FR41gCO₂e/kWh CA191gCO₂e/kWh GB217gCO₂e/kWh IT285gCO₂e/kWh DE330gCO₂e/kWh US384gCO₂e/kWh CN525gCO₂e/kWh IN670gCO₂e/kWh

Saving 1 kWh therefore avoids less CO₂ in France than in a country with more carbon-intensive electricity.

But watching a video from France does not mean that all the electricity needed to transmit it is generated in France. In exploratory tests carried out by Load Less (), some YouTube videos watched from France were, for example, served from infrastructure located in Germany or Italy. Part of the electricity involved can therefore be more carbon-intensive than the electricity in the viewer's country.

And the estimates presented here concern electricity consumption and CO₂e emissions. They do not cover other environmental impacts on resources, air, water or soil.

Apply these settings automatically with the free Load Less extension

You can lower video quality manually on streaming platforms, but the settings have to be adjusted platform by platform, and they are not always retained from one session to the next.

To make those settings systematic, we created Load Less, a free extension for Chrome and Firefox.

It automatically applies and maintains data-saving video settings on major streaming platforms, including YouTube, Netflix, Prime Video, Disney+, Twitch and Vimeo.

It also reduces unnecessary data use, for example by lowering YouTube quality while a video is playing in a background tab, or by preventing some video players embedded on websites from loading until you actually play them.

The goal is simple: transfer less data in everyday use without having to think about it, and thereby help reduce, over the long term, the pressure placed on networks and the emissions that result.

Sources

ℹ️ Show sources and methodological notes

1

European Commission, JRC/EDGAR, GHG Emissions of All World Countries - 2025 Report, 2025. 2024 data on global and sectoral emissions. The percentages and comparisons presented in the introduction are calculated by Load Less from this source and source 2.

2

Two Ericsson publications are used in this article for data on electricity consumption, emissions and changes in digital infrastructure.

Sustainability in ICT - Decrease in ICT’s Carbon Footprint Slows Down, Ericsson Mobility Report. 2024 estimates of the digital sector's electricity consumption and emissions. The percentages and comparisons presented in the introduction are calculated by Load Less from this source and source 1.

ICT Energy Evolution: Telecom, Data Centers, and AI, white paper. Data drawn from companies' public disclosures.

4

Sandvine, The Global Internet Phenomena Report, March 2024.

Load Less calculation based on these data. We add together downstream and upstream data volumes for on-demand and live streaming, excluding video calls. On fixed networks, streaming represents 10.207 GB out of 15.7 GB per subscription per day, or around 65%. On mobile networks, it represents 1.108 GB out of 1.7 GB per subscriber per day, also around 65%. The report aggregates anonymized data from several dozen Sandvine customers, covering tens of millions of fixed and mobile subscribers worldwide. This 65% figure is therefore an order-of-magnitude estimate and may vary from one network to another.

Calculation details: fixed network, 7.9 + 0.222 + 2 + 0.085 = 10.207 GB; mobile network, 0.9 + 0.026 + 0.173 + 0.009 = 1.108 GB.

5

Load Less calculation based on simplified assumptions of constant bitrate. We use 5 Mbit/s for 1080p, 2.5 Mbit/s for 720p, 1.1 Mbit/s for 480p and 0.7 Mbit/s for 360p, corresponding to the sustained connection speeds recommended by YouTube (YouTube system requirements and supported devices). Netflix (Netflix-recommended internet connection speeds) likewise recommends 5 Mbit/s or more for Full HD 1080p. These are recommended connection speeds, not the exact bitrate of every video.

Volume calculation: bitrate in Mbit/s × duration in seconds ÷ 8 ÷ 1,000. We divide by 8 because one byte contains eight bits. The actual bitrate transferred can vary depending on the platform, codec and content.

6

Main synthesis used for the network-consumption models. Fraunhofer FOKUS, Green Streaming: Guidelines on Evaluating the Energy Consumption and Reducing the CO₂ Emissions of Video Streaming, October 2024. The report presents the two models used here: the Energy Intensity Model, which allocates overall consumption according to the amount of data transported, and the Power Model, which distinguishes baseline consumption from traffic-related consumption. Fraunhofer draws in particular on Coroama for the former and Malmodin for the latter.

7

Load Less method: exploratory test of video-server locations. On July 28, 2026, from Antibes, France, Load Less recorded the IP addresses serving a small sample of YouTube videos and estimated their locations using IPinfo. Most were located in Marseille, with some in Frankfurt or Milan. This very limited test is not representative, and IP geolocation remains indicative: it simply shows that a video watched in France can be served from abroad.

8

Impact CO₂ / ADEME, Petrol-powered car, average. 2025 estimate: 170 gCO₂e per kilometer, including 31.7 gCO₂e for manufacturing and 138 gCO₂e for use. The calculations divide the emissions calculated for the video session by this value to provide an indicative equivalent distance traveled.

12

Schien, D., Shabajee, P., Krug, L., McSorley, G. and Preist, C., Causal allocation of fixed impacts in product systems: Assessing the effect of data demand on network energy consumption, Journal of Industrial Ecology, 29(5), 1618–1631, 2025. The paper examines the long-term causal relationship between traffic peaks, network capacity and baseline consumption. It shows how growth in peak traffic drives increases in network capacity, while reducing demand during peak periods can slow infrastructure expansion.