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Why a new case-study to cut heating emissions takes us closer to Net Zero industries

  • Impactful connected AI case-study between Ericsson and building management solution provider Kiona in the Nordics delivers high impact in reducing energy consumption of residential buildings.
  • The Carbon Trust case-study demonstrates the impact of the new ITU-T L. 1480 ‘Net Zero’ standard, a methodology for assessing the impact of ICT solutions in cutting greenhouse gas emissions of other sectors.
  • According to Ericsson Research, ICT solutions have the potential to directly reduce global greenhouse gas emissions by up to 15 percent by 2030 (2015 baseline).
case-study to cut heating emissions

"It’s time to wake up and step up."

In June 2023, at a press conference on Climate, the UN Secretary-General António Guterres highlighted that the climate agenda is being undermined. "A lack of ambition.  A lack of trust.  A lack of support.  A lack of cooperation.  And an abundance of problems around clarity and credibility."

Mr Guterres stressed that "We are hurtling towards disaster, eyes wide open – with far too many willing to bet it all on wishful thinking." Now is the time to act.

Collective steps taken since the inception of the Paris Agreement have fallen short. Efforts to reduce global greenhouse gas (GHG) emissions would need to be deeper, more rapid, and more sustainable. The credibility deficit that had inhibited any real efforts to measure, analyze, and enable cross-sectoral Net Zero commitments would need to be closed.

Today, the new ITU-T L.1480 Net Zero standard closes that gap. It’s a mechanism that not only aims to improve the consistency, transparency and comprehensiveness in assessing the emissions impact of ICT solutions, but in doing so it opens a pathway to real, credible change across other sectors.

Because that’s the real crux of the matter: ICT can, should, and must enable exponential decarbonization of society, as a whole, if we are to reach Net Zero emissions by 2050. 

According to Ericsson Research, ICT solutions – from AI to 5G, and cloud computing to IoT – can directly reduce GHG emissions by 15 percent by 2030 (based on a 2015 baseline), and indirectly support a further reduction of 35 percent. This is enacted through the reduction of energy consumption and material waste, in addition to supporting global health, sustainability and economic goals.

However, it’s important to weigh reward against risk, remembering that digital technologies are, after all, a wild card. Without global standards and mechanisms that can assess and measure the true net second order effect of early-stage innovations, we can never really know the full impact of those technologies.

Through a common standard that makes that possible across all sectors, geographies, and solution areas, our industries have a framework that can enable us to unleash the full, untethered promise of ICT in a sustainable way. This can be a major inflection point in the transition to Net Zero industries.

The industrial decarbonization challenge

Case Study on the Avoided Emissions from a Building Heating Management System Using an AI Steering Function

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The ITU-T L.1480 Net Zero standard explained

The ITU-T L.1480 standard, or recommendation as it is called, offers guidelines for assessing how ICT solutions impact greenhouse gas emissions in various scenarios, including individual, organizational, and global levels.

It aims to understand the net effects and higher-order consequences of using ICT, whether it reduces or increases emissions, and combines elements of both consequential and process-sum life cycle assessment (LCA) methods.

The new recommendation introduces a methodology for assessing the full emissions impact of ICT solutions, including:

  • first order effects relating to the environmental impacts caused at each stage of their lifecycles
  • positive second order effects enabled through vast efficiency gains in all sectors of the economy
  • negative second order effects caused by ICT solutions serving to maintain or even increase the fossil-based economy
  • higher order effects (can be positive or negative) caused by structural impact on a societal level in reshaping lifestyles

Piloting the new standard to lower residential heating emissions

Part of the challenge in accurately measuring the emissions impact of ICT solutions has involved the need to factor in the emissions impact of often multiple, inter-connected solutions and all associated first order, second order, and higher order effects.

In its recommendation paper, the ITU illustrates this challenge through the example of a relatively simple video-conferencing solution across multiple geographies, in which first order effects comprise the lifecycle GHG emissions of all associated software and hardware, second order effects comprise any change in GHG emissions associated with the intended usage e.g. reduced business travel, and higher order effects comprise any further consequence of introducing the videoconference system e.g. direct and indirect changes in behaviors and investment patterns.

In a recent groundbreaking case study with Kiona, provider of building management ICT solutions, we took this a step further.

We applied the framework of the new ITU standard in one of the highest-emitting sectors – building energy and heating (to put that into context, buildings account for 36 percent of total GHG emissions in the EU – including construction, usage, renovation and demolition).

In doing so, not only did we break new ground in exploring the decarbonization impact of ICT solutions in a high-emitting sector, but – importantly – we set a credible precedent for scaling and replicating those models across other sectors and solution areas.

Kiona's Edge AI solution: How it works

Kiona's Edge is a cloud platform solution that enables energy optimization within buildings through an integral AI steering function.

The AI steers the buildings’ heating supply by calculating the forward temperature and predicting the future heating energy demand using an unique energy balance model. This calculates heat losses and gains based on outdoor temperature, wind and solar radiation, resulting in more efficient building heating.

  1. Connectivity: Real-time data is collected using temperature and humidity sensors and communicated wirelessly to gateways in the building. The data is sent to the Kiona cloud platform through the cellular network.
  2. Data consolidation: Kiona’s platform Edge consolidates, analyses, and visualizes the optimal building heat steering strategy and presents the past, current and optimized energy consumption of the building to end-users through an interface.
  3. Optimization: By constantly collecting more data from your building and creating a feedback-loop, the AI is self-learning. It continuously improves and fine-tunes its optimization by taking into account unique building characteristics, high-end weather data and the thermal capacity. The algorithm also has access to 20 years of data about how thousands of buildings behave under different circumstances. This creates the unique steering strategy for each unique building.

In this case, the consequent reduction in GHG emissions from the decreased energy use sourced from district heating becomes the main second order effect.

edge computing

Figure 1. The Edge Ecosystem. Picture courtesy of Kiona.

Let’s explore how the study was set up and which data sets were considered:

  1. In line with the ITU standard, the study delivered a comprehensive assessment the total first-, second-, and higher order effects of the total energy optimization solution across 365 residential buildings in Finland and Sweden over the course of 12 months.
  2. This comprised primary data from Kiona’s cloud-based Edge platform, the radio network, IoT accelerator platform, a number of temperature- and humidity sensors, as well as gateways that transmit the data to the cloud platform.
  3. It also comprised secondary data from other reliable sources to fill data gaps, including contextual factors such as cost factors, macroeconomic factors and environmental regulations. Higher order effects were also assessed and comprised factors such as economic efficiency and the potential for an increase in carbon emitting activities, for example.
  4. Net second order effects were presented as the average annual change in GHG emissions per square meter of each building. To calculate this, the aggregated first order effects were subtracted from GHG emission changes for each building. Furthermore, building were categorized based on characteristics such as building year, ventilation type and exhaust type to provide a wider data set for evaluation.

Overall, implementing Kiona's Edge AI steering function resulted in a positive net second order effect, reducing GHG emissions. In 2022, The total net avoided emissions for the dataset were found to be 1,111 tCO2e for the location-based method and the total net avoided energy consumption was 17,325 MWh.

Even in spite of the impressive case-study results, it’s worth considering that the sample data set comprises buildings that exclusively use district heating (with relatively low emissions). This would indicate the potential for even greater savings in locations with less favorable conditions. On the other hand, the effort required to implement the solution, which only takes a couple of hours when compared to other time-consuming energy-saving methods such as glazing, can be seen as a significant benefit.

Explore the full data sets and details of the case-study in the Carbon Trust report: Avoided Emissions from Edge AI – Steering Function

By combining the power of connectivity and Edge AI energy management software, a net total of 17 GWh of consumed energy was saved (for 2022) – avoiding over 1 kTonne of CO2 emissions.


Innovating the pathway to Net Zero industries

The significance of the Carbon Trust case-study lies not only in the sizeable GHG emissions savings it can deliver across one of the highest-emitting sectors – but that it showcases the impact of a standard that can deliver real, credible impact when scaled across other sectors.

ICT can do a world of good in the race to Net Zero, but without open ecosystems and viable solutions that are both economically and environmentally sustainable, our industry cannot bring that impact to the world.

Exponential technologies such as those enabled by 5G will be decisive in enabling a rapid reduction of both production- and consumption-related emissions, while supporting social, ecological and economic goals.

While standards are instrumental, so too is the need for innovation, impact investment, and platforms that are open, flexible and enable global scale.

Opening up the full capabilities of 5G networks through network APIs will open new, scalable technological possibilities for developers across app ecosystems, hyperscale cloud providers, software providers, and device ecosystems – enabling rapid innovation in areas such as mixed reality, remote and industrial control, and urban management.

This is where the transition to Net Zero industry will be defined, developed, and built.

This is also where the new standard can provide a critical blueprint in making that happen.

Explore more

Read the case-study report in full: Case Study on the Avoided Emissions from a Building Heating Management System Using an AI Steering Function

Find out how 5G and connectivity can enable the transition to Net Zero

Explore other sustainable cellular-enabled technologies in the Ericsson case library

Learn more about Industry 4.0


AI: Artificial Intelligence

ITU:The International Telecommunication Union 

ICT: Information and Communications Technology

UN: United Nations

GHG: Global Greenhouse Gas

LCA: Life Cycle Assessment

IoT: Internet of Things

CO2: Carbon dioxide

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