Is BIM going to help make 2050 possible?

Whole Life Carbon, LCA, ESG and EU Taxonomy in BIM Problems and Opportunities

There are currently a wide range of problems that BIM could help resolve, in relation to carbon reduction/neutrality and more broadly sustainability issues.

The simplest way to imagine the historical situation is to think of all the various parties going in the same direction but having different ideas about how to get there.

Each country has its own building regulations that set their own minimum standards, whilst the many different green building certifications like LEED, DGNB, etc., set their own higher standards and how to reach them.

On top of this ESG, EU Taxonomy alignment and the Paris Climate agreements are placing far greater pressure than ever before on building owners, designers, and constructors, across the globe, to create substantially greener buildings.

Problems:

A lack of alignment.

Take the most widely used green building certification system (LEED) as an example. To score credits for carbon reduction, a reduction of 5-10% is required, yet the Paris Climate agreement sets the 2030 goal as -45% and the European Green Deal sets the EU goal as -55% meaning LEED targets will need to jump 30 to 50% in just the next 8 years, to avoid their standards becoming obsolete.

A lack of uniformity

Whilst we have an agreed system for the calculation of Whole Life Carbon(WLC). Different countries, and different green building certifications, require different build parts, life spans and what WLC life stages should be included in calculations.

A lack of data and visibility

There are now several software solutions available that can work with 3D models and Bills of Quantities to create Whole Life Carbon calculations but as they are built by private companies much of the underlying data for the calculations is hidden. Using three of the leading software applications can produce three different outputs with no visibility on how to assess which is correct.

An investigation of the life cycle stages often reveals the biggest difference, in life cycle stages where there is the least data. A5 of WLC/ LCA calculation (installation of materials) for example has very limited available data upon which to base calculations.

A lack of focus

These problems, and many more, create distractions that divert attention away from areas that require much more focus to achieve our goals for carbon reduction and sustainability in general.

As demonstrated by the earlier example of LEED, the current situation is dangerously behind where we should be to hit 2030 and 2050 goals, which are now being turned from aspirations to laws. EU Taxonomy being one example of how to force these goals in to being.

Opportunities:

Life cycle data collection

The first opportunity that BIM is a natural choice to help resolve is the collection of project data from throughout the project and building life cycle. As previously mentioned, certain parts of the Whole Life Carbon (WLC) have either very limited historical data or comes from software’s with no visibility of certain parts of the calculation, making it impossible to verify the calculations the software provides. BIM is a natural choice as a collection point for such data, that can then be used to improve accuracy and transparency, all we need is to create a complimenting framework.

Modelling (not quite the 3D version you’re thinking of)

One of the single biggest blind spots with carbon, and construction in general, is that construction professionals don’t tend to get involved until after the business case is calculated and approved. This is a huge error based around the assumption that you can’t be detailed and accurate at business case stage.

Anyone involved in the small and specialised area of cost modelling will tell you that this is incorrect, and that business case calculations can be made with the same level of detail as outline/concept design.

The secret to this is the extracting of ratios and averages from the 3D models and the Bill of Quantities.

With a broad enough data set of projects high-low ranges appear for each building type, allowing us to create base models of an average building, that can be adjusted to different ideas that can be tested with a high degree of accuracy at business case stage. This same process could be applied to carbon and EU Taxonomy alignment (for capex expenditure). All that is needed is a large enough data base of quantities and formulas to calculate the necessary ratios and outputs. This would improve the accuracy and alignment of business case studies and increase the quality and types of data the building owners can have at such a vital an early stage.

How can we gather such an amount of geometry datasets, to allow analytics and increase accuracy of calculations and assumptions in early stages?

BIM strategies are encouraging teams to standardise their data. The challenge at the moment is the collection of that data. And it will be a great contribution to the industry if that data was shared across all teams actively working with WLC.

Open source collaboration

At KOSMOS, we have some ideas of what data should be collected, and how that could be done. But this is hindered by the lack of involved skilled computer science partners, and therefore, implementing the solution is becoming a big challenge.

A collaboration across industries could benefit many stakeholders if it was to be published open source to enlarge the dataset from everybody making use of it. A so-called win-win.

How to encourage stakeholders to feed the data set with their project geometries?

The best approach will be by providing something in return.

What about Quality assurance checks for IFC models, to check LOD, LOI, and, at least from a cost perspective, to check certain quantities from elements to define project completion based on historical geometrical trends. For example:

If ceiling amount is less than x% of floor slab amount, it is possible that ceilings are just 20% design complete at that stage. Generate a report with focus areas to discuss collaboratively with the design team to clear uncertainties and reduce risk of misunderstanding when estimating. To achieve a desired output, while collecting data, the following will be necessary:

• A database to collect data from projects and create a baseline. The script will check against these geometries to define completion expected. It should classify projects by type, and record certain information such as location, building size, building type (school, industrial…).

• A script to analyse IFC models (Is something to be done in a software? Is there open-source software for this already?)

• A dashboard, or report generation, preferable accessible on the cloud to track updates and evolution of warnings.

• Eventually, an analysis of how projects change from phase to phase from a geometry perspective, to help create trends and predictions, allowances of provisional costs.

For example, if the trend shows that early projects have only 30% of doors and they end up having the remaining 70% at detail design stage, so we can cover for it minimizing missing scope assumptions. The above, will feed the dataset with data, and will enable accuracy to be analysed throughout the different stages, as well as collecting early-stage geometry insights and trends within the building industry. Ultimately, users are encouraged to share their data throughout the multiple design stages by loading the models. They will obtain valuable output in the form of enhanced quality, reports and insights. As the dataset grows, it will be possible to analyse trends and review how the geometry evolves from inception to full detailed design. Furthermore, it will be possible to predict the extent of allowances required in the earlier stages to cover for incomplete scope throughout the development lifecycle, and thus drive greater accuracy on LCA and WLC assessments supported by the full potential of statistics.