BREEAM’s targets for construction waste are a good idea in principle, but how achievable are they in practice?
Aside from building, a lot of our time on construction projects is spent measuring and tracking our performance. This includes monitoring the most expensive materials we use - those that end up in the skip or bin as construction waste.
As I’ve discussed in a previous article, the industry still produces far too much waste, so it’s helpful that the most recent versions of BREEAM include targets for reducing it. The targets allow for a number of credits which are based on different levels of performance, as shown in the table below.
|BREEAM Credits||Tonnes of waste generated per 100m2 (gross internal floor area)|
|Exemplary Level||≤ 1.9|
Source: (BREEAM 2011, Credit Wst 01)
These targets were set from historical data which was collected using BRE’s SMARTWaste tool, so it was interesting to see at the recent SMARTWaste conference, held at the end of September, their latest benchmark data being presented. This is summarised below:
Benchmarks of tonnes/100m2 for standard, good and best practice (31-08-2013)
|Best Practice||Good Practices||Standard Practice|
|Residential||<4.2||4.2 - 8.2||>8.2|
|Commercial Retail||< 3.8||3.8 - 7.3||>7.3|
|Education||< 5.2||5.2 - 8.7||> 8.7|
|< 3.6||3.6 - 7.2||> 7.2|
What’s interesting about this is that current best practice is above the level required to achieve three credits, and way beyond what’s needed to achieve the exemplary level.
This is supported by the recent findings by Southfacing Services Limited in a review of assessment data within their TrackerPlus tool, submitted as a paper to the Chartered Institution of Building Services Engineers (CIBSE) earlier this year. Over 80% of projects using their tool did not achieve three credits and a third achieved either one or no credits at all.
What this data doesn’t show is why this is. In practice there may be many reasons for waste occurring, such as the design or the weather. Some of these may be outside of the contractor’s direct control, yet they are usually tasked with delivering the required performance level.
There is also an assumption that the data, from which these targets are derived, is also entirely correct. BRE do some quality assurance on the numbers, removing outliers of anything unusually large or small, and any test projects that may have been entered. However, as Ant Wilson, Aecom’s leader for Sustainability recently wrote about here, there is always potential for errors to occur in entering the data and that may be hard to discover from just looking at the numbers. Although data gathering may be getting better and more robust, it’s always going to be an issue.
In the forthcoming update of BREEAM there are proposals to include similar targets for carbon and water.
Again, these targets will be based on data from previous SMARTWaste projects, but in this case the dataset is even more limited than it is for waste, at only a couple of hundred projects that are being measured.
Aside from the limited dataset on which the targets will be based, there can be great variation in performance levels between projects, some of which are outside of our control. For example, it’s usually colder in Scotland and the North of England than it is in London, so projects further north tend to have the heaters on more often and for longer periods, therefore producing more carbon emissions.
Even where you’d expect the numbers to be similar for different projects, there can be localised factors that can cause variations. For example, a standardised, modular school building should produce similar KPI numbers on different projects, but getting connected to the grid and avoiding the need for carbon-intensive diesel generators can vary wildly from a week or two to several months. It’s possible that this is because connections are unavailable due to a lack of local infrastructure, or the inability of utility organisations to provide services within a reasonable timescale. These factors are outside the project’s control and penalising the project for them hardly seems fair.
Having stretching targets is, in theory, a good idea. However if many people can’t achieve them, can’t understand how they were set, feel they are unachievable or unfair because there are factors outside their control, or think that they are based on unrealistic data, then they can be demotivating, and ultimately give the whole process a bad name.
Andrew Kinsey is an operations director and head of sustainability for construction at Mace