eTool in conjunction with our data suppliers maintain a number of global regions. These are included in the “Default LCI Group” within eTool. The LCI and associated default values for new building inventory entries are regionalised to ensure adequate geographic data quality for LCA studies. The following regionalisation methodology explains how this data in eTool is regionalised.
This document covers the regionalisation methods of the eTool Default data sets only. For IMPACT documentation, please refer to questions to BRE.
As users of eTool you have some responsibility maintaining data quality, and as providers of eTool we have some responsibility. LCA the standards require a data quality assessment to uphold accuracy of studies. The data quality assessment typically covers the following areas:
- Geographical Relevancy
- Technological Relevancy
- Temporal Relevancy
Regionalisation of data ensures geographic relevancy but may also improve other elements of data quality such as technological relevancy. Transparency of the methodologies applied to life cycle inventory data is required for reproducibility (hence the publication of this article). The background data of the eTool data sets is EcoInvent 3 which is well documented including detailed methodology papers. The Ecoinvent data is prepared for eTool by Life Cycle Strategies – one of the most active and respected LCA practitioner firms in Australia. Life Cycle Strategies are the primary contributors to AusLCI, contribute to Ecoinvent, and are the distributors of SimaPro LCA software in Australia. Regionalisation is an important step in the data preparation process. The regional data sets produced include Australasia, North America, United Kingdom, Europe, New Zealand and Global (for all other regions). If you have a large project that would justify the expense of adding a new region to eTool please submit a feature request.
Limitations of Regionalisation
Globalisation is increasing the flow of products between regions. This flow of products now extends to many products used in construction. In order to maintain consistency in LCA studies eTool prevents mixing of different regionalised data in the same project. Depending on your project’s supply chain data that has been regionalised to the location of the project may no longer be appropriate. Life Cycle Strategies and eTool are exploring methods for determining supply chain mixes for various products and thereby accounting better for exported and imported and exported flows of materials but as of V14 no procedures to account for this have been applied.
There is significant variation of production efficiencies, methods and supply chains between manufacturers of the same product. As such, regionalised data by no means guarantees the accuracy of your study. Ideally Environmental Product Declarations (EPDs) should be relied on to accurately account for the impacts of specific products in your design. EPDs have their own challenges relating to variations in transport distances, product lifespans etc that are specific to your project and differ from the assumptions made in the EPDs. Similarly, it is not uncommon for EPDs to exclude Environmental Indicators or Life Cycle Modules necessary for your study. Notwithstanding these constraints eTool encourage the use of EPDs where possible and are looking into features that would allow more accurate application of EPDs within building LCA studies.
eTool and Life Cycle Strategies are committed to continually improving the LCA data available both in eTool and in the primary data sets themselves. If users identify probable issues with data please contact our support team so that we may investigate and update the data if necessary.
Each regional dataset in eTool are produced from a primary data set. Where that dataset does not cover all required processes a background dataset is utilised. See the below Table 1 for details of each region’s primary and background data set. For detailed information regarding primary and background datasets users should refer to the documentation associated with that datasource (and the data source itself) via the links below.
Table 1: Primary and background data sets for each data set.
|Data Set||Primary Data Set||Background Data Set|
|Australasia||AusLCI||Ecoinvent 3 (Regionalised)|
|North America||USLCI||Ecoinvent 3 (Regionalised)|
|United Kingdom||Ecoinvent 3 UK Datasets||Ecoinvent 3 (Regionalised)|
|Europe||Ecoinvent 3 RER Datasets||Ecoinvent 3 (Regionalised)|
|New Zealand||Ecoinvent 3 NZ Datasets||Ecoinvent 3 (Regionalised)|
|Global||Ecoinvent 3 GLO Datasets||Ecoinvent 3 (Regionalised)|
Further details of the regionalisation efforts are summarised in the following sections.
In some cases regionalisation of characterisation factors is also applied. Table 2 summarises these instances. Note that the regionalisation of characterisation factors was initially introduced with the Water Stress Indicator and will likely be expanded on in V15 of the data to include Land Use and Acidification. All other indicators are using the same characterisation factors between regions.
Table 2: Regional differences in Characterisation Factors.
|Region||Water Stress||Land Use||Acidification||All Other Indicators|
|Australasia||From V12||From V15||From V15||Not Regionalised|
|North America||From V12||From V15||From V15||Not Regionalised|
|United Kingdom||From V12||From V15||From V15||Not Regionalised|
|Europe||From V12||From V15||From V15||Not Regionalised|
|New Zealand||From V12||From V15||From V15||Not Regionalised|
|Global||From V12||From V15||From V15||Not Regionalised|
Significant regionalisation of product impacts is included in the primary data sets by way of technological or inventory data that better matches the region in question. Some examples include:
- Steel Production: Where local data is available in EcoInvent primary data sets will reflect the local manufacturing efficiencies and methods. So countries with higher efficiency steel making facilities will have lower impacts. Similarly, feed stock of blast furnaces (necessary for primary steel production) vary between countries (for example recycled steel input and coking coal quality)
- Cement Production: Where local data is available in EcoInvent as well as local manufacturing efficiencies, feed stocks may also be regionalised in some primary data sets, for example the percentage of alternative fuel such as tyre waste used in clinker kilns.
Further to the technological differences outlined above, grid mixes are adjusted per region for all processes contributing to a product. Table 3 details the grid mix used for manufacturing electricity in each regional data set.
Table 3: Regional Grid Mixes for Product Manufacturing
|Product Regionalisation||Electricity Grid Mix|
|North America||US Mix|
|United Kingdom||United Kingdom (including imports and exports from EU)|
|New Zealand||New Zealand|
Default transport distances and modes have been regionalised for all products in the eTool Default LCI Group data sets. Products are categorised into groups, each group has a transport profile per region with up to three legs of transport from point of manufacture to the construction site. Users can customise transport modes and distances but defaults are applicable for each region when products are initially added to templates or designs. Tables 3 to 8 provide a summary of transport modes and distances defaults for each major product group in eTool. The transport modes are the same across all regions with the exception of the UK which aligns with the RICS Whole of Life Carbon Assessment for the Built Form professional statement. The RICS guidance is also used to inform transport distances for the UK. For other regions transport distances are informed by the proximity to major markets (for imports) and the size of the country for local road and rail (in-region) transport via the following rules:
- For sea transport distances (imports) the proximity of each country to major markets (EU, US and China) is considered and an average transport distance is calculated as follows:
- “Imported Products” group transport distance calculated as the average of the closest two major market. For regions that are part of a major market (eg US <> North America) this has the affect of assuming half of the products are sourced within the region itself.
- “Specialist Imported Products” group transport distance is calculated as the average of the furthest two major markets.
- Note that for Steel and Engineered Timber it is recognised that a high proportion of the products will likely be sourced within the region and hence transport distances for leg one (imports) are set to 500km).
- Larger regions are predicated to have greater average distances of intra-region transport due to economies of scale in manufacturing and the consequent aggregation of manufacturing plants to serve wider geographies. It follows that New Zealand is expected to have the smallest road and rail transport distances and the US and Australia are expected to have the largest. This is simulated by adjusting road and rail transport distances proportionally to the square-root of the size of the region (being a course estimate of the length and breadth of the country) as follows:
- Transport between the manufacturer and the warehouse is adjusted proportionally to the square-root of the area of the region (being a course approximation of the length and breadth of the region)
- Two thirds of the transport between the warehouse and the construction site is held static between regions with the remaining third being adjusted proportionally to the square root of the area of the region.
The resulting default transport modes and distances are included below in tables 4 to 9.
Table 4: Australasian Data – Default Transport Distances and Modes
Table 5: North America Data – Default Transport Distances and Modes
Table 6: United Kingdom Data – Default Transport Distances and Modes
Table 7: Europe Data – Default Transport Distances and Modes
Table 8: New Zealand Data – Default Transport Distances and Modes
Table 9: Global (for all other regions) Data – Default Transport Distances and Modes
Regionalisation of the energy supply is largely focused on the Electricity Grids. There are however some regional differences in processes such as distributed gas inventories.
Electricity grids are regionalised within the primary data sets by ensuring:
- The fuels contributing to the generation facility appropriately reflect the local fuel supply. For example, contaminants in coal can change significantly between regions). Regionalisation on this basis actually occurs within some regions, for example the Australasian grid has different coal supply for each major supply area (split by state).
- The mix of fuels contributing to the grid reflects the actual mix today.
- The generation technology and efficiency reflects the generation plant in the region.
- The distribution and transmission losses reflect those of the region.
Water Supply and Treatment
Where local water supply and treatment processes are available these are regionalised using applicable technology etc. In a similar way to electricity grids there are examples of localised water supply and treatment grids within regions also. As detailed above, the water stress characterisation factors are also regionalised to reflect local water stress (often on a local basis within regions).
Construction processes relying on electricity in are regionalised by using the grid mixes outlined in Table 3.