Open main menu
Home
Random
Recent changes
Special pages
Community portal
Preferences
About Wikipedia
Disclaimers
Incubator escapee wiki
Search
User menu
Talk
Dark mode
Contributions
Create account
Log in
Editing
Embodied energy
(section)
Warning:
You are not logged in. Your IP address will be publicly visible if you make any edits. If you
log in
or
create an account
, your edits will be attributed to your username, along with other benefits.
Anti-spam check. Do
not
fill this in!
==Data== Many databases exist to quantify the embodied energy of goods and services, including materials and products. These are based on various data sources, with geographic and temporal relevance variations and system boundary completeness. One such database is the [https://msd.unimelb.edu.au/research/projects/current/environmental-performance-in-construction Environmental Performance in Construction (EPiC) Database] developed at The University of Melbourne, which includes embodied energy data for over 250 mainly construction materials. This database also includes values for embodied water and greenhouse gas emissions.<ref name="Crawford 2019">{{cite book |last1=Crawford |first1=Robert |title=EPiC database 2019 |last2=Stephan |first2=AndrΓ© |last3=Prideaux |first3=Fabian |publisher=The University of Melbourne |year=2019 |isbn=978-0-7340-5495-1 |publication-place=Melbourne, Australia |page= |oclc=1132202846}}</ref> The main reason for the differences in embodied energy data between databases is the source of data and methodology used in their compilation. Bottom-up 'process' data is typically sourced from product manufacturers and suppliers. While this data is generally more reliable and specific to particular products, the methodology used to collect process data typically results in much of the embodied energy of a product being excluded, mainly due to the time, costs and complexity of data collection. Based on national statistics, top-down environmentally-extended input-output (EEIO) data can be used to fill these data gaps. While EEIO analysis of products can be useful on its own for initial scoping of embodied energy, it is generally much less reliable than process data and rarely relevant for a specific product or material. Hence, hybrid methods for quantifying embodied energy have been developed,<ref>{{cite journal |last1=Crawford |first1=R.H. |last2=Bontinck |first2=P.-A. |last3=Stephan |first3=A. |last4=Wiedmann |first4=T. |last5=Yu |first5=M. |title=Hybrid life cycle inventory methods β A review |journal=Journal of Cleaner Production |date=2018 |volume=172 |pages=1273β1288 |doi=10.1016/j.jclepro.2017.10.176|bibcode=2018JCPro.172.1273C |hdl=11343/194165 |s2cid=116770528 |url=https://unsworks.unsw.edu.au/bitstreams/05e0c708-34d3-4e54-8ad1-832fc7483270/download |hdl-access=free }}</ref> using available process data and filling any data gaps with EEIO data. Databases that rely on this hybrid approach, such as The University of Melbourne's [https://msd.unimelb.edu.au/research/projects/current/environmental-performance-in-construction EPiC Database],<ref name="Crawford 2019"/> provide a more comprehensive assessment of the embodied energy of products and materials.
Edit summary
(Briefly describe your changes)
By publishing changes, you agree to the
Terms of Use
, and you irrevocably agree to release your contribution under the
CC BY-SA 4.0 License
and the
GFDL
. You agree that a hyperlink or URL is sufficient attribution under the Creative Commons license.
Cancel
Editing help
(opens in new window)