Daily Carbon Assessment Framework: Towards Near Real-Time Building Carbon Emission Benchmarking for Operative and Design Insights
Abstract
:1. Introduction
2. Background
2.1. Building Energy Modelling
2.2. Digital Twin for Building Energy and Carbon Assessment
3. Methods
3.1. Building Description
- The availability of data including electricity consumption, on-site weather and room occupancy at a 15-min interval.
- The multi-functionality of the building is a representation of the urban dynamic at a wider context.
- It is a relatively newly constructed building that opened in September 2017. It can provide insight into the current design technology and strategy adopted.
3.2. Digital Twin Framework
3.3. Segmented Time Period
3.4. Datasets
3.5. Carbon Emission Modelling
3.5.1. Top–Down Regression Model and Carbon Emission Score
3.5.2. Bottom–Up Simulation and Carbon Emission Gap Score
4. Results
4.1. Carbon Emission Score
4.2. Carbon Emission Gap Score
5. Service Layer
5.1. Deviation between Segmented and All-Time Periods
5.2. Insights for Future Projects
6. Discussion
6.1. Summarising the Benchmark Systems
6.2. Limitation and Future Directions
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Study | Explanatory Variables |
---|---|
[11] | Building age Occupancy Chiller equipment Lighting equipment Light control |
[12] | Ambient temperature Solar radiation Relative humidity Wind speed Occupancy |
[13] | Winter climatic severity Summer climatic severity Office surface area Number of employees Glazed surface in facade HAVC installed power Office height Building age |
Period | Dates | Hours |
---|---|---|
Term occupied (a) | 7 January–29 March 29 April–17 June 23 September–13 December | 8:00–17:00 (M–F) |
Term unoccupied (b) | 7 January–29 March 29 April–17 June 23 September–13 December | 0:00–8:00 17:00–24:00 (M–F) |
Non-term occupied (c) | 1 January–4 January 1 April–26 April 17 June–21 September 16 December–31 December | 8:00–17:00 (M–F) |
Non-term unoccupied (d) | 1 January–4 January 1 April–26 April 17 June–21 September 16 December–31 December | 0:00–8:00 17:00–24:00 (M–F) |
All-time (e) | 1 January–31 December | 0:00–24:00 (M–F) |
Input Parameter | Data Source |
---|---|
Building geometry | Revit Model CAD plan and elevation |
Construction material | Revit Model |
Weather condition | EPW file |
Operational load | Building functional program |
Period | Average Carbon Emission Gap Score (Occupied) | Average Carbon Emission Gap Score (Unoccupied) |
---|---|---|
Spring term (7 January–29 March) | 0.62 | 0.40 |
Summer Term (29 April–17 June) | 0.56 | 0.39 |
Autumn Term (23 September–13 December) | 0.66 | 0.59 |
Easter break (1 April–26 April) | 0.56 | 0.33 |
Summer break (17 June–21 September) | 0.62 | 0.28 |
Christmas break (1 January–4 January and 16 December–31 December) | 0.71 | 0.69 |
Level | WWR% | Circulation BUR% | Office BUR% | Teaching BUR% | Service BUR% | Plant BUR% |
---|---|---|---|---|---|---|
3 | 32 | 25 | 21 | 38 | 11 | 5 |
4 | 31 | 22 | 25 | 37 | 10 | 6 |
5 | 37 | 2 | 65 | 9 | 20 | 4 |
6 | 37 | 1 | 79 | 0 | 16 | 4 |
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Zhu, M.; James, P. Daily Carbon Assessment Framework: Towards Near Real-Time Building Carbon Emission Benchmarking for Operative and Design Insights. Buildings 2022, 12, 1129. https://doi.org/10.3390/buildings12081129
Zhu M, James P. Daily Carbon Assessment Framework: Towards Near Real-Time Building Carbon Emission Benchmarking for Operative and Design Insights. Buildings. 2022; 12(8):1129. https://doi.org/10.3390/buildings12081129
Chicago/Turabian StyleZhu, Mingyu, and Philip James. 2022. "Daily Carbon Assessment Framework: Towards Near Real-Time Building Carbon Emission Benchmarking for Operative and Design Insights" Buildings 12, no. 8: 1129. https://doi.org/10.3390/buildings12081129