# Data repository

## Content

This dataset contains the Life Cycle Assessment (LCA) results of a German asphalt mixture (SMA 11 S) per tonne 
considering four different End-of-Life (EoL) allocation approaches: 
0:100, EN 15804, 50:50, and Circular Footprint Formula. 
The system boundaries include raw material extraction (A1), transport to asphalt plant (A2), asphalt mixing (A3), 
EoL processing, and potential savings in environmental impacts due to the avoided production of primary material (Credit).

The output of testing machine is stored in Hierarchical Data Format ([HDF5](https://www.hdfgroup.org/solutions/hdf5)). 
[HDF5](https://www.hdfgroup.org/solutions/hdf5/) files can be accessed by software tools like [HDFView](https://www.hdfgroup.org/download-hdfview) or coding languages, e.g. Python using package [`h5py`](https://docs.h5py.org/en/stable/index.html).

### file ``EoL_scenarios.h5``

This HDF5 file contains 59 EoL scenarios (see table ``Scenario Overivew`` below) stored in HDF groups. 
In each group, the results of the impact categories regarding the life cycle stages A1, A2, A3, EoL, and Credit are stored as HDF datasets.

### table ``Abbreviations``

The applied abbreviations are listed in the subsequent table.

| Abbreviation | Meaning |
| --- | --- |
| A | allocation factor of burdens and credits between supplier and user of secondary materials |
| A1 | life cycle stage of raw material extraction |
| A2 | life cycle stage of raw material transport to asphalt mixing plant |
| A3 | life cycle stage of asphalt mixing |
| CFF | circular footprint formula |
| EAPA | European Asphalt Pavement Association |
| EoL | end of life |
| EoW | end of waste |
| Q | quality ratio |
| R1 | secondary material fraction (content) |
| R2 | recovered fraction for reuse or recycling at EoL |
| R2,reuse | recovered fraction for reuse at EoL |
| R2,recycle | recovered fraction for recycling at EoL |
| RA | reclaimed asphalt |

### table ``Scenario Overivew``

An overview of the studied scenarios are listed in the subsequent table.

| No.  | Scenario characteristics | Comments |
| --- | --- | --- |
| 1 | 0% RA; 0:100; Q = 1; R2 = 1 | input of recycled material is not considered within the system boundaries |
| 2 | 0% RA; EN 15804; Q = 1; binder content from RA 50% (gray grading curve); R2 = 1 | EoW status after crushing and sieving in plant; no loads assumed in Module D; benefits and loads beyond the product system |
| 3 | 0% RA; 50:50; Q = 1 |   |
| 4 | 0% RA; CFF; Q = 1 |  |
| 5 | 30% RA; 0:100; binder content from RA 50%  (gray grading curve) | RA processing at construction site (milling) (A1) and transport of RA (A2) are not considered as burdens of secondary incoming material; Credit for avoided primary material in subsequent system is considered fully  |
| 6 | 30% RA; EN 15804; binder content from RA 50%  (gray grading curve) | RA processing at construction site (milling) is not considered as a burden of the secondary incoming material (EN 15804, EoW property) |
| 7 | 30% RA; 50:50; binder content from RA 50%  (gray grading curve) | RA processing at construction site (milling) is not considered as a burden of the secondary incoming material; RA transport to plant (A2) and further RA processing at plant (A1) are considered to a 50%; Credits are shared with subsequent system to 50% |
| 8 | 30% RA; CFF; binder content from RA 50%  (gray grading curve) | R1 = 30% |
| 9 | 60% RA; 0:100; binder content from RA 50%  (gray grading curve) |  |
| 10 | 60% RA; EN 15804; binder content from RA 50%  (gray grading curve) |  |
| 11 | 60% RA; 50:50; binder content from RA 50%  (gray grading curve) |  |
| 12 | 60% RA; CFF; binder content from RA 50%  (gray grading curve) |  |
| 13 | 90% RA; 0:100; binder content from RA 50%  (gray grading curve) |  |
| 14 | 90% RA; EN 15804; binder content from RA 50%  (gray grading curve) |  |
| 15 | 90% RA; 50:50; binder content from RA 50%  (gray grading curve) |  |
| 16 | 90% RA; CFF; binder content from RA 50%  (gray grading curve) |  |
| 17 | 30% RA; Black grading curve - 0% binder from RA; 0:100 | EoL is the same as scenario 5 |
| 18 | 30% RA; Black grading curve - 0% binder from RA; EN 15804 | EoL is the same as scenario 6 |
| 19 | 30% RA; Black grading curve - 0% binder from RA; 50:50 | EoL is the same as scenario 7 |
| 20 | 30% RA; Black grading curve - 0% binder from RA; CFF | EoL is the same as scenario 8 |
| 21 | 30% RA; Gray grading curve - 60% binder from RA; 0:100 | EoL is the same as scenario 5 |
| 22 | 30% RA; Gray grading curve - 60% binder from RA; EN 15804 | EoL is the same as scenario 6 |
| 23 | 30% RA; Gray grading curve - 60% binder from RA; 50:50 | EoL is the same as scenario 7 |
| 24 | 30% RA; Gray grading curve - 60% binder from RA; CFF | EoL is the same as scenario 8 |
| 25 | 30% RA; Gray grading curve - 80% binder from RA; 0:100 | EoL is the same as scenario 5 |
| 26 | 30% RA; Gray grading curve - 80% binder from RA; EN 15804 | EoL is the same as scenario 6 |
| 27 | 30% RA; Gray grading curve - 80% binder from RA; 50:50 | EoL is the same as scenario 7 |
| 28 | 30% RA; Gray grading curve - 80% binder from RA; CFF | EoL is the same as scenario 8 |
| 29 | 30% RA; White grading curve - 100% binder from RA; 0:100 | EoL is the same as scenario 5 |
| 30 | 30% RA; White grading curve - 100% binder from RA; EN 15804 | EoL is the same as scenario 6 |
| 31 | 30% RA; White grading curve - 100% binder from RA; 50:50 | EoL is the same as scenario 7 |
| 32 | 30% RA; White grading curve - 100% binder from RA; CFF | EoL is the same as scenario 8 |
| 33 | 30% RA; Q = 0.7; 0:100 | based on scenario 5 |
| 34 | 30% RA; Q = 0.7; EN 15804 | based on scenario 6 |
| 35 | 30% RA; Q = 0.7; 50:50 | based on scenario 7 |
| 36 | 30% RA; Q = 0.7; CFF | based on scenario 8 |
| 37 | 30% RA; Q = 0.5; 0:100 | based on scenario 5 |
| 38 | 30% RA; Q = 0.5; EN 15804 | based on scenario 6 |
| 39 | 30% RA; Q = 0.5; 50:50 | based on scenario 7 |
| 40 | 30% RA; Q = 0.5; CFF | based on scenario 8 |
| 41 | 30% RA; Q = 1.3; 0:100 | based on scenario 5 |
| 42 | 30% RA; Q = 1.3; EN 15804 | based on scenario 6 |
| 43 | 30% RA; Q = 1.3; 50:50 | based on scenario 7 |
| 44 | 30% RA; Q = 1.3; CFF | based on scenario 8 |
| 45 | 30% RA; CFF; Q = 1; A = 0.2 | A = 0.2, i.e. low offer of recyclable materials and high demand: the formula focuses on recyclability at end of life |
| 46 | 30% RA; CFF; Q = 1; A = 0.6 |  |
| 47 | 30% RA; Q = 1; EN 15804  - EoW status after milling | values for modules A1-A3 in this model are connected to scenario 6 |
| 48 | 30% RA; 0:100; Distance from EoL material to plant | distance: +500% (235 km) |
| 49 | 30% RA; EN 15804; Distance from EoL material to plant | distance: +500% (235 km) |
| 50 | 30% RA; 50:50; Distance from EoL material to plant | distance: +1000% (470km) |
| 51 | 30% RA; CFF; Distance from EoL material to plant | distance: +1300% (611km) |
| 52 | 30% RA; 0:100; Q = 1; Gray grading curve - 50% binder from RA; R2,reuse = 0.87; R2,recycle = 0.13 | A1-A3 from scenario 5; EoL and credit calculated from scratch; R2 values obtained from EAPA statistic regarding the use of RA in Germany in 2022 (https://eapa.org/asphalt-in-figures-2022-view); according to https://eapa.org/asphalt-in-figures-2022-view, 87% of RA in Germany is used in other asphalt mixtures (R2,reuse), while the rest 13% is used in unbound road layers (R2,recycle) (assumed to be only gravel); reuse and recycling terminology is adopted from the EAPA report |
| 53 | 30% RA; Module D; Q = 1; Gray grading curve - 50% binder from RA; R2,reuse = 0.87; R2,recycle = 0.13 | A1-A3 from scenario 6; EoL and credit calculated from scratch; R2 values obtained from EAPA statistic regarding the use of RA in Germany in 2022 (https://eapa.org/asphalt-in-figures-2022-view); according to https://eapa.org/asphalt-in-figures-2022-view, 87% of RA in Germany is used in other asphalt mixtures (R2,reuse), while the rest 13% is used in unbound road layers (R2,recycle) (assumed to be only gravel); reuse and recycling terminology is adopted from the EAPA report |
| 54 | 30% RA; 50:50; Q = 1; Gray grading curve - 50% binder from RA; R2,reuse = 0.87; R2,recycle = 0.13 | A1-A3 from scenario 7; EoL and credit calculated from scratch; R2 values obtained from EAPA statistic regarding the use of RA in Germany in 2022 (https://eapa.org/asphalt-in-figures-2022-view); according to https://eapa.org/asphalt-in-figures-2022-view, 87% of RA in Germany is used in other asphalt mixtures (R2,reuse), while the rest 13% is used in unbound road layers (R2,recycle) (assumed to be only gravel); reuse and recycling terminology is adopted from the EAPA report  |
| 55 | 30% RA; CFF; Q = 1; Gray grading curve - 50% binder from RA; R2,reuse = 0.87; R2,recycle = 0.13 | A1-A3 from scenario 8; EoL and credit calculated from scratch; R2 values obtained from EAPA statistic regarding the use of RA in Germany in 2022 (https://eapa.org/asphalt-in-figures-2022-view); according to https://eapa.org/asphalt-in-figures-2022-view, 87% of RA in Germany is used in other asphalt mixtures (R2,reuse), while the rest 13% is used in unbound road layers (R2,recycle) (assumed to be only gravel); reuse and recycling terminology is adopted from the EAPA report |
| 56 | 30% RA; 0:100; Q = 1; Gray grading curve - 50% binder from RA; R2,reuse = 0.93; R2,recycle = 0.03; (1-R2) = 0.04 | A1-A3 from scenario 5; EoL and credit calculated from scratch; R2 values obtained from the Mineralische Bauabfälle Monitoring Bericht 2020 (Kreislaufwirtschaft Bau) regarding the use of material from road demolition (Straßenaufbruch) in Germany (https://kreislaufwirtschaft-bau.de/Download/Bericht-13.pdf); according to https://kreislaufwirtschaft-bau.de/Download/Bericht-13.pdf, 92.9% of road demolition waste in Germany is reused (R2,reuse), while 3.0% is used for landfill construction and backfilling of excavations (R2,recycle) (assumed to be only gravel); rest 4.1% (1-R2) is taken to landfill |
| 57 | 30% RA; Module D; Q = 1; Gray grading curve - 50% binder from RA; R2,reuse = 0.93; R2,recycle = 0.03; (1-R2) = 0.04 | A1-A3 from scenario 6; EoL and credit calculated from scratch; R2 values obtained from the Mineralische Bauabfälle Monitoring Bericht 2020 (Kreislaufwirtschaft Bau) regarding the use of material from road demolition (Straßenaufbruch) in Germany (https://kreislaufwirtschaft-bau.de/Download/Bericht-13.pdf); according to https://kreislaufwirtschaft-bau.de/Download/Bericht-13.pdf, 92.9% of road demolition waste in Germany is reused (R2,reuse), while 3.0% is used for landfill construction and backfilling of excavations (R2,recycle) (assumed to be only gravel); rest 4.1% (1-R2) is taken to landfill |
| 58 | 30% RA; 50:50; Q = 1; Gray grading curve - 50% binder from RA; R2,reuse = 0.93; R2,recycle = 0.03; (1-R2) = 0.04 | A1-A3 from scenario 7; EoL and credit calculated from scratch; R2 values obtained from the Mineralische Bauabfälle Monitoring Bericht 2020 (Kreislaufwirtschaft Bau) regarding the use of material from road demolition (Straßenaufbruch) in Germany (https://kreislaufwirtschaft-bau.de/Download/Bericht-13.pdf); According to https://kreislaufwirtschaft-bau.de/Download/Bericht-13.pdf, 92.9% of road demolition waste in Germany is reused (R2,reuse), while 3.0% is used for landfill construction and backfilling of excavations (R2,recycle) (assumed to be only gravel); rest 4.1% (1-R2) is taken to landfill |
| 59 | 30% RA; CFF; Q = 1; Gray grading curve - 50% binder from RA; R2,reuse = 0.93; R2,recycle = 0.03; (1-R2) = 0.04 | A1-A3 from scenario 8; EoL and credit calculated from scratch; R2 values obtained from the Mineralische Bauabfälle Monitoring Bericht 2020 (Kreislaufwirtschaft Bau) regarding the use of material from road demolition (Straßenaufbruch) in Germany (https://kreislaufwirtschaft-bau.de/Download/Bericht-13.pdf); according to https://kreislaufwirtschaft-bau.de/Download/Bericht-13.pdf, 92.9% of road demolition waste in Germany is reused (R2,reuse), while 3.0% is used for landfill construction and backfilling of excavations (R2,recycle) (assumed to be only gravel); rest 4.1% (1-R2) is taken to landfill |

## References

The data generation as well as the underlying methods, models and software are described in 

Haverkamp, Pamela; Traverso, Marzia; Lo Presti, Davide: 
Investigating end-of-life allocation approaches for bituminous mixtures (2025),
[DOI: 10.1080/14680629.2025.2588217](https://doi.org/10.1080/14680629.2025.2588217)