Uncertainties and Limitations

Weight of RB Stock

A thoroughly detailed bottom-up approach was conducted; however, archetypes were created to reduce the otherwise not bearable workload. Material intensities for archetypes could be developed but no material intensities for all individual buildings. Though, on the total material stock this will have a minor impact.

Furthermore, it was often not possible to estimate all building materials through measuring, especially those from minor absolute weight and especially for older buildings due to not detailed building plans.

Hence assumptions had to be done. This issue was for instance severe concerning the material steel.

The estimation of steel as reinforcement is mostly based on assumptions. Moreover, pipes and wires are not included in the estimation.

To estimate the final weight of the material stock building footprint data from the BBR register was used. There is an uncertainty, that owners did not register their building. Concerning the assumptions taken for non-bulky materials as mentioned in the limitations (e.g. steel), there are uncertainties about the absolute weight.

CRV of RB Stock

For a few similar building materials, the same emission factor was selected (Appendix 7.2.1)

It is impossible to have a complete accurate emission factor per material, since only in rare cases (newly constructed buildings) information on the exact type and property of the building material is available (e.g. concrete and compressive strength). Furthermore, emission factors are based on LCA´s where the system boundary and the assumptions taken are very important for the final result.

4.1.2 Non-residential Buildings Weight of NRB stock

NRB material intensities for Odense were not estimated due to the lack of time. The material intensities were provided from Gontia (Chalmers University) who is about to finish a study about the non-residential building stock in Gothenburg (Sweden) (Gontia, 2019).

Because the material intensities are based on the NRB stock of Gothenburg (Sweden), uncertainties

importance in NRB´s and thus NRB´s should not be very diverse. Regarding the material composition though, uncertainties can be higher. For instance are clay bricks less used in masonries in Sweden as in Denmark (Lanau, 2019).

CRV of the NRB Stock

See above in “CRV of RB Stock”

4.1.3 Roads Weight of Road stock

No material intensity data for roads in Odense was available. Hence, they are based on assumptions and high uncertainty exists.

CRV of Road stock

Since high uncertainty in material intensity, a high uncertainty is here to be expected as well.

Furthermore, emission factors are based on LCA´s where the system boundary and the assumptions taken are very important for the final result.

4.1.4 Vehicles Number of Vehicles

The number of vehicles was obtained from Statbank and the statistics were collected specifically for Odense. Nevertheless, regarding the vehicle types bus and lorry sudden jumps in number were observed which can lead to the conclusion that an inconsistent counting method was applied.

Material Composition and Emission factors

Generic material compositions were used for several vehicle types including the most common passenger cars and for others, assumptions were made. Different models and therewith dimensions were not considered, why the uncertainty for the absolute material stock can be noticeable. Emission factors were obtained from the Ecoinvent database, which were generic emission factors. Here high uncertainty can be seen, because dimension model differences are not taken into account.

4.1.5 Electronic Appliances Number of Electronic Appliances

The number of electronic appliances was estimated using statistics about the possession of those in family households (%). The statistics were national but the differences between country level and Odense are assumed to be low. However, a significant issue with this approach of estimation is that

Material Composition and emission factors of Electronic Appliances

Except for the appliances – GPS-navigation, Activity-tracker watch, GPS-watch and MP3-Player – individual material compositions could be obtained from the literature. For those above mentioned, a generic composition for small electronics was used. It is assumed though, that there are no big differences in material composition and dimensions, nevertheless there is uncertainty.

Data on embodied emissions was not available for all appliances considered, why assumptions had to be made (Appendix 7.3.2, Table 52). Here a high uncertainty exists.

4.1.6 Water Inflow and Embodied Emissions

The data was provided from the local water supply company and is assumed to be accurate. Regarding embodied emissions due to the water inflow; Data on energy (or emissions) required to extract water and to distribute water into the municipality of Odense does not exist. Data is taken from an LCA on the water supply in Copenhagen. Because the data is taken from an LCA on water supply in Copenhagen, there are uncertainties due to system boundary issues. Those however can be estimated to be low, since there are no big differences between applied technologies in Denmark concerning water supply.

4.1.7 Consumption of Goods Packaging Inflow

Packaging material inflows are derived from statistics about packaging waste, however it is assumed, that the difference between inflow and outflow (waste) is minor, since waste is not likely to be transported.

Vehicle Inflow

The inflow data was derived from the stock data via modelling. No data on inflows could be obtained from statistics, therefore high uncertainty exists. The same limitations and uncertainties for the material composition and emission factors as for the stock data (4.1.4) are here to mention.

Electronic Appliances Inflow

The inflow data was derived from the stock data via modelling. Due to inconsistency in the data and fluctuations in the data, the data for most of the products had to be smoothened with the moving average tool in Excel, as well for outdated technologies inflows of zero were assumed to simplify the model and because very low inflow rates are assumed. The uncertainty is therewith very high. The same limitations and uncertainties for the material composition and emission factors as for the stock data (4.1.5) are here to mention.

Even though the uncertainty is very high. The impact on the total results is low. Electronic Appliances made up for only 0.03 % of the mass inflow in 2015 and 2 % of the total emissions respectively 9 % of the total embodied emissions in flows.

4.1.8 Food Inflow

Even though, the consumption per person is derived from a national survey from 2013, the uncertainty is assumed to be low, since minor differences can be expected. The uncertainty of the results for the embodied emissions though has to be seen higher, since the data was obtained from an IOA regarding Swiss households, as well as the data was on energy requirements for food consumption per person and not on specific food categories.

4.1.9 Construction Material

The uncertainties and limitations concerning the material intensity are those mentioned in 4.1.1 RB stock and 4.1.2 NRB stock. The data on newly added floor area was obtained from Statbank and because this data was originally collected from BBR the same issue as in 4.1.1 concerning the registration of newly added floor area is assumed.

4.1.10 Outflows

Due to data gaps and limited time, outflows of the UM were not included and important factors like recycling and energy recovery could not be considered. However, energy used in EoL processes and occurred emissions are covered with the operational emissions presented here.

4.1.11 Emission Factors per Material

A throughout difficult task in setting up the results in this report was the selection of emission factors per material or good. The preference was to find data from Danish LCA´s, but unfortunately those were in most of the cases not available. This brings uncertainty, since then another energy mix was applied to estimate the emission factor. Furthermore, concerning the number of materials included in this study, it was impossible to collect the data from just one study or database, what means there is uncertainty due to different system boundaries in the studies.