## 3 Inventory Data
### Inventory Data for the Synthesis, Purification and Drying of Gold Nanoparticles
The model accounts for average load factors and includes return trips with empty vehicles. The transport losses were considered negligible. This dataset for container shipping represents the transport of 1 tonne of freight by a container ship over 1 km, with a load capacity (DWT) of 43,000 tonnes. It includes the full life cycle of the transport service, covering ship production, maintenance, fuel consumption and port construction. The ship operates at 70% capacity utilization, factoring in empty trips and speed reductions. The emissions, including CO2, NOx, SOx and particulates, were calculated for sea and port operations with Emission-Controlled Area (ECA) adjustments. The dataset accounts for all related emissions and resource use throughout the ship's 25-year operational life. \begin{table}
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**Data** & **Quantity** & **Unit** & **Dataset** \\ \hline Packaging & & & \\ \hline Glass jar Miron 1 L & 7.17 & kg & \(\ast\)Packaging glass production, brown! packaging glass, brown! Cutoff, U<< \\ \hline Black tight-fitting & 258.16 & g & \(\ast\)Polypropylene production, granulate! polypropylene, granulate! Cutoff, U–RE\(\ast\)\({}^{2}\) \\ \hline Sealing washer & 41.72 & g & \(\ast\)Polyethylene production, linear low density, granulate! Gutoff, U–RER\(\ast\)\({}^{2}\) \\ \hline \hline \end{tabular} \({}^{1}\) U = Unit process, referring to the detailed, individual process in the Life Cycle Inventory (LCI) that contains specific data about inputs, outputs, emissions and resource use. Unit processes are the most granular level of data and are essential for building custom Life Cycle Assessment (LCA) models. \({}^{2}\) RER (Region Europe) indicates that the geographical scope of the process data applies to Europe as a region, not a specific country within Europe. This aggregation considers averages or representative values for European conditions, infrastructure and practices.  
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Table 2: _Cont._ \begin{table}
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**Data** & **Quantity** & **Unit** & **Dataset** \\ \hline Electricity for USP synthesis cycle (tube furnace, US generators, chiller) & 28.7 & kWh & \(\ast\)Market group for electricity, medium voltage! Cutoff, U<< \\ \hline Electricity for supporting equipment for the USP synthesis cycle (fume scrubber, ventilation) & 32.0 & kWh & \(\ast\)Market group for electricity, medium voltage! Cutoff, U<< \\ \hline Electricity for rotary evaporation of the prepared Au nanoparticle suspension & 12.0 & kWh & \(\ast\)Market group for electricity, medium voltage! Cutoff, U<< \\ \hline Electricity for the lyophilization cycle (nanoparticle suspension drying) & 105.0 & kWh & \(\ast\)Market group for electricity, medium voltage! Cutoff, U<< \\ \hline Electricity for lyophilization air conditioning & 172.8 & kWh & \(\ast\)Market group for electricity, medium voltage! Cutoff, U<< \\ \hline \hline \end{tabular}
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Table 3: Electricity usage inventory for gold nanoparticle synthesis, purification and drying. The inventory data for transporting substances for synthesizing, purifying and drying AuNPs are presented in Table 4.  
The inventory data for water consumption for the synthesis, purification and drying of AuNPs represent the production of 1 kg of deionized water delivered to the user by ion exchange. The process includes an anionic resin, or combined cation/anion exchange resin. The unit is operated with counterflow regeneration. The obtained water quality: about 1-0.1 \(\upmu\)S/cm for the conductivity, and silica content (as SiO\({}_{2}\)) of 5-25 \(\upmu\)S/L. For the water source, tap water was used from a public supply with a total assumed hardness of 1.71 mol/m\({}^{3}\) (range 0.7-3.2) [17]. The data for all the inputs and outputs for water use for the synthesizing, purifying and drying of AuNPs are shown in Table 5.  
During the synthesis, purification and drying of AuNPs, various waste emissions are produced, involving primarily nitrogen gas, latex gloves and paper towels (Table 6).