## 4 Discussion  
### Nonvisual Lighting Simulation  
In the first section of the Discussion, we outline the benefits and limitations of our nonvisual lighting simulation process. The process in Appendix A allows for a lighting specification in advance of a lighting intervention targeted at the nonvisual effects of light. While some specialized software allows this more directly by working with spectral parameters, such as _ALFA_ (_Solemma LLC_, Cambridge, MA, USA) [30] and _Lark Spectral Lighting_ (collaboration of University of Washington and _ZGF Architects LLP_) [31], the outlined process is software agnostic. This means that the process depends on functions that are part of most standard lighting design tools, some of which are free of charge [32; 33]. Compared to specialized software, the process has some disadvantages. First, while the process is comparatively easy, it is not guided by the software, as standard lighting software only depends on single-value photopic parameters (sometimes split into RGB values). This increases the possibility of user error while setting up the different models and measurement points or plains and when interpreting the simulation results. Second, specialized software provides a database for materials and light sources. In our process, the user has to take measurements or use third-party sources for this information. This can be a benefit as well as a limitation, as the specific information that the dedicated programs provide might not necessarily reflect the materials and light spectrum of the project. An untrained user might put too much trust in the specific information at a point in the design process when only a broad assumption is warranted. Third, our process increases inaccuracy by simplifying spectral parameters to single-value parameters. For example, the spectral distribution of a light source might lead to greater or lesser reflection from a material of a given reflectance, depending on where in the spectrum reflection dominates. This information is lost in the process and, therefore, is not part of the simulation results. However, this has always been the case for standard lighting design, where reflection values of materials stem from a standard illuminant or equal energy spectrum. A user might also calculate the single-value reflection based on the used illuminant, which increases the accuracy for the first reflection. As long as broadband white light sources are used, we argue for the more simplistic approach, as the additional error will have little impact on the results. The overall success of the process can be shown, e.g., by comparing the simulation results for the high melanopic setting (Figure 4 and File S2) with the measurement results (Table 2). We used lighting distribution and the necessary luminous flux deduced from the simulation result to specify the luminous flux of the _Drosa_ components. We reach up to 390 lx MEDI in the simulation for the _quality control_ workplace with a maintenance factor of 80% (0.8), comparable to 403 lx from the measurements (412 lx minus 9 lx background illuminance) with the lights at an 80% dimming level. In the packaging workplace, we reach up to 239 lx in the simulation, comparable to 249 lx from the measurements (324 lx minus 75 lx background illuminance). These values sound remarkably similar, but we caution the comparison insofar as the simulation values are \"up to\", and a different position for comparison would lead to different values. The simulation process described in Appendix A is not meant for pinpoint accuracy but rather to offer a comparatively easy-to-use way to specify lighting components for nonvisual aspects as part of the design process. In this way, the process is similar to that of standard lighting design, where the simulation goal is not a 1:1 representation of reality, but a good enough abstraction to make educated decisions for luminaire specification, position, and orientation. ([PERSON] et al.