For instance, while industrial users in the United States paid a mean of $0.06 per kWh of electricity in March 2020, average state prices ranged from $0.04 (Oklahoma) to $0.26 (Hawaii). Similarly, variations in the local electricity fuel source mix can substantially influence greenhouse gas (GHG) emissions, with the emissions of electricity supplied by the Bonneville Power Administration (0.081 kg CO2 eq•kWh -1 ) being an order of magnitude smaller than those of the Ohio Valley Electric Corporation (1.0 kg CO2 eq•kWh -1 ). Additionally, although contextual parameters are independent of the technology being evaluated, they may nonetheless directly or indirectly affect the technical performance of the system. For example, solar irradiance could directly impact the efficacy of sunlight-mediated disinfection technologies, while local and national regulations could indirectly affect the performance of waste sludge treatment systems through the set legal limits (e.g., how much sludge can be accepted by a landfill facility). For contextual parameters, the resolution of the data is an important consideration. While higher resolution data (i.e., data being more specific to the deployment site) will yield results that more accurately reflect the deployment context, researchers may also be limited by data availability or the feasibility of new data collection. Generally, objectives of the QSD study will determine the appropriate resolution of contextual parameters (e.g., locality-specific, regional, nationally, or internationally representative averages), and additional analyses can be performed to assess how uncertainty in these parameters impacts system sustainability. In particular, spatial analysis with integrated Geographic Information Systems (GIS) can provide location-specific contextual parameters for more tailored conclusions on the sustainability of deployed technologies (Section 5.3).