Green

Mackinac Island in the state of Michigan, United States of America (USA), is one of the most visited summertime destinations in the country. The island attracts over a million tourists in the short period of 6 months. The only commute to the island is using ferries that travel to the island from Mackinaw City and St. Ignace. In 2022, a study was conducted by the Advanced Power Systems Research Center (APSRC) at Michigan Technological University on the potential benefits of electrification of the ferry from a technical, environmental and economic standpoint. The results from the study concluded that while the retrofitting of the Mackinac Island ferry to an electric ferry was feasible based on components available in the market, electrification would lead to an increase in the CO₂ emissions. The economic analysis showed that the electric ferry would result in significant financial losses to any company operating the ferry. The overarching conclusion was that an electric ferry powered by Michigan’s electric grid was not the optimum solution for that time based on both carbon emissions as well as Total Cost of Ownership (TCO). The current work builds on the study completed in 2022 to determine whether an electric ferry powered by local solar energy can help reduce CO₂ emissions as compared to the baseline diesel engine-powered ferry. The analysis includes sizing the solar array based on the solar radiation received by Mackinaw City, the CO₂ emissions in the manufacture of solar panels based on a lifecycle assessment (LCA) of solar photovoltaics and the addition of battery energy storage as a means of energy storage between ferry trips to determine if the carbon footprint of the electric ferry can be reduced by powering it with energy from solar photovoltaics. Ferry drive cycle data used for this analysis is the same as that collected for the original study, although the appropriate parameters relating to Michigan’s electricity grid and emissions from battery manufacturing have been updated based on technological changes and the addition of different energy sources on the Michigan grid. This work also includes economic considerations for all potential electrification scenarios discussed in this work.

Large-scale artificial intelligence systems increasingly disclose energy and carbon metrics, but their freshwater costs remain less consistently measured. This paper introduces the Water Cost of Intelligence (WCI), a per-query metric combining direct water consumed for on-site data-center cooling with indirect water consumed during electricity generation, weighted by local scarcity using Aqueduct 4.0 Baseline Water Stress (BWS) scores. We first reconstruct Google’s disclosed Gemini direct-water figure from Google’s own reported parameters, an internal consistency check on the implementation rather than an independent validation. Expanding the accounting boundary to include electricity-generation water raises the estimate for a median large language model (LLM) prompt by 179% under a uniform national water-intensity value. Parameterizing that intensity by the regional generation mix instead changes the estimate substantially and reverses the regional ordering, depending on whether hydroelectric reservoir evaporation is allocated to generation: the same grid is the least water-intensive of those studied under one convention and the most water-intensive under the other. A region cannot be characterized as water-efficient in terms of electricity without first establishing that convention. Direct-only reporting can be internally accurate yet boundary-incomplete, and regional scarcity can change the interpretation of identical physical water use by an order of magnitude.

Biochar, a carbon-rich product resulting from the thermochemical transformation of organic biomass under limited oxygen condition, is currently drawing much worldwide attention due to its multiple applications in carbon sequestration, soil improvement, environmental remediation, and biomass waste management. Initially, the focus of research was primarily on the technical possibilities of biochar production, its economic aspects, and its contribution to climate change mitigation through carbon sequestration and the promotion of sustainable agriculture. Nevertheless, recent research indicates the high complexity and dynamics of biochar interactions with the environment, driven by a combination of factors like feedstock type, process conditions, biochar properties, and other factors. While biochar exhibits multiple beneficial effects, including improving soil structure, enhancing nutrient retention, promoting microbial activities, and remediating contaminants, several environmental risks associated with biochar application have also been identified, namely the formation of polycyclic aromatic hydrocarbons (PAHs), heavy metal contamination, creation of persistent free radicals, changes in soil chemistry, and modification of soil microbial community structure. Such risks are greatly related to production process parameters, treatment methods, and biochar application practices. Moreover, differences in feedstock choice, pyrolysis temperature, reactor design, biochar application rate, and analytical methods used make comparative analysis of results difficult.