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Reducing greenhouse gas emissions is an international impetus to transition from vehicles with internal combustion engines (ICE) to electric vehicles (EV). While this transition is happening rapidly in some regions of the world that are mainly urbanized, other predominantly rural and less developed regions are slower to adopt this technology. Rural Alaska serves as an example with its not-road-connected communities, high cost of electricity, extreme environmental conditions, and isolated power grids often powered by diesel. This study used co-production and mixed methods to identify barriers and perceived benefits towards EV adoption and explore EV adoption rates across the Arctic. We conducted community workshops in Bethel, Galena, and Kotzebue, Alaska, and 25 interviews with businesses and local governments. The top five impediments to EV adoption are the inability to maintain vehicles locally, cold weather performance, higher purchase prices compared to ICE vehicles, and the cost of electricity. The successful adoption of EVs in isolated microgrid communities in the Arctic requires investments in appropriate financial incentives, especially for low-income households, expansion of renewable power generation, and climate and culture-relevant proof-of-concept vehicles. Residents acknowledged that EVs generally operate much cleaner than vehicles with ICE, can have lower fuel and maintenance costs, and cause less air and noise pollution. We propose a framework to develop policies to facilitate the adoption of EVs in rural areas. Policy implications for overcoming the challenges related to the transition to EVs in remote rural parts of the globe are discussed. 

The Arctic presents various challenges for a transition to electric vehicles compared to other regions of the world, including environmental conditions such as colder temperatures, differences in infrastructure, and cultural and economic factors. For this study, academic researchers partnered with three rural communities: Kotzebue, Galena, and Bethel, Alaska, USA. The study followed a co-production process that actively involved community partners to identify 21 typical vehicle use cases that were then empirically modeled to determine changes in fueling costs and greenhouse gas emissions related to a switch from an internal combustion engine to an electric vehicle. While most use cases showed decreases in fueling costs and climate emissions from a transition to electric versions of the vehicles, some common use profiles did not. Specifically, the short distances of typical commutes, when combined with low idling and engine block heater use, led to an increase in both fueling costs and emissions. Arctic communities likely need public investment and additional innovation in incentives, vehicle types, and power systems to fully and equitably participate in the transition to electrified transportation. More research on electric vehicle integration, user behavior, and energy demand at the community level is needed. 

We used crowdsourced data in Alaska and the literature to develop a light-duty electric vehicle model to help policymakers, researchers, and consumers understand the trade-offs between internal combustion and electric vehicles. This model forms the engine of a calculator, which was developed in partnership with residents from three partner Alaskan communities. This calculator uses a typical hourly temperature profile for any chosen community in Alaska along with a relationship of energy use vs. temperature while driving or while parked to determine the annual cost and emissions for an electric vehicle. Other user inputs include miles driven per day, electricity rate, and whether the vehicle is parked in a heated space. A database of community power plant emissions per unit of electricity is used to determine emissions based on electricity consumption. This tool was updated according to community input on ease of use, relevance, and usefulness. It could easily be adapted to other regions of the world. The incorporation of climate, social, and economic inputs allow us to holistically capture real world situations and adjust as the physical and social environment changes. 

Abstract Increased wildfire activity has raised concerns among communities about how to assess and prepare for this threat. There is a need for wildfire hazard assessment approaches that capture local variability to inform decisions, produce results understood by the public, and are updatable in a timely manner. We modified an existing approach to assess decadal wildfire hazards based primarily on ember dispersal and wildfire proximity, referencing landscape changes from 1984 through 2014. Our modifications created a categorical flammability hazard scheme, rather than dichotomous, and integrated wildfire exposure results across spatial scales. We used remote sensed land cover from four historical decadal points to create flammability hazard and wildfire exposure maps for three arctic communities (Anchorage and Fairbanks, Alaska and Whitehorse, Yukon). Within the Fairbanks study area, we compared 2014 flammability hazard, wildfire exposure, and FlamMap burn probabilities among burned (2014–2023) and unburned areas. Unlike burn probabilities, there were significantly higher in exposure values among burned and unburned locations (Wilcoxon;p < 0.001) and exposure rose as flammability hazard classes increased (Kruskal–Wallis;p < 0.001). Very high flammability hazard class supported 75% of burned areas and burns tended to occur in areas with 60% exposure or greater. Areas with high exposure values are more prone to burn and thus desirable for mitigation actions. By working with wildfire practitioners and communities, we created a tool that rapidly assesses wildfire hazards and is easily modified to help identify and prioritize mitigation activities. 

The boreal forest of northwestern North America covers an extensive area, contains vast amounts of carbon in its vegetation and soil, and is characterized by extensive wildfires. Catastrophic crown fires in these forests are fueled predominantly by only two evergreen needle-leaf tree species, black spruce (Picea mariana (Mill.) B.S.P.) and lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.). Identifying where these flammable species grow through time in the landscape is critical for understanding wildfire risk, damages, and human exposure. Because medium resolution landcover data that include species detail are lacking, we developed a compound modeling approach that enabled us to refine the available evergreen forest category into highly flammable species and less flammable species. We then expanded our refined landcover at decadal time steps from 1984 to 2014. With the aid of an existing burn model, FlamMap, and simple succession rules, we were able to predict future landcover at decadal steps until 2054. Our resulting land covers provide important information to communities in our study area on current and future wildfire risk and vegetation changes and could be developed in a similar fashion for other areas. 

Food, energy, and water (FEW) security require adequate quantities and forms of each resource, conditions that are threatened by climate change and other factors. Assessing FEW security is important, and needs to be understood in the context of multiple factors. Existing frameworks make it hard to disentangle the contributors to FEW insecurity and to determine where best to expend efforts on short- and long-term solutions. We identified four consistent components of FEW security (availability, access, preference, quality). This framework provides detailed and nuanced insights into factors that limit or bolster security in each of the three sectors. The integrated framework identifies proximate and ultimate underlying causes of deficiencies in each security component providing opportunities to identify short- and long-term solutions.