Municipal Fleet Electrification Brings City of Cincinnati Closer to 2035 Carbon Neutrality Goal

A Case Study of Cincinnati, OH 

Over the last decade, City staff have been hard at work through the Green Cincinnati Program, aimed at reducing greenhouse gas (GHG) emissions by 84 percent below 2006 levels by 2050. Achieving this target will be no small feat, and the City is identifying several key actions across the built environment, energy, food and water, and transportation sectors.

The Challenge

The City of Cincinnati, Ohio purchased three all-electric fleet vehicles, a first for the municipality, ahead of their plans to purchase 20 total in 2020. The City has also been focused on new fleet electrification goals, which has historically been difficult to launch due to restrictions on budget and limited vehicle availability for the right applications. While the City has seen progress in reducing emissions across all government departments and operations, transportation has remained the most difficult, seeing the least reduction in emissions throughout the Green Cincinnati Program. The City of Cincinnati wanted to utilize the resources of The Climate Mayors Electric Vehicle Purchasing Collaborative (the Collaborative) and Bloomberg American Cities Climate Challenge (of which Cincinnati is an awardee) to tackle new goals set around solar and EV deployment. While the City of Cincinnati has considered EVs in the past, the two key barriers were:

•      Identifying the best fit for specific vehicle replacements.

•      Determining optimal EV charging locations.

Our Solution

To identify vehicles that maximize emissions and cost savings potential, the Electrification Coalition and Sawatch Labs helped the city of Cincinnati launch a fleet telematics assessment. This assessment analyzed the fleet across 11 candidate vehicles representative of light-duty sedan operation. The data was collected and analyzed across a variety of factors including daily miles driven, average parking time, and amount of fuel consumed. Considering these factors allowed Sawatch Labs to identify the best EV and PHEV replacements.

 As the City already had telematics data captured and gathered for fleet vehicles, Sawatch Labs was able to extend this analysis across multiple months, helping account for fluctuations in weather, temperature, and vehicle usage. Overall, 100 percent of the vehicles analyzed had a suitable EV match and would reduce overall fleet costs and GHG emissions. These were encouraging findings considering the hilly terrain and cold winters faced by the City. The resulting recommendations gave Cincinnati the data needed to demonstrate the cost savings and GHG reduction benefits of electrifying fleet vehicles. The below shows these results.

The Results

Incorporating the first EVs into a fleet requires dedicated planning and infrastructure improvement. Once a city gains first-hand experience, adoption is more rapid. This can be seen in their commitment to an increased number of EVs in 2020. The City remains focused on deploying EVs in the fleet and leveraging tools and resources provided by Sawatch Labs. Now, Cincinnati can access the best EV pricing available and gain valuable insight for successful and timely deployment. Cincinnati will continue to electrify growing portions of the light-duty fleet and will consider medium- and heavy-duty EVs as model availability expands.

Additional actions are complemented by the City’s development of solar generation, allowing more of the City’s operation to be powered by renewable energy and further progressing towards Cincinnati’s 2035 carbon neutrality goal. The City planned to purchase 20 EVs in 2020 based on the success of their first three vehicles and the technical support available to staff provided by Sawatch Labs.

Sarah Booth

Sarah has supported clean energy and transportation efforts around the world for more than a decade. She enjoys running on trails and breathing in the fresh ocean air in Northern California, and is dipping her toes into the fun adventure that is swimrun.

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Whitepaper – Telematics and Data Science: Informing Energy-Efficient Mobility