Comparing the Direct Costs and Infrastructure Implications of Anti-Icing Strategies

The objective of this research is to provide the Nevada Department of Transportation (NDOT) with data to select the anti-icing strategy best suitable for the Nevada highway system that balances the safety, infrastructure and environmental goals.  

Currently, there is the lack of research to systematically examine anti-icing options for NDOT’s various bridge decks and pavements. Relevant information based on field experience and reliable testing is much needed to assist NDOT in its process of developing anti-icing policies. Anti-icing has proven to be a pro-active approach to maintaining wintery roadways; however, the increased use of chemicals may pose a risk to the NDOT infrastructure such as decks and pavements and reduce their service life. Research is needed to compare various anti-icing strategies (mobile operations vs. fixed automated spray technology - FAST) and chemicals (granular salt, salt brines, magnesium chloride, potassium acetate, etc.) to determine their effects on infrastructure life-cycle.   Strategies such as high friction anti-icing pavement surfaces may serve as a desirable alternative to FAST systems in terms of cost, reliability and versatility, and their cost-effectiveness is yet to be fully evaluated for NDOT. Preliminary studies have shown the benefits of such alternative anti-icing strategies in accident prevention; but there have been user concerns over their durability. This research will address three critical research clusters for the Nevada transportation system: Infrastructure and Materials; Data‐Driven Decision Making; and Economics.   The research will synthesize information from existing research on anti-icing for comparison with NDOT practices and test the chemicals and products relevant to the NDOT current practices. The research will facilitate the understanding of how various anti-icing strategies and chemicals affect NDOT infrastructure and enable NDOT to make more informed decisions accordingly.