Search

Optimal and sensible salting for deicing operations in transportation facilities is an indispensable need, since salting operations consume a significant amount of resources and pose significant challenges to infrastructure and the environment. To realize optimal salting, a thorough understanding of the snow melting performance of salt is required. This understanding can then be used to develop optimal salt application rates, providing potential reductions in material usage and cost. This paper presents the results of a three-year field study focused on developing optimal salt application rates that apply an understanding of the physical snow melting process on empirical evidence. During the field tests, snow melting performance data, along with maintenance and weather data, were collected in the winter seasons of 2011-2014. With the collected data, a mechanistic-empirical model was developed to determine the recommended application rates for parking lots and sidewalks. The model developed through this study is the first of its kind and is a valuable tool for effective snow and ice control in parking lots and sidewalks. This research also outlines a solid framework to develop optimum application rates for other kind of transportation facilities, such as the road sector. [ABSTRACT FROM AUTHOR]

Pavement surface temperature is an essential requirement for the winter maintenance decision-making processes when determining suitable deicers and optimal application rates for transportation facilities such as parking lots. Currently, there are very few services/methods available to directly measure the pavement surface temperature. One method, the Road Weather Information System (RWIS), has less utility for parking lot and sidewalk maintenance purposes due to the operational constraints and high cost of using the RWIS service. This paper presents the results of a two-year field study focused on developing parametric and non-parametric models to forecast pavement surface temperature in parking lots based on a rigorous investigation of its correlation with common meteorological variables. The models were developed using available metrological data alongside measured pavement temperatures obtained through field observations. This study also evaluates the effects of different types of pavement (asphalt, interlocking bricks, and portland cement concrete) on pavement surface temperature. Evaluation results show that the developed models are able to predict pavement surface temperatures in different winter weather conditions with acceptable accuracy. [ABSTRACT FROM AUTHOR]