According to a 2013 report by the American Society of Civil Engineers, the infrastructure of the United States requires a $3.6 trillion investment to return it to a good condition by 2020[ 1]. A significant portion of the American infrastructure is composed of concrete, which undergoes microcracking damage over time, adversely affecting material mechanical strength, stiffness and permeability compromising the resilience and sustainability of the structural system. Although previous research identified that ultrasonic and other nondestructive approaches can characterize distributed damage content in concrete, the methods are either insensitive to early stages (low crack volumes) of damage, not repeatable, or inconsistent. We hypothesize that contactless, air-coupled ultrasonic techniques based on quantifying the extraction of backscatter energy from surface waves can provide a means of rapidly and robustly assessing microcrack damage in concrete. Ultrasonic surface guided waves in concrete were generated and detected using a fully contactless air-coupled system. Three concrete samples were prepared by varying the content of polymer fiber in the concrete samples to mimic varying degrees (0, 0.3 and 0.6%) of well-controlled and well-distributed microcracking. These samples were compared to a homogeneous sample, which was presumed to have negligible scattering from particulates or cracks in the sample. A 16 cycle tone burst at 50 kHz was transmitted into the concrete samples at an incidence angle of 8° using an electrostatic transducer (Senscomp, Livonia, MI). Contactless silicon-based miniature MEMS acoustic sensors were placed behind the ultrasonic transmitter insulated by a triple-layered acoustic baffle. The MEMS sensors were located a few millimeters above the surface and recorded backscatter from leaky waves traveling in the concrete samples. The energy in the backscattered signals (EB) from the different samples was quantified by integrating the square of the subtracted waves from spatially averaged received signals. These values were then normalized by dividing the energy in the forward propagating wave recorded by a matched MEMS sensor located in front of the transmitter. Normalized EB values for the PMMA, 0, 0.3 and 0.6% concrete samples were 0, 0.001, 0.06 and 0.15, respectively. Statistically significant differences (p < 0.05) were observed between EB values from the 0.3 and 0.6% concrete samples compared to PMMA and 0% and statistically significant differences were observed between the 0.3 and 0.6% concrete samples. By quantifying the EB from surface waves in concrete, the non-contact ultrasonic technique was able to differentiate between samples having different fiber content.