We have performed community noise assessments to determine the impact of vehicle noise, power generation, and other industrial facilities. Our scientists have worked with the WHO, AIHA, NIOSH, and other organizations to develop noise exposure limits for children and advance the understanding of noise exposure and hearing loss. We have also developed expertise in evaluating the accuracy of smart devices and wearables to measure noise exposure, so that these devices can be used to constantly collect exposure information for big data analytics and provide insight into communities that are often overlooked by occupational and environmental health professionals.
Further, we have an extensive understanding of the emerging technologies that will vastly increase the throughput of exposure measurements, and have the analytical skills that will allow our clients to make sense of these data. We have showcased our expertise through our involvement with governmental agencies, professional organizations, and contributions to the peer-reviewed literature.
Project Example: Noise Exposures in Different Community Settings Measured by Traditional Dosimeter and Smartphone Applications
Project Overview: In response to the numerous smartphone applications (“apps”) of various quality available on iOS, the National Institute for Occupational Safety and Health (NIOSH) released its own app for measuring sound levels. While this application was evaluated in a laboratory under ideal conditions, no attempt had been made to assess the accuracy of these devices in the general environment.
Our approach: Cardno ChemRisk developed a sampling strategy that involved the identification of environments commonly inhabited by individuals, but where little to no noise exposure data were available. These locations also had various levels, patterns, and characteristics of noise, which allowed for the accuracy of these apps to be comprehensively evaluated. The smartphone app was found to be within 2.0 dBA of the paired dosimeter in environments where noise levels were stable and in excess of 75 dBA, which suggests that the app can be used as a useful screening tool in environments that contain steady-state noise.
Our value: In addition to assessing noise levels in environments that have a scarcity of data, we also demonstrated that a freely available smartphone app was generally suitable for collecting measurements when traditional dosimeters are not available.