Published on in Vol 1, No 1 (2017): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/8370, first published .
Identifying Asbestos-Containing Materials in Homes: Design and Development of the ACM Check Mobile Phone App

Identifying Asbestos-Containing Materials in Homes: Design and Development of the ACM Check Mobile Phone App

Identifying Asbestos-Containing Materials in Homes: Design and Development of the ACM Check Mobile Phone App

Journals

  1. Govorko M, Fritschi L, Reid A. Using a Mobile Phone App to Identify and Assess Remaining Stocks of In Situ Asbestos in Australian Residential Settings. International Journal of Environmental Research and Public Health 2019;16(24):4922 View
  2. Govorko M, Fritschi L, Reid A. Accuracy of a mobile app to identify suspect asbestos-containing material in Australian residential settings. Journal of Occupational and Environmental Hygiene 2018;15(8):598 View
  3. Wu P, Mjörnell K, Mangold M, Sandels C, Johansson T. A Data-Driven Approach to Assess the Risk of Encountering Hazardous Materials in the Building Stock Based on Environmental Inventories. Sustainability 2021;13(14):7836 View
  4. Bloise A, Miriello D. Distinguishing asbestos cement from fiber-reinforced cement through portable µ-Raman spectroscopy and portable X-ray fluorescence. Environmental Monitoring and Assessment 2022;194(10) View
  5. Wu P, Sandels C, Johansson T, Mangold M, Kristina Mjörnell . Machine learning models for the prediction of polychlorinated biphenyls and asbestos materials in buildings. Resources, Conservation and Recycling 2023;199:107253 View