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      Particulate matter in the workplace: effects of a mental models-based folder combined with a practical assignment

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          Abstract

          Background

          With increasing knowledge on the adverse health effects of certain constituents of PM (particulate matter), such as silica, metals, insoluble ions, and black carbon, PM has been under the attention of work safety experts. Previously, we investigated the perceptions of blue-collar workers in highly exposed areas of work. Subsequently, we developed an instruction folder highlighting the most important aspects of PM risk and mitigation, and tested this folder in a digital experiment. The digital experiment yielded positive results with regards to acquired knowledge about PM, but did not on risk perception or safety behavior.

          Methods

          In this study, we investigate the effects of the folder when combined with a practical assignment involving a PM exposimeter, showing the amount of particulate matter in microgram per cubic meter in real time on its display for various activities. We tested this at six workplaces of four companies in the roadwork and construction branch.

          Results

          The results indicate that the folder itself yields an increased knowledge base in employees about PM, but the effects of the practical assignment are more contentious. Nevertheless, there is an indication that using the assignment may lead to a higher threat appraisal among employees for high exposure activities.

          Conclusion

          We recommend implementing our folder in companies with high PM exposure and focusing further research on appropriate methods of implementation.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12889-022-13362-y.

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          Most cited references14

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          Black Carbon as an Additional Indicator of the Adverse Health Effects of Airborne Particles Compared with PM10 and PM2.5

          Background: Current air quality standards for particulate matter (PM) use the PM mass concentration [PM with aerodynamic diameters ≤ 10 μm (PM10) or ≤ 2.5 μm (PM2.5)] as a metric. It has been suggested that particles from combustion sources are more relevant to human health than are particles from other sources, but the impact of policies directed at reducing PM from combustion processes is usually relatively small when effects are estimated for a reduction in the total mass concentration. Objectives: We evaluated the value of black carbon particles (BCP) as an additional indicator in air quality management. Methods: We performed a systematic review and meta-analysis of health effects of BCP compared with PM mass based on data from time-series studies and cohort studies that measured both exposures. We compared the potential health benefits of a hypothetical traffic abatement measure, using near-roadway concentration increments of BCP and PM2.5 based on data from prior studies. Results: Estimated health effects of a 1-μg/m3 increase in exposure were greater for BCP than for PM10 or PM2.5, but estimated effects of an interquartile range increase were similar. Two-pollutant models in time-series studies suggested that the effect of BCP was more robust than the effect of PM mass. The estimated increase in life expectancy associated with a hypothetical traffic abatement measure was four to nine times higher when expressed in BCP compared with an equivalent change in PM2.5 mass. Conclusion: BCP is a valuable additional air quality indicator to evaluate the health risks of air quality dominated by primary combustion particles.
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            Risk communication a mental models approach

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              Mental models and social representations of hazards: the significance of identity processes

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                Author and article information

                Contributors
                thomas.stege@rivm.nl
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                13 May 2022
                13 May 2022
                2022
                : 22
                : 968
                Affiliations
                [1 ]GRID grid.31147.30, ISNI 0000 0001 2208 0118, National Institute for Public Health and the Environment (RIVM), ; PO Box 1, 3720 BA Bilthoven, The Netherlands
                [2 ]GRID grid.449791.6, ISNI 0000 0004 0395 6083, Smart Sensor Systems Group, Faculty of Technology, Innovation, and Society, , The Hague University of Applied Sciences, ; Rotterdamseweg 137, 2628 AL Delft, The Netherlands
                [3 ]GRID grid.16872.3a, ISNI 0000 0004 0435 165X, Department of Public and Occupational Health, , Amsterdam Public Health Research Institute, Amsterdam University Medical Center, ; Amsterdam, The Netherlands
                Article
                13362
                10.1186/s12889-022-13362-y
                9106267
                35562819
                de3b9834-210d-4a15-85c4-4a9e79871d8e
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 5 July 2021
                : 26 April 2022
                Funding
                Funded by: Strategic Programme RIVM
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Public health
                particulate matter,work safety,risk communication,educational folder,exposimeter
                Public health
                particulate matter, work safety, risk communication, educational folder, exposimeter

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