In developing nations, outdated technologies and sulfur-rich heavy fossil fuel usage are major contributors to air pollution, affecting urban air quality and public health. In addition, the limited resources hinder the adoption of advanced monitoring systems crucial for informed public health policies. This study addresses this challenge by introducing an affordable internet of things (IoT) monitoring system capable of tracking atmospheric pollutants and meteorological parameters. The IoT platform combines a Bresser 5-in-1 weather station with a previously developed air quality monitoring device equipped with Alphasense gas sensors. Utilizing MQTT, Node-RED, InfluxDB, and Grafana, a Raspberry Pi collects, processes, and visualizes the data it receives from the measuring device by LoRa. To validate system performance, a 15-day field campaign was conducted in Santa Clara, Cuba, using a Libelium Smart Environment Pro as a reference. The system, with a development cost several times lower than Libelium and measuring a greater number of variables, provided reliable data to address air quality issues and support health-related decision making, overcoming resource and budget constraints. The results showed that the IoT architecture has the capacity to process measurements in tropical conditions. The meteorological data provide deeper insights into events of poorer air quality.
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http://dx.doi.org/10.3390/s24092729 | DOI Listing |
BMC Res Notes
January 2025
UQ Centre for Clinical Research, Faculty of Health Medicine and Behavioural Sciences, The University of Queensland, Brisbane, Australia.
Objectives: This data note presents a comprehensive geodatabase of cardiovascular disease (CVD) hospitalizations in Mashhad, Iran, alongside key environmental factors such as air pollutants, built environment indicators, green spaces, and urban density. Using a spatiotemporal dataset of over 52,000 hospitalized CVD patients collected over five years, the study supports approaches like advanced spatiotemporal modeling, artificial intelligence, and machine learning to predict high-risk CVD areas and guide public health interventions.
Data Description: This dataset includes detailed epidemiologic and geospatial information on CVD hospitalizations in Mashhad, Iran, from January 1, 2016, to December 31, 2020.
Environ Sci Pollut Res Int
January 2025
Research Centre for Energy, Environment and Technology (CIEMAT), Avda. Complutense, 40, 28040, Madrid, Spain.
As tailpipe emissions have decreased, there is a growing focus on the relative contribution of non-exhaust sources of vehicle emissions. Addressing these emissions is key to better evaluating and reducing vehicles' impact on air quality and public health. Tailoring solutions for different non-exhaust sources, including brake emissions, is essential for achieving sustainable mobility.
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January 2025
School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
The rapid development of low-cost sensors provides the opportunity to greatly advance the scope and extent of monitoring of indoor air pollution. In this study, calibrated particle matter (PM) sensors and a non-negative matrix factorisation (NMF) source apportionment technique are used to investigate PM concentrations and source contributions across three households in an urban residential area. The NMF is applied to combined data from all houses to generate source profiles that can be used to understand how PM source characteristics are similar or differ between different households in the same urban area.
View Article and Find Full Text PDFOccup Environ Med
January 2025
Lifestyles and Living Environments Unit, Finnish Institute for Health and Welfare, Oulu, Finland.
Objective: To assess the role of occupational noise exposure on pregnancy complications in urban Nordic populations.
Methods: A study population covering five metropolitan areas in Denmark, Finland, Norway and Sweden was generated using national birth registries linked with occupational and residential environmental exposures and sociodemographic variables. The data covered all pregnancies during 5-11 year periods in 2004‒2016, resulting in 373 184 pregnancies.
Environ Res
January 2025
Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China; National Institute for Data Science in Health and Medicine, Capital Medical University, Beijing, 100069, China; School of Medical Sciences and Health, Edith Cowan University, WA6027, Perth, Australia. Electronic address:
Existing researches had primarily investigated the associations between various air pollutants and the risk of coronary heart disease (CHD) or diabetes mellitus (DM) separately. However, the significance and effects of PM and its components in patients with CHD and comorbid DM (CHD-DM) remain unclear. Patient data was sourced from the Beijing Municipal Health Commission Information Centre between January 1, 2014, and December 31, 2018.
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