Recent studies suggests that air pollution, from among others road traffic, can influence growth and development of the human foetus during pregnancy. The effects of air pollution from heavy industry on birth outcomes have been investigated scarcely. Our aim was to investigate the associations of air pollution from heavy industry on birth outcomes. A cross-sectional study was conducted among 4488 singleton live births (2012-2017) in the vicinity of a large industrial area in the Netherlands. Information from the birth registration was linked with a dispersion model to characterize annual individual-level exposure of pregnant mothers to air pollutants from industry in the area. Associations between particulate matter (PM), nitrogen oxides (NO), sulphur dioxide (SO), and volatile organic compounds (VOC) with low birth weight (LBW), preterm birth (PTB), and small for gestational age (SGA) were investigated by logistic regression analysis and with gestational age, birth weight, birth length, and head circumference by linear regression analysis. Exposures to NO, SO, and VOC (per interquartile range of 1.16, 0.42, and 0.97 μg/m respectively) during pregnancy were associated with LBW (OR 1.20, 95%CI 1.06-1.35, OR 1.20, 95%CI 1.00-1.43, and OR 1.21, 95%CI 1.08-1.35 respectively). NO and VOC were also associated with PTB (OR 1.14, 95%CI 1.01-1.29 and OR 1.17, 95%CI 1.04-1.31 respectively). Associations between exposure to air pollution and birth weight, birth length, and head circumference were statistically significant. Higher exposure to PM, NO, SO and VOC (per interquartile range of 0.41, 1.16, 0.42, and 0.97 μg/m respectively) was associated with reduced birth weight of 21 g to 30 g. The 90th percentile industry-related PM exposure corresponded with an average birth weight decrease of 74 g.
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http://dx.doi.org/10.1016/j.envpol.2020.115741 | DOI Listing |
Environ Sci Technol
January 2025
Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, California 94609, United States.
Exposure to household air pollution has been linked to adverse health outcomes among women aged 40-79. Little is known about how shifting from biomass cooking to a cleaner fuel like liquefied petroleum gas (LPG) could impact exposures for this population. We report 24-h exposures to particulate matter (PM), black carbon (BC), and carbon monoxide (CO) among women aged 40 to <80 years participating in the Household Air Pollution Intervention Network trial.
View Article and Find Full Text PDFData Brief
February 2025
Office of Air and Radiation, US Environmental Protection Agency, 109 TW Alexander Dr, PO Box 12055, RTP, NC 27711, USA.
The Expedited Modeling of Burn Events Results (EMBER) dataset consists of 36-km grid-spacing Community Multiscale Air Quality (CMAQ) photochemical modeling for the summer of 2023. For emissions, these simulations utilized representative monthly and day-of-week anthropogenic emissions from a recent year and preliminary day-specific 2023 fire emissions derived using BlueSky pipeline. The base model run simulated ozone concentrations across the contiguous US during Apr 11-Sep 29, 2023.
View Article and Find Full Text PDFSustain Earth
December 2023
Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands.
Unlabelled: Integrated Assessment Models (IAMs) and System Dynamic Models (SDMs) are starting to incorporate representations of the impact of environmental changes on health and socio-economic development into their modelling frameworks. We use this brief review to provide an overview of how health and well-being are currently represented in IAMs and SDMs. A grey literature search on 12 selected model host websites and their corresponding Wiki pages was conducted.
View Article and Find Full Text PDFBMC 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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