Poor air quality is a leading contributor to the global disease burden and total number of deaths worldwide. Humans spend most of their time in built environments where the majority of the inhalation exposure occurs. Indoor Air Quality (IAQ) is challenged by outdoor air pollution entering indoors through ventilation and infiltration and by indoor emission sources. The aim of this study was to understand the current knowledge level and gaps regarding effective approaches to improve IAQ. Emission regulations currently focus on outdoor emissions, whereas quantitative understanding of emissions from indoor sources is generally lacking. Therefore, specific indoor sources need to be identified, characterized, and quantified according to their environmental and human health impact. The emission sources should be stored in terms of relevant metrics and statistics in an easily accessible format that is applicable for source specific exposure assessment by using mathematical mass balance modelings. This forms a foundation for comprehensive risk assessment and efficient interventions. For such a general exposure assessment model we need 1) systematic methods for indoor aerosol emission source assessment, 2) source emission documentation in terms of relevant a) aerosol metrics and b) biological metrics, 3) default model parameterization for predictive exposure modeling, 4) other needs related to aerosol characterization techniques and modeling methods. Such a general exposure assessment model can be applicable for private, public, and occupational indoor exposure assessment, making it a valuable tool for public health professionals, product safety designers, industrial hygienists, building scientists, and environmental consultants working in the field of IAQ and health.
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http://dx.doi.org/10.1016/j.scitotenv.2019.02.398 | DOI Listing |
Sci Rep
December 2024
Division of Pulmonary and Critical Care, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095-1690, USA.
Electronic cigarettes (e-cigs) fundamentally differ from tobacco cigarettes in their generation of liquid-based aerosols. Investigating how e-cig aerosols behave when inhaled into the dynamic environment of the lung is important for understanding vaping-related exposure and toxicity. A ventilated artificial lung model was developed to replicate the ventilatory and environmental features of the human lung and study their impact on the characteristics of inhaled e-cig aerosols from simulated vaping scenarios.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
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December 2024
Civil Engineering Department, Shoolini University, Solan, Himachal Pradesh, 173229, India.
Geopolymer concrete (GPC) offers a sustainable alternative by eliminating the need for cement, thereby reducing carbon dioxide emissions. Using durable concrete helps prevent the corrosion of reinforcing bars and reduces spalling caused by chemical attacks. This study investigates the impact of adding 5, 10, and 15% silica fumes (SF) on the mechanical and durability properties of GPC cured at 60 °C for 24 h.
View Article and Find Full Text PDFJ Eur Acad Dermatol Venereol
December 2024
Department of Dermatology, Medical University of Vienna, Vienna, Austria.
Background: Conventional photodynamic therapy (cPDT) is an effective treatment option for field cancerization and multiple actinic keratoses (AK). The main side effect of cPDT is pain during illumination which in severe cases might necessitate early termination of treatment. Modification of treatment parameters such as light dose and fluence rate is a promising approach to mitigate PDT-associated pain.
View Article and Find Full Text PDFFront Public Health
December 2024
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
Background: Despite examining the role of an association between particulate matter and lung cancer in low-income countries, studies on the association between long-term exposure to particulate matter and lung cancer risk are still contradictory. This study investigates the spatiotemporal distribution patterns of lung cancer incidence and potential association with particulate matter (PM) in Bagmati province, Nepal.
Methods: We performed a spatiotemporal study to analyze the LC - PM association, using LC and annual mean PM concentration data from 2012 to 2021.
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