SARS-CoV-2 virus (COVID-19) pandemic has impacted several countries, with also some differences at local levels. When lockdown restrictions were imposed, the concentrations of some air pollutants were reduced, as reported in some other cities in the world. This was often considered a positive by-product of the pandemic. However, often literature reporting the connection of air quality (AQ) and lockdown, suffers of limited and incomplete data analysis, not considering, for example, some confounding factors. This work presents a methodology, and the results of its application, to assess the impact of pandemic restrictions on AQ (in particular nitrogen oxides, NO and particulate matter, PM) in spring 2020 in Brescia, located in one of the most affected areas in terms of virus diffusion and in one of the most polluted areas in Europe (Po Valley, Italy). In particular, the proposed methodology integrates data and AQ modelling simulations to distinguish between the changes in the PM and NO pollutants concentration that occurred due to the restriction measures and due to other factors, like spatial-temporal characteristics (for example the seasonality), meteorological factors, and governmental actions that were introduced in the past to improve the air quality. Results show that NO is strongly dependent to traffic emission. On the contrary, although the expected decrease in PM concentrations, the results highlight that the reduction of transport emission would not help to avoid severe air pollution, due to the other pollution sources that contribute to its origin. The results presented for the first time in this work are of particular interest because they may be used as a basis to investigate in more details the sources that can impact on the air quality in Brescia, with the aim to propose effective measures able to reduce it.
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http://dx.doi.org/10.1016/j.envres.2022.113193 | DOI Listing |
Sci Rep
December 2024
Department of Civil Engineering, Sharif University of Technology, Tehran, Iran.
Air pollution, a global health hazard, significantly impacts mortality, cardiovascular health, mental well-being, and overall human health. This study aimed to investigate the impact of air pollution and meteorological factors on cardiovascular mortality rates in Mashhad City, northeastern Iran in 2017-2020. We utilized a Random Forest (RF) model in this study.
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December 2024
State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
The gut microbiome, recognized as a critical component in the development of chronic diseases and aging processes, constitutes a promising approach for predicting host health status. Previous research has underscored the potential of microbiome-based predictions, and the rapid advancements of machine learning techniques have introduced new opportunities for exploiting microbiome data. To predict various host nonhealthy conditions, this study proposed an integrated machine learning-based estimation pipeline of Gut Age Index (GAI) by establishing a health aging baseline with the gut microbiome data from healthy individuals.
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December 2024
Department of Food Science and Technology, Zhejiang University of Technology, Hangzhou, 310014, Zhejiang, People's Republic of China.
Visible and Near-infrared hyperspectral imaging (VNIR-HSI) combined with machine learning has shown its effectiveness in various detection applications. Specifically, the quality of cigar tobacco leaves undergoes subtle changes due to environmental differences during the air-curing phase. This study aims to evaluate the feasibility of deep learning methods in overcoming data limitations to develop a VNIR-HSI prediction model for the quality of cigar tobacco leaves at different air-curing levels.
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December 2024
School of public health, Sun Yat-sen University, Guangzhou, Guangdong, China. Electronic address:
Background: No prior study has examined the mutual association of long-term outdoor ozone (O) concentration and physical activity (PA) with emotional and behavioral problems (EBPs) in children and adolescents. This study aims to investigate the association between long-term outdoor O concentration and the risk of EBPs in children and adolescents and further explore whether increased PA levels modify this association.
Methods: Data were obtained from the 2020 wave follow-up examination of an ongoing prospective cohort study (COHERENCE project) in Guangzhou, China.
Environ Pollut
December 2024
College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, State Key Laboratory of Nutrient Use and Management, National Observation and Research Station of Agriculture Green Development (Quzhou, Hebei), China Agricultural University, Beijing 100193, China. Electronic address:
Poor management of nitrogen (N) can lead to serious environmental problems, such as air and water pollution. The accurate identification of priority control areas and emission sources is critical for making effective decisions regarding sustainable N management. This study aimed to identify hotspots for N losses and quantitatively analyze the relative contributions of different emission sources in the Huang-Huai-Hai Basin at the county scale.
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