Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1080/00022470.1968.10469220 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ.
Geosci Model Dev
November 2024
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
United States (US) background ozone (O) is the counterfactual O that would exist with zero US anthropogenic emissions. Estimates of US background O typically come from chemical transport models (CTMs), but different models vary in their estimates of both background and total O. Here, a measurement-model data fusion approach is used to estimate CTM biases in US anthropogenic O and multiple US background O sources, including natural emissions, long-range international emissions, short-range international emissions from Canada and Mexico, and stratospheric O.
View Article and Find Full Text PDFAssessment model of ozone pollution based on SHAP-IPSO-CNN and its application.
Sci Rep
January 2025
Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang, 110168, Liaoning, China.
The problem of ground-level ozone (O) pollution has become a global environmental challenge with far-reaching impacts on public health and ecosystems. Effective control of ozone pollution still faces complex challenges from factors such as complex precursor interactions, variable meteorological conditions and atmospheric chemical processes. To address this problem, a convolutional neural network (CNN) model combining the improved particle swarm optimization (IPSO) algorithm and SHAP analysis, called SHAP-IPSO-CNN, is developed in this study, aiming to reveal the key factors affecting ground-level ozone pollution and their interaction mechanisms.
View Article and Find Full Text PDFThe Wako Cohort Study: Design and Profile of Participants at Baseline.
J Epidemiol
January 2025
Research Team for Social Participation and Healthy Aging, Tokyo Metropolitan Institute for Geriatrics and Gerontology.
Background: We launched the Wako Cohort Study in 2023 to identify individual and socio-environmental factors related to the extension of healthy life expectancy and the reduction of health disparities among community-dwelling adults and to develop health promotion and care prevention strategies. This study profile aims to describe the study design and participants' profile at baseline.
Methods: The Wako Cohort Study is a prospective study of community-dwelling adults aged ≥ 40 years living in Wako City, Saitama Prefecture, Japan.
Oxidative Gaseous Air Pollutant Exposure Interacts with PNPLA3-I148M Genotype to Influence Liver Fat Fraction and Multi-Omics Profiles in Young Adults.
Environ Pollut
January 2025
Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA. Electronic address:
PNPLA3-I148M genotype is the strongest predictive single-nucleotide polymorphism for liver fat. We examine whether PNPLA3-I148M modifies associations between oxidative gaseous air pollutant exposure (O) with i) liver fat and ii) multi-omics profiles of miRNAs and metabolites linked to liver fat. Participants were 69 young adults (17-22 years) from the Meta-AIR cohort.
View Article and Find Full Text PDFInvestigating the factors contributing to the maintenance of high levels of warm season nocturnal ozone in a basin city.
Environ Pollut
January 2025
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China. Electronic address:
In recent years, ozone (O) pollution in many Chinese cities has worsened. Several cities have also experienced incidents where nocturnal O concentrations did not decrease as expected, and instead remained at high levels (above 50 ppb). However, there have been few detailed studies on the causes of these events.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!