AIMC Topic: Beijing

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Development and external validation of an interpretable machine learning-based model for obesity risk prediction in 2-18-year-old children and adolescents in Beijing and Tangshan.

Journal of global health
BACKGROUND: The multifactorial mechanisms driving childhood obesity, a global public health challenge, are yet to be fully elucidated. We aimed to develop and externally validate three widely applied machine learning models alongside logistic regress...

New insights into soil bacteria communities in Beijing urban greenspace based on urbanization gradient.

The Science of the total environment
Research on urban soils has traditionally neglected two significant dimensions: the spatial heterogeneity emerging within megacity resulting from varying urbanization rates, and the dynamic responses of soil microbial communities to ongoing urban exp...

Health benefit contributions and differences of urban green spaces in the neighbourhood, a case study of Beijing, China.

Journal of environmental management
Numerous studies demonstrate that urban green spaces enhance residents' health. However, limited clarity in green space classification and the complex interplay between green space attributes and other variables have constrained our comprehension of ...

Oxygenated Organic Molecules over the Boundary Layer Aloft in Beijing.

Environmental science & technology
Oxygenated organic molecules (OOMs) originate from both direct emissions and secondary formation via the oxidation of volatile organic compounds (VOCs) emitted from biogenic and anthropogenic sources. OOMs are suggested to play a crucial role in the ...

Planning and layout of tourism and leisure facilities based on POI big data and machine learning.

PloS one
The spatial arrangement of tourism cities and the strategic placement of tourism and leisure facilities are pivotal to the development of smart tourism cities. The integration of Point of Interest (POI) data, enriched with location-specific insights,...

PM concentration prediction using a whale optimization algorithm based hybrid deep learning model in Beijing, China.

Environmental pollution (Barking, Essex : 1987)
PM is a significant global atmospheric pollutant impacting visibility, climate, and public health. Accurate prediction of PM concentrations is critical for assessing air pollution risks and providing early warnings for effective management. This stud...

Does COVID-19 lockdown matter for air pollution in the short and long run in China? A machine learning approach to policy evaluation.

Journal of environmental management
This paper leverages a data-driven two-step approach to effectively evaluate the effects of COVID-19 lockdown on air pollution in both the short and long-term in China. Using air pollution, meteorological conditions, and air mass clusters from 34 air...

Predictive analysis and risk assessment of potentially toxic elements in Beijing gas station soils using machine learning and two-dimensional Monte Carlo simulations.

Journal of hazardous materials
Gas stations not only serve as sites for oil storage and refueling but also as locations where vehicles frequently brake, significantly enriching the surrounding soil with potentially toxic elements (PTEs). Herein, 117 topsoil samples from gas statio...

Identifying influence factors and thresholds of the next day's pollen concentration in different seasons using interpretable machine learning.

The Science of the total environment
The prevalence of pollen allergies is a pressing global issue, with projections suggesting that half of the world's population will be affected by 2050 according to the estimation of the World Health Organization (WHO). Accurately forecasting pollen ...

Short-term prediction of PM2.5 concentration by hybrid neural network based on sequence decomposition.

PloS one
Accurate forecasting of PM2.5 concentrations serves as a critical tool for mitigating air pollution. This study introduces a novel hybrid prediction model, termed MIC-CEEMDAN-CNN-BiGRU, for short-term forecasting of PM2.5 concentrations using a 24-ho...