Modeling spatial–temporal variability of PM2.5 concentrations in Belt and Road Initiative (BRI) region via functional adaptive density approach

Hael, Mohanned Abduljabbar

doi:10.1007/s11356-023-30048-z

Environ Sci Pollut Res

2023

DOI: 10.1007/s11356-023-30048-z

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Modeling spatial–temporal variability of PM2.5 concentrations in Belt and Road Initiative (BRI) region via functional adaptive density approach

Mohanned Abduljabbar Hael

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2024

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Cited by 2 publications

References 54 publications

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Dynamic clustering of spatial–temporal rainfall and temperature data over multi-sites in Yemen using multivariate functional approach

Hael,

Ma,

Al-Sakkaf

et al. 2024

Stoch Environ Res Risk Assess

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Dynamic clustering of spatial–temporal rainfall and temperature data over multi-sites in Yemen using multivariate functional approach

Hael,

Ma,

Al-Sakkaf

et al. 2024

Stoch Environ Res Risk Assess

View full text Add to dashboard Cite

Examining the Spatial and Temporal Variation of PM2.5 and Its Linkage with Meteorological Conditions in Dhaka, Bangladesh

Rahman,

Meng

2024

Atmosphere

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This study investigates the temporal and spatial variations in PM2.5 concentrations in Dhaka, Bangladesh, from 2001 to 2023 and evaluates the impact of meteorological factors and the effectiveness of mitigation strategies on air pollution. Using satellite and ground-based data, this study analyzed the seasonal trends, daily fluctuations, and the influence of COVID-19 lockdown measures on air quality. Our findings reveal a persistent increase in PM2.5 levels, particularly during winter, with concentrations frequently exceeding WHO guidelines. Our analysis suggests significant correlations between meteorological conditions and PM2.5 concentration, highlighting the significant role of meteorological conditions, such as rainfall, humidity, and temperature, in modulating PM2.5 levels. Our analysis found that PM2.5 levels exhibited a significant inverse correlation with relative humidity (r = −0.72), rainfall (r = −0.69), and temperatures (r = −0.79), highlighting the role of meteorological conditions in mitigating pollution levels. Additionally, the study underscores the temporary improvements in air quality during lockdown periods, demonstrating the potential benefits of sustained emission control measures. The research emphasizes the need for comprehensive and multi-faceted air quality management strategies, including stringent vehicular and industrial emissions regulations, enhancement of urban green spaces, and public awareness campaigns to mitigate the adverse health impacts of PM2.5 pollution in Dhaka.

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Modeling spatial–temporal variability of PM2.5 concentrations in Belt and Road Initiative (BRI) region via functional adaptive density approach

Cited by 2 publications

References 54 publications

Dynamic clustering of spatial–temporal rainfall and temperature data over multi-sites in Yemen using multivariate functional approach

Dynamic clustering of spatial–temporal rainfall and temperature data over multi-sites in Yemen using multivariate functional approach

Examining the Spatial and Temporal Variation of PM2.5 and Its Linkage with Meteorological Conditions in Dhaka, Bangladesh

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